DCS Computing GmbH and Materials Design, Inc. Announce Collaboration
Protecting the Environment with the Polymer Expert
Understanding and Predicting Hydrogen Embrittlement in Metals Demonstrates the Predictive Power of MLPs for Complex Metallurgical Phenomena
University of Kazan Develops Highly Accurate Machine-Learned Potential (MLP) for Aluminum Using n2p2 Methodology in MedeA MLPG
Materials Design Scientists, Michele Kotiuga and Volker Eyert invited as working-group members of the Psi-k Network
Materials Design Scientist, Dr. René Windiks, to Present at TechBlick’s Online Event Solid-State Batteries: Innovations, Promising Start-Ups, & Future Roadmap
On Demand Webinar: A Conversation with Professor Bruce Eichinger, a Pioneer in Computational Polymer
MedeA in Publication: Naval Nuclear Lab used MedeA to improve understanding of quantum effects
Materials Design’s State-of-the-Art Tools Supporting Tomorrow’s Energy Solutions: Controlled Fusion
Dr. Benoit Minisini presents a keynote talk at the conference “Matériaux 2022”
Webinar: Interview with Dr. Jozef Bicerano, a world-expert in polymer modeling
Webinar: Δ-Machine Learning beyond DFT: from phase transitions to quantum paraelectricity & CO...
Thursday's UGM Training: Generating and Applying Machine-Learned Potentials with MedeA
Wednesday's UGM Webinar: Atomistic Simulations with High-Dimensional Neural Network Potentials
Tuesday's UGM Webinar: Materials Innovations for Chemical Separations
Upcoming Webinar: Radionuclide Sequestration in MOFs