TiO2 nanoparticles supported microchannel monolith photoreactor

Applied Catalysis A: General 467 (2013) 483–496

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Applied Catalysis A: General journal homepage: www.elsevier.com/locate/apcata

Photocatalytic CO2 reduction and kinetic study over In/TiO2 nanoparticles supported microchannel monolith photoreactor Muhammad Tahir 1 , NorAishah Saidina Amin ∗ Low Carbon Energy Group/Chemical Reaction Engineering Group (CREG), Faculty of Chemical Engineering, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor Baharu, Johor, Malaysia

a r t i c l e

i n f o

Article history: Received 9 March 2013 Received in revised form 25 July 2013 Accepted 27 July 2013 Available online 17 August 2013 Keywords: Photocatalysis Monolith photoreactor CO2 reduction In/TiO2 nanoparticles Kinetic model

a b s t r a c t In this study, a microchannel monolith photoreactor was investigated for photocatalytic CO2 reduction with H2 O in gaseous phase using TiO2 and indium doped TiO2 nanoparticles. Effects of operating parameters such as monolith geometry, reaction temperature, indium loading and feed ratios were investigated to maximize yield rates. CO and CH4 were the main products with maximum yield rates being 962 and 55.40 ␮mol g-catal.−1 h−1 , respectively and selectivity being 94.39 and 5.44%, respectively. The performance of the photoreactor for CO production was in the order of In/TiO2 -monolith (962 ␮mol g-catal.−1 h−1 ) > TiO2 -monolith (43 ␮mol g-catal.−1 h−1 ) > TiO2 -SS cell (5.2 ␮mol g-catal.−1 h−1 ). More importantly, the quantum efficiency in microchannel monolith reactor was much higher (0.10%) than that of the cell type reactor (0.0005%) and previously reported internally illuminated monolith reactor (0.012%). The significantly improved quantum efficiency indicated photon energy was efficiently utilized in the microchannel monolith reactor. A simple kinetic model based on Langmuir-Hinshelwood model, developed to incorporate coupled effect of adsorptive photocatalytic reduction and oxidation process, fitted-well with the experimental data. © 2013 Elsevier B.V. All rights reserved.

1. Introduction Global warming, primarily due to increasing level of carbon dioxide (CO2 ) emission from fossil fuels combustion, has aroused considerable concerns [1,2]. Therefore, technologies pertinent to carbon management, which not only mitigate global temperature, but also meet increasing energy demands, are high in the priority list [3]. Photocatalytic CO2 reduction with H2 O is of significance importance for production of hydrocarbon fuels and value added chemical such as CO, CH3 OH, CH4 , HCOOH and HCHO. It is highly potential for reducing CO2 emissions and partly for resolving energy crises [4,5]. However, lower photocatalytic CO2 reduction to hydrocarbon fuels has been reported during the last decades. Under such circumstances, efficient photocatalytic reactors that can eminently enhance CO2 conversion and yield rates are inevitable. Among various semiconductors available, the focus has been on the extensively researched titanium dioxide (TiO2 ) as a photocatalyst. Some of the encouraging advantages of TiO2 , making it a

∗ Corresponding author. Tel.: +60 7 553 5579; fax: +60 7 5588166. E-mail addresses: [email protected] (M. Tahir), [email protected], [email protected] (N.S. Amin). 1 Permanent address: Department of Chemical Engineering, COMSATS Institute of Information Technology Lahore, Punjab, Pakistan. 0926-860X/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.apcata.2013.07.056

perfect candidate for the photocatalytic processes, are reasonably cheap, good photoactivity, and widely available. It is also chemically/thermally stable, non-toxic, and possesses higher oxidative potential [6,7]. However, TiO2 is photoactive only under UV light irradiations due to its wide band gap (3.2 eV). It also exhibits lower CO2 conversion efficiency due to immediate recombination of photogenerated charges. In order to enhance photocatalytic efficiency of TiO2 , it is necessary to modify its surface to enhance recombination time of electron–hole pairs. The addition of metals and/or sensitizers to TiO2 could alter TiO2 band gap to effectively prevent recombination of photogenerated electron–hole pairs [8–10]. For the last few years, different types of metals and nonmetals together with lower band gap and/or mesoporous materials have been investigated to improve TiO2 photocatalytic activity under UV and/or visible light irradiations. The most widely researched materials include Ag/TiO2 [11], Pt/TiO2 [12] iodine/TiO2 [13], Cu/TiO2 [14], Rh/TiO2 [15], Cu-iodine/TiO2 [16], FeTiO3 /TiO2 [17], kaolinite/TiO2 [18], MMT/TiO2 [19], AgBr/TiO2 [20], TiMCM-41 and Ti-MCM-48 [21], nitrogen-iron/TiO2 CoPc/TiO2 [22], N-TiO2 nanotubes [23], CeO2 -TiO2 [24], CdSe/Pt/TiO2 [25], PbS/TiO2 [26], Cu-CdS-TiO2 /SiO2 [26,27], and CdS/Bi2 S3 /TiO2 nanotubes [3]. Furthermore, Poznyak et al. [28] investigated the photo-electrochemical properties of nanocrystalline In2 O3 /TiO2 composites. It was observed that In2 O3 in TiO2 endorsed efficient separation of photogenerated electron–hole pairs. In another study,

