Carbon dioxide capture and utilization via Chemical
Looping process
Lukas Buelens
Supervisors: Dr. Hilde Poelman, Dr. Vladimir Galvita
Counsellor: Naga Venkata Ranga Aditya Dharanipragada
Master's dissertation submitted in order to obtain the academic degree of
Master of Science in Chemical Engineering
Department of Chemical Engineering and Technical Chemistry
Chairman: Prof. dr. ir. Guy Marin
Faculty of Engineering and Architecture
Academic year 2013-2014
FACULTY OF ENGINEERING AND ARCHITECTURE
Department of Chemical Engineering and Technical Chemistry
Laboratory for Chemical Technology
Director: Prof. Dr. Ir. Guy B. Marin
Laboratory for Chemical Technology
Declaration concerning the accessibility of the master thesis
Undersigned,
Lukas Buelens
Graduated from Ghent University, academic year 2013-2014 and is author of the
master thesis with title:
Carbon dioxide capture and utilization via Chemical Looping process
The author(s) gives (give) permission to make this master dissertation available for
consultation and to copy parts of this master dissertation for personal use.
In the case of any other use, the limitations of the copyright have to be respected, in
particular with regard to the obligation to state expressly the source when quoting
results from this master dissertation.
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Preface
During the past academic year, working on this master thesis, my patience and sense
of planning have been put to the test. In this preface, I wish to thank a number of
people without whom it would not have been possible to finish this work.
First, I would like to thank my counsellor Aditya Dharanipragada and supervisors
Dr. Vladimir Galvita and Dr. Hilde Poelman for their help and insight in experimental
procedures and processing of experimental results. Their support, feedback and
enthusiasm was much appreciated. I would like to thank the members of the Catalysis
group at the LCT for the interesting group seminars that were organized.
Particularly, I would like to thank prof. Dr. ir. Guy B. Marin for the opportunity to work
in a stimulating environment at the Laboratory for Chemical Technology.
Voorts ben ik mijn klasgenoten dankbaar voor de steun en afleiding tussen het werken
door, alsook voor de afgelopen twee jaar in het algemeen. Het is aangenaam om deel
uit te maken van een hechte klasgroep die het beste met elkaar voor heeft. Ik wens
ook alle leerkrachten, docenten en professoren te bedanken die mij doorheen de jaren
van de nodige kennis voorzien hebben om mijn studies en met name dit proefschrift af
te werken.
In het bijzonder wens ik mijn familie te bedanken voor hun steun en aanwezigheid.
Momenten van rust samen met mijn familie gaven me steeds moed om verder te gaan.
Bovendien is het in de eerste plaats dankzij hen dat ik de mogelijkheid gekregen heb
om studies in het hoger onderwijs aan te vangen.
Abstract
The focus of this work is twofold. First, calcium oxide based CO2 sorbent
materials are investigated. Second, CO2 utilization via chemical looping process using
iron oxide as oxygen carrier material. CO2 sorbents and oxygen carrier materials are
characterized, after which they are subjected to performance tests to get a clear view
on material stability. The best performing sorbent material 90CaO-10Al2O3 is found to
be stable over 16 hours of carbonation and decarbonation at temperatures between
650°C and 800°C. As for iron oxide, the effect of Al2O3, MgAl2O4 and MgO on material
stability and activity are addressed. MgAl2O4-promoted iron oxide shows the highest
activity and stability. 10Fe2O3-90MgAl2O4 remains stable for at least 17 hours of redox
cycles at 750°C due to a high level of dispersion of iron oxide particles. The activation
energy of iron oxide reduction and oxidation steps is estimated based on in-situ XRD
data. Finally, CO2 capture and utilization are combined in a mixed bed reactor setup.
Keywords:
CO2 capture, calcium oxide, CO2 utilization, chemical looping process, iron oxide,
magnesia-alumina spinel, in-situ XRD, kinetic modeling of TPR
CO2 capture and utilization via Chemical Looping process
Lukas Buelens
Supervisors: Dr. Vladimir Galvita, Dr. Hilde Poelman
Counsellor: Aditya Dharanipragada
Abstract The focus of this work is twofold. First, calcium
oxide based CO2 sorbent materials are investigated.
Second, CO2 utilization via chemical looping process using
iron oxide. The best performing sorbent material
90CaO-10Al2O3 is stable over 16 hours of carbonation and
decarbonation at temperatures between 650°C and 800°C.
As for iron oxide, the effect of Al2O3, MgAl2O4 and MgO on
material
stability
and
activity
are
addressed.
MgAl2O4-promoted iron oxide shows the highest activity
and stability. 10Fe2O3-90MgAl2O4 remains stable for at
least 17 hours of redox cycles at 750°C due to a high level of
dispersion of iron oxide particles. The activation energy of
iron oxide reduction and oxidation steps is estimated based
on in-situ XRD experiments. Finally, CO2 capture and
utilization are combined in a mixed bed reactor setup.
Keywords CO2 capture, calcium oxide, CO2 utilization,
chemical looping process, iron oxide, magnesia-alumina
spinel, in-situ XRD, kinetic modeling of TPR
I. INTRODUCTION
Today, over 30 billion tons of CO2 are emitted into the
atmosphere each year [1]. Because CO2 is a greenhouse gas,
this is accompanied by an increase in average global
temperature. Simulations predict a concentration of up to 570
ppm by 2100 [2]. A study by Cao et al. [3] suggested that
both the capacity and the inertia of different CO2 reservoirs is
high. The results of this study suggest that only by active
carbon dioxide removal, pre-industrial CO2 levels (280 ppm)
can be reached [3]. Removal of CO2 can be combined with
CO2 utilization by chemical looping. In chemical looping, a
metal oxide is reduced by a reducing agent (e.g. hydrogen) in
one step and re-oxidized by an oxidizing agent (e.g. carbon
dioxide) in the next. When using CO2 as oxidizing agent it is
reduced to form CO which, together with H2, may be used for
production of chemicals and fuels (e.g. via Fischer-Tropsch
synthesis).
Alumina promoted calcium oxide sorbents seem to be
suitable for CO2 capture applications. A high storage
capacity per unit mass results from the low atomic weight of
aluminum, while structural stability is guaranteed by
formation of Ca12Al14O33 and/or Ca3Al2O6 [4].
Iron oxide has shown to be a suitable material for reducing
CO2 to CO via chemical looping process because of its high
oxygen storage capacity from CO2 (0.7 mole CO2/mole Fe
per redox cycle) over a broad temperature range
(600-1800°C) [5, 6]. An additional advantage of iron oxide is
that it occurs in nature abundantly.
II. MATERIALS AND SETUP
oxide powder was suspended in ethanol, while aluminum
nitrate and citric acid were dissolved. Ethanol was boiled out
after which the sample was dried (120°C) and calcined
(750°C). Precursors were Al(NO3)3.9H2O, calcium oxide
powder and citric acid.
Samples containing 90, 80, 70 and 50 w% of Fe2O3
promoted by Al2O3, MgAl2O4 and MgO were prepared using
co-precipitation method. Precursors were dissolved in
deionized water and the mixture was stirred. Ammonium
hydroxide solution was added drop-wise. After ageing, the
precipitate was removed by filtration, dried (120°C) and
calcined (750°C). Synthesis of Fe2O3-MgAl2O4 with 100, 90,
80, 70, 50, 30, 20 and 10 w% of iron oxide was repeated
using the same procedure. Precursors were Al(NO3)3.9H2O,
Fe(NO3)3.9H2O, Mg(NO3)2.6H2O and ammonium hydroxide.
All chemicals were supplied by Sigma-Aldrich®.
B. Characterization
SEM and STEM imaging was done with a
FEI Quanta 200F and JEOL JEM-2200FS setup respectively.
EDX analysis in SEM was performed using
EDAX Genesis 4000. For XRD and in-situ XRD analysis, a
Siemens Kristalloflex D5000
and
Bruker Discover D8
(Vantec linear detector) apparatus were used respectively.
For Temperature-Programmed Reactions and stability tests,
Micromeritics Autochem II 2920 was used.
III. RESULTS AND DISCUSSION
A.
CO2 Capture
In XRD, the presence of inert calcium aluminum oxide as
found by Zhang et al. [4] is observed in all samples.
Performance tests of alumina promoted calcium oxide for 5
carbonation and decarbonation cycles show a superior
activity of 90CaO-10Al2O3 compared with other samples.
The results for 25 cycles (Figure III.1) indicate that apart
from some deactivation during the first 9 hours (15 cycles),
this material remains stable in the next 7 hours (10 cycles).
Figure III.1 TCD-monitored CO2 flow during 25 carbonationdecarbonation cycles of 90CaO-10Al2O3.
Indeed, SEM-EDX analysis of spent 90CaO-10Al2O3
A. Material Preparation
shows the presence of two different morphologies. First,
Materials containing 90, 80 and 70 w% CaO in branched structures are observed which generally show an
CaO-Al2O3 were prepared via wet physical mixing. Calcium elevated alumina content. Second, particles which mainly
consist of calcium oxide are observed. Hence, this branched
Lukas Buelens, Chemical Engineering Department, Ghent University framework is most probably calcium aluminum oxide which
(UGent), Gent, Belgium. E-mail: [email protected].
acts as physical barrier against sintering of the more
Comparing these results with data provided in a
spherical active calcium oxide particles.
bibliographic survey by Pineau et al. [7, 8] shows that the
obtained results for reduction of iron oxide are in compliance
B. CO2 Utilization
with previous work.
From XRD, iron oxide with magnesia promoter is found to
be present as magnesioferrite (MgFe2O4). Reduction of this D. Combined CO2 Capture and Utilization
material leads to severe sintering and hence, this material is
Preliminary experiments were performed using
not suitable for the desired process. When subjected to 10 90CaO-10Al2O3 and 50Fe2O3-50MgAl2O4 in a weight ratio
isothermal redox cycles (Figure III.2), alumina-promoted iron of 3:1. Carbonation of calcium oxide and reduction of iron
oxide shows a strong deactivation during the first redox oxide by hydrogen were combined in a single experiment by
cycle. This is probably due to formation of FeAl2O4 spinel. feeding a gas flow of 1:1 H2 and CO2 (molar ratio). CO was
For a given iron oxide content, MgAl2O4-promoted iron oxide formed by re-oxidation of iron oxide by CO2. The H2 and CO
shows the highest activity. Below 50w% of promoter product flow reached a steady state after a few minutes.
material however, deactivation by iron oxide sintering occurs Afterwards, increasing process temperature resulted in
readily. When the MgAl2O4 content is at least 50w%, activity evolution of CO2, indicating that a net carbonation occurred.
remains stable during the first 10 redox cycles. Specifically, By choosing the degrees of freedom (operation conditions,
these samples produce 0.45 to 0.65 mole CO/mole Fe during gas flow composition and calcium oxide to iron oxide ratio)
each cycle opposed to the 0.25 mole CO/mole Fe for wisely, this process can be optimized to obtain a desired
50Fe2O3-50Al2O3.
relative amount of H2 to CO as gas product stream while
removing all CO2 either by conversion to CO or storage as
carbonate.
IV. CONCLUSION
Figure III.2 Activity for CO2 utilization of different iron oxide based
materials over 10 redox cycles at 750°C.
Upon further increasing the number of cycles to 25
(7 hours of operation), the effects of sintering in
50Fe2O3-50MgAl2O4 are observed both from cyclic redox
tests as well as in SEM images of spent sample. In contrast
with these observations, 10Fe2O3-90MgAl2O4 remains stable
during 60 redox cycles (17 hours of operation). The high
dispersion of iron oxide initially observed using STEM-EDX
was still observed in SEM-EDX analysis of the used sample.
From activity and stability tests of alumina-promoted
calcium oxide with various compositions, sample
90CaO-10Al2O3 was found to be superior compared with
other samples. An inert framework of calcium aluminum
oxide provides a physical barrier against sintering, leading to
a high activity during 16 hours of operation even though a
decay in activity is initially observed.
For iron oxide, MgAl2O4 is a more promising promoter
compared with alumina (deactivation by formation of
FeAl2O4) or magnesia (deactivation by sintering). Activity
and stability of MgAl2O4 promoted iron oxide is especially
high for samples containing more than 50w% of promoter
material, where iron oxide is highly dispersed.
The activation energy of iron oxide reduction by hydrogen
and re-oxidation by carbon dioxide was estimated based on a
simple model and in-situ XRD experimental data.
Finally, combined CO2 capture and utilization may be an
interesting pathway for producing H2 and CO in a desired
ratio by optimization of operating conditions, calcium oxide
to iron oxide ratio and feed flow composition.
REFERENCES
Figure III.3 STEM-EDX images of 10Fe2O3-90MgAl2O4 showing a
[1]
Li, B.Y., et al., Advances in CO2 capture technology: A patent
high level of iron oxide dispersion.
review. Applied Energy, 2013. 102: p. 1439-1447.
[2]
Li, L., et al., A review of research progress on CO 2 capture,
C. Kinetic Modeling
storage, and utilization in Chinese Academy of Sciences. Fuel, 2013.
A basic model for H2-TPR and CO2-TPO of iron oxide 108(0): p. 112-130.
based on in-situ XRD results was proposed. The activation [3] Cao, L. and K. Caldeira, Atmospheric carbon dioxide removal:
energy of reduction and oxidation reactions (Table III.1) was long-term consequences and commitment. Environmental Research
Letters, 2010. 5(2): p. 024011.
estimated
for
samples
90Fe2O3-10MgAl2O4
and [4] Zhang, M., et al., Preparation of CaO–Al O sorbent and CO
2 3
2
50Fe2O3-50MgAl2O4 because these samples were expected to capture performance at high temperature. Fuel, 2013. 111(0): p. 636show the largest differences. For samples with an iron oxide 642.
content below 50w%, iron oxide could not be observed in [5] Najera, M., et al., Carbon capture and utilization via chemical
XRD due to its presence as highly dispersed nanoparticles looping dry reforming. Chemical Engineering Research & Design, 2011.
89(9): p. 1533-1543.
with crystallite size below the detection limit.
[6]
Galvita, V.V., et al., CeO2-Modified Fe2O3 for CO2 Utilization via
Table III.1 Estimated activation energy (kJ/mol) based on a simplified Chemical Looping. Industrial & Engineering Chemistry Research, 2013.
52(25): p. 8416-8426.
model and in-situ XRD experimental data.
[7]
Pineau, A., N. Kanari, and I. Gaballah, Kinetics of reduction of
iron oxides by H2: Part I: Low temperature reduction of hematite.
Reaction
50Fe2O3
90Fe2O3
Thermochimica Acta, 2006. 447(1): p. 89-100.
Fe2O3 → Fe3O4
104.3 ± 0.2
107.9 ± 0.2
[8]
Pineau, A., N. Kanari, and I. Gaballah, Kinetics of reduction of
Fe3O4 → FeO
70.7 ± 0.3
76.7 ± 0.7
iron oxides by H2: Part II. Low temperature reduction of magnetite.
FeO → Fe
78.4 ± 2.2
59.3 ± 0.4
Thermochimica Acta, 2007. 456(2): p. 75-88.
Fe → Fe3O4
99.7 ± 1.6
121.6 ± 3.0
CO2 afvang en gebruik via een chemisch kringproces
Lukas Buelens
Promotoren: Dr. Vladimir Galvita, Dr. Hilde Poelman
Coach: Aditya Dharanipragada
Abstract De focus in dit werk is tweevoudig: enerzijds
worden calciumoxide gebaseerde CO 2 sorbentia onderzocht,
terwijl daarnaast het gebruik van CO2 via een chemisch
kringproces met ijzeroxide gebaseerde materialen wordt
getest. Het best presterende CO 2 sorbent 90CaO-10Al2O3 is
stabiel gedurende 16 uur van opeenvolgende carbonatie en
decarbonatie bij temperaturen tussen 650°C en 800°C. Wat
betreft ijzeroxide wordt de invloed van Al2O3, MgAl2O4 en
MgO op de stabiliteit en activiteit van het materiaal
geëvalueerd. Ijzeroxide met MgAl2O4 promotor toont zowel
de hoogste activiteit als stabiliteit. 10Fe2O3-90MgAl2O4
blijft stabiel voor minstens 17 uur van opeenvolgende redox
cycli bij 750°C dankzij de hoge graad van dispersie van
ijzeroxide deeltjes. De activeringsenergie voor reductie en
oxidatie van ijzeroxide wordt geschat op basis van in-situ
XRD experimenten. Tot slot worden CO2 afvang en gebruik
gecombineerd in een reactoropstelling met gemengd bed.
Trefwoorden CO2 afvang, calciumoxide, CO2 gebruik,
chemisch kringproces, ijzeroxide, magnesia-alumina spinel,
in-situ XRD, kinetische modellering van TPR
II. MATERIALEN EN OPSTELLING
A. Materiaalsynthese
Materialen met een compositie van 90, 80 en 70 gew.%
CaO in CaO-Al2O3 werden gesynthetiseerd via fysische
menging in een solvent. Calciumoxide poeder werd in
ethanol gesuspendeerd, terwijl aluminiumnitraat en
citroenzuur opgelost werden. Ethanol werd uitgekookt
waarna het materiaal gedroogd (120°C) en gecalcineerd
(750°C)
werd.
Chemische
precursoren
waren
Al(NO3)3.9H2O, calciumoxide poeder en citroenzuur.
Monsters met een compositie van 90, 80, 70 en 50 gew.%
Fe2O3 met Al2O3, MgAl2O4 en MgO promotor werden
gesynthetiseerd via co-precipitatie. Precursoren werden
opgelost in gedeïoniseerd water. Een ammoniumhydroxide
oplossing werd druppelsgewijs toegevoegd. Na rusten werd
het precipitaat verwijderd door filtratie, gedroogd (120°C) en
gecalcineerd (750°C). De synthese van Fe2O3-MgAl2O4 werd
herhaald met 100, 90, 80, 70, 50, 30, 20 en 10 gew.%
I. INTRODUCTIE
ijzeroxide. Chemische precursoren waren Al(NO3)3.9H2O,
De jaarlijkse CO2-emissie naar de atmosfeer heeft de Fe(NO3)3.9H2O, Mg(NO3)2.6H2O en ammoniumhydroxide.
afgelopen jaren de kaap van 30 miljard ton overschreden [1]. B. Karakterisering
Omdat CO2 een broeikasgas is, gaat dit gepaard met een
SEM en STEM afbeeldingen werden respectievelijk met
stijging van de gemiddelde globale temperatuur. Simulaties een FEI Quanta 200F en JEOL JEM-2200FS apparaat
voorspellen een atmosferische concentratie van 570 ppm gemaakt. Voor EDX analyse in SEM werd gebruik gemaakt
tegen het jaar 2100 [2]. Een studie van Cao et al. [3] van EDAX Genesis 4000. XRD en in-situ XRD analyse
suggereert dat zowel de capaciteit als de inertie van CO2 werd respectievelijk met een Siemens Kristalloflex D5000 en
reservoirs hoog zijn. Deze resultaten geven aan dat enkel Bruker Discover D8 (Vantec lineaire detector) opstelling
door middel van actieve verwijdering van CO2, uitgevoerd. Voor TPR en stabiliteitstests werd beroep gedaan
pre-industriële CO2 concentraties (280 ppm) bereikt kunnen op een Micromeritics Autochem II 2920.
worden [3]. CO2 afvang kan gecombineerd worden met CO2
gebruik via een chemisch kringproces. In een klassiek
III. RESULTATEN EN DISCUSSIE
chemisch kringproces wordt in een eerste stap een
metaaloxide gereduceerd door een reductans (bvb. A. CO2 Afvang
waterstofgas) waarna het opnieuw geoxideerd wordt door een
In XRD werd de aanwezigheid van inert calcium
oxidans (bvb. koolstofdioxide). CO2 als oxidans wordt aluminiumoxide geobserveerd zoals beschreven door Zhang
gereduceerd tot CO dat, samen met H2, gebruikt kan worden et al. [4]. Onderzoek naar de activiteit van alumina
bij de productie van chemicaliën en brandstoffen gepromoot calciumoxide aan de hand van 5 carbonatie(bvb. via Fischer-Tropsch synthese).
decarbonatie cycli toont een superieure activiteit van
Calciumoxide met alumina promotor blijkt geschikt te zijn 90CaO-10Al2O3.
voor CO2 afvang. Een hoge specifieke opslagcapaciteit wordt
verkregen dankzij het laag atomair gewicht van aluminium,
terwijl de structurele stabiliteit verzekerd wordt door vorming
van Ca12Al14O33 en/of Ca3Al2O6 [4].
Een belangrijke kandidaat voor de reductie van CO2 tot
CO via een chemisch kringproces is ijzeroxide omwille van
de hoge opslagcapaciteit voor zuurstof gebruik makend van
CO2 als oxidans (0.7 mol CO2/mol Fe per redox cyclus) over
een breed temperatuurgebied (600-1800°C) [5, 6]. Een
Figuur III.1 TCD signaal gedurende 25 carbonatie-decarbonatie cycli
bijkomend voordeel van ijzeroxide is dat het overvloedig in
voor 90CaO-10Al2O3.
de natuur voorkomt.
De resultaten voor 25 cycli (Figuur III.1) geven aan dat
ondanks
een beperkte deactivering gedurende de eerste
Lukas Buelens, Chemical Engineering Department, Ghent University
(UGent), Gent, Belgium. E-mail: [email protected].
