Tuning the co-catalyst loading for the optimization of thermo-photocatalytic hydrogen production over Cu/TiO2

Applied Catalysis A, General 643 (2022) 118804 Available online 30 July 2022 0926-860X/© 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/). Tuning the co-catalyst loading for the optimization of thermo-photocatalytic hydrogen production over Cu/TiO 2 F. Platero, A. Caballero , G. Col´ on * Instituto de Ciencia de Materiales de Sevilla, Centro Mixto Universidad de Sevilla-CSIC, Am´ erico Vespucio s/n., 41092 Sevilla, Spain ARTICLE INFO Keywords: Thermo-photocatalysis Gas-phase Hydrogen Cu-TiO 2 . Water-gas-shift ABSTRACT We have optimized the H 2 production by methanol thermo-photocatalytic reforming in the gas phase using Cu/ TiO 2 catalyst by tuning metal loading. Metal co-catalyst has been deposited by means of chemical reduction deposition. We have stated that thermo- and thermo-photocatalytic process leads to a notable H 2 production at 200 ºC. By in-situ FTIR studies we evidenced that formate formation follows a different evolution depending on the reforming experiment. These surface formate would lead to CO formation through dehydration reaction. At higher Cu content the low CO selectivity denote that water-gas-shift reaction would predominate and exalt H 2 yield. Thus, different optimum Cu content is found for each reforming experiment. While for the photocatalytic reforming Cu/TiO 2 (2 wt%) is the best catalyst of the series, we should increase the Cu content to Cu/TiO 2 (5 wt %) to achieve the optimum performance for thermo-photocatalytic reforming of methanol. 1. Introduction It is widely accepted that hydrogen, a clean and sustainable energy vector, is considered the ideal alternative of fossil fuels. Within the actual framework of the socioeconomical and environmental situation, green hydrogen will play a crucial role for a clean energy transition process [1]. Since many years, photocatalytic water splitting towards hydrogen evolution has attracted numerous attentions because of its green sustainability [2,3]. In spite of the huge efforts to generate hydrogen via powder-based solar water-splitting systems to date have unfortunately fallen short of the efficiency values required for large scale plants [4,5]. The challenge is to develop stable and efficient catalysts that can harvest solar light, using co-catalyst alternative to precious materials that would allow the scale-up and practical applications [6,7]. In this sense, promising studies at pilot plant scale have been recently reported [8–11]. Within this frame, green H 2 production from alcohol photocatalytic reforming reaction appears as a hot topic in the field of photocatalysis [12,13]. From the enormous literature on this field, TiO 2 based systems have provided the best performances [14]. However, some factors such as rapid recombination, the occurrence of backward reaction or even the deactivation by the formed intermediates hindered the development of H 2 production at large scale [15]. The use of metal co-catalysts, used as charge trapping sites, have demonstrated necessary in order to enhance the efficiency of the photocatalytic reaction by avoiding the electron–hole recombination processes [16–18]. It has been found that the addition of these noble metals could have different effects on the photocatalytic activity which is also strongly affected not only by the nature of metal but also by other parameters from sample history and metal features [19]. Alternatively to noble metals, copper-based catalysts have been extensively considered as a cheaper option [13,20–23]. In addition to this traditional strategy, the combination of heat and light has been recently suggested as a novel approach pursuing the improving efficiency of the photocatalytic process [24–26]. Thus, by the combination of classical thermo- and photo-catalytic processes, interesting synergistic effects have been reported that drastically enhances the hydrogen production through photoreforming reaction [25]. Due to the mechanistic complexity of this multicatalytic approach, which would involve different simultaneous reactions, the origin of this cooperative effect is still unclear. In principle, the synergistic improvement would be conditioned by