Kinetics, Modeling, and Process Design of Hydrogen Production by

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Kinetics, modelling and process design of hydrogen production by aqueous phase reforming of xylitol Dmitry Yu. Murzin, Sonia Garcia, Vincenzo Russo, Teuvo Tapani Kilpiö, Lidia I. Godina, Anton Tokarev, Alexey Kirilin, Irina L. Simakova, Stephen Poulston, Dmitry A. Sladkovskiy, and Johan Warna Ind. Eng. Chem. Res., Just Accepted Manuscript • DOI: 10.1021/acs.iecr.7b01636 • Publication Date (Web): 30 Jun 2017 Downloaded from http://pubs.acs.org on July 4, 2017

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Industrial & Engineering Chemistry Research

Kinetics, modelling and process design of hydrogen production by aqueous phase reforming of xylitol Dmitry Yu. Murzin1*, Sonia Garcia2, Vincenzo Russo1,3, Teuvo Kilpiö1, Lidia I. Godina1, Anton V. Tokarev1, Alexey V. Kirilin, Irina L. Simakova4, Stephen Poulston2, Dmitry A. Sladkovskiy5, Johan Wärnå1 1

Laboratory of Industrial Chemistry and Reaction Engineering, Process Chemistry Centre, Åbo Akademi University, FI-20500 Turku/Åbo, Finland

2

Johnson Matthey Technology Centre, Sonning Common, Reading RG4 9NH, UK 3

Universita degli Studi di Napoli “Federico II”, 80138, Naples, Italy 4

5

Boreskov Institute of Catalysis, 630090, Novosibirsk, Russia

St. Petersburg State Institute of Technology (Technical University), St. Petersburg, 190013, Russia * corresponding author: [email protected]

Abstract The present study was focused on kinetic investigation of xylitol aqueous phase reforming with 2.5%Pt/C catalyst in a fixed bed reactor. For kinetic modelling a complex reaction network was taken into account considering formation not only hydrogen and CO2, but also a range of alkanes in various side reactions. Parameter investigation revealed an adequate description of the experimental data. Influence of mass transfer was elucidated by exploring the parameter space of diffusion and mass transfer coefficients as well as Peclet numbers. Aspen HYSYS software was used to design a hydrogen production plant with 500 kg/h capacity operating with xylitol as a feedstock. Heat consumption of the designed process can be fully covered by heat generated combusting alkanes formed during APR reaction. Keywords: Hydrogen production, xylitol, aqueous phase reforming, kinetic and mass transfer modelling, process design

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Introduction Aqueous phase reforming (APR) of polyols [1-6] is a promising technology to generate hydrogen at temperature lower than in the case of the most important large scale hydrogen generation technology- high temperature methane steam reforming. APR therefore can lead to a decrease of energy consumption as it requires relatively mild reaction conditions (ca. 225°C, 30-50 bar) eliminating generation of steam and generating additional hydrogen through the water gas shift reaction. A range of substrates starting from such alcohols as methanol, ethanol, propanol, and including diols and polyols has been studied [7-13]. The hydrogen yields from APR of sugars are lower than for the corresponding more reduced compounds, such as sugar alcohols [2], therefore the latter are selected as the starting compounds .Typically water solutions of polyols are utilized with the overall system pressure during APR being ca. 4 bar above the pressure of saturated water vapors at the experimental temperature. Aqueous-phase reforming of polyols can be performed over various supported metal catalysts with Pt being the most effective in terms of activity and selectivity to desired products [3]. In practice not only hydrogen and CO (or in fact carbon dioxide due to WGS reaction) but also alkanes in the gas phase and a range of different intermediates in the liquid phase are typically formed. Application of Lewis acids such as alumina as a support promotes the reaction path involving dehydration on acid sites and subsequent hydrogenation of the formed olefin. Alternatively alkanes can be formed by a sequence of direct hydrodeoxygenation of –OH groups in the substrate if sufficient amounts of hydrogen are available. Thus there is a possibility to change selectivity to alkanes by, for example, selecting a more acidic support or introducing to platinum a particular promoter, such as for example Re [9, 10]. In addition to influencing selectivity hydrothermal stability of alumina might be of concern, because metal free γ-alumina undergoes phase transformation into boehmite in liquid water at 2 ACS Paragon Plus Environment

