UB scientists awarded Genesis Mission grants for AI-focused research

UB researchers have secured three Genesis Mission grants that focus on using artificial intelligence and quantum technologies to accelerate scientific discovery, federal officials announced on Wednesday.

The awards, from the Department of Energy, showcase the university’s leadership in applied AI and quantum science and engineering, with each project spotlighting the technologies’ potential to strengthen the nation’s leadership in science and technology.

UB’s projects were among 278 selected from a pool of more than 5,000 submissions.

“The University at Buffalo is proud to contribute to the Genesis Mission’s effort to accelerate discovery and strengthen America’s future,” says Venu Govindaraju, senior vice president for research, innovation and economic development at UB.

“Being selected alongside the nation’s leading universities, national laboratories and industry partners reflects the strength of research at UB, our leadership in AI-driven innovation and our proven ability to translate breakthrough discoveries into solutions that benefit society.”

Exact funding amounts for the three awards are still being determined, but UB anticipates it will exceed $1 million, with the potential for additional funding. 

The first UB-led project focuses on creating an AI-powered tool to accelerate catalyst and process development for the electrosynthesis of carbon-based fuels and chemicals.

The tool – a closed-loop, agentic AI platform – is called CLEAR-AI.

In chemical manufacturing, scientists perform a variety of tasks – computational modeling, catalyst synthesis, materials characterization and performance testing – to identify catalyst materials and ideal operating conditions. However, these activities are often conducted separately, which limits how quickly scientists exchange information that can guide further research.

CLEAR-AI will coordinate these activities within one continuous decision-making loop. The platform will integrate physics-based modeling, automated experimentation, advanced materials characterization, electrochemical testing and data-driven analysis so that results from each round of computation and experimentation can guide the next most informative calculations and experiments.

“Our goal with CLEAR-AI is to help researchers identify promising catalyst and process conditions more quickly, reliably and resource-efficiently,” says the project’s principal investigator, Jiayu Peng, assistant professor in the Department of Materials Design and Innovation.

Collaborators come from the University of Pennsylvania, Virginia Tech, the University of Virginia, Brookhaven National Laboratory and Oak Ridge National Laboratory.

The award is a proof-of-concept demonstration of how agentic AI can support faster and more efficient chemical-manufacturing research. If successful, CLEAR-AI could establish a scalable foundation for broader electrosynthetic applications, helping advance the energy-efficient production of fuels and chemical building blocks while strengthening U.S. leadership in AI-enabled manufacturing.

The second UB-led award focuses on employing AI to control anaerobic microbiomes for producing medium-chain carboxylic acids (MCCAs), which are used to make aviation fuels, animal feed additives and other industrial products.

The challenge is that while some microbes help produce MCCAs, others in the same microbial community divert carbon toward unwanted products, reducing the amount of MCCAs that can be made.

The research team, led by principal investigator Yinyin Ye, assistant professor in the Department of Civil, Structural and Environmental Engineering, in collaboration with faculty and scientists from Johns Hopkins University and Pacific Northwest National Laboratory, will use AI to help predict and identify naturally occurring viruses (known as phages) that selectively target and kill bacteria, including these MCCA-competing microbes.

Ultimately, the project explores how AI could make it faster, less expensive, and more precise to find effective phages than current trial-and-error methods, Ye says, and the tool may be useful for engineering other microbial systems to produce high-value products that support the U.S. bioeconomy.

The third project is a subaward to Vasili Perebeinos, professor of electrical engineering, for a project, led by Stanford University, using AI to model the behavior of electrons at quantum scale. Sandia National Laboratories is also a partner on the project.

As electrical conductors shrink in modern technologies, imperfections in the shape of the channel interrupt the flow of electric current. This generates heat and significantly degrades the device’s performance.

With the project – AI-Driven Transport Optimization of Metallic and Interfacial Quantum Materials (ATOMIQ) – scientists aim to better understand the processes leading to this decreased conductivity. They also plan to identify new materials to mitigate these effects.

They will use AI, combined with fundamental physics, to model electron transport and conduct experimental studies of materials only a few atoms in width.

The Genesis Mission is a historic national initiative led by the U.S. Department of Energy, which is building the world’s most powerful integrated science discovery platform.

By uniting government, industry, academia, and philanthropy, it is accelerating breakthroughs in energy, scientific discovery, and national security through a new platform that combines AI, supercomputing, quantum systems, and advanced scientific instruments.