Covers classical force fields, molecular dynamics simulations, and supramolecular properties, including intramolecular and intermolecular interactions.
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.
By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.
Commemorates 50 years of CECAM and the Berni J. Alder CECAM Prize, covering milestones in computational methods, quantum mechanics, slip motion, and more.