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temperatures even below the one needed for APR [13]. Carbon supports being less mechanically stable and giving lower yields compared to metal oxides [15] have at the same better hydrothermal stability [16], tunable chemical and textural surface properties. For development of a viable technology kinetics of APR process should be established. There are surprising few studies addressing kinetics and in particular kinetic modeling of aqueous phase reforming with C5 and C6 polyols as a feedstock. Aiouache et al. [19] used a batch reactor for kinetic studies on sorbitol APR with over Ni and Ni-Pd catalysts supported on γAl2O3, ZrO2 and CeO2 applying a lumped kinetic model and describing only formation of gaseous products. While APR is utilized for production of hydrogen and alkanes; co-feeding of hydrogen results in so-called aqueous-phase dehydration/hydrogenation (APD/H) aiming at production of hydrocarbons [18]. Moreno et al. developed a kinetic model for sorbitol hydrodeoxygenation (i.e. APD/H) in the presence of Pt/SiO2-Al2O3 based on automated network generation method [19]. A rather complicated network of 4804 reactions and 1178 distinct chemical compounds was used to identify 43 reaction components and grouped them according to the number of carbon atoms and functionality. Finally, the authors [19] made a comparison between calculated and experimental mass flow. A mechanistic model for sorbitol APR was developed by Kirilin et al. [8] and compared with experimental data generated with Pt/Al2O3 catalyst in a continuous fixed-bed reactor. The model (Figure 1) included dehydrogenation of the substrate followed by decarbonylation (Path 1) and dehydration followed by hydrogenation (Path 2). Although formation of the main gaseous products and lumped liquid products were accounted for in the model, the experimental data were obtained at conditions giving 100% conversion of the starting substrate. While this is obviously beneficial from the viewpoint of the APR reaction per se, a comparison between experimentally observed and calculated concentrations at short residence 3 ACS Paragon Plus Environment


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times cannot be done in a reliable way.

Figure 1. Aqueous phase reforming of sorbitol. Reproduced with modifications from [8] with permission from American Chemical Society.

No kinetic data are available for aqueous phase reforming of xylitol, which is the second most abundant polyol being produced industrially by hydrogenation of xylose [20, 21]. The latter sugar is a building block for xylan and is a product of hydrolysis of the latter. A high content of a hemicellulose - xylan in hardwood species is a reason why this source is considered to be attractive for xylose and further xylitol production [22]. For instance, in some hardwood species xylose content in the heartwood part can exceed 26 wt. % [23]. Availability of natural and renewable sources for xylitol production and absence of kinetic studies on aqueous phase reforming process of xylitol (Figure 2) encouraged the current study.

Figure 2. Aqueous phase reforming of xylitol representing the stoichiometry of H2 and CO2 formed. 4 ACS Paragon Plus Environment

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Because of concerns related to poor hydrothermal stability of alumina in particular its transformations to boehmite, platinum on a carbon support was selected as a catalyst. In additional to kinetic studies and kinetic modelling based on a plausible reaction mechanism the influence of mass transfer and hydrodynamics was explored through simulations studies. Finally, the mass and energy balances for industrial scale process concept were considered based on a basic process flowsheet. 2 Experimental 2.1. Materials The catalyst used in APR of xylitol was provided by Johnson Matthey. It contained 2.5% Pt on a carbon support in the powder form below 125 µm. 2.2. Characterization methods Samples of Pt supported on carbon supports were analyzed by a variety of state-of-the-art physical methods including transmission electron microscopy (TEM) to estimate Pt NPs size, X-ray fluorescent analysis (XRF) to control Pt content, and low-temperature N2 physisorption to determine pore volume and average pore size. TEM. Transmission electron microscopy (TEM) was performed with a JEOL 2010 microscope. Before TEM measurements the samples were dispersed in ethanol and dropped on a copper grid coated with a carbon film. To estimate the value of mean diameter of Pt nanoparticles more than 250 particles were chosen. The mean diameter (dm) of particles was

∑ (x d ∑x i

calculated using the following equation: d m =

i

i

)

, where xi is the number of particles

i

i

with diameter di. The mean surface diameter (ds) of particles was calculated using the

following equation: d s

∑ (x d = ∑ (x d i

i

i

i

3

)

2

)

i

, where xi is the number of particles with diameter di.

