Fuel Processing Technology 127 (2014) 163–170

Contents lists available at ScienceDirect

Fuel Processing Technology

j ourna l homepage: www.e lsev ie r .com/ locate / fuproc

Catalytic performance of an iron-based catalyst inFischer–Tropsch synthesis

Majid Sarkari a, Farhad Fazlollahi b, Hossein Ajamein a, Hossein Atashi a,⁎, William C. Hecker b, Larry L. Baxter b

a Department of Chemical Engineering, Faculty of Engineering, University of Sistan and Baluchestan, P.O. Box 98164-161, Zahedan, Iranb Chemical Engineering Department, Brigham Young University, Provo, UT 84602, USA

⁎ Corresponding author. Tel.: +98 9121193366.E-mail address: h.ateshy@hamoon.usb.ac.ir (H. Atashi

http://dx.doi.org/10.1016/j.fuproc.2014.05.0030378-3820/© 2014 Published by Elsevier B.V.

a b s t r a c t

a r t i c l e i n f o

Article history:Received 4 March 2013Received in revised form 29 April 2014Accepted 2 May 2014Available online 17 July 2014

Keyword:Fischer–Tropsch synthesisIron–manganese catalystFixed-bed reactor

This paper documents the performance and kinetics of an iron/manganese oxide catalyst in a fixed-bed reactorby Fischer–Tropsch synthesis (FTS) under conditions favoring the formation of gaseous and liquid hydrocarbons(P: 1–12 bar; T: 513–543 K; H2/CO:1, 1.5, 2 mol/mol; gas hourly space velocity: 4200–7000 cm3 (STP)/h/gcat).Based on the hypothesis that water inhibits the intrinsic FTS reaction rate, eight kinetic models are considered:six variations of the Langmuir–Hinshelwood–Hougen–Watson representation and two empirical power-lawmodels. The kinetic expression/mechanism that most precisely fits the data assumes the following: (1) COdissociation is reversible and does not involve hydrogen; (2) all hydrogenation steps are irreversible, or thefirst hydrogenation step is slow and rate determining. Also, the performance of the catalyst for FTS and thehydrocarbon product distributions were investigated under different reaction conditions.

© 2014 Published by Elsevier B.V.

1. Introduction

Theworld energy crisis in recent years led to renewed interest in theFischer–Tropsch synthesis (FTS) reactions. Fischer–Tropsch synthesis isthe heart of themost established efficient and cost-effective conversionof non-petroleum feedstock such as biomass, natural gas or coal totransportation fuels. An early and the most expensive step in the pro-cess converts the feedstock to syngas, the most useful components ofwhich are H2 and CO. Reformers or gasifiers of various designs affectthis conversion. A subsequent water–gas shift reactor adjusts H2 to COstoichiometry by converting water to hydrogen. Finally, the FTS reactorconverts the pressurized gases to a large variety of ultra-clean olefin,paraffin and oxygenates fuels, which in some cases can happen simulta-neously with water–gas shift reaction [1–3]. Catalysts play essentialroles in the reformers, water–gas shift reactors, and the FTS reactors.The focus here is on the FTS catalysts. A variety of catalysts show FTS re-activity, including preparations involving Fe, Co, Ru, and Ni. Iron-basedcatalysts are especially attractive for synthesizing gas with H2/CO ratiosless than 2 due to their high activity in water–gas shift (WGS) reactions.In essence, the Fe-based catalysts combine some of the functions of thewater–gas shift reactor with the FTS reactor. Fe-based catalysts are alsomore resistant to poisons and produce a more flexible product slatethan alternatives [4,5]. Typically, iron-based catalysts contain smallamounts of potassium to improve the carburization and suppressmeth-ane formation [6–8] and/or other metal promoters such as manganese,

).

calcium, zinc, copper and magnesium to boost catalyst activity andselectivity [6,9].

Among the promoted iron-based catalysts, the Fe–Mn catalyst hassome industrial record and reportedly has a higher olefin and middledistillation cut selectivity [7,8,10–12].

Even though the kinetic model of the Fe-based Fischer–Tropschsynthesis reaction has been studied by many researchers, there is nogeneral agreement on the form of the kinetic rate expression [13,14].The Langmuir–Hinshelwood–Hougen–Watson (LHHW) mechanismrepresents one of the more detailed and common descriptions forindustrial applications [15]. Application of this mechanism suffersfrom its complexity and the large number of species involved [16,17].On the other hand, a combination of density functional theory (DFT)calculations and kinetic analyses describe a credible, stepwise chaingrowth process [18,19].

Two reported mechanisms for FTS include:

(1) A direct (hydrogen-unassisted) CO dissociative adsorption,including direct CO dissociation that forms monomers wherethe surface carbide species, C*, forms the intermediate for allthe reaction products [20,21], and

(2) A hydrogen-assisted CO dissociation, where CO formsintermediates HCO* and HCOH* and finally the chain initiatorintermediate CH* [22,23].

In direct (hydrogen-unassisted) CO dissociation, C* routes contrib-ute primarily to monomer formation on alkali promoted Fe-basedcatalysts at high temperatures. H-assisted CO dissociation removes Oatoms as H2O, while direct dissociation forms chemisorbed oxygen

164 M. Sarkari et al. / Fuel Processing Technology 127 (2014) 163–170

atoms that desorbs as CO2. On Fe catalysts, alkali promoters affect thecontributions from these two pathways. CO activation occurs exclusive-ly by hydrogen-assisted dissociation routes in the latter mechanism atrelevant FTS conditions [24,25]. Fig. 1 illustrates the proposed primarysurface steps for FTS on iron-based catalysts.

This investigation of Fischer–Tropsch synthesis over an impregnatediron–manganese catalyst in a fixed-bed reactor includes experimentaldata over a wide range of reaction conditions. Several detailed kineticmodels fit the observed data with varying accuracy. The best fit,and by inference perhaps themost accuratemechanism, uses LHHW in-trinsic kinetics. The non-linear regression analysis used the Levenberg–Marquardt method.

