Topical Symposium 4
An exponential growth of computational power and storage density, combined with progress in data science, have brought the information revolution. Data-driven methods are now in ubiquitous use in multiple fields, including life sciences and medicine, economics, social networks, etc. A visionary suggestion of integrating materials development with data-driven methods, materials informatics, is bringing a disruptive paradigm shift in materials science. The framework has the potential to reduce dramatically cost, risks and time for materials discoveries, by an order of magnitude or more. It is capable to produce qualitatively new insights, beyond the reach of conventional research techniques. This topical session will focus on presenting machine learning, artificial intelligence, visualization algorithms and high-throughput methods, as well as best practices of their applications for the knowledge-based materials design. Challenges related to the generation, curation and exploration of big materials data from a wide range of sources, theoretical, as well as experimental will be discussed. The topical session will bring together the broad community of researchers in metallurgical coatings and thin films with leading experts and young researchers developing and applying data-driven methods in materials science.
TS4. Invited Speakers:
- Jakoah Brgoch, University of Houston, USA, “Finding Thermally Robust Superhard Materials with Machine Learning”
- Johanna Rosén, Linköping University, Sweden, “New 3D and 2D Metal Borides from Materials Synthesis Guided by High-Throughput Simulations”
- Kenneth S. Vecchio, University of California San Diego, USA, “High Throughput Approaches for Designing Bulk Materials”