June 2026– date –
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Argonne National Laboratory to Present AI and HPC Integration Research for Accelerated Materials and Molecular Discovery at ISC High Performance 2026
Argonne National Laboratory USA Overview Argonne National Laboratory announced research at ISC High Performance 2026 on integrating Artificial Intelligence (AI), High-Performance Computing (HPC), and quantum computing to accelerate mater... -
InvDesMobility Framework Accelerates Materials Discovery with Reliability-Gated First-Principles Feedback Based on Carrier Mobility
arXiv International Overview InvDesMobility is a closed-loop inverse materials design framework utilizing reliability-gated first-principles feedback for carrier mobility. This framework integrates automated DFT, generative structural pr... -
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 ... -
LLM-Based Autonomous Agent PhyNex Achieves Automated Discovery in Computational Physics, Including Semiconductor Dielectric Spectra Prediction
arXiv International Overview An autonomous agent, PhyNex, has been developed to accelerate scientific discovery in computational physics. By combining LLM-guided search with domain-specific computational tools, PhyNex systematically expl... -
U.S. Educational Organizations Release 10 Best Practices for Generative AI Faculty Development
Every Learner Everywhere and Online Learning Consortium USA Overview Every Learner Everywhere and the Online Learning Consortium have jointly released 10 best practices for faculty development to effectively integrate generative AI into ... -
ChemCopilot’s Generative AI Instantly Generates Novel Molecules from Natural Language Prompts, Automating Molecular Design
ChemCopilot International Overview ChemCopilot unveiled its Generative AI for Molecular Design, enabling scientists to design novel molecules on demand using natural language prompts and instantly generate SMILES strings. This technology... -
Data-Driven Inverse Design Framework Achieves Robot Hand with Human-Comparable Dynamic Performance
MDPI International Overview A data-driven inverse design framework has enabled the development of a dexterous robot hand optimized for high-frequency dynamic performance, achieving human-comparable capabilities. Verified through complex ... -
Leo AI Demonstrates AI Revolutionizing Mechanical Design Material Selection for Efficient Identification of Optimal High-Performance Materials
Leo AI International Overview AI technology is fundamentally transforming the material selection process in mechanical design, dramatically streamlining the identification and optimization of high-performance materials. AI utilizes multi... -
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... -
IBM Leverages LLMs and Evolutionary Framework to Discover 465 Novel Quantum Error Correction Code Candidates
IBM Research USA Overview IBM researchers have developed an evolutionary framework powered by Large Language Models (LLMs) that identified 465 novel quantum error correction code candidates. This groundbreaking approach demonstrates LLMs...