2. Experimental

2.1. Catalyst preparation

The catalysts were prepared by incipient wetness impregnation ofAl2O3 with aqueous iron nitrate (Fe (NO3)2·6H2O) (0.5 M) (99%, Merck)and manganese nitrate (Mn(NO3)2·6H2O) (0.5 M) (99%, Merck)solutions. The Al2O3 support was first calcined at 600 °C in flowingair for 6 h before impregnation. For 50%Fe/50%Mn/5wt.%Al2O3 catalyst,the iron and manganese nitrate solution dispersed through a sprayneedle onto the support. The impregnated support dried at 120 °Cfor 16 h and calcined at 550 °C for 6 h. The BET surface area ofthe fresh catalyst was 120.2 m2/g. The phases identified in thefresh catalyst included monoclinic Fe2O3, cubic MnO2 and Mn2O3,orthorhombic AlFeO3 orthorhombic and tetragonal Al2O3. The sam-ple after the FT reaction contained orthorhombic Fe3C, monoclinicFe2C, orthorhombic Mn2O3, FeFe2O4, MnAl2O4/MnO, and cubic Al2O3.One gramof fresh, 0.15–0.25mm(60–100 ASTMmesh) catalyst reactedwith the simulated syngas, diluted 1 part to four with quartz of thesame size.

2.2. Kinetic study

A differential fixed-bed micro-reactor (ID: 6 mm, Hb: 40 mm)provided stead-state kinetic data, the detailed description of whichis found elsewhere [26,27]. The heat transfer analysis indicated anessentially isothermal catalyst under these operating conditions,with predicted conversion results based on an isothermal, one-dimensional, pseudo-homogeneous, plug-flow model [28,29]. Themodel equations consist of a mass balance for each component,which may be written as follows:

d uCið ÞdZ

þ riρβ ¼ 0;

where Ci refers to concentration of component i (mol/m3), u thesuperficial velocity (m/s), ri the overall reaction rate of componenti [mol/(kgcat·s)], and ρβ the catalyst bed density (kgcat/m3). Withthe boundary conditions Ci = Ci° at reactor entrance (Z = 0), theoverall synthesis reaction can be written as follows:

nCO + (n + m/2) H2 → CnHm + nH2O

where n is the average carbon chain length of the hydrocarbon productandm is the average number hydrogen atoms per hydrocarbonmolecule.

The operating conditions were varied in the following ranges:T= 240–270 °C, P= 1–12 bar, GHSV= 4200–7000 cm3(STP)/h/gcatand H2/CO feed molar ratio = 1, 1.5 and 2. An equimolar, atmospheric-pressure, 60 ml/min flow of H2 and N2 reduced the fresh catalyst in situfor 16 h at 300 °C 1. The catalyst then cooled to 180 °C and was flushedwith N2. After catalyst treatment, they system shifted to process condi-tions of interest. Since the TCD-GC could not analyze water accurately,an oxygen balance determined the amount of water assuming that the

contribution from oxygenates in the products was negligible. Theseideal tubular reactors have the following characteristics [30]:

IDDp

N25:

To minimize by-pass,

Hb

DpN100;

satisfying both relations minimizes back-mixing.The carbon-containing products determine CO conversion (xCO):

xCO;out %ð Þ ¼X

niMi

MCO

where ni is the number of carbon atoms in product i,Mi is the percentageof product i, and MCO is the percentage of carbon CO in feed stream.

The average reaction rate is

−rA ¼ F0COxCO;outW

:

The total number of carbon atoms in the product determines theselectivity of product i (Si) according to:

Si %ð Þ ¼X niMiX

niMi

:

Eighteen sets of experimental data over a range of 1–12 bar,513–543 K, 4200–7200 cm3 (STP)/h/gcat space velocity, and 1–2H2/CO ratio produced overall conversions from 4–12.6% and formthe primary kinetic data that determine the kinetic coefficients(Table 1).

2.3. Kinetic model evaluation

The rate of synthesis gas conversion depends on the partial pressureof the feed constituents, as well as temperature. CO absorbs more thanH2 on the iron-based catalyst surface at temperatures above 77 °C[31]. Iron catalysts are great reservoirs of surface inactive and activecarbon and bulk carbon during FT reactions [32]. Some carbonic com-pounds cover the catalyst surface. Iron-based FT synthesis producesboth water and carbon dioxide, representing two important routes foroxygen removal. Water substantially affects intrinsic FT reaction rates[33] while CO2 has less effect on iron-based FT catalysts [34]. Therefore,CO2 is not included in the rate expression of many kinetic models.Experimental evidence indicates CO and water competitively absorbson active sites of iron-based catalysts [33].

This investigation compares statistical fits of six simplified forms ofLHHW equations and two power law expressions to new experimentaldata. In represented kinetic models, it is assumed that all rate expres-sions were in inverse ratio to the number of vacant sites, CO andwater content. This physically means that the FTS rate is inhibited bycarbon monoxide and/or water.

The proposed rate expressions can be generalized as:

−RCO ¼ kFTPαCOP

βH2

1or0þX

kCOPγCOP

λH2PωH2O þ kH2OPH2OÞ

ρ�

where n is the integer 0 or 1 and the remaining parameters have typicaldefinitions (see nomenclature).

In all equations in Table 2, kFT is a kinetic parameter group, thatis considered as the reaction rate constant and kCO and kH2O repre-sent the adsorption parameter group of carbon species and water,

Fig. 1. Proposed primary surface steps for FTS on iron catalysts.

165M. Sarkari et al. / Fuel Processing Technology 127 (2014) 163–170

respectively. A simple Arrhenius expression describes the reactionrate parameter:

A ¼ A0 exp − ERT

� �

Minimizing the sum of the squares of the relative error, some-times called the Levenberg–Marquardt (LM) algorithm, determinedthe optimal reaction parameters. This expression assumes that thedata errors normally distributed with standard deviations that are

Table 1Kinetic results obtained for Fe–Mn/Al2O3 catalyst in fixed-bed reactor.

