Electrocatalysts with Increased Activity for Co-Electrolysis of Steam

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Electrocatalysts with Increased Activity for Co-Electrolysis of Steam and Carbon Dioxide in Solid Oxide Electrolyzer Cells Ara Cho, Jeonghyun Ko, Byung-Kook Kim, and Jeong Woo Han ACS Catal., Just Accepted Manuscript • DOI: 10.1021/acscatal.8b02679 • Publication Date (Web): 15 Nov 2018 Downloaded from http://pubs.acs.org on November 15, 2018

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Electrocatalysts with Increased Activity for Co-Electrolysis of Steam and Carbon Dioxide in Solid Oxide Electrolyzer Cells Ara Cho1,†, Jeonghyun Ko2,†, Byung-Kook Kim3, and Jeong Woo Han1,* 1

Department of Chemical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Gyeongbuk 37673, Republic of Korea 2 Department of Chemical Engineering, University of Seoul, Seoul 02504, Republic of Korea 3 High-temperature Energy Materials Research Center, Korea Institute of Science and Technology, Seoul 02792, Republic of Korea

Abstract

High-temperature co-electrolysis system can be helpful to solve environmental issues by reducing carbon dioxide emissions. The technology is highly promising because of its high selectivity and conversion efficiency toward the products. In addition, the produced syngas can also be further converted into very useful synthetic fuels. In this study, we investigated the series of reactions on a wide range of transition metals to evaluate their ability to increase the activity of the conventional Ni catalysts used in the fuel electrode of solid oxide electrolyzer cells. We theoretically identified that the adsorption energies of O and H are the common descriptors of co-electrolysis of steam and carbon dioxide. We then combined microkinetic analysis with density functional theory calculations to derive volcano plots to predict the activity of co-electrolysis on a variety of transition metals. We could successfully suggest good candidates of Ni-based bimetallic alloy catalysts with excellent activities in the co-electrolysis. Our result will provide insight to improve the electrode catalysts used in hightemperature co-electrolysis system.

Keyword: Solid oxide electrolyzer cells, Co-electrolysis, steam and carbon dioxide, Electrocatalytic activity, Density functional theory, Microkinetic modeling

*

Correspondence to [email protected]

†

A. Cho and J. Ko contributed equally to this work.

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1. Introduction Reducing the atmospheric concentration of carbon dioxide (CO2) released from fossil fuels is becoming a significant challenge due to its effect on climate change. One strategy to achieve this goal is to capture and convert the CO2 to a useful chemical that can be used as fuel. This is an attractive approach because the products from this technology can be utilized in existing infrastructure and vehicles 1. High-temperature co-electrolysis of steam (H2O) and CO2 by solid oxide electrolyzer cells (SOECs) can remove CO2 from the atmosphere

1-5

. By using electricity, this technology can

convert H2O and CO2 into syngas (H2 + CO), which can be a raw material for various chemical processes, and can be converted to liquid fuels by Fischer-Tropsh synthesis. SOECs have the advantages of excellent selectivity and reaction rate toward the products, and are more energy-efficient than separately operating two electrolysis systems

2, 6

. SOEC stacks

consist of air and fuel electrodes, separated by a solid electrolyte. H2O and CO2 are fed into the fuel electrode and reduced by the applied voltage to produce H2, CO, and O2-. The O2ions pass through the electrolyte, where they are oxidized and combined to produce O2 gas. At the electrode a thermochemical reverse-water gas shift reaction (rWGSR) occurs in parallel with electrochemical reactions, so the overall reaction is complex. Most previous studies of fuel electrodes for SOECs have focused on nickel-yttria stabilized zirconia (Ni/YSZ) cermet due to its high electrical conductivity and low cost

7-9

. However,

Ni/YSZ remains several issues to overcome for achieving high performance, such as low activity for CO2 reduction and a high overpotential that decreases energy efficiency. To identify good candidate catalysts for the fuel electrode of SOEC, the factors that control electro-catalytic efficiency have been investigated theoretically and electrode materials for H2O and CO2 electrolysis have been screened

10-11

; promising candidates identified were

Ni3Fe(211) for H2O electrolysis, and Ru(0001) and Co(0001) for CO2 electrolysis. However, these analyses did not consider the two electrolysis reactions on the same kind of metal catalysts nor at the same time; rWGSR during co-electrolysis was also not investigated. The alloying technique may be one of the promising strategies to promote the catalytic activity due to ligand and strain effect that changes the electronic structure

12

and therefore

may be a useful strategy to promote the catalytic activity. Previous studies reported that the SOEC’s catalytic efficiency was improved by alloying transition metals with the conventional Ni catalyst

13-18

. Typical

SOEC systems have been optimized with Ni-based electrodes, so in

this paper, we focus on increasing the activity of Ni at the fuel electrode, rather than on 2 ACS Paragon Plus Environment

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exploring entirely new catalysts. We first examine the free energies of co-electrolysis of H2O and CO2 electrochemical reactions with rWGSR on 11 transition metals (Ni, Cu, Ir, Pt, Pd, Rh, Au, Ag, Co, Ru, and Fe) by using density functional theory (DFT) calculations. A Bronsted-Evans-Polanyi (BEP) relation and scaling relation are derived from our DFT data. We identify that O and H adsorption energies are good descriptor to predict the activity of coelectrolysis. Then we perform microkinetic analysis to obtain the turnover frequencies (TOFs) for co-electrolysis under the SOEC operating condition, and derive a volcano plot that describes the relationship between the activities and the descriptors. Our results provide promising metal catalyst candidates among the Ni-based alloying materials within a consistent computational framework for high-temperature co-electrolysis systems.

