Accelerating energy molecule discovery by integrating high-throughput virtual screening and artificial intelligence

February 11th 2022

The growing production of renewable, but intermittent electricity, gives rise to a need for new electroactive molecules and materials that can be used in batteries for energy storage.

The discovery of new molecules and the engineering of the existing ones, both in order to achieve better battery performance, have a vital role in making aqueous redox flow batteries (ARFBs) a competitive technology for grid-scale electricity storage.

Image credit: Qi Zhang / AMD group

The discovery and development of active materials that would satisfy multiple battery-relevant features, such as suitable redox potentials, high solubility, good stability, and safety is not a straightforward task. High-throughput virtual screening (HTVS) provides a way for systematically exploring a large number of molecules and estimating their battery-relevant properties. In this way, the most promising candidate molecules can be identified and decided for further experimental characterization and testing.

Computational researchers of DIFFER’s Autonomous Energy Materials Discovery (AMD) research group have partnered with experimental researchers from Green Energy Storage (Italy) to perform a HTVS-guided experimental study for the large-scale exploration of electroactive molecules for ARFBs. Screening a virtual library of 3,257 redox pairs, a total of 205 compounds were identified in the computer that would potentially lead to improvements in ARFB output voltage and energy density. By means of solubility testing and electrochemical characterization of the directly purchasable compounds, molecules that show promise for use in ARFBs have been identified.

Team leader Süleyman Er: “In addition to finding good molecules for electrochemical energy storage, in this productively collaborative study, we showed that the data-driven material design is a highly effective strategy for an accelerated exploration of the chemical space of molecules.”

Qi Zhang, Abhishek Khetan, Elif Sorkun, Fang Niu, Andrea Loss, Ilaria Pucher, and Süleyman Er. Data-driven discovery of small electroactive molecules for energy storage in aqueous redox flow batteries, Energy Storage Materials (2022)

More information
DIFFER group Autonomous Energy Materials Discovery
Website Green Energy Storage