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Materials Design is Hiring
 

We are seeking a Support and Application Scientist with expertise in computational materials science and classical molecular dynamics to join our dynamic and growing team!

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MedeA Environment

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 600 commercial, government, and academic institutions.
Cheering Crowd

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.”

-Ryoji Asahi 

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

What's New

Hiring: Support and Application Scientist

We are seeking a Support and Application Scientist with expertise in computational materials

science and classical molecular dynamics to join our dynamic and growing team!

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New Publication

Machine Learning for Metallurgy: A Neural-Network Potential for Zirconium


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WEBINAR: Molecular Modeling of Kerogen Structure, Thermodynamic and Transport Properties

Understanding the properties of kerogen is necessary for a better assessment of shale gas and shale oil prospects. It is also essential to understand the physics of in-situ oil shale retorting.

Thanks to the availability of well-tested computational methods, molecular modeling can aid in directing and optimizing the value of costly and time-consuming experimentation. This talk illustrates the capabilities of molecular modeling to predict thermodynamic properties of kerogen as well as the transport of fluids through kerogen...

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Software Release: MedeA 3.4 - Material Control!

MedeA 3.4 includes groundbreaking Machine-Learned Potential (MLP) capabilities, including neural network-based potential models and a fully integrated MLP generator. With these capabilities, users can create highly accurate MLP descriptions of ab initio training sets for use with the LAMMPS simulati...

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