A Revised High-Throughput Screening Model on Oxygen Reduction Reaction Over Dual Atom Catalysts Based on the Axial Pre-Adsorption and O2 Adsorption

IF 26 1区 材料科学 Q1 CHEMISTRY, PHYSICAL Advanced Energy Materials Pub Date : 2024-10-16 DOI:10.1002/aenm.202403524
Danyang Li, Panpan Sun, Haoxiang Xu, Jimmy Yun, Dapeng Cao
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Abstract

Dual-atom catalysts (DACs) often exhibit superior electrocatalytic activity, due to their versatile combinations and synergistic effects. However, the neglect of both dynamic axial adsorption of the active site upon working potential and the reactant adsorption as a rate-determining step hinders the establishment of an accurate high-throughput screening strategy. Here, the oxygen reduction reaction (ORR) of 42 kinds of 3d–3d metal DACs by density functional theory (DFT) calculations are systematiclly investigated and demonstrated that the ORR kinetics can be limited by O2* adsorption besides the proton–electron transfer step and the active center of DACs may be reconstructed by axial pre-adsorption of intermediates under working potential. Therefore, the ORR volcano plot is proposed by using both the O2* and OH* adsorption as activity descriptors. Then, a high-throughput screening method is constructed and 38 promising ORR DACs are screened out from 267 DACs containing 3d, 4d, or 5d metals. Importantly, the previously unexplored MnCoN6 DAC is also experimentally synthesized, and exhibits ultrahigh ORR activity outperforming Pt/C, perfectly matching with theoretical prediction. In short, this work not only proposes a volcano plot-based high-throughput screening method but also provides a proof-of-concept of experimental verification of theoretical prediction to heuristically design electrocatalysts for other reactions.

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基于轴向预吸附和氧气吸附的双原子催化剂氧还原反应高通量筛选模型修订版
双原子催化剂(DAC)因其多变的组合和协同效应,通常表现出卓越的电催化活性。然而,由于忽略了活性位点在工作电位时的动态轴向吸附以及作为速率决定步骤的反应物吸附,阻碍了准确的高通量筛选策略的建立。本文通过密度泛函理论(DFT)计算系统地研究了42种3d-3d金属DACs的氧还原反应(ORR),证明了ORR动力学除了质子-电子转移步骤外,还可能受到O2*吸附的限制,并且DACs的活性中心可能在工作电位下通过中间产物的轴向预吸附而重构。因此,利用 O2* 和 OH* 吸附作为活性描述因子,提出了 ORR 火山图。然后,构建了一种高通量筛选方法,并从 267 种含有 3d、4d 或 5d 金属的 DAC 中筛选出 38 种有前景的 ORR DAC。重要的是,还实验合成了之前未曾探索过的 MnCoN6 DAC,并表现出优于 Pt/C 的超高 ORR 活性,与理论预测完全吻合。总之,这项工作不仅提出了一种基于火山图的高通量筛选方法,还为启发式设计其他反应的电催化剂提供了理论预测的实验验证概念。
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来源期刊
Advanced Energy Materials
Advanced Energy Materials CHEMISTRY, PHYSICAL-ENERGY & FUELS
CiteScore
41.90
自引率
4.00%
发文量
889
审稿时长
1.4 months
期刊介绍: Established in 2011, Advanced Energy Materials is an international, interdisciplinary, English-language journal that focuses on materials used in energy harvesting, conversion, and storage. It is regarded as a top-quality journal alongside Advanced Materials, Advanced Functional Materials, and Small. With a 2022 Impact Factor of 27.8, Advanced Energy Materials is considered a prime source for the best energy-related research. The journal covers a wide range of topics in energy-related research, including organic and inorganic photovoltaics, batteries and supercapacitors, fuel cells, hydrogen generation and storage, thermoelectrics, water splitting and photocatalysis, solar fuels and thermosolar power, magnetocalorics, and piezoelectronics. The readership of Advanced Energy Materials includes materials scientists, chemists, physicists, and engineers in both academia and industry. The journal is indexed in various databases and collections, such as Advanced Technologies & Aerospace Database, FIZ Karlsruhe, INSPEC (IET), Science Citation Index Expanded, Technology Collection, and Web of Science, among others.
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