Solid-State Kinetic Investigations of Nonisothermal Reduction...

Research ArticleSolid-State Kinetic Investigations of NonisothermalReduction of Iron Species Supported on SBA-15

N S Genz1 D Baabe2 and T Ressler1

1 Institut fur Chemie Technische Universitat Berlin Straszlige des 17 Juni 135 10623 Berlin Germany2Institut fur Anorganische und Analytische Chemie Technische Universitat Braunschweig Hagenring 3038106 Braunschweig Germany

Correspondence should be addressed to T Ressler thorstenresslertu-berlinde

Received 8 May 2017 Revised 13 September 2017 Accepted 26 September 2017 Published 1 November 2017

Academic Editor Adam Voelkel

Copyright copy 2017 N S Genz et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Iron oxide catalysts supported on nanostructured silica SBA-15 were synthesized with various iron loadings using two differentprecursors Structural characterization of the as-prepared Fe119909O119910SBA-15 samples was performed by nitrogen physisorption X-raydiffraction DR-UV-Vis spectroscopy and Mossbauer spectroscopy An increasing size of the resulting iron species correlated withan increasing iron loading Significantly smaller iron species were obtained from (Fe(III) NH4)-citrate precursors compared toFe(III)-nitrate precursors Moreover smaller iron species resulted in a smoother surface of the support material Temperature-programmed reduction (TPR) of the Fe119909O119910SBA-15 samples with H2 revealed better reducibility of the samples originating fromFe(III)-nitrate precursors Varying the iron loading led to a change in reduction mechanism TPR traces were analyzed by model-independent Kissinger method Ozawa Flynn and Wall (OFW) method and model-dependent Coats-Redfern method JMAKkinetic analysis afforded a one-dimensional reduction process for the Fe119909O119910SBA-15 samples The Kissinger method yielded thelowest apparent activation energy for the lowest loaded citrate sample (119864119886 asymp 39 kJmol) Conversely the lowest loaded nitratesample possessed the highest apparent activation energy (119864119886 asymp 88 kJmol) For samples obtained from Fe(III)-nitrate precursors119864119886 decreased with increasing iron loading Apparent activation energies from model-independent analysis methods agreed wellwith those from model-dependent methods Nucleation as rate-determining step in the reduction of the iron oxide species wasconsistent with the Mampel solid-state reaction model

1 Introduction

Metal oxide catalysts with complex chemical compositionsare often employed in selective oxidation reactions [1] Notonly oxygen mobility and lattice diffusion but also redoxproperties of the metal oxide catalyst significantly influenceperformance in selective oxidationTherefore understandingreduction and reoxidation kinetics is a fundamental start-ing point for deducing reliable structure-activity correla-tions Iron-containing catalysts are active in nitrogen oxidesremoval Friedel-Crafts reactions Fischer-Tropsch synthesiscatalytic methane decomposition and selective oxidationreactions [1ndash7]Moreover redox promotors such as Fe2+Fe3+are used to improve redox properties of selective oxidationcatalysts [1 8 9]

In catalysis research more often than not reveal-ing reliable structure-activity correlations requires reducing

chemical and structural complexity of metal oxide catalystsMoreover catalytic reactions occur on the surface of thecatalysts while the surface structure may differ significantlyfrom that of the bulk Therefore dispersing metal oxideson well-defined support materials may result in suitablemodel systems Various synthesis procedures have been usedfor dispersing active iron oxide species on suitable supportmaterials However achieving well-dispersed and small oreven isolated iron species on the support remains challenging[3] Nanostructured silica materials such as SBA-15 rep-resent suitable support materials for metal oxide catalysts[10] Furthermore the size of the resulting species can beinfluenced by using various precursors for synthesis [3]

Evolution of structure and function of heterogeneouscatalysts are frequently determined under nonisothermalconditions Hence additional solid-state kinetic analysis ofexperimental data measured under these conditions may be

HindawiJournal of Analytical Methods in ChemistryVolume 2017 Article ID 6205297 13 pageshttpsdoiorg10115520176205297

2 Journal of Analytical Methods in Chemistry

helpful in corroborating structure-activity correlations [11ndash14] Experimental measurements for solid-state kinetic anal-ysis can be performed under either isothermal or nonisother-mal reaction conditions Dependent on reaction conditionsfundamentally different analysismethods are requiredMore-over in contrast to isothermal conditions solid-state kineticinvestigations under nonisothermal conditions require amore complex mathematical analysis In this work we aimedat establishing solid-state kinetic analysis procedures fortreating conventional temperature-programmed reductiondata Although originally intended for analyzing data mea-sured for bulk samples these procedures are shown to beequally useful for treating data measured for supported oxidespecies

For solid-state kinetic analysis of data measured undernonisothermal conditions two approaches can be distin-guished First solid-state kinetic data can be analyzed bymodel-independent Kissinger or isoconversional method ofOzawa Flynn and Wall (OFW) Whereas the Kissingermethod yields one apparent activation energy of the rate-determining step the OFW method yields an evolution ofapparent activation energy as function of reaction degree120572 Model-independent kinetic analysis is not based onany model assumptions consequently the ldquokinetic triplerdquo(apparent activation energy 119864119886 preexponential factor 119860of the Arrhenius-type temperature-dependence of the rateconstant and suitable solid-state reactionmodel119892(120572)) cannotbe identified Therefore a second complementary approachto solid-state kinetic analysis is required Model-dependentsolid-state kinetic analysis employs several solid-state kineticreaction models 119892(120572) After identifying the suitable solid-state reaction model the ldquokinetic triplerdquo can be determined

Here iron oxide catalysts supported on SBA-15 as suitablemodel catalyst for selective oxidation were studied undervarious nonisothermal reaction conditions Influence of ironloading and various precursors on structural and kineticproperties of the catalysts was investigated

2 Experimental

21 Sample Preparation Mesoporous silica SBA-15 was pre-pared according to Zhao et al [10] The surfactant PluronicP123 was dissolved in a mixture of deionized water and HCl(37) and the reaction mixture was stirred at 308K for 24 hTetraethyl orthosilicate (TEOS)was added to the solution andthe reaction mixture was stirred at 308K for 24 h and thenhydrothermally treated in pressure-resistant bottles at 388Kfor 24 h The obtained white solid was filtered washed with amixture of deionized water and ethanol (20 1) air-dried andcalcined Calcination was carried out in three steps (I) 378Kfor 135min (II) 453K for 3 h and (III) 873K for 5 hThe heat-ing rate was kept at 1 Kmin Iron oxides supported on SBA-15were prepared by incipient wetness technique Therefore anaqueous solution of (Fe(III) NH4)-citrate or Fe(III)-nitratewas used After drying in air for 24 h calcination was carriedout at 723K for 2 h According to the iron loading and theused precursor samples were denoted as 25 wt Fe Citrate63 wt Fe Citrate 107 wt Fe Citrate 20 wt Fe Nitrate72 wt Fe Nitrate and 93 wt Fe Nitrate

Furthermore a mechanical mixture of SBA-15 and crys-talline 120572-Fe2O3 (105 wt Fe) was prepared and denoted asFe2O3SBA-15

22 Nitrogen Physisorption Nitrogen adsorptiondesorptionisotherms were measured at 77 K using a BELSORP-mini II(BEL Japan Inc) Prior to measurements the samples werepretreated under reduced pressure (10minus2 kPa) at 368K for35min and kept under the same pressure at 448K for 15 h(BELPREP-vac II)

23 Transmission Electron Microscopy Transmission elec-tron microscopy (TEM) images were recorded on a FEITecnai G2 20 S-TWIN microscope equipped with a LaB6cathode and a 1k times 1k CCD camera (GATAN MS794)Acceleration voltage was set to 220 kV and samples wereprepared on 300mesh Cu grids with Holey carbon film

24 Powder X-Ray Diffraction Powder X-ray diffraction pat-terns were obtained using an XrsquoPert PRO diffractome-ter (PANalytical 40 kV 40mA) in thetatheta geometryequipped with a solid-state multichannel detector (PIXel)Cu K120572 radiation was usedWide-angle diffraction scans werecollected in reflection mode Small-angle diffraction patternswere measured in transmission mode between 04∘ and 6∘ 2120579in steps of 0013∘ 2120579 with a sampling time of 90 sstep

25 Diffuse Reflectance UV-Vis Spectroscopy Diffuse reflec-tance UV-Vis (DR-UV-Vis) spectroscopy was conducted ona two-beam spectrometer (V-670 Jasco) using a bariumsulfate coated integration sphere (scan speed 100 nmminslit width 50 nm (UV-Vis) and 20 nm (NIR) and spectralregion 2000ndash220 nm) SBA-15 was used as white standard forall samples

26 Mossbauer Spectroscopy Zero-field 57Fe Mossbauerspectroscopic measurements were conducted on a transmis-sion spectrometer with sinusoidal velocity sweep Velocitycalibration was done with an 120572-Fe foil at ambient tem-perature Measurements of samples 20 wt Fe Nitrate and72 wt Fe Nitrate were performed using a Janis closed-cycle cryostat with the sample container entirely immersedin Helium exchange gas at 14 and 300K Combined withmeasurements over a time period of about one to twelvedays the helium exchange gas ensured a gradient-free sampletemperature The sample temperature was recorded with acalibrated Si diode located close to the sample containermade of Teflon or PEEK (polyether ether ketone) providinga temperature stability of better than 01 K Additional mea-surements of samples 93 wt Fe Nitrate 72 wt Fe Nitrate20 wt Fe Nitrate and 107 wt Fe Citrate were carriedout on a spectrometer equipped with a Cryovac continuousflow cryostat with comparable specifications geometry andsample environment as described aboveThenominal activityof the Mossbauer sources used was about 50mCi of 57Coin a rhodium matrix Spectra at 4 K were recorded every30 minutes during overall measurement duration EachMossbauer spectrum shown here corresponds to the last

Journal of Analytical Methods in Chemistry 3

spectrum in the respective series Quantitative analysis of therecorded spectra was conducted on basis of the stochasticrelaxationmodel developed by Blume and Tjon [15] in whichthemagnetic hyperfine field119861hf fluctuates randomly betweentwo directions (+119861hf and minus119861hf ) along the symmetry axis ofan axially symmetric electric field gradient tensor Using thismodel is motivated by the observation of a significant linebroadening in particular in the spectra obtained for 72 wtFe Nitrate at intermediate temperatures of ca 60 and 100Ksuggesting the presence of slow relaxation processes withrelaxation times 120591c that are long or of the same order ofmagnitude as the Larmor precession time of the 57Fe nuclearmagnetic moment (ie 10minus6 s lt 120591c lt 10minus8 s) The quadrupoleshift 120576 is given by 11989021199021198764 assuming that 1198902119902119876 ≪ 120583119861hf(constants 120583 119890 119902 and 119876 were used in their usual meaning)The isomer shift 120575 is reported with respect to iron metal atambient temperature and was not corrected in terms of thesecond-order Doppler shift

27 Temperature-Programmed Reduction Temperature-pro-grammed reduction (TPR) was performed using a BELCAT-B (BEL Japan Inc) Samples were placed on silica wool ina silica glass tube reactor Evolving water was trapped usinga molecular sieve (4 A) Gas mixture consisted of 5H2 in95Ar with a total gas flow of 40mlmin Heating ratesused were 5 10 15 and 20Kmin to 1223K A constantinitial sample weight was used and H2 consumption wascontinuously monitored by a thermal conductivity detector

