Lawrence Berkeley National Laboratory (Berkeley Lab) is working to transform petabytes of imaging data from advanced light and neutron scattering user facilities in the U.S. into actionable knowledge, demonstrating AI-accelerated advanced discovery capabilities that can be applied to energy, semiconductors, medicine, and other essential technologies.

The multi-lab effort, called SYNAPS-I (SYnergistic Neutron and Photon Science – Intelligence), is part of the Genesis Mission, a new national initiative led by the Department of Energy to advance AI and accelerate discovery, providing solutions for challenges in science, energy, and national security. A cornerstone of the Genesis Mission is the Transformational AI Models Consortium, which will build and deploy self-improving AI models by harnessing DOE’s unique data, facilities, and expertise. SYNAPS-I is one of three AI model teams that Berkeley Lab leads or plays a key role in, building on AI expertise in high-performance computing, managing large datasets, and pioneering AI models in partnership with industry.

“Our national lab facilities are already world leaders in scientific discovery. SYNAPS-I will radically accelerate the path from experiment to insight by embedding AI directly into the analysis workflow,” said Alex Hexemer, a senior scientist at Berkeley Lab’s Advanced Light Source (ALS) and SYNAPS-I lead point of contact.

The SYNAPS-I platform will integrate large machine learning models as well as foundation models across all participating light and neutron sources, enabling unified analysis of imaging data from cutting-edge X-ray and neutron instruments at seven DOE Basic Energy Sciences user facilities, including the ALS, a synchrotron light source that produces X-ray, ultraviolet, and infrared light. The increased data outputs of recently completed and in-progress facility upgrades, such as Berkeley Lab’s Advanced Light Source Upgrade (ALS-U) project, bring even greater opportunities to accelerate scientific discovery across a wide range of disciplines.

“Our national lab facilities are already world leaders in scientific discovery. SYNAPS-I will radically accelerate the path from experiment to insight by embedding AI directly into the analysis workflow.”
— Alex Hexemer, Berkeley Lab senior scientist and SYNAPS-I lead point of contact

SYNAPS-I is a public-private partnership uniting national laboratories, university researchers, and key industry innovators in AI, materials, pharmaceuticals, and energy, including partners from Berkeley Lab, Argonne National Laboratory, Brookhaven National Laboratory, SLAC National Accelerator Laboratory, and Oak Ridge National Laboratory.

“By pooling expertise and data across facilities, we can build AI capabilities that benefit all users and accelerate scientific discovery in ways that no single facility could achieve alone,” Hexemer said.

“SYNAPS-I marks the first step into an exciting new era for science at modern facilities. With the ALS — especially after the ALS-U upgrade — we’ll gain an unprecedented view into the inner workings of nature and technology. The challenge lies in turning that immense detail into knowledge that advances humanity. SYNAPS-I begins this next chapter of discovery,” said Dimitrios Argyriou, Interim ALS-U Project Director.

X-ray microscopy and neutron scattering techniques help scientists study phase changes in the chemical composition and molecular makeup of active materials. This information can show how chemical processes and structural defects evolve in a material, and those insights can assist in the development of more durable materials for batteries and other useful applications.

Advances in automation for X-ray microscopy have allowed scientists to speed materials analysis for new applications. For example, more than a decade ago at the ALS, a collaboration of researchers used ptychography — a lensless, computational X-ray microscopy technique that analyzes the structure of a sample down to the atomic level — to image 5-nanometer structures in lithium iron phosphate, a material of interest for energy storage applications. That record-setting breakthrough allowed new understanding of the formation of defects in lithium iron phosphate during a chemical phase transformation.