the primary importance of single thermo- and photocontributions on the kinetic behavior and reaction mechanism [27,28]. Moreover, most of the reported results do not cover the influence of the co-catalyst loading on such complex mechanism and the catalytic performance [27,28]. In the present paper we present an interesting study on methanol reforming through a multicatalytic approach, by combining heating and photonic excitation. For this scope, we use a * corresponding author. E-mail address: [email protected] (G. Col´ on). Contents lists available at ScienceDirect Applied Catalysis A, General journal homepage: www.elsevier.com/locate/apcata https://doi.org/10.1016/j.apcata.2022.118804 Received 14 June 2022; Received in revised form 26 July 2022; Accepted 27 July 2022 Applied Catalysis A, General 643 (2022) 118804 2 Cu/TiO 2 system with different Cu loading that could serve to explore how the mechanism is influenced by metal content and therefore condition the overall reaction performance. 2. Experimental 2.1. Catalysts preparation and characterisation TiO 2 (Evonik P90) was used as photoactive support (Table 1 in Supporting Information). TiO 2 Evonik P90 exhibits higher surface area than widely used Evonik P25. Since the aim of this study is to see the effect of the amount of Cu loading on the catalytic activity, we decided to use this high surface area anatase to avoid the effect of metal agglomeration at increasing contents. Metal loading was performed through chemical reduction deposition procedure using copper nitrate as metal source. In this case, 0.5 g of support was suspended in 100 mL of water containing the stoichiometric amount of Cu precursor for a nominal loading between 1.0 and 5.0 wt%. Chemical reduction of metal precursor was achieved by using NaBH 4 as reducing agent. After adding the reducing agent at certain excess (1:20 molar ratio with respect to Cu), the suspension was stirred at room temperature for 30 min. The effectiveness of the deposition was always checked by adding more NaBH 4 to the filtrated liquid. We did not appreciate in any case any turbidity or color changes due to the presence of Cu. The obtained systems were filtered, thoroughly washed with distilled water and finally dried at 90 ºC. As prepared catalysts were labeled as CunP90, being n the nominal metal loading. BET surface area measurements were carried out by N 2 adsorption using a Micromeritics 2000 instrument. X-ray diffraction (XRD) patterns were obtained using a Siemens D- 501 diffractometer with Ni filter and graphite monochromator, using the Cu K α radiation as X-ray source., We have calculated the anatase fraction as well the mean crystallite size by Rietveld fitting using HighScore- Plus software, using the line broadening of corresponding diffraction peaks. Diffuse reflectance UV–vis spectroscopy was performed using a Cary 300 instrument. Spectra were recorded in the diffuse reflectance mode using Spectralon® as white standard. Scans range was 240–800 nm. XPS data were recorded on pellets using a customized system incorporating a hemispherical analyser (SPECS Phoibos 100), a nonmonochromatized X-ray source (Al K α ; 1486.6 eV, Mg K α , 1253.6 eV). The analyser was operated at a fixed transmission and 50 eV pass energy with an energy step of 0.1 eV. Binding energies were calibrated using C 1 s (284.6 eV) as an internal reference. Prior to each analysis, the samples were evacuated to 10 −9 mbar at room temperature. In a typical experiment, the sample was initially placed in the sample holder and transferred to the spectrometer chamber where XPS spectra were acquired. In-situ FTIR studies were performed in a Harricks praying mantis cell. The spectra were recorded on a Nicolet FT-IR spectrometer at reaction conditions with a resolution of 4 cm −1 . Before reaction, catalysts were pretreated in N 2 at 50 ºC for 30 min Temperature programmed reduction (H 2 -TPR) was performed using a Chemstar instrument (Quantachrome). About 30 mg of the catalysts previously degassed at 50 ◦C for 30 min under Ar flow. The TPR spectra were collected in 10 mL/min mixture of 5% H 2 /Ar from 50 ºC to 700 ◦C with a heating rate of 10 ◦C/min. Transmission electron microscopy were performed by using a FEI Tecnai F30 microscope in