Energy

Tokamaks are machines that are meant to hold and harness the power of the sun. These fusion machines use powerful magnets to contain a plasma hotter than the sun’s core and push the plasma’s atoms to fuse and release energy. If tokamaks can operate safely and efficiently, the machines could one day provide clean and limitless fusion energy.Today, there are a number of experimental tokamaks in operation around the world, with more underway. Most are small-scale research machines built to investigate how the devices can spin up plasma and harness its energy. One of the challenges that tokamaks face is how to safely and reliably turn off a plasma current that is circulating at speeds of up to 100 kilometers per second, at temperatures of over 100 million degrees Celsius.Such “rampdowns” are necessary when a plasma becomes unstable. To prevent the plasma from further disrupting and potentially damaging the device’s interior, operators ramp down the plasma current. But occasionally the rampdown itself can destabilize the plasma. In some machines, rampdowns have caused scrapes and scarring to the tokamak’s interior — minor damage that still requires considerable time and resources to repair.Now, scientists at MIT have developed a method to predict how plasma in a tokamak will behave during a rampdown. The team combined machine-learning tools with a physics-based model of plasma dynamics to simulate a plasma’s behavior and any instabilities that may arise as the plasma is ramped down and turned off. The researchers trained and tested the new model on plasma data from an experimental tokamak in Switzerland. They found the method quickly learned how plasma would evolve as it was tuned down in different ways. What’s more, the method achieved a high level of accuracy using a relatively small amount of data. This training efficiency is promising, given that each experimental run of a tokamak is expensive and quality data is limited as a result.The new model, which the team highlights this week in an open-access Nature Communications paper, could improve the safety and reliability of future fusion power plants.“For fusion to be a useful energy source it’s going to have to be reliable,” says lead author Allen Wang, a graduate student in aeronautics and astronautics and a member of the Disruption Group at MIT’s Plasma Science and Fusion Center (PSFC). “To be reliable, we need to get good at managing our plasmas.”The study’s MIT co-authors include PSFC Principal Research Scientist and Disruptions Group leader Cristina Rea, and members of the Laboratory for Information and Decision Systems (LIDS) Oswin So, Charles Dawson, and Professor Chuchu Fan, along with Mark (Dan) Boyer of Commonwealth Fusion Systems and collaborators from the Swiss Plasma Center in Switzerland.“A delicate balance”Tokamaks are experimental fusion devices that were first built in the Soviet Union in the 1950s. The device gets its name from a Russian acronym that translates to a “toroidal chamber with magnetic coils.” Just as its name describes, a tokamak is toroidal, or donut-shaped, and uses powerful magnets to contain and spin up a gas to temperatures and energies high enough that atoms in the resulting plasma can fuse and release energy.Today, tokamak experiments are relatively low-energy in scale, with few approaching the size and output needed to generate safe, reliable, usable energy. Disruptions in experimental, low-energy tokamaks are generally not an issue. But as fusion machines scale up to grid-scale dimensions, controlling much higher-energy plasmas at all phases will be paramount to maintaining a machine’s safe and efficient operation.“Uncontrolled plasma terminations, even during rampdown, can generate intense heat fluxes damaging the internal walls,” Wang notes. “Quite often, especially with the high-performance plasmas, rampdowns actually can push the plasma closer to some instability limits. So, it’s a delicate balance. And there’s a lot of focus now on how to manage instabilities so that we can routinely and reliably take these plasmas and safely power them down. And there are relatively few studies done on how to do that well.”Bringing down the pulseWang and his colleagues developed a model to predict how a plasma will behave during tokamak rampdown. While they could have simply applied machine-learning tools such as a neural network to learn signs of instabilities in plasma data, “you would need an ungodly amount of data” for such tools to discern the very subtle and ephemeral changes in extremely high-temperature, high-energy plasmas, Wang says.Instead, the researchers paired a neural network with an existing model that simulates plasma dynamics according to the fundamental rules of physics. With this combination of machine learning and a physics-based plasma simulation, the team found that only a couple hundred pulses at low performance, and a small handful of pulses at high performance, were sufficient to train and validate the new model.The data they used for the new study came from the TCV, the Swiss “variable configuration tokamak” operated by the Swiss Plasma Center at EPFL (the Swiss Federal Institute of Technology Lausanne). The TCV is a small experimental fusion experimental device that is used for research purposes, often as test bed for next-generation device solutions. Wang used the data from several hundred TCV plasma pulses that included properties of the plasma such as its temperature and energies during each pulse’s ramp-up, run, and ramp-down. He trained the new model on this data, then tested it and found it was able to accurately predict the plasma’s evolution given the initial conditions of a particular tokamak run.The researchers also developed an algorithm to translate the model’s predictions into practical “trajectories,” or plasma-managing instructions that a tokamak controller can automatically carry out to for instance adjust the magnets or temperature maintain the plasma’s stability. They implemented the algorithm on several TCV runs and found that it produced trajectories that safely ramped down a plasma pulse, in some cases faster and without disruptions compared to runs without the new method.“At some point the plasma will always go away, but we call it a disruption when the plasma goes away at high energy. Here, we ramped the energy down to nothing,” Wang notes. “We did it a number of times. And we did things much better across the board. So, we had statistical confidence that we made things better.”The work was supported in part by Commonwealth Fusion Systems (CFS), an MIT spinout that intends to build the world’s first compact, grid-scale fusion power plant. The company is developing a demo tokamak, SPARC, designed to produce net-energy plasma, meaning that it should generate more energy than it takes to heat up the plasma. Wang and his colleagues are working with CFS on ways that the new prediction model and tools like it can better predict plasma behavior and prevent costly disruptions to enable safe and reliable fusion power.“We’re trying to tackle the science questions to make fusion routinely useful,” Wang says. “What we’ve done here is the start of what is still a long journey. But I think we’ve made some nice progress.”Additional support for the research came from the framework of the EUROfusion Consortium, via the Euratom Research and Training Program and funded by the Swiss State Secretariat for Education, Research, and Innovation. More

U.S. Secretary of Energy Chris Wright ’85 visited MIT on Monday, meeting Institute leaders, discussing energy innovation at a campus forum, viewing poster presentations from researchers supported through the MIT-GE Vernova Energy and Climate Alliance, and watching energy research demos in the lab where he used to work as a student. “I’ve always been in energy because I think it’s just far and away the world’s most important industry,” Wright said at the forum, which included a panel discussion with business leaders and a fireside chat with MIT Professor Ernest Moniz, who was the U.S. secretary of energy from 2013 to 2017. Wright added: “Not only is it by far the world’s most important industry, because it enables all the others, but it’s also a booming time right now. … It is an awesomely exciting time to be in energy.”Wright was greeted on campus by MIT President Sally Kornbluth, who also gave introductory remarks at the forum, held in MIT’s Samberg Center. While the Institute has added many research facilities and buildings since Wright was a student, Kornbluth observed, the core MIT ethos remains the same.“MIT is still MIT,” Kornbluth said. “It’s a community that rewards merit, boldness, and scientific rigor. And it’s a magnet for people with a drive to solve hard problems that matter in the real world, an enthusiasm for working with industry, and an ethic of national service.”When it comes to energy research, Kornbluth added, “MIT is developing transformational approaches to make American energy more secure, reliable, affordable, and clean — which in turn will strengthen both U.S. competitiveness and national security.”At the event, Wright, the 17th U.S. secretary of energy, engaged in a fireside chat with Moniz, the 13th U.S. secretary of energy, the Cecil and Ida Green Professor of Physics and Engineering Systems Post-Tenure, a special advisor to the MIT president, and the founding director of the MIT Energy Initiative (MITEI). Wright began his remarks by reflecting on Kornbluth’s description of the Institute.“Merit, boldness, and scientific rigor,” Wright said. “That is MIT … to me. That hit me hard when I got here, and frankly, it’s a good part of the reason my life has gone the way it’s gone.”On energy topics, Wright emphasized the need for continued innovation in energy across a range of technologies, including fusion, geothermal, and more, while advocating for the benefits of vigorous market-based progress. Before becoming secretary of energy, Wright most recently served as founder and CEO of Liberty Energy. He also was the founder of Pinnacle Technologies, among other enterprises. Wright was confirmed as secretary by the U.S. Senate in February.Asked to name promising areas of technological development, Wright focused on three particular areas of interest. Citing artificial intelligence, he noted that the interest in it was “overwhelming,” with many possible applications. Regarding fusion energy, Wright said, “We are going to see meaningful breakthroughs.” And quantum computing, he added, was going to be a “game-changer” as well.Wright also emphasized the value of federal support for fundamental research, including projects in the national laboratories the Department of Energy oversees.