{"id":422905,"date":"2026-09-01T14:14:18","date_gmt":"2026-09-01T14:14:18","guid":{"rendered":"https:\/\/www.newsbeep.com\/us-tx\/422905\/"},"modified":"2026-09-01T14:14:18","modified_gmt":"2026-09-01T14:14:18","slug":"fusion-energy-seed-grants-launch-new-interdisciplinary-collaborations-at-ut-austin","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/us-tx\/422905\/","title":{"rendered":"Fusion Energy Seed Grants Launch New Interdisciplinary Collaborations at UT Austin"},"content":{"rendered":"

Fusion energy is having a moment \u2014 and a longstanding, fusion-focused institute at The University of Texas at Austin stands ready to meet that moment head-on.\u00a0<\/p>\n

During the three and a half years since scientists at the Lawrence Livermore National Laboratory first achieved fusion ignition, there have been many developments.<\/p>\n

Last year, the private sector alone invested $2.6 billion in fusion energy research and development, a number that\u2019s projected to grow significantly this year.\u00a0<\/p>\n

Several private companies are now racing to build demonstration reactors, and a recent survey of fusion energy companies<\/a> found that 71% believe the first fusion power plant will deliver commercial electricity by 2040.<\/p>\n

The U.S. Department of Energy (DOE) is investing in research through various initiatives, including its Fusion Innovation Research Engine (FIRE) Collaboratives, two of which include researchers in The University of Texas at Austin\u2019s Institute for Fusion Studies.\u00a0<\/p>\n

The DOE has also launched the Genesis Mission<\/a>, which, among other things, provides support to universities, national labs and industry to apply artificial intelligence to accelerate the commercialization of fusion. One of its first awarded projects, just announced<\/a> in July, is a collaboration involving UT\u2019s Oden Institute for Computational Engineering and Sciences and Sandia National Laboratories.<\/p>\n

To keep UT Austin at the forefront of this booming field, Diego del-Castillo-Negrete, director of the Institute for Fusion Studies<\/a> (IFS), created a seed funding program to build bridges between the physicists in the institute and experts in the Oden Institute and Cockrell School of Engineering. Funding is provided by all three units. Four of these grants \u2014 each involving a principal investigator in either Oden or Cockrell and a second PI at IFS \u2014 were recently awarded and will support four graduate students for two years as they conduct interdisciplinary research.<\/p>\n

Bringing engineers and experts in other fields \u2014 who are accustomed to applying numerical methods to a wide range of problems outside of fusion reactors \u2014 to one of the trickiest problems in all of physics will benefit researchers across domains. Physicists will get to use new numerical methods, as engineers get to tackle problems in domains they haven\u2019t worked on yet.<\/p>\n

\u201cBringing together teams with complementary expertise, from plasma physics and from engineering, will allow us to make an impact in a way that these two different groups could never dream of alone,\u201d said UT physicist David Hatch.<\/p>\n

The new collaborations will also address a key pain point for the fusion energy industry: workforce development. Private companies need to find enough talented, creative thinkers to overcome the myriad challenges of getting a highly complex new source of energy into the world.<\/p>\n

\u201cIf we\u2019re successful with these grants, these four graduate students will find and maintain an interest in fusion research, get Ph.D.s related to this work, publish papers and gain experience that will carry them on into industry or academia,\u201d del-Castillo-Negrete said.<\/p>\n

Aligning well with DOE\u2019s focus on AI in fusion energy, three of the four newly funded collaborations involve taking big, complex computer simulations that require a tremendous amount of time and energy to run, and replacing them with far more efficient AI models that have been trained on the data produced by their beefier predecessors. The goal with each of these surrogate AI models is to produce results that are just as accurate, but at a fraction of the cost and time. Building partnerships to last is another core goal.<\/p>\n

\u201cThe most exciting aspect for me is actually the prospect of having it balloon into a larger collaboration with another research group,\u201d said Josh Burby, assistant professor of physics, one of the co-PIs on a new seed grant. \u201cYou know, it\u2019s not always easy to build bridges with other faculty because everyone is so busy. I\u2019m really excited that this will be a very structured and mutually beneficial way of building one of those bridges.\u201d<\/p>\n

Read more about the four new projects below.<\/p>\n

\"imageThis sketch of a tokamak fusion reactor highlights three aspects targeted in these four UT Austin projects: (i) the plasma edge, (ii) the magnetic confinement field, and (iii) traces of particle orbits (such as alpha particles that must be contained to sustain the plasma). Adapted from D. del-Castillo-Negrete et al., IAEA, Proc. 27th Int. Conference (2018).<\/p>\n

