Latest news with #LawrenceLivermore
Gizmodo
4 days ago
- Science
- Gizmodo
Scientists Taught AI to Predict Nuclear Fusion Success—and It's Actually Working
AI is giving a huge efficiency boost to one of the biggest nuclear fusion facilities in the world—but perhaps not in the way you think. In research published today in Science, scientists at Lawrence Livermore National Laboratory report how its newly developed deep learning model accurately predicted the results of a 2022 fusion experiment at the National Ignition Facility (NIF). The model, which assigned 74% probability for ignition in that experiment, outperforms traditional supercomputing methods by covering more parameters with greater precision. 'What we're excited about with this model is the ability to explicitly make choices for future experiments that maximize our probability of success each time,' study co-author Kelli Humbird told Gizmodo during a video call. Even a facility as large and well-established as the NIF can only 'do a couple dozen of these ignition attempts per year—so really not very many at all, given how much territory we have to cover,' added Humbird, who leads the Cognitive Simulation Group at NIF's Inertial Confinement Fusion Program. Currently, nuclear power plants run on nuclear fission, which captures the energy generated by the splitting of heavy atoms, like uranium. Researchers eventually want to shift toward nuclear fusion, a process that combines lightweight hydrogen atoms to release massive amounts of energy. Fusion produces more energy and doesn't create harmful, radioactive byproducts, so having fusion as a reliable source of energy would greatly benefit our society's transition to sustainable energy. Although the field has made some promising advances, the consensus is that we're still far from implementing nuclear fusion on a commercial scale. NIF's fusion experiments are laser-driven. First, the lasers heat up a gold cylinder called the hohlraum, which then emits a flow of powerful X-rays. The extreme temperatures compress the fuel pellets containing deuterium and tritium, two hydrogen isotopes used in fusion experiments. In an ideal scenario, this triggers enough deuterium-tritium fusion reactions to produce more energy than the lasers consume. Computer simulations can't reliably predict all the physics in this process, Humbird said. That's in part because the codes are often simplified so they're 'computationally tractable,' but the simulations themselves can also introduce some errors. Even if you've taken all sorts of precautions, it still takes days for the computers to finish running through the code, she added. Achieving nuclear fusion is like scaling a tall, uncharted mountain, Humbird said. The computer simulations are like an 'imperfect' map that's supposed to teach researchers how to reach the peak—but this map could be rife with errors that may or may not be the product of their research design. Meanwhile, the clock is ticking, and researchers have to quickly decide whether they'll take the hike that day and which tools they're going to use. And of course, each 'hike,' or ignition attempt, burns a huge hole in the budget. And so, Humbird's team embarked on a mapmaking quest, stitching together 'previously collected NIF data, high-fidelity physics simulations, and subject matter expert knowledge' to build a comprehensive dataset. Then, they uploaded the data to state-of-the-art supercomputers, which ran a statistical analysis lasting over 30 million CPU hours. 'What we basically came up with was a distribution of things that go wrong [at] NIF,' Humbird explained. 'All of the different ways that we have observed implosions. Sometimes the laser doesn't fire exactly how you asked it to. Sometimes your target has defects in it that can cause things to not go super well.' The model allows researchers to preemptively determine the efficacy of their experimental design, saving them considerable time and money. Humbird used the model to assess their own design from a 2022 experiment, which accurately described the results of the specific run in advance. In particular, Humbird was pleased to see that subsequent tweaks to the model's physics increased the accuracy of its predictions from 50 to 70%. For Humbird, the strength of the new model is that it accepts and replicates the imperfections of the real world—whether that's a flaw in the instrument, research design, or just some silly trick of nature. At the same time, it's a reminder that, while quick progress is exciting, things often take a lot of time and will even result in outright failure. 'People have been working on fusion for decades… We shouldn't be so bummed about the times things don't work,' Humbird said. 'The fact that we sometimes get 1 megajoule of yield instead of two shouldn't upset us, because not too long ago we were only getting 10 kilojoules. It's a huge step forward for research, and hopefully a huge step forward for clean energy in the future.'
