Hydrogen Production via Efficient Formic Acid Decomposition

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Hydrogen Production via Efficient Formic Acid Decomposition: Engineering Surface Structure of Pd-based Alloy Catalysts by Design Yang Yang, Haoxiang Xu, Dapeng Cao, Xiao Cheng Zeng, and Daojian Cheng ACS Catal., Just Accepted Manuscript • DOI: 10.1021/acscatal.8b03485 • Publication Date (Web): 07 Dec 2018 Downloaded from http://pubs.acs.org on December 7, 2018

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Hydrogen Production via Efficient Formic Acid Decomposition: Engineering Surface Structure of Pd-based Alloy Catalysts by Design Yang Yang1, Haoxiang Xu1, Dapeng Cao1,2*, Xiao Cheng Zeng3,1*, and Daojian Cheng1,2*

1Beijing

Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, People’s Republic of China

2State

Key Laboratory of Organic-Inorganic Composites, Beijing Key Laboratory of Energy Environmental

Catalysis, Beijing University of Chemical Technology, Beijing 100029, People’s Republic of China 3Department

of Chemistry, University of Nebraska, Lincoln, NE 68588, USA

ABSTRACT

Improving the activity and selectivity of Pd-based alloy catalysts for hydrogen production from formic acid decomposition is still an ongoing challenge. We have performed a comprehensive study, on the basis of available experimental data, of the relationship between surface structure of Pd-based alloy catalysts and their catalytic activities for formic acid decomposition by using density functional theory and Sabatier analysis. Importantly, the average Bader charge of Pd atoms on the surface and the average bond length of the surface atoms are identified as two quantitative descriptors to analyze the effect of charge redistribution and surface tension on reactivity of the Pd-based alloy catalysts. Based on the two descriptors, we propose a strategy to rationally engineer the surface structure of Pd-based alloy catalysts by introducing suitable dopants and by devising optimal atomic arrangements. The strategy allows us to identify the potential candidates - PdAu and PdAg alloy with specific atomic arrangement. We find that these alloy catalysts are superior to the state-of-the-art systems tested in previous experiments. Our strategy may be generalized for designing heterogeneous alloy catalysts beyond formic acid decomposition.

Keywords: Hydrogen Production; Pd-based Alloy Catalysts; Formic Acid Decomposition; Surface Structure Engineering; Density functional theory calculation

____________________________ 

To whom correspondence should be addressed: E-mail: [email protected] or [email protected] or [email protected] 1

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1. INTRODUCTION Hydrogen is a well-known energy carrier often used in fuel cells for generating electricity[1-3]. The storage, distribution and release of hydrogen remain to be a challenging issue for the widespread use of hydrogen in transportation sector. Recently, formic acid (HCOOH) has been proposed as a potential hydrogen storage medium capable of releasing H2 under mild conditions via catalytic decomposition[4-7]. For the formic acid to be a viable hydrogen storage material, special catalysts must be developed such that it can actively and selectively facilitate the formic acid decomposition via the dehydrogenation pathway (HCOOH → H2 + CO2), rather than the dehydration (HCOOH → H2O + CO). To produce virtually CO-free hydrogen, the selectivity toward the dehydrogenation reaction is crucial because most Pt-group metals in the fuel cell tend to be poisoned by CO if the dehydration pathway is selected. Although homogeneous catalysts can achieve selective dehydrogenation of HCOOH at ambient or near-ambient temperature, the separation issues involving organic solvents hamper their practical applications[8-10]. Pd is one of the most active heterogeneous catalysts for the HCOOH decomposition, which has been extensively studied for the H2 production via the HCOOH decomposition[11-13]. Over the past decade, Pd-based alloy catalysts have received increasing attention as the most promising catalyst for hydrogen production via selective formic acid decomposition, which include Pd-Ag[14-16], Pd-Au[17-19], Pd-Cu[20], Pd-Pt[21] and Pd-Ni[22] catalysts. These Pd-based alloys possess significantly higher catalytic activity and stronger tolerance toward the CO poisoning, compared to monometallic Pd catalysts. In addition to finding optimal alloying elements for Pd-based catalysts, the reactivity and selectivity for the 2