Tabel III.1 Geschatte activeringsenergie (kJ/mol) gebaseerd op een
9 uren (15 cycli), dit materiaal stabiel blijft in de daarop
vereenvoudigd model en in-situ XRD experimentele data.
volgende 7 uren (10 cycli).
Inderdaad,
SEM-EDX
analyse
van
gebruikt
Reactie
50Fe2O3
90Fe2O3
Fe2O3 → Fe3O4
104.3 ± 0.2
107.9 ± 0.2
90CaO-10Al2O3 toont de aanwezigheid van twee types van
Fe3O4 → FeO
70.7 ± 0.3
76.7 ± 0.7
morfologie aan. Een sterk vertakte structuur met een
FeO
→
Fe
78.4
±
2.2
59.3 ± 0.4
verhoogde concentratie aan aluminium wordt afgewisseld
Fe
→
Fe
O
99.7
±
1.6
121.6
± 3.0
3
4
met meer sferische deeltjes die een hoog gehalte aan
calciumoxide vertonen. De sterk vertakte structuur is D. Gecombineerde CO2 Afvang en Gebruik
ogenschijnlijk calcium aluminiumoxide dat als fysieke
Testexperimenten gebruik makend van een gemengd bed
barrière optreedt tegen het samenklitten van actieve van 90CaO-10Al O en 50Fe O -50MgAl O in een
2 3
2 3
2 4
calciumoxide deeltjes.
gewichtsverhouding van 3:1 werden uitgevoerd. Carbonatie
B. CO2 Gebruik
van calciumoxide en reductie van ijzeroxide door
Uit XRD resultaten volgt dat ijzeroxide met magnesia waterstofgas werden gecombineerd door voeding van 1:1 H2
promotor aanwezig is als magnesioferriet (MgFe2O4). De en CO2 (molaire verhouding). CO werd gevormd door
reductie van dit materiaal leidt tot sinteren wat het re-oxidatie van ijzeroxide door CO2. Na een toename van de
ongeschikt maakt voor het gewenste proces. Bij uitvoering temperatuur werd vorming van CO2 waargenomen, wat wijst
van 10 isotherme redox cycli (Figuur III.2) treedt een op een netto carbonatie in voorgaande stap. Door een slimme
duidelijke deactivering van alumina gepromoot ijzeroxide op. keuze van de vrijheidsgraden (procescondities, verhouding
Hoogstwaarschijnlijk ligt de oorzaak in de vorming van calciumoxide tot ijzeroxide en voedingscompositie) kan dit
FeAl2O4. Voor een gegeven gehalte aan ijzeroxide blijkt dat proces geoptimaliseerd worden om H2 en CO in een
de hoogste activiteit behaald wordt met MgAl2O4 als gewenste verhouding te verkrijgen terwijl CO2 verwijderd
promotor. Desalniettemin treedt sintering op wanneer het wordt door vorming van CO of opslag als carbonaat.
gehalte aan promotormateriaal onder de 50 gew.% ligt. In het
IV. CONCLUSIE
bijzonder produceren de materialen met een hoger gehalte
Het meest geschikte materiaal voor CO2 afvang bleek
aan MgAl2O4 per redox cyclus 0.45 tot 0.65 mol CO/mol Fe
90CaO-10Al2O3 te zijn. Een inerte structuur van calcium
tegenover 0.25 mol CO/mol Fe voor 50Fe2O3-50Al2O3.
aluminiumoxide voorziet het materiaal van een fysieke
barrière tegen sinteren. Dit leidt tot een hoge activiteit
gedurende 16 uren (25 cycli) carbonatie en decarbonatie bij
temperatuur tussen 650°C en 800°C.
MgAl2O4 is een meer belovende promotor voor ijzeroxide
dan alumina of magnesia. De activiteit en stabiliteit van
Fe2O3-MgAl2O4 is in het bijzonder hoog voor monsters die
een promotorgehalte hebben dat boven 50 gew.% ligt. Deze
materialen vertonen een hoge dispersie van ijzeroxide.
De activeringsenergie voor reductie en re-oxidatie van
Figuur III.2 Activiteit voor CO2 gebruik van verschillende ijzer oxide
ijzeroxide werd geschat op basis van een eenvoudig model en
gebaseerde materialen gedurende 10 redox cycli bij 750°C.
in-situ XRD experimentele data.
Bij toename van het aantal cycli tot 25 (7 uren bij 750°C),
Tot slot kan het proces van gecombineerde CO2 afvang en
wordt ook bij 50Fe2O3-50MgAl2O4 sintering geobserveerd.
gebruik afhankelijk van de procescondities, ijzeroxide tot
In tegenstelling tot deze waarnemingen blijft de activiteit van
calciumoxide verhouding en voedingscompositie, leiden tot
10Fe2O3-90MgAl2O4 stabiel gedurende 60 redox cycli (17
het verkrijgen van H2 en CO in verschillende verhoudingen.
uren bij 750°C). De hoge dispersie van ijzeroxide in het vers
materiaal (STEM-EDX, Figuur III.3) werd ook
REFERENTIES
teruggevonden bij SEM-EDX analyse na gebruik.
Figuur III.3 STEM-EDX afbeeldingen van vers 10Fe2O3-90MgAl2O4
C. Kinetische Modellering
Een eenvoudig model werd opgesteld voor H2-TPR en
CO2-TPO van ijzeroxide gebaseerd op in-situ XRD
resultaten. De activeringsenergie (Tabel III.1) werd geschat
voor 90Fe2O3-10MgAl2O4 en 50Fe2O3-50MgAl2O4 omdat
tussen deze materialen het grootste verschil verwacht werd.
Bij een lager ijzeroxide gehalte wordt ijzeroxide niet
waargenomen in XRD. De resultaten (Tabel III.1) stemmen
overeen met het bibliografisch onderzoek uitgevoerd door
Pineau et al. [7, 8].
[1]
Li, B.Y., et al., Advances in CO2 capture technology: A patent
review. Applied Energy, 2013. 102: p. 1439-1447.
[2]
Li, L., et al., A review of research progress on CO2 capture,
storage, and utilization in Chinese Academy of Sciences. Fuel, 2013.
108(0): p. 112-130.
[3]
Cao, L. and K. Caldeira, Atmospheric carbon dioxide removal:
long-term consequences and commitment. Environmental Research
Letters, 2010. 5(2): p. 024011.
[4]
Zhang, M., et al., Preparation of CaO–Al2O3 sorbent and CO2
capture performance at high temperature. Fuel, 2013. 111(0): p. 636642.
[5]
Najera, M., et al., Carbon capture and utilization via chemical
looping dry reforming. Chemical Engineering Research & Design, 2011.
89(9): p. 1533-1543.
[6]
Galvita, V.V., et al., CeO2-Modified Fe2O3 for CO2 Utilization via
Chemical Looping. Industrial & Engineering Chemistry Research, 2013.
52(25): p. 8416-8426.
[7]
Pineau, A., N. Kanari, and I. Gaballah, Kinetics of reduction of
iron oxides by H2: Part I: Low temperature reduction of hematite.
Thermochimica Acta, 2006. 447(1): p. 89-100.
[8]
Pineau, A., N. Kanari, and I. Gaballah, Kinetics of reduction of
iron oxides by H2: Part II. Low temperature reduction of magnetite.
Thermochimica Acta, 2007. 456(2): p. 75-88.
Table of Contents
Chapter 1
Introduction ................................................................................................................... 1
Chapter 2
Literature survey............................................................................................................ 2
2.1. General principles of CO2 capture and utilization ........................................................................ 2
2.1.1. Principles of CO2 Capture .................................................................................................. 2
2.1.1.1. Strategies for CO2 capture ................................................................................ 2
2.1.1.2. Calcium Looping Process .................................................................................. 3
2.1.2. Principles of CO2 Utilization............................................................................................... 5
2.1.2.1. Chemicals, fuels and other applications ........................................................... 5
2.1.2.2. Chemical Looping Process ................................................................................ 5
2.2. Material preparation methods..................................................................................................... 7
2.3. Material performance tests and indicators ................................................................................. 9
2.3.1. Capture performance of CO2 sorbent ............................................................................... 9
2.3.1.1. Conversion ........................................................................................................ 9
2.3.1.2. Storage capacity ............................................................................................... 9
2.3.1.3. Multicyclic carbonation-calcination tests ....................................................... 10
2.3.2. Redox performance of oxygen carrier materials............................................................. 11
2.3.2.1. Oxygen ratio ................................................................................................... 11
2.3.2.2. Fuel conversion............................................................................................... 11
2.4. Influence of chemical structure and morphology on performance ........................................... 12
2.4.1. Properties of CO2 sorbent materials ............................................................................... 12
2.4.2. Properties of oxygen carrier materials ............................................................................ 14
2.4.2.1. Chemical Looping Combustion ....................................................................... 14
2.4.2.2. Chemical Looping Dry Reforming ................................................................... 16
2.5. Kinetic modeling......................................................................................................................... 19
2.5.1. Kinetic modeling of Gas-Solid reactions .......................................................................... 19
2.5.2. Kinetic modeling of Temperature-Programmed Reactions ............................................ 19
2.5.3. Activation energy for reduction/oxidation of iron oxide ................................................ 20
2.5.3.1. Reduction of iron oxide .................................................................................. 20
2.5.3.2. Oxidation of iron oxide ................................................................................... 20
I
Table of Contents
Chapter 3
Materials and methods ............................................................................................... 21
3.1. Material synthesis ...................................................................................................................... 21
3.1.1. CO2 capture material ....................................................................................................... 21
3.1.1.1. CaO with Al2O3 promoter material ................................................................. 21
3.1.1.2. CaO with Al2O3 promoter material using citric acid ....................................... 22
3.1.2. Oxygen carrier materials ................................................................................................. 23
3.1.2.1. Fe2O3 with Al2O3, MgAl2O4 or MgO promoter ................................................ 23
3.1.2.2. Fe2O3 with MgAl2O4 promoter: extension of composition range ................... 24
3.2. Material characterization techniques ........................................................................................ 25
3.2.1. Inductively Coupled Plasma – Atomic Emission Spectroscopy (ICP-AES)........................ 25
3.2.2. Scanning Electron Microscopy (SEM) .............................................................................. 26
3.2.3. Scanning Transmission Electron Microscopy (STEM) ...................................................... 26
3.2.4. Energy Dispersive X-ray (EDX) analysis............................................................................ 26
3.2.5. N2-B.E.T. analysis ............................................................................................................. 27
3.2.6. X-Ray Diffraction (XRD) analysis ...................................................................................... 28
3.2.7. In-situ X-Ray Diffraction (XRD) analysis ........................................................................... 29
3.2.8. Temperature-Programmed Reaction (TPR) ..................................................................... 30
Chapter 4
CO2 Capture ................................................................................................................. 32
4.1. Characterization of calcium oxide based CO2 sorbents ............................................................. 32
4.1.1. SEM-EDX analysis ............................................................................................................ 32
4.1.2. N2-B.E.T. analysis ............................................................................................................. 33
4.1.3. XRD analysis..................................................................................................................... 33
4.1.4. Temperature-Programmed Carbonation-Decarbonation ............................................... 35
4.2. Stability of calcium oxide based CO2 sorbents ........................................................................... 36
Chapter 5
CO2 Utilization.............................................................................................................. 40
5.1. Characterization of iron oxide based oxygen carrier materials ................................................. 40
5.1.1. ICP-AES analysis ............................................................................................................... 40
5.1.2. SEM-EDX analysis ............................................................................................................ 41
5.1.3. N2-B.E.T. analysis ............................................................................................................. 45
5.1.4. XRD analysis..................................................................................................................... 46
5.1.5. STEM-EDX analysis........................................................................................................... 50
5.1.6. Temperature-Programmed Reduction by H2 .................................................................. 51
5.1.7. Temperature-Programmed Oxidation by CO2 ................................................................. 53
II
Table of Contents
5.2. Stability of iron oxide based oxygen carrier materials ............................................................... 55
5.2.1. In-situ XRD isothermal redox cycles ................................................................................ 55
5.2.1.1. Iron oxide promoted by alumina .................................................................... 55
5.2.1.2. Iron oxide promoted by magnesia-alumina spinel ......................................... 56
5.2.1.3. Iron oxide promoted by magnesia ................................................................. 57
5.2.2. Micromeritics isothermal redox cycles ........................................................................... 57
5.2.3. SEM-EDX study ................................................................................................................ 63
Chapter 6
Kinetic modeling .......................................................................................................... 66
6.1. Temperature-Programmed Reduction of iron oxide ................................................................. 66
6.1.1. Model description ........................................................................................................... 66
6.1.2. Estimation of kinetic parameters .................................................................................... 68
6.1.3. Model validation ............................................................................................................. 70
6.2. Temperature-Programmed Oxidation of metallic iron .............................................................. 72
6.2.1. Model description ........................................................................................................... 72
6.2.2. Estimation of kinetic parameters .................................................................................... 72
6.2.3. Model validation ............................................................................................................. 74
Chapter 7
Combined CO2 capture and utilization ........................................................................ 75
7.1. Separate bed test experiment.................................................................................................... 75
7.2. Mixed bed test experiment ........................................................................................................ 78
Chapter 8
Conclusion ................................................................................................................... 80
Future work ........................................................................................................................................... 82
Appendices ............................................................................................................................................ 83
Appendix A
Overview of performed experiments ........................................................................ 83
Appendix B
XRD Powder Diffraction Patterns .............................................................................. 89
Appendix C
Estimating particle size based on X-Ray Diffraction using Scherrer’s equation ...... 103
Appendix D
Estimating particle size based on Scanning Electron Microscopy ........................... 106
Appendix E
Methodology for estimating oxygen conversion in isothermal redox cycles ......... 109
Appendix F
Post-processing in-situ X-Ray Diffraction data ........................................................ 113
Appendix G
Athena Visual Studio (AVS®) code for modeling H2-TPR ......................................... 118
Appendix H
Athena Visual Studio (AVS®) code for modeling CO2-TPO ...................................... 119
References........................................................................................................................................... 120
III
List of symbols and acronyms
Symbol
Description
A
Pre-exponential factor
Arrhenius parameter, units depend on kinetics
Aj
Pre-exponential factor
Arrhenius parameter for reaction step j
Apparent pre-exponential factor
Arrhenius parameter for reaction step j
Aj
app
Units*
Surface area occupied by a single sorbate
molecule, B.E.T. equation
am
Molecular surface area
as
Specific surface area
[m²/g]
b
Instrumental width
[deg],[rad]
c
Molar concentration
[mol/m³]
Lambert-Beer equation
Cmax
Maximum storage capacity
[g CO2/g]
Maximum theoretical storage capacity
Cn
Storage capacity
[g CO2/g]
CO2 storage capacity after n cycles
d
Plane distance
[nm]
Distance between two lattice planes,
Bragg’s law
d
Path length of light
[m]
Lambert-Beer equation
d
Particle dimension
[nm]
dp
Particle dimension
dSEM
Particle dimension
[nm]
Measure for particle dimension based on SEM
dXRD
Particle dimension
[nm]
Measure for particle dimension based on XRD
Ea
Activation energy
[kJ/mol]
Arrhenius parameter
Apparent activation energy
[kJ/mol]
Arrhenius parameter for reaction step j
ΔH°
Standard reaction enthalpy
[kJ/mol i]
Standard reaction enthalpy per mole of
reaction unless component i is specified
I
Measured intensity
[-]
Lambert-Beer equation
I0
Measured reference intensity
[-]
Lambert-Beer equation
I0
Integrated intensity
[-]
Integrated XRD intensity of background
Ii
Integrated intensity
[-]
Integrated XRD intensity of phase i
kj
Reaction rate coefficient
Ea,j
app
[m²]
Remarks
B.E.T.-Specific surface area
Scherrer’s law
Measured particle dimension
Reaction rate coefficient of reaction step j
IV
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###
Chapter 1 Introduction
During the past decades, global awareness and concern with respect to air pollutant emission such as
SOx, NOx and CO2 has steadily grown. To counteract these developments, regulations and legislation
have triggered process revisions including offgas and fuel feedstock treatment by imposing restraints
on emissions. For reducing SOx emissions, fuels are hydrotreated forming H2S which can be recycled
using Claus’ procedure. Denitrification of fuels using ammonia in Selective Catalytic Reduction (SCR)
processes reduces NOx emissions from industry. However, emissions from non-industrial combustion
engines are significant due to prompt NOx formation of nitrogen and oxygen present in combustion
air. Recently, fuel additives were claimed to reduce these emissions. Control of CO2-emissions is
probably intrinsically the most demanding because together with water, carbon dioxide forms one of
the two main combustion products of all hydrocarbon based fuels. Evidently, formation of CO2 is
unavoidable when using hydrocarbon fuels as energy source.
With the focus on emission prevention, CO2 removal from streams with a considerable concentration
of CO2 such as combustion offgases (10-20% CO2) gains most of the attention in literature. Another
strategy could be sequestration of atmospheric CO2 (300-500 ppm) for reducing the amount of CO2
already present in the atmosphere.
There are several ideas for CO2 disposal such as storage in former oil/gas pockets. This kind of CO2
storage is perhaps the only realizable short term solution. From a sustainability and economical point
of view however, compressed CO2 storage does not seem very elegant. Therefore, CO2 capture
combined with utilization is probably a more feasible long term strategy. The CO2 sequestration
technologies are generally sorbent based technologies and combination of these techniques with CO2
utilization is increasingly becoming popular.
An application of CO2-sorbents that has come to the attention of researchers is the concept of
sorption enhanced chemical looping process. It combines the use of CO2 as oxidant in a chemical
looping procedure using a metal as reductor, where pure CO or syngas can be formed, with CO2
capture by a CO2 sorbent material. Starting from CO as activated carbon dioxide, various reaction
pathways exist to produce high quality fuels or chemicals. An additional advantage of this process is
that it could drastically reduce the amount of point sources of NOx- and SOx-emission because of this
high fuel quality. Development of efficient CO2 capture methods and CO2 utilization processes could
transform CO2 into a useful chemical rather than a redundant waste product.
Hence the emphasis in this thesis lies on preparation and investigation of novel materials which are
tested for CO2 capture and utilization through chemical looping processes. The goal of this thesis is to
study the process of CO2 capture by calcium oxide based materials followed by utilization of CO2
using iron oxide based materials. Both of these processes may be referred to as chemical looping
processes. Finally, the possibility of combined capture and utilization is considered and investigated.
1
Chapter 2 Literature survey
This Chapter is a preliminary literature survey on the subject of CO2 capture and utilization via
chemical looping processes. The focus of the literature study on CO2 capture lies on the properties of
calcium oxide as solid CO2 sorbent material. Furthermore, typical features of redox processes via
chemical looping are discussed. For CO2 utilization, iron oxide based material gains most of the
attention. Finally, an introduction to kinetic modeling of gas-solid reactions is included as well as a
brief summary on the kinetics of reduction and oxidation of iron oxide.
2.1. General principles of CO2 capture and utilization
2.1.1. Principles of CO2 Capture
2.1.1.1. Strategies for CO2 capture
In the past 150 years, the mean concentration of CO2
in the atmosphere has increased from 280 ppm to
370 ppm, mainly due to processes such as combustion
of hydrocarbon fuels, fermentation of carbohydrate
material and manufacturing of cement and lime [1, 2].
Today, over 30 billion tons of CO2 are emitted into the
atmosphere each year [2]. Because CO2 is a
greenhouse gas, this is accompanied by an increase in
average global temperature. Simulations predict a
concentration of up to 570 ppm by 2100 [1]. In a study
by Cao et al., the response of CO2 reservoirs to active
CO2 removal from the air was simulated (Figure 2.1).
The main conclusion is that both the capacity and the
inertia of different CO2 reservoirs is high. Therefore, a Figure 2.1 – Simulation results of a study by
one-time removal or zero-emission strategy most Cao et al. investigating the response of CO2
probably will not affect atmospheric CO2 levels reservoirs on active CO2 removal from air.
significantly in the first centuries because of equilibrium. The results of this study suggest that only
by active carbon dioxide removal, a return to pre-industrial CO2 levels can be achieved [3].
In order to realise the necessary CO2 removal, separation of CO2 from diluted streams is critical.
Five main strategies for CO2 separation exist, i.e. solvent absorption, cryogenic fractionation,
membrane separation, solid absorption and solid adsorption. Today, CO2 is most commonly removed
by amine scrubbing. Even though solvent absorption is widely used for de-acidification purposes, it is
probably not suitable for CO2 capture on a large scale due to excessive energy requirements for
regeneration of solvents [4] and due to toxicity of solvents such as monoethanolamine (MEA).
Furthermore, unintentional absorption of impurities such as SOx and NOx occurs if these compounds
are present [4], thereby impairing the purity of the product stream. Cryogenic fractionation allows
for a high purity product stream but demands a great amount of energy. Moreover, for CO2 capture
from air it requires cooling of a large excess of inert components for a feed stream containing no
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Chapter 3 Materials and methods
The outline of this Chapter is twofold. Firstly, the various preparation procedures followed during the
synthesis of calcium oxide materials promoted by alumina and iron oxide materials promoted by
alumina and/or magnesia are described (section 3.1). Furthermore, an overview is given of the
techniques that are used for material characterization and testing with a brief summary of some of
the basic principles on which these techniques rely (section 3.2).
