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Updated: Apr 21, 2026

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization

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Accelerated Screening of Electrolyte Solvents for High Safety Batteries Using Machine Learning.

Stephen R Xie¹, Eric C Fonseca^2,3,4,5, Pierce Pettit⁶

¹KBR Inc., Intelligent Systems Division, NASA Ames Research Center, Moffett Field, California 94035, United States.

The Journal of Physical Chemistry. B

|April 20, 2026

Summary

This summary is machine-generated.

Researchers developed a high-throughput screening method using graph neural networks to find safer, non-flammable solvents for batteries. This approach identified thousands of promising, stable, and synthesizable molecules from extensive databases.

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Synthesis of Ionic Liquid Based Electrolytes, Assembly of Li-ion Batteries, and Measurements of Performance at High Temperature

Synthesis of Ionic Liquid Based Electrolytes, Assembly of Li-ion Batteries, and Measurements of Performance at High Temperature

Published on: December 20, 2016

Area of Science:

Materials Science
Computational Chemistry
Chemical Engineering

Background:

Current commercial batteries utilize flammable carbonate-based solvents.
Safer solvent alternatives are crucial for battery safety and performance.

Purpose of the Study:

To develop a high-throughput screening approach for identifying safer nonaqueous battery solvents.
To predict key solvent properties directly from molecular structure.

Main Methods:

Trained graph neural networks using the DIPPR 801 database.
Predicted flash point, melting point, dielectric constant, and liquid viscosity.
Screened over one billion molecules from Mcule and GDB-13 databases.

Main Results:

Identified thousands of dynamically stable and easily synthesizable solvent candidates.
Discovered novel candidates, including food additives and fragrances, for battery applications.
Found one known battery additive among the promising candidates.

Conclusions:

The high-throughput screening approach is effective for discovering safer battery solvent alternatives.
Diverse and readily available candidates were identified through a dual database screening strategy.
This method opens new avenues for developing next-generation battery electrolytes.