2. Computational Methods All calculations were performed using the Vienna Ab Initio Simulation Package (VASP) 1922

periodic DFT code. Electron exchange correlation energies were treated using the Perdew-

Burke-Enrnzerhof (PBE) functional of the generalized gradient approximation (GGA)

23

. In

the expansion of the plane wave, the cutoff of kinetic energy was taken to be 400 eV. Methfessel-Paxton Fermi-level smearing

24

with a width of 0.2 eV was applied for the total

energy calculations in metal. Geometry relaxation was stopped when the difference in the total force was < 0.03 eV/Å . For Ni(111), Co(0001), and Fe(110), we considered spin polarization. To avoid the artificial electrostatic field, dipole corrections were used in computing all energies reported here 25-26. The surface calculations used DFT-calculated lattice parameters taken from a previous study 27. The most stable close-packed facets of each transition metal were selected: (111) for face-centered cubic (fcc) (Ni, Cu, Ir, Pt, Pd, Rh, Au, and Ag), (0001) for hexagonal closepacked (hcp) (Co and Ru) and (110) for body-centered cubic (bcc) (Fe) structures. In our slab model, a (3 × 3) supercell with five-layer thickness and a vacuum spacing of 15 Å were used. The bottom two layers were fixed to imitate their bulk arrangements; the other layers were fully relaxed. Monkhorst-Pack 3 × 3 × 1 k-point meshes were used. Isolated gas-phase molecules were simulated in a large periodically-repeated cubic box with sides length of 20 Å . In our calculations, we used a semi-empirical dispersion correction of the DFT-D2 method 28

to precisely describe the CO2 physisorption. Dispersion coefficient C6 = 40.62 J mm6/mol

was used for Au(111) and Ir(111), and C6 = 20 J nm6/mol was used for Pt(111). The van der Waals radius R0 = 1.772 Å was used for Au(111) and Ir(111), and R0 = 1.9 Å was used for 3 ACS Paragon Plus Environment

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Pt(111) 29-33. The parameters of other metals were obtained from the original paper 28. We also set the global scaling factor s6 = 0.75 for the PBE, as was suggested

28

, and 30.0 Å as the

cutoff radius. These adsorption energies of CO2 physisorption were not much different from those calculated by DFT-D3 method 34. The adsorption energy Eads is Eads = Etotal – Esurf – Eadsorbate, where Etotal is the total energy of the system that holds the adsorbed species, Esurf is the total energy for the optimized bare surface, and Eadsorbate is the total energy of the adsorbate in the gas phase. For atomic adsorption such as H and O, the total energies for “1/2EO2” and “1/2EH2” were used for Eadsorbate. Details of the adsorption energies of reaction intermediates and the co-adsorption configuration are available in Note 1 in the Supplementary Information. The climbing-image nudged elastic band (CI-NEB) method35 was used to determine the minimum-energy paths (MEP) and calculate the dissociation barrier. In this study, 3~5 intermediate images were taken into account with forces minimized to 0.06 eV/Å .

3. Co-electrolysis of H2O and CO2 with rWGSR on the Fuel Electrode of SOEC At the fuel electrode of SOEC, the electrolysis reactions of H2O and CO2 occur concurrently with rWGSR:

H2O (g) + 2e  H2 (g)  O2

(R1)

CO2 (g) + 2e  CO(g) + O2-

(R2)

rWGS CO2 (g) + H2 (g)   CO(g) + H2O(g) WGS

(R3)

rWGSR is a thermochemical reaction that kinetically equilibrates at temperatures > ~ 800 °C. rWGSR contributes to the conversion of CO2 when it occurs with CO2 electrolysis

36-37

.

Therefore, rWGSR must be considered in the co-electrolysis system. We assumed that the co-electrolysis on transition metal surfaces follows an oxygen spillover mechanism

38-39

, in which surface spillover transfers oxygen ions from the metal

surface to electrolyte. In this mechanism, the elementary steps of H2O electrolysis are

H 2 O (g) +   H 2 O 

(R4)

H 2 O  +   OH   H 

(R5)


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OH  +   O   H 

(R6)

O  + 2e   O 2   

(R7)

2H   H 2 (g)  2  ,

(R8)

where * denotes a free surface site or an adsorbed species on the surface. The adsorption of water (R4) is followed by its dissociation to OH* and H* (R5). Then OH* dissociates to O* and H* (R6), and O* reduces to O2- (R7). Finally, associative desorption of H2 (R8) occurs. Similarly, we assumed that CO2 electrolysis follows the oxygen spillover mechanism in four elementary steps:

CO 2 (g) +   CO 2 

(R9)

CO 2  +   CO   O 

(R10)

CO   CO(g)  

(R11)

O  + 2e   O 2   

(R12)

A CO2 gas molecule is adsorbed to a metal surface (R9), and subsequently dissociates to CO* and O* (R10). The dissociated CO* desorbs as a gas (R11), and O* is reduced to O2- (R12). Except (R7) and (R12), all elementary steps are thermochemical reactions; due to the absence of charged species, these reactions are not influenced by a cell operating potential

40

.

