Data Party THU
Data Party THU
Apr 12, 2026 · Artificial Intelligence

Physics‑Informed GP Model Enables Near‑Infinite Stability in Hot Molecular Dynamics

Researchers from the University of Manchester introduced a physics‑informed Gaussian Process atomic energy model that, unlike traditional machine‑learning potentials, remains stable in molecular dynamics simulations up to 1000 K for tens of nanoseconds, demonstrating robust force predictions and reliable long‑time behavior across diverse molecules.

Gaussian ProcessMachine Learning Potentialscomputational chemistry
0 likes · 7 min read
Physics‑Informed GP Model Enables Near‑Infinite Stability in Hot Molecular Dynamics
HyperAI Super Neural
HyperAI Super Neural
Mar 16, 2026 · Artificial Intelligence

AI‑Driven Quantum Refinement: AQuaRef Enables Full‑Atom Protein Model Optimization with Quantum Constraints

A collaborative team from Carnegie Mellon, Wrocław, and Florida universities introduced AQuaRef, an AI‑powered quantum refinement method that leverages the AIMNet2 machine‑learning potential to achieve near‑classical‑force‑field speed while closely approximating quantum‑mechanical results for full‑atom protein models, outperforming traditional restraints on low‑resolution structures.

AIAIMNet2Machine Learning Potentials
0 likes · 16 min read
AI‑Driven Quantum Refinement: AQuaRef Enables Full‑Atom Protein Model Optimization with Quantum Constraints