Nuclear fusion could be the holy grail of clean energy if scientists can crack the code of maintaining and controlling plasma for more efficient reactions. Nuclear fusion could provide critical amounts of baseload power all while producing zero greenhouse gas emissions and zero hazardous nuclear waste…someday. We’re still a long way away from being able to create the conditions for nuclear fusion to take place on a scale that’s anywhere close to energy-efficient or commercially viable. But a series of breakthroughs in the past few years have exponentially increased the speed of nuclear fusion development, bringing this potential green energy silver bullet much closer to reality than ever before.
This achievement can’t come fast enough. As runaway AI integration ratchets up energy demand growth projections across the world, tech sector bigwigs are increasingly looking to fusion research as a potential solution. Sam Altman, the founder and CEO of OpenAI, the firm behind ChatGPT, has personally invested hundreds of millions of dollars into nuclear fusion research. He sees fusion as a necessary development to meet the future needs of data centers. “There’s no way to get there without a breakthrough, we need fusion,” Altman said in a January interview.
But while the advancement of artificial intelligence has made the need for baseload clean energy more dire than ever, it could also be the key to unlocking the technology’s commercial potential. A new machine learning tool called Diag2Diag has made major steps forward in this effort. The tool can be used to help monitor and control plasma in fusion experiments, and particularly to avoid what is known as the Edge Localized Mode (ELM), a condition of instability that rapidly breaks down the materials around the plasma, causing major issues for huge and costly fusion plasma experiments like Europe’s ITER and China’s EAST.
Most nuclear fusion experiments use electromagnetic fields to control superheated plasma to mimic the conditions of our own sun and stars, which are powered by naturally occurring fusion reactions. This plasma, which can reach temperatures of 100 million degrees Celsius, is extremely unruly and difficult to control. When the plasma breaks out of its confines, it often signals the end of the fusion experiment and one more barrier to unlocking the potential of nuclear fusion as an earthbound clean energy source.
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ITER and EAST use enormous magnets to control plasma for their fusion experiments inside of massive donut-shaped reactors called tokamaks. But the “magnetic islands” created by this method are hard to observe and monitor. Diag2Diag provides a revolutionary solution to this issue. In layman’s terms, “the technology functions by analyzing the measurements from existing sensors to generate new, synthetic data for another sensor that may be failing or too slow to capture key events” according to a recent report from Interesting Engineering.
“With super-resolution diagnostics, we can experimentally verify theoretical models of magnetic islands for the first time, providing insights into their role in ELM stabilization,” the researchers write in a scientific paper detailing their breakthrough. “This advancement supports the development of effective ELM suppression strategies for future fusion reactors like ITER and has broader applications, potentially revolutionizing diagnostics in fields such as astronomy, astrophysics, and medical imaging.”
Despite this latest in a series of nuclear fusion breakthroughs, commercial nuclear fusion still remains decades out of reach – and some experts doubt whether it will ever be the silver bullet solutions that its backers promise. A narrow focus on fusion as a cure-all for AI’s drastic energy demand growth may be wishful thinking and even a misallocation of resources that would be better spent on proven clean energy technologies. According to Alex de Vries, a data scientist and researcher at Vrije Universiteit Amsterdam. “It would be a lot more sensible to focus on what we have at the moment, and what we can do at the moment, rather than hoping for something that might happen.”
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By Haley Zaremba for Oilprice.com
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