However, (R7) and (R12) are associated with the transfer of two electrons, and are highly dependent on the cell’s operating potential. rWGSR for Fe

41

, Ni, Rh, Cu

42-44

, Ir and Co

45

prominently follows a redox mechanism

(CO2 ↔ CO* + O*). On oxophilic surfaces, the redox mechanism is often favored over the hydrogenation reaction (CO2 + H* ↔ COOH*)

42

; the oxygen adsorption strength on Ru is

between those on Fe and Co, so Ru can also be assumed to follow the redox mechanism. For simplicity, here we only consider the following redox mechanism for the rWGSR:

CO 2 (g) +   CO 2 

(R13)

CO2  +   CO   O 

(R14)

H 2 (g)  2   2H 

(R15)


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O   H  OH  + 

(R16)

OH  + H   H 2 O 

(R17)

H 2 O   H 2 O(g) + 

(R18)

CO  CO(g)   ,

(R19)

where the elementary reactions (R13) ~ (R14) and (R19) are equivalent to (R9) ~ (R11), and the elementary reactions (R18) ~ (R15) are equivalent to (R4) ~ (R6) and (R8) in the reverse direction (Table 1). We excluded a disproportionation reaction (OH* + OH* ↔ H2O* + O*) because it has near-zero net rate of the reaction and does not contribute significantly to the overall rWGSR 46. Previous study reported that the chemical activity of Ni particle on YSZ is very similar to that of pure Ni surface, and not only the pure YSZ surface but also the YSZ surface of the cermet are inert for H2, CH4, and CO oxidation in solid oxide fuel cells 47. Therefore, for the computational efficiency, we did not include the YSZ support in our DFT calculations.

3.1. Thermodynamic analysis of elementary steps In the electrochemical reactions, comparison of the change G Gibbs free energies G = EDFT - TS in Gibbs free energy for each elementary step provides useful information to help predict the activity 39, 48-49. G is calculated as ΔG1  G[H 2 O]  G[H 2 O(g)]  G[]

ΔG 2  G[OH]  G[H]  G[H 2 O] ΔG 3  G[O]  G[H]  G[OH]  G[] ΔG 4  G[O 2  ]  G[]  G[O]  2eVcathode

ΔG 5  G[H 2 (g)]  2G[]  2G[H]

ΔG 6  G[CO 2 ]  G[CO 2 (g)]  G[] ΔG 7  G[CO]  G[O]  G[CO 2 ]  G[]

ΔG 8  ΔG 4 ΔG 9  G[CO(g)]  G[]  G[CO] ,


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where EDFT [eV] is the total energy obtained from the DFT calculation, T [K] is absolute temperature, and S [eV/K] is the standard entropy taken from the NIST database

50

. We set

the standard oxygen electrode (SOE) as a reference electrode to calculate G of the elementary steps involved in the charged species. The SOE is in equilibrium with PO2 = 1 atm and the metal electrode in contact with 8% Y2O3-stabilized ZrO2 (YSZ) at 673 K 38-39, 51. We assumed that O2- almost fully covers the surface electrolyte 52. To understand the kinetics of co-electrolysis of H2O and CO2, the activation energies Ea and reaction energies ∆E of rate-determining steps (RDSs) must be calculated. Ea is defined as transition state energy – initial state energy, andE is defined as final state energy – initial state energy. We assume that Ea and ∆E and of electro-reduction of an oxygen atom (R7 and R12) are identical

40

. Ea (Table 1) and ∆E (Table 2) were calculated for H2O

dissociation (R5), OH dissociation (R6), and CO2 dissociation (R10).

3.2. Rate-determining steps in the electrolysis of H2O and CO2 on pure metal surfaces By using (R4) ~ (R12), the free energy diagrams of H2O and CO2 electrolysis reactions at the applied potential U = 1.3 V vs SOE and T = 1073 K were derived for a wide range of transition metal surfaces (Fig. 1). Many previous studies reported that (R5), (R6), and (R7) have considerable activation barriers in catalytic reactions 44, 53-54, so one of these elementary steps may be the RDS for the H2O electrolysis reaction. We also assumed that (R4) and (R8) are much faster than (R5), (R6) and (R7). The reduction step of O* into O2- (R7) became exothermic on all metal surfaces due to the applied potential. During H2O electrolysis (Figure 1a, Table 2), H2O (R5) and OH (R6) dissociation steps are exothermic on Ni(111), Fe(110), Co(0001) and Ru(0001); of these metals, Fe(110) is the most energetically favorable, with E = -1.26 eV for (R5) and -0.68 eV for (R6) at U = 1.3 V vs SOE. In contrast, the H2O (R5) dissociation step is endothermic with E = 1.05 on Au(111) and 0.57 on Ag(111); similarly, the OH (R6) dissociation step is endothermic with E = 1.04 eV on Au(111), and 1.44 eV on Ag(111). Comparison of their Ea (Table 1) indicates that the OH-dissociation step (R6) is the RDS for all metal surfaces except Pt(111), on which the H2O dissociation step (R5) is the RDS (Ea = 1.21 eV). On Fe(110) and Ru(0001), the OH dissociation reaction had the lowest Ea = 0.83 eV, whereas Ag(111) has Ea = 2.32 eV and Au(111) has Ea = 2.07 eV, which are much higher than in the other metals. As a result, Ni catalyst is expected to be superior to Cu, Pt, Pd, Au, and Ag, but inferior to Fe, Co, Ir, Ru, and Rh for H2O electrolysis. 7 ACS Paragon Plus Environment