Run no T Ptot H2/CO GHxSV Outlet Conv. − rCO × 105

PCO PH2PH2O

1 523 4 2 4200 0.98 1.96 0.175 8.73 13.772 523 8 2 4200 1.15 4.97 0.358 9.44 28.203 523 1 2 4200 0.24 0.48 0.562 9.92 49.404 533 8 2 5000 1.88 3.66 0.184 12.61 15.475 533 1 2 5000 0.25 0.27 0.385 10.44 34.876 523 1 1.5 5000 0.29 0.42 0.187 8.76 13.247 533 8 1.5 5000 2.35 3.41 0.182 8.17 16.528 533 12 1.5 5000 3.53 5.52 0.339 7.83 31.299 533 1 1.5 5000 0.29 0.43 0.549 7.89 52.2210 543 1 1 5000 0.38 0.56 0.186 4.36 18.6011 513 8 1 5000 2.79 3.22 0.337 12.57 7.9612 513 12 1 6000 4.60 4.49 0.409 4.15 15.4013 513 1 1 6000 0.38 0.37 0.463 4.66 26.0514 523 1 1 6000 0.37 0.37 0.467 5.44 34.4915 523 12 1 4200 4.65 4.71 0.174 6.08 11.0116 533 1 1 7000 0.28 0.37 0.483 4.75 41.0917 543 8 1 7000 2.99 2.85 0.159 6.36 18.3818 543 4 1 7000 1.40 1.69 0.322 8.22 39. 71

Units: T(K), Ptot (bar), H2/CO (mol/mol), GHSV (cm3 (STP)/h/gcat), Conv. (%), rCO(mol CO/gcat·min).

proportional to the measured reaction rate and independent ofeach other:

Fobj ¼XNi

rexpi −rmodi

rexpi

!2

The disagreement between different kinetic models considers themean absolute relative residuals (MARR) and relative variance betweenthe predicted and measured rates:

MARR ¼ 1Nexp

XNexp

i¼1

rexpi −rmodi

��� ���rexpi

0@

1A

Srel ¼ 100

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi1

n−m

Xni¼1

rexpi −rmodi

rexpi

!vuut

Table 2proposed kinetic equations.

Model Kinetic equation Ref.

Model-I −RCO ¼ kFTPCOPH2PCOþkH2OPH2O

Anderson [35]Model-II −RCO ¼ kFTPCOP

0:5H2

PCOþkH2OPH2O

Vanberg [36]

Model-III −RCO ¼ kFTPCOP2H2

1þkCPCOþkH2OPH2O

Van deer laan [37]

Model-IV −RCO ¼ kFTP1:5H2

PCO=PH2O

1þk1PCOPH2=PH2Oð Þ2

Van Steen [38]

Model-V −RCO ¼ kFTPCOP0:5H2

1þkCOPCOð Þ2Botes [33]

Model-VI −RCO ¼ kFTPCOP2:5H2

=PH2O

1þk1PCOP0:5H2

Nakhaei Pour [39]

Power law-I −RCO ¼ kFTPnCOP

mH2PcH2O

This study

Power law-II −RCO ¼ kFTPnCOP

mH2

1þcPH2O=PH2

[40,41]

Table 4Estimated results for the parameters of the Fischer–Tropsch synthesis kinetic models.

Kinetic model Kinetic parameter Statistical result

166 M. Sarkari et al. / Fuel Processing Technology 127 (2014) 163–170

where, riexp and rimod indicate the experimental and calculated CO con-

version rate using each kinetic model in data point ith respectively,and Nexp indicates the number of experimental data points with pureerror variance σ, n is the number of included data points and m is thenumber of optimized parameters for all experimental data. Also, theR2 value (reflects the amount of variance) is a parameter for discrimina-tion of results and it is compared with calculated and experimental FTSreaction rates and defined as:

R2 ¼ 1− residual sum of squarescorrected sum of squares

3. Results

3.1. Catalyst performance

The effects of reaction temperature, total pressure, space velocityand H2/CO ratio on the catalytic performance of the Fe–Mn catalystare summarized in Table 3.

Fischer–Tropsch reactions occur on surfaces and depend on bulkconcentration of H2 and CO.

Higher reaction temperatures have always been found to favorhigher rates of CH4 production due to, on the one hand, decreasedH2/CO ratio inside the reactor and a decrease in the probability ofchain growth [42,43] and on the other hand the decreased CO and in-creased H surface coverage [44]. Therefore, as indicated in Table 3(columns 1 and 2), the selectivity to higher hydrocarbon decreasedwhile the selectivity to both methane and light gaseous hydrocarbonincreased with increasing temperature. Increased selectivity ofolefin formation with increasing temperature results from the rate ofdehydrogenation reactions increasingwith temperature [45]. CO2 selec-tivity decreased slightly with increasing temperature. At low tempera-ture, coverage of CO is higher than that of surface hydrogen. Oxygenatoms are removed by CO largely. As the temperature increases, cover-age of surface hydrogen increases relative to CO. Therefore, oxygenatoms are mostly removed by surface hydrogen at high temperature[44]. Therefore, temperature can affect the reaction pathways foroxygen removal.

Total pressure increase enhanced the selectivity of the heavyhydrocarbons (C5+) from 22.1 to 28.8, while the selectivity to bothmethane and light gaseous hydrocarbon decreased. The decreased se-lectivity to light products results from individual CH2 units remainingon the surface with increasing pressure, resulting in more chain growth[46,47]. The effects of pressure on olefin selectivity depend on olefinreactivity during FTS. Olefins, in contrast to paraffins, can be reabsorbedon the catalyst active sites and can be reinserted in the chain growthprocess (forming heavier hydrocarbons) or can be hydrogenated tothe corresponding paraffins. With increasing pressure, the olefin/paraffin ratio decreases from 1.47 to 1.37 because of these twoeffects. Pressure has no effect on CO2 selectivity.

In general, increasing the H2/CO inlet ratio lowers the CO partialpressure and associated adsorbed CO concentration, which resultsin a higher adsorption and dissociation of H2 and increases the

Table 3Catalyst performance results.