STEM mode operated at 300 kV equipped with a Gatan GIF Quantum 963 energy filter. The samples were directly dropped on a nickel grid. 2.2. Photocatalytic runs Gas phase photocatalytic H 2 production tests were performed in a flow cell (Fig. 1). The powder photocatalysts (50 mg) were placed in the cell and then degassed with N 2 at 50 ºC. Methanol steam flow (CH 3 OH = 20% v/v) at 15 mL/min was passed through the sample for 60 min before reaction. After which, the lamp (200 W lamp housing) was switched on and the sample was illuminated through the quartz topwindow of the cell. Effluent gases were analysed to quantify H 2 production by gas chromatography (Agilent microGC) using a thermal conductivity detector. Only CO and CO 2 were detected as side products. CO selectivity (S CO ) were calculated by considering all products detected: SCO(%) = [CO] ([H2] + [CO] + [CO2]) ×100 Thermo-photocatalytic runs were performed at 200 ºC. As we have evidenced in a previous study, at this temperature the synergistic effect for thermo-photocatalytic process is maximum [29]. As reference, thermo-catalytic runs were performed in the absence of light under similar reaction conditions. The apparent quantum efficiency for the H 2 evolution reaction has been determined from the reaction rate and the flux of incoming photons (calculated for the irradiation wavelengths of 365 nm) [20,30]. AQE =rate (mol⋅s−1) rate of incident photons (mol⋅s−1) The synergetic effect of the thermal contribution on thermophotocatalytic process was evaluated by considering the difference rate with single process rates [31]. ratesyn =ratethermo−photo −(ratephoto +ratethermo) From this rate syn value we have calculated the synergetic efficiency (AQE syn ) which specifically accounts the efficiency attributable to the synergy of both thermo- and photo-catalytic processes. 3. Results and discussions 3.1. Copper features study with metal content Copper deposition over TiO 2 by chemical reduction leads to well dispersed Cu nanoparticles over the range of studied systems. As it can be observed from STEM images (Fig. 2), homogeneous dispersion of Cu nanoparticles of ca. 2 nm is obtained. Moreover, no aggregation of Cu clusters is noticed as metal loading increases. From diffuse reflectance spectra (Fig. 3), important absorption bands can be found at 350–450 nm and 750 nm that can be attributed to Cu clusters at the surface. These new bands progressively increase as copper loading increases, specially bands at 410 nm and 750 nm. Thus, bands within the range 350–450 nm have been ascribed to (Cu–O–Cu) 2+ Fig. 1. Photocatalytic gas-phase flow-reactor used for thermophotocatalytic runs. F. Platero et al. Applied Catalysis A, General 643 (2022) 118804 3 clusters in a highly dispersed state as well as to three-dimensional Cu 1+ clusters. [32,33] On the other hand, the band at 750–850 nm has been assigned to 2 E g → 2 T 2 g transitions of Cu 2+ located in the distorted or perfect octahedral symmetry. [34] From these results, we could expect that Cu species would consist on highly dispersed CuO and surface doped Cu 2+/1+ . Both bands progress similarly as metal content increases (Fig. 3.b). Reduction profile also denotes the evolution of copper clusters as loading increases (Fig. 4). In all cases a single TPR peak ca. 180 ºC is found for all catalysts. This is a rather lower reduction temperature compared with values reported in the literature, and would be attributed to highly dispersed CuO species at the nanoscale. [35–37] Moreover, from the deconvolution of TPR peaks it is possible to envisage four Cu species, denoted as α to δ. The presence of different reduction peaks in the TPR profile of oxide-supported Cu samples has been extensively reported. [38,39] Thus, it is accepted that large and crystallized CuO particles would be reduced at higher temperature than smaller CuO clusters or highly dispersed Cu 2+ species in strong interaction with the oxide support. [40,41] In our case, the reduction temperature around 180 ºC clearly points out the absence of bulk CuO, as was stated above from TEM images. For all samples, species reduced at slightly higher temperature (γ+δ) are prominent. However, as metal loading increases, low reduction temperature species ( α +β) become