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Xinliang Yu

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Aug 2026

End-to-End Deep Learning Models for Predicting the Electrical Conductivity of Ionic Liquids

This study furnishes an efficient, robust, and COSMO-RS-independent computational toolkit for high-throughput virtual screening of conductive IL candidates and pinpointed temperature, molecular geometry, polarizability distribution, and nitrogen-bearing fragments as dominant conductivity modulators.

Xinliang Yu · 0 citations

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