AMS2023 Released: New universal ML potential, reaction discovery, kinetics, faster advanced TDDFT methods and much more!
The SCM team proudly announce our new AMS2023 release, with many new features and improvements!
With the new M3GNet universal graph neural network potential, you can explore the potential energy surface (PES) and run molecular dynamics calculations (MD) through the AMS driver.
Improvements in organic electronics include more accurate excitation energies with the implementation of qsGW+BSE in ADF, vibrational polarizabilities and extended OLED workflows.
For catalysis, reactivity, and kinetics, AMS2023 offers several improvements in ChemTraYzer2, PES exploration and characterisation, GUI support for reaction networks discovery with ACE Reaction, and multiscale reactor modeling with pyZacros.
Additional new features and improvements include an interface to ASE and Quantum ESPRESSO, the implementation in ADF of the accurate r2-SCAN-3c and sigma functionals, viscosity and tribology predictions with several new and improved methods (NEMD, Apple&P), and much more! See the full release notes for a more complete list!
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Key conceptsASE kinetics machine learning OLEDs organic electronics Parametrization reaction discovery tribology viscosity