Abstract
Supported metal catalysts have shown to be efficient for CO2 conversion due to their multifunctionality and high stability. Herein, we have combined density functional theory calculations with microkinetic modeling to investigate the catalytic reaction mechanisms of CO2 hydrogenation to CH3OH over a recently reported catalyst of Cd4/TiO2. Calculations reveal that the metal‐oxide interface is the active center for CO2 hydrogenation and methanol formation via the formate pathway dominates over the reverse water‐gas shift (RWGS) pathway. Microkinetic modeling demonstrated that formate species on the surface of Cd4/TiO2 is the relevant intermediate for the production of CH3OH, and CH2O# formation is the rate‐determining step. These findings demonstrate the crucial role of the Cd‐TiO2 interface for controlling the CO2 reduction reactivity and CH3OH selectivity.
Keywords: CO2 , hydrogenation, CH3OH, Cd4/TiO2 , multifunctional interface
Multifunctional catalysts: The detailed reaction mechanism of CO2 hydrogenation to CH3OH was investigated over the multifunctional catalyst of Cd4/TiO2. Benefiting from the cooperation between Lewis acids from the Cd and Ti sites and Lewis bases from TiO2 surface oxygen atoms, the Cd4/TiO2 exhibited high activity and selectivity for the CH3OH production.

Introduction
The increase of CO2 concentration in the atmosphere is one of the major factors in global climate change. CO2 capture and valorization have been considered as promising strategies to mitigate this problem. [1] Using CO2 as a feedstock to produce valuable chemicals not only can help to decrease dramatically the amount of CO2 emitted into the atmosphere but also provide economic benefits.[ 1b , 2 ] A large number of value‐added chemicals can be produced from CO2 via platform molecules such as CO, CH4, and CH3OH. [3] Among these, CH3OH is highly desirable because it is an important fuel as well as a starting feedstock for the production of more valuable chemical compounds. [4] Recently, two different approaches for CO2 hydrogenation to CH3OH have received a lot of attention: (1) electrochemical reduction and (2) thermochemical reduction. [5] The electrochemical CO2 reduction offers the advantage that product distribution can be controlled by adjusting electrolyte, electrocatalyst, and applied voltage. [6] However, the selectivity, energetic efficiency, electrode lifetime restrict to its large‐scale applications.[ 6c , 6d ] Therefore, using the thermochemical approach to synthesize CH3OH from CO2 hydrogenation is more practical for potential industrial applications compared to the alternative electrochemical CO2 reduction. It offers an opportunity for the development of sustainable technologies and environmentally benign chemical processes since H2 which is a reducing agent can readily be obtained from renewable energy resources.[ 1a , 2 ]
Many studies have been devoted to creating new tailor‐made CO2 conversion catalysts with improved activity and selectivity to methanol, of which Cu/ZnO/Al2O3 catalyst has been industrialized. [7] However, the disadvantages of low CH3OH selectivity and the sintering of Cu and ZnO motivated the development of new Cu‐based catalysts such as Cu/ZnO, [8] Cu/ZrO2, [9] and Cu/CeO2. [10] In these catalytic systems, it was found that H2 molecule is dissociated at the Cu site and CO2 is activated at the oxide surface, while the interface between Cu and metal oxide supports plays a crucial role for stabilization of the reaction intermediate for CH3OH formation. [9] Besides Cu‐based catalysts, various other materials have also been reported as promising catalysts for CO2 hydrogenation to CH3OH. For instance, Au, [11] Pd [12] , Re, [13] ZnO [14] and In2O3 [15] supported on oxides were reported to be active toward the production of CH3OH under moderate conditions. Although many different types of catalysts have been reported, all of the active sites involved in the reaction have a common feature of multi‐functionality in nature. An efficient cooperation between active sites of different catalytic natures coupled in one heterogeneous catalyst plays a key role for eventual selective CH3OH formation.
Regarding the reaction mechanism, typically, two different reaction pathways have been proposed for the hydrogenation of CO2 to CH3OH: (1) the reverse water‐gas shift (RWGS) pathway, and (2) the formate pathway. In the RWGS reaction, CO2 is hydrogenated to form CO* intermediate which is then further hydrogenated to form CH3OH. For the formate pathway, CH3OH is produced via the formate (HCOO*) intermediate. [16] Most studies have suggested that the formate pathway is preferred over the RWGS pathway.[ 7b , 12a , 17 ] The main reason is that the binding strength of CO* intermediate on these catalysts is quite weak, leading to the desorption of CO to the gas phase. However, on some other catalysts such as Cu/TiO2, Cu/ZrO2, and Cu/CeOx, CH3OH was produced through CO* intermediate due to the strong enough interaction between CO* and catalyst.[ 9b , 10 ] Therefore, the specific reaction pathway dominating methanol formation is system‐dependent and should be investigated individually.