3.1. Material synthesis
3.1.1. CO2 capture material
3.1.1.1. CaO with Al2O3 promoter material
Based on a literature survey, calcium oxide with alumina promoter material shows a satisfying
activity and stability at a composition of 80-20 (w%) CaO-Al2O3. Therefore, a sample denoted CAWI
was prepared via wet impregnation aiming at this composition. Precursors are listed in Table 3.1.
Table 3.1 – List of chemicals used for preparation of sample 80CaO-20Al2O3
(denoted CAWI). All chemicals were supplied by Sigma-Aldrich®.
Precursor
Purity
MW (g/mol)
Al(NO3)3.9H2O
98%
375.13
CaO powder
96%
56.08
Ethanol
solvent
After weighing precursors in order to obtain 5 g of the desired sample, aluminum nitrate was
dissolved in 20 ml of a 50/50 (v%) mixture of deionized water and ethanol. Next, this solution was
added to calcium oxide powder and mixed into a homogenous paste. After drying in an oven at 80°C
for 4 hours, with intermittent grinding of the paste, the material was calcined at 850°C for 1 hour
(heating rate 3.4°C/min) according to the temperature program shown in Figure 3.1.
Figure 3.1 – Temperature program for calcination of sample CAWI.
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"
Chapter 4 CO2 Capture
This Chapter presents the results and interpretation of various characterization techniques,
described in Chapter 3, employed to study alumina-promoted calcium oxide. Additionally, the
performance of these materials as CO2 capture sorbent is assessed both from an activity and stability
point of view. The synthesis of these CO2 sorbent materials is discussed in section 3.1.1. For an
overview of the performed experiments, the reader is referred to Appendix A.
4.1. Characterization of calcium oxide based CO2 sorbents
4.1.1. SEM-EDX analysis
Figure 4.1 shows SEM images for all CO2 sorbent materials. Calcium oxide based materials prepared
with citric acid as complexant (CA1-CA3) show an open porous structure whereas the sample
prepared via wet impregnation (CAWI) consists of large particle clusters. Crystallites in sample
90CaO-10Al2O3 (CA1) vary from needle-shaped to sponge-like structures. According to literature [28,
30], these needles are characteristic for CaCO3 (aragonite crystals).
Figure 4.1 – SEM images for CA1, CA2, CA3 and CAWI. Scale bars show 50 µm (upper left) and 5µm.
As for the composition, significant deviations from the expected calcium oxide content are observed
for samples CA2 and CA3 which were expected to contain 80w% and 70w% CaO respectively.
Table 4.1 – Expected and calculated (EDX) composition for different CO2
sorbent materials.
Sample
CAWI
CA1
CA2
CA3
CaO content (w%)
Expected
EDX
80
78.4
90
92.4
80
73.4
70
74.8
32
Chapter 4
CO2 Capture
4.1.2. N2-B.E.T. analysis
Table 4.2 shows that samples CA1-CA3 show a specific surface area of roughly 10 m²/g and varies
little with alumina content. Furthermore, samples prepared by a wet physical mixing method (WPM)
with citric acid as complexant show a higher specific surface area (SSA) than the reference sample
80CaO-20Al2O3 prepared by wet impregnation. The B.E.T.-SSA of this material was too low to be
measurable by N2 adsorption. The low specific surface area is in line with the observations made
from SEM-analysis (Figure 4.1).
Table 4.2 – Overview of B.E.T.-SSA for different CO2 sorbent
materials. N/A indicates that the B.E.T.-SSA for the sample prepared
by wet impregnation method was too low to be measurable.
Sample
CAWI: 80CaO-20Al2O3
B.E.T.-SSA (m²/g)
N/A
CA1: 90CaO-10Al2O3
10.44 ± 0.08
CA2: 80CaO-20Al2O3
10.80 ± 0.22
CA3: 70CaO-30Al2O3
8.42 ± 0.11
4.1.3. XRD analysis
From XRD analysis (Figure 4.2), a contribution of crystalline calcium oxide (CaO) and
mayenite (Ca12Al14O33) is observed for the sample prepared via wet impregnation (WI).
Figure 4.2 – XRD spectrum for fresh calcium oxide based samples CA1-CA3 and CAWI.
33
Chapter 4
CO2 Capture
As opposed to mayenite, which shows a whole range of peaks with weak to intermediate signal
intensity, the X-ray powder diffraction pattern of calcium oxide results in distinctive 2θ-signals at 32°,
37°, 53°, 64° and 67°. The most intense peaks at 2θ=18° and 2θ=41° confirmed the presence of
mayenite. For the samples (CA1-CA3) prepared via WPM with citric acid as complexant, the
fingerprint is somewhat different. Here, the mayenite contribution is fairly weak. Instead, the more
stable (Figure 2.5, section 2.4.1, page 14) calcium aluminum oxide (Ca3Al2O6) is observed. These three
samples, in accordance with their higher specific surface area compared with the sample prepared by
wet impregnation, are found to absorb CO2 and form calcite (CaCO3, 2θ=30°) under ambient
conditions. For a detailed overview of the XRD powder diffraction patterns of the phases assigned
in Figure 4.2, the reader is reffered to Appendix B.
The Scherrer equation as discussed in section 3.2.6 (Eq. 3.6) provides a measure for the calcium oxide
crystallite size. The average particle size and corresponding standard deviation (Table 4.3) are
determined after applying Scherrer’s equation to 5 most intense characteristic peaks of calcium
oxide. The diffraction angle 2θ and Miller indices (hkl) of these peaks are 32° (111), 37° (200),
54° (220), 64° (311) and 67 (222). For samples prepared by WPM, the estimated particle size
decreases from 72 nm to 41 nm when increasing the alumina load from 10w% to 30w%. As for the
material prepared by wet impregnation, a high average particle size is obtained. The large error bar is
due to one of following reasons. First, assuming that no peak overlap occurs and the characteristic
dimensions are well calculated, this may suggest that calcium oxide crystallites prepared by wet
impregnation show large deviations from sphericity. A second possibility is that peak broadening due
to overlap of one or more of the characteristic peaks occurs, which would lead to an underestimation
of the particle dimension perpendicular to the respective plane. For a more detailed explanation on
the application of Scherrer’s equation for particle size estimation based on XRD, the reader is
referred to Appendix C.
Table 4.3 – Crystallite size (nm) of alumina-promoted calcium oxide with different composition
and preparation method estimated from XRD data using Scherrer’s equation. The error
represents the standard deviation for averaging the crystallite size over 5 different planes.
Composition (w%)
Wet physical mixing
(CA1-CA3)
Wet impregnation
(CAWI)
90 CaO – 10 Al2O3
71.5 ± 18.1
-
80 CaO – 20 Al2O3
41.8 ± 9.1
139.3 ± 97.6
70 CaO – 30 Al2O3
40.9 ± 7.8
-
34
Chapter 4
CO2 Capture
4.1.4. Temperature-Programmed Carbonation-Decarbonation
Temperature-Programmed Carbonation-Decarbonation (CO2-TPCD) shows that the temperature at
which a maximum CO2 consumption occurs (600-650°C) is decreased with an increasing load of
promoter material (Figure 4.3). The temperature of maximum CO2 release occurs in the temperature
range of 850°C to 900°C. Carbonation of the sample prepared by wet impregnation is very slow
corresponding with the large particles (cfr. SEM images, Figure 4.1) and low specific surface area
(cfr. N2-B.E.T., Table 4.2) which results in strong diffusion limitations. It is peculiar that, despite the
similar EDX-composition of samples CA2 and CA3, a very different CO2-TPCD profile is obtained.
Figure 4.3 – CO2-TPCD of calcium oxide based samples between 100°C and 950°C
with β=20°C/min after a pretreatment of 10 min at 800°C. Gas flow rate is
60 ml/min (20% CO2 in He).
The weak absorption of CO2 in samples CA2 and CA3 with respect to CA1 is explained by formation of
inert Ca3Al2O6. Therefore, the true active calcium oxide content is lower than expected. This is
illustrated by Table 4.4, which shows the corrected composition when all Al2O3 would be converted
into Ca3Al2O6. The amount of active calcium oxide would quickly drop with the amount of alumina
promoter that was initially added. This, however, does not explain why sample CA2 shows faster CO 2
absorption kinetics than sample CA3. Indeed, according to literature [31, 33], the bulk of alumina in
alumina-promoted calcium oxide occurs under the form of mayenite or calcium aluminum oxide.
Table 4.4 – Expected, calculated (EDX) and corrected composition of different CO2 sorbent materials. The
corrected composition takes into account maximum formation of inert calcium aluminum oxide material.
Sample
CAWI
CA1
CA2
CA3
CaO content (w%)
Expected
EDX
80
78.4
90
92.4
80
73.4
70
74.8
Corrected EDX composition (w%)
58CaO - 42Ca12Al14O33
80CaO - 20Ca3Al2O6
29CaO - 71Ca3Al2O6
33CaO - 67Ca3Al2O6
35
Chapter 4
CO2 Capture
4.2. Stability of calcium oxide based CO2 sorbents
The main features found in CO2-TPCD analysis of calcium oxide based samples are confirmed when
calcium oxide based materials are subjected to carbonation-decarbonation cycles (Figure 4.4).
Compared to the samples with a higher promoter content, sample 90CaO-10Al2O3 (CA1) shows a high
CO2 absorption capacity with fast kinetics in both carbonation at 650°C and decarbonation at 800°C.
As mentioned above, the reason lies in consumption of calcium oxide during the material synthesis,
where inert calcium aluminum oxide is formed.
Figure 4.4 – CO2 flow during cycles of calcium oxide carbonationdecarbonation at 650°C and 800°C respectively. Feed flow is 60 ml/min
(20% CO2 in He) during both carbonation and decarbonation step.
During carbonation, two main regions are distinguished. Initially, CO2 consumption is rapid,
corresponding with the simultaneous occurrence of two phenomena: First, the optimum
temperature for CO2 absorption may be somewhat higher than 650°C. When cooling from 800°C to
650°C, carbonation is fast at the optimum temperature. This also explains why, upon heating towards
the decarbonation temperature after carbonation at 650°C, CO2 is initially consumed. Second, the
reaction in this region is surface-controlled. After this rapid initial CO2 consumption, a region of
diffusion-limited carbonation occurs. This is caused by the strong increase of volume when
converting CaO into CaCO3 which may form an isolating shell around particles or cause pore
blockage. As discussed earlier, carbonation increases rapidly up to 750°C. At higher temperatures,
decarbonation is favored over carbonation. The process of decarbonation is generally less hindered
by diffusion limitations because transition of CaCO3 to CaO generally corresponds with the structure
regaining its porosity. Of course, material sintering may cause loss of porosity over time. Note that
the feed flow was not changed in order to investigate decarbonation under realistic conditions,
where CO2 might be present or where the flow might even be pure CO2. Because the feed flow
during carbonation under realistic conditions is obviously not pure CO2, the feed flow composition
was chosen at 20% CO2 in an inert atmosphere. The gas flow during carbonation and decarbonation
was left unchanged in order to obtain a more stable TCD signal.
36
Chapter 4
CO2 Capture
Figure 4.4 indicates that sample CA1 sinters when subject to several cycles of carbonationdecarbonation. The decrease of specific surface area is suggested by the decreased intensity of CO2
consumption in the initial surface-controlled stage. As discussed previously, samples CA2-CA3 show a
low CO2 storage capacity due to the small content of active calcium oxide. These samples, as
expected, are less sensitive to sintering.
The best performing material, 90CaO-10Al2O3 (CA1), was then subjected to 25 subsequent
carbonation-decarbonation cycles (Figure 4.5). The experiment starts after 0.5 h. In the first 15
cycles, the activity is found to decrease. After 15 cycles however, the activity remains constant,
indicating that the material has stabilized after 9 hours at process conditions.
Figure 4.5 – CO2 flow during 25 cycles of 90CaO-10Al2O3 (CA1) carbonation-decarbonation between 650°C and
800°C. Feed flow is 60 ml/min (20% CO2 in He) during both carbonation and decarbonation step.
Figure 4.6 shows SEM images of fresh CA1-CA3 and of sample material after being subjected to
5 carbonation-decarbonation cycles. Indeed, it is found that the particle size of sample
90CaO-Al2O3 (CA1) increases when performing these experiments. For samples 80CaO-20Al2O3 (CA2)
and 70CaO-Al2O3 (CA3), it is more difficult to get a clear view on the effect of these carbonationdecarbonation cycles due to the great variety in morphology that is observed. Some images, which
probably show clusters of active calcium oxide, show severe sintering. In SEM images which show
regions that mainly consist of inert calcium aluminum oxide, sintering is expected to be limited if not
nonexistent.
37
Chapter 4
CO2 Capture
Figure 4.6 – SEM images of CA1-CA3 before and after 5 carbonation-decarbonation cycles.
Similarly as for the samples that were subjected to 5 carbonation-decarbonation cycles, the
morphology of 90CaO-10Al2O3 after 25 cycles was investigated. SEM-EDX results, shown in Figure 4.7,
indicate the presence of two types of regions. As for the morphology, a branched structure is clearly
distinguished from more spherical particle structures. Given that the composition of these branched
structures typically show a high content of alumina (30 At%) suggests, as stated above, that some
type of calcium aluminum oxide (Ca3Al2O6, cfr. Figure 4.2, page 33) is present. This structure is highly
stable under the given experimental conditions. The more spherical particles show a high calcium
oxide content (85-90 At%) and their morphology after 25 cycles corresponds with expectations for
active calcium oxide, i.e. smooth particles with a high degree of sphericity due to sintering at high
temperatures. Nevertheless, given the branched structure of the inert calcium aluminum oxide,
particle growth seems is not that outspoken. SEM images suggest that the Ca3Al2O6 framework acts
as a physical barrier against sintering of active calcium oxide particles. As stated previously, further
increasing the number of carbonation-decarbonation cycles and the duration of exposion to
operating conditions at 650°C to 800°C would be interesting to investigate how the activity and
morphology of this material will further evolve.
38
Chapter 4
CO2 Capture
Figure 4.7 – SEM-EDX study of 90CaO-10Al2O3 (CA1) after 25 carbonation-decarbonation cycles. The inset shows the
EDX-composition at specific regions. At% denotes that the composition is given in atomic/molar percentage.
Besides calcium and aluminum, EDX results show contributions of carbon, gold and oxygen.
39
Chapter 5 CO2 Utilization
In this Chapter on CO2 utilization, iron oxide based materials prepared via co-precipitation
(section 3.1.2) are characterized by using a broad variety of techniques (section 3.2).
Their reducibility and activity for CO2 conversion to CO is evaluated. Stability with respect to
deactivation and sintering is addressed for all samples. The best performing materials are subjected
to a larger number of redox cycles and hence exposed to operation conditions for a longer period.
Appendix A provides an overview of the experiments conducted for characterization and testing of
iron oxide based materials.
5.1. Characterization of iron oxide based oxygen carrier materials
5.1.1. ICP-AES analysis
First, the composition of the prepared materials was investigated using ICP-AES to check consistency
with the expected composition (Figure 5.1). For alumina-promoted iron oxide, the only significant
deviation occurs for the sample with desired iron oxide content of 50w%. When MgAl2O4 or
magnesia was used as promoter material, the measured composition was systematically lower
(resp. higher). Overall, deviations are small enough to be attributed to inevitable inaccuracies
occurring in material preparation procedures.
Figure 5.1 – ICP-measured iron oxide content compared with expected iron oxide
content for samples promoted by alumina (S1-S4), magnesia-alumina (S5-S8) and
magnesia (S9-S12). The (1) indicates that results for the first series of
MgAl2O4-promoted iron oxide are shown.
40
Chapter 5
CO2 Utilization
5.1.2. SEM-EDX analysis
From the SEM images shown in Figure 5.2, both the smallest and largest particles are observed when
using alumina as promoter material. This suggests that at least two different phases are present. As
seen best in samples with high iron oxide content, small particles are dispersed on micron-scale
particles when using alumina as promoter material. Based on these SEM images, there is not much
change in particle size with increasing iron oxide content.
Figure 5.2 – SEM images of fresh samples promoted by alumina (S1-S4), magnesia-alumina (S5-S8) and
magnesia (S9-S12) with different iron oxide content (w% Fe2O3 – w% promoter). Scale bar represents 1 µm.
For the series of iron oxide based samples with MgAl2O4 promoter, the largest particles tend to
decrease in size quite significantly between 90 and 70w% iron oxide. The two samples with the
highest iron oxide content shows finely dispersed particles. Keeping the composition in mind, it is
expected that MgAl2O4 is dispersed on Fe2O3 particles. For the sample containing 70w%,
41
Chapter 5
CO2 Utilization
distinguishing between particles of both phases is more difficult. When the weight of iron oxide and
promoter material are equal, large particles are observed along with smaller particles which have a
similar size as in the sample with 70w% iron oxide.
The evolution of magnesia-promoted iron oxide is quite similar as for MgAl2O4-promoted iron oxide
where the particle size of the former is generally higher for a fixed ratio of iron oxide to promoter
material. Also, the decrease in particle size with increasing iron oxide content is less pronounced.
The general trend in particle size of the dispersed phase (Figure 5.2) for fixed iron oxide content
is Al2O3<MgAl2O4<MgO.
EDX measurements were performed to assess the extent to which the desired composition for all
samples was achieved. The results are shown in Figure 5.3A and indicate that, according to EDX, most
of the samples showed the expected composition. Only for iron oxide with magnesia promoter
significant systematic deviations occur. Particularly, the EDX-composition of magnesia-promoted iron
oxide 50Fe2O3-50MgO is much higher than measured by ICP (Figure 5.3B). The difference could be
related to the fact that ICP is a bulk-sensitive technique whereas EDX typically provides information
about a layer with a thickness in the order of 5 µm. Because the EDX spectrum was measured and
averaged over regions of 1x1 mm, this suggests that magnesia was to some extent encapsulated by
iron oxide. For all other samples, EDX and ICP results were very similar.
Figure 5.3 – EDX measured iron oxide content compared with expected (A) and ICP (B) iron oxide content for samples
promoted by alumina (S1-S4), magnesia-alumina (S5-S8) and magnesia (S9-S12) as well as the second series of
Fe2O3-MgAl2O4 (FMA1-FMA8). ICP-AES results for the latter (FMA1-FMA8) were not available. Fe2O3-MgAl2O4 (1)
correspond with S5-S8, Fe2O3-MgAl2O4 (2) correspond with FMA1-FMA8.
As was done for samples S1-S12, SEM images were made of the series of eight Fe2O3-MgAl2O4
samples (FMA1-FMA8). The result is depicted in Figure 5.4, clearly showing the sphericity of hematite
particles in pure synthetic hematite. For the sample containing 10w% of promoter material,
in addition to the spherical hematite particles also small MgAl2O4 particles are dispersed on the iron
oxide particles. Further increasing the content of MgAl2O4 decreases the iron oxide particle size while
the particle size of the promoter material increases. The morphology of 50Fe2O3-50MgAl2O4 suggests
that, with this composition, spherical iron oxide particles are dispersed on a dense matrix of support
material. Despite the gold coating applied in order to improve sample conductivity, it is difficult to
get clear images of samples containing more than 70w% MgAl2O4. The low conductivity of the latter
led to substantial charging of these samples and the images were quite hazy. A SEM-image of gold
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coating on a flat surface is included on the same scale as the other images to differentiate between
small MgAl2O4 and iron oxide agglomerates on one hand and the clusters of gold coating which have
a size in the order of 1 to 5 nm on the other hand. For samples with an iron oxide content lower
than 30w%, it is no longer evident to distinguish between some of the dispersed iron oxide
crystallites and the gold sputter coating.
As for the EDX measurements, samples FMA1-FMA8 correspond well with expectations (Figure 5.3).
Only the sample with desired iron oxide content of 80w% is found to deviate significantly from
expectations. Indeed, looking at the SEM images shows that samples with expected iron oxide
content of 80w% and 70w% exhibit a similar particle size and morphology as suggested by their
comparable composition. Comparing SEM images of MgAl2O4-promoted iron oxide from Figure 5.2
and Figure 5.4, indeed, a sample with true composition 80Fe2O3-20MgAl2O4 is missing in the second
series of MgAl2O4-promoted samples. Reproducibility of morphology in other samples is satisfactory.
Figure 5.4 – SEM images of fresh Fe2O3-MgAl2O4 samples (FMA1-FMA8) with various (expected) composition. Scale bar
for Au coating and samples represents 500 nm and 1 µm respectively.
Based on SEM images, particle size distributions (Figure 5.5) were made by measuring the
characteristic dimension of 400 particles for each sample. Of course, for pure synthetic hematite,
deconvolution into several contributions is unnecessary and a single normal distribution is found to
be suitable. For MgAl2O4-promoted iron oxide, the global particle size distribution is deconvoluted
into two contributions, each of which is modeled by a normal distribution. This model is used for
sake of simplicity. Also, measurements are sufficiently well described by this type of distribution to
obtain qualitative and semi-quantitative information about the distribution of crystallite sizes. For
small particle size (e.g. 50Fe2O3-50MgAl2O4), this normal distribution is found to be inadequate and
an asymmetrical normal distribution would probably be more adequate to account for the
asymptotical behavior at very low particle size. The reader is referred to Appendix D for a more
detailed description on how the results, shown in Figure 5.5, are obtained.
