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用于室温钠硫电池的钒基双原子催化剂的多功能描述符设计

Multi-Functional Descriptor Design of V-Based Double Atomic Catalysts for Room Temperature Sodium-Sulfur Batteries.

作者信息

Cui Kai, Wang Tianshuai, Zhang Qiuyu, Zhang Hepeng

机构信息

Xi'an Key Laboratory of Functional Organic Porous Materials, School of Chemistry and Chemical Engineering, Northwestern Polytechnical University, Xi'an, 710129, P. R. China.

Chongqing Science and Technology Innovation Center of Northwestern Polytechnical University, Chongqing, 401135, P. R. China.

出版信息

Small. 2025 Jan;21(4):e2409866. doi: 10.1002/smll.202409866. Epub 2024 Dec 2.

DOI:10.1002/smll.202409866
PMID:39623865
Abstract

Double atomic catalysts (DACs) have emerged as a promising approach for addressing the shuttle effect and sluggish kinetics in room temperature sodium-sulfur batteries (RT-SSBs). However, identifying optimal metal combinations to meet the multiple requirements for RT-SSBs is challenging. Herein, a method for designing V-based DACs catalysts (DAC-VX, X = metal atoms) is presented by distilling descriptors through first-principle calculations and Multi-Task Learning-Sure Independence Screening and Sparsifying Operator. Theoretical calculations reveal the d-d orbital couplings between V and X significantly influences catalytic performance, highlighting the advantages of DAC-VX systems over SAV in reducing discharge reaction energy barriers and enhancing anchoring ability, although they are less effective in promoting Na₂S decomposition and Na migration. Moreover, a 3D multifunctional descriptor (C, V, R) is developed, enabling simultaneous prediction of sodium polysulfides adsorption energy, NaS decomposition energy barrier, Na migration energy barrier, and discharge reaction energy barrier on DAC-VX, overcoming the limitation of single performance descriptors. Notably, the coexisting SAV and DAC-VCr are identified as an excellent catalyst candidate, offering the lowest discharge reaction energy barrier (0.54 eV), strong anchoring ability, and the lowest decomposition energy barrier for NaS (0.96 eV). This work provides valuable insights for data-driven design of DACs for RT-SSBs.

摘要

双原子催化剂(DACs)已成为解决室温钠硫电池(RT-SSBs)中穿梭效应和缓慢动力学问题的一种有前景的方法。然而,确定满足RT-SSBs多种要求的最佳金属组合具有挑战性。在此,通过第一性原理计算和多任务学习-确定独立筛选和稀疏化算子提取描述符,提出了一种设计基于V的DACs催化剂(DAC-VX,X = 金属原子)的方法。理论计算表明,V和X之间的d-d轨道耦合显著影响催化性能,突出了DAC-VX体系在降低放电反应能垒和增强锚定能力方面优于SAV的优势,尽管它们在促进Na₂S分解和Na迁移方面效果较差。此外,还开发了一种三维多功能描述符(C、V、R),能够同时预测DAC-VX上多硫化钠的吸附能、NaS分解能垒、Na迁移能垒和放电反应能垒,克服了单一性能描述符的局限性。值得注意的是,共存的SAV和DAC-VCr被确定为优秀的催化剂候选物,具有最低的放电反应能垒(0.54 eV)、强大的锚定能力和最低的NaS分解能垒(0.96 eV)。这项工作为RT-SSBs的DACs数据驱动设计提供了有价值的见解。

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