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前进之路:应对计算估计阴极材料中锂扩散的挑战。

Path ahead: Tackling the Challenge of Computationally Estimating Lithium Diffusion in Cathode Materials.

作者信息

Bonometti Laura, Daga Loredana E, Rocca Riccardo, Marana Naiara L, Casassa Silvia, D'Amore Maddalena, Laasonen Kari, Petit Martin, Silveri Fabrizio, Sgroi Mauro F, Ferrari Anna M, Maschio Lorenzo

机构信息

Dipartimento di Chimica and NIS Centre, Università di Torino, Via P. Giuria 5, Torino 10125, Italy.

Dipartimento di Chimica, Università di Torino, Via P. Giuria 5, Torino 10125, Italy.

出版信息

J Phys Chem C Nanomater Interfaces. 2024 Jul 11;128(29):11979-11988. doi: 10.1021/acs.jpcc.4c00960. eCollection 2024 Jul 25.

Abstract

In the roadmap toward designing new and improved materials for Lithium ion batteries, the ability to estimate the diffusion coefficient of Li atoms in electrodes, and eventually solid-state electrolytes, is key. Nevertheless, as of today, accurate prediction through computational tools remains challenging. Its experimental measurement does not appear to be much easier. In this work, we devise a computational protocol for the determination of the Li-migration energy barrier and diffusion coefficient, focusing on a common cathode material such as LiNiO, which represents a prototype of the widely adopted NMC (LiNi Mn Co O) class of materials. Different methodologies are exploited, combining ab initio metadynamics, path sampling, and density functional theory. Furthermore, we propose a novel, fast, and simple 1D approximation for the estimation of the effective frequency. The outlined computational protocol aims to be generally applicable to Lithium diffusion in other materials and components for batteries, including anodes and solid electrolytes.

摘要

在设计新型高性能锂离子电池材料的发展道路上,能够估算锂原子在电极以及最终在固态电解质中的扩散系数是关键所在。然而,截至目前,通过计算工具进行准确预测仍然具有挑战性。其实验测量似乎也并非易事。在这项工作中,我们设计了一种计算方法来确定锂迁移能垒和扩散系数,重点关注一种常见的阴极材料,如LiNiO,它是广泛采用的NMC(LiNiMnCoO)类材料的原型。我们采用了不同的方法,将从头算元动力学、路径采样和密度泛函理论相结合。此外,我们还提出了一种新颖、快速且简单的一维近似方法来估算有效频率。所概述的计算方法旨在普遍适用于锂在电池其他材料和组件(包括阳极和固态电解质)中的扩散。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d427/11285369/9a68c78f295b/jp4c00960_0001.jpg

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