As anyone who has ever skimmed a book or magazine can tell you, sometimes you don’t have to read every word to grasp the essence. Inspired by this notion, scientists are harnessing the power of artificial intelligence (AI) to enable a form of “speed reading” in microscopy. This could revolutionize the way researchers acquire data and allow them to preserve the integrity of precious samples.
Researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory have developed an autonomous, or self-driving, microscopy technique. It uses AI to selectively target points of interest for scanning. Unlike the traditional point-by-point raster scan, which methodically covers every inch like the sequential reading of words on a page, this innovative approach identifies clusters of intriguing features, bypassing humdrum regions of monotonous uniformity.
“Many regions of a sample can be safely disregarded or at least not sampled heavily, but regions where there are discontinuities and boundaries can instead contribute the vast majority of information about the sample,” said Charudatta (C.D.) Phatak, a group leader and materials scientist at Argonne and one of the authors of the study. By honing in on these areas, the technique dramatically speeds up the experimental process.
The AI algorithm at the heart of the experiment initiates the scanning process by selecting a set of random points on the sample. It then simultaneously gathers data from these points while predicting subsequent points of interest. This on-the-fly prediction capability empowers researchers to accelerate data acquisition, eliminating the need for human intervention and dramatically expediting the experiment.
Saugat Kandel, a postdoctoral researcher at Argonne and lead author of the study, emphasized the time-saving benefits. “Taking the human component out of the prediction process saves a great deal of time and really speeds up the experiment,” he said. “There’s also only a small number of scientists who can perform these experiments effectively as they are done now.”
This streamlined approach to data acquisition is particularly invaluable in facilities like Argonne’s Advanced Photon Source (APS), where beam time is a precious resource. By reducing the time needed for gathering data, scientists can conduct additional experiments with the beam time they have reserved.
“The ability to automate experiments with AI will significantly accelerate scientific progress in the coming years,” said Argonne group leader and computational scientist Mathew Cherukara, another author of the study. “This is a demonstration of our ability to do autonomous research with a very complex instrument.”
One of the surprising things about the AI model is that it doesn’t need to be trained on a technical dataset. “The AI can be trained on a generic image, and it knows immediately how to recognize the areas of interest,” said Argonne Computational Mathematician Zichao (Wendy) Di, another co-author.
AI-driven microscopy could have a broad range of uses across a wide variety of microscopes, said Tao Zhou, an Argonne nanoscientist and co-author. “From X-ray microscopy to electron microscopy to atomic probe microscopy, any microscopy study in which 2D scanning is called for can be accelerated by this technique.”
This pioneering technique not only offers unparalleled speed but also opens up new avenues for scientific exploration. By rapidly scanning samples and extracting key information, scientists can delve into the intricate world of materials and gain insights that were previously unattainable. The synergy between artificial intelligence and microscopy heralds a new era of discovery, where the frontiers of science are continuously pushed, and the mysteries of the microscopic realm unravel before our eyes.
A paper based on the study appeared in Nature Communications on Sept. 7.
The work was supported by an Argonne laboratory-directed research and development grant and used the Center for Nanoscale Materials and the APS, both DOE Office of Science user facilities.
About Argonne’s Center for Nanoscale Materials
The Center for Nanoscale Materials is one of the five DOE Nanoscale Science Research Centers, premier national user facilities for interdisciplinary research at the nanoscale supported by the DOE Office of Science. Together the NSRCs comprise a suite of complementary facilities that provide researchers with state-of-the-art capabilities to fabricate, process, characterize and model nanoscale materials, and constitute the largest infrastructure investment of the National Nanotechnology Initiative. The NSRCs are located at DOE’s Argonne, Brookhaven, Lawrence Berkeley, Oak Ridge, Sandia and Los Alamos National Laboratories. For more information about the DOE NSRCs, please visit https://science.osti.gov/User-Facilities/User-Facilities-at-a-Glance.
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. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, 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.