more evident (Fig. 4.b). Such low reduction temperature species would be associated to finely disperse copper species as support Cu 2+ doped and would be hardly detected from TEM analysis. So, only small CuO nanoclusters are noticed. Therefore, for higher Cu content catalyst, Cu species distribution seems to be composed equally by small finely disperse CuO nanoclusters and surface doped Cu 2+ species. Quantitative analysis from H 2 consumption clearly denotes the efficiency of deposition method. The amount of reduced Cu follows a clear linear evolution being in all cases close to the nominal values (Fig. 4.c). From XPS analysis, the observed broad peaks as well as the presence of a shake-up satellite would denote the coexistence of Cu 2+ and Cu + /Cu species (Fig. 5.a). Thus, peaks at 932.0 eV and 951.9 eV would correspond to Cu 2p 3/2 and Cu 2p 1/2 spin-orbit split of Cu/Cu 2 O species. [42] On the other hand, a second contribution at 934.2 eV and 954.1 eV with satellite shakeup at ca. 942 eV, in all the synthesized products should correspond to CuO species. It is also worthy to mention that for lower Cu contents, partially reduced fraction seems to be slightly higher (Table 1). This fact could be explaining considering a higher dispersion in these samples. Such low dimensional CuO clusters should be easily reduced under XPS conditions. In agreement with TPR analysis, the surface Cu/Ti ratios calculated from XPS signals also follows a linear progression with nominal values, indicating the homogeneous distribution of Cu species over TiO 2 surface even at large metal loadings (Fig. 5.b). The Cu/Ti ratios obtained for samples after thermo-catalytic or thermo-photocatalytic runs at 200 ºC do not show a significant variation from fresh sample (Table 1). Therefore, no aggregation should be expected after reaction by effect of temperature. Moreover, as Cu content increases the ratio of oxidized Cu seems to be slightly increased (Table 1), similarly as α +β family evolution from TPR experiment. This can be also observed from satellite relative intensity (I sat /I Cu2p3/2 ), showing the highest value for Cu4P90 catalyst. Indeed, α +β family has been previously associated to small CuO nanoclusters. The higher partial reduced fraction in low Cu content catalysts could therefore be ascribed to highly disperse Cu 2+ entities (γ+δ species) that would easily reduce under XPS conditions. 3.2. Thermo-photocatalytic performance of Cu/TiO 2 system Fig. 6 shows the H 2 production rates and apparent efficiencies and H 2 Fig. 2. HAADF images for Cu3P90 (upper panel) and Cu5P90 (lower panel) systems. Fig. 3. a) DRS spectra for Cu/TiO 2 systems; b) Difference spectra of different Cu/TiO 2 samples with respect to bare TiO 2 . F. Platero et al. Applied Catalysis A, General 643 (2022) 118804 4 yields of Cu/TiO 2 P90 systems. Thus, the obtained rates for photo-, thermo-, and thermo-photocatalytic runs under UV–vis light illumination for 4 h are summarized in Table 2. As it can be observed, the performance for thermo-photocatalytic H 2 production are notably higher in all cases with respect to single thermo- and photocatalytic processes (Fig. S1). The apparent quantum efficiencies denote that for photocatalytic performance the maximum value is attained for Cu2P90 catalyst, showing an H 2 production of 12 mmol/h⋅g after 4 h (Fig. 6.a). A higher Cu loading negatively affects to the photoreforming activity. In principle, the higher photoactivity exhibited by Cu2P90 would be associated to the finely dispersion and stronger interaction with support observed Fig. 4. a) H 2 -TPR profiles (inset shows the deconvolution analysis for Cu5P90 TPR), b) evolution of different Cu species with content; and c) calculated Cu content from H 2 consumption for Cu/TiO 2 systems. Fig. 5. a) XPS Cu 2p spectra and b) surface Cu/Ti ratios for Cu/TiO 2 systems from XPS analysis. Table 1 XPS analysis for Cu/TiO 2 systems. Surface at% Isat/ICu2p3/2 Cu/Ti ratio Cu + /Cu 0 Cu 2+ Cu2P90 81 19 0.12 0.110 T200 70 30 0.109 TP200 77 23 0.114 Cu3P90 82 18 0.12 0.148 Cu4P90 59 41 0.25 0.192 Cu5P90 65 35 0.19 0.247 F. Platero et al. Applied Catalysis A, General 643 (2022) 118804 5 from TPR. [43] As metal loading increases, recombination processes would hinder the