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DUNE Integrates Artificial Intelligence into Neutrino Experiment to Enhance Particle Detection and Data Processing Capabilities

The team at the U.S. Fermi National Accelerator Laboratory is advancing the Deep Underground Neutrino Experiment (DUNE) by integrating artificial intelligence and machine learning tools into experiment design, detector operations, and data analysis workflows, aiming to improve neutrino interaction identification, event classification, and detector management capabilities. Located at the Long-Baseline Neutrino Facility, DUNE has begun installing structural components for its large neutrino detector modules. The experiment consists of a near detector and a far detector: the near detector is situated at Fermilab, while the far detector is located approximately one mile underground at the Sanford Underground Research Facility in South Dakota. Both detectors will employ liquid argon time projection chamber technology to record neutrino...

2026-08-07

SHINE Selected for Two U.S. Department of Energy AI Nuclear Fuel Recycling Projects

SHINE Technologies, a U.S. fusion energy company, has recently been selected for projects under the U.S. Department of Energy's Genesis Mission, participating in two artificial intelligence applications for the nuclear energy sector. Among these, SHINE will lead a nuclear fuel cycle facility optimization project and join the Prometheus project, a collaborative effort between national laboratories and industry. The project led by SHINE, named AI-Guided Fuel Cycle Facility Optimization, is a Phase 1 project with Argonne National Laboratory as the technical partner. The project plans to develop an AI-assisted workflow to help engineers...

2026-08-07

U.S. Laboratories Plan "Materials Discovery Cloud" to Use AI to Predict Impact of Defects in Microelectronic Devices

Researchers at the U.S. Department of Energy's Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, and Northwestern University are planning to develop a Materials Discovery Cloud platform that leverages a physics-based artificial intelligence framework to predict how tiny defects affect the performance and lifespan of microelectronic devices. Visualization of the Materials Discovery Cloud, a physics-based AI framework that integrates experimental data, simulations, and high-performance computing to predict how tiny defects affect the performance and lifespan of microelectronic devices. (Image provided by ChatGPT.) Microelectronic devices are widely used in smartphones, laptops, secure communications, and artificial intelligence hardware. As device dimensions continue to shrink and operating speeds increase, tiny defects within materials and at interfaces have a more pronounced impact on device stability. These defects can cause overheating, leakage current, switching instability, and other issues, or in certain conditions, improve electrical or thermal performance. Identifying critical defects and understanding their evolution under real-world operating conditions has become a key challenge in the design of next-generation microelectronic materials.

2026-08-06

UC Santa Barbara and Lawrence Livermore National Laboratory Collaborate to Accelerate Fusion Plasma Simulations with AI

The University of California, Santa Barbara (UCSB) and Lawrence Livermore National Laboratory (LLNL) are launching a new collaboration to bring artificial intelligence into extreme plasma simulations, accelerating critical computations in nuclear fusion and high-energy-density physics research. Neel Sankaran (left), a doctoral student of UCSB Professor Haewon Jeong, poses with LLNL scientist Min Sang Cho (right). The project is led by the Department of Electrical and Computer Engineering at UC Santa Barbara...

2026-08-05

Valar Atomics Completes $1 Billion Equity Financing, Sequoia Capital Partner Joins Board

Nuclear energy startup Valar Atomics confirmed on August 3 that it has completed a $1 billion equity financing round led by Sequoia Capital. Company founder and CEO Isaiah Taylor stated that Sequoia Capital partner Shaun Maguire has joined the company's board of directors. In addition to the equity financing, Valar Atomics also secured a $200 million credit facility from Erebor and other banks. Valar Atomics did not disclose its post-financing valuation. Reports indicate the company is valued at approximately $6 billion. Valar Atomics primarily...

2026-08-04

Public Meeting Held on Restart Plan for Three Mile Island Unit 1

As electricity demand from AI-related data centers rises, multiple locations across the United States are reassessing the value of nuclear reactors originally slated for decommissioning. Recently, the restart plan for Unit 1 of the Three Mile Island Nuclear Power Plant in eastern Pennsylvania has entered the public engagement phase. The Three Mile Island plant has long been under scrutiny due to the 1979 accident at Unit 2, which involved a nuclear fuel meltdown and the release of radioactive materials. The proposed restart involves the adjacent Unit 1, which has been in the decommissioning process since 2019. Upon restart, it will operate under the name "Crane Clean Energy Center." On July 28, the U.S. Nuclear Regulatory Commission...

2026-07-30