Recently we have investigated CO2 conversion to CH3OH on Cd/TiO2 and CdTiO3 catalysts by a combination of experimental and computational studies. [18] It was found that Cd/TiO2 catalyst exhibits a much higher catalytic CO2 hydrogenation activity than the CdTiO3 mixed oxide. To further identify the detailed reaction mechanism catalyzed by Cd/TiO2 and clarify the functionalities of different types of active sites in this system, we constructed a Cd/TiO2 model catalyst and investigated its catalytic activity towards CO2 conversion to methanol with H2 as a reductant. The key objective of this study is to explore the multiple‐site cooperation effects on the catalyst reactivity by combining DFT calculation with microkinetic modeling.
Results and Discussion
Cd4/TiO2 Model rationalization
A cluster containing 4 Cd atoms (Cd4) was selected as representative of the supported Cd nanoparticles on the TiO2 surface since it was reported as the smallest Cd cluster featuring a magic number of Cd atoms. In order to model the Cd4/TiO2 catalyst, two possible configurations of isolated Cd4 cluster, i. e., a tetrahedron (Td) and planar rhombus (C2V) [28] were firstly optimized in the vacuum by using a large unit cell of 15×15×15 Å (Figure S1 in the supporting information). Then the so‐obtained Cd4 clusters were deposited and optimized on the (101) surface of anatase TiO2. It is found that the most stable configuration of the supported Cd4 cluster on the (101) TiO2 surface is a deformed planar geometry even though the tetrahedron is more stable in the gas phase. As shown in Figure 1, the Cd4 (C2V) cluster is slightly distorted upon the adsorption with one of the Cd atoms lying above the plane of the other three. The adsorption energy of Cd4 over the surface is calculated to be −1.05 eV indicating a strong interaction between the metal cluster and the support of TiO2. Bader charge analysis demonstrates that the entire Cd4 cluster is +1.48|e| charged, which indicates that the electrons are transferred from Cd4 cluster to TiO2 surface through metal‐support interaction.
Figure 1.

(a) Top view and (b) side view of Cd4/TiO2(101) slab model. The O2c and O3c are twofold coordinated and threefold coordinated oxygen atoms, and the Ti5c and Ti6c are fivefold coordinated and sixfold coordinated titanium atoms on the surface of TiO2, respectively. (c) The electron density different plots upon the adsorption of Cd4 cluster on TiO2 surface. The orange and green regions represent electrons depletion and accumulation respectively (isosurface value=0.05 e/Bohr3).
H2 dissociation and H spillover
Many studies have proposed that activation and dissociation of an H2 molecule take place at the metal‐oxide interface. [29] In this work, six possible active sites of Cd4/TiO2 catalyst for the activation and dissociation of H2 molecule were systematically studied. As shown in Figure 2, site A is on top of the supported Cd4 cluster. Site B, C and D are at the interface of Cd4/TiO2 (Cd−O2c). Site E is located between two nearest O2c atoms and site F is on top of bridging Ti5c and O2c atoms of TiO2 surface. From Figure 2 it can be seen that that heterolytic H2 dissociation at the interface of Cd/TiO2 is more preferable than the other sites. Among all interface sites considered, H2 dissociation over site C has the lowest activation barrier (0.39 eV). Homolytic dissociation of H2 molecule over site A needs to overcome an activation barrier of 0.88 eV and generates two hydrides on the supported Cd4 cluster. On the TiO2 surface, both homolytic (site E) and heterolytic dissociation pathways (site F) exhibit very high activation barriers (1.74 and 2.25 eV) indicating that TiO2 surface site is inactive for H2 activation. This is in agreement with a previous theoretical study of H2 dissociation on TiO2 surfaces. [30]
Figure 2.

Activation energy (Ea) and reaction energy (ΔErxn) for H2 dissociation at all possible active sites of Cd4/TiO2 catalyst.
After we figured out the most favorable active site for H2 dissociation, the spillover process of the so‐formed H* on the surface of the Cd4/TiO2 is further studied. As shown in Figure S2, the migration of the H* generated by H2 dissociation at the interface (site C) from O2c site to its neighboring O3c site has an activation barrier of 0.73 eV. The other H* species on the Cd4 cluster can also spillover to the surface of TiO2 with an activation barrier of 0.71 eV. H* on O3c site can also hoop to another O2c site next to it by overcoming a barrier of only 0.42 eV. The overall reaction is slightly endothermic. These results indicate that the activated H* on the surface of the Cd4/TiO2 catalyst is rather dynamic and hydrogen migrations among different surface sites is thermodynamically and kinetically easy processes.
CO2 hydrogenation to HCOOH and CO
In this section, the hydrogenation of CO2 on Cd4/TiO2 catalyst will be discussed. Two main reaction pathways of CO2 hydrogenation which have been intensively debated in the literature were studied: (1) methanol formation via the intermediate of HCOOH*, and (2) methanol formation via the reversed water‐gas shift (RWGS) pathway with CO as an intermediate. Noted that the species with asterisk (*) and hash sign (#) are species that interact with TiO2 surface and Cd4 cluster of the Cd4/TiO2 catalyst, respectively.
