The SCM team proudly announces the Amsterdam Modeling Suite 2023
Advance your research with the new features and improvements in AMS2023. Selected highlights:
M3GNet, QuantumESPRESSO, ASE
Explore the potential energy surface (PES) and run molecular dynamics (MD) through our AMS driver with the new universal machine learned potential M3GNet-UP or the Quantum ESPRESSO 7.1 engine. You can use any other external method through ASE.
Organic Electronics: faster deposition, excitons, qsGW+BSE
Calculate accurate excitation energies with the very fast quasi-particle self-consistent GW + BSE implementation, deposit molecules faster with GPU-accelerated LAMMPS, and calculate excitonic properties with our OLED workflows.
Reaction discovery, kinetics
Explore possible chemical reactions more efficiently with the improved PES exploration tools, ACE-Reaction, and the MD Nanoreactor. AMS2023 also features a streamlined workflow from reaction exploration through kinetic Monte Carlo to create a machine learned model for reactive Computational Fluid Dynamics.
Additional new functionality
Viscosity and friction coefficients are available through NEMD, many new scripting capabilities and workflows (e.g. filling boxes with molecules, conformers, COSMO-RS) will help you spend less time on setting up and analyzing calculations.
New, accurate density functionals and advanced TDDFT methods have been implemented in ADF, and more robust SCF algorithms are used for BAND and DFTB.
You can now run and control multiple parametrization optimizers in parallel in ParAMS.
See full AMS2023 release notes.