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- W4386869352 abstract "We have considered different cation and anion based ionic liquids and predicted the electrochemical window of 660 ionic liquid-based electrolytes using machine learning techniques for dual ion battery studies." @default.
- W4386869352 created "2023-09-20" @default.
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- W4386869352 date "2023-01-01" @default.
- W4386869352 modified "2023-10-18" @default.
- W4386869352 title "Molecular Dynamics-Machine Learning Approaches for the Accurate Predictions of Electrochemical Windows of Ionic Liquids Electrolytes for Dual-Ion Batteries" @default.
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- W4386869352 doi "https://doi.org/10.1039/d3ta04310j" @default.
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