Integrating material science and data science to create innovative materials.
Materials exploration / Structure search / Huge computational space / Quantum computing / Quantum annealer / Hyperthermophysical materials / Robotics / Machine learning / Lab automation / Experiment automation
Materials Informatics (MI) is a novel approach that aims to accelerate materials development by bridging materials science and data science. At the core of this approach is the feature to identify and utilize correlations within data, not just relying on the principles of physics and chemistry alone. This enables to fill gaps between available data and composition or structure of high performance materials, leading to the identification of "optimal" materials. By adopting a data-driven approach alongside traditional insight-based methods, more efficient materials development becomes achievable. We utilize MI to develop materials with optimal thermal properties such as thermal conductivity, thermoelectricity, and thermal radiation. Additionally, we are working on integrating robotics and machine learning to automate materials experiments in the real world.