Researchers Turn to OIPCs for High-Performance Solid Electrolyte Batteries
The surge in renewable energy and EV adoption has dramatically increased the demand for high-performance, all-solid-state batteries offering higher energy density, improved safety, longer lifespan, and reliable operation over a wide temperature range. However, the technology still faces challenges like low ionic conductivity, high interfacial resistance, and particle-particle interfaces in the electrolytes, which cause increased resistance and lower energy density.
Research on high-performance solid electrolytes focused on inorganic and organic solid electrolytes. While inorganic solid electrolytes transport only lithium ions, organic solid electrolytes allow the migration of anions and other species. This causes reactions at the electrodes, resulting in reduced capacity and adverse effects, such as decreased battery performance and lifespan.
Inorganic electrolytes are less prone to side reactions and offer longer battery life and higher performance. Still, oxide-type inorganic solid electrolytes suffer from reduced stability and require high-temperature sintering, whereas sulfide-type electrolytes react with atmospheric moisture, generating toxic hydrogen sulfide gas.
A research team led by Professor Masahiro Yoshizawa-Fujita from the Department of Materials and Life Sciences at Sophia University, along with Takuto Ootahara and Morgan L. Thomas, also from Sophia University, and Kan Hatakeyama-Sato from Tokyo Institute of Technology, used Material Informatics (MI) to explore highly conductive OIPCs, or organic ionic plastic crystals.
“MI leverages informational science, such as statistical science and machine learning, for efficient material development. In this study, we explored OIPCs by combining empirical rules and a machine learning-based MI model,” explains Prof. Yoshizawa-Fujita.
First, the researchers created a training dataset using chemical structures and conductivity data from OIPC-related literature and verified the prediction accuracy of the MI model on two test compounds. The prediction accuracy improves when the training data includes similar chemical structures. They used MI to further narrow down the candidate substances. They successfully synthesized eight new compounds, including six OIPCs and two ionic liquids. One compound exhibited excellent ionic conductivity of 1.75 × 10-4 S cm-1 at 25°C, among the highest reported values.
MI results also revealed new insights into the relationship between ionic radius and ionic conductivity of OIPCs. While conventional empirical rules suggest a lower ionic radius to ionic conductivity ratio is desirable, the newly synthesized compounds indicate that an optimal value exists. The MI model predicted discontinuous changes in the OIPC structure, suggesting that further improvements in prediction accuracy can also enable the prediction of phase transitions.
Their findings were made available online on July 29, 2024, and published in Volume 6, Issue 8 of the ACS Applied Electronic Materials.
