Two Cornell-led research teams will receive nearly $1.2 million from the U.S. Department of Energy to develop artificial intelligence tools for energy systems and materials science.
The nine-month Phase I awards are part of the DOE's Genesis Mission, a national initiative connecting laboratories, universities and industry to accelerate work in energy, manufacturing, biotechnology, critical materials and quantum science.
Jian-Xun Wang, an associate professor of mechanical and aerospace engineering, will lead a $550,000 project to build an AI framework that can rapidly predict turbulent fluid flows. The work could apply to nuclear reactor cooling systems, heat exchangers, manufacturing processes and fusion energy devices.
Wang's team includes Cornell professor Olivier Desjardins and researchers at Columbia University and Oak Ridge National Laboratory. The model is designed to learn from high-fidelity simulation data and produce physics-informed predictions without being retrained whenever conditions change.
Physics professor Kyle Shen will lead a $636,000 project to predict the electronic properties of materials before they are synthesized. Cornell professors Eun-Ah Kim and Darrell Schlom and Brookhaven National Laboratory researcher Elio Vescovo are also participating.
That team plans to build a large machine-readable database of angle-resolved photoemission spectroscopy measurements and train an AI model using the data. Researchers will compare its predictions with new measurements from Brookhaven.
Phase I recipients may compete for Phase II awards ranging from $6 million to $15 million over three years.
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