Of course, the results shown in Figure 5.5 need to be treated with care because small particles
(generally smaller than 10-15 nm) are difficult to observe in SEM and their contribution is possibly
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not fully taken into account. Furthermore, the use of a gold coating to enhance sample conductivity
limits the range of particle sizes to which this method may provide information. Nevertheless, when
maxima in the particle size distribution occur at particle sizes above the minimum threshold size of
detectability (e.g. 20 nm), this method is sufficient to provide quantitative information.
Also, as illustrated by the distribution for sample 50Fe2O3-50MgAl2O4 (Figure 5.5), the number of
counts for small particles in a SEM-image will always overrule that of large particles when particle
size differs in order of magnitude. This can be addressed easily by decreasing the magnification and
repeating the procedure when small particles are not observed.
Figure 5.5 – SEM particle size distribution (400 counts/sample) for MgAl2O4-promoted iron oxide (second series).
Blue dots represent the measured distribution. Solid blue lines represent the modeled particle size distribution
with normal distributed contributions in blue dashed lines. The number of counts in each interval is normalized.
By modeling the particle size distribution and assuming that MgAl2O4 remains the dispersed phase
(smaller crystallite size than hematite) below 50w% of magnesia-alumina, the average particle size
and standard deviation for Fe2O3 and MgAl2O4 are estimated. The results are shown in Figure 5.6.
Figure 5.6 – Average particle size and standard deviation of Fe2O3
and MgAl2O4 crystallites in MgAl2O4-promoted iron oxide based
on measuring characteristic dimensions in SEM images
(400 counts/sample).
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In compliance with the qualitative analysis of SEM images, iron oxide particle size decreases with
increasing amount of promoter material. As seen in Figure 5.4, samples 80Fe2O3-20MgAl2O4 and
70Fe2O3-30MgAl2O4 show a quite uniform distribution of particle sizes with a similar average particle
size in accordance with the comparable ratio of iron oxide to promoter material of these samples
found by EDX analysis. When the relative amount of promoter material reaches 50 w%, this
homogeneity disappears which corresponds with an increased particle size of MgAl2O4.
5.1.3. N2-B.E.T. analysis
The results of the N2-B.E.T. analysis are summarized in Figure 5.7. In compliance with the small
particles (cfr. SEM, Figure 5.2), iron oxide with alumina as promoter material shows the highest
specific surface area which increases approximately linear with promoter content. For the samples
with MgAl2O4 and MgO as promoter material, an analogous link with results from SEM (Figure 5.2)
can be made. The former, with its moderate iron oxide particle size, has an intermediate specific
surface area. The latter, which consisists of large particles, shows a rather limited specific surface
area. Furthermore, reproducibility of the results for Fe2O3-MgAl2O4 is quite good. When using
MgAl2O4 as promoter material, the trend between pure Fe2O3 and 30Fe2O3-70MgAl2O4 may be
approximated as linear. Further increasing the amount of promoter material results in a steep
increase in B.E.T.-SSA.
Figure 5.7 – N2-B.E.T. specific surface area of iron oxide based materials with
different promoter material and composition.
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5.1.4. XRD analysis
XRD analysis of alumina-promoted iron oxide shows, as expected, mainly the presence of hematite
(Fe2O3) characterized by 2θ-peaks at 24°, 33°, 36°, 41°, 50°, 55°, 58°, 63° and 65° (Figure 5.8).
Alumina, characterized by a broad signal between 2θ=64° and 2θ=70°, is observed once the iron
oxide content is 70w% or lower. This means that either small alumina particles or amorphous
alumina is formed.
Figure 5.8 – XRD-spectrum for fresh alumina-promoted Fe2O3 with various
compositions (w%).
For MgAl2O4-promoted iron oxide, the same characteristic peaks for hematite are observed as
described above for Fe2O3-Al2O3. Characteristic peaks of magnesia-alumina spinel with 2θ of 31°, 37°,
45°, 59° and 65° are observed (Figure 5.9A). Again, the signal of this phase is quite broad. This is most
likely due to inhomogeneities with respect to alumina and magnesia content leading to local
deviations from the supposed 2:1 Al2O3-MgO stoechiometry. Hence, the signal is broadened by
overlap of a multitude of XRD-signals with similar diffraction behavior. XRD results from the second
series of MgAl2O4-promoted iron oxide (Figure 5.9B) shows the same characteristic peaks. Note that
characteristic peaks of hematite are no longer observed when the iron oxide content is 30w% or
lower. This indicates that the particle size of Fe2O3 is strongly reduced making crystallites invisible in
XRD analysis. To summarize, from Figure 5.8 and Figure 5.9, it is clear that the fresh samples with
alumina and magnesia-alumina promoter show the expected compounds, namely hematite (Fe2O3)
with Al2O3 and MgAl2O4 respectively.
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Figure 5.9 – XRD-spectrum for fresh samples of the first (A) and second (B)
series of MgAl2O4-promoted Fe2O3 with various compositions (w%).
In magnesia-promoted iron oxide, MgO is not observed when iron oxide content is high (Figure 5.10).
Instead, a spinel form of iron and magnesia was formed. Below 30 w% magnesia, both hematite and
magnesioferrite are observed. When the promoter content is 30w% or higher, hematite is no longer
observed and all iron oxide is present as magnesioferrite. Characteristic 2θ-peaks for magnesioferrite
are 30°, 36°, 43°, 54°, 57° and 63°. Note that the XRD-fingerprint of magnesioferrite (MgFe2O4) is
close to that of magnetite (Fe3O4) given the similar spinel-structure of both phases. A similar pattern
is also observed for magnesia-alumina spinel, but a shift in 2θ position of 1° to higher diffraction
angles is observed.
Based on the molecular weight of Fe2O3 (160 g/mol) and MgO (40 g/mol), it is clear that the
stoechiometric composition for magnesioferrite is 80Fe2O3-20MgO (w%). With an excess of iron
oxide, all magnesia is expected to form magnesioferrite and hence an Fe2O3-MgFe2O4 system is
expected. With an excess of magnesia, all iron oxide is expected to be transformed into
magnesioferrite and the expected phases are MgFe2O4 and magnesia. Characteristic peaks for
periclase (MgO) are expected at diffraction angles 43° and 62° for samples containing excess
magnesia. Indeed, for 50Fe2O3-50MgO, the magnesioferrite signal at 43° and at 63° may overlap with
the diffraction signal of magnesia (Figure 5.10). Of course, in each of both limiting cases, it is likely
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that traces of the limiting phase (magnesia and iron oxide respectively) still occur as small crystallites
which are not observable in XRD.
Figure 5.10 – XRD-spectrum for fresh magnesia-promoted Fe2O3 with
various compositions (w%).
Using the Scherrer equation, the particle size of iron oxide in all fresh samples is estimated. The
results are shown in Figure 5.11A. In this figure, the error bars represent the standard deviation
when averaging the calculated characteristic dimension over several peaks. Table 5.1 gives an
overview of which characteristic peaks were included.
Table 5.1 – Overview of characteristic peaks (with respective diffraction angle and Miller indices) from which the
Scherrer particle dimension was calculated (see Figure 5.11). An average particle size and standard deviation, providing
insight with respect to crystallite sphericity, was calculated based on these peaks.
Phase (# peaks included)
Characteristic peaks included in estimation: 2θ (hkl)
Fe2O3 (7)
24° (210), 33° (104), 35° (110), 41° (113), 50° (024), 54° (116), 63° (440)
MgFe2O4 (4)
30° (220), 35° (311), 43° (400), 57° (511)
Fe2O3 (5)
33° (104), 35° (110), 41° (113), 50° (024), 54° (116)
Generally, it is clear that the crystallite size of iron oxide is smallest (28 nm) when using aluminum as
promoter material (Figure 5.11A). Note that the XRD-signal of alumina is very broad and noisy
(cfr. Figure 5.8). Because this may indicate small or amorphous phases, the large particles in the SEM
images shown in Figure 5.2 are possibly amorphous alumina. When alumina is present as large
particles, a high dispersity of iron oxide is possible. This is in line with the calculated XRD particle
dimensions which are found to be very small and invariant with increasing load of alumina.
As for the samples with MgAl2O4 as promoter material, correspondence between both series is
satisfying. Even though the first batch suggested an unexpected increase in iron oxide particle size
from 70Fe2O3-30MgAl2O4 to 50Fe2O3-50MgAl2O4, this was addressed by analyzing a second batch
which shows that the estimated crystallite size of iron oxide is approximately 53 nm in
50Fe2O3-MgAl2O4. At lower iron oxide content, the particle size can no longer be estimated based on
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XRD spectral data because the signal is too low and/or particle size is too small. Figure 5.11B
compares the crystallite size of the second series of MgAl2O4-promoted iron oxide as calculated using
the Scherrer equation with the results from the particle size distributions made based on SEM
images. Compared with the XRD particle dimensions, SEM particle size is systematically lower by
10 to 20 nm. As discussed previously, the fact that smaller particles generally have more counts in
SEM images may lead to a shift of the average particle size to smaller sizes. On the other hand, XRD
particle size does not account for particles that are below the detection threshold of XRD ( 3 nm).
Anyhow, the results of both methods are well in line with eachother qualitatively.
Figure 5.11 – (A) Crystallite particle size based on XRD data using Scherrer’s equation for iron oxide with different
promoter materials. Legend shows iron oxide phase with the number of XRD peaks over which the particle size was
averaged between brackets. Error bars represent the standard deviation on averaging the crystallite size over different
planes. (B) Crystallite particle size for MgAl2O4-promoted iron oxide (second series) for various compositions estimated
by XRD spectral data (cfr. part (A)) and SEM images.
As for magnesia-promoted iron oxide, because of the low signal of hematite when using magnesia as
promoter material and the overlap of some peaks with magnesioferrite, calculation of the crystallite
size may be inaccurate. The error bars in Figure 5.11A, assuming that the crystallite size is correct,
give an indication of particle sphericity. Hence, two possibilities exist: First, it is possible that the
crystallite size of magnesia-promoted hematite was inaccurately estimated for some planes because
of overlap with other peaks. Second, it is possible that hematite particles in magnesia-promoted iron
oxide increase in size and show significant deviations from sphericity. Judging from the particle size
of magnesioferrite and the absence of magnesia peaks in the XRD spectrum (Figure 5.10),
magnesioferrite crystallites are possibly dispersed on hematite agglomerates. SEM images (Figure
5.2) indicate that the calculated crystallite size is probably underestimated because of peak
broadening due to overlap. According to crystallite size calculations based on XRD, crystallites of
magnesioferrite are smaller than those of hematite. Hence, SEM images for samples with high iron
oxide content (Figure 5.2) probably show magnesioferrite dispersed on hematite. With decreasing
iron oxide content, magnesia possibly takes over this role of carrier for dispersed magnesioferrite.
The interested reader is referred to Appendix B for the powder diffraction patterns of phases
assigned in XRD and to Appendix C for the methodology that was used for estimating crystallite
dimensions based on Scherrer’s equation.
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5.1.5. STEM-EDX analysis
To investigate structure of small iron oxide particles occurring in samples with a high content of
promoter material, STEM-EDX analysis is performed. Figure 5.12 gives an overview of the results
obtained for MgAl2O4-promoted iron oxide with different compositions.
From the results for 50Fe2O3-50MgAl2O4
(sample S8, Figure 5.12A), iron oxide
particles are clearly distinguished in zones
which are white in the iron (Fe K)
elemental map and dark zones in the
elemental map representing the local
aluminum (Al K) and magnesium (Mg K)
content. The iron oxide particle size in this
image is in the order of 50 nm which
complies with previously found estimates
based on SEM and XRD.
Results for both 30Fe2O3-70MgAl2O4
(sample FMA6) and 10Fe2O3-90MgAl2O4
(sample FMA8) are shown in Figure 5.12B
and Figure 5.12C respectively. In both of
these materials, iron oxide is found to be
highly dispersed on MgAl2O4. This
corresponds with the results from XRD,
where iron oxide was not observed.
Indeed, these results show that iron oxide
occurs as nanoparticles when MgAl2O4
promoter content is 70w% or higher.
As for magnesium and aluminum, it is
clear that a high homogeneity is obtained
for these three investigated samples.
Figure 5.12 – STEM images of fresh 50Fe2O3-50MgAl2O4 (A),
30Fe2O3-70MgAl2O4 (B) and 10Fe2O3-90MgAl2O4 (C). The inset shows
EDX elemental mapping of Fe, Mg and Al for each of these samples.
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5.1.6. Temperature-Programmed Reduction by H2
Figure 5.13 gives an overview of
in-situ XRD H2-TPR of samples
containing 70w% iron oxide
promoted by Al2O3, MgAl2O4 and
MgO. Samples promoted by
alumina (Figure 5.13A) and
magnesia-alumina (Figure 5.13B)
show similar behavior for reduction
of hematite (2θ at 41°, 50°, 55°,
58°, cfr. section 5.1.4) to magnetite
(2θ at 43°, 54°, 57°). However,
reduction of magnetite to wuestite
(2θ=42°) is significantly impaired in
Al2O3-promoted
iron
oxide
compared with the MgAl2O4promoted sample. In the former,
hematite is fully reduced to
magnetite around 500°C and
further reduction to wuestite and
metallic iron (2θ at 45°) occurs
simultaneously above 700°C. For
MgAl2O4-promoted iron oxide, the
onset of magnetite reduction
occurs at 600°C while reduction of
wuestite starts at 650°C. Also, the
intensity of both the wuestite and
metallic iron phase seems to be
much higher for MgAl2O4-promoted
iron oxide compared with Al2O3promoted iron oxide.
For magnesia-promoted iron oxide,
reduction to metallic iron is
Figure 5.13 – In-situ XRD H2-TPR between RT and 800°C for samples
containing 70w% Fe2O3 with 30w% Al2O3 (A), MgAl2O4 (B) and MgO (C)
possible at temperatures above
promoter material. Gas flow: 60 ml/min H2 (5% in Ar). Heating rate:
600°C even though XRD results
ß=30K/min.
(Figure 5.10) show that iron oxide is
present under the form of a magnesioferrite spinel. Figure 5.13C shows that MgFe2O4 is reduced to
(MgO)x(FeO)1-x (2θ=42-43°) between 500°C and 750°C, where x is a number between 0 and 1
indicating that the composition of this phase is generally not uniform throughout the sample
material. Between 600°C and 800°C, further reduction to metallic iron occurs and a peak of magnesia
is observed at 2θ=42°.
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Figure 5.14 shows the results of H2-TPR experiments performed in a quartz-tube reactor setup
coupled to a thermal conductivity detector (TCD). For pure synthetic hematite, the three expected
contributions in hydrogen consumption are easily distinguished at 440°C, 640°C and 740°C. This
corresponds with the reduction of hematite, magnetite and wuestite respectively. Also, at 850°C,
reduction to metallic iron is found to be incomplete.
Figure 5.14 – H2-TPR for MgAl2O4 promoted iron oxide with different
compositions by use of a TCD. Gas flow: 60 ml/min hydrogen (5% in Ar).
Heating rate: ß=20K/min.
When adding MgAl2O4 as promoter material, the temperature at which hematite is reduced
decreases to 400°C. The maximum hydrogen consumption corresponding to magnetite and wuesite
reduction are no longer separated because reduction of magnetite to wuestite seems to shift
towards higher temperatures. On the other hand, reduction to metallic iron is found to be near
completion at 850°C for samples containing 10w% or 20w% promoter material. Further increasing
the promoter content results in a shift of hematite reduction back to 440°C for sample
50Fe2O3-50MgAl2O4, while in this sample, the magnetite reduction contribution is shifted down to
lower temperature. Besides the lower hydrogen consumption due to the lower iron oxide content,
the behavior of this sample is similar to that of pure hematite.
By further increasing the amount of promoter material to 70w% MgAl2O4, reduction of hematite is
again shifted to lower temperatures after which it increases with decreasing iron oxide content.
For these samples, reduction to metallic iron requires a higher temperature than for samples
containing more iron oxide.
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5.1.7. Temperature-Programmed Oxidation by CO2
Analogously as for in-situ XRD
H2-TPR shown in section 5.1.6,
page 51, a 2D map for
in-situ XRD CO2-TPO of samples
with a different promoter
material is shown in Figure 5.15.
The same samples that were
reduced by hydrogen, were
reoxidized by carbon dioxide.
When oxidizing metallic iron
using CO2 as oxidizing agent,
hematite is not formed. The
highest oxidation state of iron
that is reached corresponds with
magnetite.
During oxidation of metallic iron
promoted by alumina (Figure
5.15A) or magnesia-alumina
(Figure 5.15B), wuestite is
generally not observed. This
suggests that wuestite either
occurs as reactive intermediate
between metallic iron and
magnetite, either it is not formed
at all. For alumina-promoted iron
oxide, it is clear that a
contribution of FeAl2O4 is
present at 2θ=58°. Oxidation of
metallic iron to magnetite
(2θ=56-57°) combined with the
spinel signal results in a broad
signal between 2θ=56°-58°.
Oxidation of metallic iron to
magnetite by CO2 for these two Figure 5.15 – In-situ XRD CO2-TPO between RT and 800°C for samples
samples occurs between 250 and containing 70w% Fe2O3 with 30w% Al2O3 (A), MgAl2O4 (B) and MgO (C)
promoter material. Gas flow: 60 ml/min CO2 (100%). Heating rate: ß=30°C/min.
600°C.
After reduction of magnesia-promoted iron oxide, reoxidation by CO2 is found to require
temperatures above 500°C (Figure 5.15C). However, oxidation of magnesia-promoted iron is clearly
incomplete at temperatures below 800°C. The intermediate (MgO)x(FeO)1-x is observed up to
temperatures as high as 800°C. The onset of further oxidation to magnesioferrite, lies around 750°C.
Even at the end of the experiment, the intensity of this phase is fairly low.
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To get a better view on the effect of MgAl2O4 promoter content on the oxidation of iron after H2-TPR,
CO2-TPO experiments were performed on a series of MgAl2O4-promoted iron oxide with various
compositions (sample FMA1, S5-S8 and FMA6-FMA8). The results are shown in Figure 5.16. After
reduction of pure hematite, oxidation appears to occur in two steps. The first step, starting around
400°C, most likely corresponds with oxidation of iron at the particle surface. As seen in Figure 5.15,
wuestite is generally not observed as intermediate and a single-step oxidation from metallic iron to
magnetite is assumed. The second step during reoxidation of unpromoted iron requires higher
temperatures to allow for diffusion of lattice oxygen and iron to the inside and outside of the particle
respectively. At temperatures as high as 750°C, reoxidation of the material containing only iron
remains incomplete. Hence, with increasing promoter content, the general trend is that reoxidation
by CO2 occurs at lower temperatures and in shorter temperature ranges due to a decrease in iron
oxide particle size. In compliance with the evolution of particle sizes found in SEM and XRD, the
largest differences occur in the transition from pure hematite to 90Fe2O3-10MgAl2O4 and from
50Fe2O3-50MgAl2O4 to 30Fe2O3-70MgAl2O4. The samples with the lowest iron oxide content are fully
oxidized to magnetite in the range of 300 to 500°C.
Figure 5.16 – CO2-TPO for MgAl2O4 promoted iron oxide with different
compositions using a TCD. Gas flow: 60 ml/min carbon dioxide (20% in He).
Heating rate: ß=20°C/min.
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5.2. Stability of iron oxide based oxygen carrier materials
5.2.1. In-situ XRD isothermal redox cycles
As a means for testing stability as oxygen carrier material, several samples were subjected to 5
subsequent in-situ XRD redox cycles. In general, one redox cycle is composed of reduction by H2,
followed by purging/stabilizing under helium, oxidation by CO2 and again purging/stabilizing under
helium (Figure 5.17).
Figure 5.17 – Schematic representation of one isothermal redox cycle. Hydrogen is diluted
in argon. In each region, the total gas flow is 60 ml/min.
The results for 50% Fe2O3 and Al2O3, MgAl2O4 and MgO as promoter are shown in Figure 5.18, Figure
5.19 and Figure 5.20 respectively. The discussion focuses on the samples with the highest content of
promoter material because these materials are expected to show the highest stability.
5.2.1.1. Iron oxide promoted by alumina
When using alumina as promoter material (Figure 5.18), the reduction of hematite to metallic iron
(2θ=45°, intense peak expected) in the first cycle is incomplete, i.e. magnetite is present in large
amounts. Also, part of the iron oxide is deactivated by alumina, forming phases such as FeAl2O4,
(FeO)x(Al2O3)1-x, etc. This variety of deactivation compounds, which may locally differ in composition,
leads to a broad band in the XRD spectrum between 2θ=58° and 2θ=60°.
Figure 5.18 – In-situ XRD isothermal redox cycles at 750°C for sample S4 (50Fe2O3-50Al2O3). Each cycle
(16 min) is composed of 4 min H2 (5% in Ar), 4 min He, 4 min CO2 (100%) and 4 min He. Flow rate is 60 ml/min.
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From the second cycle onwards, the signal of metallic iron is very weak, indicating that only trace
amounts of metallic iron are formed upon treatment with H2 at 750°C. Hence, the redox cycle
probably occurs between magnetite and wuestite. It is concluded that, for this application
(high-temperature redox cycles), aluminum oxide is not a suitable promoter material.
5.2.1.2. Iron oxide promoted by magnesia-alumina spinel
In order to address the deactivation of iron oxide when using aluminum oxide as promoter material,
a different promoter material is suggested. Previously, it was stated that deactivation with alumina
occurs through formation of an inert FeAl2O4 spinel. Hence, addition of a promoter material that
would form a more stable spinel with alumina than iron oxide may prevent loss of iron oxide activity.
