Npj Comput. Mater.: 高熵合金催化剂—吸附能的线性关系
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高温合金的发展为设计新的、性能可调的催化剂材料提供了崭新的机遇。借助于其异质表面化学性质，高温合金可同时激活不同的化学反应，将构成催化和能源应用的范式转变。同时，高温合金的成分丰富，也可以实现催化剂活性、选择性和稳定性的优化。作为催化反应的重要一步，高温合金表面上原子和分子的吸附能在前面得到了广泛研究，如基于密度泛函理论的理论计算和机器学习方法等，但迄今研究还不够清楚。更重要的是，金属表面原子和分子的吸附能存在线性关系，而采取策略打破这种关系是当前催化领域的一个研究热点。
Alloying has been proposed to circumvent scaling relations between the adsorption energies thus allowing for the complete optimization of multistep reactions. Herein the fidelity of scaling rules on high-entropy alloy (HEA) surfaces is assessed focusing on hydrogen-containing molecules, *AHx for A = C and N (x = 0, 1, 2, 3), A = S (x = 0, 1, 2) and A = O (x = 0, 1). Using an adsorbate- and site-specific deep learning model to rapidly compute the adsorption energies on CoMoFeNiCu HEA surfaces, the energies of *AHx and *A are shown to be linearly correlated if *A and *AHx have identical adsorption site symmetry. However, a local linear dependence emerges between the configuration-averaged adsorption energies irrespective of the site symmetry. Although these correlations represent a weaker form of the scaling relationships, they are sufficient to prohibit the optimization of multistep reactions. The underpinning of this behavior is twofold (1) the nearsightedness principle and (2) the narrow distribution of the adsorption energies around the mean-field value. While the nearsightedness is general for all electronic systems, the second criterion applies in HEAs with relatively strong reactive elements. The present findings strongly suggest that alloys may not generally enable the breaking of scaling relationships.
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