Blueprints for automated material discovery using artificial intelligence

Tailor-making materials for a given application is one of the most desired, yet challenging, technological advancements of our century. We need these materials to reach the global sustainability goals of our society, including climate action and affordable clean energy. The success in generating large quantities, high-quality data on materials in the past decade makes the field ready for an abrupt growth toward this aim by applying the tools from the field of artificial intelligence. To enable this, however, we need to develop material-specific machine learning approaches and methodologies. In my talk, I will discuss how we are approaching this challenge by discussing a few success stories from the field of nanoporous materials for energy applications, including quantifying the novelty of new materials, learning from failures, and multi-scale design from atoms to chemical plants.