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it was observed that nitrogen doped In2 O3 thin film electrodes were efficient for H2 O splitting [29]. Recently, Kuo et al. [30] reported titanium–indium oxy (nitride) with RuO2 for H2 O splitting and observed higher H2 yield rate over the In2 O3 /TiO2 catalyst. Due to indium ability to produce large number of electrons and hinder their recombination, it is envisaged that indium is able to improve TiO2 photocatalytic activity for efficient CO2 conversion to value added chemicals and fuels. In addition to an efficient semiconductor photocatalyst, the design of photoreactor is also vital for improving product yield rates. In the period of 1980–2000, slurry reactors have been employed excessively for the photocatalytic CO2 reduction [31–33]. However, slurry type reactors have several limitations including inefficient light distribution throughout the system, catalyst attrition, and product separation challenges and fewer catalyst recycling possibilities. During the last 10 years, fixed-bed, catalyst supported and optical fiber reactors have been under investigation for photoreduction. The fixed-bed with its lower surface to volume ratio, inefficient light distribution and lower interaction between reactant and catalyst [34] seem not suitable for the photoreduction process. The optical fiber photoreactors, however, fall in the category of efficient photocatalytic reactors. These reactors have been explored for photocatalytic CO2 reduction since the exposed surface area to light ratio are larger, delivering light efficiently and uniformly throughout the reactor [35,36]. However, several disadvantages such as lower adhesion strength, relatively low surface area and only 20–30% of effective total reactor volume hindered the progress of the reactor toward commercialization [37,38]. Among photocatalytic reactors, the monoliths with large illuminated surface area to reactor volume ratio and efficient light utilization/distribution over the catalyst surface are considerably effective for photocatalytic CO2 reduction applications. Basically, monoliths composed of large number of channels with catalyts usually coated as thin layer along the walls to allow higher surface interaction with irradiation [39,40]. In addition, higher flow rates in the honeycomb monoliths give lower pressure drops, and its substrate can provide specific surface area 10–100 times more than other types of catalyst supports having the same outer dimensions [34,41,42]. Internally illuminated monolith photoreactor was tested by Liou et al. [37] for photocatalyitc CO2 reduction in which optical fibers were inserted inside the channels of the honeycomb substrate. Increased yield rates were observed using the monolith reactor with optical fibers. However, such experimental system needs higher aperture of channels to increase space for inserting the fibers. Consequently, using higher aperture of channels, light could not be distributed efficiently over the catalyst surface. The other disadvantages of larger aperture channels are decreased in mass transfer rates, non uniform gas distribution, and lower illuminated surface area per volume of reactor. However, recently it has been reported that, higher efficiency of CO2 reduction process is posssible using monolith of smaller aperture channels [43]. Smaller channels with higher surface area per unit volume are useful for efficient light distribution and increasing mass transfer rate on the catalyst surface. In addition, light distributions along the axial length of the monolith decreases gradually and higher CO2 mass transfer coefficient can be achieved using shorter monolith length [44]. The objective of this study is to test the performance of a microchannel monolith as photoreactor for the conversion of CO2 using H2 O as the reducing agent over In/TiO2 nanoparticles. The catalyst samples were characterized using XRD, FE-SEM, TEM, BET, and UV–vis spectroscopy. The monolith geometric and operating parameters effects were investigated to maximize yield rates. Kinetic model based on Langmuir-Hinshelwood equation was

developed to determine the kinetic parameters and to provide fundamental insights on possible reaction mechanisms. 2. Experimental 2.1. Catalyst preparation and coating procedure Fig. 1 describes the procedure of catalyst synthesis and coating on monolith channels. The sol–gel single step method was used to prepare mesoporous TiO2 and In/TiO2 nanoparticles. The precursory of titanium solution was prepared with molar ratios: Ti (C4 H9 O)4 :15C2 H5 OH:2CH3 COOH (1 M). Typically, 30 ml of isopropanol was added into 10 ml of titanium tetra iso-propoxide and stirred well for 30 min. The controlled hydrolysis was conducted by adding drop wise a mixture of 6.37 ml acetic acid (1 M) and 10 ml isopropanol under vigorous stirring. The mixture was continuously stirred for 24 h at 30 ◦ C. Subsequently, indium(III) nitrate dissolved in isopropanol was added drop-wise and stirred for another 12 h until clear sol was produced. The sol obtained was poured into a glass container for monolith coating. The monolith was initially washed with acetone and isopropanol to remove any organic material, and then dried at 80 ◦ C for 12 h. The SHIMADZU analytical balance ATY-224 with specifications: Max = 220 g, Min = 10 mg, d = 0.1 mg, e = 1 mg was used to measure the weight of the monoliths. For every sample, three readings were noted for bare monolith as well as coated monoliths and their average values are reported. For example, the weight of the 2 cm 100 CPSI bare monolith was 46.8219 g, aggregated from three different readings, i.e. (a) 46.8214 g, (b) 46.8225 g, and (c) 46.5218 g. After the weight of the dried monolith was recorded, it was immersed slowly into the indium loaded TiO2 sol and kept for a few minutes. The excess sol from the channels was blown off using compressed air and dried with an air drier. To increase the film thickness and catalyst loading, the monolith was dipped for the second time using the same procedure. The coated monolith was then put into the oven, dried at 80 ◦ C for 12 h and finally calcined in a muffle furnace at a rate of 5 ◦ C min−1 up to a maximum of 500 ◦ C and held for 5 h. After calcination, the average weight of the coated monolith was 47.3532 g calculated from three readings (a) 47.3539 g, (b) 47.3531 g, and (c) 47.3526 g. Therefore, the catalyst coated over monolith channels was 0.5313 g calculated by subtracting coated monolith weight (47.3532 g) from un-coated monolith weight (46.8219 g). In/TiO2 sol was dried and calcined with the same procedure as explained above to obtain In/TiO2 powder. For comparison, bare TiO2 nanoparticles were also similarly prepared and coated inside the microchannels of the monolith. 2.2. Characterization of nanocatalysts In order to determine the structure and crystallinity of the photocatalysts, powder X-ray diffraction (XRD) was performed on Bruker D8 advance diffractometer (Cu K␣ radiation, wavelength ˚ operated at 40 kV and 40 mA). The surface morphology  = 1.54 A, was examined using scanning electron microscopy (SEM) with JEOL JSM6390 LV SEM instrument. The particle size and lattice structure of the individual crystals was visualized by high resolution transmission electron microscope (HR-TEM) carried out with FEI-Tecni G2 Transmission Electron Microscope (TEM) at EFGO Scientific, Kulim, Kedah, Malaysia. Textural characterization of the samples was carried out with a Micromeritics ASAP 2020. The nitrogen adsorption–desorption properties were examined at 77 K. The specific surface area (SBET ) of monolayer coverage was determined using Brunauer–Emmett–Teller (BET) method. The pore size distribution was calculated using the adsorption branch of the isotherm by means of Barrett–Joyner–Halenda (BJH) method. Meanwhile,

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Fig. 1. Preparation of In/TiO2 nanoparticles and In/TiO2 coated over monolith.