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HCOOH decomposition on Pd-based catalysts can be modified by changing atomic arrangement of surface Pd and doping atoms[23-28]. For example, supported Pd-Au catalysts with core-shell structures were tested for selective HCOOH decomposition, and a higher hydrogen yield was observed than that with pure Pd catalyst[29]. Furthermore, the Pd-based catalysts can have different particle shapes, such as icosahedral, tetrahedral, octahedral, cuboctahedral, and decahedral, which usually exhibit the (111), (100), and (110) surfaces, together with edges and steps. The particle shape can be controlled by careful selection of the preparation techniques, and usually, the (111) surface is the most abundant surface. Since the experimentally tested Pd-based alloy catalysts most contain noble-metal elements, the optimization of surface structure of Pd-based alloy to achieve the maximum utilization of noble metal elements is timely and important task. Today, trial-and-error approaches are still a common practice to optimize the surface structure of Pd-based alloy catalysts in the laboratory due to the lack of theoretical guideline. In recent years, adsorption strength of reactants is regarded as a key catalytic reactivity descriptor based on the combination of the Sabatier analysis and density functional theory (DFT) calculations[30-32], which has been tested successfully for many reactions, such as oxygen reduction reaction (ORR)[33-35], CO2 reduction[36, 37], hydrogen evolution reaction (HER)[38-41], direct synthesis of H2O2[42, 43], and formic acid decomposition[44, 45] on metal catalysts. However, adsorption-reactivity relationship alone reflects too few chemical properties of various surface structures of Pd-based alloy catalysts to provide convincing guideline for seeking promising Pd-based alloy catalysts. To rationally engineer the surface structure of Pd-based alloy catalysts by design, it is crucial to identify intrinsic 3


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characteristics of the surface structure, especially the synergistic effect of alloying elements, as well as the atomic arrangement that dominates the catalytic activity and selectivity. In this work, we systematically investigate the activity and selectivity of Pd-based alloy catalysts for HCOOH decomposition to produce hydrogen, by combining available experimental data, Sabatier analysis, and DFT calculations. Pd-M bimetallic catalysts with seven alloying elements (M = Ag, Au, Cu, Ni, Ir, Pt and Rh) and five atomic arrangements are considered. Two descriptors are identified to quantitatively analyze the effect of surface tension and charge redistribution on the reactivity of Pd-based alloy catalysts. Based on the descriptors, we propose a strategy to rationally engineer the surface structure of Pd-based alloy catalyst by introducing suitable dopants and devising optimal atomic arrangement. As a result, PdAu and PdAg alloys with specific atomic arrangement are predicted to possess excellent activity and selectivity for the formic acid decomposition. Our work shows the importance of rationally engineering the surface structure of Pd-based catalysts, which may be extended for applications in designing other heterogeneous catalysts beyond hydrogen production from selective HCOOH decomposition.

2. CALCULATION DETAILS Our calculations were performed in the framework of DFT, implemented in the plane-wave based Vienna ab initio Simulation Package (VASP)[46, 47]. The interaction between ion and core electrons was described by the projector augmented wave (PAW) method[48], and plane waves with an energy cutoff of 400 eV were used to expand the Kohn-Sham

(KS)

wave functions.

Generalized

gradient

4


approximation of

the

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Perdew-Burke-Ernzernhof (PBE) functional was taken to describe the electronic exchange and correlation[49]. The optimized bulk lattice constants (experimental value[50] in parentheses) are Ag 4.16Å (4.09 Å), Au 4.17Å (4.08 Å), Cu 3.63Å (3.52Å), Ir 3.87Å (3.83 Å), Ni 3.52Å (3.52 Å), Pd 3.96Å (3.89Å), Pt 3.98Å (3.92Å), Rh 3.84Å (3.80Å). The bimetallic surfaces were modeled by using a slab with (111) crystal surface and five atomic layers and a p(3 × 3) supercell with nine atoms at each layer constructed by fcc lattice. A 12 Å vacuum in the z direction was used to separate the slabs. In the calculations, full optimization of the cell parameters for the bulk was carried out by using the 9 × 9 × 9 k points in the Monkhorst-Pack grids and the integrals in the reciprocal space were evaluated through the summations over 7 × 7 × 1 k points in the Monkhorst-Pack grids[51, 52]. The positions of all atoms except those in the two bottommost layers were fully relaxed according to the calculated atomic forces (less than 0.05 eV Å-1). Spin polarization was included for the correct description of magnetic properties. Zero-point energy (ZPE) corrections for HCOOH(g), CO2(g), H2(g), HCOOH*, HCO*O*, COOH*, H*, CO*, and OH* were calculated by using harmonic approximation for vibrational frequencies. The ZPE-corrected overall gas-phase reaction energy for HCOOH → CO2 + H2 is -0.06 eV, very close to the tabulated value of -0.15 eV[50]. Bader charge analysis was performed for the alloy surfaces[53, 54]. The reaction pathways for the HCOOH decomposition on alloy surfaces were obtained using the Climbing Image Nudged Elastic Band (CI-NEB) technique [55-57]. Transition states were confirmed through vibrational frequency calculations.

