Recent developments at synchrotron facilities have enabled routine scanning diffraction measurements on biological tissues using micron–size X-ray beams. These measurements produce thousands of scattering patterns per scan. Extracting the rich structural information contained in the scattering data calls for a generic data processing pipeline that can be configured to perform sample-specific data analysis. We demonstrate such a pipeline using data collected from plant tissues. The typical data flow starts from the conversion of scattering data into intensity maps with reciprocal coordinates that are independent of the experimental configuration. This is accomplished using py4xs, which also performs common preprocessing such as gap-filling in the detector data. Sample-specific functions are then used to distill the intensity maps into attributes that are informative of the underlying structure. For plant tissues, we have developed to functions that calculate cellulose crystallinity, fiber size and microfibril angle by fitting both SAXS and WAXS data, from data collected in either powder diffraction or fiber diffraction geometry. The extracted features are then assembled into false-color maps to reveal structural variations that are invisible in optical images. Tomographic reconstruction from 2D projections collected from different angles is also possible.

Data analysis pipeline for scanning micro–diffraction measurements on plant tissues

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.