i



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XRF. Semi-quantitative analysis of metal concentrations was performed using wavelength dispersive X-ray fluorescence (WDXRF) spectrometry with the powder pellet method. Undiluted samples (0.5 g) were milled and put in the 29 mm diameter die. The intensities of the metal lines in the samples were measured in vacuum conditions on an ARL Advant’X spectrometer equipped with a rhodium anode X-Ray tube. Excitation conditions were as follows: tube voltage of 50 kV; current of 40 mA; collimator with a divergence of 0.25°; LiF200 crystal was used as a monochromator; scintillation counter was used as a detector; counting time was 12 s. Contents of elements in the sample were estimated using semiquantitative method by means of a QuantAS program for analysis without standards. Surface area and porosity. The textural properties were determined using BET method by physisorption of nitrogen at 77K in a Micromeritics Model ASAP 2400 equipment. The specific surface area was calculated using BET method within the relative partial pressure range of 0.05 – 0.25. Prior to surface area measurements, the samples were treated in vacuum (0.05 mbar) at 200°C for 12 hours. Chemisorption. The metal dispersion was determined by CO pulse chemisorption with Autochem 2900 instrument (Micrometrics). The catalyst was reduced prior to measurement with the following program: 25–50°C at 10°Cmin-1 in He, dwell for 30 min, gas-switch to H2, 5°Cmin-1 to 250°C, dwell for 2 h, followed by flushing for 60 min in He at 250°C. Thereafter the catalyst was cooled to ambient temperature and CO pulses were introduced utilizing 10 vol. % CO in He. A Pt/CO stoichiometry of 1:1 was assumed. Temperature programmed reduction. The temperature programmed reduction (TPR) of the catalyst was performed in an AutoChem (Micromeritics). The TPR was measured by placing approximately 0.1 g of catalyst in a U-shaped tube which was cooled to 25°C in Ar. The catalyst was reduced using 5% H2 in Ar with the temperature being ramped from 25°C to


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400°C at a rate of 5°C/min and the hydrogen uptake monitored by a thermal conductivity detector (TCD). Ammonia Temperature Programmed Desorption. The NH3-TPD measurements were performed using Micromeritics Autochem 2910 apparatus. A detailed description of the measurement procedure is provided in [7]. Prior to NH3 treatment the catalyst sample (0.1 g) was dried in oven at 100°C overnight. After reduction in a hydrogen flow (20 ml×min-1) at a ramping rate 5°C×min-1 to 250°C followed by dwelling for 2 h and flushing with He (20 ml×min-1) for 30 min to remove hydrogen, the catalyst was cooled to ambient temperature and then saturated with NH3 (gas mixture 5% of NH3 in He) for 1 h. This was followed by flushing with He for 30 min to remove physically adsorbed ammonia. Temperatureprogrammed desorption was performed in the temperature interval 25-225°C at the various heating rates. In between the cycles the catalyst was treated by a mixture of ammonia in helium as described above. Ammonia desorption was monitored by the changes in TCD signal. Heats of desorption were calculated by plotting Tp (temperature at maximum of desorption) versus ln (Tp2/β) (where β corresponds to a heating rate) followed by calculation of the slope (k), Edes = R/k [kJ×mol-1]. The amount of acid sites for each catalyst was counted as amount of ammonia desorbed upon heating at 3°C×min-1. The values are reported as amount of NH3 desorbed per gram of catalyst.

2.3. Catalytic experiments and reaction component analysis A continuous fixed-bed reactor setup (stainless steel reactor, d = 64 mm (external diameter), l = 52 cm) equipped with a furnace was used [10]. In the experiment the catalyst (0.5 g) was mixed with 0.5 g of quartz sand and loaded into the reactor. The catalyst was reduced in-situ prior to the measurements in H2 flow (AGA Oy, purity >99.999%) at 250oC. The reaction was carried out at 498 K and 29.3 bar, at a range of flow rates 0.1 – 0.8 ml /min corresponding to



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space velocities from 1.2 to 9.6 h–1. A mixture of 1 vol.% of He in N2 (AGA Oy) was used as a carrier gas (flow 33 ml/min). Weight hourly space velocity (WHSV) is defined as mass of substrate fed per mass of the catalyst per hour [gsub x gcat-1 x h-1]. An aqueous solution (10 wt.%) of xylitol (Sigma Aldrich) was used as the feedstock and fed in a continuous manner via HPLC pump. The reactor is coupled to the micro-GC system; therefore, gaseous products were taken periodically and analyzed with Agilent Micro GC 3000A. The GC is equipped with 4 columns: Plot U, OV-1, Alumina and Molsieve. The micro-GC was calibrated to perform quantitative analysis for the following gases: H2, CO2, CO, CH4, linear and branched hydrocarbons C1-C7 while 1 vol.% of He in N2 was used as an internal standard. Liquid samples were withdrawn periodically and analyzed by means of high-performance liquid chromatography (HPLC), applying an injection volume 3 µl, Aminex HPX-87H column, eluent 5mM H2SO4, flow rate 0.6 ml min-1, 318 K, 70 min) using a refractive index (RI) detector to determine conversion of the substrate. The carbon balance was monitored by means of total organic carbon analysis (TOC instrument) and was confirmed to a degree of 80-100% for all the measurements. The following equations were used for calculation of conversion and selectivity: The substrate conversion is determined from

