Suppr超能文献

揭示电荷转移在BX片(X = As、P、Sb)上单原子催化剂增强电化学固氮中的作用。

Unveiling the Role of Charge Transfer in Enhanced Electrochemical Nitrogen Fixation at Single-Atom Catalysts on BX Sheets (X = As, P, Sb).

作者信息

Zafari Mohammad, Umer Muhammad, Nissimagoudar Arun S, Anand Rohit, Ha Miran, Umer Sohaib, Lee Geunsik, Kim Kwang S

机构信息

Center for Superfunctional Materials, Department of Chemistry, Ulsan National Institute of Science and Technology (UNIST), 50 UNIST-gil, Ulsan 44919, Republic of Korea.

出版信息

J Phys Chem Lett. 2022 May 26;13(20):4530-4537. doi: 10.1021/acs.jpclett.2c00918. Epub 2022 May 16.

Abstract

To tune single-atom catalysts (SACs) for effective nitrogen reduction reaction (NRR), we investigate various transition metals implanted on boron-arsenide (BAs), boron-phosphide (BP), and boron-antimony (BSb) using density functional theory (DFT). Interestingly, W-BAs shows high catalytic activity and excellent selectivity with an insignificant barrier of only 0.05 eV along the distal pathway and a surmountable kinetic barrier of 0.34 eV. The W-BSb and Mo-BSb exhibit high performances with limiting potentials of -0.19 and -0.34 V. The Bader-charge descriptor reveals that the charge transfers from substrate to *NNH in the first protonation step and from *NH to substrate in the last protonation step, circumventing a big hurdle in NRR by achieving negative free energy change of *NH to *NH. Furthermore, machine learning (ML) descriptors are introduced to reduce computational cost. Our rational design meets the three critical prerequisites of chemisorbing N molecules, stabilizing *NNH, and destabilizing *NH adsorbates for high-efficiency NRR.

摘要

为了调整单原子催化剂(SACs)以实现有效的氮还原反应(NRR),我们使用密度泛函理论(DFT)研究了负载在砷化硼(BAs)、磷化硼(BP)和锑化硼(BSb)上的各种过渡金属。有趣的是,W-BAs表现出高催化活性和优异的选择性,沿着远端路径的势垒仅为0.05 eV,动力学势垒为0.34 eV,易于克服。W-BSb和Mo-BSb表现出高性能,极限电位分别为-0.19和-0.34 V。Bader电荷描述符表明,在第一步质子化过程中电荷从底物转移到NNH,在最后一步质子化过程中从NH转移到底物,通过实现NH到NH的负自由能变化,克服了NRR中的一个大障碍。此外,引入了机器学习(ML)描述符以降低计算成本。我们的合理设计满足了化学吸附N分子、稳定NNH和使NH吸附质不稳定以实现高效NRR的三个关键先决条件。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验