OpenAI and the U.S. Department of Energy Team Up to Use Frontier AI to Speed Up Scientific Discovery

OpenAI has announced a collaboration with the U.S. Department of Energy (DOE) and its national laboratories. The partnership aims to apply frontier AI models to accelerate scientific research and discovery.

What OpenAI announced

OpenAI commits to advancing a new generation of American science by working directly with the U.S. Department of Energy and its network of national laboratories. The plan is to put the company's most powerful models to work on real research problems, from fundamental physics to energy and materials science. The company describes the move as a contribution to the "next era of national science" — which is also the title of its announcement.

The Department of Energy oversees one of the country's largest scientific infrastructures. According to DOE, it manages a network of 17 national laboratories, including Los Alamos, Oak Ridge, Argonne and Lawrence Berkeley, where researchers work on high-energy physics, nuclear security, climate science and computing.

Key facts from the announcement:

• Partners: OpenAI, the U.S. Department of Energy (DOE) and the national laboratories
• Tool: frontier AI models, the latest generation of advanced models
• Goal: accelerating scientific research and discovery
• Infrastructure: DOE manages a network of 17 U.S. national laboratories

Why national laboratories need AI

National laboratories need AI to compress research cycles that now take years. Frontier models help researchers screen hypotheses, simulate experiments and analyze huge datasets faster than research teams can by hand. In practice, that could mean faster screening of battery materials, the search for stable catalysts, or calculations of scenarios for fusion reactors.

The DOE national laboratories trace their history back to the 1940s; Los Alamos was founded in 1943 as part of the Manhattan Project. Their remit today is far broader: nuclear fusion, development of new materials and batteries, climate modeling, genomics and nuclear security.

The DOE national laboratories are also among the world's largest computing centers. In 2022, the Frontier supercomputer at Oak Ridge National Laboratory became the world's first exascale-class system, capable of more than a quintillion operations per second. That power, combined with frontier AI models, forms the "big compute plus big models" pairing the partnership is betting on.

Part of OpenAI's science strategy

OpenAI positions accelerating scientific discovery as one of the main goals of its technology. The partnership with the Department of Energy moves this line of work out of the demo stage and into applied work with U.S. national research infrastructure.

OpenAI reaffirms its commitment to advancing American science, working with the U.S.

Department of Energy and the national laboratories to apply advanced AI to accelerate discovery — that is how the company describes the core of the initiative in its blog.

The bet is not groundless: AI has already reshaped some areas of science. DeepMind's AlphaFold model predicted the structures of more than 200 million proteins and in 2024 earned its developers the Nobel Prize in Chemistry. OpenAI and DOE hope to repeat that leap in physics, energy and materials science. For the government, this is a way to connect the strongest commercial models to national-level problems; for OpenAI, it means access to unique scientific data and the computing resources of the national laboratories.

What this means

Frontier AI is moving beyond consumer products and chatbots into big science: OpenAI and the U.S. Department of Energy are betting that advanced models will speed up discoveries in energy, materials and fundamental physics. The announcement does not disclose specific projects or timelines. Still, a direct partnership between a leading AI lab and a government scientific system marks a new stage in the application of AI. For the industry, it is a signal: governments increasingly see advanced AI as a tool of scientific and technological sovereignty.