conversion, (%) = (1 −

N ( feed _ out) ) ×100% N ( feed _ in)

(1)

where N(feed in) is an incoming molar flow of the substrate (mol/min), and N(feed out) is an outgoing molar flow of the unreacted substrate (mol/min). Selectivity to hydrogen is determined by

selectivity, H 2 (%) =

N (H2 ) ×1 / RR ×100% , N (Cin gas )

(2)

where N(H2) is hydrogen molar flow (mol/min), N(Cin gas) is the total molar flow of carbon in the gas phase (mol/min), and RR is the theoretical H2/CO2 ratio. The latter corresponds to the 8 ACS Paragon Plus Environment

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theoretically possible one at full conversion of an alcohol exclusively to CO2 and hydrogen and depends on the substrate type. The reforming ratio 11/5 was used according to the overall stoichiometry followed from Figure 2. Selectivity to other gas-phase products is determined by selectivity, X (%) =

N (Cx ) × 100% , N (Cin gas )

(3)

where N(Cx) is the carbon molar flow in component X (mol C/min). Calculations of the Weisz-Prater showed that it has the value of ca. 10-4, confirming absence of intraparticle mass transfer limitations.

3. Results and Discussion 3.1. Catalyst characterization XRF, TEM, CO chemisorption, N2 physisorption, TPD NH3 and TPR H2 techniques were applied to characterize Pt/C catalyst. The metal loading according to XRF in the fresh catalyst was 2.5% the same loading was obtained for the spent catalyst indicating absence of metal losses during the reaction. According to CO impulse chemisorption the metal dispersion in fresh Pt/C catalyst was 43% and subsequently the mean diameter of Pt particles was calculated to be dPt = 2.6 nm. TEM analysis of the fresh catalyst confirmed the mean particle size of Pt to be rather close to CO chemisorption giving dm = 2.05 nm with a standard deviation of 0.55, as shown in Figure 3a. TEM measurements were also applied to estimate Pt NPs size and distribution in the spent Pt/C after 130 h time-on-stream. The Pt nanoparticles found by TEM in the spent sample is characterized with a semispherical shape practically without any well detectable crystallographic planes (Fig. 3b). The values of mean diameter of Pt nanoparticles estimated from TEM images are presented in Fig. 3. The spent sample is characterized with the mean



size of Pt nanoparticles dm = 1.7 nm closed to mean surface size ds =1.8 nm (Fig. 3b) demonstrating high resistance of Pt NPs to sintering. Surface area and porosity. According to N2-physisorption data Pt/C catalyst contains microand mesopores. The textural characteristics of the spent Pt/C catalyst are collected in Table 1.

a) Sampel JM2 size - 307 mean - 1.7 nm SD - 0.3 ds - 1.8 nm

160 140 120

dm - 1.8 nm

100

Count

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

80 60 40 20 0 1.0

1.5

2.0

2.5

3.0

3.5

size, nm

b)

Figure 3. TEM images and histogram of a) fresh and b) spent Pt/C catalyst.

Table 1. The textural characteristics for the fresh and spent Pt/C catalysts. N2 physisorption Catalyst Specific surface

Pore Volume,


dav, nm

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area, m2/g

cm3/g

by BJH method

Pt/C fresh

951 ± 15

0.80

6.3

Pt/C spent

1150 ±15 (incl. micropore area 843)

0.82 (incl. micropore volume 0.37)

