The AMS2023 Release: New Features

TIMESTAMPS
00:00 Introduction
01:36 AMS Overview
02:39 Outline
04:21 Excitations and charge transport (OLED Workflow, qsGW-BSE)
05:48 New methods/functionals in ADF (r2SCAN-3c, Sigma functional)
06:54 New M3GNET Machine Learning Potential
08:42 Machine Learning Potentials in AMS
09:10 Conformers (CREST, RDKit, Boltzmann averaging,...)
10:41 DEMO: M3GNET
12:27 DEMO: Conformers & Boltzmann averaged spectrum
15:11 APPLE & P polarizable force field for electrolytes and polymers
16:23 DEMO: Viscosity with APPLE & P
17:06 ACE Reaction Network
17:51 Multiscale Modeling for Heterogeneous Catalysis
19:34 DEMO: ReaxFF and DFTB parametrization with ParAMS
22:22 ParAMS: Parameter Sensitivity Analysis
23:21 ASE interface
24:34 DEMO: ASE engine / PES exploration
26:25 Quantum Espresso as AMS engine
27:52 Python tips, Jupyter Lab, PLAMS
28:37 DEMO: Jupyter Lab & AMS, Molecular Dynamics
31:36 Licensing for AMS2023
32:06 Thank you, Collaborators, partners, and contributors!
32:32 Summary

Presented by SCM's product manager Matti Hellström.

Release notes: https://www.scm.com/news/ams2023-rele...

More information on AMS - including a free trial - on https://www.scm.com/?utm_source=youtu...