Webinar: Unlock the Code - MedeA 2.22 Software Release Highlights
November 17, 2017
Explore the MedeA 2.22 atomistic simulation environment.
This free webinar lets you explore the new release of the atomistic simulation environment MedeA. Learn about exciting new features, extensions to existing functionality, and enhanced compute performance.
MedeA 2.22 includes:
Updated versions of compute engines VASP, GIBBS, LAMMPS, GAUSSIAN, and MOPAC, accelerating performance and providing many new properties and features
Builder capability extensions – enhancing model construction and accelerating simulation studies
Updates to the MedeA Forcefield library with many new parameter sets and extensions broadening coverage and improving simulation accuracy for many materials
Database updates and enhancements providing access to the latest in materials science information
The release of MedeA 2.22 allows the user to:
Benefit from using updated versions of all the MedeA environment compute engines, with many new features and incorporating improvements in computing performance.
VASP 5.4.4 automated protocols provide response functions including electron-hole excitonic effects, accurate correlation energies from the random phase approximation, as well as new metaGGA and van der Waals functionals, efficiently and straightforwardly delivering advanced calculations.
GIBBS 9.6.2 handles flexible multi-cyclic molecules opening new perspectives in property prediction for compounds of interest to a broad range of industries.
MedeA-UNCLE cluster-expansion engine extends the predictive power and accuracy of ab-initio methods to efficient large scale modeling of disordered systems, and now enables simulations for multi component alloys and surfaces, permitting the study of high-entropy alloys, surface segregation and surface coverage of adsorbents.
Efficiently build complex models, with the extension of the capabilities of the Thermoset Builder to allow control over relative probabilities of crosslink formation at sites capable of reacting multiple times and improve creation of large numbers of thermosets using Flowcharts and High-Throughput features.