6.4

The surface area and the pore volume of the spent catalyst are very close to the properties of the fresh catalysts and to the properties of the carbon support used in catalyst preparation (surface area of 1050 m2/g and pore volume 0.8 m3/g). The catalyst was analysed with NH3 TPD (Fig. 4). The heat of desorption was rather low (37 kJ×mol-1) indicating that presence of weak acidic sites. This is also confirmed by the Tp of ammonia desorption not exceeding 376 K. Previously similar values of maximum desorption temperature were reported for several Pt/C catalysts [7]. Surface acidity is determined by various functional groups present on the carbon surface, such as carboxyl, carbonyl and hydroxyl species. Low acidity of the carbon support should be beneficial for selective formation of hydrogen and CO2 in APR of xylitol as formation of alkanes is promoted in the presence of acid sites. 0.7

103°C 7.4

0.6

98°C

0.5

7.2

20°C/min

0.4

7.0

89°C

ln (T p 2 /β)

Concentration of NH3, %

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


15°C/min

0.3

10°C/min 0.2

6.8 6.6

69°C

0.1

6.4

3°C/min 0.0

Edes= 37 kJ/mol

6.2

0

50

100

150

200

250

9

10

Temperature, °C

11

12

13

14

15

103/Tp

Figure 4. Ammonia TPD from 2.5%Pt/C catalyst.

H2 TPR is shown in Figure 5. The catalyst was reduced after preparation. The peak at 175oC correspond to the reduction PtOx species, while a broad peak starting with the maximum at 11 ACS Paragon Plus Environment


360oC can correspond to reduction of weak surface groups of the support [24]. In the the current work the catalyst was reduced at 250°C which is sufficient enough to reduce the metal per se as can be seen from TPR.

0.1

H 2 uptake, a.u.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

360°C

175°C 0.0

0

100

200

300

400

500

Temperature , °C

Figure 5. H2 TPR of 2.5%Pt/C catalyst.

3.2 Catalytic results The catalyst stability was studied at T=498K and p=29.3 bar (Figure 6). Stability measurements were combined with studies of catalytic performance. A flow rate of 0.2 ml/min was used regularly in the long-term experiment with varying the flow rates to elucidate if there were changes in catalytic behavior. After a certain initial decline in activity with time-on-stream (TOS) conversion stabilized and the catalyst demonstrated a stable performance after 40 h TOS. Previously [6] stable behavior exceeding 160 hours was shown for xylitol APR on Pt with alumina as a support. Interestingly enough, similar to [6] the selectivity profiles in the current work were also dependent on TOS. In particular, selectivity to CO2 was constant, while selectivity to H2 was increasing. However, production of both gases and the overall carbon content in the gas-phase products diminished with time-onstream. In [6] it was suggested that various oxygenated intermediates formed during


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reforming may adsorb on the Pt surface influencing selectivity to hydrogen rather than the overall activity. 100

H2

80

selectivity to H2 [%]

60

conversion [%]

40

20

gas production [mol/min]

selectivity to CO2 [%]

[%]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


0

0,0004

0,0003

CO2 0,0002

0,0001

Total carbon in gas 0,0000

0

50

100

150

0

50

TOS (h)

100

150

TOS (h)

Figure 6. Time-on-stream behaviour of 2.5 wt% Pt/C in xylitol APR.

The observed decline of CO2 and H2 production could not be affected by change in Pt nanoparticles size since catalyst demonstrated high resistance to sintering (Fig. 3). Cleavage of C-O bonds, i.e. hydrogenolysis, occurring over platinum sites may lead to a partial oxidation of platinum particles and can be a reason for time-on-stream behavior. In fact higher oxidation of platinum was reported based on XPS results for the catalyst applied for APR of C3 alcohols and diols [24]. In general deactivation in APR is mainly attributed to either changes of the oxidation state of the active metal or hydrothermal degradation of the support [2] as deactivation by coking is much less probable because of large excess of water and reasonably moderate reaction temperatures. Conversion of the feedstock, selectivity to hydrogen, CO2, individual alkanes, and total selectivity to alkanes as a function of space velocity are shown in Figure 7.



a)

8

b)

H2

100

6

60

selectivity [%]

CO2

80

[%]

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conversion

40

C3H8

4

CH4 C2H6

n-C4H10

2

n-C5H12

alkanes

20

others

0 0

2

4

6

8

10

0

2

WSHV [1/h]

4

6

8

10

WSHV [1/h]

Figure 7. Catalytic data on xylitol APR with 2.5 wt % Pt/C. a) Conversion of the feedstock, selectivity to hydrogen and CO2, and total selectivity to alkanes vs WSHV; b) Selectivity to alkanes as a function of WSHV. “Others” stand for iso-C5H12, n-C6H14 and iso-C6H14.

