XMIDAS Software Enables Chemical Analysis from Nanoscale Spectroscopy Data
Synchrotron-based X-ray spectromicroscopy tools are widely used to understand the chemistry and morphology of complex material systems owing to their high penetration depth and sensitivity. High-resolution scanning X-ray spectromicroscopy expands the spectroscopy toolbox into the nanoscopic scale, but additional tools are needed to process the resulting multi-dimensional spectromicroscopy data.
X-ray Multimodal Image Data Analysis Software (XMIDAS) is an open-source python package for analysis of spectromicroscopy data from both image and spectrum representations for nanoscale and microscale chemical imaging. XMIDAS is publicly distributed with the help of scientists at the Data Science & Systems Integration Program at Brookhaven National Laboratory’s (BNL) National Synchrotron Light Source II (NSLS-II). A key motivation behind the software development project, conducted in collaboration with BNL’s Center for BioMolecular Structure and NSLS-II’s Imaging and Microscopy Program, was to create a user-friendly tool to extract meaningful chemical information from high-dimensional (4D+) spectromicroscopy data. The program combines conventional data processing workflows with well-established machine-learning tools in an easy-to-use graphical user interface environment.
Researchers used a combination of nanoprobe-based X-ray fluorescence spectromicroscopy (nano-XRF) X-ray absorption near edge structure spectromicroscopy (nano-XANES), and differential phase-contrast imaging to probe elemental and chemical state information of aggregate samples, and then used XMIDAS to visualize the complete chemistry of localized nanostructures. The optimized data-reduction strategies and tool development facilitate the analysis of complex biological and environmental samples at both micro- and nanoscales using X-ray spectromicroscopy techniques.
- BER Resource: Center for BioMolecular Structure
- Download XMIDAS open-source software: github.com/NSLS-II/xmidas
Pattammattel et al. 2022. Multimodal X-ray nano-spectromicroscopy analysis of chemically heterogeneous systems. Metallomics, 14, 10, mfac078. [DOI: 10.1093/mtomcs/mfac078]