Delves into the intersection of physics and data in machine learning models, covering topics like atomic cluster expansion force fields and unsupervised learning.
Explores Molecular Dynamics simulations for studying cement materials and diffusion processes, covering algorithms, force fields, data analysis, and recommended resources.
Explores Generalized Langevin Equations and their computational implications in molecular dynamics simulations, emphasizing the impact of noise details on particle trajectories.
Commemorates 50 years of CECAM and the Berni J. Alder CECAM Prize, covering milestones in computational methods, quantum mechanics, slip motion, and more.
Explores the evolution of biomolecular simulations, emphasizing accurate models, increased sampling, and the transformative role of simulations in predicting experimental outcomes.
Explores the trends and challenges in modeling complex molecular systems using hierarchical multi-scale approaches, covering length-time scales, atomistic simulations, and force matching techniques.
Covers theory and practical applications of protein folding simulations using molecular dynamics, focusing on solvent effects and analysis of folding dynamics.