the UV–vis absorption spectra of the samples were measured with UV-Vis-NIR spectrophotometer, Shimadzu UV 3101pc. 2.3. Photocatalytic CO2 reduction The schematic photocatalytic reaction system for reduction of CO2 with H2 O in gaseous phase is illustrated in Fig. 2. The reactor consisted of a stainless steel cylindrical vessel with 5.5 cm length and a total volume of 150 cm3 . The monoliths were supplied by Pingxiang Meitao Chemical Packing Co., Ltd., China. The dimensions of the monolith are as follows: diameter = 6 cm; length = from 0.50 to 10 cm, channels per square inch (CPSI) = 100 and 400. After coating with about 50 mg catalyst the monolith was placed at the center of the cylindrical stainless steel reactor, equipped with a quartz window for passing light irradiations from the reflector lamp located above the reactor. The reactor temperature was adjusted using heating and cooling jackets. The light source used to activate the photocatalytic reactions was a 200 W mercury lamp for UV irradiations source, having non-collimated irradiations with maximum intensity at 252 nm. The lamp was equipped with a cooling

fan at the top and sides to remove lamp heat. The light intensity was measured with an online optical process monitor ILT OPM-1D and a SED008/W sensor. The average irradiation intensity passing through the top of the reactor was 150 mW/cm2 . The reactor was covered with aluminum foil to ensure lights for reactions came through the quartz window only. In case of the cell type photoreactor, the reactor chamber and the light source was the same with the monolith reactor. Furthermore, 50 mg of nanocatalyst powder was suspended uniformly at the bottom of the reactor to ensure the light was efficiently distributed over the catalyst surface. Prior to feeding, both reactors were purged using helium (He) flow to remove air as well as to check for leakage under 2 bar pressure for 10 h. Pure CO2 (purity = 99.995%) was bubbled through deionized water saturator for 1 h to remove dissolved oxygen and air. The temperature inside the water bubbler was controlled using a temperature controller. The compressed CO2 regulated by a mass flow controller (MFC), was bubbled through the deionized water and its concentration was adjusted with helium regulated by the MFC. The partial pressure of H2 O vapors was adjusted by changing the temperature of the water saturator. The gases, CO2 , He and H2 O

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Fig. 2. Schematic of experimental set-up using monolith photoreactor for photocatalytic CO2 reduction with H2 O vapors.

mixed well inside the gas mixer, continuously passed through the reactor containing powdered catalyst or coated monolith for about 1 h prior to switching on the lamp. The pressure inside the reactor was adjusted to 0.20 bars above atmospheric pressure while temperature inside the reactor was controlled using a heating jacket. The products were analyzed using an on-line gas chromatograph (GC-Agilent Technologies 6890N, USA) equipped with thermal conductivity detector (TCD) and flame ionized detector (FID). The gaseous products from the reactor were also taken using gastight syringe (Agilent, 1000 ␮l) for offline analysis using the same volume as in the online analysis. Furthermore, the FID detector was connected with a HP-PLOT Q capillary column (Agilent, length 30 m. ID 0.53 mm, film 40 ␮m) for separation of C1 –C6 paraffins and olefins hydrocarbons, alcohols and oxygenated compounds. The TCD detector was connected to UCW982, DC-200, Porapak Q and Mol Sieve 13X columns. The UCW-982 was used for back flush and reversed flow to ensure C6 and higher compounds could be detected earlier in the chromatogram. Meanwhile, C1 –C2 , C3 –C5 compounds and light gasses (H2 , O2 , N2 , CO) were separated using Porapak Q, DC-200, and MS-13X columns, respectively.

associated with tetragonal anatase. The average crystallite sizes of TiO2 and In/TiO2 nanoparticles were calculated using Scherer’s equation (Eq. (1)) according to the (1 0 1) peak [45,46]. L=

k ˛ cos 

where L is the thickness of crystallite (nm), k is a constant depending on the crystallite shape (0.90 for this study),  is the X-ray wavelength (nm), ˛ is full peak width at half max in radians and  is Bragg’s angle of the 2 peak. The calculated crystallite sizes of TiO2 , 10% In/TiO2 and 20% In/TiO2 samples were 18.73, 13.8 and 11.32 nm, respectively. It was observed that the size of the TiO2 nanoparticles decreased gradually, possibly due to indium controlling the crystal growth in TiO2 . The SEM micrographs of monoliths are depicted in Fig. 4. The pore morphology of the bare and coated monolith is shown in Fig. 4(a) and (b), respectively. It is obvious that catalyst was entirely coated over the monolith channels with no broken layer observed. Fig. 4(c) indicates smooth and thoroughly distributed uniform

3. Results and discussion 3.1. Characterization of monolith and catalysts The X-ray diffraction (XRD) patterns of bare TiO2 and In/TiO2 coated monolith samples are shown in Fig. 3. All the TiO2 peaks corresponded to pure crystalline and anatase phases calcined at 500 ◦ C for 5 h. The XRD data do not infer any presence of indium. However, the anatase peaks become wider while the intensities also increase with indium loadings, with no shifts in the anatase peaks observed. The wider anatase In/TiO2 peaks indicate the crystallite size of TiO2 decreases with indium loading. In order to confirm bulk compositions of each sample, the XRD peaks are compared with the JCPDS-ICSD standards for anatase (89-4921). The diffraction peaks for TiO2 and In/TiO2 are essentially equivalent, exhibiting 2 peaks at 25.54◦ , 38.02◦ , 48.26◦ , 55.29◦ , and 62.90◦ , which are consistent with the (1 0 1), (0 0 4), (2 0 0), (1 0 5), (2 1 1) and (2 0 4) planes

(1)

Fig. 3. XRD patterns of anatase TiO2 nanoparticles and In/TiO2 catalysts.

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Fig. 4. SEM micrographs of bare monolith and In/TiO2 coated monolith at different magnifications; (a) bare monolith channels, (b) catalyst coated monolith channels, (c) top view image at magnification 1000 and scale 10 ␮m, and (d) mesroprous structure of coated catalyst at magnification 15,000 and scale 1 ␮m.

catalyst layer investigated at 10 ␮m of SEM magnification over the monolith surface. At magnification of 1 ␮m, it is identified that the catalyst nanoparticles are uniformly distributed on the monolith surface, as shown in Fig. 4(d). It is also observed that the indium-loaded TiO2 mesoporous particles are uniform in size. The TEM micrographs of mesoporous In/TiO2 catalyst are shown in Fig. 5. From Fig. 5(a), TEM image revealed mesoporous anatase TiO2 nanoparticles consisted of average particle size with diameter less than 13 nm. The particle size is close to the estimated crystallite size by Scherrer equation. It can be observed that the nanoparticles have interparticle mesoporous structure. The growth and aggregation of the small particles probably caused interparticle mesoporosity. The HR-TEM image in Fig. 5(b) confirms the morphology of TiO2 nanoparticles where 0.35 nm aligned anatase phase grown along 1 0 1 directions is observed, as already confirmed with XRD. These results are in good agreement with previous reports [4,47]. Fig. 6 exhibits the N2 adsorption and desorption isotherms and Barrett–Joyner–Halenda (BJH) pore-size distribution of TiO2 and In/TiO2 samples. It is obvious from Fig. 6(a) that the hysteresis loops increase with increasing indium loading, resulting obvious increase in the N2 volume adsorbed. The isotherms of the samples are similar to type IV curves with hysteresis loops, corresponding to mesoporous materials [19]. Furthermore, the initial part of the isotherms (at low P/Po ) is related to monolayer–multilayer adsorption on the internal surface. However, at higher P/Po , there was a steep increment in the adsorption volume, attributed to capillary condensation, then pores saturated with liquid. The monolayer–multilayer is more dominant in TiO2 in which capillary action starts at P/Po = 0.60. Both capillary and condensation processes are more obvious in In/TiO2 samples and eminent at P/Po of 0.55.

