Welcome
Welcome to the research website of Dr. Steven R. Spurgeon! I'm a materials scientist focused on AI-guided research into structure, properties, and defects in nanomaterials for energy systems, next-generation electronics, and quantum computing.
My research interests span the synthesis, processing, and evolution of nanomaterials, with a particular focus on the development of artificial intelligence-guided experiments in extremes. My work has resulted in dozens of journal publications, invited talks, and awards from the U.S. Department of Energy, the Department of Defense, the National Science Foundation, the Materials Research Society, the Microscopy Society of America, and many others.
We’re always looking for new scientists, students, and collaborators. Visit the site to learn more and contact me!
Research Areas
Directing order in nanomaterials
Evolution of materials in extremes
Data-driven materials discovery and design
Artificial intelligence, machine learning, and automated experimentation
Scanning transmission electron microscopy
Photo by Andrea Starr / PNNL
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Research Interests
Materials Synthesis Pathways
Control over synthesis pathways is crucial for the development of next-generation devices for electronics, clean energy, and quantum computing. Minor perturbations at small length and time scales are often difficult to predict, necessitating the use of new methods to characterize and model these pathways.
Functional Materials in Extremes
The behavior of functional materials in extreme environments is poorly understood, impeding our ability to control and harness property-defining defects. Development of functional materials with tailored properties requires us to examine transient defect formation mechanisms in highly non-equilibrium conditions.
Harnessing Emergent Interface Properties
Interfaces mediate a spectrum of important functionalities whose optimization depends on precise control of structure and chemistry. We are developing highly integrated approaches to manipulate interfaces for the technologies of tomorrow.
Advancing AI-Driven Science
Emerging data-driven and artificial intelligence approaches promise to revolutionize the design and characterization of materials. We are exploring sparse data analytics and automation approaches that will allow us to more richly probe materials and chemical processes.