Neural Network Accelerated Investigation of the Dynamic Structure–Performance Relations of Electrochemical CO2 Reduction over SnOx Surfaces

Heterogeneous catalysts, especially metal oxides, play a curial role in improving energy conversion efficiency and production of valuable chemicals. However, the surface structure at the atomic level and the nature of active sites are still ambiguous due to the dynamism of surface structure and difficulty in structure characterization under electrochemical conditions. This paper describes a strategy of the multiscale simulation to investigate the SnOx reduction process and to build a structure–performance relation of SnOx for CO2 electroreduction. Employing high-dimensional neural network potential accelerated molecular dynamics and stochastic surface walking global optimization, coupled with density functional theory calculations, we propose that SnO2 reduction is accompanied by surface reconstruction and charge density redistribution of active sites. A regulatory factor, the net charge, is identified to predict the adsorption capability for key intermediates on active sites. Systematic electronic analyses reveal the origin of the interaction between the adsorbates and the active sites. These findings uncover the quantitative correlation between electronic structure properties and the catalytic performance of SnOx so that Sn sites with moderate charge could achieve the optimally catalytic performance of the CO2 electroreduction to formate.


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For HER, ΔGH* is considered as the major descriptor of HER, and |ΔGH*| is numerically 62 equal to the UL of HER. 63 Therefore, the largest Gibbs free energy change (ΔGmax) of CO2RR to formate is max{ΔGR1, 64 ΔGR2}, of CO2RR to CO is max{ΔGR3, ΔGR4} and of HER is |ΔGR5|.

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Theoretical current density and faradaic efficiency calculation 66 The theoretical current densities of CO2ER and HER can be simulated by the following 67 formulations [3]: Among them, U is the external bias potential which is defined versus the reversible 72 hydrogen electrode (RHE), Nsurf is the number of surface atoms exposed to the different reduced 73 degree surfaces. kB is the Boltzmann constant and T is the reaction temperature. 3.31 × 10 -11 mA·cm -2 , and J0 H2 = 1.28 × 10 -14 mA/cm -2 . As for the theoretical Faradaic efficiency, 80 it can be obtained by the following forms: We counted the number of surface atoms (Nsurf) exposed to the different reduced degree

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We selected last 0.5 ns and every 0.1 ns are used to perform RDFs to compare the equilibrium. It 118 can be found that the trends of five times RFDs are the same, which means the system are in 119 equilibrium and 2 ns is enough to simulate the MD-NN. S10 Figure S4. Energy profile of Sn/SnO2(110) surface NN-MD simulation.

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The insert shows the structure of Sn/SnO2 (110)    In Figure S8 (110). The annealing temperature increased from 300 K to 164 500 K and then cooled down to 300 K.

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In the annealing process, the temperature was increased every 50 K, and the MD-NN is 167 used to optimize the structure for 0.5 ns each time in vacuum. The annealing test did not lead to 168 significant reconstruction of Sn/SnO2(110) (75%), indicating that the structure obtained from the 169 simulations is kinetically and thermodynamically stable. Figure S10. Annealing test for SnOx (Osec). The annealing temperature increased from 300 K to 174 500 K and then cooled down to 300 K.

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In the annealing process, the temperature was increased every 50 K, and the MD-NN is