Deep Learning– tag –
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Tokyo Institute of Science Achieves Sub-Millisecond AI for Semiconductor Inverse Problems
東京科学大学 Japan Overview Scientists at the Tokyo Institute of Science have developed a tandem neural network that solves complex semiconductor inverse problems in under one millisecond. This AI system infers critical material paramete... -
Chalmers University Leverages Physics-Informed AI to Drastically Accelerate Quantum Optical Component Development
SciTechDaily スウェーデン Overview Researchers at Chalmers University of Technology in Sweden have developed a novel "physics-informed AI" approach that directly embeds fundamental physical laws into neural networks, significantly boosti... -
QNM-Net: Swedish Breakthrough Fuses AI and Physics to Supercharge Photonic Inverse Design
Laser Photonics Rev. スウェーデン Overview Swedish researchers have introduced QNM-Net, a novel method that fuses machine learning with fundamental physics to drastically accelerate the inverse design of photonic components. This hybrid ... -
Symmetry-Guided AI Model SG-CDVAE Identifies Four Stable Novel Antiferromagnets for Spintronics Applications
AZoM International Overview A novel symmetry-guided AI model, SG-CDVAE, has identified four stable candidate antiferromagnets specifically for spintronics applications. This generative deep learning framework significantly accelerates th... -
U.S. DOE Pioneers AI-Driven Closed-Loop Systems to Slash Material Development Time from Decades to Months
Department of Energy USA Overview The U.S. Department of Energy (DOE) announced a transformative approach integrating AI into materials design workflows, aiming to reduce time-to-market for new materials from decades to months. This init... -
Formal Theory for Crystal Structure Prediction Revolutionizes Inverse Design and Material Property Prediction
arXiv USA Overview A groundbreaking formal theory for crystal structure prediction has been introduced, detailing the inverse design of crystal structures using Constrained Crystal Deep Convolutional Generative Adversarial Networks (CG-D... -
Google DeepMind’s GNoME Discovers 2.2 Million New Crystal Structures, Propelling Clean Energy Material Design into a New Era
DEV Community 多国籍 Overview Google DeepMind's GNoME AI has identified an unprecedented 2.2 million new stable crystal structures, including 380,000 deemed practical, surpassing all previously known inorganic materials. This monumental ... -
PhysicsX Raises $135M at ~$170M Total Funding for AI to Reduce Industrial Engineering Simulation from Days to Seconds
The AI World UK Overview London-based AI startup PhysicsX successfully raised $135 million in Series B funding, bringing its total funding to nearly $170 million, for its deep learning-powered AI technology that reduces industrial engine... -
IJCRT.org Paper Argues AI and Mathematical Modeling Fusion Revolutionizes Materials Engineering, Accelerating Discovery
IJCRT.org India Overview A paper published on IJCRT.org argues that the combination of mathematical modeling and AI is revolutionizing materials engineering by providing predictive insights and accelerating materials discovery. Machine l... -
U.S. DOE Pioneers Physics-Aware AI Framework to Accelerate Materials Design and Discovery
Department of Energy USA Overview The U.S. Department of Energy (DOE) has developed a physics-aware AI framework integrating foundation models, deep learning, generative AI, and agent AI to dramatically enhance materials design capabilit...
