Molecular dynamics simulations offer an atomistic window into the structure, dynamics and properties of nanostructured materials by numerically integrating the equations of motion for interacting ...

Machine learning potentials represent a transformative bridge between empirical force fields and fully fledged quantum-mechanical simulations, offering near ab initio accuracy at a fraction of the ...

Nanoscale wetting of water has stumped physicists for over a century. University of Tokyo simulations now reveal why: water's ...

Simulating how atoms and molecules move over time is a central challenge in computational chemistry and materials science. Classical machine learning approaches to molecular dynamics (MD) encode ...

Researchers at the Center for Computational Sciences, University of Tsukuba, have developed an accessible platform to overcome the limitations of conventional static docking simulations, offering new ...