The Most Comprehensive Atomistic Modeling and Simulation Software for Materials Science
MedeA is the leading environment for the atomistic simulation of materials. MedeA enables professional, day-to-day deployment of atomic-scale and nano-scale computations for materials engineering, materials optimization and materials discovery. In MedeA, world-class simulation engines are integrated with elaborate property prediction modules, experimental databases, structure builders and analysis tools, all in one user-friendly environment.
Trusted by thousands of users in over 700 commercial, government, and academic institutions.
Computational material science tools have revolutionized the evaluation of neutron thermal scattering laws. All of the new thermal scattering laws including in the new US national ENDF/B-VIII.0 nuclear data library were developed using DFT or MD simulations. The vast majority were developed by MedeA users using VASP, PHONON, and LAMMPS.
-Michael L. Zerkle, Ph.D., Senior Advisor,
Reactor Physics Methods Development,
Naval Nuclear Laboratory
“I like MedeA, it gives me more time to think.”
Toyota Central Research and Development Laboratories, Nagoya, Japan
We are currently working with industrial partners to improve materials used in photodetectors. MedeA is ideal for what we need, as it allows me to study a wide range of material properties. The interface allows me to simulate what I want to, and the software comes with lots of built in materials which is really helpful. The MedeA support team is also excellent, in case of any problems. I highly recommend MedeA!
-Dr Jamie Williams, Post Doctoral Research Associate, Department of Physics and Astronomy,
University of Leicester, United Kingdom
A Report on the Advanced Simulation Engineering Tool
A recent report details the extraordinary work carried out at the Idaho National Laboratory (INL) High Performance Computing (HPC) facility. In excess of one billion core hours, delivered in less than 12 months, provided by this leading supercomputer facility have driven radically improved understanding in nuclear materials, energy storage, andrenewable energy. A highlight of the report is the contribution of Jonathan Wormald, Richard Sm...
New Application Note: The structural Phase Transition in Ti Investigated Using a Machine-learned Interatomic Potential
This application note describes the generation of a machine-learned potential (MLP) using the highly automated MedeA Machine-Learned Potential Generator (MLPG). Our MLPG inputs a training set consisting of results from a set of MedeA VASP calculations selected by the user and generates a machine-learned potential for use with MedeA LAMMPS...
Thank you for subscribing.
Check your entries