Framework for processing operando neutron radiography of energy devices

Abstract

Abstract Neutron radiography is a powerful diagnostic technique for operando studies of electrochemical devices, such as fuel cells, batteries, and electrolyzers. However, processing time-series neutron images is challenging due to high spatial/temporal resolution requirements, limited neutron flux, complex sample geometry, and low signal-to-noise ratios. Existing image processing platforms are not adequate to mitigate these issues, causing bottlenecks in data analysis and interpretation. In this work, we present our Python-based framework: neutron radiography of electrochemical devices (NeuRED). This framework integrates a robust set of image processing functions within a transparent, reproducible, and user-friendly workflow. The advantages and unique features of the framework are outlined, and demonstrations are provided for proton exchange membrane fuel cells, Li-ion batteries, and gas-liquid systems. NeuRED is a unique open-access software tool for the electrochemistry community that will contribute to the advancements of operando imaging applications in energy research.