Chapter 3

The materials discovery process naturally presents a slew of questions about the character of a material. These range from simply trying to learn basic facts about the atomic structure of the compound [1–3] all the way to producing a time-resolved profile of a functional process in operando from start to finish [4]. Spectros-copy is the process of measuring a materials’ response to external electromagnetic stimulus to deduce the properties of interest. Spectroscopy can help to solve problems in experimental design and decision-making (probing response of certain energy domains, measuring particular properties), inference (moving from raw data to the property of interest), and analysis (rationalizing and interpreting the data). These are all classes of problems which artificial intelligence (AI) is well-posed to address.As such, the interface between practitioners in both spectroscopy and AI has sparked a great deal of excitement and research activity. Because characterization is a crucial process of the materials discovery pipeline, insightful pairings of algorithms and experimental protocols can lead to gains in both experimental efficiency and accuracy.These gains may significantly compress the timescales of experimental procedures and help experimentalists learn more in less time or answer questions which were previously inaccessible with a given experimental apparatus. READ MORE