Formate pathway
The reaction mechanisms of CO2 hydrogenation to formate (HCOO*) and formic acid (HCOOH*) are shown in Figure 3. After heterolytic dissociation of H2 at the interface of Cd4/TiO2, a hydride coordinated to Cd (H#) and a proton bonded to O2c site (H*) are produced. CO2 is adsorbed over the Ti5c site nearby both H* and H# species. The adsorption energy is calculated to be −0.14 eV. Then CO2 can be hydrogenated by the transfer of H# from Cd4 cluster to the C atom of CO2 forming formate intermediate of HCOO*. The activation barrier for this step is only 0.26 eV. Further protonation of HCOO* to form formic acid (HCOOH*) can be realized via two different reaction routes, either by protonation of monodentate HCOO* intermediate to form cis‐HCOOH* (gray line in Figure 3), or protonation of bidentate HCOO*# intermediate which can be formed by structure rearrangement to form trans‐HCOOH*# (orange line in Figure 3). The activation barriers of proton transfer for both routes are relatively low (0.22 and 0.41 eV), however, the configurational transformation of HCOO* from monodentate coordination to bidentate coordination with both Ti5c and Cd before protonation reaction is dramatically favorable. Another possible pathway for HCOOH* formation is also identified with a small activation barrier of 0.15 eV, the so‐called concerted reaction mechanism with CO2 hydrogenation by both H* and H# in one step (green line in Figure 3).
Figure 3.
Reaction energy profiles for the CO2 hydrogenation to HCOOH* on Cd4/TiO2 catalyst. Green line is the concerted pathway. Gray line is the stepwise pathway via monodentate HCOO*. Orange line is the stepwise pathway via bidentate HCOO*#. The species with asterisk (*) and hash sign (#) are species that interact with TiO2 surface and Cd4 cluster of the Cd4/TiO2 catalyst, respectively.
RWGS pathway
The RWGS reaction mechanism is initiate by CO2 hydrogenation to first form carboxylate intermediate (HOCO#), from which CO is produced and can be further converted into methanol by continuous hydrogenation reactions. As shown in Figure 4, the reaction starts with the adsorption of CO2 at the perimeter site of Cd4 cluster after hydrogen spillover process. Then, the CO2 can be protonated by the H* on TiO2 surface forming HOCO#. It is found that this reaction cannot occur directly due to the long distance between CO2 and H* (4.93 Å). However, it can proceed by the assist of an H2O molecule which acts as a proton shuttle between H* and CO2 (blue line in Figure 4). The activation energy in this case is calculated to be 0.42 eV indicating that this process is feasible. Subsequent hydrogenation of the HOCO# intermediate at its terminal OH group with the breaking of C−O bond produces CO# and H2O*. This process requires overcome an activation barrier of 0.35 eV. Finally, CO and H2O can be desorbed from the catalyst with desorption barriers of 0.13 and 0.19 eV, respectively.
Figure 4.
Reaction energy profiles for the CO2 hydrogenation to CO on Cd4/TiO2 catalyst (RWGS pathway). Blue line is the reaction with the assist of H2O molecule.
Due to the unfavorable adsorption of CO2 on the supported Cd4 cluster, we also explored the CO2 adsorption on a separate TiO2 surface site without interaction with the Cd4 cluster. The mechanisms of RWGS reaction on the TiO2 surface are shown in Figure 5. In this case this reaction starts with the adsorption of CO2 on the TiO2 surface after hydrogen spillover process. The adsorption energy of CO2 is calculated to be −0.45 eV which is relatively stronger than that on supported Cd4 cluster. The bent CO2 geometry can be formed on the TiO2 surface with an activation barrier of 0.44 eV. Then the adsorbed CO2* is directly hydrogenated to form HOCO* without the H2O mediator. The activation energy for this step is calculated to be 0.74 eV. The diffusion of the second H* to the O3c site close to the OH group of HOCO* needs overcome an activation barrier of 0.76 eV. After that, the cleavage of the C−O bond of HOCO* intermediate to generate CO* and OH* species on the TiO2 surface is rather difficult with an activation barrier of 1.86 eV. However, the presence of H2O molecule can again decrease this activation barrier to 0.94 eV with C−O bonding breaking and OH group hydrogenation occurring simultaneously.
Figure 5.
Reaction energy profiles for the CO2 hydrogenation to CO on clean TiO2 surface (RWGS pathway). Blue line is the reaction with the assist of H2O molecule.
It is found that H2O molecule plays an important role as a proton shuttle to promote the most difficult reaction steps during the RWGS reactions taking place at both interface and TiO2 surface of Cd4/TiO2 catalyst. The hydrogenation reaction of CO2 is the most difficult step for the reaction occurred at the interface while the C−O bond cleavage of HOCO* carboxylate intermediate is found to be the most difficult step for the reaction occurred at the TiO2 surface. The highest activation energy of the RWGS reaction that occurs at the interface of Cd4 and TiO2 surface (TS‐R1w) is about two times lower than that of the other reaction route on the TiO2 surface (TS‐r6w). Therefore, it is concluded that the most preferable active site for the RWGS reaction is the interface of Cd4/TiO2 catalyst. Therefore, in the next section, the discussion of CH3OH formation via CO* will only focus on the reaction route at the interface.
