AI Solves Nuclear Fusion Quandary For Almost Limitless Clean Energy

Princeton researchers made a major breakthrough toward realizing viable nuclear fusion energy, a promising clean energy source. Using artificial intelligence, the scientists significantly improved the confinement of the hot plasma that fuels fusion reactions.

The advances at Princeton’s tokamak bring scientists substantially closer to the goal of harnessing fusion energy on a commercial scale. Nuclear fusion promises immense benefits as an abundant, safe, and environmentally friendly energy solution.

The Promise of Nuclear Fusion Energy

If harnessed successfully, nuclear fusion reactions could provide an abundant source of clean energy without producing greenhouse gas emissions. Unlike nuclear fission, which splits atoms to release energy, nuclear fusion combines lighter atoms into heavier ones, releasing vast amounts of energy in the process.

The input fuels for nuclear fusion are abundant: deuterium can be extracted from seawater, and tritium can be produced from lithium. While nuclear fusion promises significant benefits, achieving controlled nuclear fusion reactions has proven extremely challenging.

A Promising Step Towards Viable Fusion Energy

The results represent an important step towards developing nuclear fusion as a viable source of clean energy. Predicting and preventing plasma instabilities has been one of the biggest roadblocks in achieving controlled nuclear fusion.

The AI control system developed by researchers at Princeton provides a promising solution to this challenge and a foundation for further optimizing plasma performance. With continued progress, nuclear fusion could emerge as an abundant source of clean energy to meet the world’s needs while mitigating the worst effects of climate change.

Challenges in Achieving Sustained Nuclear Fusion

Nuclear fusion holds immense promise as a source of clean energy, but realizing its potential on a commercial scale faces significant challenges. Chief among them is controlling the volatile plasma at the high temperatures required for fusion.

The plasma used in nuclear fusion experiments must be heated to extremely high temperatures, over 100 million degrees Celsius, to enable the fusion of hydrogen isotopes. At these temperatures, the plasma becomes unstable and prone to disruptions that can damage the reactor.

Scaling Up to Commercial Viability

Producing energy at a commercially viable scale requires sustaining plasma at high enough temperatures and densities for long durations. The record for sustaining fusion currently stands at five seconds, achieved by scientists at the Lawrence Livermore National Laboratory in California in 2022. Sustaining the reaction for minutes at a time will be required for commercial power plants.

In addition to controlling instabilities, this will require advances in superconducting magnets, reactor materials that can withstand the heat and neutron bombardment, and generating and harnessing the heat produced. Despite recent progress, most experts estimate that commercially viable fusion power plants are still 15-25 years away.

How Princeton Is Using AI to Overcome Barriers

Princeton researchers have devised a novel solution to forecast and mitigate instabilities in the plasma during nuclear fusion reactions. According to Kolemen, the team developed an AI model trained on data from past experiments at the DIII-D National Fusion Facility to anticipate disruptive events up to 300 milliseconds in advance.

Source: Adena Stevens

With adequate warning, the AI controller can make adjustments to stabilize the plasma before the reaction terminates abruptly. Controlling the plasma is one of the biggest obstacles to achieving viable nuclear fusion energy.

Foundation for Broad Applications of AI

The success of the experiments establishes a basis for utilizing AI to address various plasma instabilities and brings fusion energy closer to reality. Kolemen notes, “By learning from past experiments, rather than incorporating information from physics-based models, the AI could develop a final control policy that supported a stable, high-powered plasma regime in real-time, at a real reactor.”

The findings provide hope that AI and machine learning can help solve other complex challenges in plasma physics and accelerate progress in the field. With the new AI system, Princeton researchers have overcome a significant roadblock on the path to viable nuclear fusion energy.

Optimizing Plasma Confinement With Machine Learning

With its ability to anticipate and circumvent plasma instabilities, the AI system could enable fusion reactors to operate continuously without disruption. According to lead researcher Egemen Kolemen, “Being able to predict instabilities ahead of time can make it easier to run these reactions than current approaches, which are more passive.”

Continuous, optimized fusion reactions are necessary to produce energy at a commercial scale. By overcoming instabilities that have long hindered progress in fusion energy, this AI system provides a foundation for using machine learning to solve other challenges in plasma physics and bring fusion closer to viability.

A Step Towards Viable Fusion Energy

The findings represent progress toward developing nuclear fusion as a viable source of energy. According to Kolemen, “This is one of the big roadblocks – disruptions – and you want any reactor to be operating 24/7 for years without any problem.

And these types of disruption and instabilities would be very problematic, so developing solutions like this increases their confidence that we can run these machines without any issues. “Solving the problem of plasma instabilities could help enable nuclear fusion reactors to run continuously, a necessity for commercial power generation.

Early Results Show AI Models Outperform Humans

Princeton University researchers have demonstrated that artificial intelligence (AI) models can outperform humans in controlling nuclear fusion reactions. In a recent study published in Nature, the researchers detailed how they developed an AI system that can predict and mitigate plasma instabilities in a tokamak nuclear fusion reactor up to 300 milliseconds in advance.

The researchers carried out experiments at the DIII-D National Fusion Facility in San Diego, California. Their AI system monitored the plasma in the tokamak for signs of impending instabilities and made adjustments to stabilize the plasma before disruptions occurred.

The Path to a Scalable Fusion Reactor

The successful demonstration of an AI model’s ability to predict and mitigate plasma instabilities in fusion reactors represents significant progress toward achieving stable, long-duration fusion reactions. According to researchers from Princeton University and the Princeton Plasma Physics Laboratory, their AI controller was able to forecast potential plasma disruptions up to 300 milliseconds in advance.

The researchers’ findings provide a foundation for leveraging AI to address a wide range of plasma instabilities that have long impeded the development of fusion energy. According to Princeton physicist Egemen Kolemen, co-author of the study published in Nature, “This is one of the big roadblocks-disruptions-and you want any reactor to be operating 24/7 for years without any problem.