  X-Ray Fluorescence (XRF) scanning is a widespread technique of high
importance and impact since it provides chemical composition maps crucial for
several scientific investigations. There are continuous requirements for
larger, faster and highly resolved acquisitions in order to study complex
structures. Among the scientific applications that benefit from it, some of
them, such as wide scale brain imaging, are prohibitively difficult due to time
constraints. However, typically the overall XRF imaging performance is
improving through technological progress on XRF detectors and X-ray sources.
This paper suggests an additional approach where XRF scanning is performed in a
sparse way by skipping specific points or by varying dynamically acquisition
time or other scan settings in a conditional manner. This paves the way for
Compressive Sensing in XRF scans where data are acquired in a reduced manner
allowing for challenging experiments, currently not feasible with the
traditional scanning strategies. A series of different compressive sensing
strategies for dynamic scans are presented here. A proof of principle
experiment was performed at the TwinMic beamline of Elettra synchrotron. The
outcome demonstrates the potential of Compressive Sensing for dynamic scans,
suggesting its use in challenging scientific experiments while proposing a
technical solution for beamline acquisition software.
