Research
Chemical disorder opens an enormous space for materials design. When many elements share a crystal lattice, both composition and atomic arrangement can be varied. The number of possibilities quickly becomes too large to explore one material at a time.
We develop AI and computational methods that learn from these spaces and propose new materials for energy production, chemical manufacturing, nuclear technology, and extreme environments. Our goal is to move beyond brute-force screening toward models that can generate materials with the chemistry and atomic structure needed for a particular function.
Students in the S4E lab can follow a material from computational prediction through synthesis and experimental testing. Our current research centers on AI-driven materials design, hydrogen production, and nuclear energy.
Learning and generating chemical disorder
AI is changing what is possible in materials design. Disordered materials present a particularly difficult challenge because a single composition can contain many different atomic arrangements.
We want AI models that learn both which elements belong in a material and how those elements arrange themselves at the atomic scale. This creates a path from predicting known materials to generating new ones with targeted chemistry and disorder.
Students in this area work at the intersection of materials science, physics, AI, and scientific computing. Projects can involve electronic-structure calculations, machine-learned potentials, molecular dynamics, large-scale materials data, generative modeling, and open scientific software.
- Structural benchmarks overlook density-of-states errors in machine-learned interatomic potentials, APL Mach. Learn. (2026)
- Beyond the four core effects: revisiting thermoelectrics with a high-entropy design, Mater. Horiz. (2025)
- High entropy powering green energy: hydrogen, batteries, electronics, and catalysis, npj Comput. Mater. (2025)
Hydrogen production
Hydrogen is a backbone of the energy and chemical industries. It is used at enormous scale in refining, chemical manufacturing, and fertilizer production, and its role is expanding across energy technologies. Most hydrogen production relies on natural gas, tying its economics to natural-gas prices. Alternative production routes offer greater flexibility in how and where hydrogen is made.
We design materials for producing hydrogen from water using electricity or heat. Machine learning helps us explore complex alloys as alternatives to precious-metal catalysts, and we use first-principles calculations to understand how atomic arrangement changes catalytic behavior.
Students working in this area encounter catalysis, electronic structure, thermodynamics, machine learning, materials synthesis, and experimental characterization.
Nuclear energy: fission and fusion
Growing electricity demand will require enormous amounts of reliable power. Nuclear fission is one of the few technologies already capable of supplying electricity continuously at that scale. Its continued and expanded use requires materials that can operate safely for long periods and durable approaches to nuclear waste.
We design materials for both challenges. In recent work, we demonstrated for the first time that iodine can be incorporated directly into the crystal lattice of a pyrochlore. We also study chemically complex materials for demanding reactor environments.
Fusion is one of the great scientific and engineering challenges of our time: reproducing on Earth the reactions that power the stars and turning them into a practical source of energy. Doing that is also a materials problem. Components near the plasma must survive conditions encountered almost nowhere else in engineering. We investigate chemically complex materials designed for these extreme environments.
Research in nuclear materials spans phase stability, defect chemistry, extreme environments, first-principles calculations, machine learning, synthesis, and characterization.
The group is recruiting at every level, from undergraduates to postdoctoral researchers. See the Jobs page for how to apply.