3 Results and Discussion

31 Sample Characterization

311 Nitrogen Physisorption Measurements Fe119909O119910SBA-15samples and support material SBA-15 exhibited type IVnitrogen adsorptiondesorption isotherms indicating meso-porous materials (Figure 1) Adsorption and desorptionbranches were nearly parallel at the hysteresis loop asexpected for regularly shaped pores Both SBA-15 andFe119909O119910SBA-15 samples exhibited high specific surface areaswith narrow pore size distributions Independent of theused precursor low loaded Fe119909O119910SBA-15 samples showedsignificantly higher specific surface areas than higher loadedsamples Compared to SBA-15 all Fe119909O119910SBA-15 samplesshowed a decrease in specific surface area Whereas SBA-15 possessed a BET-surface between 7434 and 7794m2gthose of the Fe119909O119910SBA-15 samples were determined to bebetween 6059 and 7252m2g Pore size distribution wascalculated by the BJH method and revealed a decrease inpore radius from 46 nm of SBA-15 to 40 nm of Fe119909O119910SBA-15 samples This decrease in specific surface area as wellas the decrease in pore radius with increasing iron loadingindicated the presence of iron species in the mesopores ofSBA-15 Moreover transmission electron microscopy (TEM)measurements of the Fe119909O119910SBA-15 samples also indicatedthat iron species were located in the pore system of SBA-15with no iron species detected on the external surface of SBA-15 TEM micrograph of the highest loaded nitrate sample

25 wt Fe_Citrate20wt Fe_Nitrate72 wt Fe_Nitrate

02 04 06 08 1000

Relative pressure pp0

0

100

200

300

400

500

600

700

800

V＞

Ｍ(c

m3

(STP

) gminus1)

Figure 1 Nitrogen adsorptiondesorption isotherms of the samples25 wtFe Citrate (straight lines) 20 wtFe Nitrate (dashed lines)and 72 wt Fe Nitrate (dotted lines)

Figure 2 TEM micrograph of sample 93 wt Fe Nitrate Darkcontrast (arrows) indicates the iron species

93 wt Fe Nitrate is depicted in Figure 2 The dark contrast(arrows in Figure 2) indicated the presence of iron species inthe pore channels of SBA-15

In addition to BET method and BJH method themodified FHH method was used to analyze the nitrogenphysisorption data Herein the fractal dimension 119863119891 wasdetermined as a measure of the roughness of the surface[16 17] For Fe119909O119910SBA-15 samples as well as SBA-15 thefractal dimension was between 2 and 3 This indicated arough surface In order to elucidate the effect of supportediron species on surface roughness of the support materialΔ119863119891 values were calculated as difference from 119863119891 valuesof SBA-15 and those of the corresponding Fe119909O119910SBA-15samples In contrast to the nitrate samples citrate samplespossessed significantly higher values of Δ119863119891 (Tables 1 and2) Therefore compared to those of the nitrate samples the


Table 1 Characteristics of Fe119909O119910SBA-15 samples specific surface area 119886BET (BET method) pore volume 119881Pore and average pore radius119903Pore (BJH method) unit cell parameter119886 (hexagonal pore system) and difference in fractal dimension Δ119863119891 (difference before and afterdeposition of iron species on SBA-15 (Table 2) modified FHHmethod)

Sample 119886119904BETm2g 119881porecm3g 119903porenm 119886nm Δ119863119891

25 wt Fe Citrate 7252 plusmn 07 1112 plusmn 0001 4030 plusmn 0004 1115 plusmn 002 012 plusmn 00263 wt Fe Citrate 6509 plusmn 07 0968 plusmn 0001 4030 plusmn 0004 1102 plusmn 002 021 plusmn 005107 wt Fe Citrate 6057 plusmn 06 0898 plusmn 0001 4030 plusmn 0004 1094 plusmn 002 015 plusmn 00120 wt Fe Nitrate 7030 plusmn 07 1096 plusmn 0001 4030 plusmn 0004 1116 plusmn 001 006 plusmn 00172 wt Fe Nitrate 6478 plusmn 06 0971 plusmn 0001 403 plusmn 0004 1111 plusmn 002 007 plusmn 00193 wt Fe Nitrate 6331 plusmn 06 0939 plusmn 0001 403 plusmn 0004 1110 plusmn 001 minus006 plusmn 002

surface of the citrate samples appeared to be smoother Apossible explanation for the differences in surface roughnessof the support material might be the differently pronouncedchelating effect of the two precursors The citrate precursorshowed a more pronounced chelating effect and thereforestronger bonds between citrate ligands and Fe(III) centralatoms Due to the stronger bonds between citrate ligands andFe(III) atoms polydentate citrate ligands encapsulated theFe(III) ions thereby preventing agglomeration of iron speciesduring calcinationThus after calcination and removal of thecitrate ligands the resulting Fe(III) speciesweremore isolatedand dispersed on the support material Conversely nitrateligands showed minor interactions with the Fe(III) ions dueto the less pronounced chelating effect Therefore nitrateremoval during calcination was facilitated and the resultingFe(III) species readily aggregated and formed less dispersediron oxide species on the support material [16 17]

312 X-Ray Diffraction Figure 3 depicts the small-angleXRD patterns of the Fe119909O119910SBA-15 samples and the mechan-ical mixture Fe2O3SBA-15 Diffraction peaks (10l) (11l)and (20l) correspond to the two-dimensional hexagonalsymmetry of SBA-15 The diffraction peaks were visible forall samples and themechanicalmixture Fe2O3SBA-15Wide-angle X-ray diffraction patterns of the Fe119909O119910SBA-15 samplesshowed no long-range ordered phases indicative of small andisolated iron species (Figure 4) Conversely XRD patternsof the mechanical mixture of SBA-15 and Fe2O3 showeddiffraction peaks of crystalline Fe2O3

313 Diffuse Reflectance UV-Vis Spectroscopy DR-UV-Visspectra of the Fe119909O119910SBA-15 samples are depicted in Fig-ure 5(a) Independent of the utilized precursor a red-shiftand broadening of the absorption bands with increasing ironloading can be seen (Figure 5(a))The red-shift of the absorp-tion and thus a decreasing edge energy with increasingiron loading can be correlated with an aggregation of Fe(III)species [18 19] All Fe119909O119910SBA-15 samples possessed edgeenergy values higher than 21 eV (edge energy in the DR-UV-Vis spectrum of crystalline Fe2O3) Hence the size of thesupported iron species was smaller than that of crystallineFe2O3 in all samples Both citrate samples and nitrate samplesexhibited a decrease in edge energy with increased iron load-ing (Figure 5(b)) However the citrate samples showed higher

25 wt Fe_Citrate63 wt Fe_Citrate107 wt Fe_Citrate20 wt Fe_Nitrate

72 wt Fe_Nitrate93 wt Fe_NitrateFe2O3SBA-15

(10l)

(11l)(20l)

15 20 2510 30

Diffraction angle 2 (∘)

00

02

04

06

08

10

Nor

mal

ized

inte

nsity

Figure 3 Small-angle X-ray diffraction patterns of all Fe119909O119910SBA-15 samples and the mechanical mixture Fe2O3SBA-15

25 wt Fe_Citrate

63 wt Fe_Citrate

107 wt Fe_Citrate

20 wt Fe_Nitrate

72 wt Fe_Nitrate

93 wt Fe_Nitrate

Fe2O3SBA-15

Fe2O30

1

2

3

4

5

6

7

Nor

mal

ized

inte

nsity

20 8010 50 60 7030 40


Figure 4 Wide-angle X-ray diffraction patterns of all Fe119909O119910SBA-15 samples a reference (mechanically mixed SBA-15 and crystallineFe2O3) and crystalline Fe2O3


Table 2 Fractal dimension 119863119891 of all Fe119909O119910SBA-15 samples and corresponding SBA-15 (modified FHH method) and difference in fractaldimension Δ119863119891 between SBA-15 and corresponding Fe119909O119910SBA-15 samples

Sample 119863119891 119863119891 (SBA-15) Δ11986311989125 wt Fe Citrate 2520 plusmn 0009 2637 plusmn 0006 012 plusmn 00263 wt Fe Citrate 2350 plusmn 0042 2563 plusmn 0011 021 plusmn 005107 wt Fe Citrate 2345 plusmn 0039 2497 plusmn 0014 015 plusmn 00120 wt Fe Nitrate 2549 plusmn 0005 2604 plusmn 0004 006 plusmn 00172 wt Fe Nitrate 2550 plusmn 0004 2617 plusmn 0005 007 plusmn 00193 wt Fe Nitrate 2613 plusmn 0009 2557 plusmn 0007 minus006 plusmn 002

25 wt Fe_Citrate63 wt Fe_Citrate20 wt Fe_Nitrate72 wt Fe_Nitrate

4000020000 3000010000

Wavenumber (cmminus1)

00

05

10

15

20

25

30

35

40

Kube

lka-

Mun

k fu

nctio

n

(a)

NitrateCitrateFe2O3SBA-15

2 4 6 80 1210

Iron loading (wt)

20

22

24

26

28

30

32

34

36

DR-

UV-

Vis e

dge e

nerg

y (e

V)

(b)

Figure 5 (a) DR-UV-Vis spectra of 25 wt Fe Citrate (straight line) 20 wt Fe Nitrate (dashed line) 63 wt Fe Citrate (dashed double-dotted line) and 72 wt Fe Nitrate (dotted line) (b) Edge energy as function of iron loading for nitrate samples (circles) citrate samples(squares) and mechanical mixture (square)

edge energy values than the corresponding nitrate samplesTherefore iron species obtained by citrate precursor weresmaller compared to those obtained by nitrate precursor

314 Mossbauer Spectroscopy Mossbauer spectra of 93 wtFe Nitrate and 107 wt Fe Citrate recorded above 200Kshowed a broadened and asymmetric doublet independentof the used precursor Therefore this doublet was analyzedusing two nonequivalent Fe sites The determined values forthe isomer shift 120575 and the quadrupole shift 120576 are consistentwith those reported for superparamagnetic particles of Fe2O3[20 21] At low temperatures that is at 14 K for 93 wtFe Nitrate and at 4K for 107 wt Fe Citrate (Figure 6)the doublet almost disappeared and a magnetically splithyperfine pattern was detected This observation indicatedthe presence of small superparamagnetic iron oxidic speciesThe related Mossbauer parameters (Table 3) are furthermoreconsistent with those reported for (magnetically blocked)superparamagnetic particles with a local geometry similarto Fe2O3 supported on SBA-15 [20] Therefore a blockingtemperature lower than 200K implied an upper limit for theFe species diameter of lt10 nm [22] for 93 wt Fe Nitrate

Conversely the observation of an almost complete blockingat lower temperatures for 107 wt Fe Citrate compared to93 wt Fe Nitrate suggested a significantly smaller speciessize obtained from citrate precursor Furthermore refine-ment of the Mossbauer spectra of 93 wt Fe Nitrate and72 wt Fe Nitrate at 14 K and of 107 wt Fe Citrate at14 K and 4K required an additional component (Table 3)indicating a bimodal particle size distribution

The Mossbauer spectra of the lower loaded nitratesamples 72 wt Fe Nitrate and 20 wt Fe Nitrate alsoexhibited a broadened and asymmetric doublet at 300K withsimilar values for isomer shift and quadrupole splitting asdetermined for 93 wt Fe NitrateWhile this doublet almostcompletely transformed into a magnetically split sextet forsample 93 wt Fe Nitrate at 14 K (vide supra) this trans-formation remained incomplete in the Mossbauer spectra of72 wt Fe Nitrate and 20 wt Fe Nitrate at 14 K (Figure 7)The determined site population ratio of the doublet relativeto themagnetically split sextet signal increased systematicallywith decreasing iron loading from about 2 98 for 93 wtFe Nitrate to 45 55 for 20 wt Fe Nitrate (Table 3) Further-more a similar trend was observed for the determined values


