Materials Informatics– category –
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India and Japan Announce $69 Billion AI and Semiconductor Investment, Strengthening International Partnership for Supply Chain Resilience
Trax Technologies International (India/Japan) Overview India and Japan are reportedly strengthening their technology partnership, targeting a massive $69 billion investment in AI and semiconductors. This strategic alliance aims for both ... -
LG AI Research Unveils LLM ‘EXAONE Discovery,’ Showcases Real-World Application in New Hair Growth Ingredient and Immersion Coolant Discovery at ICML 2026
LG AI Research (via Korea JoongAng Daily) South Korea Overview LG AI Research showcased 'EXAONE Discovery,' an industrial AI application powered by its EXAONE LLM, at ICML 2026, highlighting real-world applications. EXAONE Discovery is a... -
Japan’s Kao and Ajinomoto Boost Semiconductor Material Production Amid Surging AI Chip Demand, Strengthening ABF and High-Purity Cleaner Supply
Lanceum (Nikkei Asia report) Japan Overview Japanese consumer brands Kao and Ajinomoto are reportedly ramping up semiconductor material production to meet the surging demand for AI chips. Ajinomoto is increasing its production capacity f... -
Japan Accelerates Semiconductor Industry Reconstruction for AI Era, Driven by Micron Hiroshima Investment and Major Material Manufacturer Expansion
MK Japan Overview Japan is reportedly accelerating the reconstruction of its semiconductor industry, targeting the AI era. Leveraging its world-class competitiveness in semiconductor materials, components, and equipment, Japan aims to re... -
University at Buffalo Develops Millisecond-Scale Nanoparticle Catalyst Synthesis Method, Targets Automated AI-Integrated Development
University at Buffalo (UB) USA Overview Researchers at the University at Buffalo have unveiled a novel method for rapidly creating advanced catalyst materials by uniformly combining multiple metals into nanoparticles in milliseconds. Thi... -
Argonne National Laboratory Unveils AI-Driven ‘ChemGraph’ Framework, Accelerating Materials Research with LLMs
Argonne National Laboratory USA Overview Argonne National Laboratory has announced 'ChemGraph,' an open-source, AI-driven framework that automates the setup, execution, and analysis of computational chemistry and materials science simula... -
Tohoku University’s AI Framework ‘ChatHEA’ Unlocks Superior Fuel Cell Catalyst Outperforming Platinum
Tohoku University AIMR Japan Overview Researchers at Tohoku University's AIMR and an international team have developed 'ChatHEA,' an innovative AI framework that integrates large language models (LLMs) with experimental methodologies to ... -
Quandela Announces Spin-Optical Quantum Computer Can Simulate Fermi–Hubbard System in ~2 Hours, Accelerating Quantum Materials Science
Quandela France Overview French quantum computing company Quandela and Walrus Computing have published detailed resource estimates demonstrating that a fault-tolerant spin-optical quantum computer can simulate commercially relevant Fermi... -
Machine Learning Designs Biomedical High-Entropy Alloys for Additive Manufacturing, Selecting Optimal Zr Alloys from 15 Million Compositions
Taylor & Francis Group - Figshare International Overview A machine learning framework has been successfully introduced and validated for designing biomedical high-entropy alloys (BioHEAs) for additive manufacturing (AM), identifying opti... -
Human-LLM Collaboration Discovers Novel Perovskite-Type Material Ba3PtO5, Accelerating Materials Synthesis and Discovery
arXiv International Overview Addressing the challenge where LLMs accelerate material prediction but experimental discovery lags, this study demonstrates the power of human-LLM collaboration. Through this collaborative process, researcher...
