Highlights with ‘machine learning’

Solving arson cases with AI and thermodynamics (COSMO-RS)

In arson cases, evidence such as DNA or fingerprints is often destroyed. One of the most important evidence modalities left is relating fire accelerants to a suspect. When gasoline is used as accelerant, the aim...

Graphical user interface for AMS2020 | live Q&A

Last but not least in the demonstration of features by SCM staff, Olivier will demonstrate the graphical user interface to our new AMS2020 release. He will give tips & tricks on using the new features in...

New in AMS2020: QM/MM, G0W0, ML Potentials | live Q&A

Fedor will demonstrate a few new features in our 2020 release: machine learning potentials, the hybrid engine for QM/MM and multi-layer calculations, G0W0, and the new ADF input structure. See also the full release notes....

AMS2020 released: ML Potentials, G0W0, QM/MM, multiple COSMO-RS species

The SCM team is proud to present the Amsterdam Modeling Suite 2020. Read the release notes for more details. A fast G0W0 and RPA implementation is available in ADF. Furthermore, ADF has been fully integrated...

Machine Learning Potentials with AMS2020: live Q&A

Matti will demonstrate how easy it is with the 2020 release of the Amsterdam Modeling Suite to install the machine learning backends to the AMS driver, and run quick geometry optimizations of organic molecules with...

SCM at the F19MRS in Boston

Going to the 2019 MRS fall meeting 1-5 December 2019? Check out Matti’s talk on Machine Learning potentials for next generation materials modeling -his EU project MaLeR– on 3 December, 9.45am at Hynes 210. Thomas...

SCM at TechConnect Boston

ReaxPro, the recent H2020 EU project led by SCM, aims to bring together atomistic, mesoscale, and macroscale simulation tools into a platform for multiscale modeling of reactive materials and processes. We are proud to announce...

Matti Hellström joins SCM to improve ReaxFF with machine learning

The SCM staff is very happy to welcome Matti as a Marie Curie fellow to combine the accuracy of machine learning with the flexibility and transferability of ReaxFF in the EU funded Machine Learning applied...