Dear CCL’ers,
The SCM team is thankful to our collaborators with whom we continue to improve our software. We encourage you to try out the Amsterdam Modeling Suite 2023 release: www.scm.com/2023
Enhanced
DFT capabilities
- overcome typical DFT
pitfalls for
excited states with (spin-orbit coupling) qsGW+BSE
- get more accurate energies with the sigma-functional, the
efficient and
robust composite r2SCAN-3c(STO) method, and TASKCC in
combination with the
TASKxc functional
- perform easy and difficult tasks on the potential energy
surfaces with the integrated
of Quantum ESPRESSO 7.1 to our AMS driver
- run many other external codes through the new ASE interface
Improved discovery tools:
- easily explore reaction pathways with the ACE-Reaction
graphical interface
- explore many potential reactions with the Molecular Dynamics
nanoreactor
- create workflows from reaction exploration to kinetic Monte
Carlo, generating
a machine learned surrogate model for CatalyticFOAM
reactor-scale modeling
Furthermore,
AMS2023 also provides improved training and parametrization
methods in ParAMS,
featuring multiple algorithms and stopping and restarting
criteria to find the
best DFTB and ReaxFF parameters.
Chen and Ong’s universal graph neural network machine learning potential M3GNet-UP-2022 can be used with AMS to optimize almost any material, calculate stress tensors, or run non-equilibrium molecular dynamics (NEMD) for tribology and viscosity calculations.
You will
also enjoy many other usability improvements in our python
scripting and graphical
user interfaces.
We look forward to your feedback and suggestions when you have
tested AMS2023: www.scm.com/trial
With kind
regards, on behalf
of the SCM team,
Fedor Goumans
-- Dr. T. P. M. (Fedor) Goumans Chief Customer Officer Software for Chemistry & Materials BV De Boelelaan 1083 1081 HV Amsterdam, The Netherlands https://www.scm.com https://twitter.com/SCM_Amsterdam https://www.linkedin.com/company/software-for-chemistry-&-materials