As global interest in renewable energy continues to increase, there has been a pressing need for developing novel energy storage devices based on organic electrode materials that can overcome the shortcomings of the current lithium-ion batteries. One critical challenge for this quest is to find materials whose redox potential (RP) meets specific design targets.

In our recent study below, we proposed a computational framework for addressing this challenge:

Hyun-Myung Woo, Omar Allam, Junhe Chen, Seung Soon Jang, Byung- Jun Yoon, “Optimal high-throughput virtual screening pipeline for efficient selection of redox- active organic materials,” iScience (2023), doi: https://doi.org/10.1016/j.isci.2022.105735

Given a high-fidelity model for estimating the RP of a given material, we showed how a set of surrogate models with different accuracy and complexity may be designed to construct a highly accurate and efficient HTVS pipeline. The performance of the screening campaigns based on the constructed HTVS pipeline can be optimized by designing the optimal screening policy, which enables rapid screening of organic materials that satisfy the desired criteria. We demonstrated that the proposed HTVS pipeline construction and operation strategies can substantially enhance the overall screening throughput.

Further details of this study can be found in iScience.