Under Control<\/p>\n

Problem: A tokamak fusion reactor is like a set of Russian nesting dolls \u2014 a donut-shaped plasma floats inside a larger, donut-shaped vessel, trapped by a donut-shaped magnetic field. To avoid damaging the container, the plasma must maintain this exact shape and alignment. But a host of different kinds of instabilities can easily creep in, for example, causing the plasma to drift away from the center line or making the surface wavy instead of smooth. These instabilities can increase interactions between the plasma and the inner wall of the container or other components, leading to loss of confinement.\u00a0<\/p>\n

Solution: Develop a kind of digital twin of the plasma, based on indirect sparse measurements, that tells you its 3D shape, alignment and other properties in real time. And then use that digital twin to continuously tweak the knobs of a second set of magnetic coils to help keep the plasma well behaved. (Note: The Genesis Mission project, involving Oden Institute director Karen Willcox, is applying digital twins to the components inside the fusion energy reactor, from design through years of service, so those parts can be built and trusted to survive extreme heat, radiation and chemical stress.)<\/p>\n

The Team\u2019s Plan: Diego Del-Castillo-Negrete (IFS), Omar Ghattas (Oden Institute\/Cockrell School) and Aaron West (graduate student in the Computational Science, Engineering, and Mathematics interdisciplinary program) plan to use a computationally expensive, yet high fidelity simulation to generate a set of training data for a surrogate AI model that\u2019s fast and accurate. This then can serve as a digital twin that provides real-time control optimization.<\/p>\n

What Could Come Next: The researchers aim to build a real-time control optimization system that is faster and more accurate than state-of-the-art systems such as the one announced by Google\u2019s DeepMind group in 2022<\/a>. Eventually, they hope to test their model in a working fusion reactor, like the Variable Configuration Tokamak (TCV) in Lausanne, Switzerland or the DIII-D tokamak at General Atomics in San Diego.<\/p>\n

\u201cMachine learning methods recently applied to plasma control, such as reinforcement learning, have demonstrated impressive capabilities, but they can require large amounts of simulated training data and offer limited guarantees,\u201d del-Castillo-Negrete said. \u201cOur project with Omar\u2019s team brings together unique expertise in physics-constrained optimization, adjoint methods, uncertainty quantification, and real-time neural-operator surrogates \u2014 a potentially transformative combination for fast, reliable fusion plasma control.\u201d<\/p>\n

\"imageScientists are experimenting with ways of using liquid metals to cool excess heat from fusing plasma. Shown here is a stream of a liquid metal alloy. Credit: Michael Livingston\/Princeton Plasma Physics Laboratory.<\/p>\n

Liquid Metal Alloys<\/p>\n

Problem: The plasma inside a fusion reactor generates so much heat, radiation and high-energy particles that it can potentially destroy the surrounding walls and other plasma-facing components. One possible solution is to build them out of \u201cliquid metals\u201d \u2014 such as lithium, indium, gallium or tin \u2014 that can be continuously recycled to replenish the surface. But there\u2019s a catch: No pure liquid metal has all the properties that are desirable for a fusion reactor.<\/p>\n

Solution: A potential alternative would be an alloy of a liquid metal with other materials that would have a better mix of properties than any individual liquid metal. This idea builds on concepts that were first developed at UT Austin and led to a spinoff company that\u2019s exploring liquid metals for fusion reactors, called ExoFusion.\u00a0<\/p>\n

The Team\u2019s Plan: David Hatch (IFS), Narayana Aluru (Oden Institute\/Cockrell School), Yuanyue Liu (Oden Institute\/Cockrell School), and Md Rashidul Alam (Cockrell School graduate student) will work to find candidate alloys by running big computer simulations. They aim to learn what happens to liquid metal alloys in contact with a plasma for extremely short periods (tens of picoseconds) and then use that data to train machine learning models that can then simulate these alloys at much longer timescales, but using far fewer computing resources than a traditional simulation does.<\/p>\n

What Could Come Next: Once the researchers identify strong candidates, they have multiple partnerships to test them in real-world experiments funded by the DOE, including at Penn State and at a soon-to-be-online fusion platform at Princeton University, called NSTX-U.<\/p>\n

