A Collaborative National Center for Fusion & Plasma Research

Artificial Intelligence

Subscribe to RSS - Artificial Intelligence

In short, there is a global demand for clean, cheap, reliable energy – and artificial intelligence (AI) is increasingly being used to help meet this need. 

Extreme-scale computing and AI help forecast a promising outlook for divertor heat-loads in next-step fusion reactors

Efforts to duplicate on Earth the fusion reactions that power the sun and stars for unlimited energy must contend with extreme heat-load density that can damage the doughnut-shaped fusion facilities called tokamaks, the most widely used laboratory facilities that house fusion reactions, and shut them down.

Extreme-scale computing and AI help forecast a promising outlook for divertor heat-loads in next-step fusion reactors

Efforts to duplicate on Earth the fusion reactions that power the sun and stars for unlimited energy must contend with extreme heat-load density that can damage the doughnut-shaped fusion facilities called tokamaks, the most widely used laboratory facilities that house fusion reactions, and shut them down.

New machine learning theory that can be applied to fusion energy raises questions about the very nature of science

A novel computer algorithm, or set of rules, that accurately predicts the orbits of planets in the solar system could be adapted to better predict and control the behavior of the plasma that fuels fusion facilities designed to harvest on Earth the fusion energy that powers the sun and stars.

New twist in artificial intelligence could enhance the prediction of fusion disruptions

Researchers at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) have used Artificial Intelligence (AI) to create an innovative technique to improve the prediction of disruptions in fusion energy devices — a grand challenge in the effort to capture on Earth the fusion reactions that power the sun and stars.

Former PPPL intern honored for outstanding machine learning poster

The American Physical Society (APS) has recognized a summer intern at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) for producing an outstanding research poster at the world-wide APS Division of Plasma Physics (DPP) gathering last October. The student, Marco Miller, a senior at Columbia University majoring in applied physics, used machine learning to accelerate a leading PPPL computer code known as XGC as a participant in the DOE’s Summer Undergraduate Laboratory Internship (SULI) program in 2019.

Artificial intelligence — an exciting new way to speed development of fusion energy

How can scientists foresee and avoid massive disruptions in plasma, a key hurdle to bringing the fusion reactions that power the sun and stars to Earth to generate electricity? “You can’t have a prototype reactor if it’s disrupting,” says William Tang, a physicist at PPPL and a Princeton University professor who leads a project to forecast disruptions through artificial intelligence (AI) — the branch of computer science that is transforming scientific inquiry and industry.  

Machine learning speeds modeling of experiments aimed at capturing fusion energy on Earth

Machine learning (ML), a form of artificial intelligence that recognizes faces, understands language and navigates self-driving cars, can help bring to Earth the clean fusion energy that lights the sun and stars. Researchers at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) are using ML to create a model for rapid control of plasma — the state of matter composed of free electrons and atomic nuclei, or ions — that fuels fusion reactions.

Pages

U.S. Department of Energy
Princeton Plasma Physics Laboratory is a U.S. Department of Energy national laboratory managed by Princeton University.

Website suggestions and feedback

Pinterest · Instagram · LinkedIn · Tumblr.

PPPL is ISO-14001 certified

Princeton University Institutional Compliance Program

Privacy Policy · Sign In (for staff)

© 2021 Princeton Plasma Physics Laboratory. All rights reserved.

Princeton University
Princeton Plasma Physics Laboratory
P.O. Box 451
Princeton, NJ 08543-0451
GPS: 100 Stellarator Road
Princeton, NJ, 08540
(609) 243-2000