Accelerating X-ray photoemission spectroscopy measurements using Bayesian super-resolution

Abstract

Abstract This study applies Bayesian super-resolution to X-ray photoelectron spectroscopy (XPS), achieving up to a 20-fold reduction in measurement time while preserving data quality. Traditional XPS, crucial for surface analysis, typically requires extensive measurement durations. Our methodology significantly accelerates the process, as demonstrated with glass and Polytetrafluoroethylene samples, where we reduced measurement times by up to 1/20th without compromising spectral accuracy. This approach decreases noise levels and retains spectral integrity, offering a highly efficient solution for XPS. This innovation is particularly valuable in material science, enabling rapid, reliable surface analysis.