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3. RESULTS AND DISCUSSION 3.1 Bimetallic models For bimetallic catalysts, the effect of atomic arrangement of catalysts on catalytic performance is as important as choosing suitable dopants. In this work, for the core-shell structures, Pd with one, two and three atomic layers are considered. For the uniform alloy Pd-M and core-shell structured Pd@Pd-M (M = Ag, Au, Cu, Ni, Ir, Pt and Rh), the atomic ratios of Pd to M considered are 1:1, 1:3 and 3:1, respectively. To obtain the surface models, we optimize the unit cells of Pd, M, and Pd-M alloy. Then the bimetallic surfaces are modeled by using a slab with (111) crystal surface and with five atomic layers. After adjusting atomic arrangements, we optimize these structures once again. Due to lattice mismatch, the layer with atomic arrangement adjustment is stretched or compressed, and this treatment illustrates that the surface tension exists in our models. Thus, five atomic arrangements are considered, including overlayer structure (MPd1L, Figure 1 (c, d); MPd2L Figure 1 (e, f); MPd3L Figure 1 (g, h)), core-shell structured Pd@M (Figure 2 (a)), core-shell structured Pd@Pd-M (Figure 2 (b)), uniform alloy (Figure 2 (c)) and subsurface structure (Figure 2 (d)). For overlayer structures, the models are original from the previous experimental work[17], including the Au and Pd pure surfaces (Au5L and Pd5L) and overlayer structures (AuPd1L, AuPd2L and AuPd3L), as shown in Figure 1 (see Section 1 of Supporting Information for details). All the models are shown in Figure S1. The mixing energies are calculated to explore the relative stability of our models, as listed in Table S2. The mixing energies are calculated by Emixing  ( Etotal  mEPdbulk  nEM bulk ) / (m  n) 6


(1)

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where Etotal is the total energy of our models, m and n are the number of Pd and M atoms on our models and EPdbulk and EM bulk are the energies of per Pd and doped transition metal atom in their corresponding metal bulk structure, respectively. The mixing energies of our alloy models are negative, indicating the models are of high relative stability. In this work, the original models, including Pt5L, AuPd1L, AuPd2L, Pd2L@Ag, Pd3L@Ag, Pd3Au1, Pd1L@Pd3Ag1, PtPd2L and PtPd3L are chosen as example to design efficient catalyst for HCOOH decomposition.

3.2 Reaction Mechanism and Sabatier Analysis Reaction Pathways. A schematic diagram of the reaction network considered for heterogeneous formic acid decomposition is shown in Figure 3. The pathways of HCOOH decomposition start from either O-H or C-H bond scission. Because of the subsequent decomposition process, three feasible HCOOH decomposition pathways (Path a, b, c, see Section 2 of Supporting Information for details) are considered. Activating the C-O bond of HCOOH to form formyl (CHO*) species on the surface was excluded from the mechanic study because it is energetically unfavorable compared to activating either O-H or C-H bond of HCOOH[58-60]. To understand the reaction pathways of HCOOH decomposition, the most stable adsorption configurations of the main reaction intermediates (HCOOH*, COOH*, HCO*O*, CO*, OH*, H*) are calculated. Determination of the adsorption energies of reaction intermediates can be found in the Section 3 of Supporting Information for details, and the results are given in Tables S3-S5. The activity energy ( Ea ) and reaction energy (ΔE) of each elementary steps are calculated by 7


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Ea  ETS  ERS

(2)