\u201cOne of the most compelling aspects of this project is that it\u2019s coming at just the right time to test our candidate alloys out in a real fusion environment,\u201d Hatch said.\u00a0<\/p>\n

\"imageIn the project related to plugging \u201cmagnetic bottles,\u201d an AI model (center) will be trained to ingest a candidate magnetic field configuration (left) and return the distribution of fusion-born alpha particles after they\u2019ve had time to escape (right). This will allow scientists to rapidly assess the size of leaks in the magnetic bottle, hopefully faster than any previous method. Credit: Nicholas Nelsen.<\/p>\n

Plugging Magnetic Bottles<\/p>\n

Problem: When high-energy alpha particles leak from a fusion reactor, the plasma is prevented from getting hot and dense enough to sustain fusion. To prevent them from leaking, engineers design elaborate magnetic confinement systems, or \u201cmagnetic bottles,\u201d but there are often holes in the magnetic field. In the design phase, they can run simulations to track thousands to millions of alpha particles moving through the device to determine where they tend to leak out and how quickly, allowing them to tweak the design. But it\u2019s slow, takes much computing power, and requires many iterations to optimize a design.<\/p>\n

Solution: Advances in artificial intelligence could help designers explore potential designs faster and more accurately than previously possible.<\/p>\n

The Team\u2019s Plan: Josh Burby (IFS), Nicholas Nelsen (Oden Institute\/Cockrell School) and Matthew Meeker (Oden Institute graduate student) plan to train a surrogate AI model to track these particle trajectories more efficiently than the state-of-the-art model, perhaps 10 to 100 times as fast.<\/p>\n

What Could Come Next: \u201cRight now, where people might either not do these alpha particle calculations during design, or maybe they\u2019ll use them for fine-tuning a design late in the process, our hope is that these machine learning-based tools we develop will allow people to confidently include these alpha particle calculations in all of their design optimizations without worrying about how much it\u2019s going to slow down the process,\u201d Burby said. \u201cThe thing that I\u2019m most excited about technically is that if we can demonstrate a significant speed-up on this aspect of the problem, then we should have a very good shot at enticing private fusion companies to use our methods and even partner with us.\u201d<\/p>\n

\"AA colorized photograph of the inside of NSTX-U, an experimental fusion reactor that could be used to test liquid metal alloys identified by UT Austin. Credit: Princeton Plasma Physics Laboratory.<\/p>\n

Living on the Edge<\/p>\n

Problem: Inside a fusion reactor, some designs have a feature called a divertor \u2014 which functions somewhat like the exhaust on a car \u2014 it\u2019s where excess heat and high-energy particles are funneled away or \u201cscraped off.\u201d To design a working fusion reactor, you need a high-fidelity computer simulation of how the scrape-off layer behaves, but the scrape-off layer (or SOL, meaning the outer edge of the plasma) is much more complex and challenging to simulate than the core of the plasma. State-of-the-art simulations are accurate but slow and costly in terms of computing resources.<\/p>\n

Solution: Take advantage of numerical techniques that are new, at least in this setting, to develop a higher fidelity simulation that is faster and cheaper.<\/p>\n

The Team\u2019s Plan: Diego Del-Castillo-Negrete (IFS), George Biros (Oden Institute\/Cockrell School) and Joseph Wick (Oden Institute graduate student) aim, in del-Castillo-Negrete\u2019s words, to \u201cleverage UT Austin\u2019s unique expertise to develop the next generation of state-of-the-art numerical tools for the fast and accurate simulation of the plasma edge.\u201d<\/p>\n

What Could Come Next: \u201cThis collaboration is a win-win because we are bringing unique problems from plasma physics that our colleagues in computational engineering and sciences haven\u2019t encountered before, for which they can develop their own numerical techniques, which is their cup of tea,\u201d del-Castillo-Negrete said. \u201cAnd by bringing in new, advanced numerical methods, we hope they\u2019ll help us crack this problem that\u2019s critical for fusion energy.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"Fusion energy is having a moment \u2014 and a longstanding, fusion-focused institute at The University of Texas at…\n","protected":false},"author":2,"featured_media":422906,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[132,134,133],"class_list":["post-422905","post","type-post","status-publish","format-standard","has-post-thumbnail","category-austin","tag-austin","tag-austin-headlines","tag-austin-news"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/posts\/422905","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/comments?post=422905"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/posts\/422905\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/media\/422906"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/media?parent=422905"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/categories?post=422905"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/tags?post=422905"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}