Key Takeaways
- The U.S. Department of Energy’s Genesis Mission awarded funding to only 278 of over 5,000 applicants, selecting projects that demonstrate strong AI integration and viable data.
- Five University of Texas (UT) research teams received grants, with Kevin Clarno’s nuclear‑reactor work already advancing to Phase II funding.
- The funded projects span nuclear energy, additive manufacturing, extreme‑environment materials, sustainable mineral recovery, and laboratory automation.
- Each team plans to use artificial intelligence to accelerate discovery, improve safety, or bridge the gap between academic research and industrial application.
- DOE officials emphasize that the Genesis Mission is reshaping how science is conducted nationwide, aiming to bolster U.S. leadership in energy, science, and national security.
Overview of Genesis Mission Funding
On July 22, the U.S. Department of Energy (DOE) announced the recipients of its Genesis Mission grants at a summit in Washington, D.C. The initiative, designed to strengthen American capabilities in energy, science, and national security through artificial intelligence, attracted more than 5,000 applications. Only 278 proposals were selected for funding, a selectivity rate of roughly 5.5 %. According to a UT news release, awards were based on the viability of project data and the clarity with which AI would be woven into the research plan. Shawn Whitman, the DOE’s principal deputy under secretary for science, highlighted the transformative intent of the program:
“We’re changing how science is going to be done in a way that is not really happening anywhere else in the world.”
The Genesis Mission operates in two phases. Phase I awards provide up to $750,000 for nine months of work; projects that show promise after this period may be eligible for Phase II funding to pursue further discovery.
Kevin Clarno’s Nuclear Reactor Research
Kevin Clarno, an associate professor of mechanical engineering at UT, secured Genesis Mission funding for his investigation into the internal dynamics of nuclear reactors. His goal is to demonstrate the viability of various nuclear system designs so they can obtain regulatory approval more swiftly. Clarno’s project is the only one among the five UT awardees to have already progressed to Phase II funding, underscoring the DOE’s confidence in its potential impact.
Speaking about the current state of the nuclear sector, Clarno remarked:
“The nuclear industry right now is in the process of transforming… They’re tackling some of the most challenging problems to really (make) nuclear energy real again.”
By applying AI‑driven simulations and predictive modeling, Clarno hopes to reduce the time and cost associated with licensing new reactor concepts, thereby supporting a renaissance for clean nuclear power.
George Biros’ AI‑Enhanced 3‑D Printing
George Biros, a professor of computational and mechanical engineering, is leveraging artificial intelligence to predict the formation of a material’s internal microstructure during additive manufacturing. Accurate prediction of these internal structures is critical for producing reliable, high‑performance parts in industries ranging from aerospace to biomedical devices.
Biros emphasized the collaborative nature of the Genesis Mission:
“This program really integrates industry, national labs and universities to develop state-of-the-art technologies that will be used … to integrate academic research with (actual) production‑level problems.”
His team will train machine‑learning models on experimental data from national labs, aiming to close the loop between fundamental materials science and real‑world manufacturing constraints.
Karen Willcox’s Extreme‑Environment Materials
Karen Willcox, director of the Oden Institute for Computational Engineering and Sciences, is partnering with Sandia National Laboratory—a DOE contractor—to study materials that can withstand extreme heat, chemical stress, and irradiation. The project seeks not only to create such robust materials but also to track their performance throughout their entire life cycles.
Willcox, who also holds a professorship in the Department of Aerospace Engineering and Engineering Mechanics, is working alongside co‑principal investigator Anirban Chaudhuri. Chaudhuri explained the AI component of the effort:
“The project will use AI to develop digital models of the materials they are developing.”
These digital twins will enable researchers to simulate degradation mechanisms, optimize composition, and predict service life under harsh conditions—capabilities vital for next‑generation reactors, hypersonic vehicles, and space exploration hardware.
Benjamin Keitz’s Protein‑Based Mineral Recovery
Benjamin Keitz, an associate professor in the McKetta Department of Chemical Engineering, is leading a multidisciplinary team that designs environmentally benign proteins capable of binding to specific metals. The concept is to introduce these proteins into waste streams—such as electronic‑waste pits or mining tailings—where they would selectively capture valuable metals, making recovery economically feasible where traditional refining is not.
Keitz described the vision succinctly:
“If you had a protein that’s environmentally benign, maybe you could throw it into this pit of electronic waste or a mining waste pit where it’s not economic for them to refine the additional metals that are in there… You just throw the protein in, and then you have a method to suck out all of the valuable metals of interest.”
By coupling protein engineering with AI‑guided screening of binding affinities, Keitz’s team hopes to create a scalable, low‑impact alternative to conventional hydrometallurgical processes, reducing both energy consumption and hazardous waste.
Volkan Isler’s Laboratory Assistant Robots
Volkan Isler, a professor of computer science, is developing autonomous robots intended to serve as lab assistants. These machines aim to alleviate workforce shortages, streamline repetitive experimental procedures, and handle tasks that pose safety risks to human researchers.
Isler articulated the broader ambition behind the effort:
“In the long run, robots can be faster or more accurate than humans… However, the bigger prize is automated scientific discovery.”
The robots will be equipped with vision systems, manipulators, and AI planners that can adapt protocols on the fly, log data, and even suggest hypothesis‑driven modifications to experiments. By augmenting human scientists with reliable robotic partners, Isler’s work could accelerate the pace of discovery across chemistry, biology, and materials science.
Impact and Future Outlook
Collectively, these five UT projects illustrate how the DOE’s Genesis Mission is catalyzing a new paradigm in research funding—one that prioritizes AI integration, cross‑sector collaboration, and tangible pathways from laboratory breakthroughs to real‑world deployment. The selected teams have already begun the nine‑month Phase I period, with deliverables ranging from validated nuclear‑reactor simulations to prototype protein binders and robotic lab assistants.
Should their initial results meet the DOE’s benchmarks for viability and innovation, many will qualify for Phase II support, allowing them to scale up their technologies, engage industrial partners, and potentially influence national policy on energy resilience, advanced manufacturing, and sustainable resource management.
As Shawn Whitman noted, the Genesis Mission is not merely a funding mechanism; it is an attempt to reshape the scientific enterprise itself. By embedding artificial intelligence into the core of discovery processes, the initiative aims to keep the United States at the forefront of technological advancement in energy, security, and scientific leadership—an ambition that, if fulfilled, could reverberate far beyond the walls of the University of Texas.
https://thedailytexan.com/2026/08/03/ut-artificial-intelligence-researchers-awarded-grants-in-department-of-energy-initiative/