The energy released when two atomic nuclei fuse together. This process powers the sun and stars. Read more
Stewart Prager was the sixth director of PPPL. He joined the Laboratory in 2009 after a long career at the University of Wisconsin in Madison. At Wisconsin, he led research on the “Madison Symmetric Torus” (MST) experiment and headed a center that studied plasmas in both the laboratory and the cosmos. He also co-discovered the “bootstrap current” there—a key finding that has influenced the design of today’s tokamaks. He earned his PhD in plasma physics from Columbia University.
The U.S. Department of Energy (DOE) has launched an ambitious new program to encourage private-pubic partnerships to speed the development on Earth of the fusion energy that powers the sun and most stars. The DOE’s Princeton Plasma Physics Laboratory (PPPL) and Oak Ridge National Laboratory, home of the US ITER Project Office, will manage the program, with PPPL physicist Ahmed Diallo serving as deputy director and Oak Ridge fusion engineer Dennis Youchison serving as director.
The U.S. Department of Energy (DOE) has launched an ambitious new program to encourage private-pubic partnerships to speed the development on Earth of the fusion energy that powers the sun and most stars. The DOE’s Princeton Plasma Physics Laboratory (PPPL) and Oak Ridge National Laboratory, home of the US ITER Project Office, will manage the program, with PPPL physicist Ahmed Diallo serving as deputy director and Oak Ridge fusion engineer Dennis Youchison serving as director.
A key obstacle to controlling on Earth the fusion that powers the sun and stars is leakage of energy and particles from plasma, the hot, charged state of matter composed of free electrons and atomic nuclei that fuels fusion reactions. At the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL), physicists have been focusing on validating computer simulations that forecast energy losses caused by turbulent transport during fusion experiments.
A key obstacle to controlling on Earth the fusion that powers the sun and stars is leakage of energy and particles from plasma, the hot, charged state of matter composed of free electrons and atomic nuclei that fuels fusion reactions. At the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL), physicists have been focusing on validating computer simulations that forecast energy losses caused by turbulent transport during fusion experiments.
Institutions ranging from NASA to the Korean Physical Society have recently bestowed national and international honors on four scientists at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL). The awards recognize a veteran and three early career physicists for their path-setting achievements in fusion and plasma science research. The honorees and their notable contributions:
Rajesh Maingi named Fellow of the American Nuclear Society
Institutions ranging from NASA to the Korean Physical Society have recently bestowed national and international honors on four scientists at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL). The awards recognize a veteran and three early career physicists for their path-setting achievements in fusion and plasma science research. The honorees and their notable contributions:
Rajesh Maingi named Fellow of the American Nuclear Society
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 (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.
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.
Princeton Plasma Physics Laboratory is a U.S. Department of Energy national laboratory managed by Princeton University.
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