MIT assistant professor Dean Price is developing advanced multiphysics models that could make small modular reactors commercially viable, potentially reshaping how startups and utilities approach clean energy.
Nuclear energy currently produces nearly 20 percent of United States electricity through 94 operating reactors, more than any other nation. Yet the field remains surprisingly niche, with a workforce so small that a single engineer can meaningfully influence the nation's carbon-free power output. Dean Price, an assistant professor in MIT's Department of Nuclear Science and Engineering, intends to do exactly that by solving a critical modeling problem standing between the industry and its next generation of reactors.
The reactors operating today are large-scale light water units, each generating roughly 1,000 megawatts. Modeling tools for these established designs work well enough. The challenge lies with what comes next: small modular reactors producing 20 to 300 megawatts, and microreactors rated at just 1 to 20 megawatts. These compact designs promise lower construction costs, enhanced safety profiles, and far greater flexibility in where and how they deploy. A microreactor could power a remote mining operation, a military base, or a data center campus without requiring the massive infrastructure of a traditional plant. The simulation methods needed to predict their behavior, however, remain rudimentary.
Price focuses on an approach called multiphysics modeling, which examines how different physical processes inside a reactor core interact simultaneously rather than in isolation. Two processes dominate. Neutronics describes how neutrons move through the core and trigger fission, the reaction that generates power. Thermal hydraulics covers how coolant flows through the system to extract the heat those neutrons produce. These two systems constantly influence each other: as fuel temperature rises, fission becomes less likely to occur. Understanding that feedback loop is essential for predicting how a reactor responds when operators adjust power levels or when conditions shift unexpectedly.
For conventional light water reactors, decades of operational data have refined multiphysics simulations into reliable tools. Engineers can model a 1,000-megawatt plant with reasonable confidence because the physics are well understood and validated against real-world performance. Small modular and microreactors operate under different conditions, use different materials, and in some cases rely on entirely different cooling approaches. The handful of advanced reactors running today simply does not generate enough operational data to build the same caliber of simulation. Price's work aims to close that gap, creating models accurate enough to give regulators confidence and developers predictability without waiting years for empirical results.
The timing matters because the commercial landscape is shifting rapidly. As CNBC recently reported, venture capital and government funding have poured into nuclear startups at levels not seen in decades, driven by surging electricity demand from artificial intelligence infrastructure, manufacturing reshoring, and electrification of transport and heating. Companies like Oklo, NuScale, and TerraPower are racing to bring advanced reactor designs to market within the next decade. The Department of Energy has backed multiple demonstration projects, and several states have passed legislation streamlining permitting for nuclear construction.
What this means for the energy market
If researchers like Price can deliver accurate, validated multiphysics models for small reactor designs, the practical implications are substantial. Better simulations reduce development costs by catching design flaws virtually rather than through expensive prototype testing. They accelerate regulatory approval by giving agencies like the Nuclear Regulatory Commission clearer pictures of how novel designs behave under stress. And they make nuclear projects more bankable, an important consideration for startups trying to raise hundreds of millions in project finance from investors who demand predictability.
Price came to this work through a straightforward calculus. The nuclear engineering community is small, close-knit, and deeply mission-driven, qualities that attracted him as an undergraduate at the University of Illinois, where he first studied the safety of dry cask storage for spent fuel. His analysis confirmed that current storage methods are safe, though the long-term disposal question remains unresolved politically. By graduate school at the University of Michigan, he had shifted toward reactor physics, drawn by the opportunity to shape technology still early enough in its development that a single researcher can move the needle.
For startups and investors watching the nuclear space, the trajectory of multiphysics modeling is worth tracking. Reactor designs may grab headlines, but the simulation tools validating those designs will quietly determine how quickly any of them actually get built. Expect modeling capabilities to become a competitive differentiator among advanced reactor companies, and a key factor in how fast the United States can scale its nuclear fleet beyond the 94 reactors operating today.