photocatalytic performance. It can be also stated that thermo-catalytic process also leads to significant production of H 2 . As we already discussed, H 2 formation under these conditions could be explained considering methanol thermal decomposition (Eq. i) [44,45]. CH3OH → 2 H2+CO methanol decomposition Eq. i In this case, AQE values lineally increases in the whole range of Cu content, reaching an H 2 yield of ca 30 mmol/h⋅g for Cu5P90 catalyst (Fig. 6.a). Therefore, in this case and within the range of metal content studied, thermo-catalytic activity is clearly favoured by the increasing surface Cu over TiO 2 . Finally, the combined thermo-photoreforming leads to notable values of efficiency, with a maximum yield of ca. 60 mmol/h⋅g also for Cu5P90 catalyst. However, in this case the photocatalytic performance of Cu5P90 is close to that exhibited by Cu4P90 denoting certain exhausting effect in the thermo-photocatalytic activity with increasing metal loading. Thus, at this Cu loading the optimum metal content could be considered. (Fig. 6.a). Since calculated rate syn always show positive values, the combined process cannot be explained as the sum of both single ones, and a certain synergistic effect can be envisaged for all catalysts. Moreover, the calculated AQE syn clearly denote that the combination of thermo- and photoprocesses notably affects to the overall reaction performance and appear clearly affected by metal loading (Fig. 6.b). In this sense, it is also interesting to highlight the evolution of the synergy with Cu loading (Fig. 6.b). For the lowest Cu content, since the photocatalytic performance is rather low, thermal contribution appears important. Minimum AQE syn is found for Cu2P90, for which the photocatalytic performance is maximum. Thermal-photocatalytic synergy reaches a minimum for Cu2P90 catalyst, for which photocatalytic performance is maximum and thermo-catalytic activity is still low. Catalysts with metal contents higher than 2 showed outstanding thermophotocatalytic AQE that progressively increases with Cu content. However, though thermal reforming lineally grows with Cu, a maximum in the AQE syn is found for Cu4P90 catalysts. This fact would point out a process that would hinder the thermo-photocatalytic performance for Cu5P90. In order to understand the evolution showed by AQE and AQE syn in different studied photoreforming processes, we followed CO and CO 2 as interesting intermediates from side reactions that would simultaneously take place (Fig. 7). Thus, CO can be derived from side reactions that would proceed simultaneously with photoreforming; that is, methanol decomposition as well as formic acid dehydration (Eqs. i and ii) [45]. HCOOH →H2O+CO formic acid dehydration Eq. ii From the evolution of CO selectivity, the single photocatalytic process clearly denotes a concomitant formation of CO. The observed CO formation progressively decreases as Cu loading increases. For the thermocatalytic process, low amounts of copper do not lead to CO formation, starting at Cu loading higher than 2 wt%. It is worthy to notice that the combine thermo-photocatalytic process shows a similar trend as photocatalytic one, but with much lower CO selectivity. Thus, for higher Cu loading S CO values are similar to that obtained by thermocatalysis. The marked lower S CO values attained for thermo- and thermophotocatalytic processes would denote an important CO consumption (probably associated with a higher H 2 yield). Thus, two probable processes could be involved to explain the lower CO formation and higher H 2 production. On one hand, formic acid Fig. 6. a) H 2 production and b) Photonic Efficiencies (AQE and AQE syn ) for Cu/ TiO 2 systems after 4 h of reaction. Table 2 Rates for the H 2 photoreforming under different conditions. Catalysts Reforming rate (mmol/h⋅g) @ 4 h 50 ºC T 200ºC TP 200ºC Cu1P90 2.2 1.4 8.0 Cu2P90 3.7 8.7 Cu3P90 2.8 6.1 12.2 Cu4P90 2.1 6.9 Cu5P90 1.9 8.3 14.0 Fig. 7. CO Selectivity during the gas-phase methanol thermo-photocatalytic reforming using Cu/TiO 2 after 4 h of reaction. F. Platero et al. Applied Catalysis A, General 643 (2022) 118804 6 dehydrogenation as alternative way to decompose formic acid instead of dehydration; and water gas shift reactions (Eqs. iii and iv). Indeed, the occurrence of water-gas-shift reaction has been previously argued within H 2 photoreforming reaction [29,44]. HCOOH →H2+CO2dehydrogenation Eq. iii CO +H2O→H2+CO2water gas shift (WGS)Eq. iv We may also point out that the presence of CO during photoreforming reaction would probably affect to the photocatalytic activity during the reaction time by CO poisoning of the metal active sites [46, 47]. 