Patterned X-rays map 3D chemical structures faster with fewer measurements
Seeing inside an object is one thing; seeing exactly what it is made of, in three dimensions, is far more difficult. Now, researchers at Bar-Ilan University and collaborating institutions have developed a new X-ray imaging technique that can map the three-dimensional chemical composition of an object 43 times faster than conventional approaches, while using more than 97% less measurement data.
Researchers at Bar-Ilan University have devised a novel X-ray imaging method that captures 3D chemical structures 43 times quicker than standard techniques while requiring less than 2% of the traditional measurement data. Published in Optica, this technique could revolutionize the examination of complex materials and biological samples that are otherwise time-consuming and challenging to study.
Unlike conventional X-ray fluorescence imaging, which maps elements and their locations by individually measuring each point, this new approach employs a randomly patterned tungsten mask in front of the X-ray beam. This creates a structured pattern that encodes data from various parts of the sample simultaneously. By rotating a sample containing copper, zirconium, and silver and measuring the emitted fluorescent X-rays, researchers were able to reconstruct the three-dimensional elemental structures directly from the compressed data using a mathematical algorithm.
This innovative method, which builds upon previous work on 2D X-ray fluorescence ghost imaging, could significantly benefit researchers at synchrotron facilities where X-ray beam access is limited and measurement time is precious. Potential applications span multiple fields, including materials science, green energy, biology, and geology.
The researchers plan to expand the technique's application to more intricate biological and geological samples and incorporate artificial intelligence and deep learning to further enhance imaging speed and resolution.
Written by urgent.news from Phys.org's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