E  EFS  EIS

(3)

where ERS , ETS , EFS and EIS are the total energies of the reactant state (RS), transition state (TS), initial state (IS) and final state (FS), respectively. Then, the activation energy barriers (Ea) and reaction energies (ΔE) of all elementary steps (see the Section 4 of Supporting Information for details) are shown in Table S7. For Pd5L, the rate limiting steps are HCO*O* dissociation on Path a, H2O formation on Path b, and COOH* dissociation on Path c, with activation energy of 1.23, 0.58, and 1.46 eV, respectively, as shown in Figure S3. The least activation energy of 0.58 eV shows that the HCOOH decomposition on Pd5L prefers Path b towards CO and H2O formation, that is, the dehydration pathway. For AuPd1L, the dehydrogenation pathway with Path c is the most favorable because it has the least activation energy for the rate-determining step (H2 formation, 0.50 eV) compared with other two pathways. Moreover, the activation energy for the rate-determining step in the dehydrogenation pathway (0.50 eV) is much smaller than that in the dehydration pathway (1.92 eV), indicating that the catalyst shows better selectivity towards H2 generation from the HCOOH decomposition, as shown in Figure S4. For AuPd2L in Figure S5, it is clear that the reaction occurs preferably by the dehydrogenation pathway. The activation energy of 0.50 eV is slightly lower than that of the dehydration pathway (0.71 eV). However, the smaller difference of the activation energy on AuPd2L than AuPd1L brings out the competition of two pathways, due to the increase of Pd atoms on the surface. The results indicate that the dehydrogenation pathway 8


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occurs more easily on Au-Pd bimetallic surfaces, while the dehydration pathway more easily on Pd surfaces, which is in good agreement with the experiment results[17]. For Pd2L@Ag, Pd3L@Ag and PtPd3L, the activation energy of rate-determining step in the dehydrogenation pathway (0.58, 0.66 and 0.45 eV) is much smaller than that in the dehydration pathway (1.62, 1.45 and 1.14 eV). The lower activation energy illustrate H2 is preferable product on these surface during the process, as shown in Figures S6-S8. For Pd3Au1, Pd1L@Pd3Ag1 and PtPd2L, the activation energy of rate-determining step in the dehydrogenation pathway is similar as that in the dehydration pathway, bringing about the competition of two pathways, as shown in Figures S9-S11. Microkinetic Model. To verify the accuracy of our results, the kinetics of different reaction pathways for formic acid decomposition are obtained from the self-consistent steady state solution to a microkinetic model built to include all reaction steps, as shown in Figure 3. The reaction rates of these steps are described on the basis of the mean field approximation, and harmonic transition state theory[61, 62] (see the Section 5 of Supporting Information for details). According to the calculation method above, the HCOOH decomposition rate and turnover frequency (TOF) for H2 production are calculated[45, 63], as listed in Table 1. The HCOOH decomposition rate is relatively lower than the measured rates for both AuPd1L and AuPd2L. For both AuPd1L and AuPd2L, the TOF for H2 production in experiment is close to the results in our calculations, which confirms the accuracy of our calculations. Sabatier Analysis We extended the study to other Pd-based alloy surfaces to establish trends from the calculated activation energies along the whole reaction pathway and from 9


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the adsorption energy of CO and OH (ΔECO and ΔEOH), as both CO and OH are involved in the reaction mechanism[64, 65]. Figure 4 (a,b) shows that the scaling relations of relative energies to the absorbates or transitions states in each elementary steps along the whole reaction pathway with ΔECO and ΔEOH (See Figures S12 and S13 for details). The relative adsorption energies show a good linear relationship with ΔECO and ΔEOH (corresponding scaling relation coefficients are listed in Tables S8 and S9). The x and y are introduced for numerical modifications in order to make existing data exhibiting the best possible linear relation. A slight deviation for some adsorbates is considered to be the result of geometric effect, which is consistent with the previous research[45]. Sabatier analysis provides upper bounds for reaction rates and can successfully describe trends in reactivity, in terms of simple descriptors, e.g., adsorption energies of certain intermediates. In this work, a multidimensional activity volcano-shaped relation is obtained in which activation barriers of all elementary steps are mapped as a function of ΔECO and ΔEOH. Figure 5 (a,b) shows the Sabatier analysis of HCOOH decomposition via dehydrogenation and via dehydration, respectively. As shown in Figure 5 (a), Sabatier activity volcano is divided into four regions (by blue line), indicating that there are four differently predicted rate-controlling steps during this process. When the adsorption energy (absolute value) of CO is relatively low and OH is relatively high, HCOOH* dehydrogenation to COOH* and H* is the rate-controlling step, according to the lower right corner of Figure 5 (a). Hydrogen formation as the rate-controlling step is located in the middle section, and the rate-controlling steps, including HCO*O* and COOH* dehydrogenation are located at the rest of map. Hydrogen formation is the rate-controlling 10


