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基于第一性原理的固态电池高附着力界面电解质涂层

Electrolyte Coatings for High Adhesion Interfaces in Solid-State Batteries from First Principles.

作者信息

Ransom Brandi, Ramdas Akash, Lomeli Eder, Fidawi Jad, Sendek Austin, Devereaux Tom, Reed Evan J, Schindler Peter

机构信息

Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, United States.

Aionics, Inc., Palo Alto, California 94301, United States.

出版信息

ACS Appl Mater Interfaces. 2023 Sep 20;15(37):44394-44403. doi: 10.1021/acsami.3c04452. Epub 2023 Sep 8.

Abstract

We introduce an adhesion parameter that enables rapid screening for materials interfaces with high adhesion. This parameter is obtained by density functional theory calculations of individual single-material slabs rather than slabs consisting of combinations of two materials, eliminating the need to calculate all configurations of a prohibitively vast space of possible interface configurations. Cleavage energy calculations are used as an upper bound for electrolyte and coating energies and implemented in an adapted contact angle equation to derive the adhesion parameter. In addition to good adhesion, we impose further constraints in electrochemical stability window, abundance, bulk reactivity, and stability to screen for coating materials for next-generation solid-state batteries. Good adhesion is critical in combating delamination and resistance to lithium diffusivity in solid-state batteries. Here, we identify several promising coating candidates for the LiLaZrO and sulfide electrolyte systems including the previously investigated electrode coating materials LiAlSiO and LiAlO, making them especially attractive for experimental optimization and commercialization.

摘要

我们引入了一个粘附参数,可用于快速筛选具有高粘附性的材料界面。该参数是通过对单个单一材料平板而非由两种材料组合而成的平板进行密度泛函理论计算获得的,从而无需计算可能的界面构型这一极其庞大空间中的所有构型。劈裂能计算用作电解质和涂层能量的上限,并在一个经过调整的接触角方程中实施,以推导粘附参数。除了良好的粘附性外,我们还对电化学稳定性窗口、丰度、体相反应性和稳定性施加进一步限制,以筛选用于下一代固态电池的涂层材料。良好的粘附性对于固态电池中防止分层和抵抗锂扩散至关重要。在此,我们确定了几种适用于LiLaZrO和硫化物电解质体系的有前景的涂层候选材料,包括先前研究过的电极涂层材料LiAlSiO和LiAlO,这使得它们对于实验优化和商业化特别具有吸引力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdf4/10520915/f23b0e144f0e/am3c04452_0002.jpg

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