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The free energy diagram (Figure 1b) represents CO2 electrolysis on metal surfaces under the same condition as in H2O electrolysis. A CO2 dissociation (R10) step is exothermic with the reaction free energies of -1.46 ~ -0.20 eV except for Cu(111), Pt(111), Au(111) and Ag(111) (Table 1). On Fe(110) and Co(0001), the CO2 dissociation reaction has the lowest Ea = 0.11 eV (Table 2). Similar to the result of H2O electrolysis, Au(111) had Ea = 2.92 eV and Ag(111) had Ea = 2.29 eV, which are much higher than the other metals. The free energy diagram (Figure 1c) of rWGSR can be obtained from the thermodynamic DFT data of both H2O and CO2 electrolysis reactions (Tables 1, 2). In this reaction, the metals have different RDSs: for Ni(111), Fe(110), Cu(111), and Co(0001), the H2O-formation step (R17) is the RDS; for Ir(111), Ru(0001), and Rh(111) the OH-formation step (R16) is the RDS; for Pt(111), Pd(111), Au(111), and Ag(111), the CO2-dissociation step (R14) is the RDS. If the RDS of rWGSR is a CO2 dissociation step that has the same RDS in the CO2 electrolysis, CO2 conversion may occur by both CO2 electrolysis and rWGS. However, Pt(111), Pd(111), Au(111), and Ag(111) actually follow the hydrogenation mechanism 42 even though we have assumed that they follow the redox mechanism, so our calculated Ea at the RDS may be overestimated. Ea at the RDS is lower in rWGSR than in CO2 electrolysis, so rWGSR may convert more CO2 to CO than CO2 electrolysis does. CO2 hydrogenation to COOH has 1.07 ≤ Ea ≤ 1.15 eV, whereas the CO2-dissociation step which is the main step for CO2 conversion on Ni, has Ea = 0.69 eV 45. Combining our results, Pt, Pd, Au, and Ag are less active than Ni for CO production and for H2O electrolysis that generates H2. Therefore, our assumption does not significantly affect the purpose of searching for catalyst candidates that are superior to Ni in SOEC. Ea for the H2O-formation step on Ni(111), Fe(110), Cu(111) and Co(0001) ranges from 1.31 to 1.86 eV and Ea for the OH-formation step on Ir(111), Ru(0001), and Rh(111) ranges from 1.15 to 1.53 eV. However, Ea for the CO2-dissociation step, which is the RDS for CO2 electrolysis ranges from 0.11 to 1.15 eV on the metals that have a H2O-formation or OHformation step as the RDS in rWGSR. (Table 1); i.e., for these metals, CO2 conversion will occur predominantly by electrolysis rather than by rWGSR. Our prediction concurs with a previous result that most of the CO2 conversion on Ni/YSZ was generated by CO2 electrolysis, whereas rWGSR contributed only 10 ~ 15% at 1.3 V

55

. By combining our

thermodynamic data from DFT, we performed microkinetic modeling in the later section.


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Figure 1. Free energy diagram of (a) H2O electrolysis and (b) CO2 electrolysis via oxygen spillover mechanism (c) rWGSR via redox mechanism on transition metals at 1073 K and applied potential (U=1.3 V vs SOE). Table 1. Activation energies Ea [eV] of each dissociation reaction

Ni(111) Fe(110) Cu(111) Co(0001) Ir(111) Ru(0001) Pt(111) Pd(111) Rh(111) Au(111) Ag(111)

H2O dissociationa (R5)

OH dissociationb (R6)

CO2 dissociationc (R10)

Ea,f

Ea,f

Ea,f 0.48 0.11 1.15 0.11 0.79 0.66 1.12 1.40 0.56 2.92 2.29

0.86 0.60 1.16 0.92 0.73 0.80 1.21 1.03 0.92 1.66 1.50

Ea,r

1.31 1.86 1.38 1.51 0.54 1.24 0.71 0.73 0.88 0.61 0.93 a H 2O *    OH *  H * ;

Ea,r

0.97 0.83 1.25 0.93 0.92 0.83 0.98 1.05 0.95 2.07 2.32

1.21 1.51 0.80 1.23 1.15 1.53 0.95 1.10 1.20 1.03 0.88 b OH *    O *  H * ;


c

Ea,r 1.79 1.57 0.90 1.32 1.57 1.98 0.94 1.60 1.41 0.69 0.16

CO2 *    CO *  O * .

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Table 2. Reaction energies ∆E [eV] of each dissociation reaction H2O dissociationa (R5)

OH dissociationb (R6)

CO2 dissociationc (R10)

∆E

∆E

∆E –1.31 –1.46 0.25 –1.21 –0.78 –1.32 0.18 –0.20 –0.85 2.23 2.13

–0.45 –1.26 –0.22 –0.61 0.19 –0.44 0.50 0.30 0.04 1.05 0.57 a H 2O *    OH *  H * ;

–0.24 –0.68 0.45 –0.30 –0.23 –0.70 0.03 –0.05 –0.25 1.04 1.44

Ni(111) Fe(110) Cu(111) Co(0001) Ir(111) Ru(0001) Pt(111) Pd(111) Rh(111) Au(111) Ag(111)

b

OH *    O *  H * ;

c

CO2 *    CO *  O * .

3.3. Brønsted–Evans–Polanyi and scaling relation The BEP relation describes the linear correlation between E and Ea of a surface reaction on transition metals

56-57

. It can effectively reduce the efforts to estimate Ea; this relation has

been widely used in the fields of heterogeneous catalysis. Here, to identify the BEP relations, we calculated Ea (Table 1) and E (Table 2) of each dissociation over the 11 transition metal surfaces. The linear BEP relations were also effective for each dissociation step in our system (Figure 2), so Ea [eV] can be estimated as Ea ( H 2O)  0.41  E ( H 2O)  1.04 ,

(1)

Ea (OH )  0.73  E (OH )  1.16 ,

(2)

Ea (CO2 )  0.52  E (CO 2 )  1.03 .

