Computations for materials – discovery, design and the role of data

The integration of theory, computation and data is transforming modern materials design and discovery. This symposium brings together global leaders in theory, computation and data driven materials research as well as artificial intelligence experts and renowned experimentalists to present and discuss the latest achievements in the field.

Scope:

The large-scale deployment of first-principles electronic structure calculations in combination with the ever-increasing power and availability of massively parallel supercomputers launched in the last couple of decades an entirely new paradigm in modern materials science. Intuition and serendipity that were the hallmarks of materials discovery and design are now complemented by computationally guided searches and collaborative theory-experiment efforts. Furthermore, availability of the data that is produced in the process and the use of advanced artificial intelligence tools generate unprecedented opportunities to further advance and accelerate design and discovery of novel materials at a scale that has not been seen before.

The main goal of this symposium is to gather leading scientists and engineers from academia, national labs and industry to discuss the status and the outlook for research and applications of computation and data driven materials science, with an emphasis on the experimental validation and the integration of theory, computations, artificial intelligence, and experiment. The common challenges and opportunities will be at the focus of the discussions. The symposium will cover a wide range of studies including advancements in theory, computational methods (including high-throughput and AI, machine (deep) learning), the role of data in modern materials science, and materials synthesis and characterization for accelerated design and discovery.

Hot topics to be covered by the symposium:

• Materials Design and Discovery
• Designing Magnetism and Strongly Correlated Systems
• Metastability and Metastable Materials
• Materials Thermodynamics and Thermochemistry
• Defects, Doping and Transport
• Structure predictions, Applications and Recent Advancements
• The role of data: Data mining and Machine (deep) Learning
• The role of data: The Rise of Experimental Databases
• Modeling of interfaces
• Materials Synthesis and Characterization for Accelerated Design and Discovery