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用于增强锂硫电池中硫还原的 MXenes 的有效筛选描述符。

Effective Screening Descriptor for MXenes to Enhance Sulfur Reduction in Lithium-Sulfur Batteries.

机构信息

Nano and Heterogeneous Materials Center, School of Materials Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.

State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, China.

出版信息

J Am Chem Soc. 2023 Jun 14;145(23):12601-12608. doi: 10.1021/jacs.3c01834. Epub 2023 Jun 5.

Abstract

MXenes, two-dimensional transition (2D) metal carbides/nitrides, have shown promise as cathodic catalysts for accelerating the conversion of lithium polysulfides (LiPSs) in lithium-sulfur (Li-S) batteries due to their diverse redox-active sites and rapid electron transfer. However, efficiently screening the optimal cathodic catalysts out of thousands of MXenes is challenging. To address this, we developed a model that accurately predicts the thermodynamic energy barrier of the rate-limiting step in Li-S batteries. Our model relates the local chemical reactivity of the MXene sites to the p-band center of the terminations and the electronegativity of subsurface transition metals. The accuracy of the model was verified through density functional theory calculations and contrast experiments in pure and Zn-doping MXenes qualitatively. By utilizing this model, we screened a large library of MXenes (27 types of five-atom-layer MXenes) and identified TiCS, MoCS, and WCS as potential cathodic catalysts for Li-S batteries.

摘要

MXenes(二维过渡金属碳化物/氮化物)由于其多样的氧化还原活性位点和快速的电子转移,有望成为加速锂硫(Li-S)电池中多硫化锂(LiPS)转化的阴极催化剂。然而,要从数千种 MXenes 中筛选出最佳的阴极催化剂是具有挑战性的。为了解决这个问题,我们开发了一个能够准确预测 Li-S 电池中限速步骤热力学能垒的模型。该模型将 MXene 位点的局部化学反应性与端基的 p 带中心和亚表面过渡金属的电负性联系起来。该模型的准确性通过密度泛函理论计算和纯 MXenes 和 Zn 掺杂 MXenes 的对比实验得到了验证。利用该模型,我们筛选了一个大型的 MXenes 库(27 种五原子层 MXenes),并确定 TiCS、MoCS 和 WCS 是 Li-S 电池的潜在阴极催化剂。

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