||Recent advancements in computational methods, computing power and materials informatics present us with an exciting opportunity to predictively discover and design materials for a variety of technologically relevant applications. In particular, quantum mechanical ab-initio methods such as density-functional theory simulations, dynamical mean-field theory, quantum Monte-Carlo simulations and time-dependent density functional theory have been pivotal in developing an atomistic-scale fundamental understanding of complex phenomena, and in the discovery and the design of several emerging materials such as – superconductors, topological insulators, magnetic materials, photocatalysts, battery materials, and most recently, quantum materials.
This symposium will cover the state-of-the art in the application as well as the integration of computational methods, particularly ab-initio simulation methods, with experiments and materials informatics applied to the discovery and design of emerging materials.
* Computational discovery and design of correlated electron materials, quantum materials, and superconductors
* Computational discovery and design of magnetic materials and topological insulators
* Application of computational methods for photocatalytic and battery materials discovery and design
* Computational discovery and design of materials for nanoelectronics
* Application of materials informatics approaches such as machine learning, genetic algorithms, and cluster expansion for an accelerated discovery and design of materials