Nanoscale chemical imaging with structured X-ray illumination

Author:

Li Jizhou12ORCID,Chen Si3,Ratner Daniel4,Blu Thierry5,Pianetta Piero1ORCID,Liu Yijin6ORCID

Affiliation:

1. Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Menlo Park, CA 94025

2. School of Data Science, City University of Hong Kong, Hong Kong, China

3. X-ray Science Division, Argonne National Laboratory, Lemont, IL 60439

4. Machine Learning Initiative, SLAC National Accelerator Laboratory, Menlo Park, CA 94025

5. Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China

6. Walker Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX 78705

Abstract

High-resolution imaging with compositional and chemical sensitivity is crucial for a wide range of scientific and engineering disciplines. Although synchrotron X-ray imaging through spectromicroscopy has been tremendously successful and broadly applied, it encounters challenges in achieving enhanced detection sensitivity, satisfactory spatial resolution, and high experimental throughput simultaneously. In this work, based on structured illumination, we develop a single-pixel X-ray imaging approach coupled with a generative image reconstruction model for mapping the compositional heterogeneity with nanoscale resolvability. This method integrates a full-field transmission X-ray microscope with an X-ray fluorescence detector and eliminates the need for nanoscale X-ray focusing and raster scanning. We experimentally demonstrate the effectiveness of our approach by imaging a battery sample composed of mixed cathode materials and successfully retrieving the compositional variations of the imaged cathode particles. Bridging the gap between structural and chemical characterizations using X-rays, this technique opens up vast opportunities in the fields of biology, environmental, and materials science, especially for radiation-sensitive samples.

Funder

U.S. Department of Energy

Publisher

Proceedings of the National Academy of Sciences

Subject

Multidisciplinary

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