Table 3 Mossbauer parameters for 93 wt Fe Nitrate 72 wt Fe Nitrate 20 wt Fe Nitrate and 107 wt Fe Citrate Temperature 119879isomer shift 120575 (referred to 120572-Fe at 298K and not corrected for 2nd-order Doppler shift) quadrupole shift 120576 line widths ΓHWHM hyperfinemagnetic field 119861hf fluctuation rate ]119888 and area lowast indicates values held fixed in simulation [119886] indicates that relaxation rate reached thedynamic limit

Sample 119879K 120575mms 120576mms ΓHWHMmms 119861hf T ]119862mms Area

93 wt Fe Nitrate

300 0320 (9) 0173 (42) 029 (11) 483lowast [119886] 480327 (8) 0536 (37) 0277 (45) 483lowast [119886] 52

140401 (21) minus0012 (20) 028lowast 465 (27) 013 450465 (11) minus0018 (11) 028lowast 500 (12) 002 520401lowast 043lowast 037lowast 483lowast 310lowast 3

72 wt Fe Nitrate

300 0330 (5) 0299 (15) 0190 (16) 483lowast [119886] 520307 (7) 0508 (27) 0233 (17) 483lowast [119886] 48

140394 (35) minus0014 (43) 023lowast 454 (5) 03 490462 (19) minus0034 (19) 023lowast 497 (2) 01 390431 (72) 0518 (59) 045lowast 483lowast [119886] 12

20 wt Fe Nitrate300 0336 (15) 0346 (78) 0273 (60) 483lowast [119886] 60

0312 (21) 0583 (95) 0265 (71) 483lowast [119886] 40

14 0421lowast 008 (12) 024 (76) 438 (15) 07 550423 (48) 0500 (60) 0437 (80) 483lowast 520 45

107 wt Fe Citrate

300 0294 (12) 0206 (39) 034 (12) 483lowast [119886] 450316 (12) 0672 (50) 0376 (49) 483lowast [119886] 55

14

0451lowast minus0008 (64) 020lowast 435lowast 56 340451 (10) minus0005 (97) 020lowast 435 (7) 05 310438 (15) 0466 (22) 023lowast 483lowast [119886] 250416 (38) 0814 (50) 023lowast 483lowast [119886] 10

4

0497 (62) 0018 (62) 020lowast 489 (5) 005 140424 (47) minus0026 (45) 020lowast 450 (6) 045 810438lowast 047lowast 023lowast 483lowast [119886] 10416lowast 081lowast 023lowast 483lowast [119886] 4

of the local magnetic hyperfine field (ie decreasing 119861hf withdecreasing Fe loading) Assuming that all iron in the nitratesamples consisted of iron oxide both results independentlysuggested a correlation of increasing average iron species sizeand increasing iron loading within the nitrate samples

315 Temperature-Programmed Reduction Figures 8 and9 depict TPR traces of Fe119909O119910SBA-15 samples measuredduring reduction with H2 at a heating rate of 10 KminSignificant differences in reduction profiles are discernibleLowest loaded citrate and nitrate samples possessed onesingle reduction peak Conversely higher loaded citratesamples showed a two-step reduction (not considering a verysmall secondTPRpeak for sample 107 wtFe Citrate) whilehigher loaded nitrate samples showed a three-step reductionThe first reduction step can be assigned to the reductionof Fe(III) oxidic species to Fe(II) oxidic species The smalliron species of the lowest loaded citrate and nitrate sampleinteracted strongly with the surface of SBA-15 preventingfurther reduction in the applied temperature range Hencethese samples showed only one single reduction peak in theTPR profile Conversely the larger iron species in the higherloaded citrate and nitrate samples exhibited further reductionof the Fe(II) species and hence a two-step or even three-step

reduction mechanismThus increasing iron loading resultedin weaker interactions between iron species and supportmaterial

For both nitrate and citrate samples an increasing tem-perature of the first TPR maxima correlated with an increas-ing iron loading Furthermore nitrate samples showed a shiftof the TPR maxima to lower temperatures compared to thecitrate samplesThis shift of the TPRmaxima indicated betterreducibility of the nitrate samples The mechanical mixtureFe2O3SBA-15 exhibited two TPR maxima with a shoulderat the second TPR peak indicating a three-step reduction(Figure 10) TPR traces of the mechanical mixture differedsignificantly from those of the Fe119909O119910SBA-15 samples More-over neither the Fe119909O119910SBA-15 samples nor the mechanicalmixture showed a TPR profile characteristic for crystallineFe2O3 (Figure 10) Differences in the TPR profiles of themechanical mixture and crystalline Fe2O3 resulted fromdifferences in both particle sizes and dispersion of Fe2O3crystallites [23] Dispersion of smaller Fe2O3 crystalliteson SBA-15 in the mechanical mixture compared to pureFe2O3 induced a decreased first TPR peak and a shift of thesecond TPR peak to lower temperature Significantly smallerFe2O3 crystallites of the mechanical mixture correlated witha significantly decreased first reduction peak [23]


Tran

smiss

ion

(arb

uni

ts)

14 K

14 K

4 K

107 wt Fe_Citrate

107 wt Fe_Citrate

93 wt Fe_Nitrate

630 9 12minus6minus9 minus3minus12

Velocity (mms)

Figure 6 Mossbauer spectra of 93 wt Fe Nitrate (top) and107 wt Fe Citrate (middle and bottom) at 14 and 4K Dotsexperimental data lines fit curves based on stochastic Blume-Tjonrelaxation model

Tran

smiss

ion

(arb

uni

ts)

minus9 minus6 minus3minus12 3 6 9 120

Velocity (mms)

14 K

14 K

14 K20 wt Fe_Nitrate

72 wt Fe_Nitrate

93 wt Fe_Nitrate

Figure 7 Mossbauer spectra of 93 wt Fe Nitrate (top) 72 wtFe Nitrate (middle) and 20 wt Fe Nitrate (bottom) at 14 K Dotsexperimental data lines fit curves based on stochastic Blume-Tjonrelaxation model

107 wt Fe_Citrate63 wt Fe_Citrate25 wt Fe_Citrate

800600400 12001000

Temperature (K)

0

5

10

15

20

25

TCD

sign

al (

V)

times102

00

02

04

06

08

10

750 900 1050600

Temperature (K)

Figure 8 TPR traces of 25 wt Fe Citrate (straight line) 63 wtFe Citrate (dashed line) and 107 wt Fe Citrate (dotted line) mea-sured in 5 H2 in 95 argon at 10 Kmin Inset depicts reductiondegree traces with increasing iron loading from left to right

93 wt Fe_Nitrate72 wt Fe_Nitrate20 wt Fe_Nitrate

0

5

10

15

20

25

TCD

sign

al (

V)

800700 900600

Temperature (K)

02

04

06

08

10

800500 600 700400 900300 11001000

Temperature (K)

times102

Figure 9 TPR traces of 20 wt Fe Nitrate (straight line) 72 wtFe Nitrate (dashed line) and 93 wt Fe Nitrate (dotted line) mea-sured in 5 H2 in 95 argon at 10 Kmin Inset depicts reductiondegree traces with increasing iron loading from left to right

32 Reduction Kinetics under Nonisothermal Conditions Inthe following a more detailed solid-state kinetic analysis ofthe reduction traces is presented Besides TPR traces of allnitrate samples those of themechanical mixture and the low-est loaded citrate sample were analyzed After transformingTPR traces to reduction degree 120572 traces model-independentand model-dependent solid-state kinetic analysis methodswere applied


Fe2O3SBA-15Fe2O3

800600400 12001000

Temperature (K)

800700 850750

Temperature (K)

000204 060810

0

2

4

6

8

10

12

TCD

sign

al (

V)

times103

Figure 10 TPR traces of mechanical mixture Fe2O3SBA-15(straight line) and crystalline Fe2O3 (dashed line) measured in 5H2 in 95 argon at 10 Kmin Inset depicts reduction degree trace

All Fe119909O119910SBA-15 samples showed symmetrically shapedTPR profiles This indicates no rate limitation by removal ofthe small amount of H2O formed by reduction of the lowconcentration of iron species on SBA-15 Additionally masstransport limited processes exhibit characteristic apparentactivation energies of less than 10 kJmol [24] Apparentactivation energies for all Fe119909O119910SBA-15 samples were sig-nificantly higher than 10 kJmol Therefore mass transportlimitation of reactant gas H2 was considered to be not rate-limiting in the reduction of Fe119909O119910SBA-15

321 Kissinger Method Apparent activation energy 119864119886 ofthe rate-determining step during reduction was determinedby applying the Kissinger method Therefore ln[1205731198791198982] wasdepicted as function of 1119879119898 [11 25] Here 119879119898 correspondedto the first maximum of the TPR traces (Figures 8ndash10) Fromthe slope of the resulting straight line the apparent activationenergy for the reduction of Fe119909O119910SBA-15 was calculated(Figure 11) The lowest loaded citrate sample possessed thelowest apparent activation energy of 39 plusmn 8 kJmol Thehighest apparent activation energy of 88 plusmn 8 kJmol wascalculated for sample 20 wt Fe Nitrate (Table 4) Increasingthe iron loading of the nitrate samples resulted in a decreasingapparent activation energy of the rate-determining stepduring reduction Moreover results of the Kissinger methodalso correlated with the species size resulting from DR-UV-Vis and Mossbauer spectroscopy Hence increasing size ofthe iron species of the nitrate samples was accompaniedby better reducibility and a decreasing apparent activationenergy of reduction The apparent activation energy of themechanical mixture was calculated to be 59 plusmn 7 kJmol Thislower apparent activation energy compared to the nitratesamples was consistent with a further increased speciessize

Table 4 Apparent activation energy of the rate-determining stepin reduction of iron-containing samples in 5 H2 as determined byKissinger method

Sample 119864119886kJmol25 wt Fe Citrate 39 plusmn 820 wt Fe Nitrate 88 plusmn 872 wt Fe Nitrate 84 plusmn 193 wt Fe Nitrate 62 plusmn 8Fe2O3SBA-15 59 plusmn 7

Linear regression

155 160 165150

1000Tm (Kminus1)

minus115

minus110

minus105

minus100

ln(

T2 m

)

Figure 11 Kissinger plot for 72 wt Fe Nitrate sample extractedfrom TPR traces measured during reduction (5 H2 in 95 argon)

322 Method of Ozawa Flynn and Wall A single apparentactivation energy value resulting from the Kissinger methodmay not be sufficient for a detailed kinetic analysis of asolid-state reaction Therefore the isoconversional model-independent OFW method was applied for determining theevolution of the apparent activation energy of the rate-determining step as function of reduction degree 120572 [11 26ndash28] Reduction degree 120572 traces were extracted by integrationof the TPR traces measured at various heating rates 120573First temperatures 119879120572120573 for defined reduction degrees 120572 weredetermined from the experimental 120572 traces at various heatingrates Temperatures 119879120572120573 were determined for reductiondegrees in the range of 01 and 08 with Δ120572 = 01 Seconddecade logarithm of the heating rate as function of 1000119879120572120573for the different reduction degrees was calculated based on

log (120573) = log(119860120572119864119886120572119892 (120572) 119877) minus 2315 minus 0457 119864119886120572119877119879120572120573 (1)

with heating rate 120573 preexponential (frequency) factor 119860120572 atreduction degrees 120572 apparent activation energy at reductiondegrees 120572 119864119886120572 integral solid-state reaction model 119892(120572) gasconstant119877 and temperatures119879120572120573 Figure 12 shows the result-ing straight lines for heating rates of 5 10 15 and 20Kminand various reduction degrees 120572 Linear regression of theresulting straight lines resulted in apparent activation energyas a function of reduction degree 120572 Because of 119864119886120572119877119879120572120573 lt


