Predicting Damage Growth using Multimode Characterization and Machine Learning

Executive Summary

We will develop a non-destructive, diagnostics-based strategy to predict the growth of laser-induced damage on optics by leveraging multi-modal characterization of damage sites and machine learning techniques. This effort will directly impact the long-term operational sustainability of fusion-class lasers, enabling them to operate more effectively, at higher energies.