X-ray technique maps 3D chemistry 43 times faster with 97% less data

For more than a century, X-rays have given scientists the ability to look beneath the surface of things, revealing bones, cracks in metal, and the hidden architecture of materials. But looking inside an object and knowing exactly what it is made of, element by element, in three dimensions, are two very different challenges. A team of researchers at Bar-Ilan University, working with collaborators at the European Synchrotron Radiation Facility and CEA and Université Grenoble Alpes, has now demonstrated a computational X-ray imaging technique that maps the three-dimensional chemical composition of an object 43 times faster than conventional approaches, while requiring more than 97 percent less measurement data. The work, published in the journal Optica, points toward a future in which detailed chemical maps of complex samples could be captured in a fraction of the time that today’s methods demand.

The technique addresses a fundamental bottleneck in X-ray fluorescence imaging, one of the most widely used tools for determining which chemical elements are present in a sample and where they are located. When an X-ray beam strikes a material, the atoms within it absorb energy and then re-emit fluorescent X-rays at characteristic energies, each one acting as a fingerprint for a specific element. By detecting these emissions, scientists can identify the presence of copper, zirconium, silver, or any other element without destroying the sample. The problem arises when researchers want a full three-dimensional picture. Traditional approaches require scanning the object point by point, measuring the fluorescence at each individual location, and repeating the process across many angles to build up a volumetric reconstruction. For large or intricate samples, that process can take considerable time and generate enormous volumes of data.

The Bar-Ilan-led team took a fundamentally different approach. Instead of measuring every point individually, they placed a randomly patterned tungsten mask in front of the X-ray beam. This mask imposes a structured pattern on the illumination, so that each measurement encodes information from multiple parts of the sample simultaneously. Rather than a series of isolated point readings, the detector captures compressed, overlapping signals that contain information about the whole volume in a form that is not immediately readable but is mathematically recoverable. The researchers then rotated a sample containing copper, zirconium, and silver while measuring the fluorescent X-rays emitted by the different elements, and a reconstruction algorithm pieced together the three-dimensional elemental structures directly from the compressed data.

The results were striking. The researchers were able to eliminate more than 97 percent of the measurements that would normally be required, yet still accurately reconstruct the locations of microscopic metal wires and particles within the sample. In practical terms, that means the same chemical map that once demanded a long, data-heavy scanning session can be recovered from a small fraction of the exposure. Adi Ben-Yehuda, a PhD student in Prof. Sharon Shwartz’s laboratory at Bar-Ilan University’s Department of Physics, described the surprise the team felt at how much information could be recovered from so little data. Instead of measuring every point separately, she explained, the method uses a structured X-ray pattern and lets the reconstruction algorithm assemble the information, a different way of thinking about how an X-ray image can be created.

The underlying idea belongs to a family of techniques known as ghost imaging, in which the image-bearing information is split between two correlated signals and recovered computationally rather than recorded directly. The new work builds on the team’s previous demonstration of two-dimensional X-ray fluorescence ghost imaging, extending the concept into a full three-dimensional imaging system. In the two-dimensional version, the structured illumination allowed the researchers to recover elemental maps without ever forming a conventional image on the detector. The leap to three dimensions required combining that compressed-sensing philosophy with tomographic reconstruction, the same mathematical framework that underlies computed tomography in medicine, but applied to fluorescence data rather than simple transmission. The result is a system in which the illumination pattern, the rotation of the sample, and the reconstruction algorithm work together as a single designed pipeline.

Why does speed matter so much in this field? The answer lies largely in the economics and physics of synchrotron facilities, the enormous particle-accelerator complexes where scientists use extremely bright X-ray beams to study materials at microscopic scales. Beamtime at these facilities is scarce and highly competitive, and every hour of measurement is precious. A technique that reduces the required measurements by more than 97 percent effectively multiplies the amount of science that can be extracted from a given allocation of beamtime. Faster imaging also opens experimental possibilities that are simply impractical today: scanning larger samples that would otherwise take days to map, following chemical processes as they unfold in real time, and studying delicate biological materials while reducing their cumulative exposure to damaging X-ray doses.

The potential applications span an unusually broad range of disciplines. In materials science, three-dimensional elemental maps reveal how alloys, catalysts, and electronic components are structured at the microscopic level, information that guides the design of stronger and more efficient materials. In green energy research, understanding the chemical distribution inside batteries and fuel cells as they charge and discharge is central to improving performance and longevity. In biology, researchers could map the distribution of trace elements within cells and tissues, where metals such as zinc, iron, and copper play essential roles in enzymes and signaling. In geology, elemental tomography can expose the growth history of minerals and the microstructure of rocks that record the planet’s past. For all of these fields, a 43-fold acceleration in acquisition time changes not just efficiency but the very scope of what can be attempted.

Prof. Sharon Shwartz of Bar-Ilan University framed the advance as a change in a long-standing trade-off. X-ray imaging has traditionally forced researchers to balance the amount of information they want against the time and data required to obtain it, he noted, but the new approach shows that this trade-off can be altered. By designing the X-ray illumination together with the computational reconstruction, the team can recover detailed three-dimensional chemical information from a remarkably small number of measurements. That co-design principle, in which hardware and software are developed as an integrated system rather than as separate stages, reflects a broader trend in modern imaging science, where clever mathematics increasingly substitutes for brute-force data collection.

The study was conducted with Dr. Alexander Rack of the European Synchrotron Radiation Facility and Dr. Nicola Viganò of CEA and Université Grenoble Alpes, and was supported by the Israel Science Foundation and the European Synchrotron Radiation Facility. The combination of an academic physics laboratory with two major European photon facilities underscores the kind of collaboration this technique will need as it matures, since structured-illumination experiments depend on precisely engineered masks and stable, brilliant X-ray sources of the kind found only at synchrotrons.

The researchers are already looking ahead. Their next steps include applying the technique to more complex biological and geological samples, whose heterogeneous structures and weaker elemental signals will test the robustness of the reconstruction algorithm, and incorporating artificial intelligence and deep learning to further improve imaging speed and resolution. If those efforts succeed, the compressed-measurement philosophy demonstrated here could become a standard tool at light sources around the world, turning what was once a slow, data-hungry mapping process into something fast enough to watch chemistry happen in three dimensions, live.

Subject of Research: Compressive three-dimensional X-ray fluorescence ghost tomography for rapid chemical imaging

Article Title: New X-ray imaging method maps 3D chemical structures 43 times faster

Article References: New X-ray imaging method maps 3D chemical structures 43 times faster. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: X-ray fluorescence, ghost imaging, tomography, Bar-Ilan University, synchrotron, compressed sensing, chemical imaging, Optica, tungsten mask, 3D reconstruction, materials science, beamtime efficiency