Operating condition Selectivity of products

Tem(K)

Press(bar)

H2/CO(mol/mol)

GHSV(cm3 (STP)/h/gcat)

C1 C2−4 C5+ CO2 Ole/par

513 4 1 4200 14.1 32.1 25.4 28.4 1.25523 4 1 4200 16.2 36.0 22.1 25.7 1.47523 8 1 4200 12.2 33.4 28.7 25.7 1.38523 8 2 6000 15.3 35.5 24.1 25.0 1.59523 8 2 7000 11.4 38.6 25.2 24.8 1.74543 12 3 7000 18.2 31.2 21.2 29.4 1.38543 12 2 7000 13.6 29.1 24.5 32.8 1.12

hydrogenation reaction rate [48]. Low H2/CO ratio leads to a CO ad-sorption rate higher than the hydrogen adsorption rate, therefore,the scarcity of surface H causes low activity for FTS catalyst. As theH2/CO ratio increases, CO coverage decreases and H coverage in-creases, and the lower CO decreases of activity of FT synthesis andwhile the abundance of H species leads to less heavy hydrocarbonsand increases methane selectivity significantly, from 13.3 to 18.2with the H2/CO ratio in the range of 2 to 3. Selectivity to the lighthydrocarbons exponentially increases by increasing the H2 contentof the feed gas similar to other investigations. Hydrogen is responsi-ble for the termination of hydrocarbon chains into paraffins. As theH2/CO feed ratio increases, the partial pressure of H2 in the reactionmedia and the associated termination rate into paraffins increases,reducing the amount of olefins produced by the reaction [49]. Also,as the H2/CO feed ratio increases, selectivity to CO2 decreases dueto the increase of the hydrogen partial pressure and the weakenedforce of the positive water gas shift reaction.

Table 3 also indicates that space velocity at 523 K affects hydrocar-bon selectivity in complex ways, not all of which are consistent withthe literature. Increasing space velocity decreases residence time [11]and a low residence time reduces the rate of temperature increase inthe fixed bed reactor, which is favorable for chain growth [43]. CO andH2 supply rates must be at least as rapid as CH4 desorption rates toproduce long-chain hydrocarbons. If CH4 desorbs from the catalystbefore encountering reactants, the reactants will react with each otherto produce more CH4. As space velocity decreases, the selectivity tomethane decreases, while the selectivity to light (C2–4) and heavy(C5+) hydrocarbons increases. Olefin selectivities increasewith increas-ing space velocity for similar reasons. Results show a lower GHSV withhigher WGS activity.

3.2. Kinetic model

An experimental campaign generated data that helps determine boththe mechanisms and kinetics of FTS over the range of partial pressuresand temperatures measured. Table 2 summarizes the eight differentmechanisms considered. Ratemodels yielding negative adsorption coeffi-cients were excluded because the estimation of the kinetic parametersmust have physical relevance. Furthermore, the surface fractions ofadsorbed species should be realistic and the residuals between modeland experimental data should be normally distributed with zero averageshould produce random patterns, not trends, as functions of the indepen-dent variables. The statistical results (Table 4) reject model-I and model-VI, because the optimized parameters of these models were unrealistic.The comparison of the experimental and calculated rates for the remain-ing kinetic models for the CO reaction appears in Fig. 2. With regard tothese results, among the LHHW kinetic models, it is evident that themodel-IV having the minimal MARR and Srel and the highest R2 value

aA0bkC kH2

ckH2O Eactiv(kJ) Srel% MARR%

Model-I 70.92 1 – b0 59.89 30.49 19.39Model-II 0.486 1 – 0.111 35.41 147.52 98.42Model-III 635.6 41.81 – 54.85 73.66 46.32 35.42Model-IV 2.253 0.018 – – 52.41 26.81 17.68Model-V 17.157 0.189 – – 51.28 30.29 21.01Model-VI 75010 137.759 b0 – 92.24 103.21 90.00

aA0 n m c Eactiv Srel MARRPower law-I 273.70 −0.19 1.00 0.14 65.11 19.33 16.11Power law-II 199.36 −0.14 1.14 −0.80 65.11 23.03 19.19

a A0(mol·g−1·min−1·bar(−x)) where x:I (−2), II (−1.5), III (−3), IV (−1.5),V (−1.5), VI (−2.5), Pl-I (−0.95), Pl-II (0.20).

b kC (bar(−y)) where y: I (–),II (–), III (−1), IV (−1), V (−1), VI (−1.5).c kH2O (bar(−z)) where z: I (−1), II (−1). III (−1).

Fig. 2. Accuracy of selected kinetic models.

167M. Sarkari et al. / Fuel Processing Technology 127 (2014) 163–170

fits the experimental data well and also has the statistical significancewith F-value of 123.21. The corresponding kinetic and activation energyestimated values of the best fitted model (model-IV) appear in Table 5.Model-IV shows that the dominant mechanism on the catalyst surfaceis based on the direct CO dissociation pathway and forming surface car-bon. This model is consistent with the following sequence of kineticallyrelevant reaction steps in the iron-FT synthesis:

COþΨ↔COΨ

COΨ þΨ↔CΨ þ OΨ

Table 5Kinetic parameter and statistical indicator for best selected model.

Model-IV-Van Steen kinetic equation

A0 (molCO·gcat−1·min−1·bar−1.5): 2.25 ± 0.12kCO (bar−1):0.018 ± 0.015Reaction activation energy (kJ/mol): 52.41 ± 11.96Goodness of fit (R2):95.4MARR (%):17.68§F0.5 (4,28) = 2.71 b F-test: 123.21

H2 þ 2Ψ↔2HΨ

CΨ þHΨ→CHΨ þΨ

CHΨ þHΨ→CH2Ψ þΨ

OΨ þ 2HΨ↔H2Oþ 3Ψ

COΨ þ OΨ→CO2;Ψ þΨ

The rate equation derivation based on the LHHW follows:The rate-determining step is CO dissociation:

−RCO ¼ kC→CHΨCΨH

The surface fraction estimates for each species result from a sitebalance, the preceding reaction steps being at quasi-equilibrium andan assumed reaction rate for water formation as follows:

ΨH ¼ KHP0:5H2

ΨS

ΨCO ¼ KCOPCOΨS

168 M. Sarkari et al. / Fuel Processing Technology 127 (2014) 163–170

ΨO ¼ PH2OΨS=KH2OK2HPH2

ΨO

Fig. 3. Effect of carbon monoxide (a) and hydrogen (b) partial pressure on the CO rateover Fe/Mn/Al2O3. Comparison between experimental (data points) and predicted rateequation (model FT-III; solid line).