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step for AuPd1L, Pd2L@Ag, Pd3L@Ag, PtPd2L, PtPd3L and Pd1L@Pd3Ag1, whereas HCO*O* dehydrogenation for Pd5L and AuPd2L and COOH* dehydrogenation for Pd3Au1. AuPd2L, PtPd3L, Pd2L@Ag and Pd3Au1 are located at the top of volcano, which shows very high activities of H2 production. In comparison, other surfaces lie on hillside of the volcano and show lower activities than the structures above. Likewise, as shown in Figure 5 (b), Sabatier activity volcano is divided into two regions, corresponding to two differently predicted rate-controlling steps, i.e., H2O formation and COOH* decomposition to CO* and OH*. When the adsorption energy of OH is relatively high and that of CO is relatively low, COOH* decomposition is the rate-controlling step, and conversely, the H2O formation is the rate-controlling step. It is obvious that CO production on AuPd1L occurs more difficult than that on others. However, the activation energy of the entire alloy models during dehydration process is relatively high. CO selectivity is defined as the activation energy of the rate-determining steps for H2O + CO production minus that for H2 + CO2 production, and the boundary means that the difference is zero. Catalysts with CO production preference are delineated by shaded area in Figure 5 (c), otherwise CO2 and H2. CO2 and H2 on the entire alloy models and CO and H2O on Pd5L are preferably produced, in line with the experimental results. In addition, the dot of Pd3Au1 is located closer to the shaded area than others, indicating relatively low stability.

3.3 Rational Screening Models Sabatier analysis is performed with the help of ΔECO and ΔEOH. However, the 11


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associated factors, which affect ΔECO and ΔEOH, are not clear. To explore the influence factors, more Pd-based catalysts with other alloying elements (MPd1L, M = Ag, Cu, Ir, Ni, Pt, Rh) are considered, all having the same atomic arrangement of AuPd1L. It is known that adsorption energy is affected by both electronic and geometric effects of catalyst surfaces[66, 67]. We therefore introduce two descriptors to quantitatively analyze the effect of charge redistribution (electronic effect) and surface tension (geometric effect) of the Pd-based alloy catalysts on the adsorption energy of CO and OH, respectively. The descriptor for the geometric effect is taken to be the ratio (x) of the average bond length of alloy surface to that of Pd5L surface, while the descriptor for the electronic effect is taken to be the ratio (y) of the average Bader charge of Pd atoms on the surface to that of Pd5L surface, as listed in Table S10. Following the fitting by Wheat Marquardt method and general global optimization method, Equation 4 is obtained and the parameters are shown in Table S11. ECO / OH  ( p1  p 2* x  p3 / y  p 4 / y 2  p5 / y 3 ) *1eV

(4)

The plot of adsorption energy of CO and OH versus p 2* x  p3 / y  p 4 / y 2  p5 / y 3 is shown in Figure 6, and the error of adsorption energy with 0.2 eV is considered. To verify the reliability of Equation 4, the adsorption energies of OH and CO on more structures are added, especially for y with a large range, as listed in Table S12. Comparing the adsorption energies at the favorite site on these surfaces with the predicted adsorption energies of CO and OH, the absolute value of the difference is less than 0.1 eV, as listed in Table S13. Therefore, Equation 4 we obtained is reasonable for the prediction of the adsorption energies of CO and OH on Pd-based alloy surfaces. To verify the accuracy of 12


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the our screening models, the adsorption energy of CO and OH on the AuPd3L surface is obtained by the Equation 4, as listed in Table S10 (italic). The Sabatier analysis of AuPd3L based on the predicted ΔECO and ΔEOH by Equation 4 is shown in Figure S14. The rate-controlling step is HCO*O* dehydrogenation. CO2 and H2 are likely produced with relatively high activity, whereas the activation barrier of CO and H2O production is also not very high, meaning that HCOOH decomposition via dehydration and dehydrogenation are comparable, consistent with the experimental result[17]. Based on the scaling relationship shown in Figure 4 and microkinetic model, the HCOOH decomposition rate and TOF for H2 production on AuPd3L are calculated in Table 1. The results are reasonable in view of the approximations made for the whole analysis, confirming the accuracy of our models. Thus, Pd-based alloy catalysts with appropriate charge distribution (average Bader charge of Pd atoms on the surface) and suitable surface tension (average bond length of surface atoms) show relatively high activity and selectivity, an insightful guide to the design of Pd-based alloy catalyst through rationally engineering surface structure.

