Webinar: Developing and Applying Correlative Model

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發佈日期 2018-11-16


Webinar: Developing and Applying Correlative Model






 

Webinar: Developing and Applying Correlative Models in Materials Science


Join this months webinar to:

  • Review a variety of correlative models and their role in materials science research and development
  • View practical interactive correlative model construction
  • See how correlative models focus your research and increase your efficiency

REGISTER NOW

Correlative models provide materials properties and insights that accelerate problem solving and optimization. MedeA QT provides interactive correlative modeling methods that leverage the descriptors and properties made accessible by the MedeA Environment. This webinar focuses on the development and application of correlative models in MedeA.

Tue, November 28th: 
2 am Taiwan (CST) 

Wed, November 28th:
11 pm Taiwan (CST) 

Thu, November 29th:
3 pm Taiwan (CST) 
 

 

 

Webinar Hosts

 

Clive M. Freeman, Ph.D.

Clive has authored over 50 scientific articles and publications examining a broad range of molecular, materials, sensor, catalyst, and sorption applications.
 

 

Dr. Marianna Yiannourakou 

Dr. Yiannourakou is a senior research scientist and developer at Materials Design. Her focus is on property prediction of fluids (soft matter in general) using classical molecular simulations.

 

 

 

 

 

MedeA The Atomistic Modeling and Simulation Environment
 

MedeA is the leading software environment for atomistic materials modeling, used by thousands of customers at more than 500 institutions worldwide. Scientists and engineers in industry and research institutions rely on MedeA to simulate materials properties and understand diverse phenomena. MedeA enables users to create better products through the accurate simulation of materials properties.

MedeA integrates world-leading structural databases (totaling over 980,000 entries), electronic structure programs (VASP
GaussianMOPAC), molecular dynamics (LAMMPS), and Monte Carlo methods (GIBBS) with a host of powerful building, editing, and analysis tools in a unified environment allowing the creation of efficient workflows. Its innovative high-throughput (HT) capabilities enable the exploitation of computational resources.


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