The pore size distribution of the samples is presented in Fig. 6(b). The pore size distribution, calculated from adsorption branch, is based on the BJH model. The BJH adsorption isotherms show that the interparticle pore size diameter falls in the range of 2.5–25 and 2.4–14 nm for TiO2 and In/TiO2 samples, respectively. The BET surface area, pore volume and pore size of bare TiO2 and In/TiO2 samples are summarized in Table 1. Obviously, the indium loading into TiO2 influences the surface area, pore volume and pore size. The BET surface areas for indium doped TiO2 samples are larger than bare TiO2 . Besides this, the t-plot external and BJH adsorption surface areas also increased significantly. The increase in surface area was probably due to suppression of TiO2 crystal growth by indium and also due to increase in mesoporosity. Furthermore, the BJH adsorption pore volume also increased with indium loading. Conversely, the pore diameter gradually decreased with indium loading. The increase in the pore volume with reduced pore diameter is attributed to higher sample mesoporosity. The well-developed mesopores, larger surface area and higher pore volume could enhance molecular transportation rates of reactants and products to increase CO2 conversion efficiency.

3.2. UV–vis analysis The UV–vis absorbance spectra of the TiO2 nanoparticles and In/TiO2 samples are depicted in Fig. 7. The absorption band edge of TiO2 is located at 400 nm, which indicates obvious red shift in wavelength of TiO2 compared to standard anatase TiO2 ( ∼ 380 nm). The peaks identified for 5, 10, 15 and 20 wt.% In/TiO2 are located at 401, 402, 403 and 404 nm respectively. It can be seen that indium has no significant effect on shifting TiO2 band

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Fig. 5. TEM and HR-TEM images of In/TiO2 sample.

Fig. 6. (a) N2 adsorption–desorption isotherms of TiO2 nanoparticles and In/TiO2 samples and (b) BJH pore size distribution of corresponding samples.

edge. The band gap of the samples was calculated according to Eq. (2). Eg =

hc 

20 wt.% indium doped TiO2 samples, respectively. It is identified that loading indium into TiO2 decreased the band gap but not red shift was observed as compared to TiO2 nanoparticles.

(2) 3.3. Photocatalytic reduction of CO2 with H2 O

where Eg is the band gap energy (eV), h is the Planks constant, c is the light velocity, and  the wavelength (m). The Ebg estimated were 3.105, 3.098, 3.090, 3.082 and 3.075 for TiO2 and 5, 10, 15 and

Initially, a series of preliminary tests were conducted in the absence of CO2 and H2 O under UV irradiations for 2 h at 373 K for

Table 1 Summary of physiochemical characteristics of TiO2 and In/TiO2 samples. Type of catalyst

TiO2 5% In–TiO2 10% In–TiO2 20% In-–TiO2

Surface area (m2 /g)

Pore volume (cm3 /g)

Pore width (nm)

BET surface area

t-Plot external surface area

BJH adsorption surface area

BJH adsorption pore volume

BJH pore width

42.98 61.40 98.01 123.04

34.05 60.66 95.16 123.32

52.19 68.10 113.04 170.20

0.14 0.16 0.22 0.31

10.33 8.34 7.67 7.38

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Fig. 7. UV–vis absorption spectra of TiO2 and In/TiO2 samples.

the following cases; (1) empty reactor with helium, (2) reactor with monolith without coating and helium, (3) reactor with TiO2 coated monolith and helium and (4) monolith coated with In/TiO2 catalyst with helium. In all cases, no reaction products were detected. This confirmed that no products were due to photodecomposition of organic residues in catalyst, if any. In addition, other preliminary tests were also conducted using H2 O vapors and helium in presence of photocatalyst. The results again confirmed in either case no carbon containing compounds were produced. Therefore, it can be reiterated that photocatalytic reduction process require all three components, i.e. catalyst coated monolith and/or catalyst, feed (CO2 , H2 O), and light source. Meanwhile any carbon containing compounds should be produced from CO2 through photocatalytic reactions. Furthermore, all the experiments were repeated three to five times and aggregated results have been reported. The effect of cell density on photocatalytic CO2 reduction over different irradiation time is illustrated in Fig. 8(a). Higher CH4 yield rate observed over TiO2 using monolith with cell density of 100

489

compared to 400 CPSI. The higher yield rate was probably due to efficient harvesting and utilization of light irradiations inside 100 CPSI channels compared to very dense channels (400 CPSI) [43]. Conversely, further increase in yield rates possibility exist over 150 and/or 200 CPSI channels, as smaller apertures support more illuminated surface area to volume ratio of reactor granting further investigation for optimum channel aperture. Fig. 8(b) shows the effect of monolith channel lengths on photocatalytic CO2 reduction over TiO2 photocatalyst at different irradiation times. It was found that CO2 reduction with H2 O vapors to CH4 improved using longer monolith. As the channel length increased beyond 2 cm, a gradual reduction in CH4 yield was observed. Although the same amount of irradiation penetrated inside the channels yet only small portion of light probably passes through longer channels because of non-collimated light source. Besides, there is higher catalyst loading and lower CO2 mass transfer on the catalyst surface at prolonged monolith length, resulting in lower yield rate [44]. Furthermore, only the front part of the monolith was efficiently irradiated and after a certain length there was probably inefficient light being distributed over the catalyst required for photocatalysis. Therefore, the monolith geometry is vital and optimum monolith dimensions are critical to enhance CO2 reduction efficiency. Based on such observations, it is obvious that photon flux distribution inside reactor is very important, since it directly influences reactor performance [48]. Fig. 9 illustrates the effect of reaction temperature on photocatalytic CO2 reduction at three different temperatures (70, 80 and 100 ◦ C) using 10 wt.% In/TiO2 catalyst. In all the three temperatures investigated, the reaction rate exhibits similar behavior, which is slow initially for CO production, but becomes considerably faster after 2 h of irradiations. The other products observed were CH4 and traces of C2 –C3 alkanes and alkenes (figure not shown). The increased in yield rates at elevated temperature can be explained on the basis of adsorption–desorption phenomenon. In heterogeneous photocatalysis process, especially in gaseous phase, simultaneous adsorption and desorption processes occurred over the catalyst surface. The rate of reaction depends on the efficiency

Fig. 8. Effects of channel length on performance of monolith photoreactor for photocatalytic CO2 reduction with H2 O vapors.over TiO2 catalyst (T = 373 K, PH2 O = 0.074 bar and PCO2 = 0.020 bar).

