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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.

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.

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.

The transcript features an interview with renowned science fiction author Isaac Asimov, discussing his predictions and visions for the future of space exploration, computers, robotics, and humanity’s role in shaping that future. It touches on concepts like permanent space settlements, harnessing solar power, the increasing importance of computers and AI, the impacts of robotics on jobs, and taking an optimistic yet cautionary view of technological progress. It also covers some earlier inaccurate and exaggerated predictions about robots replacing humans, as well as actual technological developments in 1982 like artificial hearts and fusion reactors. The overall theme is Asimov’s hopeful but measured outlook on future scientific and technological advancements.

The interaction of solids with high-intensity ultra-short laser pulses has enabled major technological breakthroughs over the past half-century. On the one hand, laser ablation of solids offers micromachining and miniaturization of elements in medical or telecommunication devices. On the other hand, accelerated ion beams from solids using intense lasers may pave the way for new opportunities for cancer treatment with laser-based proton therapy, fusion energy research, and analysis of cultural heritage.