3.4 Prediction of Pd-based Nanocatalysts Pd alloying with secondary metals, e.g., Ag, Au, Cu, Ir, Ni, Pt, and Rh, as Pd-based catalysts are analyzed by two descriptors above. The ratio of average bond length (x), the ratio of average Bader charge of Pd atoms (y), the adsorption energy of CO and OH, the barriers of rate-controlling step (Ear (CO2+H2) and Ear (CO+H2O)), and the difference of barriers (Ear-diff) on the surface of Pd-Au, Pd-Ag, Pd-Cu, Pd-Ir, Pd-Ni, Pd-Pt and Pd-Rh alloy catalysts are listed in Tables S14-S20, respectively. And the multidimensional activity volcano-shaped relations are shown in Figures S14-S20, respectively. 13


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For the core-shell structure of Pd@M, the average bond length of surface atoms changes with M, rather than with the number of Pd atomic layers. For the core-shell structure of Pd@Pd-M, the average bond length of surface atoms keeps unchanged for different Pd over layers, atomic ratio and elements. For subsurface, the average bond length of surface atoms is nearly identical as Pd(111). This behavior may be caused by the difference of the bottom layers of models. Nonetheless, the average Bader charge of Pd atoms on the surface varies substantially, bringing about the different ΔECO and ΔEOH based on Equation 4. For alloy models, the activity energy of HCOOH dehydrogenation is 0.483 ~ 0.756 eV, much lower than that of HCOOH dehydration, indicating the models with preferable activity and selectivity, except Pd1L@Pt, AuPd2L and AuPd3L. For the core-shell models, in general, the progressively lowering selectivity with the increase of Pd atomic layers stems from the decreased charge transfer between M and Pd atoms. As shown in Figure S15, S16-S18 and S20 for Pd-Ag, Pd-Cu, Pd-Ir, Pd-Ni and Pd-Rh alloy catalysts, H2 formation is the rate-limiting step for HCOOH dehydrogenation process. For Pd-Au and Pd-Pt alloy catalysts, the rate-limiting step for HCOOH dehydrogenation process includes HCO*O* and COOH* dehydrogenation into CO2 and H* and H2 formation. For the HCOOH dehydration, the rate-limiting step is H2O formation or COOH* dehydration. Except Pd1L@Pt, AuPd2L and AuPd3L, the catalysts mentioned above are of the feasible selectivity. Therefore, the activity is a more important factor for our prediction. The activity and selectivity chart on the hydrogen formation via HCOOH decomposition for the surface of Pd-based alloy catalysts with different alloying elements and atomic arrangement are shown in Figure 7. The darker red stands for higher activity, 14


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while the dark purple corresponds to better selectivity. Clearly, it is hard to achieve high activity and selectivity simultaneously for the models considered here. As mentioned above, the activity energy of HCOOH dehydrogenation is 0.483 ~ 0.756 eV and the difference of the barriers is 0.077 ~ 1.498 eV; hence the activity is a more important factor for our prediction. Considering possible commercialization of the catalyst, the doping metals with lower prices and higher doping amounts are more appropriate. Therefore, combining Figure 7 and Tables S14-S20, commercialization of the catalyst and the principle of focus on activity value, four models, i.e., Pd2L@Pd1Ag1, Pd2L@Pd1Au1, Pd1L@Pd1Au3 and Pd2L@Pd1Cu1 are selected as candidates of feasible catalysts of HCOOH dehydrogenation, since both their activity and selectivity are comparable to or beyond that of AuPd alloy with the overlayer structure which has been proven experimentally to be an excellent catalyst. Regarding stability of the candidates, the mixing energies of Pd2L@Pd1Ag1 (-0.163 eV) and Pd2L@Pd1Au1 (-0.175 eV) are higher than that of AuPd2L (-0.162 eV), suggesting that Pd2L@Pd1Ag1 (-0.163 eV) and Pd2L@Pd1Au1 are stable under reaction conditions. Moreover, Ag-Pd core-shell nanocatalyst in the earlier experiment[14] can markedly promote the hydrogen production from HCOOH decomposition at room temperature and the results give the compelling validation of our models.