Therefore, magnesium oxide was added to the initial mixture in a stoichiometric ratio with respect to
alumina for formation of MgAl2O4. This compound is known to show a high thermal stability and is
widely used as catalyst carrier material [54, 55]. The results of the in-situ isothermal redox cycles are
shown in Figure 5.19. Even though the intensity of metallic iron (2θ=45°) decreases in subsequent
cycles, a broader range in reduction-oxidation state is obtained compared with the aluminapromoted iron oxide. In each cycle, all magnetite (2θ=57°) is reduced into a mixture of wuestite
(2θ=42°) and metallic iron (2θ=45°). Because of the intrinsic high intensity of the metallic iron peak at
2θ=45°, the true amount of metallic iron that is formed may be limited. The residual signal around
2θ=45°, observed in oxidation steps, as well as the band at 2θ=59° are characteristic for MgAl2O4.
Figure 5.19 – In-situ XRD isothermal redox cycles at 750°C for sample S8 (50Fe2O3-50MgAl2O4). Each cycle
(16 min) is composed of 4 min H2 (5% in Ar), 4 min He, 4 min CO2 (100%) and 4 min He. Flow rate is 60 ml/min.
Note that magnetite is not observed during the initial reduction of hematite because the reduction
rate of hematite is high at 750°C.
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5.2.1.3. Iron oxide promoted by magnesia
Figure 5.20 shows the in-situ XRD stability test for magnesia-promoted iron oxide. From the
XRD-analysis in section 5.1.4, page 46, it was found that hematite was not present in the fresh
sample. Instead, all iron oxide was found to be present under the form of MgFe2O4 spinel. Upon
cyclic reduction-oxidation cycles, reduction to metallic iron is only significantly observed in the first
cycle. More specifically, upon reduction in the first cycle, (FeO)x(MgO)1-x is decomposed into metallic
iron and magnesia. In the cycles that follow, reduction and oxidation state of iron mainly alternates
between Fe(III) and Fe(II), i.e. MgFe2O4 and (FeO)x(MgO)1-x. Note that, given the onset temperature
(750°C for sample 70Fe2O3-30MgO, cfr. CO2-TPO Figure 5.15, page 53) for formation MgFe2O4 during
oxidation by CO2, the intensity of this signal is quite low.
Figure 5.20 – In-situ XRD isothermal redox cycles at 750°C for sample S12 (50Fe2O3-50MgO). Each cycle
(16 min) is composed of 4 min H2 (5% in Ar), 4 min He, 4 min CO2 (100%) and 4 min He. Flow rate is 60 ml/min.
5.2.2. Micromeritics isothermal redox cycles
To assess material stability upon isothermal redox cycles from a different angle, stability tests were
performed in a Micromeritics setup where reagents and products in the reactor effluent were
monitored by means of a mass spectrometer. In this case, the focus lies on the gas phase (feed
versus product flow composition) rather than the solid phase. Figure 5.21 shows the results for the
same materials as investigated by in-situ XRD (cfr. section 5.2.1). From the shape of these results,
two regions occur upon reduction. First, a region of rapid hydrogen consumption appears,
corresponding with reduction at the particle surface. After this region, reduction is probably limited
by lattice oxygen diffusion. As opposed to the 2-region reduction of iron oxide, it is apparent that
subsequent reoxidation to magnetite is completed in 4 minutes under these conditions for all
samples. This corresponds with the relatively low temperature needed to oxidize metallic iron to
magnetite (cfr. Figure 5.16), particularly when the particle size of iron is small.
57
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The reproducibility for samples containing 50w% iron oxide promoted by MgAl2O4 is found to be
satisfactory. The initial difference between both samples may be explained by the fact that the
sample of the first series was pretreated by H2-TPR and CO2-TPO at temperatures up to 850°C.
This thermal pretreatment may have resulted in cracking of large particles, due to which the initial
reduction occurs more rapidly.
Figure 5.21 – CO and H2 signal for all samples with 50w% Fe2O3 and 50w% promoter material (S4, S8,
S12 and FMA5) when subjected to isothermal redox cycles at 750°C. Each cycle (16 min) is composed of
4 min H2 (5% in Ar), 4 min He, 4 min CO2 (100%) and 4 min He. Flow rate is 60 ml/min.
Using alumina as promoter material, the integrated hydrogen consumption is significantly lower.
For alumina-promoted iron oxide, the integrated hydrogen consumption mainly decreases in the first
two cycles, after which it stabilizes. The results for magnesia-promoted iron oxide are similar with a
more pronounced deactivation and a lower integrated hydrogen consumption. Particularly, the
negligible formation of CO upon re-oxidation is striking. As observed in Figure 5.20 (section 5.2.1.3),
a net reduction of MgFe2O4 to (FeO)x(MgO)1-x possibly occurs upon cycling. As seen from in-situ XRD
CO2-TPO as well as redox cycles, this phase is stable under carbon dioxide atmosphere up to
temperatures around 750°C.
Note that the relative intensity of the initial sharp peak in hydrogen consumption of different
samples corresponds with expectations based on their particle size. Because fresh alumina-promoted
iron oxide has the smallest particles, the surface contribution in hydrogen consumption is the highest
among these samples. The opposite is true for magnesia-promoted iron oxide. Using MgAl2O4
promoter, an intermediate particle size was obtained corresponding with the relative intensity of the
surface contribution in hydrogen consumption during the first cycles.
The absolute amount of hydrogen consumed in each cycle can be estimated since the hydrogen flow
rate as well as mass spectrometer background signal for hydrogen is known. Also, the amount of
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sample is known. Hence, using the EDX-calculated composition, the theoretical amount of reducible
oxygen present in all samples is known. Assuming that hydrogen is only consumed by reduction of
iron oxide with formation of water vapor, the conversion of iron oxide lattice oxygen is calculated for
each cycle (cfr. Figure 5.22). The formula for the oxygen conversion XO is shown below (Eq. 5.1).
[
]
Eq. 5.1
As observed in Figure 5.21, the oxygen conversion after the first cycle decreases significantly for both
alumina and magnesia-promoted iron oxide (50-50 w%). In subsequent cycles, XO stabilizes at 19%
and 7% respectively. Even though the oxygen conversion of alumina and magnesia-alumina
promoted iron oxide are similar in the first cycle, the latter is less prone to deactivation and its
oxygen conversion remains stable at 38% over several cycles. Samples containing less than 50w%
iron oxide are expected to reach a higher oxygen conversion because of the decreased iron oxide
particle size. However, results from H2-TPR (Figure 5.14) suggests that the reduction temperature for
transition of wuestite to metallic iron increases when the MgAl2O4 promoter content exceeds 50w%.
Hence, it is clear that the exact relation between iron oxide content and XO is not evident. It is found
that the initial oxygen conversion is highest (stable at 48%) for 10Fe2O3-90MgAl2O4. When iron oxide
content is 20w%, XO is stable at 38%. Note that this is very similar to the sample containing 50w%
iron oxide. Finally, for 30w% iron oxide, XO is stable at 35%. For magnesia-alumina promoted iron
oxide with promoter content below 50w%, activity decreases rapidly with increasing number of
redox cycles. This suggests that the particle size of structural promoter for these samples is not large
enough to avoid iron oxide particles from sintering.
Figure 5.22 – Estimated oxygen conversion XO over several redox cycles (750°C) for alumina, magnesia-alumina and
magnesia-promoted iron oxide samples (S4, S5-S8, FMA6-FMA8 and S12) based on hydrogen consumption. Each
cycle (16 min) is composed of 4 min H2 (5% in Ar), 4 min He, 4 min CO2 (100%) and 4 min He. Flow rate is 60 ml/min.
59
Chapter 5
CO2 Utilization
As described in section 2.3.2, the oxygen storage capacity RO of a material is defined as the amount
of oxygen released during reduction with respect to the total sample mass in its oxidized form (Eq.
5.2). Hence, RO is a measure for the amount of material needed to deliver a certain amount of oxygen
to a reducing agent. Because one mole of hydrogen consumed corresponds with removal of one
oxygen atom, this oxygen storage capacity can be estimated based on the integrated hydrogen
consumption.
[
]
Eq. 5.2
The results for the oxygen conversion shown in Figure 5.22 are transformed into oxygen storage
capacity and shown in Figure 5.23. First of all, the higher the amount of inert promoter, the higher
the amount of oxygen carrier needed to reach a certain amount of oxygen delivery. However, this is
only valid if the conversion of these materials with different iron oxide content is similar. Due to the
rapid decrease in conversion of materials containing less than 50w% of promoter material,
the oxygen storage capacity of these materials under the given conditions rapidly decays. After 10
cycles, the amount of oxygen delivered per unit mass of 90Fe2O3-10MgAl2O4 is less than that of
30Fe2O3-70MgAl2O4 even though the former contains 3 times as much of the active iron oxide phase.
Figure 5.23 – Estimated oxygen storage capacity RO over several redox cycles (750°C) for samples of iron oxide
promoted by alumina, magnesia-alumina and magnesia (S4, S5-S8, FMA6-FMA8 and S12) based on hydrogen
consumption. Each cycle (16 min) is composed of 4 min H2 (5% in Ar), 4 min He, 4 min CO2 (100%) and
4 min He. Flow rate is 60 ml/min.
The most effective material after 10 cycles per unit mass of promoted oxygen carrier is sample
50Fe2O3-50MgAl2O4. Note that, because the oxygen storage capacity was based on hydrogen
60
Chapter 5
CO2 Utilization
consumption, the oxygen storage capacity of magnesia-promoted iron oxide is largely overestimated.
In reality, hydrogen is consumed but re-oxidation does not occur so that under these conditions, this
sample hardly acts as oxygen carrier material in the sense as required in a chemical looping process.
On the assumption that hydrogen consumption results in reduction of only iron oxide and that full
reoxidation to magnetite occurs in each cycle, hydrogen consumption during reduction is related to
carbon monoxide production. Consumption of H2 and formation of CO are related in the sense that
these molecules respectively consume and provide one oxygen atom. Hence, the molar amount of
hydrogen consumption corresponds with the molar amount of carbon monoxide production. The
results with respect to the iron content are shown in Figure 5.24. Naturally, these results correspond
with the oxygen conversion results from a qualitative point of view. It is found that, after 10 cycles,
10Fe2O3-90MgAl2O4 shows the highest activity (0.65 mole CO/mole Fe) per unit mass of iron. This is a
similar result as found in literature [46]. MgAl2O4-promoted iron oxide with a promoter content
between 50w% and 80w% show a similar activity (0.45 to 0.5 mole CO/mole Fe). When the promoter
content is lower, the activity quickly decays. Finally, for alumina-promoted iron oxide, the activity
decreases from 0.65 mole CO/mole Fe to 0.25 mole CO/mole Fe during the first 5 cycles.
Figure 5.24 – Estimated activity for CO2 utilization (mole CO formed during each cycle per mole of iron
present) over several redox cycles (750°C) for alumina and magnesia-alumina iron oxide samples (S4, S5-S8,
FMA6-FMA8) based on hydrogen consumption. Each cycle (16 min) is composed of 4 min H2 (5% in Ar), 4 min
He, 4 min CO2 (100%) and 4 min He. Flow rate is 60 ml/min. magnesia-promoted iron oxide was omitted due
to the lack of correspondence between H2 consumption during reduction and CO formation during oxidation.
After this broad screening of materials, the scope was reduced to samples 50Fe2O3-50MgAl2O4 and
10Fe2O3-90MgAl2O4 being the oxygen carrier materials with respectively the highest oxygen storage
capacity and oxygen conversion after 10 redox cycles. The results of 25 redox cycles using
50Fe2O3-50MgAl2O4 as oxygen carrier material are shown in Figure 5.25.
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Chapter 5
CO2 Utilization
Figure 5.25 – Overview of H2 consumption and CO formation during 25 isothermal redox cycles at
750°C using 50Fe2O3-50MgAl2O4 (S8) as oxygen carrier material. Each cycle (16 min) is composed of
4 min H2 (5% in Ar), 4 min He, 4 min CO2 (100%) and 4 min He. Flow rate is 60 ml/min.
From these results, it is clear that deactivation does occur. The high hydrogen consumption observed
during first reduction is due to the presence of hematite in the fresh sample. The strongest
deactivation starts after 2 to 3 hours of operation.
Figure 5.26 shows the results of 60 isothermal redox cycles using 10Fe2O3-90MgAl2O4 as oxygen
carrier material.
Figure 5.26 – Overview of H2 consumption and CO formation during 60 isothermal redox cycles at
750°C using 10Fe2O3-90MgAl2O4 (FMA8) as oxygen carrier material. Each cycle (16 min) is composed
of 4 min H2 (5% in Ar), 4 min He, 4 min CO2 (100%) and 4 min He. Flow rate is 60 ml/min.
As for hydrogen consumption, this material is definitely stable over the whole length of the
experiment (17 hours). With respect to the formation of CO, despite some oscillations, the results
seem quite stable. The reason for these oscillations remains unclear. First of all, repeating this
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CO2 Utilization
experiment with an increased amount of sample material may give a view on whether the reason is
related to the detector sensitivity or whether it is process-related.
Generally, it is concluded that the content of MgAl2O4 should definitely be higher than 50w% to
obtain structural stability. The sample containing 90w% of promoter material remains stable for
17 hours under operating conditions.
5.2.3. SEM-EDX study
Next, a SEM-EDX study of some of the used samples discussed in sections 5.2.1 and 5.2.2 was
performed. Figure 5.27 shows SEM images of these materials after 5 or 10 redox cycles at 750°C.
Figure 5.27 – SEM images of fresh and used samples indicating the effect of cyclic reduction and oxidation of iron oxide
and of different promoter materials on morphology.
For 50w% iron oxide with alumina, magnesia-alumina and magnesia promoter, morphology of fresh
and spent oxygen carrier material is quite similar. This shows that the loss of activity in
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CO2 Utilization
alumina-promoted iron oxide is not related to sintering but more likely to incorporation of alumina in
iron oxide or vice versa, leading to a stable phase at process conditions. For magnesia-promoted iron
oxide, particle growth even after as few as 5 redox cycles is clearly observed. In a more global
overview, it is clear that the material surface is covered by large crystallites which are all connected
and reduce material porosity significantly. It is possibly due to this severe sintering that reoxidation
of this material remains incomplete.
When studying the effect of promoter content in the MgAl2O4-promoted iron oxide series, the reason
for the findings in section 5.2.2 with respect to activity decay is clearly illustrated. In
90Fe2O3-10MgAl2O4 and 70Fe2O3-30MgAl2O4, two types of regions occur. Part of the material remains
its initial morphology quite well, whereas other regions exhibit immense particle growth compared
with fresh material. In the large crystalline structures of spent 70Fe2O3-30MgAl2O4, terraces are
clearly observed. Again, zooming out shows the presence of different regions at the particle surface.
Curiously, EDX-analysis of these large crystallite regions was not possible and only iron was detected.
This may possibly be due to magnetic properties of iron in magnetite, which could cause virtually all
primary electrons to interact with iron.
Next, the sample of spent 50Fe2O3-50MgAl2O4 after 25 redox cycles was investigated by SEM-EDX
(Figure 5.28). The features that were observed (Figure 5.27) for iron oxide with MgAl2O4-promoter
content lower than 50w% are found in this material as well. Regions of very large crystallites showing
steps and terraces are alternated with regions where smaller particles occur.
Figure 5.28 – SEM-EDX study of 50Fe2O3-50MgAl2O4 after 25 isothermal redox cycles at 750°C. The inset shows
EDX composition charts where the emphasis lies on iron, magnesium and aluminum. Besides these elements,
gold (coating), carbon (tape) and oxygen are observed. At% denotes the atomic/molar percentage.
64
Chapter 5
CO2 Utilization
Unlike for previously discussed samples, EDX-analysis was possible for this material.
Crystalline regions clearly show a much lower content of magnesia and alumina. The reason why only
the aluminum and magnesium content are so different and whether this is coincidal or not is unclear.
Fact is that, in regions where the local composition of magnesia and alumina is relatively high,
particles sinter less fast because of the presence of this structural promoter material. This illustrates
the importance of homogeneity for obtaining an optimal material activity. The occurring process
leading to the decay in activity of 50Fe2O3-50MgAl2O4 during 25 redox cycles is illustrated quite well
by these images.
Finally, SEM images of the spent sample of 10Fe2O3-90MgAl2O4 after 60 isothermal redox cycles were
made (Figure 5.29). Again, two types of regions are distinguished based on morphology: Regions with
high porosity are alternated with regions which seem quite flat and less porous. From EDX however,
atomic composition of these regions was found to differ by less than 1%.
Furthermore, EDX-composition at the highest achievable resolution is equal to the average EDXcomposition of fresh sample material. Generally, material morphology in fresh and spent sample is
quite similar. Some particle growth may have occurred. Nevertheless, it is not always evident to get a
clear image at this scale. Because hematite is less conductive than magnetite, the image quality of
fresh sample is often poorer due to charging of strong insulators such as hematite and MgAl2O4.
Figure 5.29 – SEM images of 10Fe2O3-90MgAl2O4 after 60 isothermal redox cycles at 750°C compared with fresh sample
material. Two regions with a slightly different morphology are magnified.
65
Chapter 6 Kinetic modeling
In this Chapter, the activation energy for reduction by hydrogen and re-oxidation by carbon dioxide
of iron oxide based materials is determined based on in-situ XRD H2-TPR and CO2-TPO experiments.
Based on the conducted experiments it was observed that MgAl2O4-promoted iron oxide is the most
promising oxygen carrier among the investigated materials. Hence the focus lies on iron oxide
promoted by MgAl2O4. More specifically, materials which were expected to show the highest
difference in behavior were investigated. Therefore, reduction/oxidation behavior of samples
90Fe2O3-10MgAl2O4 (S5) and 50Fe2O3-50MgAl2O4 (S8), described in Chapter 5, was modeled.
Section 6.1 discusses H2-TPR modeling whereas in section 6.2, the focus lies on CO2-TPO. Both of
these sections are divided in a part on model description, parameter estimation and model
validation. Validation of the model generally consists of investigating whether the modeled
activation energy describes the process well when experimental data is obtained using a different
setup (e.g. Micromeritics setup instead of in-situ XRD). For an overview of the model simulations
incorporated in this Chapter, the reader is reffered to Appendix A.
6.1. Temperature-Programmed Reduction of iron oxide
6.1.1. Model description
Reduction of hematite (Fe2O3) to metallic iron (Fe) by hydrogen is assumed to be a three-step
process as given in Table 6.1. Rate coefficients k are determined such that the stoichiometry of the
reactant for each respective reaction (Fe2O3, Fe3O4 and FeO) is equal to 1.
Note that the model is based on following assumptions:
•
•
•
Under conditions of H2-TPR, the reduction of iron oxide occurs via three subsequent
irreversible reactions which are first order in the respective iron oxide phase. Water vapor
accumulation is assumed to be negligible.
Partial pressure of hydrogen is assumed to be uniform, and hence no gas phase diffusion
limitations occur for hydrogen. This also implies the assumption that reduction is limited
by lattice oxygen diffusion. As for the model, the partial pressure of hydrogen as well as its
partial reaction order m are lumped into the pre-exponential factor under the assumption
that this contribution remains constant.
No heat transfer limitations: Sample temperature is controlled by the imposed
temperature-program.
The linear temperature program with heating rate β is introduced by an additional ordinary
differential equation (ODE) (Table 6.1).
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Chapter 6
Kinetic modeling
Because experimental data from in-situ XRD H2-TPR are used for modeling purpose, following
assumptions were made for converting the in-situ XRD spectra into a useful experimental dataset:



A suitable background 2θ-range is available as reference for temperature dependence of
XRD-signal intensities. This means that over the line of the experiment, no activity occurs
in this region.
Characteristic peaks do not overlap with other peaks corresponding with another active
species. If this assumption is valid, the change in relative intensity is due to activity of the
considered species.
The change in XRD-intensity of a characteristic peak is assumed to be proportional with the
change in molar amount of respective species (Eq. 6.1) where the asterisk represents a
dimensionless molar amount. In particular, all molar amounts are normalized with respect
to the initial amount of hematite.
Eq. 6.1

At the start of the H2-TPR experiment, hematite is the only phase that is present. After the
experiment, only metallic iron remains.
The assumptions made and procedures followed during post-processing of in-situ XRD experimental
data are discussed in Appendix F.
Table 6.1 – Overview of reactions, reaction rate equations and reaction rate coefficients in the proposed model for
H2-TPR of iron oxide.
Reaction
Reaction rate
Rate coefficient
Temperature-Program:
For solving the set of ODE’s shown in Table 6.1, the software package Athena Visual Studio (AVS®)
was used. The reader is referred to Appendix G for the code that was implemented in AVS®.
67
Chapter 6
Kinetic modeling
6.1.2. Estimation of kinetic parameters
The model results for sample 50Fe2O3-50MgAl2O4 are shown graphically in Figure 6.1. For each phase
(hematite, magnetite, wuestite and metallic iron), the experimental and modeled dimensionless
amount is plotted as a function of temperature. The experiment at heating rate 30°C/min was found
to lead to a higher deviation of the model with respect to experimental data obtained at lower
heating rates. Because the quality of the data at lower heating rates is expected to be more accurate,
the experimental data at heating rate 30°C/min was omitted. In general, it can be concluded that the
maximum rate temperature corresponds quite well between model and experimental data. As
expected, the only large deviation lies in the reduction of hematite to magnetite at 30°C/min.