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Fig. 9. Effect of reaction temperature on yield rate of CO (L = 2 cm, CPSI = 100, 10% In–TiO2 , CO2 = 0.02 bar, PH2 O = 0.074 bar).

of these processes. Therefore, at elevated temperature, the CO2 mass transfer rate on the catalyst surface can be increased, thus the probability of CO2 adsorption increases which can result in higher reaction rate [41]. Furthermore, at higher reaction temperature, the possibility of species desorption at the catalyst surface increased. In this way, the chances of efficient collisions between the charge transfer excited state species and reactant molecules also increased [10]. Besides this, the increase in reaction rate at higher temperature may be possibly due to a decrease in activation energy during the course of reaction. Similar observations have been reported in other studies during the investigations of the effect of temperature on the reduction of CO2 with H2 O in gaseous phase [19,49]. Fig. 10 illustrates the effect of indium loading on TiO2 photocatalytic activity for transformation of CO2 with H2 O to CO and CH4 . By using un-doped TiO2 nanoparticles, small amount of CO was produced, while CO yield increased significantly by the dispersion of indium into the TiO2 structure. The higher yield rate is an evidence that photocatalytic activity of TiO2 can be enhanced by increasing indium content to an optimum loading of 10 wt.%. Beyond the 10 wt.% loading, the CO2 reduction rate slowed down probably due to increase in recombination rate of charges. The

Fig. 10. Effect of indium loading into TiO2 for photocatalytic CO2 reduction over monolith keeping all the parameters fixed (L = 2 cm, CPSI = 100, T = 373 K, PH2 O = 0.074 bar, PCO2 = 0.02 bar).

difference in the photocatalytic activity of bare TiO2 with doped TiO2 may be attributed to reduced crystal size and increased surface area, resulting in efficient charge production and separations over the mesoporous In/TiO2 samples. Similar observations are reported in literature using doped TiO2 catalysts [13,35,50]. The effects of partial pressure of CO2 and irradiation time for photocatalytic CO2 reduction over 10 wt.% indium doped TiO2 supported microchannel monolith are investigated for a period of 0–10 h as depicted in Fig. 11. There is continuous production of CO and CH4 over the entire irradiation period. CO was identified as the major product and its higher yield over In/TiO2 catalyst confirmed higher CO2 reduction efficiency using this process. Initially CO yield was very low, but gradually increased over the time. The lower yield rate at the start of reaction was supposedly due to higher CO2 adsorption and lower CO desorption. The yield of CH4 increased continuously with irradiation time; due to surface reaction and efficient desorption of hydrocarbon based products. Trace distribution of C2 H4 , C2 H6 , and C3 H6 with time was also observed in the product mixture. However, yield of CH4 was lower than CO and this was probably attributed to the conductance band (CB) of the thermodynamic reduction potential. Furthermore, the concentrations of CO and CH4 increased with increasing CO2 partial pressure at fixed water vapor pressure (0.074 bar) (Fig. 11). This phenomenon is likely due to adsorption competition between CO2 and H2 O molecules on the active sites of In/TiO2 catalyst during photoreduction process. At lower CO2 concentration, large amount of H2 O molecules could adsorb over the catalyst surface to react with CO2 resulting in higher CO2 photoreduction. However, at higher CO2 concentration, it covers supposedly maximum active sites and H2 O would have to compete with CO2 for the active sites resulting in lower reaction rate. Therefore, an optimum concentration of both reactants would be favorable for higher CO2 conversion. Similar findings have been reported in literature during photocatalytic CO2 with H2 O vapors using various TiO2 based photocatalysts [19,51]. The photocatalytic performance of In/TiO2 supported over microchannels with respect to the product yield is in the following order (␮mol g-catal.−1 ): CO > CH4 > C2 H6 > C2 H4 > C3 H6 . The higher yield of CO and hydrocarbons was likely due to significant increase in the number of electron–hole pairs and inhibited recombination times over In/TiO2 supported microchannels. Fig. 12 compares photocatalytic CO2 reduction with H2 O vapors using stainless steel (SS) cell and monolith photoreactor. Interestingly, the yield rate of CO obtained was much higher over In/TiO2 supported microchannels and this reveals indium enhances rate of reaction for CO production. Under the same experimental conditions, the CO yield rate over indium modified TiO2 was 962 ␮mol g-catal.−1 h−1 22.4-fold higher compared to TiO2 supported monolith photoreactor and 185-fold higher compared to SS cell reactor. Overall, the presence of monolith enhanced the photoactivity of TiO2 . These results confirmed indium is efficient to inhibit recombination of electrons–hole pairs. Furthermore, in TiO2 coated monolith, the CO yield was 8.3 times higher than cell type reactor. This was also probably due to increased light irradiation utilization and better contact efficiency between reactants and catalyst coated monolith due to the microchannels. Basically, honeycomb configuration of monolith provides a higher geometrical surface area to support catalyst over microchannels and to increase mass transfer; thus, higher reactor volume could be used for photocatalytic reactions. It is also inferred that electrons produced were immediately utilized over thin film coated microchannel, thus reducing the rate of electron–hole pair recombination as similarly observed previously [52]. The product compositions of photoreactors are usually quantified based on quantum efficiency. Table 2 highlights the operating parameters used in both type of reactors to calculate quantum

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491

Fig. 11. Photocatalytic CO2 reduction with H2 O over 10% In/TiO2 catalyst at different irradiations time and CO2 partial pressures (L = 2 cm, CPSI = 100, In = 10 wt.%, T = 373 K, and PH2 O = 0.074 bar).

efficiency, calculated for each experiment, as the ratio of product rate (mol per s) with photonic flux (mol per s) [38]. The quantum efficiency of the microchannel monolith photoreactor coated with In/TiO2 for CO production was 0.10%, 24 times higher than that of TiO2 coated monolith and 198 times higher than catalyst suspended cell type photoreactor. Liou et al. [37] reported quantum efficiency of internally illuminated monolith photoreactor for methanol production during CO2 reduction with H2 O vapors which was 0.012%, 8.33 times lower than the value reported above for CO production. Significantly higher quantum efficiency was observed using

microchannel monolith photoreactor, which may be attributed to higher photons absorption inside the microchannels due to larger illuminated active surface area. The significant improvement in the performance of the monolith is due to more catalyst being exposed to incoming irradiation flux. In this way, a much larger fraction of the reactor volume was effectively used to convert CO2 to products, thus resulting in higher quantum efficiency. The lower efficiency in TiO2 is related to higher probability of electron–holes recombination over TiO2 where large number of photons remained unproductive.

