2022
DOI: 10.1002/anie.202201913
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Nature of the Active Sites of Copper Zinc Catalysts for Carbon Dioxide Electroreduction

Abstract: The electrochemical CO2 reduction (CO2ER) to multi‐carbon chemical feedstocks over Cu‐based catalysts is of considerable attraction but suffers with the ambiguous nature of active sites, which hinder the rational design of catalysts and large‐scale industrialization. This paper describes a large‐scale simulation to obtain realistic CuZn nanoparticle models and the atom‐level structure of active sites for C2+ products on CuZn catalysts in CO2ER, combining neural network based global optimization and density fun… Show more

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Cited by 49 publications
(25 citation statements)
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“…(b) Construction of thermodynamically stable models for CuZn NPs and high-throughput screening of surface C–C coupling active sites. Reproduced with permission from ref . Copyright 2022 John Wiley and Sons.…”
Section: Design and Synthesis Of Copper-based Catalystsmentioning
confidence: 99%
See 1 more Smart Citation
“…(b) Construction of thermodynamically stable models for CuZn NPs and high-throughput screening of surface C–C coupling active sites. Reproduced with permission from ref . Copyright 2022 John Wiley and Sons.…”
Section: Design and Synthesis Of Copper-based Catalystsmentioning
confidence: 99%
“…Following this research framework, we also identified the active sites for C 2+ products on the surface of CuZn catalysts. Neural network-accelerated global optimization based on an algorithm of stochastic surface walking (NN-SSW) was utilized to search the global minima (GM) of CuZn nanoparticles (NPs, Figure b) . Using a high-throughput calculation method based on the NN potential, more than 2000 surface sites were evaluated, and 2 types of active sites were clarified, namely, the balanced Cu–Zn sites and Zn-heavy Cu–Zn sites.…”
Section: Design and Synthesis Of Copper-based Catalystsmentioning
confidence: 99%
“…The root-mean-square errors (RMSE) of CuZnCHO.pot and CuAgAu.pot potentials are 2.991 and 3.591 meV/atom, respectively. The comparison between NN potential predicted adsorption energy of *CO and *COOH (Figure S1) on Cu-based NPs and that from density functional theory (DFT) calculation has been reported in our recent publication, and the results indicate that the accuracy of NN potential can reach the level of DFT calculation such that this can be used for high-throughput active sites screening.…”
Section: Models and Methodsmentioning
confidence: 60%
“…Sargent et al [101] investigated 244 different intermetallic crystals containing copper from the Materials Project and enumerated 12,229 surfaces and 228,969 adsorption sites based on these crystals to train a machine learning model, and finally proved CuÀ Al as the most promising candidate for CO 2 RR (Figure 7a). In addition, Gong et al [102] obtained realistic active sites on CuZn catalysts at the atom level through a neural network based global optimization combined with density functional theory calculations. There are two kinds of typical active sites, which are balanced CuÀ Zn sites and Zn-heavy CuÀ Zn sites, respectively.…”
Section: Advanced Theoretical Methodsmentioning
confidence: 99%