Figure 6.1 – Experimental data (dots) obtained from in-situ XRD H2-TPR of 50Fe2O3-50MgAl2O4 (S8) compared with
modeled data (lines). Only data with β=5, 10, 15 and 20°C/min were used for estimating kinetic parameters.
Experimental data for β=30°C/min are included in the graph with predicted values using the obtained kinetic parameters.
The model results for sample 90Fe2O3-10MgAl2O4 with respect to the dimensionless amount of
hematite, magnetite, wuestite and metallic iron are shown in Figure 6.2.
Compared with 50Fe2O3-50MgAl2O4, deviations are found to be more significant. In this case, the
poor accuracy of wuestite experimental data is clearly illustrated. Therefore, experimental data for
wuestite was omitted for estimating the parameters. Nevertheless, the obtained model was also
compared with this data. Again, deviations are largest at high heating rates, which is why
experimental data of the experiment at 30°C/min were not used for parameter estimation.
Also, according to the model, the assumption of full reduction to iron at 800°C is not fulfilled at high
heating rate.
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Chapter 6
Kinetic modeling
Figure 6.2 – Experimental data (dots) obtained from in-situ XRD H2-TPR of 90Fe2O3-10MgAl2O4 (S5) compared with
modeled data (lines). Only data with β=5, 10 and 20°C/min were used for estimating kinetic parameters. Experimental
data for β=30°C/min are included in the graph with predicted values using the obtained kinetic parameters.
The estimates for the 6 model parameters (pre-exponential factor and activation energy for each
reduction step) are summarized in Table 6.2.
Table 6.2 – Parameter estimates by regression of experimental data with H2-TPR model equations using
Athena Visual Studio (AVS®).
Reaction
Parameter
50Fe2O3-50MgAl2O4
90Fe2O3-10MgAl2O4
No statistical information provided by AVS®
For 90Fe2O3-10MgAl2O4, it is found that the activation energy decreases from 107.9 kJ/mol to
76.7 kJ/mol and 59.3 kJ/mol for reduction of hematite to magnetite, magnetite to wuestite and
wuestite to metallic iron respectively. As for 50Fe2O3-50MgAl2O4, estimates for the activation energy
are 104.3 kJ/mol, 70.7 kJ/mol and 78.4 kJ/mol for subsequent reduction steps. In this case, the
activation energy for the reduction of wuestite is found to be higher than for reduction of magnetite.
69
Chapter 6
Kinetic modeling
Comparing the results obtained for both compositions, it is found that a minor difference occurs in
the activation energy for reduction of hematite to magnetite and magnetite to wuestite in both
materials.
It was found that the Arrhenius parameters of reduction step 2 and 3 showed some correlation.
A possible solution lies in reparametrization with respect to an intermittent temperature.
Nevertheless, the obtained results correspond quite well with the literature survey performed by
Pineau et al. (Table 6.3).
Table 6.3 – Summary of bibliographic survey on the activation energy for reduction of iron oxide with hydrogen [49, 50].
Reduction step
Type of material
Ea (kJ/mol)
Fe2O3 (natural/pure)
89.1-246.0
Fe2O3 (+Al2O3)
107.8
Fe2O3 (+MgO)
109.9
Fe3O4 (natural/pure)
60.6-86.0*
Fe3O4 (promoted)
46.0-117.7
* Excluding 1 out of 12 studies which reported an activation energy of 13.4 kJ/mol
6.1.3. Model validation
A first method for investigation of the model validity is by examining its adequacy to describe the
same process in a different setup. Different experimental setups are expected to give rise to different
reaction behavior and hence, reproducibility will give an indication on the validity of the model
assumptions. Hence, the model is applied to describe data from regular TPR measurements. The
activation energy is obtained from in-situ XRD H2-TPR modeling, whereas the pre-exponential factor
is re-estimated. This is necessary because dimensionless activities were used for the model based on
in-situ XRD. The result is shown in Figure 6.3 for the same two materials that were studied in
previous section.
Apart from the reduction of wuestite to metallic iron in sample 90Fe2O3-MgAl2O4, the model is in
compliance with the measured signal. The reason for the lack of fit in the reduction of wuestite
(90Fe2O3-10MgAl2O4) possibly lies in the results shown in Table 6.2. There, it is indicated that the
pre-exponential factor was not well estimated by software package AVS® and hence, the activation
energy is estimated with suboptimal accuracy. Repeating the regression several times with varying
initial conditions did not resolve this problem.
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Chapter 6
Kinetic modeling
Figure 6.3 – H2-TPR of 50Fe2O3-50MgAl2O4 (S8) and 90Fe2O3-10MgAl2O4 (S5) using Micromeritics Autochem setup.
Gas flow: 60 ml/min H2 (5% in Ar). Heating rate β=20K/min. Full line shows the measured TCD signal. Dotted lines
show modeled reduction contributions and dashed line represents the global modeled H2 consumption.
As for the reduction of hematite to magnetite, there are some systematic deviations as well. Overall,
given the large list of assumptions made for obtaining experimental data as well as the bold model
assumptions, the results are quite satisfactory. This indicates that besides being a useful qualitative
technique, in-situ XRD may also provide valuable quantitative information when data are processed
with care. Nevertheless, the basics of XRD should always be kept in mind, i.e. crystalline phases are
measured and when crystallites of a certain phase shrink below a threshold size or become
amorphous, no signal will be detected for that phase even though its presence may still be
significant.
Furthermore, this example illustrates the importance of using several independent methods or
setups to evaluate the same process. Nevertheless, a detailed study on one type of reactor setup is
necessary in order to assess the model assumptions with respect to concentration gradients,
temperature gradients, etc. Because this lies beyond the scope of this thesis, this chapter should be
regarded as a proof of concept for obtaining quantitative results from in-situ XRD experiments.
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Chapter 6
Kinetic modeling
6.2. Temperature-Programmed Oxidation of metallic iron
6.2.1. Model description
Oxidation of metallic iron (Fe) to magnetite (Fe3O4) by carbon dioxide is assumed to occur as a
single-step process. The model is summarized in Table 6.4. similar to the H2-TPR model
(cfr. section 6.1.1, page 66), and is based on following assumptions:



Oxidation of metallic iron to magnetite is assumed to follow first order irreversible kinetics
under CO2-TPO conditions. Accumulation of CO is assumed to be negligible.
Partial pressure of carbon dioxide is assumed to be uniform (no gas phase diffusion
limitations). This implies the assumption that oxidation is limited by lattice oxygen
diffusion. The partial pressure of carbon dioxide and its partial reaction order are lumped
with the pre-exponential factor.
No heat transfer limitations: Sample temperature is controlled by the temperatureprogram.
Besides the rate equation for the oxidation of metallic iron to magnetite, a second ODE accounts for
the linear temperature program with heating rate β (Table 6.4).
Table 6.4 – Model overview for CO2-TPO of metallic iron.
Reaction
Reaction rate
Rate coefficient
Temperature-Program:
For the assumptions made for using experimental data from in-situ XRD CO2-TPO, the reader is again
referred to Appendix F. The set of ODE’s described above is solved using software package Athena
Visual Studio (AVS®), cfr. Appendix H.
6.2.2. Estimation of kinetic parameters
Figure 6.4 shows the results for 50Fe2O3-50MgAl2O4. It is peculiar that the experimental data do not
show the expected behavior with increasing heating rate. Instead, the onset of oxidation is found to
occur at a lower temperature when this material is heated at 10°C/min compared with 5°C/min.
Possibly, one of the assumptions made during the post-processing of in-situ XRD results was not
fulfilled. Also, comparing the experimental data with those of 90Fe2O3-10MgAl2O4 (Figure 6.5), this
data set is found to be much more noisy. This is due to the in-situ XRD detector settings which were
apparently set at a low collection time. For modeling purposes, this indicates that it is advisable to
choose the collection time sufficiently long. Overall, a balance between the number of data points
and the spectral resolution should be made to obtain a set of experimental data of optimal quality.
72
Chapter 6
Kinetic modeling
Figure 6.4 – Experimental data (dots) obtained from in-situ XRD CO2-TPR of 50Fe2O3-50MgAl2O4 (S8) compared with
modeled data (lines).
As stated above, the data obtained from in-situ XRD CO2-TPO of 90Fe2O3-10MgAl2O4 corresponds
better with the proposed model. With respect to the experimental data, the model generally
underestimates the extent of low-temperature oxidation. Most probably, the first phase of oxidation
is a reaction at the particle surface, followed by diffusion-controlled bulk oxidation. Because the
model does not differentiate between these two stages, the obtained estimates are mainly
determined by the bulk oxidation step.
Figure 6.5 – Experimental data (dots) obtained from in-situ XRD CO2-TPR of 90Fe2O3-10MgAl2O4 (S5) compared with
modeled data (lines).
Parameter estimates for both materials are summarized in Table 6.5. It is found that the activation
energy for oxidation of metallic iron by CO2 decreases with increasing promoter content. This is in
line with the findings in section 5.1.7.
Table 6.5 – Parameter estimates by regression of experimental data with CO2-TPO model equations using
Athena Visual Studio (AVS®).
Reaction
Parameter
50Fe2O3-50MgAl2O4
90Fe2O3-10MgAl2O4
73
Chapter 6
Kinetic modeling
Despite the lack of reference material, the activation energy for oxidation of metallic iron by CO 2 was
expected to lie in the range 50 kJ/mol to 130 kJ/mol corresponding with a study by
Graham et al. [51]. The values obtained in this work lie in this range. Note that, also in this case,
reparametrization may resolve the high correlation between pre-exponential factor and activation
energy.
6.2.3. Model validation
The same procedure was followed for assessing the validity of the obtained kinetic parameters as for
H2-TPR (cfr. section 6.1.3, page 70), namely by modeling a regular CO2-TPO. The results are shown in
Figure 6.6.
Figure 6.6 – CO2-TPO of 50Fe2O3-50MgAl2O4 (S8) and 90Fe2O3-10MgAl2O4 (S5) using Micromeritics Autochem setup.
Gas flow: 60 ml/min CO2 (100%). Heating rate β=20°C/min. Full line shows the measured TCD signal. Dashed line
represents the modeled CO2 consumption.
For sample 90Fe2O3-10MgAl2O4, the fit is quite reasonable. Deviations are higher for sample
50Fe2O3-50MgAl2O4, which is probably due to a lack of quality of the post-processed in-situ XRD data
shown in Figure 6.4.
74
Chapter 7 Combined CO2 capture and utilization
The outline of this Chapter is an investigation on the combination of CO2 capture with calcium oxide
and CO2 utilization via redox cycles with iron oxide in a single reactor setup. First, a setup with two
separate material beds (section 7.1) was used. Second, the effect of mixing both materials in a single
bed (section 7.1) was assessed. The materials showing the highest activity were chosen as oxygen
carrier and CO2 capture material. Based on this criterion, samples 90CaO-10Al2O3 (CA1) and
50Fe2O3-50MgAl2O4 (S8), described in Chapter 4 and Chapter 5 respectively, were selected for the
investigation on combined CO2 capture and utilization. The ratio of these samples was 3:1 (CA1:S8)
by weight in both setups.
7.1. Separate bed test experiment
In this experimental setup, a bed containing
50Fe2O3-50MgAl2O4 and a bed of 90CaO-10Al2O3
both diluted with corundum are separated by a
layer of quartz wool. This is schematically
represented in Figure 7.1. First, calcium oxide is
carbonated in 60 ml/min CO2 (100%) at 650°C.
Second, iron oxide is reduced at the same
temperature in 60 ml/min H2 (5% in Ar). Finally,
calcium carbonate is regenerated at 800°C in
60 ml/min He (100%) with release of CO2. When
passing the reduced iron oxide bed, CO2 is
expected to oxidize this bed, while being
reduced to CO. Hence, evolution of CO is
Figure 7.1 – Schematic representation of experimental
expected during this step. When using hydrogen setup for combined CO2 capture and utilization with a
as reduction agent, the global reaction in this separate bed of calcium oxide and iron oxide.
experiment is actually the reverse water-gas shift reaction:
CO
H →H O
CO
The results of a second cycle of the experimental procedure described above is shown in Figure 7.2.
Therefore, iron oxide in its most oxidized state occurs as magnetite. The reactions expected to take
place in each step of the experiment are shown in a window above the graph. During the first 5
minutes, absorption of CO2 is clearly observed as a sharp downward peak in the CO2 signal. Next after
preparation of the hydrogen flow, H2 is fed to the reactor after 8 minutes in order to reduce iron
oxide. Note that, upon reduction of iron oxide by H2, CO formation is observed. This is probably due
to partial decarbonation of calcium carbonate. The evolved CO2 passes the partially reduced iron
oxide bed, reoxidizing the latter with formation of CO. A minor peak of CO2 after 9 minutes occurs,
indicating evolution of some CO2. As seems from Figure 7.2 however, all CO2 which evolves is
reduced to CO. Hydrogen flow was stopped after 16.5 minutes, after which the reactor is purged
with helium. In the last step (after 19 minutes), the sample is heated to 800°C under helium for
75
Chapter 7
Combined CO2 capture and utilization
decarbonation of the remaining calcium carbonate. In this step, reduced iron oxide is reoxidized by
CO2 with formation of CO. The onset of this process occurs at 700°C and, even though both CO2 and
CO evolve, the maxima occur at a different moment in time (23 and 22 minutes, respectively).
Figure 7.2 – Experimental results for combined CO2 capture and utilization with a separate bed of
90CaO-10Al2O3 and 50Fe2O3-50MgAl2O4 diluted by corundum (α-Al2O3). The experiment consists of
subsequent calcium oxide carbonation (650°C, 60 ml/min CO2 (100%)), iron oxide reduction
(650°C, 60 ml/min H2 (5% in Ar)) and decarbonation of calcium carbonate (heating to 800°C,
60 ml/min He (100%)). Tsp denotes the sample setpoint temperature.
The general conclusions of this test experiment are the following. First, it is found that calcium
carbonate is probably not completely stable under hydrogen flow since decomposition is observed.
Of course, the presence of water vapor may also be related to this decomposition. Further
investigation on the effect of hydrogen and/or water vapor by performing experiments with only
calcium oxide may provide insight in this process. Second, even though reduced iron oxide is partially
reoxidized by released CO2, there is a net reduction of iron oxide. This is evidenced by the shifted
maximum of CO evolution upon decarbonation under helium, which would not occur if iron oxide
would be in its highest oxidation state. Finally, it is clearly possible to optimize the experimental
conditions for obtaining different ratios of H2 to CO in the product stream.
In a second experimental procedure, the first two steps were combined. Hence, CO2 and H2 were fed
to the reactor with a molar ratio close to one. From previous experiment, carbonation of calcium
oxide and reduction of iron oxide are expected to occur simultaneously. Afterwards, the reactor is
heated to decarbonation temperature to assess the extent to which CO2 and/or CO evolve. The result
is shown in Figure 7.3. Again, the reactions that are presumed to occur are included in a box above
the respective region. This time, the reactor was operated at 700°C for carbonation of calcium oxide
and reduction of iron oxide because at this temperature, iron oxide is more readily reduced. As for
calcium oxide, carbonation is still favored over decarbonation at this temperature. When feeding a
mixture of H2 and CO2 to the reactor (after 0.5 minutes), three trends are observed. First, it is clear
that H2 is consumed which most likely corresponds with a reduction of iron oxide. Note that the
76
Chapter 7
Combined CO2 capture and utilization
amount of H2 that is consumed after the initial deep peak remains quite high compared with
previous experiment (Figure 7.2). Second, consumption of CO2 is observed, corresponding with
carbonation of calcium oxide. Finally, CO is clearly formed by reduction of CO2 upon reoxidation of
iron. Previously (Figure 7.2), it was observed that there is some release of CO2 in H2 flow at a
temperature of 650°C. At 700°C, carbonation of calcium oxide in presence of hydrogen is most likely
reversible. Here, the bed of calcium oxide seems to act as a buffer of CO2 and only part of the fed CO2
reaches the reduced iron oxide bed where it is reduced to CO. Nevertheless, the net reaction in this
case seems to be in favour of carbonation. Possibly, increasing the amount of calcium oxide allows
for a reduction of CO2 evolution to such an extent that it is no longer significantly observed at the
outlet. A careful choice of reaction conditions may lead to different ratios of H2 to CO at the outlet.
Figure 7.3 – Experimental results for combined CO2 capture and utilization with a separate bed of
90CaO-10Al2O3 and 50Fe2O3-50MgAl2O4 diluted by corundum (α-Al2O3). The experiment consists of
simultaneous calcium oxide carbonation and iron oxide reduction (700°C, 95 ml/min H2 (5% in Ar) and
5 ml/min CO2 (100%)) followed by quenching to 650°C under helium and decarbonation of calcium
carbonate (heating to 800°C, 60 ml/min He (100%)). Tsp denotes the sample setpoint temperature.
The inset shows a magnification of the CO and CO2 signal between 9 and 14 minutes.
After 5 minutes, the feed flow is switched to helium at a lower flow rate with as side effect a strong
temporary increase in the CO2 and CO signal. The signal stabilizes at 8 minutes. When heating the
sample to decarbonation temperature, CO evolution reaches a maximum after 11 minutes whereas
the maximum in CO2 evolution is reached around 11.5 minutes. This indicates that the net reactions
occurring during the first 5 minutes are reduction of iron oxide and carbonation of calcium oxide
along with formation of CO by reduction of CO2. Depending on the application, co-feeding of
hydrogen and carbon dioxide may be preferable. A major advantage is that it allows for continuous
production of e.g. syngas in a ratio determined by process conditions and the relative amount of
calcium oxide and iron oxide. Separating these processes leads to a higher complexity with respect to
operation and reactor setup.
77
Chapter 7
Combined CO2 capture and utilization
7.2. Mixed bed test experiment
The same experiments as performed in previous
section were repeated with a slightly different
experimental setup (Figure 7.4). Here, samples of
50Fe2O3-50MgAl2O4 and 90CaO-10Al2O3 were
mixed in a single bed and diluted with corundum
(α-Al2O3). During a first experiment, following
procedure was followed (cfr. also section 7.1).
First, calcium oxide was carbonated in 60 ml/min
CO2 (100%) at 650°C. Second, iron oxide was
reduced at the same temperature in 60 ml/min
H2 (5% in Ar). Finally, calcium carbonate was
regenerated at 800°C in 60 ml/min He (100%)
with release of CO2. When passing the mixed
Figure 7.4 – Schematic representation of experimental
bed, which contains reduced iron oxide, CO2 is setup for combined CO capture and utilization with a
2
expected to reoxidize iron while reducing to CO. mixed bed of calcium oxide and iron oxide.
Hence, evolution of CO is expected during this step. As described previously, the net result of the
experimental procedure is the reverse water-gas shift reaction.
Figure 7.5 gives an overview of the experiment with a mixed bed of calcium oxide and iron oxide. The
reactions that are assumed to occur during each regime are shown above the graph.
Figure 7.5 – Experimental results for combined CO2 capture and utilization with a mixed bed of
90CaO-10Al2O3 and 50Fe2O3-50MgAl2O4 diluted by corundum (α-Al2O3). The experiment consists of
subsequent calcium oxide carbonation (650°C, 60 ml/min CO2 (100%)), iron oxide reduction (650°C,
60 ml/min H2 (5% in Ar)) and decarbonation of calcium carbonate (heating to 800°C, 60 ml/min
He (100%)). Tsp denotes the sample setpoint temperature.
78
Chapter 7
Combined CO2 capture and utilization
These results show the same features as observed in the separate bed experiment. After 1 minute,
CO2 is fed to the reactor and a sharp peak in the consumption of CO2 indicates carbonation of
calcium oxide. At 6 minutes, the CO2 flow is stopped and the reactor is purged with helium while the
hydrogen flow is prepared. Hydrogen flow is directed to the reactor at 8.5 minutes. Consumption of
hydrogen clearly indicates reduction of iron oxide. Along with the consumption of hydrogen, CO is
observed in the reactor effluent. As mentioned previously, this indicates that calcium carbonate is
decomposed in presence of hydrogen and/or water vapor at 650°C with subsequent re-oxidation of
reduced iron oxide by CO2. Note that virtually all CO2 that is formed by decomposition is converted
into CO and the ratio of H2 to CO in the reactor effluent seems to stabilize after 4 minutes of
reduction (after 12.5 minutes of the experiment). Next, the reactor is again purged with helium after
which the sample setpoint is set to 800°C. Again, a maximum in CO evolution occurs before the
maximum of CO2 evolution in a very similar fashion as for the separated bed (Figure 7.2, page 76).
As for the second experiment, in which the first two processes were combined by feeding a mixture
of H2 and CO2, the obtained results (Figure 7.6) are also similar as for the experiment with a separate
bed. In this case, consumption of CO2 in the initial 5 minutes seems to be lower. However, it should
be born in mind that for a quantitative comparison between different experiments, calibration would
be necessary. The shift between the CO and CO2 evolution peak (after 12.2 and 12.4 minutes
respectively) seems to be less pronounced.
