AIBullisharXiv – CS AI · 10h ago7/10
🧠
Teaching Molecular Dynamics to a Non-Autoregressive Ionic Transport Predictor
Researchers propose a non-autoregressive machine learning framework that predicts ionic transport properties—critical for battery and energy materials—200 times faster than existing methods while maintaining accuracy. The approach treats atomic trajectories as optional training data, enabling the model to learn dynamic behavior without sequential inference, addressing a major bottleneck in computational materials science.