On a Mission To Discover

The Genesis Mission, a national initiative led by the U.S. Department of Energy, is building the world’s most powerful integrated science discovery platform. The goal is to combine artificial intelligence, supercomputing, quantum systems and advanced scientific instruments to accelerate breakthroughs in energy, scientific innovation and national security.

Researchers from the University at Buffalo have secured three grants as part of this historic initiative, reflecting the university’s leadership in applied AI and quantum science and engineering. UB’s projects were among 278 selected from a pool of more than 5,000 submissions.

“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,” says Venu Govindaraju, senior vice president for research, innovation and economic development at UB.

The first UB-led project focuses on creating CLEAR-AI, an AI-powered tool to support faster and more efficient chemical manufacturing, which could help advance the energy-efficient production of fuels and chemical building blocks.

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

CLEAR-AI will coordinate these activities within one continuous decision-making loop. The goal, says the project’s principal investigator, Jiayu Peng, assistant professor in the Department of Materials Design and Innovation, is “to help researchers identify promising catalyst and process conditions more quickly, reliably and resource-efficiently.”

The second award focuses on using AI to control anaerobic microbiomes—communities of microorganisms that thrive without oxygen—to produce 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 produce MCCAs, others interfere with that process. Led by principal investigator Yinyin Ye, assistant professor in the Department of Civil, Structural and Environmental Engineering, the research team will use AI to predict and identify naturally occurring viruses, known as phages, that selectively target and kill bacteria that hinder MCCA production.

Ultimately, the project explores how AI could make finding effective phages faster, less expensive and more precise, Ye says. The tool could also help engineer 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 Stanford University-led project using AI to model the behavior of electrons at quantum scale.

As electrical conductors shrink in modern devices, interruptions to the flow of electric currents generate heat and significantly degrade device performance. The research team aims to better understand the processes leading to decreased conductivity and identify new materials to mitigate these effects.