PyMESpec: a Python toolbox for automated modulation excitation spectroscopic data analysis and transient experiments

Abstract

Recent advances in laboratory automation have created a growing need for efficient and scalable tools to process experimental data without human intervention. Of great interest to the catalysis community is the analysis of time-resolved spectroscopic data, which can capture transients and identify highly active minority species. One such technique is modulation excitation spectroscopy (MES). Modulation produces large datasets unsuitable for manual processing. We introduce the python modulation excitation spectroscopy (PyMESpec) toolkit, an open-source library for analyzing MES experiments. PyMESpec offers a fast and flexible baseline correction, phase-sensitive detection (PSD), chemometric deconvolution, and automated reaction rate extraction. PyMESpec can be used through a command-line interface with configuration files or via a graphical user interface (GUI). This facilitates high-throughput, reproducible processing of spectroscopic datasets in automated and adaptive experimentation. PyMESpec applies to large datasets from spectroscopies and transient experiments in general. We demonstrate it using spectra from diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) over CeO₂ and modulation excitation ultraviolet-visible (ME UV-vis) and near-ambient pressure x-ray photoemission spectroscopy (NAP-XPS) on vanadia/titania catalyst for oxidative propane dehydrogenation.