(3)

It seems that the R2 value in the BEP relation for H2O dissociation is not very high. However, we cannot statistically say whether fittings are good or not only based on the R2 values because they are highly sensitive to the outliers 58. For example, if we get rid of Ir(111) data point on the BEP plot for H2O dissociation, the R2 value significantly increases from 0.66 to 0.80. To evaluate the linearity more precisely, therefore, we would like to provide mean absolute error (MAE) values for each BEP line of dissociation reactions. Indeed, the MAE value has used as a criterion to determine the linearity for many theoretical studies based on 10 ACS Paragon Plus Environment

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BEP and scaling relations

59-62

. We confirmed that MAE values between the DFT-calculated

activation energies and activation energies predicted from the BEP of H2O, OH and CO2 dissociations are 0.14, 0.11 and 0.21 eV, respectively which are smaller than typically accepted MAE values (≤ 0.3 eV) 63-65. Adsorption energies Eads on transition metal surfaces also show scaling relations

56, 66-67

.

Eads(O) has a linear correlation (Eq. 4) with Eads(OH) (Figure 3a). Eads(H) has a linear correlation with both Eads(H2O) (Eq. 5) and Eads(CO) (Eq. 6) (Figure 3b). It is noteworthy that the adsorption energies of molecules that do not participate in a certain reaction often have good linear relations with E, such as Eq. 6 68-69. However, Eads(CO2) does not show a linear relationship with any other parameters, because molecular CO2 adsorption is physisorption, which is not associated with charge transfer 70. In addition, the distribution of the adsorption energies of physisorbed CO2 on the metal surfaces we considered is very narrow (within the standard deviation of 0.04 eV) (Table S1, Figure 4). We thus assume that the Eads(CO2) is constant, and use an arithmetic average value of Eads(CO2) = –0.28 eV for 11 pure metal surfaces in the following calculations of kinetics. Eads (OH)  0.53  Eads (O)  2.26 ,

(4)

Eads ( H 2O)  0.33  Eads ( H )  0.36 ,

(5)

Eads (CO )  2.49  Eads ( H )  0.56 .

(6)

Figure 2. Linear Brønsted–Evans–Polanyi (BEP) relations between activation energies and reaction energies for H2O, OH, and CO2 dissociation. Symbols: DFT-calculated energies of dissociation; solid lines: linear fits to each dissociation reaction. 11 ACS Paragon Plus Environment

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To explore other types of scaling relations between Eads and ΔE, we plot the adsorption energies as a function of the reaction energies for each dissociation (Figure 4). Regression results indicate clear linear relations between E of each dissociation and the Eads of adsorbates that participate in the reactions. For H2O dissociation, ΔE(H2O) is strongly correlated with both Eads(O) and Eads(OH) (Figure 4a). For OH dissociation, ΔE(OH) has linear correlations with Eads(H), Eads(CO), Eads(O) and Eads(H2O) (Figure 4b). For CO2 dissociation, ΔE(CO2) has linear correlations with Eads(O) and Eads(CO) (Figure 4c). Based on these relations, the reaction energies [eV] can be estimated as E ( H 2O)  0.68  Eads (O)  1.34 ,

(7)

E (OH )  2.66  Eads ( H )  1.46 ,

(8)

E (CO2 )  0.66  ( Eads (CO)  Eads (O))  2.12 .

(9)

Figure 3. The scaling relations between the adsorption energies of on pure metals. (a) O and OH, (b) H, CO, and H2O. Lines: linear fits.

Figure 4. The correlations between reaction energies for (a) H2O, (b) OH and (c) CO2 dissociation and adsorption energies on pure metal surfaces. Solid lines: linear fits. 12 ACS Paragon Plus Environment

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Here, we briefly summarize our results of exploring the relations between Eads and kinetic parameters. (1) By exploiting scaling relations, we can reduce the number of the descriptors. The adsorption energies of O and H can represent those of the other intermediates, except for Eads(CO2) (Eq. 4~6). (2) A scaling relation can estimate E from Eads for each dissociation step (Eq. 7~9). (3) BEP relations determine Ea for each dissociation step as a function of E (Eq. 1~3). The results of (1) ~ (3) indicate that Eads(O) and Eads(H) are key descriptors to predict Ea of H2O and CO2 co-electrolysis. Considering only one descriptor might result in some deviations from the experimental results, because more than one factor can influence the activity of some materials in multi-step reactions. For example, some scatter occurs in the regression of ethylene-hydrogenation activity obtained from the experiment on the calculated Ea of first hydrogenation step

71

; the variation may occur because the activities of Rh and Ir were

determined by one descriptor of the first hydrogenation step, whereas the activities of other metals such as Ru, Pd, Os, and Pt showed additional dependency on the second hydrogenation step

71

. In addition, it is not easy to precisely detect the optimal catalyst with

1-D volcano alone intuitively. Although the Eads of nitrogen is enough to predict the activity of ammonia synthesis, adding the activation barrier for N2 dissociation to the descriptor broadens the possibility of finding a new catalyst with the highest activity

69

. Similarly,

various studies have exploited the 2-D volcano chart to suggest strategies to reach the maximum activity region; examples include breaking the scaling relation

12, 72

adding

promoters 65, 69 and others 54,73. Furthermore, Eads(C) and Eads(O) are relatively independent whereas Eads(C) and Eads(H) are dependent 74. This can be attributed to the fact that adsorbates with low highest occupied molecular orbitals (HOMOs) experience a higher level of Pauli repulsion than those with higher HOMOs: C and H correlate each other because they both have high HOMO energies whereas O does not correlate with C or H due to its low HOMO energy 75. Therefore, because the reactants, products and intermediates for co-electrolysis are bonded to the surface by C or H or O, two descriptors would be enough to describe the overall reactions in this study. These complications can affect our catalyst design of co-electrolysis systems. Therefore, using two descriptors which are independent of each other can provide a reliable volcano-shape of activity of co-electrolysis.