= 01

= 08

06

08

10

12

14

log(

)

180145 150 155 160 165 175170140135

1000T (Kminus1)

Figure 12 Logarithmic heating rate 120573 as function of reciprocaltemperature for the reduction of 72 wt Fe Nitrate in 5H2 in 95argon and reduction degree range from 01 to 08 (OFWmethod)

72 wt Fe_Nitrate20 wt Fe_Nitrate

25 wt Fe_CitrateFe2O3SBA-15

02 04 06 08 1000

0

20

40

60

80

100

120

140

160

180

Ea

(kJm

ol)

Figure 13 Apparent activation energy 119864119886 as function of reductiondegree 120572 for the reduction of 25 wt Fe Citrate (circles) 20 wtFe Nitrate (triangles) 72 wt Fe Nitrate (squares) and Fe2O3SBA-15 (pentagons) in 5 H2 in 95 argon (with Senum-Yang approxi-mation) Apparent activation energies as determined fromKissingermethod are indicated at 120572 = 0 (stars)

20 the apparent activation energy was corrected accordingto Senum-Yang [11 26] The resulting apparent activationenergy together with the apparent activation energy deter-mined by Kissinger method is depicted in Figure 13

The apparent activation energy obtained from theKissingermethod for samples 25 wt Fe Citrate and 20 wtFe Nitrate agreed with the apparent activation energyobtained from the OFW method (Figure 13) Furthermoreapparent activation energies119864119886(120572) of the lowest loaded citrateand nitrate samples were invariant in the 120572 range withinthe error limits Thus a single-step reduction mechanismwas assumed for the lowest loaded Fe119909O119910SBA-15 samples

corresponding to the single reduction peak in the TPRprofiles of these samples (Figures 8 and 9) Such a reactionmechanism is more similar to homogeneous kinetics thanto complex heterogeneous kinetics Compared to the lowestloaded citrate and nitrate samples 72 wt Fe Nitrate differednot only in the higher apparent activation energy values butalso in the evolution of the apparent activation energy asfunction of reduction degree The increase of the apparentactivation energy may indicate a change in rate-determiningstep during a more complex reduction mechanism [29]Moreover such a more complex reduction mechanism cor-related with the multistep TPR profile due to the presenceof larger weakly interacting iron species for sample 72 wtFe Nitrate (Figure 9)

323 Coats-Redfern Method In addition to the model-independent Kissinger and OFW methods the model-dependent Coats-Redfern [30] method provided a comple-mentary analysis of nonisothermal kinetic data Comparedto a model-independent kinetic analysis model-dependentanalysis enables a more detailed characterization of thereaction mechanism Here resulting activation energies arebased on assuming a suitable solid-state kinetic model TheCoats-Redfern method can be expressed by

ln(119892 (120572)1198792 ) = ln( 119860119877120573119864119886 [1 minus (2119877119879119864119886 )]) minus 119864119886

119877119879 (2)

with the integral solid-state reaction model 119892(120572) tempera-ture 119879 heating rate 120573 apparent activation energy of rate-determining step 119864119886 gas constant 119877 and preexponential(frequency) factor A Plotting ln[119892(120572)1198792] as function ofreciprocal temperature results in straight lines for suitablesolid-state reaction models Linear regression was conductedto determine the apparent activation energy Here onlyreaction models 119892(120572) resulting in both suitable apparentactivation energies and good linear regressions were selectedfor further analysis [30 31]

For the reduction of 25 wt Fe Citrate 20 wtFe Nitrate 72 wt Fe Nitrate and the mechanical mixtureFe2O3SBA-15 reduction degree 120572 curves were analyzedApplied solid-state reaction models were nucleation modelsincluding power law models (P) and Avrami-Erofeyevmodels (A) as well as the autocatalytic Prout-Tompkinsmodel (B1) Furthermore diffusion models (D) geometricalcontractionmodels (R) and reaction order-basedmodels (F)were tested [31] D4 F1 A2 R2 and B1 solid-state reactionmodels revealed wide linear ranges by plotting ln[119892(120572)1198792]as function of reciprocal temperature for sample 25 wtFe Citrate Apparent activation energies for those modelsas obtained from the slope of the resulting straight lines aregiven in Table 5

Compared to the results of the Kissinger and OFWmeth-ods apparent activation energies at different heating rateswere significantly higher for the D4 model and significantlylower for the A2 model Hence D4 and A2 reaction modelswere not considered for further analysis The B1 model (ieProut-Tompkins model) yielded apparent activation energiessimilar to those obtained from Kissinger and OFWmethods


Table 5 Apparent activation energy of reduction of sample 25 wt Fe Citrate in 5 H2 at various heating rates depending on the appliedsolid-state kinetic reaction model

Heating rateKmin 119864119886kJmolB1 R2 A2 D4 F1

5 438 plusmn 02 657 plusmn 001 326 plusmn 003 1389 plusmn 01 750 plusmn 0110 416 plusmn 03 657 plusmn 01 319 plusmn 003 1404 plusmn 03 737 plusmn 0120 546 plusmn 03 655 plusmn 01 357 plusmn 01 1421 plusmn 02 779 plusmn 03

However the autocatalysis B1 model assumes that defectsformed at the reaction interface during nuclei growth furthercatalyze and hence accelerate the reaction This conceptappears hardly applicable to Fe119909O119910SBA-15 samples withdispersed Fe species located in a nanostructured pore systemTherefore the B1 model was also not further consideredSimilar constraints hold for the R2 model The R2 reactionmodel is described as geometrical contracting model inwhich nucleation occurs on the surface of the cylindricalcrystal Thus the reaction rate is determined by the decreas-ing interface area between reactant and product phase duringreaction [31] Again such a concept seems not applicable forsmall and dispersed iron species on the surface of poroussupport Consequently the F1 model was chosen as suitablereaction model for the lowest loaded citrate and nitratesamples as well as for sample 72 wt Fe Nitrate

The first-order reaction model (F1 Mampel model)describes solid-state reactions with a large number of nucle-ation sites resulting in fast nucleation Apparently reductionof Fe119909O119910SBA-15 samples was inhibited neither by limitedmobility of reactants nor by increasing product layer Order-based reaction models are the simplest solid-state reactionmodels similar to those used in homogeneous kinetics whereions in solution interact weakly with each other [31 32]Because the Fe(III) species of the Fe119909O119910SBA-15 samplesconstituted small and isolated nucleation sites the F1 modelcan be readily applied to these samples

For the mechanical mixture Fe2O3SBA-15 an R3 modelwas a suitable reaction model The R3 model is denoted ascontracting volume model with nucleation occurring rapidlyon the surface of the particles This reaction model wasconsistent with a mixture of Fe2O3 crystallites and SBA-15material as obtained by conventional sample characteriza-tion

324 JMAK Kinetics In order to enable a geometrical de-scription of the reduction reaction under nonisothermal con-ditions Johnson-Mehl-Avrami-Kolmogorov (JMAK) kineticanalysis was applied [33 34] JMAK kinetics are based on thefollowing equation

ln [minus ln (1 minus 120572)] = minus119899 ln (120573) minus 1052119898119864119877119879 + Const (3)

with heating rate 120573 apparent activation energy of the rate-determining step 119864 temperature119879 gas constant 119877 reductiondegree 120572 topological dimension m and Avrami exponentn Plotting ln[minus ln(1 minus 120572)] as function of reciprocal tem-perature at different heating rates resulted in straight lines(Figure 14(a)) From the slope of the resulting straight lines

the topological dimension 119898 can be determined Here theapparent activation energy obtained by the Kissinger methodwas inserted in (3) Based on (3) the Avrami exponent 119899 isderived according to

minus119899 = 119889 ln [minus ln (1 minus 120572)]119889 [ln (120573)]

100381610038161003816100381610038161003816100381610038161003816119879 (4)

with Avrami exponent 119899 reduction degree 120572 heating rate120573 and temperature 119879 Thus values of ln[minus ln(1 minus 120572)] werecalculated at fixed temperatures and plotted as function ofln(120573) Temperature intervals were equidistant The slopesof the resulting straight lines (Figure 14(b)) were used todetermine the Avrami exponents Plotting ln[minus ln(1 minus 120572)]as function of reciprocal temperature did not afford straightlines for sample 25 wt Fe CitrateTherefore JMAKkineticswere not applied to the data of this sample Topologicaldimension and Avrami exponent as function of temperatureand heating rate for sample 72 wt Fe Nitrate and 20 wtFe Nitrate are depicted in Figures 15 and 16 Topologicaldimension and Avrami exponent for both samples were oneA topological dimension of one corresponded to linear andone-dimensional iron species in these nitrate samples One-dimensionality was consistent with the iron species beingin the pore system of SBA-15 At 119899 = 119898 = 1 thereduction mechanism is governed by site saturation Thus atthe beginning of the reduction nucleation sites either alreadyexisted or were formed immediately

The Coats-Redfern method identified the F1 Mampeland solid-state kinetic reaction model being suitable todescribe the kinetic data The Mampel model is consistentwith the assumption of site saturationMoreover theMampelmodel represents an exception of the Avrami-Erofeyevmodelwith an Avrami exponent of 119899 = 1 Hence results fromJMAK kinetic analysis and model-dependent Coats-Redfernmethod agreed well for the nitrate samples

Themechanicalmixture Fe2O3SBA-15 exhibited a highertopological dimension Topological dimension as functionof the heating rate ranged between 2 and 3 (Figure 17)This increase in topological dimension correlated with thepresence of Fe2O3 crystallites in this sample The mechanicalmixture exhibited Fe2O3 crystallites mixed with the supportmaterial Model-dependent Coats-Redfern method identi-fied the geometrical contraction model R3 being a suitablereaction model Therefore three-dimensional reduction wascompatible with a rapid nucleation on the Fe2O3 crystallitesThus for the mechanical mixture Fe2O3SBA-15 results frommodel-dependent Coats-Redfern analysis were confirmed bythe JMAK analysis


5Kmin10 Kmin

15 Kmin20 Kmin

180160 165 170 175155150

1000T (Kminus1)

minus3

minus2

minus1

0

ln[minus

ln(1

minus

)]

(a)

645K623 K602 K

583 K565K

21 2814

ln()

minus3

minus2

minus1

0

1

ln[minus

ln(1

minus

)]

(b)

Figure 14 (a) ln[minusln(1 minus120572)] as function of 1000119879 according to JMAK kinetics for determining the topological dimension of the reduction of72 wt Fe Nitrate (5H2 in 95 argon) (b) ln[minusln(1 minus120572)] as function of ln(120573) according to JMAK kinetics in order to determine the Avramiexponent for sample 72 wt Fe Nitrate

4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

13

12

11

10

09

08

Topo

logi

cal d

imen

sionm

580 600 620 640 660560

Temperature (K)

04

06

08

10

12

14

Avra

mi e

xpon

entn

Figure 15 Topological dimension and Avrami exponent fromJMAK kinetic analysis as function of temperature and heating ratefor sample 72 wt Fe Nitrate

33 Correlation between Sample Characterization and Solid-State Kinetic Analysis Results from sample characterizationagreed well with those from solid-state kinetic analysis ofthe Fe119909O119910SBA-15 samples An increasing species size withincreasing iron loading (DR-UV-Vis and Mossbauer spec-troscopy) correlated with a decreasing apparent activationenergy of reduction for the nitrate samples Conversely smalliron species resulting from (Fe(III) NH4)-citrate precursorcoincided with the lowest apparent activation energy forthe reduction of 25 wt Fe Citrate Sample characterizationanalysis methods identified the Fe(III) species as beingisolated in the pore system of SBA-15 and interacting weaklywith each other Even for the higher loaded samples with