3.3. In-situ FTIR analysis of thermo-photocatalytic reaction In Fig. 8 we depict the FTIR spectra during in-situ photoreforming reaction. From these spectra, two important regions can be envisaged. In the higher wavenumber region, C–H stretching modes can be found. Thus, C–H contributions at 2920/2820 cm −1 have been associated to metoxy species [45,48]. The appearance of these bands is accompanied by a negative broad peak at around 3620 cm –1 due to the disappearance of surface hydroxyl groups through the dissociative adsorption of methanol. As described in the literature, the C–O stretching region located in the region 1800–700 cm –1 also shows the characteristics bands associated to methanol. Thus, at room temperature it can be notice a sharp band at around 1060 and 1135 cm –1 that can be ascribed to C–O stretching modes of methoxy group. The evolution of bands in this region during different experimental conditions is similar for all catalysts, varying the relative intensity of certain bands. Thus, during photocatalytic experiment at 50 ºC, new intense bands appear within this region at 1580 cm –1 and 1360 cm –1 . These new bands can be ascribed respectively to the υ as (COO) and υ s (COO) for bidentate formate ions adsorbed on TiO 2 surface. The intensity of these bands remains almost similar as Cu loading increases for Cu contents higher than 2 wt% (Fig. S2). It is worthy to mention that these bands do not appear during thermal treatment. In this case, only the band at 1135 cm –1 seems to be exalted (Fig. S2). Concerning the thermo-photocatalytic process, as temperature increases, bands associated to formates become notably marked. However, at 200 ºC these bands completely disappear. At 120 ºC, such bands are noticeable, showing exponential growing intensities as Cu content increases (Fig. S2). Therefore, the formation of formates seems to be clearly favoured by the increasing metal sites. As previously stated, the presence of formates would determine the different evolution of CO.[29] Thus, for photocatalytic runs we have already showed that S CO values were particularly lower with respect to those found for thermo- and thermo-photocatalytic experiments (Fig. 8). These two facts can be correlated by considering formic acid dehydration reaction which leads to the formation of CO and H 2 O. As above discussed, during thermo-photocatalytic experiment, at moderate temperatures the formation of formates was exalted and increases with Cu content. It is clear that formate formation is favoured by temperature. The absence of formate bands at reaction temperature clearly indicates that they were completely transformed into CO through dehydration. At the same time, we have also stated that S CO drastically decays. Therefore, during thermo-catalytic reforming at 200 ºC the outstanding H 2 formation can be ascribable to the enhanced transformation of methanol into formate which proceed to CO and then through WGS reaction to H 2 formation. From both facts it would be inferred that WGS reaction is playing an important role. In this sense, the higher the Cu load, the more important the WGS reaction becomes in the overall process. Thus, it can be argued that the efficiency of the thermophotocatalytic reaction over Cu/TiO 2 systems would be improved with Cu loading. Thus, the different optimum Cu loading attained for photocatalytic and thermo-photocatalytic reforming was conditioned by the thermal contribution through WGS reaction. From these results, it seems that this later process would be favoured by increasing Cu loadings. Thus, while for photocatalytic reforming Cu2P90 showed the optimum value, for the combined thermo-photocatalytic process Cu5P90 would be the best catalyst. Therefore, we evidenced a clear dependency of the mechanism on the metal content. Moreover, as we stated from TPR and XPS Cu