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4. Microkinetic Modeling for H2O and CO2 Electrolysis on Pure and Bimetallic Alloy Catalysts A microkinetic analysis was performed to determine the activity of co-electrolysis on various transition metals by the mechanism outlined in (R4) ~ (R12). The steady-state approximation is applied because adsorption of reactants (H2O, CO2) and desorption of products (H2, CO) are fast enough to be in equilibrium. Rate constants for RDSs were calculated as

k

 E  T S  kbT exp   a , h kbT  

(10)

where kb = 8.617 × 10-5 eV/K is the Boltzmann constant, T [K] is temperature, h = 4.136 × 10-15 eV·s is the Plank constant, and ΔS [eV/K] is the entropy difference between the transition state and initial state. The adsorbed species were assumed to have entropy = zero (see Note 2 in the Supplementary Information). The turnover frequencies (TOF) for co-electrolysis of H2O and CO2 on transition metal surfaces were calculated as a function of Eads(O) and Eads(H) (activity = log(TOF)) (Figure 5), where the feed gas consisted of 50% H2O and 50% CO2. For comparison, volcano plots for H2O electrolysis and CO2 electrolysis were also obtained. (Figure S5 in the Supplementary Information). The region at which TOF was maximal for co-electrolysis had Eads(O) ~ 3.5 eV and Eads(H) ~ 0.8 eV. Fe is the only transition metal that located in this maximum window. Ru and Co also show good activities of co-electrolysis compared to the conventional Ni catalysis for SOEC fuel electrode. These results agree well with previous experimental demonstrations that addition of Co and Ni to ceramic composite electrode improves its catalytic activities in co-electrolysis environment, whereas addition of Cu degrades the catalytic activity

76

.

However, changing the fuel electrode from conventional Ni to the other metals would cause many practical problems. In addition, pure Fe catalyst shows poor efficiency under coelectrolysis condition, due to the ease of oxidation of Fe 76; we did not consider this factor.


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Figure 5. Normalized activities (ln(TOF); filled black circles) of co-electrolysis (PH2O = 0.5, PCO2 = 0.5) on pure transition metal surfaces at T = 1073 K, V = 1.3. Yellow circles: Alloy materials for which only the O and H adsorption energies were calculated. Therefore, we focused on a bimetallic system in which the second metal is doped into Ni host to improve its catalytic activity. We modeled Ni-based alloy (111) surfaces with the top three candidates in Figure 5 (Fe, Ru, and Co) as a dopant metal (see Note 3 and Figure S4 in the Supplementary Information). To obtain the activities, the adsorption energies of O and H were calculated for model compositions of Ni3Fe, Ni3Ru, and Ni3Co. To confirm that the extrapolation from calculations on individual transition metal surfaces to bimetallic catalysts is effective, we performed the additional calculations for the BEP relation of H2O dissociation on Ni3M alloy surfaces (M = Fe, Co, Ru) as an example. We confirmed that although we added the data for Ni-based alloys to those for pure metals, a linearity of the BEP relation was still effective with almost same MAE and R2 value (see Figure S5 in the Supplementary Information). Indeed, there have been many other reports that use the scaling and BEP relations obtained by pure metals to design alloy materials 65, 77-80. Figure 5 shows that Ni-Fe is 1.9 times more active in TOF than pure Ni, and also better than other Ni-based alloys. This improvement may occur because addition of Fe to Ni makes Eads(O) close to the optimal point. Ru (1.8 times) and Co (1.4 times) were also more active in TOF than Ni. Indeed, Ni-Ru/Gd0.1Ce0.9O1.95 (Ni-Ru/GDC) provided higher efficiency for coelectrolysis than Ni/GDC 81; this result supports the validity of our theoretical predictions.


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For H2O electrolysis, a theoretical study suggested that Ni3Fe(211) and Ni3Co(211) show higher activity than Ni(211)11; we also predict this difference here (Figure S6(a) in the Supplementary Information). However, a separate study for CO2 electrolysis showed that only Co(0001) and Ru(0001) are superior to Ni(111) 10 whereas we found that Fe(110) is also better than Ni(111) and has even higher activity than Co(0001) and Ru(0001) (Figure S6(b) in the Supplementary Information). Although Eads(O) represents the transition state well, the adsorption and desorption processes of CO2 and CO would both significantly influence the total rate. We thus used two descriptors (Eads(O) and Eads(H) which has a scaling relation with Eads(CO) as in Eq. 6), but [11] used only Eads(O) as a predictor; this restriction is the cause of the discrepancy. However, our results and 11 agree about H2O electrolysis because Eads(O) is a more dominant factor than Eads(H) 40 to predict the reaction. Experimental reports have also shown that alloying of Ni with a small amount of Fe significantly improves the electrochemical activities of H2O electrolysis