CH3OH formation
In this section, we will discuss the reaction mechanism of CH3OH formation from HCOOH* as well as CO* intermediates generated from the formate and the RWGS reaction pathways. The results are shown in Figure 6. Totally 4 elementary hydrogenation reaction steps are involved for CH3OH formation from CO i. e. CO*→HCO*#, HCO*#→CH2O*, CH2O*→CH3O* and CH3O*→CH3OH. The activation barrier for CO hydrogenation to form HCO*# is 0.32 eV by H# on Cd4 cluster. The next step of dissociative adsorption of H2 on top of HCO*# intermediate generating CH2O* and H# species has an activation barrier of 1.10 eV. Subsequent CH3O* formation by CH2O* hydrogenation is a barrierless process with a reaction energy of −1.40 eV. Finally, the CH3OH is formed by hydrogenation of CH3O* intermediate with the activation barrier of 0.48 eV. In addition, CH3OH can be produced by the hydrogenolysis of CH3O* (green line in Figure 6). The activation energy of this step is only 0.04 eV lower than that of the CH3O* hydrogenation step. These results imply that both CH3O* hydrogenolysis and CH3O* hydrogenation coexist in the formation of CH3OH.
Figure 6.
Reaction energy profiles for the production of CH3OH from CO and HCOOH.
Alternatively, CH3OH can also be formed from HCOOH* (blue line in Figure 6). The initial step is the hydrogenation of HCOOH* to produce formaldehyde (CH2O#) and an OH* species (CH2O#+OH*+H*). The activation energy of this step is calculated to be 0.65 eV. Then, the OH* is protonated to form H2O and regenerate a vacant interfacial active site on the surface. In the next step, after another H2 molecule is dissociated at the interface, the CH3OH can be formed by two successive hydrogenation steps from CH2O*, which is the same process as the reactions via the RWGS pathway.
To summarize, Figure 7 gives a schematical representation of the whole DFT reaction mechanism identified in this work, and the whole reaction pathways of CO2 hydrogenation to CH3OH on Cd4/TiO2 catalyst is shown in Figure S4. It can be seen that the formate pathway dominates over the RWGS pathway for the production of CH3OH from CO2 and H2. The formation of CH2O* intermediate is found to be the most difficult reaction step for CH3OH production from both RWGS and formate reaction routes.
Figure 7.
A schematically representation of the whole reaction mechanism for CO2 hydrogenation to CH3OH on Cd4/TiO2 catalyst. Numbers in parenthesis represent activation energies in eV. Solid lines and dash lines represent reaction that occurs at the interface and TiO2 surface, respectively.
Microkinetic modeling
All considered elementary steps of the CO2 hydrogenation to CH3OH on Cd4/TiO2 catalyst, and corresponding activation energies are listed in Table 1. The MKM is performed using a dual‐site model representing TiO2 (*) and Cd (#) sites on Cd4/TiO2 catalyst, respectively. The ratio between the number of * and # sites is 0.5 : 0.5. The reaction rate, surface coverages, and degree of rate control (DRC) are calculated under the following steady‐state reaction conditions: total pressure=2 MPa., H2/CO2=3 : 1, temperature=270–310 °C. The apparent activation energy (Eapp) is determined from the slope of the Arrhenius plot, as shown in Figure 8a. The Eapp for the CH3OH formation is calculated to be 1.46 eV (141.0 kJ/mol), while that for the CO formation is much higher, 4.10 eV (395.4 kJ/mol). This agrees with the experiment that the Cd/TiO2 catalyst exhibits high CH3OH selectivity (70 %). [18] These results also indicate that the reaction rate of products increases with the increasing of reaction temperature.
Table 1.
Summary of elementary reaction steps and activation energies from DFT calculations used for microkinetic modeling. Ea–f and Ea–b are activation energy for forward and backward reaction, respectively. * and # represent TiO2 and Cd sites on Cd4/TiO2 catalyst.