ΨC ¼ KCΨCOΨS=ΨO

Under these assumptions:

ΨC ¼ K2H2KCOKCKH2O

PCOPH2

PH2OΨS

A site balance determines the concentration of free sites Ψs. For aconstant total number of sites, this produces:

ΨT ¼X

Ψi þΨS

WhereΨT is the total surface sites,ΨS is the fraction free sites andΨi

are the surface fractions occupiedwith adsorbed species such as carbon,carbonmonoxide, hydrogen, alkyl chains, water, carbon dioxide, and soforth. Under realistic FTS condition the catalyst surface mainly coveredwith surface carbon [38]. So, in this model it follows that only surfacecarbon occupies a significant fraction of the total number of sites, sothe site balance becomes:

ΨT ¼ ΨC þΨS

To simplify, it may be considered that S =ΨS/ΨT, thus the previousequation can be changed to:

1 ¼ ΨC þ θS:

By substituting surface fraction of carbon in above equation:

θS ¼1

1þ K2HKCOKCKH2OPCOPH2

=PH2O:

Also, substituting the surface fraction of carbon, hydrogen andfraction free sites in FTS rate equation:

−RCO ¼kC→CHK

3HKCOKCKH2O

PCOP1:5H2

PH2O

1þ K2HKCOKCKH2O

PCOPH2PH2O

� �2

This kinetic includes: a) double functionalities of hydrogen thatindicate hydrogenation of surface carbon to produce organic compoundsand the removal of surface oxygen from catalyst surface, and, b) theindirect effect of water in FTS rate [50].

In addition to the LHHW kinetic models, two empirical power-lawequations results also appear below. They produced the unexpectedresult that water had a positive effect in the rate of FTS. The kineticparameters for these models appear in Table 4. It is of interest thatthe positive effect of water only occurs at low water partial pressure,where an increase in water partial pressure reduces the inhibitionof the FTS by surface carbon. In other words, at low water partialpressure the surface coverage of carbon species is high and in-hibits the adsorption of hydrogen. With increasing water partialpressure under these conditions, the amount of surface carbonspecies decreases, which will cause an increased rate of organiccompounds [50,51].

The effects of CO and hydrogen partial pressure on the rate of FT syn-thesis appear in Fig. 3 carried at two levels. The effects of CO involvedtwo constant H2 partial pressures (H2 = 1.5 and 2.5 bar) and influenceof hydrogen pressure was done at 1.5 and 2.5 bar CO partial pressures.The model-IV adequately predicts the observed effect of CO partialpressure, but not for more than about 5 bar. At low H2 pressure the

CO reaction rate increases with increasing CO inlet pressure to 5 bardue to the increase in the availability of surface carbon on the cata-lyst for the formation of carbon based compounds. Thereafter a de-crease in the CO reaction rate predicts at higher carbon monoxidepartial pressures due to the inhibition of surface carbon. At higherconstant H2 = 2.5 bar, the trend of CO pressure on CO rate was thesame as H2 = 1.5 bar but the rate is higher and inhibition of surfacecarbon starts after 4 bar. Higher H2 partial pressure decreases theWGS rate and therefore increases water partial pressure, increasingthe overall kinetics as described earlier. This observed trend of COpartial pressure effect agrees with the literature data for iron-basedcatalysts [44]. The kinetic rate equation predicted the observed influ-ence of the hydrogen partial pressure on the rate of reaction. The ratepredicted that the reaction rate increased linearly with respect to theincrease in hydrogen partial pressure, and the experimental dataplotted in Fig. 3 agrees over the range of experimental conditions.The trends of the rate of CO reaction are the same at two levels ofconstant inlet CO pressure i.e. 1.5 and 2.5 bar. Others observe similarincreases in the rate of FTS reaction with increasing hydrogen partialpressure [17,44].

The sophistication of iron-FT rate expressions proceeds in stagesas follows:

(a) A transition from the Eley–Rideal typemechanismwith a first-order denominator to a Langmuir–Hinshelwood expressionwith a second order inhibition term;

(b) Including the influence of vacant sites in the site balanceinstead of considering full coverage of the catalytic surface;

(c) Including the influence of water in the rate expression [52].

3.2.1. Progression of kinetic modelsAnderson (1956) [35] proposed Eley–Rideal first-order kinetics in

hydrogen as a rate equation to describe the FT reaction rate over ironcatalysts which included water inhibition, which forms the basis ofmodel-I. Years later, Dry (1976) [53] was able to derive this equationassuming that the hydrogenation of chemisorbed CO was the rate

169M. Sarkari et al. / Fuel Processing Technology 127 (2014) 163–170

determining step. Atwood and Bennett (1979) [54] used this kineticmodel with data taken over a fused iron catalyst. It was found thatwater inhibition was important only at the highest temperatures andconversions. Nonetheless, model-I became the basis of many subse-quent kinetic studies and was used by Leib and Kuo (1984) [55],Nettelhoff et al. (1985) [56] Zimmerman and Bukur (1990) [57] andShen et al. (1994) [58] to describe their own Fe-based kinetic data.

Van berg (1994) [36] considered a general kineticmodel and follow-ed a statistical design process. After further parameter optimization, thegeneralizedmodel could be simplified tomodel-II with high confidenceand fit experimental data over K-promoted precipitated iron catalyst.The observed negative influence of water on the reaction rate presum-ably resulted from the competitive adsorption between water and COon the catalyst surface. Since the assumptions included that by thesetwo species fully covering the surface, no constant term was includedin the denominator.

Van der Laan in 1999 [37] at first developed various LHHW-typekinetic expressions based on two hypotheses accounting for vacantsites and considering only entire coverage of surface in site balance.Accounting the vacant site in the site balance was a transition fromfull coverage of the catalytic surface to influence of vacant sites.By means of a statistical procedure to fit the best model with data,Van der Laan clarified that the effect of vacant sites on the surface isan important aspect in the site balance equation.

