Artificial intelligence (AI) is transforming nearly every branch of science. And researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory are helping lead the way.
“There is a lot of hype around AI today in the media,” said Mathew Cherukara, a computational scientist and group leader at Argonne’s Advanced Photon Source (APS), a DOE Office of Science user facility. “Yet there is no question that AI can help researchers at APS and other light sources make breakthroughs in advanced chemical processes critical to American industry.”
As proof, the Argonne team has developed an AI-guided method that dramatically speeds up a widely used X-ray technique known as X-ray absorption near-edge structure (XANES) spectroscopy. It does so with far less risk of human error or damage to the sample from the X-ray beams.
This powerful analytical tool reveals the hidden chemistry inside materials important to modern life, such as batteries, catalysts and materials through which electricity flows without resistance. The team’s AI approach cuts the number of measurements previously needed by as much as 80%, with no loss of accuracy. The result is a dramatic shortening of data acquisition duration, allowing researchers to capture fast chemical changes in real time.
Here’s how XANES works: Scientists shine X-ray beams with increasing energy onto a material. Each X-ray beam is a tiny packet of energy. When the energy is high enough to knock a tightly bound electron out of an atom, the material suddenly absorbs more X-rays. This sharp jump in absorption is called the absorption edge.
By tracking how X-ray absorption changes before, during and after this edge, researchers can watch the chemistry of a specific element unfold within a material, from how a metallic catalyst reacts with other chemicals to how the charge state of a battery element changes during cycling.
“XANES is incredibly powerful, but until now, scientists had to make dozens or even hundreds of choices about where to measure and how long to measure at each X-ray energy level,” said Shelly Kelly, an APS physicist and group leader.
Some regions of X-ray energy are rich with chemical information, calling for numerous measurements. Other parts are not, meaning far fewer measurements are needed. “It is often not easy for experimenters to set the optimal number of measurements to make in a given energy region,” Kelly said. “AI is helping us take the guesswork out of XANES.”
The team’s new approach replaces the manual measurement process with an AI algorithm that automatically selects the most useful measurement points. The algorithm identifies where the absorption edge is likely to occur, which regions hold the most chemical detail and which regions offer little added information.
“Our AI method measures only where needed,” said Ming Du, a computational scientist and lead author on the paper. “It’s smarter, faster and more efficient, and it lets researchers focus on the big picture.”
The system also enables something new: AI-directed experiments. By comparing a sample’s evolving spectrum against known starting and ending states (for example, a fully charged electrode versus fully discharged), the AI can tell researchers in real time the state of the chemical progress, when enough information has been collected, and when it’s time to move on.
“It’s not just speeding up the measurement,” Kelly said. “It’s making decisions during the experiment — decisions a human used to make.”
The work points toward a future in which X-ray beamlines, such as those at the APS, are more autonomous and better able to track complex chemical reactions as they happen.
“This brings us closer to intelligent X-ray stations that make the most of every photon,” Cherukara said. “Argonne plans to continue developing AI-driven tools for next-generation X-ray science, especially as the upgraded APS delivers beams up to 500 times brighter than before.”
The team demonstrated the method using beamlines 25-ID-C, 20-BM and 10-ID at the APS. The project was supported by the DOE Office of Science, Office of Basic Energy Sciences.
The research first appeared in npj Computational Materials. In addition to Du, Kelly and Cherukara, contributors include Mark Wolfman and Chengjun Sun.
About the Advanced Photon Source
The U. S. Department of Energy Office of Science’s Advanced Photon Source (APS) at Argonne National Laboratory is one of the world’s most productive X-ray light source facilities. The APS provides high-brightness X-ray beams to a diverse community of researchers in materials science, chemistry, condensed matter physics, the life and environmental sciences, and applied research. These X-rays are ideally suited for explorations of materials and biological structures; elemental distribution; chemical, magnetic, electronic states; and a wide range of technologically important engineering systems from batteries to fuel injector sprays, all of which are the foundations of our nation’s economic, technological, and physical well-being. Each year, more than 5,000 researchers use the APS to produce over 2,000 publications detailing impactful discoveries, and solve more vital biological protein structures than users of any other X-ray light source research facility. APS scientists and engineers innovate technology that is at the heart of advancing accelerator and light-source operations. This includes the insertion devices that produce extreme-brightness X-rays prized by researchers, lenses that focus the X-rays down to a few nanometers, instrumentation that maximizes the way the X-rays interact with samples being studied, and software that gathers and manages the massive quantity of data resulting from discovery research at the APS.
This research used resources of the Advanced Photon Source, a U.S. DOE Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357.
Argonne National Laboratory seeks solutions to pressing national problems in science and technology by conducting leading-edge basic and applied research in virtually every scientific discipline. Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science.
The U.S. Department of Energy’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit https://energy.gov/science.