|
|
Elementary reaction step |
Ea–f [eV] |
Ea–b [eV] |
|---|---|---|---|
|
|
H2 dissociation |
|
|
|
R0: |
[H2]+[*]+[#]↔[H2*#] |
0.00 |
0.02 |
|
R1: |
[H2*#]↔[H*]+[H#] |
0.39 |
0.38 |
|
R2: |
[H#]+[*]↔[H*]+[#] |
0.71 |
0.78 |
|
|
Formate pathway 1 (CO2 to HCOOH) |
|
|
|
R3: |
[CO2]+[H*]+[H#]↔[CO2_H*H#] |
0.00 |
0.01 |
|
R4: |
[CO2_H*H#]↔[HCOOH*]+[#] |
0.15 |
0.49 |
|
R5: |
[CO2]+[*]+[H#]↔[CO2*_H#] |
0.00 |
0.14 |
|
R6: |
[CO2*_H#]↔[HCOO*]+[#] |
0.26 |
0.35 |
|
R7: |
[HCOO*]+[H*]↔[HCOOH*]+[*] |
0.22 |
0.34 |
|
R8: |
[HCOO*]+[#]↔[HCOO*#] |
0.00 |
1.04 |
|
R9: |
[HCOO*#]+[H*]↔[HCOOH*#]+[*] |
0.41 |
0.12 |
|
R10: |
[HCOOH*#]↔[HCOOH*]+[#] |
0.63 |
0.00 |
|
|
Formate pathway 2 (HCOOH to CH2O) |
|
|
|
R11: |
[HCOOH*]+[H#]↔[CH2O#]+[OH*] |
0.65 |
0.33 |
|
R12: |
[CH2O#]+[*]↔[CH2O*]+[#] |
0.00 |
0.44 |
|
R13: |
[OH*]+[H*]↔[H2O*]+[*] |
0.18 |
0.63 |
|
R14: |
[H2O]+[*]↔[H2O*] |
0.00 |
0.57 |
|
|
CH3OH formation (CH2O to CH3OH) |
|
|
|
R15: |
[CH2O*]+[H#]↔[CH3O*]+[#] |
0.00 |
1.40 |
|
R16: |
[CH3O*]+[H*]+[#]↔[CH3OH*#]+[*] |
0.48 |
0.61 |
|
R17: |
[CH3OH]+[*]+[#]↔[CH3OH*#] |
0.00 |
0.73 |
|
|
RWGS pathway 1 (CO2 to CO) |
|
|
|
R18: |
[H2O]+[H*]↔[H2O_H*] |
0.00 |
0.26 |
|
R19: |
[CO2]+[H2O_H*]↔[CO2_H2O_H*] |
0.00 |
0.06 |
|
R20: |
[CO2_H2O_H*]+[#]↔[HOCO#]+[HOH*] |
0.42 |
0.37 |
|
R21: |
[H2O]+[*]↔[HOH*] |
0.00 |
0.19 |
|
R22: |
[HOCO#]+[H*]↔[CO#]+[HOH*] |
0.35 |
0.20 |
|
R23: |
[CO]+[#]↔[CO#] |
0.00 |
0.13 |
|
|
RWGS pathway 2 (CO to CH2O) |
|
|
|
R24: |
[CO]+[*]↔[CO*] |
0.00 |
0.03 |
|
R25: |
[CO*]+[H#]↔[HCO*#] |
0.32 |
0.77 |
|
R26: |
[HCO*#]+[H2]↔[HCO*#_H2] |
0.00 |
0.01 |
|
R27: |
[HCO*#_H2]↔[CH2O*]+[H#] |
1.10 |
1.67 |
|
|
CH3O* hydrogenolysis to CH3OH |
|
|
|
R28: |
[CH3O*]+[H2]+[#]↔[CH3OH*]+[H#] |
0.44 |
0.34 |
|
R29: |
[CH3OH]+[*]↔[CH3OH*] |
0.00 |
0.46 |
Figure 8.

Results of the microkinetic modeling for the CO2 hydrogenation on Cd/TiO2 catalyst. (a) is product formation rates as a function of temperature (T=270–310 °C) and the calculated apparent activation energy (Eapp). (b) is surface coverages of major surface intermediates at 270–310 °C. (c) is degree of rate control analysis at 270–310 °C. (d) is the partial pressure dependence of the CH3OH formation rate at 290 °C. The partial pressure of another reactant is fixed as 1 MPa.
Figure 8b shows that the HCOO*# has the highest surface coverage (σ≈0.5), indicating the formation of this intermediate is the resting state of the overall reaction. This results is consistent with the experimental in‐situ IR observation. [18] DRC analysis (Figure 8c) shows that the conversion of HCOOH* to CH2O# (R11), the most difficult reaction step of the formate pathway, is also the rate‐determining step. This result demonstrates that formate pathway dominates over RWGS pathway for the CO2 hydrogenation to CH3OH on the surface of Cd/TiO2 catalyst. In addition, it was found that the H2 dissociation reaction step (R1 in Table 1) has only a minor influence on the overall reaction rate. The effect of H2 and CO2 partial pressure on the reaction rate is also investigated by MKM, as shown in Figure 8d. These results indicate that increasing H2 partial pressure can enhance significantly the methanol production rate, which, in turn, is not affected by the CO2 partial pressure.
Conclusion
In conclusion, the reaction mechanisms of CO2 hydrogenation to methanol by H2 have been investigated in this study by comprehensive DFT and MKM. It is proposed that the interface between the Cd4 cluster and the support of TiO2 plays a key role for H2 dissociation as well as preactivation of CO2. H2 dissociation and CO2 activation are energetically more favorable at the Cd‐TiO2 interface than that at bare TiO2 surface and Cd cluster. Both CO2 hydrogenation reactions to formate and CO are remarkably facilitated by the synergy between H− on Cd and H+ on TiO2 surface (Figure 3, formate pathway; Figure 4, RWGS pathway). In contrast, CO2 conversion to CH3OH on bare TiO2 is very difficult compared to the Cd/TiO2 interface. Cd‐TiO2 interface is crucial for stabilizing various reaction intermediates and promoting the rate‐determining step of formaldehyde formation identified by DFT and MKM. All these mechanism results indicates that the multifunctionality of Cd/TiO2 interface including Lewis acids of metals and Lewis base of surface oxygen is of great importance accounting for the outstanding catalytic activity of Cd/TiO2 material. Water molecules produced from the reaction or present in the reaction system can dramatically facilitate the most difficult reaction steps of RWGS reaction. However, formate is identified to be the relevant intermediate for CO2 hydrogenation to methanol, with formaldehyde formation being the rate‐limiting reaction step. Our results demonstrate that Cd/TiO2 can be a promising candidate for valorization of CO2 to produce methanol and the multifunctionality of the metal‐support interface is a crucial aspect for rational design of CO2 hydrogenation catalyst.
