Automated Electrochemical Experiments Team
Member
Shoichi MATSUDA
SAMURAI
Team Leader, Automated Electrochemical Experiments Team, Battery and Cell Materials Field, Research Center for Energy and Environmental Materials (GREEN)
Accelerating the development of electrochemical materials by integrating the automated robotic experiments and data scientific technique
Materials informatics (MI), a data-driven approach for materials discovery, has attracted significant recent attention in the field of electrochemistry. Instead of relying on the experience and intuition of researchers for exploring new materials, the MI approach employs data-science techniques that can, in principle, reduce the time and cost of the discovery of new materials with superior device performance. In fact, virtual screening of compounds has been a particularly active research field; new solid-state materials (primarily crystalline) have been successfully discovered with this strategy by applying computational techniques to conveniently predict desirable properties. By contrast, the MI-based approach has not been frequently employed for liquid-state materials (primarily liquid electrolytes). This is primarily because of the difficulties involved in obtaining sufficient datasets for applying MI techniques. Especially, the complicated mechanism of the formation of the SEI film can induce significant computational costs for preparing the numerous datasets required to apply MI techniques.
An automated robotic experimental system was recently developed by our group for discovering new multi-component electrolytes for rechargeable batteries. By applying data science methods to a series of acquired experimental data groups, we are conducting research with the main purpose of early discovery of innovative electrochemical materials.
1. Material search using electrochemical automatic experiment technology
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 1000 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 integrated with data scientific technique, over 10,000 samples, a specific combination of five additives was selected that drastically improved the coulombic efficiency (CE) of a lithium metal electrode. Importantly, the CE was remarkably decreased merely by removing one of these components, highlighting the synergistic basis of this mixture. The results of this study show that the HTS presented herein is a viable means of accelerating the discovery of ideal yet complex electrolytes with multiple components that are very difficult to identify via conventional bottom-up approach.
2. Development of high energy density storage device
Although the market share for Li-ion batteries (LiBs) has continuously expanded, the limited theoretical energy density of conventional LiBs will no longer meet the advanced energy storage requirements. Lithium–air batteries (LABs) are potential candidates for next-generation rechargeable batteries because of their extremely high theoretical energy density. However, the reported values for the actual energy density of LABs are much lower than those for LiBs, mainly due to the excess amount of electrolyte in the cell. Using the developed self-standing carbon membrane as the positive electrode, a 500-Wh/kg class rechargeable lithium-oxygen battery was fabricated and a repeated discharge/charge cycle was demonstrated at 0.1 C-rate. The results obtained in this study provide new material research directions to realize high energy density rechargeable lithium-oxygen batteries and facilitate their future development.
