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Published on: October 28, 2025
Reducing acquisition time and radiation damage: data-driven subsampling for spectro-microscopy
Maike Meier1,2, Lorenzo Lazzarino1,3, Boris Shustin1
1Scientific Computing Department, STFC, Rutherford Appleton Laboratory, Harwell Campus, Didcot OX11 0QX, United Kingdom.
Journal of Synchrotron Radiation
|July 28, 2026
Summary
New spectro-microscopy methods significantly reduce experiment times and radiation dose by using sparse acquisition and computational reconstruction. This data-driven approach captures essential information with minimal measurements.
Area of Science:
- Materials Science
- Chemistry
- Physics
Background:
- Spectro-microscopy analyzes chemical states in materials and biological samples.
- Current limitations include long acquisition times and radiation damage.
Purpose of the Study:
- To develop faster and less damaging spectro-microscopy techniques.
- To reduce experiment time and total radiation dose.
Main Methods:
- Implemented sparse acquisition (subsampling) strategies.
- Utilized data-driven, computationally reconstructing mathematical techniques.
- Employed spectral and spatial importance subsampling distributions.
Main Results:
- Achieved significantly shorter experiment times and lower total radiation doses.
- Successfully reconstructed unobserved measurements from a small subset of data.
- As little as 4-6% of measurements captured equivalent information to conventional scans.
Conclusions:
- The novel strategies enhance spectro-microscopy efficiency and reduce sample damage.
- Data-driven subsampling and reconstruction offer a powerful alternative for rapid chemical state analysis.
