A structure-preserving neural density functional for the ions of a polymer electrolyte
The research developed a neural density functional to predict ion structure in polymer electrolytes while preserving fundamental physical symmetries like spatial invariance and thermodynamic integrability. Trained only on molecular dynamics force profiles, this method accurately predicts bulk structure factors and long-wavelength number responses, outperforming other neural architectures with less training data.