Experimental Section
All DFT calculations have been performed using the Vienna Ab Initio Simulation Package (VASP). [19] The generalized gradient approximation (GGA) with PBE exchange and correlation functional was used to account for the exchange‐correlation energy.[ 19b , 20 ] The kinetic energy cutoff of the plane wave basis set was set to 400 eV. The threshold for energy convergence for each iteration was set to 10−5 eV. Geometries were assumed to be converged when forces on each atom were less than 0.05 eV/Å. Gaussian smearing of the population of partial occupancies with a width of 0.10 eV was used during iterative diagonalization of the Kohn‐Sham Hamiltonian. The bulky TiO2 unit cell in the phase of anatase was firstly fully optimized. The optimized lattice vectors of a=3.799 Å b=3.799 Å c=9.716 Å have a good agreement with the experiment parameters. [21] For Cd4/TiO2 model, 1x3 and 2×4 supercells of anatase TiO2 (101) surface with a vacuum space of 15 Å were built for investigation of the reaction mechanism of H2 dissociation and CO2 hydrogenation, respectively. These slab models contain six titanium layers with the bottom three layers were fixed while the rest was allowed to relax during the geometry optimization. The lattice parameters were fixed throughout the surface calculations. The nudged‐elastic band method with the improved tangent estimate (CI‐NEB) was used to determine the minimum energy path and to locate the transition state structure for each elementary reaction step. [22] The maximum energy geometry along the reaction path generated by the NEB method was further optimized using a quasi‐Newton algorithm. In this procedure, only the extra‐framework atoms were relaxed. Vibrational frequencies were calculated by determining the second derivatives of the Hessian matrix using the density functional perturbation theory as implemented in VASP 5.3.5. Transition state was confirmed by showing a single imaginary frequency corresponding to each reaction coordinate. Bader charge analysis was visualized by VESTA software. [23]
Mean‐field microkinetic modeling (MKM) is applied based on the DFT calculations of all elementary reaction steps. The rate constant of the adsorption reaction is calculated by the Hertz‐Knudsen equation [Eq. 1]: [24]
| (1) |
where is the rate constant of adsorption reaction, is the partial pressure of the adsorbate in the gas phase, is the surface area of the adsorption site, is the mass of adsorbate, is the Boltzmann constant, is the temperature, and is the sticking coefficient.
The desorption reaction is calculated by Equation 2:
| (2) |
whare is the rate constant of desorption reaction, is the Plank's constant, is the symmetry number of a molecule, is the rotational temperature of a molecule, and is the desorption energy.
For the surface reaction, it is calculated by the Eyring equation [Eq. 3]: [25]
| (3) |
where is the rate constant of surface reaction, is the activation energy, and R is the gas constant.
The approach to MKM has been presented in detail elsewhere. [26] The differential equations are constructed using the rate constants and the set of elementary reaction steps. For each of the M components in the kinetic network, a single differential equation is in the form [Eq. 4]:
| (4) |
where is the rate reaction, is the elementary reaction constant, is the stoichiometric coefficient of component in elementary reaction step and is the concentration of component on the catalytic surface.
The degree of rate control (DRC) was performed to investigate the elementary steps that contribute to the rate control over the overall reaction ref: [21–23[. [27] For elementary step , the degree of rate control is defined as [Eq. 5]
| (5) |
where and are the rate constants, the equilibrium constant for step and the reaction rate, respectively. All MKM results are simulated by a homemade script.
Conflict of interest
The authors declare no conflict of interest.
1.
Supporting information
As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.
Supporting Information
Acknowledgements
Authors acknowledge financial support from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 725686) J. M. gratefully acknowledges the Royal Thai Government Scholarships for the financial support. The use of supercomputer facilities was sponsored by NWO Domain Science. The authors thank the Netherlands Organization for Scientific Research (NWO) for the access to SURFsara computational facilities and Dr. Dapeng Sun from Supermicro for valuable discussions about the MKM modeling.
G. Li, J. Meeprasert, J. Wang, C. Li, E. A. Pidko, ChemCatChem 2022, 14, e202101646.
Contributor Information
Dr. Guanna Li, Email: guanna.li@wur.nl, https://www.wur.nl/en/Research‐Results/Chair‐groups/Agrotechnology‐and‐Food‐Sciences/Laboratory‐of‐Organic‐Chemistry/Research/Theoretical‐Surface‐Chemistry.htm.
Prof. Evgeny A. Pidko, Email: E.A.Pidko@tudelft.nl, https://www.tudelft.nl/tnw/over‐faculteit/afdelingen/chemical‐engineering/principal‐scientists/evgeny‐pidko/evgeny‐pidko.
Data Availability Statement
The data that support the findings of this study are available in the supplementary material of this article.
References
- 1.