17

and CO2

electrolysis 18 due to prevention of Ni aggregation. By combining our results, we can suggest that the increase in activity of Ni-Fe is the result of not only increased stability but also of the catalytic property of Fe. Another study reported that Ni-Co alloy with Sm-doped ceria (NiCo/SDC) enhances the performance of H2O electrolysis in SOEC. Although they attributed the enhancement to the effective enlargement of the active reaction region by the addition of Co 14, we think that Co also increased the intrinsic catalytic activity of pure Ni. Using a low operating voltage VO can result in cost benefit by replacing expensive electric energy with heat energy in the isothermal mode 2. However, materials such as Fe that have strong oxygen affinity may have difficulty transferring O2- from the electrode to the electrolyte at the low VO. By calculating the free energy of oxygen ion transfer step consisting of oxygen desorption and two electron transfers, we can obtain VO below which oxygen poisoning starts on the metal surfaces at 1073 K (Table S2 in the Supplementary Information). At VO = 1.13 V, electroreduction of adsorbed oxygen on Fe becomes endothermic. Therefore, VO can affect the shape of the volcano plot. The ‘maximum’ region shifts to the right as VO decreases, and shifts to the left as VO increases. For example, at VO = 1.1 V, Ru would be located on the maximum region, and the activity on Ni3Fe would also be increased. Although operating an SOEC at a low VO would reduce the cost, the reduction would not be significant, so a thermoneutral voltage of 1.3 V been has recommended in practice 2. Nevertheless, further investigation of the change in the activity with regard to the sensitivity of voltage for each transition metal might yield valuable insights. 16 ACS Paragon Plus Environment

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We have confirmed that Fe, Ru, and Co have superior activity to Ni, in co-electrolysis of H2O and CO2, and are good candidates as dopants for Ni-based catalytic alloys. In particular, Ni-Fe is a promising electrode material, because its descriptors are close to the optimal binding energies.

4. Conclusion DFT calculations were performed to search for superior materials as the fuel electrode catalysts of SOEC. We calculated the reaction energies E and activation energies Ea of H2O and CO2 electrolysis on 11 transition metals (Ni, Cu, Ir, Pt, Pd, Rh, Au, Ag, Co, Ru, and Fe) on the basis of oxygen spillover mechanism. We also considered rWGSR in co-electrolysis, which may contribute to CO2 conversion. Based on the Brønsted-Evans-Polanyi (BEP) relationship and scaling relation, we found that adsorption energies of hydrogen and oxygen are promising key descriptors of the activity for co-electrolysis. We obtained volcano plots of electro-catalytic activity for co-electrolysis by microkinetic modeling. Our results showed that Fe is located near the top of volcano plot, and that Ru and Co are also close. We suggest that Fe-doped Ni is experimentally feasible and is a good candidate for SOEC catalysts.

Supporting Information Adsorption energies and configurations; microkinetic modeling; surface structures of Nibased alloys; normalized activities for each of H2O and CO2 electrolysis; operating voltage below which oxygen poisoning starts at 1073K.

Acknowledgements This study was supported by the KIST Institutional Program (2E28040-18-041) and the R&D program of the Global Frontier Center for Multiscale Energy System

(NRF-

2014M3A6A7074784) and the Nano Material Technology Development Program (NRF2018M3A7B4062825) funded by the Korea government (MSIT).

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55. Aicart, J.; Usseglio-Viretta, F.; Laurencin, J.; Petitjean, M.; Delette, G.; Dessemond, L., Operating Maps of High Temperature H2O Electrolysis and H2O+CO2 Co-Electrolysis in Solid Oxide Cells. International Journal of Hydrogen Energy 2016, 41, 17233-17246. 56. Bligaard, T.; Nørskov, J. K.; Dahl, S.; Matthiesen, J.; Christensen, C. H.; Sehested, J., The Brønsted–Evans–Polanyi Relation and the Volcano Curve in Heterogeneous Catalysis. Journal of Catalysis 2004, 224, 206-217. 57. Pallassana, V.; Neurock, M., Electronic Factors Governing Ethylene Hydrogenation and Dehydrogenation Activity of Pseudomorphic PdML/Re(0001), PdML/Ru(0001), Pd(111), and PdML/Au(111) Surfaces. Journal of Catalysis 2000, 191, 301-317. 58. N. Moriasi, D.; G. Arnold, J.; W. Van Liew, M.; L. Bingner, R.; D. Harmel, R.; L. Veith, T., Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations. Transactions of the ASABE 2007, 50, 885-900. 59. Fernández, E. M.; Moses, P. G.; Toftelund, A.; Hansen, H. A.; Martínez, J. I.; AbildPedersen, F.; Kleis, J.; Hinnemann, B.; Rossmeisl, J.; Bligaard, T.; Nørskov, J. K., Scaling Relationships for Adsorption Energies on Transition Metal Oxide, Sulfide, and Nitride Surfaces. Angewandte Chemie International Edition 2008, 47, 4683-4686. Sakong, S.; Naderian, M.; Mathew, K.; Hennig, R. G.; Groß, A., Density Functional 60. Theory Study of the Electrochemical Interface between a Pt Electrode and an Aqueous Electrolyte Using an Implicit Solvent Method. The Journal of Chemical Physics 2015, 142, 234107. 61. Latimer, A. A.; Aljama, H.; Kakekhani, A.; Yoo, J. S.; Kulkarni, A.; Tsai, C.; GarciaMelchor, M.; Abild-Pedersen, F.; Nørskov, J. K., Mechanistic Insights into Heterogeneous Methane Activation. Physical Chemistry Chemical Physics 2017, 19, 3575-3581. 62. Latimer, A. A.; Kulkarni, A. R.; Aljama, H.; Montoya, J. H.; Yoo, J. S.; Tsai, C.; Abild-Pedersen, F.; Studt, F.; Nørskov, J. K., Understanding Trends in C–H Bond Activation in Heterogeneous Catalysis. Nature Materials 2016, 16, 225. 63. Sutton, J. E.; Vlachos, D. G., A Theoretical and Computational Analysis of Linear Free Energy Relations for the Estimation of Activation Energies. ACS Catalysis 2012, 2, 1624-1634. 64. Grabow, L. C., CHAPTER 1 Computational Catalyst Screening. In Computational Catalysis, The Royal Society of Chemistry: 2014; pp 1-58. 65. Schumann, J.; Medford, A. J.; Yoo, J. S.; Zhao, Z.-J.; Bothra, P.; Cao, A.; Studt, F.; Abild-Pedersen, F.; Nørskov, J. K., Selectivity of Synthesis Gas Conversion to C 2+ Oxygenates on fcc(111) Transition-Metal Surfaces. ACS Catalysis 2018, 8, 3447-3453. 66. Jones, G.; Bligaard, T.; Abild-Pedersen, F.; Nørskov, J. K., Using Scaling Relations to Understand Trends in the Catalytic Activity of Transition Metals. Journal of Physics: Condensed Matter 2008, 20, 064239.


