A Dual-cutoff Machine-learned Potential for Condensed Organic Systems Obtained via Uncertainty-guided Active Learning
DCS Computing GmbH and Materials Design, Inc. Announce Collaboration
Protecting the Environment with the Polymer Expert
Webinar: Materials Design presents an interview with a pioneer in computational materials design: Prof. Gregory B. Olson
Understanding and Predicting Hydrogen Embrittlement in Metals Demonstrates the Predictive Power of MLPs for Complex Metallurgical Phenomena
Upcoming: MedeA VASP Training
Alexander Mavromaras and René Windiks to Represent Materials Design at Oslo Battery Days Conference 2024
Webinar: From the Femtoscale to the Mesoscale and Back: An Integrated Multiscale Approach
QuesTek and Materials Design, Inc. Announce Collaboration Partnership
Webinar: Polyvalent Machine-Learned Potential for Cobalt: from Bulk to Nanoparticles
Webinar: Sorption and Diffusion of Small Gas Molecules in Semicrystalline Models: A Molecular-Scale Investigation
Webinar: Advancing Molecular-Scale Modeling: A Novel Approach for Semicrystalline Polymers
Revolutionizing Materials Research: Machine-Learned Interatomic Potentials Unleash the Power of Computational Innovation
Webinar: De Novo Polymer Design Breakthrough
Webinar: Machine-Learned Potentials: Surpassing the Limits of the Ab Initio World without Leaving...
Upcoming Webinar: A Multi-scale Computational Framework for Property Prediction of Fluid Mixtures
On Demand Webinar: A Conversation with Professor Bruce Eichinger, a Pioneer in Computational Polymer
Materials Design’s State-of-the-Art Tools Supporting Tomorrow’s Energy Solutions: Controlled Fusion
