We will discuss applications of atomic-scale computations and machine learning in oxide materials, metals, plastics, complex functional materials, and ceramics.

The Vienna Ab-initio Simulation Package (VASP) is the most cited electronic structure program for first principles condensed matter simulation. Its robustness, accuracy, and efficiency, together with innovative implementations of machine-learning capabilities, offer a solid basis for multi-scale materials modeling.

This webinar will provide a glimpse into the underlying implementation of machine learning methods for materials simulation in high-performance computing environments, and it will highlight the seamless integration of VASP in the workflows of the premier multi-scale materials modeling environment, MedeA. By making this leading technology accessible to the growing number of computational materials scientists and engineers, we enable solutions for many urgent challenges from sustainable power production to energy storage and communications.


Examples in this webinar will include:

• The quantitative simulation of temperature-induced phase transitions in oxide materials

• The construction of machine-learned potentials for simulations of plastic deformation and crack propagation in metals

• Simulations of complex functional materials

• The formation of grain boundary structures in ceramics