- 1a. Wang W., Wang S., Ma X., Gong J., Chem. Soc. Rev. 2011, 40, 3703–3727; [DOI] [PubMed] [Google Scholar]
- 1b. Alvarez A., Bansode A., Urakawa A., Bavykina A. V., Wezendonk T. A., Makkee M., Gascon J., Kapteijn F., Chem. Rev. 2017, 117, 9804–9838. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Pérez-Fortes M., Schöneberger J. C., Boulamanti A., Tzimas E., Appl. Energy 2016, 161, 718–732. [Google Scholar]
- 3.
- 3a. Li W., Wang H., Jiang X., Zhu J., Liu Z., Guo X., Song C., RSC Adv. 2018, 8, 7651–7669; [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3b. Ye R.-P., Jie Ding W. G., Argyle M. D., Zhong Q., Wang Y., Russell C. K., Xu Z., Russell A. G., Li Q., Fan M., Yao Y.-G., Nat. Commun. 2019, 10, 5698. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Ghasemzadeh K., Sadati Tilebon S. M., Nasirinezhad M., Basile A., in Methanol, 2018, pp. 613–632. [Google Scholar]
- 5. Albo J., Alvarez-Guerra M., Castaño P., Irabien A., Green Chem. 2015, 17, 2304–2324. [Google Scholar]
- 6.
- 6a. Yang W., Dastafkan K., Jia C., Zhao C., Advanced Materials Technologies 2018, 3; [Google Scholar]
- 6b. Qiao J., Liu Y., Hong F., Zhang J., Chem. Soc. Rev. 2014, 43, 631–675; [DOI] [PubMed] [Google Scholar]
- 6c. Khezri B., Fisher A. C., Pumera M., J. Mater. Chem. A 2017, 5, 8230–8246; [Google Scholar]
- 6d. Sun Z., Ma T., Tao H., Fan Q., Han B., Chem 2017, 3, 560–587. [Google Scholar]
- 7.
- 7a. Behrens M., Studt F., Kasatkin I., Kühl S., Hävecker M., Abild-Pedersen F., Zander S., Girgsdies F., Kurr P., Kniep B.-L., Tovar M., Fischer R. W., Nørskov J. K., Schlögl R., Science 2012, 336, 893–897; [DOI] [PubMed] [Google Scholar]
- 7b. Kattel S., Ramírez P. J., Chen J. G., Rodriguez J. A., Liu P., Science 2017, 355, 1296–1299. [DOI] [PubMed] [Google Scholar]
- 8.
- 8a. Wu J., Saito M., Takeuchi M., Watanabe T., Appl. Catal. A 2001, 218, 235–240; [Google Scholar]
- 8b. Hu X., Qin W., Guan Q., Li W., ChemCatChem 2018, 10, 4438–4449. [Google Scholar]
- 9.
- 9a. Larmier K., Liao W. C., Tada S., Lam E., Verel R., Bansode A., Urakawa A., Comas-Vives A., Coperet C., Angew. Chem. Int. Ed. Engl. 2017, 56, 2318–2323; [DOI] [PubMed] [Google Scholar]
- 9b. Kattel S., Yan B., Yang Y., Chen J. G., Liu P., J. Am. Chem. Soc. 2016, 138, 12440–12450. [DOI] [PubMed] [Google Scholar]
- 10. Graciani J., Mudiyanselage K., Xu F., Baber A. E., Evans J., Senanayake S. D., Stacchiola D. J., Hrbek P. L., Sanz J. F., Rodriguez J. A., Science 2014, 345, 546–550. [DOI] [PubMed] [Google Scholar]
- 11.
- 11a. Vourros A., Garagounis I., Kyriakou V., Carabineiro S. A. C., Maldonado-Hódar F. J., Marnellos G. E., Konsolakis M., J. CO2 Util. 2017, 19, 247–256; [Google Scholar]
- 11b. Hartadi Y., Widmann D., Behm R. J., J. Catal. 2016, 333, 238–250; [Google Scholar]
- 11c. Rodriguez J. A., Evans J., Feria L., Vidal A. B., Liu P., Nakamura K., Illas F., J. Catal. 2013, 307, 162–169. [Google Scholar]
- 12.
- 12a. Malik A. S., Zaman S. F., Al-Zahrani A. A., Daous M. A., Driss H., Petrov L. A., Appl. Catal. A 2018, 560, 42–53; [Google Scholar]
- 12b. Snider J. L., Streibel V., Hubert M. A., Choksi T. S., Valle E., Upham D. C., Schumann J., Duyar M. S., Gallo A., Abild-Pedersen F., Jaramillo T. F., ACS Catal. 2019, 9, 3399–3412; [Google Scholar]
- 12c. Wu D., Deng K., Hu B., Lu Q., Liu G., Hong X., ChemCatChem 2019, 11, 1598–1601; [Google Scholar]
- 12d. Jiang F., Wang S., Liu B., Liu J., Wang L., Xiao Y., Xu Y., Liu X., ACS Catal. 2020, 10, 11493–11509. [Google Scholar]
- 13. Ting K. W., Toyao T., Siddiki S. M. A. H., Shimizu K.-i., ACS Catal. 2019, 9, 3685–3693. [Google Scholar]
- 14. Wang J., Li G., Li Z., Tang C., Feng Z., An H., Liu H., Liu T., Li C., Sci. Adv. 2017, 3, e1701290. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.