Yahoo
03-07-2025
- Business
- Yahoo
Oklo (OKLO) Partners for HALEU Production with AVLIS Technology
Oklo Inc. (NYSE:OKLO) is one of the top 10 nuclear energy stocks to invest in for the next decade. On June 25, the company announced strategic collaborations aimed at accelerating the domestic production of High-Assay Low-Enriched Uranium (HALEU). Photo by Frédéric Paulussen on Unsplash The company partnered with Hexium, a company specializing in isotope enrichment, and TerraPower, a nuclear innovation company, to evaluate Atomic Vapor Laser Isotope Separation (AVLIS) technology for commercial-scale uranium enrichment. The collaboration includes Lawrence Livermore National Laboratory (LLNL), which is working with the three companies to assess the potential of AVLIS as a scalable uranium enrichment technology. According to Oklo, this initiative aims to develop 'a validated conceptual design and technoeconomic assessment of AVLIS-based HALEU production.' Oklo's stock has gained over 500% this year, which, according to the CEO, is driven by three key factors: an advanced nuclear focus, AI and data center demand, and a cost and deployment edge. Jacob DeWitte, the CEO, emphasized Oklo's role as an energy infrastructure disruptor, likening their microreactor tech to a 'data center revolution' in energy. Oklo Inc. (NYSE:OKLO) is a nuclear energy company. It develops advanced fission power plants—specifically compact, modular reactors designed to deliver clean, reliable, and affordable electricity. Its flagship product is the Aurora Powerhouse, which uses recycled nuclear waste as fuel. While we acknowledge the potential of OKLO as an investment, we believe certain AI stocks offer greater upside potential and carry less downside risk. If you're looking for an extremely undervalued AI stock that also stands to benefit significantly from Trump-era tariffs and the onshoring trend, see our free report on the best short-term AI stock. READ NEXT: 10 Best Healthcare Penny Stocks to Buy According to Analysts and Goldman Sachs Energy Stocks: 10 Stocks to Buy. Disclosure: None. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Gizmodo
19-05-2025
- Science
- Gizmodo
Record-Breaking Fusion Lab More Than Doubles Its 2022 Energy Breakthrough
The world's only fusion experiment that actually gives back more energy than it takes in is now breaking its own records. According to TechCrunch, the National Ignition Facility (NIF) at Lawrence Livermore National Laboratory recently pushed its fusion yield—first to 5.2 megajoules, and then to 8.6 megajoules—more than doubling the energy released in its historic shot in 2022. That original breakthrough was the first time scientists had ever achieved 'ignition'—a fusion reaction that generated more energy (3.15 megajoules) than the lasers put into the fuel (2.05 megajoules). Importantly, that achievement does not take into account the amount of energy put into the system to power the reaction—essentially, 300 megajoules of energy from the plug in the wall. Nevertheless, the accomplishment indicated the tantalizing promise of nuclear fusion as a carbon-free, essentially limitless source of energy. Jill Hruby, the under secretary for nuclear security, summed it up as 'the first tentative steps towards a clean energy source that could revolutionize the world.' Fusion isn't new—scientists have been chasing it for nearly a century. The problem has always been scale: It generally costs way more energy to trigger a fusion reaction than what comes out of said reaction. The NIF's achievement changed that—for a moment, humanity replicated the energy source of stars and came out ahead. The new surge in energy yield is a large jump for the experiment, though it's still very far off from providing a sustainable clean energy source (consider the 300 megajoules necessary to power the 2022 experiment). And that's to say nothing of building an actual fusion energy plant, and figuring out a way to produce fusion power at scale and integrate the budding technology into the world's power grid. The system works via inertial confinement fusion, using 192 laser beams to compress a diamond-coated pellet the size of a peppercorn—basically giving it a tiny, star-like explosion inside a golden cylinder. The laser blast occurs inside a 10-meter-wide vacuum chamber, heating the fuel to over 100 million degrees Fahrenheit and pressures hundreds of billion of times Earth's atmosphere. The team repeated the trick in 2023, and by the recent report, it seems the experiment's efficiency has only improved. Experts still see big roadblocks for inertial confinement as a practical energy source. That's why other teams are pursuing other means of fusion—namely magnetic confinement, which uses magnetic fields to hold plasma—to prove that pathway to clean energy. Other projects like ITER—a massive tokamak under construction in France—are attempting to generate record amounts of energy output, though they will never be part of the energy grid. Still, fusion's long-held reputation as a pipe dream—'always 30 years away'—might finally be changing. The engineering problems ensnaring the field are vast, but the substantial progress of NIF is an indication of the field's momentum at a time when the world is in dire need of clean energy solutions at scale.
