| Abstract Scope |
Directing the evolution of functional materials in extreme environments is a longstanding challenge that requires new approaches to precision synthesis, characterization, and analytics. Our current inability to acquire, interpret, and act on multi-modal signatures limits our control of devices, such as fuel cells, sensors, and electronics, particularly in high-radiation environments. Here I will show how we are operationalizing machine reasoning to induce, probe, and model the evolution of functional materials more richly than ever before. I will describe an artificial intelligence-guided instrument and analytics workflow to quantify radiation effects in materials, which yields improved capacity for discovery and more interpretable analysis of fast-evolving phenomena. I will show how this new approach can accelerate the discovery and design of functional materials in extremes. |