species present in each case is different. Thus, while for Cu2P90 Cu 2+ with strong interaction with support are the predominant, for Cu5P90 CuO dispersed nanoclusters would be also present. The influence of cluster size on the photocatalytic performance of H 2 photoreforming was studied by Zheng et al. which stated that small clusters usually possess higher charge separation efficiency [49]. In this sense, Li et al. showed that through ligand assisted method, ultrafine size clusters of Cu species (with about 1 nm), dispersed on the surface of TiO 2 were obtained [50]. These authors reported that the superior H 2 evolution performance of CuO/TiO 2 mainly originates from the cluster size and unique interfacial structure formed. On the other hand, CuO clusters modulated in the range 4–8 nm by controlling the loading amount of Cu and calcining temperature were obtained for photocatalytic WGS reaction [51]. Therefore, it is clear that different process would require not only a particular metal loading but also an optimum cluster size. Moreover, different copper species distribution could be also correlated with the better performance as temperature increases. Fig. 8. In situ DRIFTS spectra of Cu/TiO 2 systems under methanol steam at different reaction conditions. F. Platero et al. Applied Catalysis A, General 643 (2022) 118804 7 4. Conclusions Copper supported TiO 2 with different metal loadings was used as catalyst for the gas phase methanol thermal photoreforming. From the wide characterization of the catalyst, we have shown that copper metal co-catalyst has been efficiently deposited and well dispersed on the support surface within the studied range of metal loading. We have stated the important synergistic effect in the thermal-photocatalytic reaction. Thus, ca 60 mmol/h⋅g cat was obtained after 4 h at 200 ºC upon illumination. Different optimum metal loading can be envisaged for different methanol reforming experiments. Moreover, as increasing metal loading, the nature of Cu species seems to be modified, subsequently conditioning the catalytic performance. Thus, while for the photocatalytic reforming Cu2P90 was the best catalyst, the thermocatalytic reforming performance follows a lineal evolution with Cu content in the range of the studied metal content. For thermophotocatalytic reforming, the optimum value would be Cu5P90 for which the synergistic improvement started to decay. During thermophotocatalytic reaction different thermo- and photo-processes are involved, resulting in different optimal catalyst formulation. We have shown that while for photocatalytic reaction low co-catalyst loading leads to the better performance, for thermo-photocatalytic process higher loading is needed. These results clearly highlight the necessity of metal loading optimization due to the occurrence of different catalytic mechanism that simultaneously takes place during the thermophotocatalytic reaction. CRediT authorship contribution statement F. Platero: Methodology, Investigation, Writing – original draft. A. Caballero: Conceptualization, Methodology, Supervision. G. Col´ on: Conceptualization, Methodology, Writing – original draft, Writing – review & editing, Supervision. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Data Availability Data will be made available on request. Acknowledgments Authors acknowledge the financial support from the EU FEDER and Junta de Andalucía under I+D+i Project P20-00156. We also acknowledge the financial support from PID2020-119946RB-I00 project funded by MCIN/AEI/ 10.13039/501100011033 and, as appropriate, by “ERDF A way of making Europe”, by the “European Union”. Appendix A. Supporting information Supplementary data associated with this article can be found in the online version at doi:10.1016/j.apcata.2022.118804. References [1] S. Wu, N. Salmon, M.M.J. Li, R. Ba˜ nares-Alc´ antara, S.C.E. Tsang, Energy decarbonization via green H 2 or NH 3 ? ACS Energy Lett. 7 (2022) 1021–1033. [2] Q. Wang, K. Domen, Particulate photocatalysts for light-driven water splitting: mechanisms, challenges, and design strategies, Chem. Rev. 120 (2020) 919–985. [3] W.H. Chen, J.E. Lee, S.H. Jang, S.S. Lam, G.H. Rhee, K.J. Jeon, M. Hussain, Y. K. 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