Fig. 12. Comparison of photocatalytic CO2 reduction with H2 O using cell type and monolith photoreactor (V = 150 cm3 , T = 373 K, PH2 O = 0.074 bar, PCO2 = 0.04 bar).

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Table 2 Summary of operating parameters used for cell type and microchannel monolith photoreactor and calculated quantum efficiencies. System

Cell type photoreactor

Volume Catalyst loading Light source Temperature Pressure Main product Yield rateb (␮mol g-catal.−1 h−1 ) Quantum efficiency for COc Quantum efficiency for CH4 c a b c

3

150 cm 0.5000 g TiO2 200 W Hg,  = 252 nm, I = 150 mW/cm2 373 K 0.20 bar CO/CH4 5.2/7.7 0.0005% 0.0028%

Monolitha photoreactor coated with TiO2 3

Monolitha photoreactor coated with In/TiO2 150 cm3 0.5520 g 10% In/TiO2 200 W Hg,  = 252 nm, I = 150 mW/cm2 373 K 0.20 bar CO/CH4 962.0/55.40 0.10% 0.022%

150 cm 0.5341 g TiO2 200 W Hg,  = 252 nm, I = 150 mW/cm2 373 K 0.20 bar CO/CH4 43.0/78.0 0.0042% 0.0301%

The dimensions of monolith were length = 2 cm, CPSI = 100, diameter = 6 cm. Yield rates were calculated at 10 h irradiation basis, PH2 O = 0.074 bar and PCO2 = 0.040 bar. Quantum efficiency = (number of electrons × moles of production rate)/(moles of UV photons flux) × 100%.

Table 3 summarizes the yields over various catalysts used in cell type and monolith photoreactor with 10 h irradiation time. The presence of mesoporous In/TiO2 and microchannel monolith played important roles and CO2 reduction was obviously increased. The performance of the photoreactor for CO production was in the order of In/TiO2 -monolith (962 ␮mol gcatal.−1 h−1 ) > TiO2 -monolith (43 ␮mol g-catal.−1 h−1 ) > TiO2 -SS −1 −1 cell (5.2 ␮mol g-catal. h ). Similarly, the yield rates of CH4 produced were 55.4, 78.0 and 7.7 ␮mol g-catal.−1 h−1 , for In/TiO2 monolith, TiO2 -monolith and TiO2 cell type, respectively. In addition, less concentrations of C2 H4 , C2 H6 , and C3 H6 were also produced over TiO2 and In/TiO2 coated monoliths. Based on these results, it is obvious that mesoporous In/TiO2 catalyst with higher surface area and lower particle size is more favorable for efficient reduction of CO2 to CO. In general, higher efficiency of the catalysts and reactors may be attributed to the followings:

• CO− 2

radicals. On the other hand, holes (h+ ) were transferred to H2 O initiating its photooxidation yielding hydrogen ions (H+ ) and hydroxyal radical (• OH) and further oxidized with • OH radicals for the production of O2 and H+ [53]. The • H radicals originated during reduction of proton were reacted with carbon radicals on the catalyst surface to produce intermediate • CH2 , • CH3 and finally CH4 and higher hydrocarbons (C2 H4 , C2 H6 and C3 H6 ). All possible reaction steps during photocatalytic CO2 reduction with H2 O are explained by Eqs. (3)–(11). E

≥E

TiO2 ph (TiO2 ) + h+ −→bg e− vb (TiO2 ) cb

(3)

In + e− → In − e− cb cb

(4) e− ,H2 O

H2 O + h+ → • OH + H+ −→ • H + O2

(5)

•H

− CO2 + e− → • CO− 2 −→CO + OH

(6)

•H

(1) Larger illuminated surface area, higher light utilization, efficient adsorption–desorption process and higher catalyst interparticle mesoporosity are probably the important factors to improve the yield rates in monolith photoreactor. Conversely, in cell type photoreactor, there is lower light utilization and mass transfer rates. (2) Indium in TiO2 controls the crystal growth, increases the mesoporosity and the surface area, and reduced the particle size. Indium doped TiO2 catalysts with smaller particle sizes coated over microchannels have higher photocatalytic activity because electrons are more mobile over the photocatalysts. Furthermore, indium trapped electrons and hindered recombination of electrons–hole pairs during TiO2 photocatalysis, and possibly enhanced TiO2 photocatalytic activity. 3.4. Mechanism of photocatalytic CO2 reduction During photocatalytic CO2 reduction with water vapors the first step was the production of electrion–holes pairs when light striked on the TiO2 surface. The electrons (e− ) were transferred from the conduction band of TiO2 for the photoreduction of CO2 yielding

CO + e− → • CO− −→• C + OH− •C + •H

•H

•H

(7) •H

→ • CH−→• CH2 −→• CH3 −→CH4

(8)

• CH

2

+ • CH2 → C2 H4

(9)

• CH

3

+ • CH3 → C2 H6

(10)

• CH

2

+ • CH3 + • CH → C3 H6

(11)

Since all the above products were detected experimentally, therefore, CH4 was confirmed to be produced from methyl radicals (• CH3 ) through Eq. (8). Similarly, CO was probably produced according to Eq. (6). The higher yield rate of CO production also confirmed that there were significant productions of electrons which were efficiently trapped by indium and then transferred to CO2 for its reduction to CO. However, there are many possible routes for the production of C2 –C3 hydrocarbons and most possible routes are explained in Eqs. (9)–(11). According to above reaction mechanism, all the possible products are dependent on the production of intermediate product, CO and its further reduction to C1 –C3 hydrocarbons through Eqs. (7)–(11). The possibility for production of C2 –C3 compounds enhanced if there are series of reaction taking place over catalyst surface. Similar observations have been reported

Table 3 Summary of products from photocatalytic CO2 reduction with H2 O for different type of reactors and catalysts. Products

CO CH4 C2 H4 C2 H6 C3 H6

Yield rates (␮mol g-catal.−1 h−1 )a

Selectivity (%)

TiO2 -cell

TiO2 -monolith

In/TiO2 -monolith

TiO2 -monolith

In/TiO2 -monolith

5.2 7.7 0.79 0.00 0.00

43.0 78.0 1.50 0.79 0.00

962.0 55.40 0.34 1.50 0.068

34.87 63.27 1.22 0.64 0.00

94.39 5.44 0.034 0.147 0.00

Operating conditions: PCO2 = 0.040 bar, PH2 O = 0.074 bar, T = 373 K. a Yield rates calculated on 10 h irradiation basis.