- 15a. Yang C., Pei C., Luo R., Liu S., Wang Y., Wang Z., Zhao Z.-J., Gong J., J. Am. Chem. Soc. 2020, 142, 19523–19531; [DOI] [PubMed] [Google Scholar]
- 15b. Dang S., Qin B., Yang Y., Wang H., Cai J., Han Y., Li S., Gao P., Sun Y., Sci. Adv. 2020, 6, eaaz2060. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.
- 16a. Li Y., Chan S. H., Sun Q., Nanoscale 2015, 7, 8663–8683; [DOI] [PubMed] [Google Scholar]
- 16b. Kattel S., Liu P., Chen J. G., J. Am. Chem. Soc. 2017, 139, 9739–9754. [DOI] [PubMed] [Google Scholar]
- 17.
- 17a. Dou M., Zhang M., Chen Y., Yu Y., Surf. Sci. 2018, 672–673, 7–12; [Google Scholar]
- 17b. Wang J., Li G., Li Z., Tang C., Feng Z., An H., Liu H., Liu T., Li C., Sci. Adv. 2018, 3, e1701290; [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17c. Ye J., Liu C., Mei D., Ge Q., ACS Catal. 2013, 3, 1296–1306; [Google Scholar]
- 17d. Liu C., Yang B., Tyo E., Seifert S., DeBartolo J., von Issendorff B., Zapol P., Vajda S., Curtiss L. A., J. Am. Chem. Soc. 2015, 137, 8676–8679. [DOI] [PubMed] [Google Scholar]
- 18. Wang J., Meeprasert J., Han Z., Wang H., Feng Z., Tang C., Sha F., Tang S., Li G., Pidko C. L. E. A., Chin. J. Catal. 2021, 42. [Google Scholar]
- 19.
- 19a. Kresse G., Furthmüller J., Comput. Mater. Sci. 1996, 6, 15–50; [Google Scholar]
- 19b. Kresse G., Furthmüller J., Phys. Rev. B 1996, 54, 11169–11186. [DOI] [PubMed] [Google Scholar]
- 20. Perdew J. P., Burke K., Ernzerhof M., Phys. Rev. Lett. 1996, 77, 3865–3868. [DOI] [PubMed] [Google Scholar]
- 21. Diebold U., Surf. Sci. Rep. 2003, 48, 53–229. [Google Scholar]
- 22. Henkelman G., Uberuaga B. P., Jónsson H., J. Chem. Phys. 2000, 113, 9901–9904. [Google Scholar]
- 23. Momma K., Izumi F., J. Appl. Crystallogr. 2011, 44, 1272–1276. [Google Scholar]
- 24. Nitoń P., Żywociński A., Fiałkowskia M., Hołyst R., Nanoscale 2013, 5, 9732–9738. [DOI] [PubMed] [Google Scholar]
- 25. Eyring H., J. Chem. Phys. 1935, 3, 107. [Google Scholar]
- 26.
- 26a. Filot I. A. W., v. Santen R. A., Hensen E. J. M., Angew. Chem. Int. Ed. 2014, 53, 12746–12750; [DOI] [PubMed] [Google Scholar]; Angew. Chem. 2014, 126, 12960–12964; [Google Scholar]
- 26b. Filot I. A. W., Broos R. J. P., v. Rijn J. P. M., v. Heugten G. J. H. A., v. Santen R. A., Hensen E. J. M., ACS Catal. 2015, 5, 5453–5467; [Google Scholar]
- 26c. Liu J.-X., Su Y., Filot I. A. W., Hensen E. J. M., J. Am. Chem. Soc. 2018, 140, 4580–4587. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.
- 27a. Campbell C. T., Top. Catal. 1994, 1, 353–366 ; [Google Scholar]
- 27b. Campbell C. T., J. Catal. 2001, 204, 520–524; [Google Scholar]
- 27c. Stegelmann C., Andreasen A., Campbell C. T., J. Am. Chem. Soc. 2009, 131, 8077–8082. [DOI] [PubMed] [Google Scholar]
- 28. Zhao J., Phys. Rev. A 2001, 64, 043204. [Google Scholar]
- 29.
- 29a. Boronat M., Illas F., Corma A., J. Phys. Chem. A 2009, 113, 3750–3757; [DOI] [PubMed] [Google Scholar]
- 29b. Wan W., Nie X., Janik M. J., Song C., Guo X., J. Phys. Chem. C 2018, 122, 17895–17916; [Google Scholar]
- 29c. Sun K., Kohyama M., Tanaka S., Takeda S., J. Phys. Chem. C 2014, 118, 1611–1617. [Google Scholar]
- 30. Hu G., Wu Z., Jiang D.-e., J. Phys. Chem. C 2018, 122, 20323–20328. [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.
Supporting Information
Data Availability Statement
The data that support the findings of this study are available in the supplementary material of this article.





