Harnessing Artificial Intelligence for the Unlimited Generation of Clean Energy through Fusion

In the pursuit of a cleaner, carbon-free future, nuclear fusion has emerged as a promising source of energy. This article explores the latest developments in the field, with a focus on the role of Artificial Intelligence (AI) in advancing fusion power plants.

Microsoft Corporation, a global leader in technology, is among those actively exploring nuclear energy and its acceleration via AI. In 2023, the tech giant signed a deal with private fusion startup Helion Energy to supply fusion-generated power to Microsoft data centers by 2028.

Plasma, a charged gas consisting of positive ions and free-moving electrons, is the substance at the heart of fusion reactions. Extremely hot and difficult to control, a magnetic field is required to prevent it from escaping. One of the major challenges for the next generation of fusion devices is the power exhaust, which needs innovative solutions in divertor design and operation.

AI is being utilised to address this challenge. A new AI approach, HEAT-ML, is being used to protect the insides of fusion reactors from the extreme heat of plasma. HEAT-ML significantly speeds up the calculations required to find "magnetic shadows" in the fusion containers, enabling the possibility of real-time applications for divertor protection and control actions.

HEAT-ML is a machine learning-based surrogate model designed to simulate a small part of SPARC, a tokamak under development by CFS. It uses a deep neural network to trace magnetic field lines from a component's surface to see if they intersect other internal parts, marking the intersection as a shadowed region or a magnetic shadow.

The public-private partnership between PPL, the DOE's Oak Ridge National Laboratory, and fusion power company Commonwealth Fusion Systems led to the development of HEAT-ML. The team created shadow masks, 3D maps of magnetic shadows, to protect the materials from direct heat. These maps are specific areas on the surfaces of a fusion system's internal components that are protected from direct heat.

AI is also being used to optimise reactor design, find and correct fundamental measurement errors, accelerate materials discovery, predict and prevent plasma disruptions, control the plasma state, and improve the efficiency and stability of fusion reactions.

While scientists have been able to routinely achieve conditions for nuclear fusion, plasma stability and improved confinement properties are yet to be attained to maintain the reaction and produce energy in a sustained manner. However, recent advancements in AI are bringing us closer to this goal.

In a significant milestone, a multibillion-dollar fusion experiment finally got a tiny isotope sample to release more energy than the laser energy used to ignite it, but it lasted only about one-tenth of a nanosecond. Despite this brief duration, it marks a significant step forward in the quest for sustainable nuclear fusion.

With AI playing an increasingly vital role in accelerating nuclear fusion research and development, the future of fusion power plants looks promising. AI models are being developed to forecast potential tearing mode instabilities in advance and then make changes to certain operating parameters to avoid the tearing within the plasma's magnetic field lines.

Nuclear fusion, a potential future source of clean energy, offers the promise of no carbon dioxide or other harmful emissions. As major institutions such as the international ITER project, the German Wendelstein 7-X Stellarator experiment, the UK Atomic Energy Authority, Russia’s Rosatom, and private companies like Helion Energy and Proxima Fusion continue their work, we move one step closer to harnessing the power of the stars on Earth.

The ultimate goal is to integrate the model for real-time control and future operational decisions for fusion power plants, with the aim of laying down the foundation for software that will accelerate the design of future fusion systems and prevent problems before they happen by adjusting the plasma. As we continue to make strides in this field, the prospect of a sustainable, carbon-free future powered by nuclear fusion becomes increasingly within reach.