The Department of Energy's Oak Ridge National Laboratory brought a large contingent of researchers to the 2026 AI+ Expo for National Competitiveness, held May 7-9 in Washington D.C., where they demonstrated AI-powered systems for 3D printing, quantum materials, and autonomous plant phenotyping. The event, hosted by the Special Competitive Studies Project, gathered leaders from technology, academia, industry, and government to discuss how AI can strengthen U.S. innovation, energy resilience, and national security.
The expo underscored DOE's focus on AI as a strategic capability for scientific discovery, with the Genesis Mission playing a central role. That initiative aims to double the productivity and impact of American science, engineering, and R&D within a decade by integrating AI for Science & Research, high-performance computing, and advanced instrumentation across the national lab system.
Collaboration across national labs
ORNL Associate Laboratory Director Gina Tourassi joined a panel of computing leaders from other national labs to discuss the Genesis Mission. "The Genesis Mission reflects a bold national commitment to accelerate discovery by integrating AI, high-performance computing, advanced scientific instrumentation, and multidisciplinary expertise across the Department of Energy ecosystem," Tourassi said. "Events like the AI+ Expo are critical because they bring together varied stakeholders to align capabilities around a shared goal: dramatically increasing the productivity, impact and competitiveness of American science and technology."
Arjun Shankar, director of the National Center for Computational Sciences at ORNL, detailed the lab's leadership role in the American Science Cloud, a cornerstone of the Genesis Mission. He described presenting at the DOE booth as "truly energizing" because it connected practitioners, designers, and users around the shared infrastructure for open science.
AI agents, 3D printing, and quantum materials
Senior computational scientist Stephen DeWitt demonstrated LOOP, an AI-driven system that monitors metal 3D printing in real time and automatically adjusts the manufacturing process. The system combines AI agents, supercomputing, and advanced manufacturing tools to produce reliable parts for critical energy infrastructure more efficiently.
Yongqiang Cheng, a distinguished staff scientist at ORNL's Spallation Neutron Source, showed how AI and high-performance computing can uncover hidden spin interactions in quantum materials. The approach analyzes experimental data faster and more accurately, accelerating the discovery of materials for future electronics and quantum computing.
Rafael Ferreira da Silva, a distinguished research scientist, presented OPAL, the Orchestrated Platform for Autonomous Laboratories, which uses AI Agents & Automation and the Frontier supercomputer to monitor plant growth at the Advanced Plant Phenotyping Laboratory. The system collapses week-long detection cycles into sub-minute autonomous responses. "We're moving past the era of AI as a research assistant and into one where agents actively run the science," Ferreira da Silva said. "Coupling foundation vision models with exascale-class agentic workflows turns high-throughput plant phenotyping into a discovery engine that learns continuously and steers itself, with scientists on the loop where it matters most."
Why this matters for science and research professionals
The demonstrations point to a shift in how national labs conduct research: autonomous systems that combine AI, exascale computing, and robotics are now running experiments and making decisions in closed loops. For researchers, this means working alongside AI agents that collapse experimental timelines, analyze data in real time, and free scientists to focus on higher-level questions. The Genesis Mission's push to double R&D productivity signals that this approach will become standard across DOE facilities, not an isolated experiment.
UT-Battelle manages ORNL for the DOE Office of Science, the single largest supporter of basic research in the physical sciences in the United States. Learn more about the Office of Science.
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