“The 17 national labs we have in this country are absolute jewels. They are gems of this country,” Wright said. He later noted, “There are things, like this foundational research, that are just an essential part of our country and an essential part of our future.”Moniz asked Wright a range of questions in the fireside chat, while adding his own perspective at times about the many issues connected to energy abundance globally.“Climate, energy, security, equity, affordability, have to be recognized as one conversation, and not separate conversations,” Moniz said. “That’s what’s at stake in my view.”Wright’s appearance was part of the Energy Freedom Tour developed by the American Conservation Coalition (ACC), in coordination with the Hamm Institute for American Energy at Oklahoma State University. Later stops are planned for Stanford University and Texas A&M University.Ann Bluntzer Pullin, executive director of the Hamm Institute, gave remarks at the forum as well, noting the importance of making students aware of the energy industry and helping to “get them excited about the impact this career can make.” She also praised MIT’s advances in the field, adding, “This is where so many ideas were born and executed that have allowed America to really thrive in this energy abundance in our country that we have [had] for so long.”The forum also featured remarks from Roger Martella, chief corporate officer, chief sustainability officer, and head of government affairs at GE Vernova. In March, MIT and GE Vernova announced a new five-year joint program, the MIT-GE Vernova Energy and Climate Alliance, featuring research projects, education programs, and career opportunities for MIT students.“That’s what we’re about, electrification as the lifeblood of prosperity,” Martella said, describing GE Vernova’s work. “When we’re here at MIT we feel like we’re living history every moment when we’re walking down the halls, because no institution has [contributed] to innovation and technology more, doing it every single day to advance prosperity for all people around the world.”A panel discussion at the forum featured Wright speaking along with three MIT alumni who are active in the energy business: Carlos Araque ’01, SM ’02, CEO of Quaise Energy, a leading-edge firm in geothermal energy solutions; Bob Mumgaard SM ’15, PhD ’15, CEO of Commonwealth Fusion Systems, a leading fusion energy firm and an MIT spinout; and Milo Werner SM ’07, MBA ’07, a general partner at DCVC and expert in energy and climate investments. The panel was moderated by Chris Barnard, president of the ACC.Mumgaard noted that Commonwealth Fusion Systems launched in 2018 with “an explicit mission, working with MIT still today, of putting fusion onto an industrial trajectory,” although there is “plenty left to do, still, at that intersection of science, technology, innovation, and business.”Araque said he believes geothermal is “metric-by-metric” more powerful and profitable than many other forms of energy. “This is not a stop-gap,” he added. Quaise is currently developing its first power-plant-scale facility in the U.S.Werner noted that the process of useful innovation only begins in the lab; making an advance commercially viable is the critical next step. The biggest impact “is not in the breakthrough,” she said. “It’s not in the discovery that you make in the lab. It’s actually once you’ve built a billion of them. That’s when you actually change the world.”After the forum, Wright took a tour of multiple research centers on the MIT campus, including the MIT.nano facility, guided by Vladimir Bulović, faculty director of MIT.nano and the Fariborz Maseeh Chair in Emerging Technology.At MIT.nano, Bulović showed Wright the Titan Krios G3i, a nearly room-size electron microscope that enables researchers to take a high-resolution look at the structure of tiny particles, with a variety of research applications. The tour also viewed one of MIT.nano’s cleanrooms, a shared fabrication facility used by both MIT researchers and users outside of MIT, including many in industry.On a different note, in an MIT.nano hallway, Bulović showed Wright the One.MIT mosaics, which contain the names of all MIT students and employees past and present — well over 300,000 in all. First etched on a 6-inch wafer, the mosaics are a visual demonstration of the power of nanotechnology — and a searchable display, so Bulović located Wright’s name, which is printed near the chin of one of the