4. Discussion

Van Steen and Schulz [38] in the same year proposed a kineticscheme for the FT reaction where it was not necessary to apply theassumption of a slow, rate-determining step. As an alternative, theyassumed that the FT reaction proceeds via a series of consecutive,irreversible hydrogenation steps. Model IV results from this pro-posed scheme. Water still played a notable role in the kinetics, notby competing with CO for adsorption onto catalytic sites, but via amechanism where water influences the concentration of a surfacecarbon intermediate.

Years later, Botes (2006) considered a kinetic expression similar tothat of Van der Laan, but applied assumptions similar to those of vanSteen's, i.e., irreversibility of the hydrogenation steps has no precisemechanism whereby the reaction proceeds or the specific monomerare involved in the polymerization steps. After testing themodel againstvarious literature data sets, they concluded that there was no statisticalbasis for including thewater term. Consequently, themodel was simpli-fied to model-V, which described kinetic data better than the rateexpressions incorporating the effects of water or CO2.

Recently, Nakhaei pour et al., (2012) [39] has derived several LHHWtype rate equations based on detailed sets of possible reaction mecha-nisms originating from the carbide, enolic and combined enol/carbidemechanisms and developed three models for the Fischer–Tropsch reac-tion rates in agreement with observations. Model-VI is one of the mostsuccessful models based on the reaction step CH*+H2→ CH3* as a ratedetermining step.

5. Conclusion

Catalyst performance and kinetic of an iron-manganese catalyst wascarried out in a fixed-micro bed reactor. The results indicate that theincrease of the total pressure increases selectivity to the heavy hydro-carbons (C5+), while the selectivity to both methane and light gaseoushydrocarbon decreases. CO2 selectivity decreases with increasingtemperature because temperature shifts reaction pathways for oxygenremoval. Increasing the H2/CO feed ratio increases the partial pressureof H2 in the reaction media and thus increases the termination rateinto paraffins, reducing the amount of olefins produced by the reaction.Decreasing space velocity decreases selectivity to methane, while theselectivity to light (C2–4) and heavy (C5+) hydrocarbons and olefins

increases with increasing space velocity. Results also demonstrated alower GHSV results in higher WGS activity. The kinetic results showedthat water had an indirect influence in FTS rate. Comparisons ofobserved data to six mechanistic models and two power–law modelsindicates that the LHHWmechanisms are important, but not all equallysuited, to describe FTS.

NomenclatureA Kinetic parameter, unit is kinetic model dependentA0 Frequency factor, unit is kinetic model dependentCi Concentration of component i (mol/m3)kCO,H2

Adsorption parameter, unit is kinetic model dependentk0 Frequency factor, unit is kinetic model dependentdp Diameter of particle (m)E Activation energy, (J mol−1)L Length of reactor (m)ΔH Heat of adsorption (J mol−1)MARR Mean absolute relative residualsNCO,in CO molar flow rates in the reactor feed (m3 min−1)NCO,out CO molar flow rates in exit stream (m3 min−1)Nexp Number of experimental data points−rCO Rate of CO consumption (mol CO gcat−1 min−1),rCO,iexp Experimental CO conversion rate from in data point ith,

(mol CO min−1 gcat−1)rCO,imod Calculated CO conversion rate from each kinetic model in data

point ith, (mo CO min−1 gcat−1)P°CO Reactor inlet CO partial pressure (MPa, bar)R Universal gas constant (J mol−1 K−1)R2 Goodness of fitT Temperature (K, °C)u Superficial velocity (m/s)ν°in Volumetric flow rate of feed gas (m3 min−1)W Catalyst mass (g)

Greek symbolδ Mean absolute relative residualsρβ The catalyst bed density (kgcat/m3)Ψ Surface fractionσ mean value of initial rate

Acknowledgments

The authors gratefully acknowledge University of Sistan andBaluchestan for their kindness and support in this research.

References

[1] D. Dasgupta, T. Wiltowski, Enhancing gas phase Fischer–Tropsch synthesis catalystdesign, Fuel 90 (2011) 174–181.

[2] J. Hu, Yu. Fei, Y. Lu, Application of Fischer–Tropsch synthesis in biomass to liquidconversion, Catalysts 2 (2012) 303–326.

[3] D. Glasser, D. Hildebrandt, X. Liu, L. Xiaojun, M.M. Cornelius, Recent advances inunderstanding the Fischer–Tropsch synthesis (FTS) reaction, Current Opinion inChemical Engineering 1 (2012) 296–302.

[4] J. Xu, C.H. Bartholomew, Temperature-Programmed Hydrogenation (TPH) and insitu Mössbauer spectroscopy studies of carbonaceous species on silica-supportediron Fischer–Tropsch catalysts, Journal of Physical Chemistry B 109 (2005)2392–2403.

[5] J. Xu, C.H. Bartholomew, J. Sudweeks, D.L. Eggett, Design, synthesis, and catalyticproperties of silica-supported, pt-promoted iron Fischer–Tropsch catalysts, Topicsin Catalysis 26 (2003) 55–71.

[6] S. Li, A. Li, S. Krishnamoorthy, E. Iglesia, Effects of Zn, Cu, and K promoters on thestructure and on the reduction, carburization, and catalytic behavior of Fe-basedFischer Tropsch synthesis catalyst, Catalysis Letters 77 (2001) 197–210.

[7] Y. Liu, B.T. Teng, X.H. Guoa, Y. Li, J. Chang, L.X. Haoa, Y. Wang, H.W. Xiang, Y.Y. Xu, Y.W. Li, Effect of reaction conditions on the catalytic performance of Fe–Mn catalystfor Fischer–Tropsch synthesis, Journal of Molecular Catalysis A: Chemical 272(2007) 182–190.

170 M. Sarkari et al. / Fuel Processing Technology 127 (2014) 163–170

[8] Y. Yang, H.W. Xiang, Y.Y. Xu, L. Bai, Y.W. Li, Effect of potassium promoter onprecipitated iron manganese catalyst for Fischer–Tropsch synthesis, AppliedCatalysis A: General 266 (2004) 181–194.

[9] A. Nakhaei Pour, M.R. Housaindokht, S.F. Tayyari, J. Zarkesh, M.R. Alaei, Kineticstudies of the Fischer–Tropsch synthesis over La, Mg and Ca promoted nano-structured iron catalyst, Journal of Natural Gas Science and Engineering 2(2010) 61–68.

