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Category: nuclear energy – Page 46

New insights on the role of nucleon exchange in nuclear fusion

A recent study has explored the influence on low-energy fusion processes of isospin composition. This is a key nuclear property that differentiates protons from neutrons. The researchers used and theoretical modeling to investigate the fusion of different nuclei with varying isospin configurations. The results show that the isospin composition of the nuclei in a fusion reaction plays a crucial role in understanding the reaction. The paper is published in the journal Physical Review C.

In this study, researchers at Fisk University and Vanderbilt University used high-performance computational and theoretical modeling techniques to conduct a detailed many-body method study of how the dynamics of isospin influence nuclear fusion at low energies across a series of isotopes. The study also examined how the shape of the nuclei involved affect these dynamics. In systems where the nuclei are not symmetrical, the dynamics of isospin become particularly important, often leading to a lowered fusion barrier, especially in systems rich in neutrons. This phenomenon can be explored using facilities that specialize in the generation of beams composed of exotic, unstable nuclei.

The findings provide critical knowledge regarding the fundamental nuclear processes governing these reactions, which have broad implications for fields such as , astrophysics, and, perhaps someday, fusion-based energy.

Tony Seba’s Prediction: Nuclear Obsolete by 2030 — Wind, Solar, and Battery Storage the Future

Small modular nuclear reactors are too expensive, too slow, and too risky, and the focus should be on wind, solar, and battery storage for energy needs Questions to inspire discussion What did Tony Seba predict about nuclear power in 2014? —Tony Seba predicted in 2014 that nuclear power would be obsolete by 2030, and recent research has shown that his predictions about the cost blowouts and inefficiency of small modular nuclear reactors were accurate.

Photon Polarization: The Next Breakthrough in Fusion Technology?

New studies show photon polarization is constant in varying environments, potentially improving plasma heating methods for fusion energy advancement.

Light, both literally and figuratively, pervades our world. It eliminates darkness, conveys telecommunications signals across continents, and reveals the unseen, from distant galaxies to microscopic bacteria. Light can also help heat the plasma within ring-shaped devices known as tokamaks as scientists work to leverage the fusion process to produce green electricity.

Recently, researchers from Princeton Plasma Physics Laboratory have discovered that one of the fundamental properties of photons—polarization—is topological, meaning it remains constant even as the photon transitions through various materials and environments. These findings, published in Physical Review D, could lead to more effective plasma heating techniques and advancements in fusion research.

AI-Powered Fusion: The Key to Limitless Clean Energy

Researchers at the Princeton Plasma Physics Laboratory are harnessing artificial intelligence and machine learning to enhance fusion energy production, tackling the challenge of controlling plasma reactions. Their innovations include optimizing the design and operation of containment vessels and using AI to predict and manage instabilities, significantly improving the safety and efficiency of fusion reactions. This technology has been successfully applied in tokamak reactors, advancing the field towards viable commercial fusion energy. Credit: SciTechDaily.com.

The intricate dance of atoms fusing and releasing energy has fascinated scientists for decades. Now, human ingenuity and artificial intelligence are coming together at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) to solve one of humankind’s most pressing issues: generating clean, reliable energy from fusing plasma.

Unlike traditional computer code, machine learning — a type of artificially intelligent software — isn’t simply a list of instructions. Machine learning is software that can analyze data, infer relationships between features, learn from this new knowledge, and adapt. PPPL researchers believe this ability to learn and adapt could improve their control over fusion reactions in various ways. This includes perfecting the design of vessels surrounding the super-hot plasma, optimizing heating methods, and maintaining stable control of the reaction for increasingly long periods.

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