4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

20

18

16

14

12

10

0802

04

06

08

10

12

14

16

18

20

Avra

mi e

xpon

entn

600 625 700 725650 675575

Temperature (K)


more aggregated Fe119898O119899-nanoclusters weakly interacting andwell-dispersed Fe(III) species can be assumed With respectto the kinetic analysis iron species in the pores of SBA-15react similar to isolated ions in a homogeneous solutionAccordingly a first-order reaction model (Mampel model)was suited best to describe the similarity of the Fe119909O119910SBA-15 samples and homogeneous systems Additionally JMAKkinetics were consistent with a one-dimensional reduction ofFe species localized in the pore system of SBA-15

Not only for the Fe119909O119910SBA-15 samples but also forthe mechanical mixture Fe2O3SBA-15 results from samplecharacterization agreed with those from kinetic analysisAccording to JMAK analysis the fraction of crystalline


4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

00

05

15

20

25

30

35

40

10

00

05

10

15

20

25

30

35

40

Avra

mi e

xpon

entn

700 750 800650600

Temperature (K)

Figure 17 Topological dimension and Avrami exponent fromJMAK kinetic analysis as function of temperature and heating ratefor the mechanical mixture Fe2O3SBA-15

Fe2O3 in Fe2O3SBA-15 as detected by XRD resulted inthree-dimensional reduction kinetics Hence reduction wasgoverned by rapid nucleation in the three-dimensional Fe2O3crystallites This was confirmed by the model-dependentanalysis yielding a contracting volumemodel (R3) with rapidnucleation occurring on the surface of the Fe2O3 crystallitesas suitable model for the rate-determining step in reduction

Apparently for both supported systems and the mechan-ical mixture the results of conventional characterizationand solid-state kinetic analysis corroborated each other Thisshowed that the concept of solid-state kinetic analysis (ienonisothermal reaction conditions and model-dependent aswell as model-independent methods) can be successfullyapplied to supported systems in addition to conventional bulkmaterials Time- and temperature-dependent measurementssuch as TPR or TGDTA are readily used in characterizingsupported materials Those techniques however yield littleto no structural details of the supported species Hencesolid-state kinetic analysis of the already available data cangive additional information without additional experimentaleffort

4 Conclusions

Iron oxides supported on SBA-15 were successfully syn-thesized using two different precursors (Fe(III)-nitrate and(Fe(III) NH4)-citrate) Independent of the precursor anincreasing size of iron species correlated with an increas-ing iron loading For all Fe119909O119910SBA-15 samples a long-range ordering of iron oxidic species was excluded Fe(III)-nitrate precursor induced larger iron oxide species Con-versely (Fe(III) NH4)-citrate precursor resulted in smalleriron species accompanied by more distinct smoothing ofthe SBA-15 surface Temperature-programmed reductionof the Fe119909O119910SBA-15 samples revealed better reducibilityof the nitrate samples compared to the citrate samplesThe lowest loaded nitrate and citrate sample possessed a

single-step reduction mechanism Conversely higher loadedFe119909O119910SBA-15 samples revealed a more complex multistepreduction mechanism

Solid-state kinetic analysis using model-dependent andmodel-independent methods demonstrated their applicabil-ity to dispersed iron species on a high surface area supportmaterial Iron species obtained from the lowest loaded citrateprecursor exhibited the lowest apparent activation energy Inthe series of nitrate samples a decreasing apparent activationenergy and an increasing size of the iron species correlatedwith an increasing iron loading Coats-Redfern methodidentified the Mampel reaction model as suitable to accountfor the rate-determining step in reduction Moreover sitesaturation as suggested by the Mampel reaction model wasconsistent with the results of JMAK analysis (119899 = 119898 = 1)

Conflicts of Interest

The authors declare that there are no conflicts of interestregarding the publication of this paper

Acknowledgments

M Broring and F J Litterst at the TU Braunschweig areacknowledged for providing access to the 57Fe Mossbauerequipment The authors are grateful to A Muller and SSchwarz for assistance during solid-state kinetics and N2physisorption measurements respectively and to S Selve atZELMI (TU Berlin) for TEMmeasurements

References

[1] U S Ozkan and R B Watson ldquoThe structure-function rela-tionships in selective oxidation reactions over metal oxidesrdquoCatalysis Today vol 100 no 1-2 pp 101ndash114 2005

[2] Y Y Sun S Walspurger J-P Tessonnier B Louis and JSommer ldquoHighly dispersed iron oxide nanoclusters supportedon ordered mesoporous SBA-15 a very active catalyst forFriedel-Crafts alkylationsrdquo Applied Catalysis A General vol300 no 1 pp 1ndash7 2006

[3] Z Gabelica A Charmot R Vataj R Soulimane J Barraultand S Valange ldquoThermal degradation of iron chelate complexesadsorbed on mesoporous silica and aluminardquo Journal of Ther-mal Analysis and Calorimetry vol 95 no 2 pp 445ndash454 2009

[4] M Oschatz W S Lamme J Xie A I Dugulan and KP de Jong ldquoOrdered Mesoporous Materials as Supports forStable Iron Catalysts in the FischerndashTropsch Synthesis of LowerOlefinsrdquo ChemCatChem vol 8 no 17 pp 2846ndash2852 2016

[5] H M Torres Galvis A C J Koeken J H Bitter et al ldquoEffectof precursor on the catalytic performance of supported ironcatalysts for the Fischer-Tropsch synthesis of lower olefinsrdquoCatalysis Today vol 215 pp 95ndash102 2013

[6] Y Q Jiang K F Lin Y N Zhang et al ldquoFe-MCM-41nanoparticles as versatile catalysts for phenol hydroxylation andfor Friedel-Crafts alkylationrdquo Applied Catalysis A General vol445-446 pp 172ndash179 2012

[7] A S Al-Fatesh A H Fakeeha A A Ibrahim et al ldquoIron OxideSupported on Al2O3 Catalyst for Methane Decomposition


Reaction Effect of MgO Additive and Calcination Tempera-turerdquo Journal of the Chinese Chemical Society vol 63 no 2 pp205ndash212 2016

[8] J C Vedrine G Coudurier and J-M M Millet ldquoMoleculardesign of active sites in partial oxidation reactions on metallicoxidesrdquo Catalysis Today vol 33 no 1-3 pp 3ndash13 1997

[9] B Grzybowska-Swierkosz ldquoThirty years in selective oxidationon oxides What have we learnedrdquo Topics in Catalysis vol 11-12 no 1-4 pp 23ndash42 2000

[10] D Zhao J Feng Q Huo et al ldquoTriblock copolymer synthesesof mesoporous silica with periodic 50 to 300 angstrom poresrdquoScience vol 279 no 5350 pp 548ndash552 1998

[11] A Khawam and D R Flanagan ldquoBasics and applications ofsolid-state kinetics a pharmaceutical perspectiverdquo Journal ofPharmaceutical Sciences vol 95 no 3 pp 472ndash498 2006

[12] S Vyazovkin and C A Wight ldquoKinetics in Solidsrdquo AnnualReview of Physical Chemistry vol 48 no 1 pp 125ndash149 1997

[13] A Khawam and D R Flanagan ldquoRole of isoconversionalmethods in varying activation energies of solid-state kineticsI isothermal kinetic studiesrdquoThermochimica Acta vol 429 no1 pp 93ndash102 2005

[14] S Vyazovkin ldquoKinetic concepts of thermally stimulated reac-tions in solids A view from a historical perspectiverdquo Interna-tional Reviews in Physical Chemistry vol 19 no 1 pp 45ndash602000

[15] M Blume and J A Tjon ldquoMossbauer spectra in a fluctuatingenvironmentrdquoPhysical ReviewAAtomicMolecular andOpticalPhysics vol 165 no 2 pp 446ndash456 1968

[16] P Pfeifer Y J Wu M W Cole and J Krim ldquoMultilayeradsorption on a fractally rough surfacerdquoPhysical Review Lettersvol 62 no 17 pp 1997ndash2000 1989

[17] M A Smith and R F Lobo ldquoA fractal description of porestructure in block-copolymer templated mesoporous silicatesrdquoMicroporous andMesoporousMaterials vol 131 no 1-3 pp 204ndash209 2010

[18] R S Weber ldquoEffect of local structure on the UV-visibleabsorption edges of molybdenum oxide clusters and supportedmolybdenum oxidesrdquo Journal of Catalysis vol 151 no 2 pp470ndash474 1995

[19] J He Y Li D An Q Zhang and Y Wang ldquoSelective oxidationof methane to formaldehyde by oxygen over silica-supportediron catalystsrdquo Journal of Natural Gas Chemistry vol 18 no 3pp 288ndash294 2009

[20] L A Cano M V Cagnoli N A Fellenz et al ldquoFischer-Tropschsynthesis Influence of the crystal size of iron active species onthe activity and selectivityrdquo Applied Catalysis A General vol379 no 1-2 pp 105ndash110 2010

[21] F Arena G Gatti G Martra et al ldquoStructure and reactivityin the selective oxidation of methane to formaldehyde of low-loaded FeOxSiO2 catalystsrdquo Journal of Catalysis vol 231 no 2pp 365ndash380 2005

[22] W Kundig H Bommel G Constabaris and R H LindquistldquoSome properties of supported small 120572-Fe2O3 particles deter-mined with the mossbauer effectrdquo Physical Review A AtomicMolecular and Optical Physics vol 142 no 2 pp 327ndash333 1966

[23] J-Y Park Y-J Lee P K Khanna K-W Jun J W Bae and Y HKim ldquoAlumina-supported iron oxide nanoparticles as Fischer-Tropsch catalysts Effect of particle size of iron oxiderdquo Journalof Molecular Catalysis A Chemical vol 323 no 1-2 pp 84ndash902010

[24] T Ressler J Wienold R E Jentoft O Timpe and T NeisiusldquoSolid state kinetics of the oxidation of MoO2 investigatedby time-resolved X-ray absorption spectroscopyrdquo Solid StateCommunications vol 119 no 3 pp 169ndash174 2001

[25] H E Kissinger ldquoReaction kinetics in differential thermalanalysisrdquo Analytical Chemistry vol 29 no 11 pp 1702ndash17061957

[26] B Jankovic ldquoKinetic analysis of the nonisothermal decompo-sition of potassium metabisulfite using the model-fitting andisoconversional (model-free) methodsrdquo Chemical EngineeringJournal vol 139 no 1 pp 128ndash135 2008

[27] J H Flynn ldquoThe isoconversional method for determinationof energy of activation at constant heating rates - Correctionsfor the Doyle approximationrdquo Journal of Thermal Analysis andCalorimetry vol 27 no 1 pp 95ndash102 1983

[28] T J Ozawa ldquoKinetic analysis of derivative curves in thermalanalysisrdquo Journal of Thermal Analysis and Calorimetry vol 2no 3 pp 301ndash324 1970

[29] M Khachani A El Hamidi M Kacimi M Halim and SArsalane ldquoKinetic approach of multi-step thermal decomposi-tion processes of iron(III) phosphate dihydrate FePO4sdot2H2OrdquoThermochimica Acta vol 610 pp 29ndash36 2015

[30] A W Coats and J P Redfern ldquoKinetic parameters fromthermogravimetric datardquo Nature vol 201 no 4914 pp 68-691964

[31] A Khawam and D R Flanagan ldquoSolid-state kinetic modelsbasics and mathematical fundamentalsrdquoThe Journal of PhysicalChemistry B vol 110 no 35 pp 17315ndash17328 2006

