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作 者:Xinyi Li Dongxu Jiao Xiao Zhao
出 处:《Renewables》2024年第4期242-249,共8页可再生能源(英文)
基 金:supported by the Jilin Province Science and Technology Development Project(Grant Numbers:YDZJ202401329ZYTS);the Fundamental Research Funds for the Central Universities.
摘 要:Diatomic catalysts as a class of emerging non-noble oxygen reduction reaction(ORR)catalysts show superior activity over their single-atom counterparts.However,the strategies to further enhance their performance remain few and only involve tuning the first-shell coordination environment.Herein we demonstrate the introduction of high-shell heteroatoms(B,O,F,P,and S)around diatomic FeCoN6 sites(HSHA-FeCoN_(6))that results in superior ORR performance over unmodified FeCoN6 ones.Particularly,P-FeCoN_(6) possesses a low ORR overpotential of 0.32 V and a high stability substantiated by calculating formation energy,the dissolution potential of FeCoN_(6),and ab initio molecular dynamics simulations.Machine learning is utilized to understand the underlying descriptor and reveals that the single descriptor insufficiently explains activity trends,necessitating a comprehensive descriptor(Φ)that comprises the average distance between heteroatoms and active center(d)and the adsorption energy of OH*(ΔG_(OH)*).Our work provides a fundamental understanding of high-shell coordination atoms for fine regulation of active centers and guide to the rational design of efficient diatomic ORR catalysts.
关 键 词:oxygen reduction reaction dual-atom catalysts density functional theory machine learning comprehensive descriptors
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