A Raman Spectroscopy Shortcut That Could Speed Up Battery Material Discovery
A machine learning pipeline can predict Raman spectra for solid battery electrolytes at near-quantum accuracy and a fraction of the computational cost, revealing that low-frequency Raman features reliably flag the liquid-like ion motion needed for high performance.
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