In the previous work of the authors on xylitol APR [6] using 5 wt% Pt/alumina catalyst in range of space velocities from 0.6 h-1 to 1.5 h-1, the conversion was always 100%. Such behavior was attributed to the fact that only a part of the catalyst layer is active preventing at the same time any meaningful kinetic analysis. As one can see from Figure 7, in the current work conversion of xylitol was in the region of 20-100%, allowing assessment of reaction kinetics. The fluctuations of the curve are related to the changes in the catalytic activity during experiments. About a half of the carbon from the substrate was transformed to CO2, which can be seen by comparison of selectivity to CO2 and total selectivity to alkanes (Figure 7) and carbon distribution (Figure 8). Only negligible formation of carbon monoxide was detected.


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100

Gas-phase products

80

carbon content [%]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


60

Liquid -phase intermediates

40

Xylitol

20

0 20

40

60

80

100

Conversion [%]

Figure 8. Carbon distribution in gas and liquid phases vs conversion of xylitol: molar percentage of carbon in gas-phase products (the upper segment), in liquid-phase intermediates (the middle segment) and in the initial feed (the lower segment).

Various light alkanes of linear structure ranging from C1 to C6 were observed. Figure 7 illustrates that propane was the dominant alkane, followed by methane and ethane. Selectivity to butane was ca. two-three fold lower than that of propane. From Figure 7 it can be also seen, that there are traces of hexane among other gas products. Previously formation of hexane was reported by Jiang et al [25] during APR of xylitol over Pt/HZSM-5 and Ni/HZSM-5 catalysts. In [10] n-heptane generation was observed in APR of sorbitol. Such alkanes having an extra carbon atom than the substrate can be formed through condensation reaction and subsequent hydrodeoxygenation. In addition it should be mentioned that the catalyst became more selective to alkanes and less to hydrogen at higher conversion levels, which is unfavourable for hydrogen production by APR. Total carbon balance is visualised in Figure 8 (the upper line). It can be seen that carbon present in the substrate is gradually transformed from the initial feed to the gas phase products through various liquid-phase intermediates. It should be noted that hydrogen generation using similar type of organic compounds present in waste waters can be an additional benefit in utilization of APR [2]. 15 ACS Paragon Plus Environment


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There have been several studies targeted on identification of reaction products and intermediates in APR of xylitol [6] and sorbitol [7, 8, 10]. It was reported that compounds with different functionality such as monoalchohols, diols, triols, carboxylic acids, ketones and hydroxyketones are formed as liquid phase intermediates [10]. 3.3. Reaction network and kinetic modelling As mentioned above the main products which are formed during aqueous-phase reforming of xylitol are H2, CO2, a mixture of alkanes in the gas phase (mainly C1-C5) as well as oxygenated products present in the liquid phase. Because concentration of carbon monoxide was very low it can be suggested that CO formed in APR is converted very fast via WGS reaction giving CO2 and additional hydrogen. Rather complex reaction network and far from precise knowledge of various reaction intermediates call for a simplification of the reaction network focusing predominantly on consumption of xylitol, formation of hydrogen, CO2 and alkanes (Figure 9). Within the framework of such approach several intermediates with different carbon number have been considered leading to CO2 and hydrogen as well as different alkanes. For the data fitting purposes

these

intermediates

were

lumped

into

one

pseudo-component

named

“intermediates”. Gas phase compounds C6H14 were not included in the model due to their lower concentrations.


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Figure 9. Reaction network used in kinetic modelling of xylitol APR, where Int. denotes various intermediates.

The equation for the reaction rates presented in Figure 9 are written for formation of intermediates in various ri steps

ri1 =

ri 4 =

ki1CXylitol (1 + K xC Xylitol )

; ri 2 =

ki 2CInt,1 ki 3CInt,2 ; ri 3 = ; (1 + KxCXylitol) (1 + KxCXylitol)

ki 4CInt,3 ki5CInt,4 ki 6C Xylitol ; ri 5 = ; r1i 6 = (1 + KxCXylitol) (1 + K1CXylitol ) (1 + K xCXylitol )

(4)

Reaction rates for generation of carbon dioxide and hydrogen are defined as

r1 =

k1CInt ,1 k2CInt ,2 k3CInt ,3 ; r2 = ; r3 = ; (1 + K xC Xylitol ) (1 + K xC Xylitol ) (1 + K xCXylitol )

r4 =

k4CInt ,4 k5CInt ,5 k6CInt ,6 ; r5 = ; r6 = (1 + K xCXylitol ) (1 + K xCXylitol ) (1 + K xCXylitol )

(5)

In the equations (4) and (5) only adsorption of xylitol was taken into account. In the preliminary development of the kinetic model adsorption of other reactants was also considered. However, initial parameter estimation showed that the calculated terms in the denominator involving adsorption coefficients for other substances and their concentrations are very low. This allows to assume that coverage of these species is rather low. The constants in eq. (4) and (5) are in fact lumped ones comprising also respective adsorption constants.