[10] S. Rojas, F.J. Pe'rez Alonso, M. Ojeda, P. Terreros, J.L.G. Fierro, Hydrogenation ofcarbon oxides over promoted Fe–Mn catalysts prepared by the microemulsionmethodology, Applied Catalysis A: General 311 (2006) 66–75.

[11] B.T. Teng, J. Chang, C.H. Zhang, D.B. Cao, J. Yang, Y. Liu, X.H. Guo, H.W. Xiang, Y.W. Li,A comprehensive kinetics model of Fischer–Tropsch synthesis over an industrialFe–Mn catalyst, Applied Catalysis A: General 301 (2006) 39–50.

[12] N. Lohitharn, J.G. Goodwin Jr., Effect of K promotion of Fe and FeMn Fischer–Tropschsynthesis catalysts: analysis at the site level using SSITKA, Journal of Catalysis 260(2008) 7–16.

[13] J. Gaube, H.F. Klein, Studies on the reaction mechanism of the Fischer–Tropschsynthesis on iron and cobalt, Journal of Molecular Catalysis A: Chemical 283(2008) 60–68.

[14] B.H. Davis, Fischer–Tropsch synthesis: reaction mechanisms for iron catalysts,Catalysis Today 141 (2009) 25–33.

[15] C.N. Satterfield, Heterogeneous catalysis in industrial practice, 2nd ed. McGraw Hill,New York, 1991.

[16] Y.C. Lin, L.T. Fan, S. Shafie, B. Bertk, F. Friedler, Generation of light hydrocarbonsthrough Fischer–Tropsch synthesis: identification of potentially dominant catalyticpathways via the graph-theoretic method and energetic analysis, Computers andChemical Engineering 33 (2009) 1182–1186.

[17] M. Ojeda, R. Nabar, A.U. Nilekar, A. Ishikawa, M. Mavrikakis, E. Iglesia, CO activationpathways and the mechanism of Fischer–Tropsch synthesis, Journal of Catalysis 297(2010) 272–287.

[18] J. Cheng, P. Hu, P. Ellis, S. French, G. Kelly, C.M. Lok, Some understanding of Fischer–Tropsch synthesis from density functional theory calculations, Topics in Catalysis 53(2010) 326–337.

[19] D.B. Cao, Y.W. Li, J. Wang, H. Jiao, Chain growth mechanism of Fischer–Tropschsynthesis on Fe5C2(001), Journal of Molecular Catalysis A: Chemical 346(2011) 55–69.

[20] F. Fischer, H. Tropsch, The direct synthesis of petroleumhydrocarbonswith standardpressure (First report), Berichte der Deutschen Chemischen Gesellschaft 59 (1926)830–831.

[21] P.M. Maitlis, A new view of the Fischer–Tropsch polymerisation reaction, Pure andApplied Chemistry 61 (1989) 1747–1754.

[22] O.R. Inderwildi, S.J. Jenkins, D.A. King, Fischer–Tropsch mechanism revisited:alternative pathways for the production of higher hydrocarbons from synthesisgas, Journal of Physical Chemistry C 112 (2008) 1305–1307.

[23] M. Ojeda, A. Ishikawa, E. Iglesia, R. Nabar, A. Nilekar, M. Mavrikakis, Fischer–TropschSynthesis Catalysis: Low-Temperature Fe Catalysts and the Mechanism for CODissociation on Fe and Co, paper presented at the 20th NAM, Houston, TX, June,2007, pp. 17–22.

[24] M. Ojeda, R. Nabar, A.U. Nilekar, A. Ishikawa, M. Mavrikakis, E. Iglesia, CO activationpathways and the mechanism of Fischer–Tropsch synthesis, Journal of Catalysis 272(2010) 287–297.

[25] C. Zhang, G. Zhao, K. Liu, Y. Yang, H. Xiang, Y. Li, Adsorption and reaction of CO andhydrogen on iron-based Fischer Tropsch synthesis catalysts, Journal of MolecularCatalysis A: Chemical 328 (2008) 35–43.

[26] H. Atashi, F. Siami, A.A. Mirzaei, M. Sarkari, Kinetic study of Fischer–Tropsch processon titania-supported cobalt–manganese catalyst, Journal of Industrial and EngineeringChemistry 16 (2010) 952–961.

[27] M. Arsalanfar, A.A. Mirzaei, H.R. Bozorgzadeh, H. Atashi, S. Shahriari, A. Pourdolat,Structural characteristics of supported cobalt–cerium oxide catalysts used inFischer–Tropsch synthesis, Journal of Natural Gas Science and Engineering 9(2012) 119–129.

[28] A.R. Miroliaei, F. Shahraki, H. Atashi, Computational fluid dynamics simulations ofpressure drop and heat transfer in fixed bed reactor with spherical particles, KoreanJournal of Chemical Engineering 28 (2011) 1474–1479.

[29] A.R. Miroliaei, F. Shahraki, H. Atashi, R. Karimzadeh, Comparison of CFD results andexperimental data in a fixed bed Fischer–Tropsch synthesis reactor, Journal ofIndustrial and Engineering Chemistry 18 (2012) 1912–1920.

[30] C. Perego, S. Peratello, Experimentalmethods in catalytic kinetics, Catalysis Today 52(1999) 133–145.

[31] G.P.V. Laan, A.A.C.M. Beenackers, Kinetics and selectivity of the Fischer–Tropschsynthesis: a literature review, Catalysis Reviews: Science and Engineering 41(1999) 255–318.

[32] M.E. Dry, The Fischer–Tropsch process: 1950–2000, Catalysis Today 71 (2002)227–241.

[33] F.G. Botes, B.B. Breman, Development and testing of a newmacro kinetic expressionfor the iron-based low-temperature Fischer–Tropsch reaction, Industrial andEngineering Chemistry Research 45 (2006) 7415–7426.

[34] Y. Liu, C.H. Zhang, Y.Wang, Y. Li, X. Hao, L. Bai, H.W. Xiang, Y.Y. Xu, B. Zhong, Y.W.Li, Effect of co-feeding carbon dioxide on Fischer–Tropsch synthesis over aniron–manganese catalyst in a spinning basket reactor, Fuel Processing Technology89 (2008) 234–241.