[32] A J Smith L O Garciano T Tran and M S WainwrightldquoStructure and kinetics of leaching for the formation of skeletal(raney) cobalt catalystsrdquo Industrial amp Engineering ChemistryResearch vol 47 no 5 pp 1409ndash1415 2008

[33] E Lorente J A Pena and J Herguido ldquoKinetic study of theredox process for separating and storing hydrogen Oxidationstage and ageing of solidrdquo International Journal of HydrogenEnergy vol 33 no 2 pp 615ndash626 2008

[34] K Matusita T Komatsu and R Yokota ldquoKinetics of non-isothermal crystallization process and activation energy forcrystal growth in amorphous materialsrdquo Journal of MaterialsScience vol 19 no 1 pp 291ndash296 1984

Submit your manuscripts athttpswwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Inorganic ChemistryInternational Journal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 201

International Journal ofInternational Journal ofPhotoenergy


Carbohydrate Chemistry

International Journal ofInternational Journal of


Journal of

Chemistry


Advances in

Physical Chemistry

Hindawi Publishing Corporationhttpwwwhindawicom

Analytical Methods in Chemistry

Journal of

Volume 2014

Bioinorganic Chemistry and ApplicationsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

SpectroscopyInternational Journal of


The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Medicinal ChemistryInternational Journal of


Chromatography Research International


Applied ChemistryJournal of



Theoretical ChemistryJournal of


Journal of

Spectroscopy

Analytical ChemistryInternational Journal of


Journal of


Quantum Chemistry


Organic Chemistry International

ElectrochemistryInternational Journal of



CatalystsJournal of


helpful in corroborating structure-activity correlations [11ndash14] Experimental measurements for solid-state kinetic anal-ysis can be performed under either isothermal or nonisother-mal reaction conditions Dependent on reaction conditionsfundamentally different analysismethods are requiredMore-over in contrast to isothermal conditions solid-state kineticinvestigations under nonisothermal conditions require amore complex mathematical analysis In this work we aimedat establishing solid-state kinetic analysis procedures fortreating conventional temperature-programmed reductiondata Although originally intended for analyzing data mea-sured for bulk samples these procedures are shown to beequally useful for treating data measured for supported oxidespecies

For solid-state kinetic analysis of data measured undernonisothermal conditions two approaches can be distin-guished First solid-state kinetic data can be analyzed bymodel-independent Kissinger or isoconversional method ofOzawa Flynn and Wall (OFW) Whereas the Kissingermethod yields one apparent activation energy of the rate-determining step the OFW method yields an evolution ofapparent activation energy as function of reaction degree120572 Model-independent kinetic analysis is not based onany model assumptions consequently the ldquokinetic triplerdquo(apparent activation energy 119864119886 preexponential factor 119860of the Arrhenius-type temperature-dependence of the rateconstant and suitable solid-state reactionmodel119892(120572)) cannotbe identified Therefore a second complementary approachto solid-state kinetic analysis is required Model-dependentsolid-state kinetic analysis employs several solid-state kineticreaction models 119892(120572) After identifying the suitable solid-state reaction model the ldquokinetic triplerdquo can be determined

Here iron oxide catalysts supported on SBA-15 as suitablemodel catalyst for selective oxidation were studied undervarious nonisothermal reaction conditions Influence of ironloading and various precursors on structural and kineticproperties of the catalysts was investigated

2 Experimental

21 Sample Preparation Mesoporous silica SBA-15 was pre-pared according to Zhao et al [10] The surfactant PluronicP123 was dissolved in a mixture of deionized water and HCl(37) and the reaction mixture was stirred at 308K for 24 hTetraethyl orthosilicate (TEOS)was added to the solution andthe reaction mixture was stirred at 308K for 24 h and thenhydrothermally treated in pressure-resistant bottles at 388Kfor 24 h The obtained white solid was filtered washed with amixture of deionized water and ethanol (20 1) air-dried andcalcined Calcination was carried out in three steps (I) 378Kfor 135min (II) 453K for 3 h and (III) 873K for 5 hThe heat-ing rate was kept at 1 Kmin Iron oxides supported on SBA-15were prepared by incipient wetness technique Therefore anaqueous solution of (Fe(III) NH4)-citrate or Fe(III)-nitratewas used After drying in air for 24 h calcination was carriedout at 723K for 2 h According to the iron loading and theused precursor samples were denoted as 25 wt Fe Citrate63 wt Fe Citrate 107 wt Fe Citrate 20 wt Fe Nitrate72 wt Fe Nitrate and 93 wt Fe Nitrate

Furthermore a mechanical mixture of SBA-15 and crys-talline 120572-Fe2O3 (105 wt Fe) was prepared and denoted asFe2O3SBA-15

22 Nitrogen Physisorption Nitrogen adsorptiondesorptionisotherms were measured at 77 K using a BELSORP-mini II(BEL Japan Inc) Prior to measurements the samples werepretreated under reduced pressure (10minus2 kPa) at 368K for35min and kept under the same pressure at 448K for 15 h(BELPREP-vac II)

23 Transmission Electron Microscopy Transmission elec-tron microscopy (TEM) images were recorded on a FEITecnai G2 20 S-TWIN microscope equipped with a LaB6cathode and a 1k times 1k CCD camera (GATAN MS794)Acceleration voltage was set to 220 kV and samples wereprepared on 300mesh Cu grids with Holey carbon film

24 Powder X-Ray Diffraction Powder X-ray diffraction pat-terns were obtained using an XrsquoPert PRO diffractome-ter (PANalytical 40 kV 40mA) in thetatheta geometryequipped with a solid-state multichannel detector (PIXel)Cu K120572 radiation was usedWide-angle diffraction scans werecollected in reflection mode Small-angle diffraction patternswere measured in transmission mode between 04∘ and 6∘ 2120579in steps of 0013∘ 2120579 with a sampling time of 90 sstep

25 Diffuse Reflectance UV-Vis Spectroscopy Diffuse reflec-tance UV-Vis (DR-UV-Vis) spectroscopy was conducted ona two-beam spectrometer (V-670 Jasco) using a bariumsulfate coated integration sphere (scan speed 100 nmminslit width 50 nm (UV-Vis) and 20 nm (NIR) and spectralregion 2000ndash220 nm) SBA-15 was used as white standard forall samples

26 Mossbauer Spectroscopy Zero-field 57Fe Mossbauerspectroscopic measurements were conducted on a transmis-sion spectrometer with sinusoidal velocity sweep Velocitycalibration was done with an 120572-Fe foil at ambient tem-perature Measurements of samples 20 wt Fe Nitrate and72 wt Fe Nitrate were performed using a Janis closed-cycle cryostat with the sample container entirely immersedin Helium exchange gas at 14 and 300K Combined withmeasurements over a time period of about one to twelvedays the helium exchange gas ensured a gradient-free sampletemperature The sample temperature was recorded with acalibrated Si diode located close to the sample containermade of Teflon or PEEK (polyether ether ketone) providinga temperature stability of better than 01 K Additional mea-surements of samples 93 wt Fe Nitrate 72 wt Fe Nitrate20 wt Fe Nitrate and 107 wt Fe Citrate were carriedout on a spectrometer equipped with a Cryovac continuousflow cryostat with comparable specifications geometry andsample environment as described aboveThenominal activityof the Mossbauer sources used was about 50mCi of 57Coin a rhodium matrix Spectra at 4 K were recorded every30 minutes during overall measurement duration EachMossbauer spectrum shown here corresponds to the last








02 04 06 08 1000


0

100

200

300

400

500

600

700

800

V＞

Ｍ(c

m3

(STP

) gminus1)














(10l)

(11l)(20l)

15 20 2510 30


00

02

04

06

08

10

Nor

mal

ized

inte

nsity


25 wt Fe_Citrate

63 wt Fe_Citrate

107 wt Fe_Citrate

20 wt Fe_Nitrate

72 wt Fe_Nitrate

93 wt Fe_Nitrate

Fe2O3SBA-15

Fe2O30

1

2

3

4

5

6

7

Nor

mal

ized

inte

nsity

20 8010 50 60 7030 40







4000020000 3000010000


00

05

10

15

20

25

30

35

40

Kube

lka-

Mun

k fu

nctio

n

(a)


2 4 6 80 1210

Iron loading (wt)

20

22

24

26

28

30

32

34

36

DR-

UV-

Vis e

dge e

nerg

y (e

V)

(b)









93 wt Fe Nitrate

300 0320 (9) 0173 (42) 029 (11) 483lowast [119886] 480327 (8) 0536 (37) 0277 (45) 483lowast [119886] 52


72 wt Fe Nitrate

300 0330 (5) 0299 (15) 0190 (16) 483lowast [119886] 520307 (7) 0508 (27) 0233 (17) 483lowast [119886] 48



0312 (21) 0583 (95) 0265 (71) 483lowast [119886] 40

14 0421lowast 008 (12) 024 (76) 438 (15) 07 550423 (48) 0500 (60) 0437 (80) 483lowast 520 45

107 wt Fe Citrate

300 0294 (12) 0206 (39) 034 (12) 483lowast [119886] 450316 (12) 0672 (50) 0376 (49) 483lowast [119886] 55

14


4







Tran

smiss

ion

(arb

uni

ts)

14 K

14 K

4 K

107 wt Fe_Citrate

107 wt Fe_Citrate

93 wt Fe_Nitrate


Velocity (mms)


Tran

smiss

ion

(arb

uni

ts)


Velocity (mms)

14 K

14 K


72 wt Fe_Nitrate

93 wt Fe_Nitrate



800600400 12001000

Temperature (K)

0

5

10

15

20

25

TCD

sign

al (

V)

times102

00

02

04

06

08

10

750 900 1050600

Temperature (K)



0

5

10

15

20

25

TCD

sign

al (

V)

800700 900600

Temperature (K)

02

04

06

08

10

800500 600 700400 900300 11001000

Temperature (K)

times102




Fe2O3SBA-15Fe2O3

800600400 12001000

Temperature (K)

800700 850750

Temperature (K)

000204 060810

0

2

4

6

8

10

12

TCD

sign

al (

V)

times103






Linear regression

155 160 165150

1000Tm (Kminus1)

minus115

minus110

minus105

minus100

ln(

T2 m

)






= 01

= 08

06

08

10

12

14

log(

)

180145 150 155 160 165 175170140135

1000T (Kminus1)




02 04 06 08 1000

0

20

40

60

80

100

120

140

160

180

Ea

(kJm

ol)






ln(119892 (120572)1198792 ) = ln( 119860119877120573119864119886 [1 minus (2119877119879119864119886 )]) minus 119864119886

119877119879 (2)
















100381610038161003816100381610038161003816100381610038161003816119879 (4)





5Kmin10 Kmin

15 Kmin20 Kmin

180160 165 170 175155150

1000T (Kminus1)

minus3

minus2

minus1

0

ln[minus

ln(1

minus

)]

(a)

645K623 K602 K

583 K565K

21 2814

ln()

minus3

minus2

minus1

0

1

ln[minus

ln(1

minus

)]

(b)


4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

13

12

11

10

09

08

Topo

logi

cal d

imen

sionm

580 600 620 640 660560

Temperature (K)

04

06

08

10

12

14

Avra

mi e

xpon

entn



4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

20

18

16

14

12

10

0802

04

06

08

10

12

14

16

18

20

Avra

mi e

xpon

entn

600 625 700 725650 675575

Temperature (K)





4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

00

05

15

20

25

30

35

40

10

00

05

10

15

20

25

30

35

40

Avra

mi e

xpon

entn

700 750 800650600

Temperature (K)




