利用可解释的数据驱动方法提升目标正极负载下的电解液性能
Improving Electrolyte Performance for Target Cathode Loading Using Interpretable Data-Driven Approach
AI总结：
本文提出一种可解释的数据驱动方法，通过图深度学习模型优化4溶剂4盐电解液配方，使新型卤间电池在目标正极负载下比容量额外提升20%。
摘要：
电池中，尤其是基于转化反应的电池，期望更高的活性电极材料负载，以提高能量密度和成本效率。然而，增加电极中活性材料的负载可能会因内阻、穿梭效应和寄生副反应而导致显著的性能衰减，而通过兼容的电解液设计可以在一定程度上缓解这一问题。在本工作中，利用数据驱动方法为一种新型卤间电池寻找针对目标正极负载定制的高性能电解液配方。针对一种基于多电子氧化还原反应的新型卤间电池，实验设计了一种由4种溶剂和4种盐组成的电解液。使用具有可变电解液组成和活性正极负载的实验数据集来训练一个基于图的深度学习模型，该模型将电池材料设计中的变化变量映射到其比容量。训练后的模型被用于进一步优化电解液配方组成，以通过双重方法提升目标正极负载下的电池容量：大规模筛选和解读不同正极负载下的电解液设计原则。结果表明，该数据驱动方法使电池的比容量在实验优化所得容量的基础上额外提升了20%。
英文摘要：
Higher loading of active electrode materials is desired in batteries, especially those based on conversion reactions, for enhanced energy density and cost efficiency. However, increasing active material loading in electrodes can cause significant performance depreciation due to internal resistance, shuttling, and parasitic side reactions, which can be alleviated to a certain extent by a compatible design of electrolytes. In this work, a data-driven approach is leveraged to find a high-performing electrolyte formulation for a novel interhalogen battery custom to the target cathode loading. An electrolyte design consisting of 4 solvents and 4 salts is experimentally devised for a novel interhalogen battery based on a multi-electron redox reaction. The experimental dataset with variable electrolyte compositions and active cathode loading, is used to train a graph-based deep learning model mapping changing variables in the battery's material design to its specific capacity. The trained model is used to further optimize the electrolyte formulation compositions for enhancing the battery capacity at a target cathode loading by a two-fold approach: large-scale screening and interpreting electrolyte design principles for different cathode loadings. The data-driven approach is demonstrated to bring about an additional 20% increment in the specific capacity of the battery over capacities obtained from the experimental optimization.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
