Materials Design announces MedeA 3.11, delivering significant performance improvements and expanded capabilities to accelerate materials modeling and simulation workflows. The MedeA 3.11 release enhances visualization performance, upgrades key computational engines, and introduces new analysis tools to meet the evolving needs of materials scientists and engineers.

The study explores the use of tantalum (Ta) doping to improve the performance and stability of LiNi0.80Mn0.1Co0.1O2 (NMC811) cathode mate...

MedeA VASP makes it easy to analyze and understand chemical bonding. By leveraging the integrated MedeA Environment you can quantify the...

At-a-Glance: MedeA Flowcharts make it easy to design and conduct systematic computational materials science studies with a visual...

MedeA 3.10 offers an integrated suite of multiscale modeling capabilities with advanced features that empower researchers to explore and des

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 Psik Network

Accelerating Materials Innovation: Connecting Quantum Simulations, Machine Learning, and Mesoscale Modeling to Speed Up Materials Research

Dr. René Windiks has been invited to speak at the online event, "Solid-State Batteries: Innovations, Promising Start-Ups, & Future...

Materials Design Announces the Release of MedeA 3.8 “Micro to Macro”! Materials Design is delighted to announce the latest release of its...

Upcoming Webinar: Machine-Learned Potentials: Surpassing the Limits of the Ab Initio World without Leaving it Behind

Materials Design Announces the Release of MedeA 3.7, Material Performance! Materials Design announces the release of MedeA 3.7 the latest...

A Multi-scale Computational Framework for Property Prediction of Fluid Mixtures Leveraging limited experimental data through simulation...

Please join University of Washington Professor Bruce Eichinger and Materials Design Chief Scientific Officer Dr. Erich Wimmer for an...

Materials Design’s State-of-the-Art Tools Supporting Tomorrow’s Energy Solutions: Controlled Fusion

MedeA 3.6 - highly integrated machine learning methods that extend 'ab initio' accuracy to mesoscale system sizes and time scales...battery

Dr. Benoit Minisini presents a keynote talk at the conference “Matériaux 2022” Materials Design research scientist Dr. Benoit Minisini...

UGM Plenary Speaker Spotlight Tuesday, we host Dr. Jozef Bicerano; founder and President of Bicerano & Associates Consulting, LLC, USA...

UGM Plenary Speaker Spotlight Tuesday, we host Dr. Carla Verdi; Faculty at University of Vienna, Austria and Dr. Georg Kresse; Professor...

Radionuclide Sequestration in MOFs: DFT Method Exploration and a Conceptualization of Graph Neural Networks This webinar will be focused...