4 Conclusions






Acknowledgments


References














































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of








02 04 06 08 1000


0

100

200

300

400

500

600

700

800

V＞

Ｍ(c

m3

(STP

) gminus1)














(10l)

(11l)(20l)

15 20 2510 30


00

02

04

06

08

10

Nor

mal

ized

inte

nsity


25 wt Fe_Citrate

63 wt Fe_Citrate

107 wt Fe_Citrate

20 wt Fe_Nitrate

72 wt Fe_Nitrate

93 wt Fe_Nitrate

Fe2O3SBA-15

Fe2O30

1

2

3

4

5

6

7

Nor

mal

ized

inte

nsity

20 8010 50 60 7030 40







4000020000 3000010000


00

05

10

15

20

25

30

35

40

Kube

lka-

Mun

k fu

nctio

n

(a)


2 4 6 80 1210

Iron loading (wt)

20

22

24

26

28

30

32

34

36

DR-

UV-

Vis e

dge e

nerg

y (e

V)

(b)









93 wt Fe Nitrate

300 0320 (9) 0173 (42) 029 (11) 483lowast [119886] 480327 (8) 0536 (37) 0277 (45) 483lowast [119886] 52


72 wt Fe Nitrate

300 0330 (5) 0299 (15) 0190 (16) 483lowast [119886] 520307 (7) 0508 (27) 0233 (17) 483lowast [119886] 48



0312 (21) 0583 (95) 0265 (71) 483lowast [119886] 40

14 0421lowast 008 (12) 024 (76) 438 (15) 07 550423 (48) 0500 (60) 0437 (80) 483lowast 520 45

107 wt Fe Citrate

300 0294 (12) 0206 (39) 034 (12) 483lowast [119886] 450316 (12) 0672 (50) 0376 (49) 483lowast [119886] 55

14


4







Tran

smiss

ion

(arb

uni

ts)

14 K

14 K

4 K

107 wt Fe_Citrate

107 wt Fe_Citrate

93 wt Fe_Nitrate


Velocity (mms)


Tran

smiss

ion

(arb

uni

ts)


Velocity (mms)

14 K

14 K


72 wt Fe_Nitrate

93 wt Fe_Nitrate



800600400 12001000

Temperature (K)

0

5

10

15

20

25

TCD

sign

al (

V)

times102

00

02

04

06

08

10

750 900 1050600

Temperature (K)



0

5

10

15

20

25

TCD

sign

al (

V)

800700 900600

Temperature (K)

02

04

06

08

10

800500 600 700400 900300 11001000

Temperature (K)

times102




Fe2O3SBA-15Fe2O3

800600400 12001000

Temperature (K)

800700 850750

Temperature (K)

000204 060810

0

2

4

6

8

10

12

TCD

sign

al (

V)

times103






Linear regression

155 160 165150

1000Tm (Kminus1)

minus115

minus110

minus105

minus100

ln(

T2 m

)






= 01

= 08

06

08

10

12

14

log(

)

180145 150 155 160 165 175170140135

1000T (Kminus1)




02 04 06 08 1000

0

20

40

60

80

100

120

140

160

180

Ea

(kJm

ol)






ln(119892 (120572)1198792 ) = ln( 119860119877120573119864119886 [1 minus (2119877119879119864119886 )]) minus 119864119886

119877119879 (2)
















100381610038161003816100381610038161003816100381610038161003816119879 (4)





5Kmin10 Kmin

15 Kmin20 Kmin

180160 165 170 175155150

1000T (Kminus1)

minus3

minus2

minus1

0

ln[minus

ln(1

minus

)]

(a)

645K623 K602 K

583 K565K

21 2814

ln()

minus3

minus2

minus1

0

1

ln[minus

ln(1

minus

)]

(b)


4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

13

12

11

10

09

08

Topo

logi

cal d

imen

sionm

580 600 620 640 660560

Temperature (K)

04

06

08

10

12

14

Avra

mi e

xpon

entn



4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

20

18

16

14

12

10

0802

04

06

08

10

12

14

16

18

20

Avra

mi e

xpon

entn

600 625 700 725650 675575

Temperature (K)





4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

00

05

15

20

25

30

35

40

10

00

05

10

15

20

25

30

35

40

Avra

mi e

xpon

entn

700 750 800650600

Temperature (K)




4 Conclusions






Acknowledgments


References














































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of










(10l)

(11l)(20l)

15 20 2510 30


00

02

04

06

08

10

Nor

mal

ized

inte

nsity


25 wt Fe_Citrate

63 wt Fe_Citrate

107 wt Fe_Citrate

20 wt Fe_Nitrate

72 wt Fe_Nitrate

93 wt Fe_Nitrate

Fe2O3SBA-15

Fe2O30

1

2

3

4

5

6

7

Nor

mal

ized

inte

nsity

20 8010 50 60 7030 40







4000020000 3000010000


00

05

10

15

20

25

30

35

40

Kube

lka-

Mun

k fu

nctio

n

(a)


2 4 6 80 1210

Iron loading (wt)

20

22

24

26

28

30

32

34

36

DR-

UV-

Vis e

dge e

nerg

y (e

V)

(b)









93 wt Fe Nitrate

300 0320 (9) 0173 (42) 029 (11) 483lowast [119886] 480327 (8) 0536 (37) 0277 (45) 483lowast [119886] 52


72 wt Fe Nitrate

300 0330 (5) 0299 (15) 0190 (16) 483lowast [119886] 520307 (7) 0508 (27) 0233 (17) 483lowast [119886] 48



0312 (21) 0583 (95) 0265 (71) 483lowast [119886] 40

14 0421lowast 008 (12) 024 (76) 438 (15) 07 550423 (48) 0500 (60) 0437 (80) 483lowast 520 45

107 wt Fe Citrate

300 0294 (12) 0206 (39) 034 (12) 483lowast [119886] 450316 (12) 0672 (50) 0376 (49) 483lowast [119886] 55

14


4







Tran

smiss

ion

(arb

uni

ts)

14 K

14 K

4 K

107 wt Fe_Citrate

107 wt Fe_Citrate

93 wt Fe_Nitrate


Velocity (mms)


Tran

smiss

ion

(arb

uni

ts)


Velocity (mms)

14 K

14 K


72 wt Fe_Nitrate

93 wt Fe_Nitrate



800600400 12001000

Temperature (K)

0

5

10

15

20

25

TCD

sign

al (

V)

times102

00

02

04

06

08

10

750 900 1050600

Temperature (K)



0

5

10

15

20

25

TCD

sign

al (

V)

800700 900600

Temperature (K)

02

04

06

08

10

800500 600 700400 900300 11001000

Temperature (K)

times102




Fe2O3SBA-15Fe2O3

800600400 12001000

Temperature (K)

800700 850750

Temperature (K)

000204 060810

0

2

4

6

8

10

12

TCD

sign

al (

V)

times103






Linear regression

155 160 165150

1000Tm (Kminus1)

minus115

minus110

minus105

minus100

ln(

T2 m

)






= 01

= 08

06

08

10

12

14

log(

)

180145 150 155 160 165 175170140135

1000T (Kminus1)




02 04 06 08 1000

0

20

40

60

80

100

120

140

160

180

Ea

(kJm

ol)






ln(119892 (120572)1198792 ) = ln( 119860119877120573119864119886 [1 minus (2119877119879119864119886 )]) minus 119864119886

119877119879 (2)
















100381610038161003816100381610038161003816100381610038161003816119879 (4)





5Kmin10 Kmin

15 Kmin20 Kmin

180160 165 170 175155150

1000T (Kminus1)

minus3

minus2

minus1

0

ln[minus

ln(1

minus

)]

(a)

645K623 K602 K

583 K565K

21 2814

ln()

minus3

minus2

minus1

0

1

ln[minus

ln(1

minus

)]

(b)


4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

13

12

11

10

09

08

Topo

logi

cal d

imen

sionm

580 600 620 640 660560

Temperature (K)

04

06

08

10

12

14

Avra

mi e

xpon

entn



4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

20

18

16

14

12

10

0802

04

06

08

10

12

14

16

18

20

Avra

mi e

xpon

entn

600 625 700 725650 675575

Temperature (K)





4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

00

05

15

20

25

30

35

40

10

00

05

10

15

20

25

30

35

40

Avra

mi e

xpon

entn

700 750 800650600

Temperature (K)




4 Conclusions






Acknowledgments


References














































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of





4000020000 3000010000


00

05

10

15

20

25

30

35

40

Kube

lka-

Mun

k fu

nctio

n

(a)


2 4 6 80 1210

Iron loading (wt)

20

22

24

26

28

30

32

34

36

DR-

UV-

Vis e

dge e

nerg

y (e

V)

(b)









93 wt Fe Nitrate

300 0320 (9) 0173 (42) 029 (11) 483lowast [119886] 480327 (8) 0536 (37) 0277 (45) 483lowast [119886] 52


72 wt Fe Nitrate

300 0330 (5) 0299 (15) 0190 (16) 483lowast [119886] 520307 (7) 0508 (27) 0233 (17) 483lowast [119886] 48



0312 (21) 0583 (95) 0265 (71) 483lowast [119886] 40

14 0421lowast 008 (12) 024 (76) 438 (15) 07 550423 (48) 0500 (60) 0437 (80) 483lowast 520 45

107 wt Fe Citrate

300 0294 (12) 0206 (39) 034 (12) 483lowast [119886] 450316 (12) 0672 (50) 0376 (49) 483lowast [119886] 55

14


4







Tran

smiss

ion

(arb

uni

ts)

14 K

14 K

4 K

107 wt Fe_Citrate

107 wt Fe_Citrate

93 wt Fe_Nitrate


Velocity (mms)


Tran

smiss

ion

(arb

uni

ts)


Velocity (mms)

14 K

14 K


72 wt Fe_Nitrate

93 wt Fe_Nitrate



800600400 12001000

Temperature (K)

0

5

10

15

20

25

TCD

sign

al (

V)

times102

00

02

04

06

08

10

750 900 1050600

Temperature (K)



0

5

10

15

20

25

TCD

sign

al (

V)

800700 900600

Temperature (K)

02

04

06

08

10

800500 600 700400 900300 11001000

Temperature (K)

times102




Fe2O3SBA-15Fe2O3

800600400 12001000

Temperature (K)

800700 850750

Temperature (K)

000204 060810

0

2

4

6

8

10

12

TCD

sign

al (

V)

times103






Linear regression

155 160 165150

1000Tm (Kminus1)

minus115

minus110

minus105

minus100

ln(

T2 m

)






= 01

= 08

06

08

10

12

14

log(

)

180145 150 155 160 165 175170140135

1000T (Kminus1)




02 04 06 08 1000

0

20

40

60

80

100

120

140

160

180

Ea

(kJm

ol)






ln(119892 (120572)1198792 ) = ln( 119860119877120573119864119886 [1 minus (2119877119879119864119886 )]) minus 119864119886

119877119879 (2)
















100381610038161003816100381610038161003816100381610038161003816119879 (4)





5Kmin10 Kmin

15 Kmin20 Kmin

180160 165 170 175155150

1000T (Kminus1)

minus3

minus2

minus1

0

ln[minus

ln(1

minus

)]

(a)

645K623 K602 K

583 K565K

21 2814

ln()

minus3

minus2

minus1

0

1

ln[minus

ln(1

minus

)]

(b)


4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

13

12

11

10

09

08

Topo

logi

cal d

imen

sionm

580 600 620 640 660560

Temperature (K)

04

06

08

10

12

14

Avra

mi e

xpon

entn



4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

20

18

16

14

12

10

0802

04

06

08

10

12

14

16

18

20

Avra

mi e

xpon

entn

600 625 700 725650 675575

Temperature (K)





