合金
分解
星团(航天器)
蒙特卡罗方法
材料科学
热力学
集群扩展
电化学
氨生产
化学
氨
化学物理
动力学蒙特卡罗方法
统计物理学
相对标准差
冶金
作者
C.S. Wang,Xingyu Li,Liang Cao
标识
DOI:10.1021/acs.jpclett.5c03867
摘要
We establish an end-to-end framework that generalizes across alloy families and, applied here to Co–Cu–Fe–Mo–Ni, maps alloy composition to B5 step ensembles (B5 sites) on fcc(211), *N-adsorption energies Δ E (*N) and rates for ammonia decomposition reaction (ADR). A DFT-trained cluster-expansion (CE) model, combined with Metropolis Monte Carlo (MMC) and microkinetics, predicts site-resolved Δ E (*N) and enables composition-wide predictions of site-specific turnover frequencies (TOFs) and surface-averaged activities (⟨TOF⟩). MMC reveals temperature-driven Cu enrichment in the outermost layer, shifting Δ E (*N) toward weaker binding relative to statistically random surfaces and suppresses ⟨TOF⟩. Reducing Cu content systematically enhances activity, whereas Cu-free Co–Fe–Mo–Ni medium-entropy alloys cluster near the volcano maximum and deliver high, composition-robust rates. Site-level analysis shows that the most active B5 sites are Cu-lean and typically multimetallic, consistent with surface-averaged trends. DFT validation on 40 CE-screened high-activity B5 sites confirms predictive fidelity. The framework provides practical, testable design rules─minimize Cu participation at B5 and preserve configurational disorder─and is readily extensible to other alloy families and to both thermochemical and electrochemical reactions.
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