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The energy released when two atomic nuclei fuse together. This process powers the sun and stars.  Read more

Updated computer code improves prediction of energetic particle motion in plasma experiments

A computer code used by physicists around the world to analyze and predict tokamak experiments can now approximate the behavior of highly energetic atomic nuclei, or ions, in fusion plasmas more accurately than ever. The new capability, developed by physicist Mario Podestà at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL), outfits the code known as TRANSP with a subprogram that simulates the motion that leads to the loss of energetic ions caused by instabilities in the plasma that fuels fusion reactions.

Updated computer code improves prediction of energetic particle motion in plasma experiments

A computer code used by physicists around the world to analyze and predict tokamak experiments can now approximate the behavior of highly energetic atomic nuclei, or ions, in fusion plasmas more accurately than ever. The new capability, developed by physicist Mario Podestà at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL), outfits the code known as TRANSP with a subprogram that simulates the motion that leads to the loss of energetic ions caused by instabilities in the plasma that fuels fusion reactions.

PPPL researchers perform first basic-physics simulation of the impact of recycled atoms on plasma turbulence

Turbulence, the violently unruly disturbance of plasma, can prevent plasma from growing hot enough to fuel fusion reactions. Long a puzzling concern of researchers has been the impact on turbulence of atoms recycled from the walls of tokamaks that confine the plasma.

PPPL researchers perform first basic-physics simulation of the impact of recycled atoms on plasma turbulence

Turbulence, the violently unruly disturbance of plasma, can prevent plasma from growing hot enough to fuel fusion reactions. Long a puzzling concern of researchers has been the impact on turbulence of atoms recycled from the walls of tokamaks that confine the plasma.

Machine learning technique offers insight into plasma behavior

Machine learning, which lets researchers determine if two processes are causally linked without revealing how, could help stabilize the plasma within doughnut-shaped fusion devices known as tokamaks. Such learning can facilitate the avoidance of disruptions — off-normal events in tokamak plasmas that can lead to very fast loss of the stored thermal and magnetic energies and threaten the integrity of the machine.

Predhiman Kaw, founder of India’s fusion program and former PPPL physicist, is dead at age 69

Predhiman Kaw, an internationally-known plasma physicist who is considered the father of India’s nuclear fusion program, was remembered fondly by his colleagues at the U.S. Department of Energy’s Princeton Plasma Physics Laboratory (PPPL) last week after they learned of Kaw’s June 19 death.  He was 69. 

PPL researchers demonstrate first hot plasma edge in a fusion facility

Two major issues confronting magnetic-confinement fusion energy are enabling the walls of devices that house fusion reactions to survive bombardment by energetic particles, and improving confinement of the plasma required for the reactions. At the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL), researchers have found that coating tokamak walls with lithium— a light, silvery metal— can lead to progress on both fronts.

U.S.-China collaboration makes excellent start in optimizing lithium to control fusion plasmas

China has the Experimental Advanced Superconducting Tokamak (EAST) facility, a steady-state capable superconducting tokamak with many auxiliary systems being developed to qualify reactor-relevant technology.  As such, EAST is well-suited to address gaps in the physics basis for steady-state operation, plasma control, and plasma-material interfaces. Continued collaborations with EAST (ongoing since the start of the EAST project) enables U.S.

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