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67. Logadottir, A.; Rod, T. H.; Nørskov, J. K.; Hammer, B.; Dahl, S.; Jacobsen, C. J. H., The Brønsted–Evans–Polanyi Relation and the Volcano Plot for Ammonia Synthesis over Transition Metal Catalysts. Journal of Catalysis 2001, 197, 229-231. 68. Shi, C.; Hansen, H. A.; Lausche, A. C.; Norskov, J. K., Trends in Electrochemical CO2 Reduction Activity for Open and Close-Packed Metal Surfaces. Physical Chemistry Chemical Physics 2014, 16, 4720-4727. 69. Medford, A. J.; Vojvodic, A.; Hummelshøj, J. S.; Voss, J.; Abild-Pedersen, F.; Studt, F.; Bligaard, T.; Nilsson, A.; Nørskov, J. K., From the Sabatier Principle to a Predictive Theory of Transition-Metal Heterogeneous Catalysis. Journal of Catalysis 2015, 328, 36-42. 70. Ko, J.; Kim, B.-k.; Han, J. W., Density Functional Theory Study for Catalytic Activation and Dissociation of CO2 on Bimetallic Alloy Surfaces. Journal of Physical Chemistry C 2016, 120, 3438-3447. 71. Heard, C. J.; Hu, C.; Skoglundh, M.; Creaser, D.; Grönbeck, H., Kinetic Regimes in Ethylene Hydrogenation over Transition-Metal Surfaces. ACS Catalysis 2016, 6, 3277-3286. 72. Kulkarni, A.; Siahrostami, S.; Patel, A.; Nørskov, J. K., Understanding Catalytic Activity Trends in the Oxygen Reduction Reaction. Chemical Reviews 2018, 118, 2302-2312. Vojvodic, A.; Nørskov, J. K.; Abild-Pedersen, F., Electronic Structure Effects in 73. Transition Metal Surface Chemistry. Topics in Catalysis 2014, 57, 25-32. 74. Medford, A. J.; Lausche, A. C.; Abild-Pedersen, F.; Temel, B.; Schjødt, N. C.; Nørskov, J. K.; Studt, F., Activity and Selectivity Trends in Synthesis Gas Conversion to Higher Alcohols. Topics in Catalysis 2014, 57, 135-142. Montemore, M. M.; Medlin, J. W., A Unified Picture of Adsorption on Transition 75. Metals through Different Atoms. Journal of the American Chemical Society 2014, 136, 92729275. 76. Ahn, J.-Y.; Kim, B.-K.; Park, J.-S., Effects of Metal Catalysts on Co-Electrolysis of Steam and Carbon Dioxide. Journal of The Electrochemical Society 2016, 163, F1288-F1293. 77. Studt, F.; Sharafutdinov, I.; Abild-Pedersen, F.; Elkjæ r, C. F.; Hummelshøj, J. S.; Dahl, S.; Chorkendorff, I.; Nørskov, J. K., Discovery of a Ni-Ga Catalyst for Carbon Dioxide Reduction to Methanol. Nature Chemistry 2014, 6, 320. 78. Andersen, M.; Medford, A. J.; Nørskov, J. K.; Reuter, K., Scaling-Relation-Based Analysis of Bifunctional Catalysis: The Case for Homogeneous Bimetallic Alloys. ACS Catalysis 2017, 7, 3960-3967. Jacobsen, C. J. H.; Dahl, S.; Clausen, B. S.; Bahn, S.; Logadottir, A.; Nørskov, J. K., 79. Catalyst Design by Interpolation in the Periodic Table: Bimetallic Ammonia Synthesis Catalysts. Journal of the American Chemical Society 2001, 123, 8404-8405. 80. Andersson, M. P.; Bligaard, T.; Kustov, A.; Larsen, K. E.; Greeley, J.; Johannessen, T.; Christensen, C. H.; Nørskov, J. K., Toward Computational Screening in Heterogeneous Catalysis: Pareto-Optimal Methanation Catalysts. Journal of Catalysis 2006, 239, 501-506. 23 ACS Paragon Plus Environment

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81. Kim-Lohsoontorn, P.; Bae, J., Electrochemical Performance of Solid Oxide Electrolysis Cell Electrodes under High-Temperature Coelectrolysis of Steam and Carbon Dioxide. Journal of Power Sources 2011, 196, 7161-7168.


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Electrocatalysts with Increased Activity for Co-Electrolysis of Steam

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