Developing advanced electrolytes has been regarded as a pivotal strategy for enhancing the electrochemical performance of batteries; however, the criteria for electrolyte design remain elusive. In this study, we present an electrolyte design chart reframed through intermolecular interactions. By combining systematic nuclear magnetic resonance, Fourier transform infrared measurements, molecular dynamics (MD) simulations, and machine-learning-assisted classifications, we establish semiquantitative correlations between electrolyte components and the electrochemical reversibility of electrolytes. We propose the equivalent increment of Li salt resulting from functional cosolvent and solvent-solvent interactions for effective electrolyte design and prediction. The controllable regulation of the electrolyte design chart by the properties of solvent-solvent interactions presents varying equivalent effects of increasing Li salt concentrations in different electrolyte systems. Based on this mechanism, we demonstrate highly reversible and nonflammable phosphate-based electrolytes for graphite||NCM811 full cells. The proposed electrolyte design chart, semiquantitatively determined by intermolecular interactions, provides the necessary experimental foundation and basis for the future rapid screening and prediction of electrolytes using machine-learning methods.
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