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493

Fig. 13. (a) Schematic reaction scheme for photocatalytic CO2 reduction and H2 O oxidation to hydrocarbons using CO as intermediate over In/TiO2 and (b) thermodynamic reduction based mechanism of CO2 reduction with H2 O vapors to CO and CH4 over In/TiO2 catalyst.

in other studies using TiO2 based photocatalysts [19,49]. The reaction scheme for the production of CO, CH4 and higher hydrocarbons using In-loaded TiO2 is elaborated further in Fig. 13(a). The photocatalytic CO2 transformation to CO and CH4 as main products over In/TiO2 catalyst could be further explained using energy band theory, which is based on the relative positions of conductance band, valance band and oxidation potentials. In general, photo-excited electrons could consume effectively, if the reduction potential of reaction is lower than the conductance band potential of the semiconductor [54]. The mechanims for photocatalytic CO2 reduction in terms of thermodynamic reduction potentials versus normal hydrogen electrode (NHE) at pH 7 is explained in Fig. 13(b) [17]. The possible reactions that can occur during photocatalytic CO2 with H2 O to produce CO and CH4 in terms of thermodynamic reduction potentials versus normal hydrogen electrode (NHE) at pH 7 can be described by reactions (12)–(15) [11,55,56]. CO2 + 2H+ + 2e− → CO + H2 O 2H+ + 2e− → H2 +

E o = −0.48 V

E o = −0.41 V

−

CO2 + 8H + 8e → CH4 + 2H2 O 2H2 O + 4h+ → 4H+ + O2

(12) (13)

o

E = −0.24 V

E o = +0.82 V

(14) (15)

The conductance band potential of TiO2 is ECB = −0.50 V at pH 7, which is higher than reduction potential of Eo (CO2 /CO) = −0.48 V, thus reduction of CO2 to CO is possible. On the other hand, production of CH4 was also posisble because of lower reduction potential difference (Eo (CO2 /CH4 ) = −0.24 V). However, higher production rate of CO is possible since two electrons are required for CO production compared to eight electrons to produce CH4 . Besides, there was possible higher production of electrons than holes due to indium loading which enhanced CO production. On the other

hand, traces amount C2 to C3 were possible due to a series of reaction that occured ove rthe catalyst surface. Using bare TiO2 , CH4 was found as the major product which revealed TiO2 coated over microchannel is more feasible for CH4 production than CO. Thus, the CO production over In/TiO2 was probably due to a more negative conductance band and possibility of CH4 reduction to CO. However, further investigations are needed to find out the exact reaction mechanism of CO and hydrocarbons production. In other studies, CO was also observed as the main product during CO2 reduction with H2 O vapors using TiO2 and the modified TiO2 catalysts [13,14]. 3.5. Development of kinetic model In heterogeneous photocatalytic processes, rates are usually proportional to adsorption of reactants with efficient desorption of products on the catalyst surface. When the two reactants competitively adsorbed on the same catalyst surface active sites, but with different adsorption and desorption rate constants, and undergoes a reaction to yield different products, the reaction could be represented by Langmuir-Hinshelwood mechanism, as explained by Eq. (16) [44]. Rate = kA B = k

KA PA KB PB (1 + KA PA + KB PB )2

(16)

where  A and  B represent the fractional surface coverage of each reactant while PA and PB are the partial pressures of each species. The rate constant k and adsorption equilibrium constant parameters KA and KB are all temperature dependent. If the adsorption is random, the probability of adsorption would be taken as the fraction of the surface not covered (1 − ) and desorption taken as the surface covered . By employing these assumptions, the kinetic model for photocatalytic CO2 reduction with H2 O could be

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developed. The results from previous section could enable kinetic model development for photocatalytic reduction of CO2 and H2 O. In general, the CO2 with H2 O was photocatalytically reduced to CH4 and CO as the main products through the following reaction scheme as illustrated in Eq. (17). hv, In2 O3 /TiO2

3CO2 + 2H2 O

−→

CH4 + 2CO + 3O2

(17)

Some of the products would photo-adsorb on the catalyst surface, blocked the active sites and slowed down the CO2 reduction process. There is also possibility some of these products recombined in a reversed reaction. For example, when CO and oxygen produced were not effectively desorbed from the catalyst surface, these products would undergo photo-oxidation back to CO2 in the reversed reaction. The kinetic model is developed using these assumptions to investigate the coupled effect of adsorptive photocatalytic reduction and oxidation processes. By assuming reactants and products are adsorbed on same active sites, rate of reaction can be explained by using Langmuir-Hinshelwood mechanism as described in Eq. (18). Rate of reduction = kI a

(1 + KH2 O PH2 O + KCO2 PCO2 + KCO PCO + KO2 PO2 + KCH4 PCH4 )

where ‘k’ is the rate constant, I is UV light flux intensity for which kinetic constants is evaluated, ‘a’ is the reaction order of light intensity, having value 1 or less depending on the light intensity [57]. KH2 O , KCO2 , KCO , KO2 , and KCH4 are the ratios of adsorption to desorption equilibrium rate constants for H2 O, CO2 , CO, O2 and CH4 , respectively. During photocatalytic CO2 reduction over the catalyst surface the rate equation can be determined with the assumptions: (a) reaction rate is proportional to the fraction of surface covered by CO2 ; (b) H2 O, CH4 and O2 are weakly adsorbed over the catalyst; (c) while CO2 and CO are moderately adsorbed, then the rate equation becomes Eq. (19) [44]. (1 + KCO2 PCO2 + KCO PCO )2

dP = dt

Rate of reduction = k1

(KCO PCO )

(20)

where k1 = (kred Ia ) is the photoreduction rate constant affected by temperature and light intensity. The rate of formation of the products is dependent on CO conversion and/or desorption over the catalyst surface. During photocatalytic CO2 reduction, when CO entirely covers the catalyst surface, it also undergoes partial oxidation with oxygen. The Langmuir-Hinshelwood model could also be used to evaluate rate of photo-oxidation. When CO oxidation reaction with oxygen undergoes dissociative adsorption process,

(KCO PCO )

 − k2

KO2



PO2

(22)

KCO PCO

k   k  3 4 −

P





P

where



k3 = k1

(23)

P 1/2

dP

k3 − k4 P 1/2

(24)

KH2 O PH2 O KCO2 PCO2



 k 4 = k2

,

KCO

KO2

KCO

The differential equation (Eq. (24)) was solved using integral approach as shown in Eq. (25). t=−

2k33 3k44

2k32 P 1/2 2P 3/2 k3 P − 2 − +C 3k4 k42 k4

ln(k3 − k4 P 1/2 ) −

(25)

Applying initial boundary condition (t → to , Po = 0), constant C could be calculated, where, to is the reaction start up time or time delay of photo-activities due to transient state at which Po = 0. After inserting the value of C in Eqs. (25) and (26) is obtained which was further simplified to get Eq. (27)



A simple kinetic model incorporating the coupled effect of the adsorptive photocatalytic reduction and oxidation could be developed using the modified Langmuir-Hinshelwood model (Eq. (19)) using the following assumptions:

KH2 O PH2 O KCO2 PCO2

KH2 O PH2 O KCO2 PCO2

Under constant temperature and pressure, partial pressure of CO2 and H2 O vapors will be constant. Similarly, partial pressures of CO and oxygen would be proportional to partial pressure of desired product, i.e. PCO = PO2 = P. Based on these assumptions, product formation Eq. (22) in simplified form can be expressed by Eqs. (23) and (24).

t − to = −

The rate of reduction in Eq. (19) is simplified to Eq. (20).