[35] R.B. Anderson, in: P.H. Emmett (Ed.), Catalysis, vol. IV, Reinhold PublishingCorporation, New York, 1956, (Chapter 3).

[36] P.J. van Berge, Cobalt as an alternative Fischer–Tropsch catalyst to iron for theproduction of middle distillates, Studies in Surface Science and Catalysis 107(1997) 207–212.

[37] Gerard P. van der Laan, Antonie A.C.M. Beenackers, Intrinsic kinetics of the gas–solidFischer–Tropsch and water gas shift reactions over a precipitated iron catalyst,Applied Catalysis A: General 193 (2000) 39–53.

[38] E. Van Steen, H. Schulz, Polymerisation kinetics of the Fischer–Tropsch COhydrogenation using iron and cobalt based catalysts, Applied Catalysis, A: General186 (1999) 309–320.

[39] A. Nakhaei Pour, M.R. Housaindokht, J. Zarkesh, M. Irani, E. Ganji Babakhani, Kineticsstudy of CO hydrogenation on a precipitated iron catalyst, Journal of Industrial andEngineering Chemistry 18 (2012) 597–603.

[40] K. Tapan, Z. Xiaodong, L. Jinlin, G. Jacobs,M.E. Dry, B.H. Davis, in: H. Davis,M.L. Occelli(Eds.), Fischer–Tropsch Synthesis: Kinetics and Effect of Water for a Co/Al2O3Catalyst, Fischer–Tropsch Synthesis, Catalysts and Catalysis, 2007, pp. 289–314.

[41] K. Tapan,W.A. Conner, Li Jinlin, G. Jacobs, M.E. Dry, H. Burtron Davis, Fischer Tropschsynthesis: kinetics and effect of water for a Co/SiO2 catalyst, Energy & Fuels 19(2005) 1430–1439.

[42] Y. Liu, B.T. Teng, X.H. Guoa, Y. Li, J. Chang, H. Tian, L.X. Wang, Y. Xiang, Y.Y. Xu, Y.W.Li, Effect of reaction conditions on the catalytic performance of Fe–Mn catalyst forFischer–Tropsch synthesis, Journal of Molecular Catalysis A: Chemical 272 (2007)182–190.

[43] M.E. Dry, Practical and theoretical aspects of the catalytic Fischer–Tropsch process,Applied Catalysis, A: General 138 (1996) 319–344.

[44] L. Tian, C.F. Huo, D.B. Cao, Y. Yang, J. Xu, B.S. Wu, H.W. Xiang, Y.Y. Xu, Li, Effects ofreaction conditions on iron catalyzed Fischer–Tropsch synthesis: xA kinetic MonteCarlo study, Journal of Molecular Structure: THEOCHEM 941 (2010) 30–35.

[45] R. Sethuraman, N.N. Bakhshi, S.P. Katikaneni, R.O. Idem, Production of C4hydrocarbons from Fischer–Tropsch synthesis in a follow bed reactor consisting ofCo–Ni–ZrO2 and sulfated ZrO2 catalyst beds, Fuel Processing Technology 73(2001) 197–222.

[46] A. Sari, Y. Zamani, S.A. Taheri, Intrinsic kinetics of Fischer–Tropsch reactions over an in-dustrial Co–Ru/γ-Al2O3, catalyst in slurry phase reactor, Fuel Processing Technology90 (2009) 1305–1313.

[47] T. Ngwenya, D. Glasser, D. Hildebrandt, N. Coville, P. Mukoma, Fischer–Tropschresults and their analysis for reactor synthesis, Industrial and Engineering ChemistryResearch 44 (2005) 5987–5994.

[48] C.G. Visconti, Z. Ballova, L. Lietti, E. Tronconi, R. Zennaro, P. Forzatti, Advances inFischer–Tropsch Synthesis, Catalysts and CatalysisCRC Press Taylor & FrancisGroup, New York, 2010.

[49] H. Zarrin, M.T. Sadeghiy, M.A. Marvast, Modeling and sensitivity analysis of acatalyst pellet with non-uniform activity distribution in Fischer–Tropsch synthesis,International Journal of Chemical Reactor Engineering 7 (2009) (Article A52).

[50] A. Steynberg, M. Dry, Fischer–Tropsch technology, basic studies, Study in surfacescience and catalysis, Elsevier Science & Technology Books, 2004, ISBN 044451354X.(chapter 8).

[51] M. Claeys, E.V. Steen, On the effect of water during Fischer–Tropsch synthesis with aruthenium catalyst, Catalysis Today 71 (2002) 419–427.

[52] F.G. Botes, The effects of water and CO2 on the reaction kinetics in the iron-basedlow-temperature Fischer–Tropsch synthesis: a literature review, Catalysis Reviews:Science and Engineering 50 (2008) 471–491.

[53] M.E. Dry, Advances in Fischer–Tropsch chemistry, Industrial and EngineeringChemistry Product Research and Development 15 (1976) 282–286.

[54] H.E. Atwood, C.O. Bennett, Kinetics of the Fischer–Tropsch Reaction over iron,Industrial and Engineering Chemistry Product Research and Development 18(1979) 163–170.

[55] T.B. Leib, J.C.W. Kuo, Modeling the Fischer–Tropsch synthesis in slurry bubble-column reactors, Paper presented at the AIChE Annual Meet., San Francisco,California, 1984.

[56] H.R. Nettelhoff, S. Ledakowicz, W.D. Deckwer, Studies on the kinetics of Fischer–Tropsch synthesis in slurry phase, German Chemical Engineering 8 (1985) 177–185.

[57] W.H. Zimmerman,D.B. Bukur, Reaction kinetics over iron catalysts used for the Fischer–Tropsch synthesis, Canadian Journal of Chemical Engineering 68 (1990) 292–301.

[58] W. Shen, J. Zhou, B. Zhang, Kinetics of Fischer–Tropsch synthesis over precipitatediron catalyst, Journal of Natural Gas Chemistry 4 (1994) 385.