文献类型：期刊文献

英文题名：Rationalizing the d-Band Model from Theory to Practice in Catalyst Design

作者：Chen, Wenyao[1];Qian, Gang[1];Wang, Haifeng[2,3];Chen, De[1,4];Zhou, Xinggui[1];Yuan, Weikang[1];Duan, Xuezhi[1]

机构：[1]East China Univ Sci & Technol, State Key Lab Chem Engn & Low Carbon Technol, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Ctr Computat Chem, State Key Lab Green Chem Engn & Ind Catalysis, Shanghai 200237, Peoples R China;[3]East China Univ Sci & Technol, Res Inst Ind Catalysis, Shanghai 200237, Peoples R China;[4]Norwegian Univ Sci & Technol, Dept Chem Engn, N-7491 Trondheim, Norway

年份：2025

卷号：147

期号：51

起止页码：46729

外文期刊名：JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

收录：;EI(收录号：20255219800761);WOS:【SCI-EXPANDED(收录号:WOS:001639272800001)】；

基金：This work was financially supported by the National Key R&D Program of China (2024YFA1510303), the Natural Science Foundation of China (22478107, 22038003, 22178100, 22178101, and U22B20141), the Shanghai Pilot Program for Basic Research (22TQ1400100-15), the Shanghai Rising-Star Program (24QA2701900), the Innovation Program of Shanghai Municipal Education Commission, and the Shanghai Science and Technology Innovation Action Plan (22JC1403800).

语种：英文

外文关键词：Catalysts - Describing functions - Design - Learning systems

摘要：Catalyst design remains central to the industrial implementation of catalytic processes, and the descriptor-based approach marks a pivotal milestone toward more rational design strategies. Among various descriptors, the d-band has emerged as one of the most thoroughly investigated and theoretically grounded concepts, underpinning fundamental models of adsorbate-metal interactions. Despite substantial theoretical progress and numerous in-depth reviews, its practical application in catalyst design remains nontrivial due to the inherent complexity and variability of real catalytic systems. Hence, this Perspective is rooted in emerging tools and real-world catalysts, highlighting new insights rather than rehashing classical theory on the modulation, characterization, and interpretation of the metal d-band structure. We begin by revisiting the classical d-band model with constant d-band filling (rigid band) and elucidate how strain and ligand effects modulate the d-band center, thereby tuning catalytic performance via a bottom-up strategy combined with machine learning. We then discuss recent progress in experimental techniques that enable independent characterization of d-band center and filling. Finally, we examine the conflicting interpretations frequently reported in the literature and seek to contextualize them within a flexible-band framework that accounts for variable d-band filling, with the goal of developing a multidescriptor approach capable of effectively guiding catalyst design under realistic conditions. This Perspective aims to clarify recent advances, identify key challenges, and provide a forward-looking outlook for descriptor-based catalyst design.