Figure 7.6 – Experimental results for combined CO2 capture and utilization with a mixed bed of
90CaO-10Al2O3 and 50Fe2O3-50MgAl2O4 diluted by corundum (α-Al2O3). The experiment consists of
simultaneous calcium oxide carbonation and iron oxide reduction (700°C, 95 ml/min H2 (5% in Ar)
and 5 ml/min CO2 (100%)) followed by quenching to 650°C under helium and decarbonation of
calcium carbonate (heating to 800°C, 60 ml/min He (100%)). Tsp denotes the sample setpoint
temperature. The inset shows a magnification of the CO and CO2 signal between 10 and 15 minutes.
79
Chapter 8 Conclusion
The focus of this thesis was characterization and testing of CO2 capture sorbents and oxygen carrier
materials for chemical looping process. alumina-promoted calcium oxide appears to be a promising
CO2 sorbent both from activity and stability point of view. The reason was found to lie in the
formation of a highly branched calcium aluminum oxide (Ca3Al2O6) framework which acts as a
physical barrier between calcium oxide particles. For obtaining a material with a good activity, loss of
activity by incorporation formation of calcium aluminum oxide should be accounted for when
choosing the ratio of precursor materials. A material composed of 90w% calcium oxide and 10w%
alumina was subjected to 16 hours of cyclic carbonation-decarbonation (25 cycles). During the first 9
hours (15 cycles) some deactivation due to sintering was observed, after which the activity remained
stable for the next 7 hours (10 cycles). As a conclusion, it can be stated that the amount of structural
promoter necessary to obtain a stable operation over 16 hours of cyclic carbonation and
decarbonation is relatively low. Nevertheless, a quantitative study on the decay of activity of the
prepared materials during subsequent carbonation-decarbonation cycles would be interesting.
Next, the potential of iron oxide with different promoter materials (alumina, magnesia-alumina
spinel and magnesia) for CO2 reduction to CO by chemical looping was studied. During the first
reduction of alumina-promoted iron oxide, deactivation was found to be significant. The nature of
deactivation is formation of an inert iron-alumina spinel. In magnesia-promoted iron oxide,
magnesioferrite (MgFe2O4) was formed during material preparation. Magnesioferrite was found to
be reducible to (MgO)x(FeO)1-x at elevated temperature. Further reducing this material, it was
decomposed in magnesia and metallic iron. Reoxidation of this material by CO2 was found to occur
less readily due to sintering. Finally, a thorough study of MgAl2O4 promoted iron oxide for CO2
utilization was performed. Comparing samples with a given iron oxide content promoted by different
materials, the highest activity was found using MgAl2O4 as promoter material. Nevertheless, a strong
decay in activity of samples containing less than 50w% MgAl2O4 during 10 redox cycles was observed
due to sintering. The activity of 50Fe2O3-50MgAl2O4 decreases significantly from the 10th redox cycle
onward. As for 10Fe2O3-90MgAl2O4, material activity was found to remain stable for 17 hours of
operation at 750°C (60 redox cycles). From this, it follows that iron oxide particles should be present
as highly dispersed nanoparticles. The major conclusion for this part is that promoting iron oxide with
MgAl2O4 results in an active and stable material for CO2 utilization where the compositional region of
interest probably lies between 50w% and 90w% of MgAl2O4 promoter material.
80
Chapter 8
Conclusion
Information on the kinetics of iron oxide reduction and oxidation was extracted by post-processing of
in-situ XRD data of H2-TPR and CO2-TPO for samples 90Fe2O3-10MgAl2O4 and 50Fe2O3-50MgAl2O4.
Next, a model of first order irreversible reactions was proposed where partial pressures of the gas
phase reactant were assumed to be constant and uniform throughout the material. Model regression
of H2-TPR resulted in an estimate of the activation energy for reduction of hematite to magnetite
(104-108 kJ/mol), reduction of magnetite to wuestite (70-77 kJ/mol) and reduction of wuestite to
metallic iron (59-78 kJ/mol). As for CO2-TPO modeling, reoxidation of metallic iron to magnetite by
CO2 was assumed to follow a single-step process. The activation energy was estimated to be
100-122 kJ/mol. To conclude, kinetic modeling based on in-situ XRD data may provide good initial
estimates for the activation energy of solid state reactions. Constraints of this method lie in the
detectability of XRD, which for example does not allow modeling of 10Fe 2O3-90MgAl2O4 because of
its small iron oxide particle size. Model validation by a technique relying on different assumptions is
necessary to evaluate the quality of the estimates based on in-situ XRD measurements
Finally, test experiments for combined CO2 capture and utilization were performed using
90CaO-10Al2O3 as CO2 sorbent because of its superior activity as compared with the other samples.
The chosen oxygen carrier material was 50Fe2O3-50MgAl2O4 because of its high activity for CO2
utilization per unit mass of sample material. Formation of CO was observed during reduction of iron
oxide, indicating reoxidation of iron oxide by CO2 after reduction by H2. When hydrogen and carbon
dioxide were fed simultaneously, an increased evolution of CO was observed. Using a mixed or
separated bed of calcium oxide and iron oxide was not found to have a major influence on process
behavior. As a conclusion, changing the ratio of calcium oxide and iron oxide as well as process
conditions and feed composition may allow production of syngas with a variable ratio of H2 to CO.
81
Futurework
One of the main challenges with respect to CO2 capture using calcium oxide based materials is
assessing the influence of parameters such as temperature and feed composition. A basic kinetic
model for this equilibrium process, taking into account the partial pressure of CO2, would be helpful
for predicting the activity under different conditions. Particularly, the effect of realistic feed
compositions such as stack gases or air on activity should be investigated. More specific, the effect of
water vapor or sulphur compounds may be important. Also, a more profound characterization of
materials and the influence of material synthesis procedure may provide answers with respect to the
strong decrease of calcium oxide activity with increasing amount of alumina promoter. By calibration
of the detector with respect to CO2 consumption, determination of the total consumption of CO2 by
different materials is possible. This would give an indication on the amount of active calcium oxide
present in each sample. From this, the extent to which calcium oxide and alumina interact to form an
inert calcium aluminum oxide could be estimated. Furthermore, Transmission Electron Microscopy
combined with Elemental X-ray Diffraction analysis (TEM-EDX) may provide information on local
stoichiometry and structure as a function of alumina content.
As for the modeling part of iron oxide, it may be interesting to check the effect of particle size on the
rate of reduction and oxidation. This will give an indication on whether the assumption of a uniform
gas phase is valid or not. In practice, the effect of grain size and hence external mass and heat
transfer limitations may be assessed by testing reproducibility for several sieve fractions. As for the
effect of nanometer-scale particle size and porosity, different synthesis conditions may be applied.
This may provide insight on whether mass and heat transfer limitations occur at the pore scale.
Analogously, the effect of increased partial pressure of hydrogen and carbon dioxide (during
reduction and oxidation respectively) will give information with respect to mass transfer limitations.
Modeling of the reverse reactions may be investigated by performing reduction and oxidation
experiments with carbon monoxide and water vapor respectively. After determination of conditions
where the reaction is limited by reaction at the gas-solid interface, more detailed models, e.g. based
on a Mars van Krevelen or Langmuir-Hinshelwood mechanism, may be proposed.
When combining CO2 capture and utilization, many degrees of freedom exist. Modeling of both
processes as reversible with a distinct dependence in gas partial pressures allows optimization of this
combined process for a given purpose (fixed feed flow or desired product flow). Particularly, the
effect of hydrogen and water vapor on calcium carbonate decomposition should be studied.
For a specified application, an optimum ratio in iron oxide and calcium oxide for obtaining H2 and CO
in a pre-defined ratio may be determined when all processes are well described.
82
Appendices
Appendix A
Overview of performed experiments
MATERIAL SYNTHESIS
Experiment
Date
Journal page number
Co-precipitation, drying and calcination of Fe2O3-Al2O3 with
composition 90-10, 80-20, 70-30 and 50-50 (w%)
13/11/2013 - 21/11/2013
Co-precipitation (p. 1 & 3),
drying (p. 2) and calcination
(p. 4-5)
Co-precipitation, drying and calcination of Fe2O3-MgAl2O4
with composition 90-10, 80-20, 70-30 and 50-50 (w%)
14/11/2013 - 21/11/2013
Co-precipitation (p. 2 & 3),
drying (p. 4) and calcination
(p. 4-5)
Co-precipitation, drying and calcination of Fe2O3-MgO with
composition 90-10, 80-20, 70-30 and 50-50 (w%)
14/11/2013 - 21/11/2013
Co-precipitation (p. 3),
drying (p. 4) and calcination
(p. 5)
Synthesis of 80-20 (w%) CaO-Al2O3 via wet impregnation
(WI), drying and calcination.
20/01/2014-21/01/2014
Synthesis,
drying
calcination (p. 101).
Co-precipitation and drying of Fe2O3-MgAl2O4 with Fe2O3
content of 100, 90, 80, 70, 50, 30, 20 and 10 w%
12/02/2014-13/02/2014
Synthesis (p. 41-42) and
drying (p. 43)
Synthesis of 90-10, 80-20 and 70-30 (w%) CaO-Al2O3 via wet
physical mixing, drying and calcination
13/02/2014-18/02/2014
Synthesis (p. 105-106),
drying (p. 105-106) and
calcination (p. 106)
Calcination of Fe2O3-MgAl2O4 with Fe2O3 content of 100, 90,
80, 70, 50, 30, 20 and 10 w%
19/02/2014-27/02/2014
Calcination (p. 43-45)
and
83
Appendix A
Overview of performed experiments
CO2 CAPTURE MATERIALS
Experiment
X-Ray Diffraction
Material
80CaO-20Al2O3 (CAWI)
Date
p. 103
27/02/2014
90-10, 80-20 and 70-30 CaO-Al2O3 (CA1-CA3)
N2-B.E.T.
80CaO-20Al2O3 (CAWI)
p. 107
p. 103
25/03/2014
90-10, 80-20 and 70-30 CaO-Al2O3 (CA1-CA3)
CO2-TPCD
Journal page number
p. 107
80CaO-20Al2O3 (CA2)
25/04/2014
p. 108
90-10 an 70-30 CaO-Al2O3 (CA1 & CA3)
28/04/2014
p. 108
80CaO-20Al2O3 (CAWI)
29/04/2014
p. 103
80CaO-20Al2O3 (CAWI)
SEM-EDX
p. 103
28/04/2014
90-10, 80-20 and 70-30 CaO-Al2O3 (CA1-CA3)
p. 108
90CaO-10Al2O3 (CA1)
01/05/2014
Micromeritics 5 cycles
80CaO-10Al2O3 (CA2)
p. 109
70CaO-30Al2O3 (CA3)
02/05/2014
SEM-EDX
Spent CaO-Al2O3 (CA1-CA3, 5 cycles)
08/05/2014
p. 109
Micromeritics 25 cycles
90CaO-10Al2O3 (CA1)
15/05/2014
p. 109
SEM-EDX
Spent 90CaO-10Al2O3 (CA1, 25 cycles))
23/05/201424/05/2014
p. 109
84
Appendix A
Overview of performed experiments
CO2 UTILIZATION MATERIALS (S1-S12)
Experiment
Material
Date
Journal page number
X-Ray Diffraction
Fe2O3-Al2O3 (S1-S4), Fe2O3-MgAl2O4 (S5-S8),
Fe2O3-MgO (S9-S12) with composition 90-10,
80-20, 70-30 and 50-50 (w%)
21/11/2013
p. 7
SEM-EDX
Fe2O3-Al2O3 (S1-S4), Fe2O3-MgAl2O4 (S5-S8),
Fe2O3-MgO (S9-S12) with composition 90-10,
80-20, 70-30 and 50-50 (w%)
27/11/2013
p. 7
13/12/2013
p. 8
Samples S1-S12
16/12/2013
p. 9
Samples S4, S8 and S12
19/12/2013
p. 9
Samples S5, S6 and S11
20/12/2013
p. 9
Samples S9 and S10
23/01/2014
p. 9
90Fe2O3-10MgAl2O4 (S5)
24/01/2014
p. 9
In-situ XRD H2-TPR, CO2-TPO
and 5 redox cycles
70Fe2O3-30Al2O3 (S3)
70Fe2O3-30MgAl2O4 (S7)
ICP
In-situ XRD H2-TPR, CO2-TPO
and 5 redox cycles
In-situ XRD H2-TPR study
(5, 10 and 20°C/min)
90-10, 80-20, 70-30 and 50-50 Fe2O3-MgAl2O4
N2-B.E.T.
p. 10
20/03/2014
90-10, 80-20, 70-30 and 50-50 Fe2O3-Al2O3
Micromeritics H2-TPR and
CO2-TPO
Micromeritics
cycles
10
redox
N2-B.E.T.
Micromeritics
cycles
N2-B.E.T.
10
redox
p. 11
90-10 and 80-20 Fe2O3MgAl2O4 (S5-S6)
20/03/2014
p. 10-11
70-30 and 50-50 Fe2O3MgAl2O4 (S7-S8)
24/03/2014
p. 11
70-30 and 50-50 Fe2O3MgAl2O4 (S7-S8)
24/03/2014
p. 11
90-10, 80-20, 70-30 and 50-50 Fe2O3-MgO
24/03/201425/03/2014
p. 12
50Fe2O350Al2O3 (S4)
26/03/2014
p. 12
70Fe2O3-30MgO (repeat, neg. volume in
previous measurement)
07/04/2014
p. 12
85
Appendix A
Overview of performed experiments
CO2 UTILIZATION MATERIALS (S1-S12)
Material MATERIALS (S1-S12)
Date
CO2 UTILIZATION
Experiment
Journal page number
90Fe2O3-10MgAl2O4 (S5)
07/04/2014
p. 12
80Fe2O3-20MgAl2O4 (S6)
15/04/2014
p. 12
In-situ XRD H2-TPR study
(5, 10, 15, 20 and 30°C/min)
50Fe2O3-50MgAl2O4 (S8)
16/04/2014
p. 13
In-situ XRD CO2-TPO study
(5, 10 and 30°C/min)
50Fe2O3-50MgAl2O4 (S8)
17/04/2014
p. 13
In-situ XRD CO2-TPO study
(5, 10, 20 and 30°C/min)
90Fe2O3-10MgAl2O4 (S5)
18/04/2014
p. 14
SEM-EDX
90-10, 80-20, 70-30 and 50-50 Fe2O3-Al2O3
(repeat with gold coating)
28/04/2014
p. 14
70Fe2O3-30MgAl2O4 (S7, repeat experiment)
29/04/2014
p. 14
02/05/2014
p. 14
Micromeritics
cycles
Micromeritics
cycles
10
10
redox
redox
50Fe2O3-50MgO (S12)
90Fe2O3-10MgAl2O4 (S5, repeat experiment)
50Fe2O3-50MgAl2O4 (S8, repeat experiment)
Micromeritics H2-TPR and
CO2-TPO
70Fe2O3-30MgAl2O4 (S7, repeat experiment)
05/05/2014
p. 15
N2-B.E.T.
90-10, 80-20, 70-30 and 50-50 Fe2O3-MgO
(repeat measurements)
05/05/201408/05/2014
p. 15
SEM-EDX
90-10, 80-20, 70-30 and 50-50 Fe2O3-MgAl2O4
and Fe2O3-MgO (repeat with gold coating)
and spent samples (S4: 5 cycles, S5: 10 cycles,
S7: 10 cycles, S8: 10 cycles and S12: 5 cycles)
08/05/2014
p. 15
50Fe2O3-50MgAl2O4 (S8)
09/05/2014
p. 15
STEM-EDX analysis
50Fe2O3-50MgAl2O4 (S8)
21/05/2014
p. 15
SEM-EDX
50Fe2O3-50MgAl2O4 (S8) after 25 cycles
23/05/2014
p. 15
Micromeritics
cycles
25
redox
86
Appendix A
Overview of performed experiments
CO2 UTILIZATION MATERIALS (FMA1-FMA8)
Experiment
Material
Date
Journal page number
X-Ray Diffraction
100-0, 90-10, 80-20, 70-30, 50-50, 30-70,
20-80 and 10-90 (w%) Fe2O3-MgAl2O4
(FMA1-FMA8)
27/02/2014
p. 45
N2-B.E.T.
Samples FMA2 and FMA6
26/03/2014
p. 45
50-50, 30-70 and 10-90 (w%) Fe2O3-MgAl2O4
(FMA5, FMA6 and FMA8)
26/03/2014
p. 45-46
Samples FMA3-FMA5
27/03/2014
p. 46
Samples FMA7 and FMA8
28/03/2014
p. 46
Sample FMA1
07/04/2014
p. 46
Samples FMA1-FMA8
08/04/2014
p. 47
20Fe2O3-80MgAl2O4 (FMA7)
14/04/2014
p. 47
28/04/2014
p. 47
Samples FMA1, FMA6, FMA7 and FMA8
05/05/2014
p. 47
Samples FMA8 (repeat)
06/05/2014
p. 47
Sample FMA6 and FMA7 (repeat)
06/05/2014
p. 47-48
Sample FMA8 (repeat)
07/05/2014
p. 48
Sample FMA6 and FMA8 (repeat)
08/05/2014
p. 48
Micromeritics H2-TPR and
CO2-TPO
Samples FMA1 (extend CO2-TPO to 920°C)
and FMA8 (extend H2-TPR to 950°C)
19/05/2014
p. 48
Micromeritics
cycles
10Fe2O3-90MgAl2O4 (FMA8)
19/05/201420/05/2014
p. 49
30Fe2O3-70MgAl2O4 (FMA6)
21/05/2014
p. 49
10Fe2O3-90MgAl2O4 (FMA8)
22/05/2014
p. 49
10Fe2O3-90MgAl2O4 (FMA8) after 60 cycles
23/05/2014
p. 49
Micromeritics
cycles
10
redox
N2-B.E.T.
SEM-EDX
Micromeritics
cycles
10
redox
Samples FMA3 and FMA4
double-check composition via EDX)
SEM-EDX
Micromeritics H2-TPR and
CO2-TPO
Micromeritics
cycles
10
60
(repeat,
redox
redox
STEM-EDX analysis
SEM-EDX
87
Appendix A
Overview of performed experiments
KINETIC MODELING OF H2-TPR AND CO2-TPO
Calculation
AVS®
H2-TPR
model
regression for parameter
estimation
AVS®
CO2-TPO
model
regression for parameter
estimation
Description
Date
Journal page number
90Fe2O3-10MgAl2O4
(S5)
first
order
irreversible model (6 parameters) for 3
heating rates (5, 10 and 20°C/min) excluding
wuestite. Data sets of each heating rate
contain an equal amount of data points.
20/05/2014
p. 73
50Fe2O3-50MgAl2O4
(S8)
first
order
irreversible model (6 parameters) for 4
heating rates (5, 10, 15 and 20°C/min). Data
sets of each heating rate contain an equal
amount of data points.
20/05/2014
p. 73
90Fe2O3-10MgAl2O4
(S5)
first
order
irreversible model (2 parameters) for 3
heating rates (5, 10 and 20°C/min). Data sets
of each heating rate contain an equal amount
of data points.
20/05/2014
p. 81
50Fe2O3-50MgAl2O4
(S8)
first
order
irreversible model (2 parameters) for 2
heating rates (5 and 10°C/min). Data sets of
each heating rate contain an equal amount of
data points.
20/05/2014
p. 81
COMBINED CO2 CAPTURE AND UTILIZATION
Experiment
Material
Date
Journal page number
Separated bed test
experiment
50Fe2O3-50MgAl2O4 (S8) and 90CaO-10Al2O3 (CA1)
07/05/2014
p. 151-153
Mixed
bed
experiment
50Fe2O3-50MgAl2O4 (S8) and 90CaO-10Al2O3 (CA1)
08/05/2014
p. 153-154
test
88
Appendix B
XRD Powder Diffraction Patterns
89
Appendix B
XRD Powder Diffraction Patterns
90
Appendix B
XRD Powder Diffraction Patterns
91
Appendix B
XRD Powder Diffraction Patterns
92
Appendix B
XRD Powder Diffraction Patterns
93
Appendix B
XRD Powder Diffraction Patterns
94
Appendix B
XRD Powder Diffraction Patterns
95
Appendix B
XRD Powder Diffraction Patterns
96
Appendix B
XRD Powder Diffraction Patterns
97
Appendix B
XRD Powder Diffraction Patterns
98
Appendix B
XRD Powder Diffraction Patterns
99
Appendix B
XRD Powder Diffraction Patterns
100
Appendix B
XRD Powder Diffraction Patterns
101
Appendix B
XRD Powder Diffraction Patterns
102
Appendix C
Estimating particle size based on X-Ray
Diffraction using Scherrer’s equation
Based on the peak width of X-Ray Diffraction (XRD) signals, characteristic dimensions of crystallites
can be determined by applying Scherrer’s equation. Hence, for all particles large and/or crystalline
enough to diffract incident X-rays an estimate for the crystallite size may be calculated.
d
=
K∙λ
(β − b) ∙ cos θ
where
λ
X-ray wavelength
[nm]
dXRD
Measure for particle dimension
[nm]
θ
Diffraction angle
[deg]
ß
Peak width (FWHM)
[rad]
b
Instrumental width
[rad]
K
Constant
Angle between incoming X-rays and the normal
to the reflecting lattice plane
The Scherrer equation indicates that small crystallites will yield broad peaks, whereas large
crystallites should correspond to narrow diffractions. In practice, following procedure is followed.
First, the respective peak is isolated from the rest of the XRD-spectrum. If overlap occurs, the extent
to which an undesired contribution is incorporated should be minimized as much as possible.