(21)

(KCO PCO )

Rate of formation = k1

(19)

(1) The surface reactions occurred at the outer surface of the monolith channel where the catalyst is coated as thin layer. (2) The reduction of CO2 on the surface produced CO, which strongly adsorbed and overall rate of reaction may be limited by the rate of CO desorption. (3) Initially reaction rate was very fast but the rate decreased as CO accumulated on the surface, strongly adsorbed and the surface was nearly completely covered by CO, i.e. KCO PCO  1 + KCO2 PCO2 .

KO2 PO2

Rate of oxidation = k2

2

(18)

KH2 O KCO2 (PH2 O PCO2 )



dt =

KH2 O KCO2 (PH2 O PCO2 )

Rate of reduction = kI a

the L–H mechanism could be written as in Eq. (21) [44]. The rate of product formation can be obtained by subtracting rate of oxidation from rate of reduction as explained in Eq. (22) where, k2 = (koxd Ia ) is dependent on reaction temperature and light intensity factor.

2k33 3k44

 −

k3





k42

 P−

 t − to = −k5 ln where



k5 =

 k9 =

2k3

3

3k4

4

2k3

2

k4

1−

ln



1−



2k32

(k3 /k4 )

k42

, k6 =

 k 2 k4



3k4

P 3/2

P 1/2

k6

3

−

2



 P 1/2 



1/2    2

P

(26)



k8 k9 − (P 3/2 ) k7 + √ + P P

, k7 =

 2  3k4

 , k8 =

 (27)

k3 k4

2

 ,

2

Eq. (27) is known as the kinetic equation and it could be used to evaluate experimental data. However, it is further simplified by applying assumption that k5  (k7 + (k8 /P1/2 ) + (k9 /P)) as described in Eq. (28).



t − to = −k5 ln

1−

 P 1/2  k6

(28)

Eq. (28) is the simplified kinetic model equation while, k5 and k6 are constants related to reaction rate constants, adsorption–desorption ratio constants, light intensity, and experimental conditions. By assuming ideal gas law, P can be assumed to be the yield of the

M. Tahir, N.S. Amin / Applied Catalysis A: General 467 (2013) 483–496

495

Table 4 Summary of kinetic constants for model fitting (Eq. (28)) with experimental data. Catalyst

PCO2 (bar)

PH2 O (bar)

Product

k5

k6

Error

In/TiO2 In/TiO2 In/TiO2 In/TiO2 In/TiO2 In/TiO2 TiO2 TiO2

0.02 0.04 0.06 0.02 0.04 0.06 0.04 0.04

0.074 0.074 0.074 0.074 0.074 0.074 0.074 0.074

CO CO CO CH4 CH4 CH4 CO CH4

250 250 250 260 220 220 220 210

9650 11,700 10,500 490 600 530 500 840

±5% ±5% ±5% ±3% ±3% ±3% ±2% ±2%

desired product at any interval of time t. This kinetic model would be suitable for most of the photocatalytic CO2 reduction processes in gaseous phase in which there will be strong movement of electrons at the catalyst surface and efficient conversion of CO to other products or desorption of CO from the catalyst surface. The kinetic equation should be useful for optimization purposes and can also be used to deduce the rate and product yield at any particular reaction time. The curves representing the profiles of CO production could be generated as a function of irradiation time using the proposed kinetic model (Eq. (28)) to fit with the experimental data using the values of k5 and k6 as summarized in Table 4. CO and CH4 formation profiles for proposed model and experimental data are illustrated in Figs. 14 and 15. After inserting the constants, the model fittedwell with the experimental data. The good fitting of the model with experimental data confirmed CO to be strongly adsorbed over

Fig. 15. Comparison of model fitting with the experimental data for formation of CH4 and CO on TiO2 supported monolith photoreactor.

the catalyst surface as compared to other products. It may also be attributed to the possibility of strong mobility of electrons, and efficient desorption of products over the catalyst coated monolith surface. 4. Conclusions A microchannel monolith photoreactor with catalysts coated as very thin film on the walls of the channels is presented for higher CO2 reduction rate. By doping TiO2 with indium, pure anatase phase of TiO2 was achieved with smaller particle size, larger surface area and mesoporous structure. The geometric of the monolith profoundly improved product yield rates. Furthermore, the effect of temperature, catalyst loading and partial pressure of CO2 were also investigated. CO and CH4 were observed as the main products with yield rate 962 and 55.4 ␮mol g-catal.−1 h−1 , respectively and selectivity of 94.39 and 5.44%, respectively over 10 wt.% indium doped TiO2 supported over microchannels at 373 K and 0.20 bars. The other products observed were C2 H4 , C2 H6 , and C3 H6 . The performance comparison between the photoreactors revealed 183-fold higher yield of CO in the monolith compared to cell type reactor. The quantum efficiency achieved in the cell type reactor was also much lower (0.0005%) compared to the microchannel monolith reactor (0.10%). More importantly, the quantum efficiency was significantly improved using microchannels compared to internally illuminated monolith as reported previously. The higher efficiency of the monolith photoreactor was supposedly due to higher illuminated surface area, higher photon energy consumption and better utilization of reactor volume. The kinetic equation based on L–H mechanism could effectively estimate the reaction rate and product formation during photocatalytic CO2 reduction with H2 O. Therefore, a new monolith photoreactor design is eminent in the photocatalytic reactor research field while indium doped TiO2 is a highly efficient catalyst for maximizing CO yield rates and selectivity. Acknowledgments

Fig. 14. Comparison of model fitting with the experimental using data for the formation of CH4 on 10% In/TiO2 supported monolith at different CO2 partial pressure; (a) for the formation of CO and (b) for the formation of CH4 .

The authors would like to extend their deepest appreciation to the Ministry of Higher Education (MOHE), Malaysia and Universiti Teknologi Malaysia for financial support of this research under LRGS (Long-term Research Grant Scheme) and RUG (Research University Grant).

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