4. CONCLUSION In conclusion, we suggested a strategy to seek high-performance Pd-based catalysts for hydrogen production from formic acid by rationally engineering the surface structure. We combined DFT calculations and microkinetic model to investigate activity and selectivity 15


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of Pd-Au alloy catalysts for hydrogen production from HCOOH decomposition. The obtained results were validated by available experimental data[17]. Based on Sabatier analysis, the CO and OH adsorption energies are correlated with the activity and selectivity for HCOOH decomposition. The average Bader charge of Pd atoms on the surface and the average bond length of surface atoms are identified as two key factors to adjust the adsorption energy of CO and OH, respectively. Thus, bother factors can be treated as two quantitative descriptors to analyze the effect of surface tension and charge redistribution on the reactivity of Pd-based alloy catalysts. Highly active and selective Pd-based alloy nanocatalysts can be achieved when the two descriptors are tuned towards optimal values through engineering the surface structure, including alloying appropriate elements and making suitable atomic arrangement. According to the proposed strategy, two surface structures, i.e., Pd2L@Pd1Ag1 and Pd2L@Pd1Au1 are predicted as promising catalysts for highly selective HCOOH dehydrogenation. Our work serves as a generic example on rationally engineering the surface structure of Pd-based catalysts. The proposed strategy can be extended for designing new heterogeneous catalysts beyond hydrogen production from selective HCOOH decomposition.

Supporting Information Origin of overlayer structure, HCOOH decomposition pathways, adsorption of HCOOH decomposition intermediates, elementary steps and microkinetic model (PDF).

Acknowledgment

16


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This work is supported by the National Natural Science Foundation of China (21822801, 21576008, 91634116, 21625601). XCZ thanks the computational support by UNL Holland Computing Center.

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Table 1. The HCOOH decomposition rate, and TOF for H2 production, based on Au-Pd bimetallic models for calculations, and experiments[17]. HCOOH Decomposition Rate (HCOOH

TOF for H2 Production

cm-2 s-1)

(H2 Pds-1 s-1)

Models

Experimental Value

Theoretical Value

Experimental Value

Theoretical Value

AuPd1L

3.5×1012

3.21×1012

0.006

0.0052

AuPd2L

1.4×1013

1.19×1013

0.012

0.0109

AuPd3L

3.3×1013

6.75×1012

0.011

0.0090

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Figure 1. Top view of the surfaces; adsorption sites on (a) Pd5L, (b) Au5L, and over-layer structures (c, e and g); and top view of the atomic configuration of over-layer structures (d, f, and h). Yellow (pink) stands for Au (Pd).

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Figure 2. Models for the surface structures (a) core-shell with Pd-M; (b) core-shell with Pd-alloy; (c) alloy; (d) subsurface.

Figure 3. Reaction mechanisms of the HCOOH decomposition.

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Figure 4. Scaling relations of adsorption energies of (a) all adsorbates, and (b) transition states of each elementary step along the whole reaction pathway versus CO and/or OH adsorption energies (ΔECO, ΔEOH). The solid lines are obtained by the best fits through the nine data points. The slopes and the intercepts of the fiting lines, as well as the values of x and y in the x-axes are given in Tables S8 and S9.

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Figure 5. Activity volcano for HCOOH decomposition. The activation energy of rate-determining step for (a) H2 + CO2 production, and (b) H2O + CO production versus CO and OH adsorption energies (ΔECO and ΔEOH). (c) CO selectivity versus CO and OH adsorption energies (ΔECO and ΔEOH). CO selectivity is defined as the activation energy of the rate-determining steps for H2O +CO production minus that for H2 + CO2 production. 27


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The values for different model systems can be taken from their indicated positions. The dashed area is the selective HCOOH decomposition toward H2O + CO production, where CO selectivity is below zero.

Figure

6.

A

plot

of

adsorption

energy

of

p 2* x  p3 / y  p 4 / y 2  p5 / y 3 in Equation 4. 28


CO

and

OH

versus

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Figure 7. Activity and selectivity of hydrogen formation via HCOOH decomposition on the surface of Pd-based alloy catalysts, arranged according to catalysts with different elements and surface structures. Each square corresponds to a metal facet and is subdivided into two halves. As indicated in the upper left box of each subfigure, the activation energies of rate-controlling step on dehydrogenation process are given in the upper left half, whereas the difference of activation energies of rate-controlling step on dehydration process and dehydrogenation process is given in the lower right half. The reaction energies are presented numerically (in eV) and by color-coding according to the legend. The green square stands for the feasible catalysts, which are chosen by overall consideration from both activity and selectivity.

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TOC Figure

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Hydrogen Production via Efficient Formic Acid Decomposition

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