News Releases

Can plasma be sufficiently heated inside a tokamak using only microwaves? New research suggests it can! Eliminating the central ohmic heating coil normally used in tokamaks will free up much-needed space for a more compact, efficient spherical tokamak.

New research from PPPL and the University of Delaware offers an enhanced understanding of common defects in transition-metal dichalcogenides (TMDs) — a potential replacement for silicon in computer chips — and lays the foundation for etching smaller features.

PPPL physicists have developed a computer program incorporating machine learning that could help identify blobs of plasma in outer space known as plasmoids. In a novel twist, the program has been trained using simulated data.

Ravinder Bhatia, a leader and engineer with three decades of experience managing collaborative science initiatives, is the new head of ITER projects at PPPL. In this role, Bhatia oversees the design and fabrication of six diagnostic systems that PPPL is building for ITER.

The exhaust heat generated by a fusing plasma in a commercial-scale reactor may not be as damaging to the vessel’s innards as once thought, according to new research about escaping plasma particles made by researchers at the Princeton Plasma Physics Laboratory, Oak Ridge National Laboratory and the ITER Organization (ITER).

Shantenu Jha, former chair of the Data-Driven Discovery Division at Brookhaven National Laboratory, has been named the new head of computational sciences at the U.S. Department of Energy’s Princeton Plasma Physics Laboratory (PPPL). Jha is excited to be at the helm of the Lab’s computing efforts, fusing computer science expertise with  PPPL’s pioneering research into the fourth state of matter.

A new PPPL model for ballooning instabilities in apple-shaped fusion vessels considers the height and width of the plasma’s edge.

Scientists have made discoveries about light particles known as photons that could aid the quest for fusion energy.

Researchers at the Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) are using artificial intelligence to perfect the design of the vessels surrounding the super-hot plasma, optimize heating methods and maintain stable control of the reaction for increasingly long periods. A new paper published in Nature Communications demonstrates PPPL's expertise in this area. The paper explains how the researcher team used machine learning to avoid magnetic perturbations, or disruptions, which destabilize fusion plasma.