Formation of alkanes by various hydrodeoxygenation involves hydrogen participation, therefore concentration of hydrogen was taken into account in those reactions



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r11 =

r15 =

k11CInt,1CH 2 (1 + KxCXylitol)

; r12 =


; r13 =


; r14 =

k15CInt,5CH 2


Page 18 of 40

;

(6)

(1 + KxCXylitol)

Eq. (6) implies the first order in hydrogen, very often observed in various hydrogenation reactions, especially at low partial pressures of hydrogen as is the case in the present work. Preliminary calculations with a model assuming competitive adsorption of hydrogen on the same sites resulted in negligible influence of the hydrogen adsorption term, therefore, it was omitted in subsequent calculations.

The consumption rate of xylitol is thus

− rxylitol = ri1 + ri 6

(7)

Formation rates for hydrogen should take into account the stoichiometry of various reactions leading to hydrogen generation and consumption. If no alkanes would be formed in APR giving exclusively CO2 and hydrogen the stoichiometric coefficient for hydrogen should be equal to 11 as implicitly follows from Figure 2. Hydrogen is, however, generated from various intermediates, which have different content of hydrogen, oxygen and carbon even at the same carbon number, and thus different stoichiometry for hydrogen formation. Due to a large number of reactions involved in hydrogen generation, it is impossible to use exact stoichiometric coefficients. Instead it was decided to use a lumped stoichiometric coefficient b

rH 2,tot = b(r1 + r2 + r3 + r4 + r5 + r6 − r11 − r12 − r13 − r14 − r15 )

(8)

For carbon dioxide a somewhat different approach was used. It can be suggested that intermediates have a different number of carbon atoms. For instance intermediate 5 giving pentane can have 5 carbons atoms, while 4 carbons atoms are present in intermediate 2, etc. In this way the reaction rate for carbon dioxide formation is


Page 19 of 40

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rCO 2,tot = c(5r6 + 5r1 + 4r2 + 3r3 + 2r4 + r5 )

(9)

If APR results only in hydrogen and carbon dioxide without any alkanes the value of lumped coefficient c should be equal to unity. The following relationship was also introduced keeping the ratio between some rate constants to ensure that there are not big changes in selectivity to CO2 and alkanes after complete transformation of xylitol

r11 + r12 + r13 + r14 + r15 =d r6 + r1 + r2 + r3 + r4 + r5 − r11 − r12 − r13 − r14 − r15

(10)

The generation rates of intermediate are given as

rInt ,1 = ai1ri1 − r11 − r1 − ri 2 / ai 2 ; rInt ,2 = ai 2 ri 2 − r12 − r2 − ri 3 / ai 3 ; rInt ,3 = ai 3ri 3 − r13 − r3 − ri 4 / ai 4 ; rInt ,4 = ai 4 ri 4 − r14 − r4 − ri 5 / ai 5 ; rInt ,5 = ai 5ri 5 − r15 − r5 ; rInt ,6 = ri 6 − r6

(11)

Parameters ai1 to ai5 reflect stoichiometry of intermediate transformations to other intermediates. Assuming that the carbon number in a particular intermediate corresponds to the number of carbons in a respective alkane, the values of these parameters are: ai1=1; ai2=1.25; ai3=1.33; ai4=1.5; ai5=2. For instance when C2 reacts by splitting a carbon-carbon bond, 2 C1 molecules are formed, therefore ai5=2, analogously 4C5 give 5C4, thus ai2=5/4=1.2. The kinetic modeling was done for all reaction rates using a steady state model of a packed bed reactor. For the calculation of parameters, a set of differential equations, describing the changes in the concentrations profiles of the reagents and products along the reactor length (proportional to residence time) was solved by means of ModEst software [26] taking into account changes in the volume. Using Levenberg-Marquardt simplex method, the target function, which was defined as incompliance between the experimental and calculated values of concentrations with residence time was used to solve the system. The sum of the residual



