Serial Femtosecond Crystallography

Serial femtosecond crystallography (SFX) uses ultrashort X-ray pulses to determine the structures of macromolecules and materials, but analyzing the massive datasets generated poses significant computational challenges. Current research focuses on developing machine learning (ML) methods, particularly deep neural networks (DNNs), to automate data processing tasks such as Bragg peak finding and structure solution from incomplete or noisy diffraction data. These advancements improve efficiency and enable structure determination from increasingly complex samples, significantly impacting structural biology and materials science by accelerating research and expanding the range of analyzable systems.