AI solves nuclear fusion puzzle for near-limitless clean energy
By Daniel Walker | March 28, 2024
Advancing the quest
In a groundbreaking development, a team of scientists from Princeton University has successfully harnessed the power of artificial intelligence (AI) to predict and prevent instabilities within plasma during nuclear fusion reactions.
This achievement holds immense promise for advancing the quest for near-limitless clean energy through nuclear fusion.
Revolutionize energy production
Nuclear fusion, the process by which two atoms merge to release a tremendous amount of energy, holds the potential to revolutionize energy production. This clean energy source, akin to the power of the sun, offers the prospect of abundant energy without reliance on fossil fuels or the generation of hazardous waste.
Superheated plasma
However, maintaining the stability of the superheated plasma within fusion reactors presents a significant challenge, as even a momentary instability can terminate the fusion reaction and potentially damage the reactor.
U.S. Department of Energy
The team at Princeton University, in collaboration with the U.S. Department of Energy's Princeton Plasma Physics Laboratory (PPPL), leveraged AI to address this critical issue.
Researchers trained a model
Through the use of AI, the researchers trained a model to predict tearing mode instabilities—disruptions in the magnetic field lines within plasma that can lead to the escape of the plasma from a tokamak's control, thereby halting the fusion reaction.
Past experiments
The AI model, having been fed data from past experiments at the DIII-D tokamak in San Diego, was trained to anticipate the likelihood of tearing mode instabilities based on real-time plasma characteristics.
Trial and error
Subsequently, it was used to train a reinforcement learning algorithm, which learns through trial and error, to control the fields and prevent predicted tearing mode instabilities in simulated fusion experiments.
Fusion experiment
The researchers successfully tested their AI algorithm in a real fusion experiment at the DIII-D tokamak, demonstrating its ability to predict tearing mode instabilities up to 300 milliseconds in advance.
Timely action t
This advance notice allows the system to take timely action to avert instabilities, thereby maintaining a stable, high-powered plasma regime in real time.
Proof of concept
While this achievement represents a pivotal proof of concept, the team plans to conduct further experiments at the DIII-D tokamak and explore the expansion of the AI's capabilities to predict and prevent other issues hindering the sustainable realization of nuclear fusion.
Several types of instabilities
This includes the potential to simultaneously control for several types of instabilities, paving the way for more comprehensive and effective AI solutions for fusion reactions.
Nuclear fusion
The successful integration of AI to predict and prevent instabilities within nuclear fusion reactions marks a significant stride in the pursuit of near-limitless clean energy.
Offers a pathway
This pioneering approach not only offers a pathway to surmounting the challenges of maintaining stable fusion reactions but also holds the potential to propel the realization of fusion power as a transformative and sustainable energy source for the future.
Enabled by the fusion
This groundbreaking development, enabled by the fusion of AI and plasma physics, represents a crucial step forward in the quest for near-limitless clean energy through nuclear fusion.