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Page 20 of 40

squares between the model and the experimental data was minimized using the following objective function;

Q = xexp − xest

2

= ∑∑ (xexp,iτ − xest ,iτ )

2

τ

(12)

i

where xexp is the experimental value and xest denotes the predictions given by the model, i is the component index and

τ

is the residence time value. The quality of the fit and accuracy of

the model description was defined by the degree of explanation R2; which reflects comparison between the residuals given by the model to the residuals of the simpliest model one may −

think of, i.e. the average value of all the data points y exp . The R2 value is given by the expression 2

R = 100

( ymod − yexp )2

(13)

−

( ymod − y exp )2 The results of calculations are presented in Figure 10, while the kinetic parameters are shown in Table 2. The proposed kinetic model fits the experimental data rather well (Fig. 10) being able to describe concentration of the main compounds very well. Some deviations were observed for minor components such as pentane, present in almost trace amounts. Due to a large number of parameters on one hand and lumping intermediates to a single pseudo-component, the errors of some parameters are rather high thus their absolute values should be treated with caution. The same holds for calculated concentrations of intermediates. The calculations suggest that mainly intermediates responsible for ethane and pentane formation are mostly present in the liquid phase, while others are transformed in a fast way to respective alkanes.


mol/ml

mol/ml mol/ml

mol/ml

mol/ml

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mol/ml

Page 21 of 40


mol/ml mol/ml

mol/ml

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mol/ml


Figure 10. Comparison between experimental and calculated data as a function of residence time τ.

Table 2. Estimated kinetic parameters, degree of explanation 99.4%

parameter ki1 ki2 ki3 ki4 ki5* ki6* b* c* d Kx

value 0.498 393 0.383 103 64.1 9.53 10-7 10 0.88 252 4.24 103

units min-1 min-1 min-1 min-1 min-1 min-1 dimensionles dimensionless dimensionless ml/mol

parameter k1 * k2 k3 * k4 k5 k6 k11 k12* k13

value units 50.1 min-1 1.00 10-7 min-1 3.80 10-3 min-1 32 min-1 0.067 min-1 500 min-1 4 1.36 10 min-1ml mol-1 14.9 min-1ml mol-1 4 1.50 10 min-1ml mol-1 5.13 103 min-1ml mol-1 k14 18.3 k15* min-1ml mol-1 *For these constants the relative errors are below 20%, for the rest of the constants the relative errors are above 50%


Page 22 of 40

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As follows from Table 2 the value of parameter b is somewhat lower than 11 while the value of lumped coefficient c is also marginally lower than unity. 3.4. Reactor simulations Simulation of reactor performance was done to explore the influence of various parameters on xylitol APR. Mass balances of fluid compounds and the particles were respectively written as:

∂Ci , F ∂t

= −u

∂Ci ,F ∂z

+ Dz

∂ 2Ci , F ∂z 2

− k s as (Ci , F − Ci ,S )

(14)

Mass balance for particles: − k s a s (C i , F − C i ,S ) = ∑ vi , j ri , j

(15)

The reactor was modelled as an axial dispersion unit using the Pe number as a single criterion for the extent of axial dispersion. The main assumption of the model is that the reaction occurs on the solid surface, where the reactant/intermediate/product concentrations are transferred from/to the fluid bulk phase through the stagnant fluid film surrounding the solid particle. In order to solve the system, a pseudo-steady state condition was introduced (eq. 15), stating the flux arriving from the bulk phase to the solid phase reacts thereafter and neglecting any kind of accumulation. In practice, the system is described by a set of Ordinary Differential Equation (ODE) referred to the bulk phase components (eq. 14) and a Non-linear Equation set (NLE), eq. 15. Mass transfer coefficient to the solid surface ks was calculated using the definition of the Sherwood number Sh P

ks = ShP Dmol/dP

(16)

where the molecular diffusion coefficient was calculated as [27]

D mol = 1.71134 *10-9 - 3.88472 *10-11 T + 1.21396 *10-13 * T

(17)

and the Sherwood number was related to the Reynolds ( Re P = ud P /v ) and Schmidt ( Sc = v/Dmol ) numbers 23 ACS Paragon Plus Environment


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1/3

Sh P = 5.4Re P Sc1/4

Page 24 of 40

(18)

The Couret correlation [28] was used to determine the Sherwood number value. It is valid for packed bed reactors operating in the range of Reynolds numbers 0.04

Kinetics, Modeling, and Process Design of Hydrogen Production by

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