figures on the MIT seal.The tour ended in the basement of Building 10, in what is now the refurbished Grainger Energy Machine Facility, where Wright used to conduct research. After earning his undergraduate degree in mechanical engineering, Wright entered into graduate studies at MIT before leaving, as he recounted at the forum, to pursue business opportunities.At the lab, Wright met with David Perreault, the Ford Foundation Professor of Engineering; and Steven Leeb, the Emanuel Landsman Professor, a specialist in power systems. A half-dozen MIT graduate students gave Wright demos of their research projects, all involving energy-generation innovations. Wright readily engaged with all the graduate students about the technologies and the parameters of the devices, and asked the students about their own careers.Wright was accompanied on the lab tour by MIT Provost Anantha Chandrakasan, himself an expert in developing energy-efficient systems. Chandrakasan delivered closing remarks at the forum in the Samberg Center, noting MIT’s “strong partnership with the Department of Energy” and its “long and proud history of engaging industry.”As such, Chandrakasan said, MIT has a “role as a resource in service of the nation, so please don’t hesitate to call on us.” More

The new TX-Generative AI Next (TX-GAIN) computing system at the Lincoln Laboratory Supercomputing Center  (LLSC) is the most powerful AI supercomputer at any U.S. university. With its recent ranking from  TOP500, which biannually publishes a list of the top supercomputers in various categories, TX-GAIN joins the ranks of other powerful systems at the LLSC, all supporting research and development at Lincoln Laboratory and across the MIT campus. “TX-GAIN will enable our researchers to achieve scientific and engineering breakthroughs. The system will play a large role in supporting generative AI, physical simulation, and data analysis across all research areas,” says Lincoln Laboratory Fellow Jeremy Kepner, who heads the LLSC. The LLSC is a key resource for accelerating innovation at Lincoln Laboratory. Thousands of researchers tap into the LLSC to analyze data, train models, and run simulations for federally funded research projects. The supercomputers have been used, for example, to simulate billions of aircraft encounters to develop collision-avoidance systems for the Federal Aviation Administration, and to train models in the complex tasks of autonomous navigation for the Department of Defense. Over the years, LLSC capabilities have been essential to numerous award-winning technologies, including those that have improved  airline safety,  prevented the spread of new diseases, and  aided in hurricane responses. As its name suggests, TX-GAIN is especially equipped for developing and applying generative AI. Whereas traditional AI focuses on categorization tasks, like identifying whether a photo depicts a dog or cat, generative AI produces entirely new outputs. Kepner describes it as a mathematical combination of interpolation (filling in the gaps between known data points) and extrapolation (extending data beyond known points). Today, generative AI is widely known for its use of large language models to create human-like responses to user prompts. At Lincoln Laboratory, teams are applying generative AI to various domains beyond large language models. They are using the technology, for instance, to evaluate radar signatures, supplement weather data where coverage is missing, root out anomalies in network traffic, and explore chemical interactions to design new medicines and materials.To enable such intense computations, TX-GAIN is powered by more than 600 NVIDIA graphics processing unit accelerators specially designed for AI operations, in addition to traditional high-performance computing hardware. With a peak performance of two AI exaflops (two quintillion floating-point operations per second), TX-GAIN is the top AI system at a university, and in the Northeast. Since TX-GAIN came online this summer, researchers have taken notice. “TX-GAIN is allowing us to model not only significantly more protein interactions than ever before, but also much larger proteins with more atoms. This new computational capability is a game-changer for protein characterization efforts in biological defense,” says Rafael Jaimes, a researcher in Lincoln Laboratory’s Counter–Weapons of Mass Destruction Systems Group. The LLSC’s focus on interactive supercomputing makes it especially useful to researchers. For years, the LLSC has pioneered software that lets users access its powerful systems without needing to be experts in configuring algorithms for parallel processing.  “The LLSC has always tried to make supercomputing feel like working on your laptop,” Kepner says. “The amount of data and the sophistication of analysis methods needed to be competitive today are well beyond what can be done on a laptop. But with our user-friendly approach, people can run their model and get answers quickly from their workspace.”Beyond supporting programs solely at Lincoln Laboratory, TX-GAIN is enhancing research collaborations with MIT’s campus. Such collaborations include the Haystack Observatory, Center for Quantum Engineering, Beaver Works, and Department of Air Force–MIT AI Accelerator. The latter initiative is rapidly prototyping, scaling, and applying AI technologies for the U.S. Air Force and Space Force, optimizing flight scheduling for global operations as one fielded example.The LLSC systems are housed in an energy-efficient data center and facility in Holyoke, Massachusetts. Research staff in the LLSC are also tackling the immense energy needs of AI and leading research into various power-reduction methods. One software tool they developed can reduce the energy of training an AI model by as much as 80 percent.”The LLSC provides the capabilities needed to do leading-edge research, while in a cost-effective and energy-efficient manner,” Kepner says.All of the supercomputers at the LLSC use the “TX” nomenclature in homage to Lincoln Laboratory’s Transistorized Experimental Computer Zero (TX-0) of 1956. TX-0 was one of the world’s first transistor-based machines, and its 1958 successor, TX-2, is storied for its role in pioneering human-computer interaction and AI. With TX-GAIN, the LLSC continues this legacy. More

Mostafa Fawzy became interested in physics in high school. It was the “elegance and paradox” of quantum theory that got his attention and led to his studies at the undergraduate and graduate level. But even with a solid foundation of coursework and supportive mentors, Fawzy wanted more. MIT Open Learning’s OpenCourseWare was just the thing he was looking for.  Now a doctoral candidate in atomic physics at Alexandria University and an assistant lecturer of physics at Alamein International University in Egypt, Fawzy reflects on how MIT OpenCourseWare bolstered his learning early in his graduate studies in 2019.  Part of MIT Open Learning, OpenCourseWare offers free, online, open educational resources from more than 2,500 courses that span the MIT undergraduate and graduate curriculum. Fawzy was looking for advanced resources to supplement his research in quantum mechanics and theoretical physics, and he was immediately struck by the quality, accessibility, and breadth of MIT’s resources. “OpenCourseWare was transformative in deepening my understanding of advanced physics,” Fawzy says. “I found the structured lectures and assignments in quantum physics particularly valuable. They enhanced both my theoretical insight and practical problem-solving skills — skills I later applied in research on atomic systems influenced by magnetic fields and plasma environments.”  He completed educational resources including Quantum Physics I and Quantum Physics II, calling them “dense and mathematically sophisticated.” He met the challenge by engaging with the content in different ways: first, by simply listening to lectures, then by taking detailed notes, and finally by working though problem sets. Although initially he struggled to keep up, this methodical approach paid off, he says. He is grateful to his undergraduate mentors, professors M. Sakr and T. Bahy of Alexandria University, as well as to MIT OpenCourseWare, calling it a “steadfast companion through countless solitary nights of study, a beacon in times when formal resources were scarce, and a living testament to the nobility of open, unbounded learning.”  Recognizing the power of mentorship and teaching, Fawzy serves as an academic mentor with the African Academy of Sciences, supporting early-career researchers across the continent in theoretical and atomic physics.  “Many of these mentees lack access to advanced academic resources,” he explains. “I regularly incorporate OpenCourseWare into our mentorship sessions, using it as a foundational teaching and reference tool. It’s an equalizer, providing the same high-caliber content to students regardless of geographical or institutional limitations.” As he looks toward the future, Fawzy has big plans, influenced by MIT. “I aspire to establish a regional center for excellence in atomic and plasma physics, blending cutting-edge research with open-access education in the Global South,” he says. As he continues his research and teaching, he also hopes to influence science policy and contribute to international partnerships that shine the spotlight on research and science in emerging nations.  Along the way, he says, “OpenCourseWare remains a cornerstone resource that I will return to again and again.”  Fawzy says he’s also interested in MIT Open Learning resources in computational physics and energy and sustainability. He’s following MIT’s Energy Initiative, calling it increasingly relevant to his current work and future plans.  Fawzy is a proponent of open learning and a testament to its power. “The intellectual seeds sown by Open Learning resources such as MIT OpenCourseWare have flourished within me, shaping my identity as a physicist and affirming my deep belief in the transformative power of knowledge shared freely, without barriers,” he says.  More