In principle, only part of the peak (including the maximum) is necessary for obtaining adequate
results. Next, the peak is fitted to a Gaussian of the following form:
I
=I∙
C
β ∙ √π
∙ exp#
%%%)&
−C ∙ (2θ − %2θ
'
β&
where
Imeasured
Measured XRD intensity
[-]
I
Maximum intensity
[-]
Model parameter
θ
Diffraction angle
[deg]
%2θ
%%%
Peak position
[deg]
Angle between incoming X-rays and the normal
to the reflecting lattice plane
Model parameter
ß
Peak width (FWHM)
[deg]
Model parameter
C0
Constant
[-]
C0=2.773
Figure C.1 shows an illustration on how the full width half maximum (β) is determined for a
characteristic XRD peak of hematite in 90Fe2O3-10Al2O3. The previously described model parameters
are optimized by minimization of the residual sum of squares using Excel® non-linear solver.
103
Appendix C
Estimating particle size based on X-Ray Diffraction using Scherrer’s equation
Hence, for the given example, the peak position is estimated to lie at 33.4° whereas the full width
half maximum is estimated at 0.400°.
Figure C.1 – Illustration on methodology for determining the width of a characteristic XRD peak.
Using these estimates, characteristic particle dimensions are calculated by applying Scherrer’s
equation. The instrumental width is in general determined by measuring a LaB6 reference using the
same instrument and measuring conditions (Figure C.2). The latter sample displays a diffraction
pattern with peaks evenly spread throughout the measuring range. Moreover, it consists of large
crystallites, > 100 nm, yielding the narrowest possible peaks, which reflect only instrumental width.
From the characteristic peak widths of this reference, the instrumental width at a certain diffraction
angle θ may be estimated by linear interpolation.
Figure C.2 – Characteristic XRD spectrum for a LaB6 reference. The inset summarizes the peak widths (FWHM) for
given peak positions (2θ).
104
Appendix C
Estimating particle size based on X-Ray Diffraction using Scherrer’s equation
In this example, linear interpolation between the instrumental widths at 30.4° and 37.4° gives
an estimate for the instrumental width at 33.4° (b=0.178°). Given that the value of ή ɉ is 0.1386 for
the detector that was used, the Scherrer particle dimension can be calculated. Note that, for applying
the Scherrer equation, peak widths must be converted into radians.
†ଡ଼ୖୈ ൌ
ήɉ
ͲǤͳ͵ͺ͸݊݉
ൌ
ൌ ͵͹ǤͶ݊݉
ሺȾ െ „ሻ ή …‘• Ʌ ሺ͸ǤͻͺͳͲିଷ ‫ ݀ܽݎ‬െ ͵ǤͳͳͳͲିଷ ‫݀ܽݎ‬ሻ ή …‘•ቀ͵͵ǤͶιቁ
ʹ
When this estimation is repeated for characteristic peaks with a different diffraction plane (or Miller
indices (hkl)), particle sphericity can be investigated on the assumption that particle dimensions are
well estimated. This implies the assumption that no significant peak overlap occurs. Figure C.3(A)
shows the Scherrer particle dimension for 7 characteristic peaks of hematite (i.e. 7 most intense
peaks) in samples containing different fraction of alumina promoter. It is clear that the largest spread
occurs in samples containing 90w% and 50w% iron oxide. This feature is also observed when
calculating the mean and standard deviation of the different particle dimensions for each sample
(Figure C.3 (B)). As stated before, under the condition of well estimated particle dimensions, this
indicates that particles are most spherical in samples containing 80w% or 70w% iron oxide.
Figure C.3 – (A) Estimated Scherrer particle dimensions based on 7 different characteristic peaks (hkl).
(B) Average particle dimension and standard deviation based on the results shown in (A).
105
Appendix D
Estimating particle size based on Scanning
Electron Microscopy
Based on Scanning Electron Microscopy (SEM), an estimate for particle dimensions may be obtained
simply by estimating the size of a large number of particles and determining the distribution.
An example for pure synthetic hematite is shown in Figure D.1. Sizes are simply determined as
follows:
∙ 1000
Where 1000 nm is the microscopic value of the scalebar.
Figure D.1 – SEM image for pure synthetic hematite (FMA1) showing
estimates for particle size dimensions (400 counts).
The corresponding particle size distribution in shown in Figure D.2(A) and shows a maximum around
110 nm. Next, the frequency can be normalized for the total number of counts to obtain a
probability. It is then possible to fit a probability density function to the obtained particle size
distribution. In this case, a normal distribution of the following form was assumed to be adequate for
approximating the particle size distribution.
∙ exp !
#
!"
%
2∙ #
Where P(dp) is the fraction of particles with size dp. The fitting parameters a, b and c correspond with
a scaling factor, the average particle size and the standard deviation with respect to this average
particle size, respectively. A fit of the measured particle size distribution with this model was
performed by minimizing the residual sum of squares using Excel® non-linear solver. The result is
106
Appendix D
Estimating particle size based on Scanning Electron Microscopy
shown in Figure D.2(B) with the corresponding parameters in the inset. Hence, according to the
model, the particle size distribution is characterized by an average particle size of 109 nm with a
standard deviation of 29 nm.
Figure D.2 – (A) SEM particle size distribution of pure synthetic hematite (FMA1) based on 400 counts.
(B) Measured (dots) and modeled (solid line) particle size distribution.
Figure D.3 shows a SEM image for 80Fe2O3-20MgAl2O4 (FMA3), with much smaller particles. In this
case, the region of measuring was restricted to a smaller area represented by the blue box. Also,
because two contributions (Fe2O3 and MgAl2O4) in the particle size distribution are expected, an
attempt in deconvoluting the particle size distribution was made. Again, a normal distribution was
assumed for each of both contributions. As before, the parameters a, b and c were estimated by
minimizing the total sum of squares using Excel® non-linear solver.
Figure D.3 – SEM image for 80Fe2O3-20MgAl2O4 (FMA3) showing estimates
for particle size dimensions (400 counts). The blue box shows the region to
which the measurements were restricted.
107
Appendix D
Estimating particle size based on Scanning Electron Microscopy
The result, shown in Figure D.4, consists of two contributions with average and standard deviation
at 28 ± 7 nm and 45 ± 9 nm.
Figure D.4 – (A) SEM particle size distribution of 80Fe2O3-20MgAl2O4 (FMA3) based on 400 counts. (B) Measured (dots)
and modeled (solid line) particle size distribution. Dashed line show separate model contributions.
The same procedure was followed in estimating the average particle size of other samples based on
SEM images. In general, maximum two contributions were considered and a normal distribution was
assumed to be adequate for describing all distributions.
108
Appendix E
Methodology
for
estimating
oxygen
conversion in isothermal redox cycles
For enabling a more quantitative means of comparing different samples with respect to their oxygen
storage capacity upon cyclic reduction and oxidation, following method for estimation of the oxygen
conversion was used. The raw data is the signal obtained from mass spectrometry during redox
cycles, shown in Figure E.1.
Figure E.1 – Mass spectrometer measurements during 25 redox cycles of 50Fe2O3-50MgAl2O4 (S8). Reduction cycles with
5% H2 (in Ar) are alternated with CO2 (100%) oxidation cycles. In between cycles, helium is used as purging agent.
Because of the low intensity, the signal of H2 and H2O is magnified on the right axis.
During reduction only argon, hydrogen and water are measured. The signal of water is not used for
quantitative purposes because of its tendency to adsorb in the tubing before analysis. Hence, its
signal is broadened up to the extent that a new reduction cycle starts before the water signal reaches
its background level. Because of this broadening, information about the reduction rate is lost
compared with the hydrogen signal. Therefore, the reduction phase will be studied by analyzing the
hydrogen signal even though its signal is inherently weaker. To account for changes in background,
argon is used as reference (Figure E.2) and the H2/Ar signal is assumed to allow comparison over
time.
During oxidation, carbon dioxide and carbon monoxide are observed along with water due to the
previously discussed phenomenon of peak broadening. In this regime, the CO signal is used as a
measure for oxidation and an interpolation of the argon signal between reduction regimes is used as
reference to account for changes in background. Similarly as for H2, it is assumed that with this
interpolation of argon reference signal, CO/Ar signal in subsequent cycles can be compared.
109
Appendix E
Methodology for estimating oxygen conversion in isothermal redox cycles
Figure E.2 – Mass spectrometer measurements of Ar as internal standard during 25 redox cycles of
50Fe2O3-50MgAl2O4 (S8). Reduction cycles with 5% H2 (in Ar) are alternated with CO2 (100%) oxidation cycles. In between
cycles, helium is used as purging agent. The dashed line shows how the signal of Ar during reduction was used as internal
standard. Linear interpolation between cycles provides an estimate for this standard during oxidation steps.
Figure E.3 – Single redox cycle showing background signal of H2 during reduction and of CO during
oxidation. The lower background signal of H2 shows corresponds with no H2 flow whereas the upper
background signal corresponds with 3 ml/min H2 (60ml/min of 5% H2 in Ar). The background signal of CO
results from CO formation by ionization of CO2 (60 ml/min, 100% CO2) inside the mass spectrometer.
Figure E.3 shows the point at which no hydrogen is consumed right before the onset of reduction as
well as the point where no hydrogen flows through the reactor. Also, CO signal before the onset of
oxidation where no carbon monoxide has formed inside the reactor tube is indicated. Note that,
110
Appendix E
Methodology for estimating oxygen conversion in isothermal redox cycles
when CO2 is fed, CO is always observed to some extent by mass spectrometry because ionization of
CO2 within the mass spectrometer leads to CO formation. Hence, the signal of hydrogen and carbon
monoxide due to reaction can be extracted (Figure E.4) by taking into account these background
signals phenomena.
Figure E.4 – CO formation and H2 consumption for 50Fe2O3-50MgAl2O4 (S8) in 25 redox cycles.
By assuming that the point of no hydrogen consumption shown in Figure E.3 corresponds with a flow
of 5% hydrogen in argon (60 ml/min), hydrogen flow after the reactor tube can be estimated by
linear interpolation given that the background signal corresponds with zero flow. Because the
amount of sample and its composition are known, integration of the amount of hydrogen consumed
during reduction (integral was approximated using rectangle method) enables estimation of the
extent of reduction of iron oxide. The conversion of iron oxide lattice oxygen may be determined
taking into account that, after the first cycle, the highest oxidation state of iron with CO 2 as oxidizing
agent corresponds with magnetite:
୓ ൌ
‘Žଶ …‘•—‡†
‘Ž”‡†—…‹„Ž‡
Figure E.5 shows the obtained results. The oxygen conversion in the first cycle is probably
overestimated given the strongly decreasing signal during the first cycle (Figure E.1) which is not fully
accounted for. This method for estimation of the iron oxide oxygen conversion allows for calculation
of properties such as the oxygen storage capacity under the given conditions.
111
Appendix E
Methodology for estimating oxygen conversion in isothermal redox cycles
Figure E.5 – Estimated oxygen conversion of iron oxide in 50Fe2O3-50MgAl2O4 (S8)
for 25 redox cycles.
112
Appendix F
Post-processing in-situ X-Ray Diffraction data
In order to extract as much quantitative data as possible from in-situ XRD experiments,
a methodology for processing raw in-situ XRD data was established. Figure F.1 illustrates the
followed procedure starting from a characteristic in-situ XRD map (Figure F.1[A]) showing the peak
intensity at a given diffraction angle 2θ and a given temperature which is correlated with time in
Temperature-Programmed Reactions. In what follows, each step will be discussed. Step 1-4 are
repeated for each transition (reduction of hematite, magnetite and wuestite). Step 5 consists of
combining these results and finally, in step 6, reaction stoichiometry is introduced.
step 1
Using in-situ XRD data processing software, the XRD intensity of hematite characteristic
peaks (Fe2O3, 2θ=49°-50.3° and 2θ=53.8°-55.1°) was obtained as a function of temperature.
Analogously, the XRD intensity of background (i.e. diffraction angles with no phase activity, in
this case 2θ=51°-52°) was determined. The integrated XRD-signal in all of these intervals is
shown as a function of temperature in Figure F.1[B].
step 2
Next, the background signal was shifted so that the initial hematite peak intensity coincides
with the initial background signal (Figure F.1[C], blue and green lines are integrated XRD
intensities of hematite and red lines are shifted background signals). It is observed that the
relative integrated intensity of hematite XRD peaks decreases with respect to the background
signal. This corresponds with consumption of hematite, i.e. reduction of hematite to
magnetite.
step 3
After shifting the background signal, the integrated XRD intensity of hematite characteristic
peaks is divided by the shifted background signal (Figure F.1[D]). Because no phase activity is
assumed in the background 2θ-range, the integrated intensity of the background shows
temperature and time dependence of the integrated XRD signal throughout the experiment.
Hence, the temperature and time dependence of the XRD signal are eliminated by division of
the integrated phase signal by the integrated background signal. In Figure F.1[D], the
temperature range at which reduction of hematite to magnetite occurs is observed clearly.
In the initial plateau where the relative integrated intensity of hematite with respect to the
background is equal to one (T=300°C), reduction has not yet started. At temperatures around
350°C, the relative integrated intensity decreases sharply until a plateau is reached at 500°C.
This indicates that the reduction of hematite to magnetite for this material occurs between
350°C and 500°C. Note that deviations may occur depending on which phase signal is
integrated (2θ=50° or 2θ=54°). In general, the most intense peak is used in further
processing. In this case, this corresponds with the peak at 2θ=54°.
113
Appendix F
Post-processing in-situ X-Ray Diffraction data
Figure F.1 – Stepwise procedure for obtaining quantitative experimental data from raw in-situ XRD
(H2-TPR) data of sample 90Fe2O3-10MgAl2O4 (S5). Step 1 to 4 are specifically shown for the
reduction of hematite. Step 5 indicates that the same procedure was followed for reduction of
magnetite and wuestite. Step 6 accounts for reaction stoichiometry.
114
Appendix F
Post-processing in-situ X-Ray Diffraction data
step 4
In this step, the relative integrated intensity is linked to a dimensionless amount of material
or activity, denoted ni*. For choosing the relative integrated phase signal to continue with,
two important criteria should be considered: First, the phase signal should show no overlap
with other phases that are active in the same temperature or time span. Second, as
mentioned previously, the most intense peak with the highest signal to noise ratio should be
used.
In this case, the relative integrated intensity of the hematite peak at 2θ=54° was used for
further processing. For obtaining the results as shown in Figure F.1[E], following assumption
was made:
݊ி௘మ ைయ
‫ܫ‬
‫כ‬
̱
ൌ ݊ி௘
మ ைయ
‫ܫ‬଴ ݊ி௘మ ைయ ǡ଴
Because the dimensionless amount of hematite varies between 1 and 0, the relative
integrated intensity of the characteristic peak should be scaled between 1 and 0. The former
corresponds with the situation before the onset of reduction whereas the latter corresponds
with full reduction of hematite to magnetite. In Figure F.1[D], this correspond with the
plateaus in relative integrated intensity at 300°C and above 500°C, respectively.
step 5
The procedure followed in steps 1-4 is repeated for consumption (hematite, magnetite and
wuestite) and formation (magnetite, wuestite and metallic iron) of each phase. Of course,
when a phase is formed scaling is between 0 and 1 in accordance with the increasing amount
of the respective phase with temperature or time.
Figure F.2 – XRD spectrum before and after in-situ XRD H2-TPR of 90Fe2O3-10MgAl2O4 (S5).
Dark blue dots and light blue triangles represent hematite and iron respectively.
The result, showing the stepwise reduction of hematite to metallic iron, is shown in Figure
F.1[F]. Note that two boundary conditions were imposed for coming to this result. First, it
115
Appendix F
Post-processing in-situ X-Ray Diffraction data
was assumed that iron oxide is only present as hematite at the start of the experiment. This
is justified looking at the XRD spectrum of a fresh sample (Figure F.2). Second, it was
assumed that iron oxide is fully reduced to metallic iron at 800°C and hence, the residual
amounts of magnetite and wuestite are negligible. The last assumption is more difficult to
justify given that there is still some activity of wuestite in Figure F.1[A] at diffraction angle
42°. When looking at the XRD spectrum taken after the in-situ XRD H2-TPR experiment (Figure
F.2), however, only metallic iron is observed. This is due to post-treatment (2 to 5 minutes) at
the final temperature after which the sample was cooled and a full XRD scan was performed.
Anyhow, this indicates that it is good practice to choose the final temperature of the
experiment sufficiently high. This ensures that the assumption of a single phase occurring at
the end of the experiment is valid.
step 6
The final step lies in scaling each phase signal in order to close the iron balance as well as
possible. All phases are scaled with respect to the initial amount of hematite ୊ୣమ ୓య ǡ଴:
ʹ
‡ଶ ଷ ՜ ‡ଷ ସ ՜ ʹ‡ ՜ ʹ‡
͵
Hence, the maximum dimensionless amount ni* of hematite, magnetite, wuestite and
metallic iron is 1, 2/3, 2 and 2 respectively according to reaction stoichiometry:
‫כ‬୧ ൌ
୧
୊ୣమ ୓య ǡ଴
™Š‡”‡‹ ൌ ‡ଶ ଷ ǡ ‡ଷ ସ ǡ ‡‘”‡
Following balance with respect to the amount of iron should be fulfilled at each timestep:
ͳ ‫כ‬
ͳ ‫כ‬
͵ ‫כ‬
‫כ‬
୊ୣ
ሺ–ሻ ൅ ୊ୣ
୓ర ሺ–ሻ ൅ ୊ୣ୓ ሺ–ሻ ൅ ୊ୣ ሺ–ሻ ൌ ͳ
య
మ ୓య
ʹ
ʹ
ʹ
The signal of magnetite, wuestite and iron obtained in step 5 is now multiplied with a
separate scaling parameter while minimizing the residual sum of squares on the iron balance.
This problem is solved using Excel® non-linear solver while imposing the following conditions:
‫כ‬
Ͳ ൏ ୊ୣ
൑ ʹȀ͵
య ୓ర
‫כ‬
ቐ Ͳ ൏ ୊ୣ୓ ൑ ʹ
Ͳ ൏ ‫כ‬୊ୣ ൑ ʹ
The result is shown in Figure F.1[G]. The iron balance is well closed up to 5% and indicates
that it reaches -5% at the end of the experiment. This probably corresponds with the error
that was made by assuming that all wuestite is reduced to metallic iron before 800°C. Despite
this kind of deviations, the obtained data is expected to be sufficiently accurate to serve as
experimental data for estimating the activation energy of the separate transitions.
Furthermore, the shape of the different contributions may provide insight in (partial)
reaction orders or the reaction mechanism. Again, analysis of the data requires caution
because peak overlap with other active phases may significantly distort the shape of the
phase profiles.
116
Appendix F
Post-processing in-situ X-Ray Diffraction data
The procedure for processing in-situ XRD CO2-TPO experimental data is similar. In this case,
however, metallic iron is chosen as reference phase instead of hematite.
‫כ‬୧ ൌ
୧
୊ୣǡ଴
™Š‡”‡‹ ൌ ‡‘”‡ଷ ସ
The assumed boundary conditions in this case are the following: Initially, all iron oxide is
present as metallic iron. At the end of the experiment, all metallic iron is oxidized to
magnetite. Oxidation of metallic iron to magnetite is assumed to occur in a single step. This
results in following equations for reaction stoichiometry and iron balance:
ͳ
‫כ‬
ሺ–ሻ ൌ ͳ
‡ ՜ ‡ଷ ସ ƒ†‫כ‬୊ୣ ሺ–ሻ ൅ ͵୊ୣ
య ୓ర
͵
with following conditions when minimizing the residual sum of squares on the iron balance.
Ͳ ൏ ‫כ‬୊ୣయ ୓ర ൑ ͳȀ͵
117
Appendix G
Athena Visual Studio
modeling H2-TPR
(AVS®)
code
for
The implemented AVS®-code for parameter estimation based on H2-TPR experiments is shown in
Figure G.1.
Figure G.1 – Athena Visual Studio (AVS®) code for modeling H2-TPR.
The model is also summarized in Table G.1.
Table G.1 – Overview of reactions, reaction rate equations and rate coefficients in the model for H2-TPR of iron oxide.
Reaction
1
3
2
→ 3
→ 3
→
Reaction rate
1
3
Rate coefficient
R
k ∙ n∗
k
A ∙p
∙ exp "#
R
k ∙ n∗
k
A ∙p
∙ exp1#
k
A ∙p
∙ exp"#
R
0
k ∙ n∗
R ∙ )T
R ∙ )T
R ∙ )T
'((
E%,
/
273.15.
â((
E%,
3
273.15.
'((
E%,
/
273.15.
Temperature-Program:
dT
dt
β
118
Appendix H
Athena Visual Studio
modeling CO2-TPO
(AVS®)
code
for
The simplified model for CO2-TPO for parameter estimation is implemented in AVS® as shown in
Figure H.1.
Figure H.1 – Athena Visual Studio (AVS®) code for modeling CO2-TPO.
An overview of the model for CO2-TPO is given in Table H.1.
Table H.1 – Overview of simplified model for CO2-TPO of iron.
Reaction
4
3
1
→ 3
Reaction rate
4
3
R
k ∙ n∗
Rate coefficient
k
A ∙p
∙ exp !"
R ∙ (T
&''
E$,
/
273.15.
Temperature-Program:
dT
dt
β
119
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Krishna, R. and J.M. van Baten, A comparison of the CO2 capture characteristics of zeolites and metal–
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