4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

00

05

15

20

25

30

35

40

10

00

05

10

15

20

25

30

35

40

Avra

mi e

xpon

entn

700 750 800650600

Temperature (K)




4 Conclusions






Acknowledgments


References














































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of




93 wt Fe Nitrate

300 0320 (9) 0173 (42) 029 (11) 483lowast [119886] 480327 (8) 0536 (37) 0277 (45) 483lowast [119886] 52


72 wt Fe Nitrate

300 0330 (5) 0299 (15) 0190 (16) 483lowast [119886] 520307 (7) 0508 (27) 0233 (17) 483lowast [119886] 48



0312 (21) 0583 (95) 0265 (71) 483lowast [119886] 40

14 0421lowast 008 (12) 024 (76) 438 (15) 07 550423 (48) 0500 (60) 0437 (80) 483lowast 520 45

107 wt Fe Citrate

300 0294 (12) 0206 (39) 034 (12) 483lowast [119886] 450316 (12) 0672 (50) 0376 (49) 483lowast [119886] 55

14


4







Tran

smiss

ion

(arb

uni

ts)

14 K

14 K

4 K

107 wt Fe_Citrate

107 wt Fe_Citrate

93 wt Fe_Nitrate


Velocity (mms)


Tran

smiss

ion

(arb

uni

ts)


Velocity (mms)

14 K

14 K


72 wt Fe_Nitrate

93 wt Fe_Nitrate



800600400 12001000

Temperature (K)

0

5

10

15

20

25

TCD

sign

al (

V)

times102

00

02

04

06

08

10

750 900 1050600

Temperature (K)



0

5

10

15

20

25

TCD

sign

al (

V)

800700 900600

Temperature (K)

02

04

06

08

10

800500 600 700400 900300 11001000

Temperature (K)

times102




Fe2O3SBA-15Fe2O3

800600400 12001000

Temperature (K)

800700 850750

Temperature (K)

000204 060810

0

2

4

6

8

10

12

TCD

sign

al (

V)

times103






Linear regression

155 160 165150

1000Tm (Kminus1)

minus115

minus110

minus105

minus100

ln(

T2 m

)






= 01

= 08

06

08

10

12

14

log(

)

180145 150 155 160 165 175170140135

1000T (Kminus1)




02 04 06 08 1000

0

20

40

60

80

100

120

140

160

180

Ea

(kJm

ol)






ln(119892 (120572)1198792 ) = ln( 119860119877120573119864119886 [1 minus (2119877119879119864119886 )]) minus 119864119886

119877119879 (2)
















100381610038161003816100381610038161003816100381610038161003816119879 (4)





5Kmin10 Kmin

15 Kmin20 Kmin

180160 165 170 175155150

1000T (Kminus1)

minus3

minus2

minus1

0

ln[minus

ln(1

minus

)]

(a)

645K623 K602 K

583 K565K

21 2814

ln()

minus3

minus2

minus1

0

1

ln[minus

ln(1

minus

)]

(b)


4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

13

12

11

10

09

08

Topo

logi

cal d

imen

sionm

580 600 620 640 660560

Temperature (K)

04

06

08

10

12

14

Avra

mi e

xpon

entn



4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

20

18

16

14

12

10

0802

04

06

08

10

12

14

16

18

20

Avra

mi e

xpon

entn

600 625 700 725650 675575

Temperature (K)





4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

00

05

15

20

25

30

35

40

10

00

05

10

15

20

25

30

35

40

Avra

mi e

xpon

entn

700 750 800650600

Temperature (K)




4 Conclusions






Acknowledgments


References














































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of


Tran

smiss

ion

(arb

uni

ts)

14 K

14 K

4 K

107 wt Fe_Citrate

107 wt Fe_Citrate

93 wt Fe_Nitrate


Velocity (mms)


Tran

smiss

ion

(arb

uni

ts)


Velocity (mms)

14 K

14 K


72 wt Fe_Nitrate

93 wt Fe_Nitrate



800600400 12001000

Temperature (K)

0

5

10

15

20

25

TCD

sign

al (

V)

times102

00

02

04

06

08

10

750 900 1050600

Temperature (K)



0

5

10

15

20

25

TCD

sign

al (

V)

800700 900600

Temperature (K)

02

04

06

08

10

800500 600 700400 900300 11001000

Temperature (K)

times102




Fe2O3SBA-15Fe2O3

800600400 12001000

Temperature (K)

800700 850750

Temperature (K)

000204 060810

0

2

4

6

8

10

12

TCD

sign

al (

V)

times103






Linear regression

155 160 165150

1000Tm (Kminus1)

minus115

minus110

minus105

minus100

ln(

T2 m

)






= 01

= 08

06

08

10

12

14

log(

)

180145 150 155 160 165 175170140135

1000T (Kminus1)




02 04 06 08 1000

0

20

40

60

80

100

120

140

160

180

Ea

(kJm

ol)






ln(119892 (120572)1198792 ) = ln( 119860119877120573119864119886 [1 minus (2119877119879119864119886 )]) minus 119864119886

119877119879 (2)
















100381610038161003816100381610038161003816100381610038161003816119879 (4)





5Kmin10 Kmin

15 Kmin20 Kmin

180160 165 170 175155150

1000T (Kminus1)

minus3

minus2

minus1

0

ln[minus

ln(1

minus

)]

(a)

645K623 K602 K

583 K565K

21 2814

ln()

minus3

minus2

minus1

0

1

ln[minus

ln(1

minus

)]

(b)


4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

13

12

11

10

09

08

Topo

logi

cal d

imen

sionm

580 600 620 640 660560

Temperature (K)

04

06

08

10

12

14

Avra

mi e

xpon

entn



4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

20

18

16

14

12

10

0802

04

06

08

10

12

14

16

18

20

Avra

mi e

xpon

entn

600 625 700 725650 675575

Temperature (K)





4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

00

05

15

20

25

30

35

40

10

00

05

10

15

20

25

30

35

40

Avra

mi e

xpon

entn

700 750 800650600

Temperature (K)




4 Conclusions






Acknowledgments


References














































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of


Fe2O3SBA-15Fe2O3

800600400 12001000

Temperature (K)

800700 850750

Temperature (K)

000204 060810

0

2

4

6

8

10

12

TCD

sign

al (

V)

times103






Linear regression

155 160 165150

1000Tm (Kminus1)

minus115

minus110

minus105

minus100

ln(

T2 m

)






= 01

= 08

06

08

10

12

14

log(

)

180145 150 155 160 165 175170140135

1000T (Kminus1)




02 04 06 08 1000

0

20

40

60

80

100

120

140

160

180

Ea

(kJm

ol)






ln(119892 (120572)1198792 ) = ln( 119860119877120573119864119886 [1 minus (2119877119879119864119886 )]) minus 119864119886

119877119879 (2)
















100381610038161003816100381610038161003816100381610038161003816119879 (4)





5Kmin10 Kmin

15 Kmin20 Kmin

180160 165 170 175155150

1000T (Kminus1)

minus3

minus2

minus1

0

ln[minus

ln(1

minus

)]

(a)

645K623 K602 K

583 K565K

21 2814

ln()

minus3

minus2

minus1

0

1

ln[minus

ln(1

minus

)]

(b)


4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

13

12

11

10

09

08

Topo

logi

cal d

imen

sionm

580 600 620 640 660560

Temperature (K)

04

06

08

10

12

14

Avra

mi e

xpon

entn



4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

20

18

16

14

12

10

0802

04

06

08

10

12

14

16

18

20

Avra

mi e

xpon

entn

600 625 700 725650 675575

Temperature (K)





4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

00

05

15

20

25

30

35

40

10

00

05

10

15

20

25

30

35

40

Avra

mi e

xpon

entn

700 750 800650600

Temperature (K)




4 Conclusions






Acknowledgments


References














































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of


= 01

= 08

06

08

10

12

14

log(

)

180145 150 155 160 165 175170140135

1000T (Kminus1)




02 04 06 08 1000

0

20

40

60

80

100

120

140

160

180

Ea

(kJm

ol)






ln(119892 (120572)1198792 ) = ln( 119860119877120573119864119886 [1 minus (2119877119879119864119886 )]) minus 119864119886

119877119879 (2)
















100381610038161003816100381610038161003816100381610038161003816119879 (4)





5Kmin10 Kmin

15 Kmin20 Kmin

180160 165 170 175155150

1000T (Kminus1)

minus3

minus2

minus1

0

ln[minus

ln(1

minus

)]

(a)

645K623 K602 K

583 K565K

21 2814

ln()

minus3

minus2

minus1

0

1

ln[minus

ln(1

minus

)]

(b)


4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

13

12

11

10

09

08

Topo

logi

cal d

imen

sionm

580 600 620 640 660560

Temperature (K)

04

06

08

10

12

14

Avra

mi e

xpon

entn



4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

20

18

16

14

12

10

0802

04

06

08

10

12

14

16

18

20

Avra

mi e

xpon

entn

600 625 700 725650 675575

Temperature (K)





4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

00

05

15

20

25

30

35

40

10

00

05

10

15

20

25

30

35

40

Avra

mi e

xpon

entn

700 750 800650600

Temperature (K)




4 Conclusions






Acknowledgments


References














































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of













100381610038161003816100381610038161003816100381610038161003816119879 (4)





5Kmin10 Kmin

15 Kmin20 Kmin

180160 165 170 175155150

1000T (Kminus1)

minus3

minus2

minus1

0

ln[minus

ln(1

minus

)]

(a)

645K623 K602 K

583 K565K

21 2814

ln()

minus3

minus2

minus1

0

1

ln[minus

ln(1

minus

)]

(b)


4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

13

12

11

10

09

08

Topo

logi

cal d

imen

sionm

580 600 620 640 660560

Temperature (K)

04

06

08

10

12

14

Avra

mi e

xpon

entn



4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

20

18

16

14

12

10

0802

04

06

08

10

12

14

16

18

20

Avra

mi e

xpon

entn

600 625 700 725650 675575

Temperature (K)





4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

00

05

15

20

25

30

35

40

10

00

05

10

15

20

25

30

35

40

Avra

mi e

xpon

entn

700 750 800650600

Temperature (K)




4 Conclusions






Acknowledgments


References














































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of


5Kmin10 Kmin

15 Kmin20 Kmin

180160 165 170 175155150

1000T (Kminus1)

minus3

minus2

minus1

0

ln[minus

ln(1

minus

)]

(a)

645K623 K602 K

583 K565K

21 2814

ln()

minus3

minus2

minus1

0

1

ln[minus

ln(1

minus

)]

(b)


4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

13

12

11

10

09

08

Topo

logi

cal d

imen

sionm

580 600 620 640 660560

Temperature (K)

04

06

08

10

12

14

Avra

mi e

xpon

entn



4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

20

18

16

14

12

10

0802

04

06

08

10

12

14

16

18

20

Avra

mi e

xpon

entn

600 625 700 725650 675575

Temperature (K)





4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

00

05

15

20

25

30

35

40

10

00

05

10

15

20

25

30

35

40

Avra

mi e

xpon

entn

700 750 800650600

Temperature (K)




4 Conclusions






Acknowledgments


References














































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of


4 6 8 10 12 14 16 18 20 22

Heating rate (Kmin)

Topo

logi

cal d

imen

sionm

00

05

15

20

25

30

35

40

10

00

05

10

15

20

25

30

35

40

Avra

mi e

xpon

entn

700 750 800650600

Temperature (K)




4 Conclusions






Acknowledgments


References














































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of







































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of

Solid-State Kinetic Investigations of Nonisothermal Reduction...

Documents

Transcript of Solid-State Kinetic Investigations of Nonisothermal Reduction...