Simon Billinge
University of California-Santa Barbara, CA·Materials Science
Whether a material conducts electricity, survives extreme heat, or stores energy well depends on how its atoms are arranged. X-ray diffraction (XRD) and related scattering methods are the main way to see that arrangement: a beam scatters off a sample and the resulting pattern encodes the atomic structure.
- Fields
Materials Science
Physics
Computer Science
- Topics
X-ray diffraction
powder diffraction
neutron diffraction
- Grants
- 1 known grant, through Apr 2029
What they work on
- Build an extensible data architecture for experimental powder diffraction, combining metadata schemas, JSON-based records and a public repository with persistent DOIs, curated releases and open APIs for reproducible workflows.
- Develop agentic large language model workflows that find relevant literature, detect and classify X-ray diffraction figures, extract their labels, and digitize plotted patterns into machine-readable data.
- Create software that automatically captures data and metadata from laboratory diffractometers and from synchrotron X-ray and neutron instruments at national laboratories.
- Train and deploy domain-adapted AI models that bridge synthetic training sets and real measurements to validate diffraction data and metadata and support structure determination for complex materials such as quantum materials.
More about the research
Analyzing those patterns is hard, the datasets are large, and the thousands of patterns measured each year in labs and national facilities end up buried in publications or on local disks in nonstandard formats. There is no public database of experimental powder diffraction data. This project builds one, together with artificial intelligence tools to analyze it.
Why it matters
Materials discovery is slowed when hard-won diffraction measurements cannot be found or reused. A public, searchable repository with automated analysis could let researchers anywhere, including those without access to large facilities, interpret diffraction data and determine structures of complex materials such as candidate quantum materials relevant to future quantum information technology. The methods for recovering data from published figures could also serve other experimental fields.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
David Elbert
Johns Hopkins University, MD·Materials Science
Coordinate data producers, users, repositories and publishers through the Materials Research Coordination Network (MaRCN) to make depositing materials data in trusted repositories the norm under FAIR (findable, accessible, interoperable, reusable) principles.
Abdellah Lisfi
Morgan State University, MD·Materials Science
Test whether two-phase nanostructures break the spin-orbit coupling link to produce large magnetostriction with weak anisotropy in Fe-Ga-based alloys containing aluminum or germanium.
Kenneth Poeppelmeier
Northwestern University, IL·Chemistry
Develop targeted hydrothermal, solvothermal and solid-state synthesis methods that control how anionic building units align in oxide and oxide-fluoride crystals, so that crystals form without inversion symmetry.
The school
University of California-Santa Barbara: 17 labs on PI Pages, $303M a year on research, 403 research doctorates a year.
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