High-throughput combinatorial screening of multi-component electrolyte additives to improve the performance of Li metal secondary batteries.

ABSTRACT: Data-driven material discovery has recently become popular in the field of next-generation secondary batteries. However, it is important to obtain large, high quality data sets to apply data-driven methods such as evolutionary algorithms or Bayesian optimization. Combinatorial high-throughput techniques are an effective approach to obtaining large data sets together with reliable quality. In the present study, we developed a combinatorial high-throughput system (HTS) with a throughput of 400 samples/day. The aim was to identify suitable combinations of additives to improve the performance of lithium metal electrodes for use in lithium batteries. Based on the high-throughput screening of 2002 samples, a specific combination of five additives was selected that drastically improved the coulom

SUBMITTER: Matsuda S 

PROVIDER: S-EPMC6470175 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature