2026– date –
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Frontiers Launches Research Topic on “High-Throughput AI-Driven Materials Discovery for High-Rate Batteries,” Accelerating Next-Gen Energy Storage
Frontiers Switzerland Overview Frontiers has initiated a new research topic, "High-Throughput AI-Driven Materials Discovery and Design for High-Rate Batteries," aiming to revolutionize battery material development through machine learnin... -
Institute of Science Tokyo Dramatically Enhances Material Prediction Interpretability with ALIGNN and Clustering AI, Precisely Forecasting Optical Absorption Spectra
Lab Manager Japan Overview Researchers at the Institute of Science Tokyo have developed a novel method combining a graph neural network (ALIGNN) with hierarchical clustering to significantly improve the interpretability of AI-driven mate... -
CVC Analyzes 8 Leading AI Material Development Companies: Investment Strategies and Public Market Proxies Explored
note Japan Overview From a Corporate Venture Capital (CVC) perspective, eight key AI material development companies—Cusp AI, DeepMind, Microsoft, Orbital, Matlantis, Citrine Informatics, Aionics, and Kebotix—have been analyzed. This arti... -
Digital Twin Technology Transforms Urban Development and Manufacturing, Demonstrated by Performance Monitoring and Prediction at NASA MAF
Axiom USA Overview Digital twin technology is revolutionizing diverse sectors from urban development to manufacturing, with dynamic digital replicas of physical assets linked to real-time data for performance monitoring, behavior predict... -
Machine Learning Predicts Thermal Properties of PHB/PHBV-Based Materials with Improved Accuracy Using Integrated Polymer Database
MDPI Switzerland Overview This study reports a novel machine learning (ML) approach for predicting thermal properties (glass transition temperature, melting point, crystallization temperature) of PHB and PHBV-based materials. By building... -
ASML, TSMC, and Imec Announce Breakthrough 300mm Integration for 2D Material Transistors, Advancing Next-Gen Logic
The cleanroom Portal ヨーロッパ Overview Semiconductor industry leaders ASML, TSMC, and imec have unveiled a 300mm wafer integration process for 2D material transistors (MoS2 nFET and WSe2 pFET) featuring a 50nm contact poly pitch (CPP).... -
South Korea’s Pohang City to Establish AI-Driven ‘K-Graphene Foundry’ with Government Support, Accelerating 2D Material R&D
The Investor South Korea Overview South Korea's Pohang City has announced plans to establish the 'K-Graphene Foundry,' an AI-driven manufacturing and validation platform for graphene and other 2D materials, with government backing. This ... -
South Korea’s Hanwha Essential Advances Localization of AI Chip Substrate Build-up Film, Challenging Market Monopoly
The Elec Inc. South Korea Overview South Korea's Hanwha Essential has announced accelerated efforts towards localizing build-up film (BuF), a critical material for AI semiconductor substrates, now entering customer sample evaluation and ... -
IBM Revolutionizes AI Chip Design with Sub-1 nm NanoStack, Achieving 50% Performance Boost or 70% Power Reduction
Data Center Knowledge USA Overview IBM has announced "NanoStack," an innovative semiconductor technology extending chip scaling to sub-1 nm to meet the growing demands of AI workloads. This 3D architecture, which vertically stacks transi... -
Applied Materials Unveils New Manufacturing Systems to Accelerate DRAM and Advanced Packaging for AI Chips
GLOBE NEWSWIRE USA Overview Applied Materials has announced a suite of innovative chip manufacturing systems to accelerate the production of advanced 3D chip architectures (DRAM and advanced packaging) critical for next-generation AI wor...
