<ul><li>Scientists introduce TrajCast, a transferable and data-efficient framework based on autoregressive equivariant message passing networks for molecular dynamics simulations.</li><li>TrajCast allows for large-scale simulations over extended timescales, enabling the acceleration of materials discovery and exploration of physical phenomena beyond the reach of traditional simulations and experiments.</li><li>Benchmarking of TrajCast demonstrates excellent agreement with reference MD simulations for structural, dynamical, and energetic properties across various systems.</li><li>The open-source implementation of TrajCast is available on GitHub for accessibility and further development.</li></ul>

Force-Free Molecular Dynamics Through Autoregressive Equivariant Networks

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