June 2026– date –
-
Queensland University of Technology Researchers Discover Method to Control Quantum Effect, Paving Way for Battery-Free Devices
ScienceDaily (Queensland University of Technology) Australia Overview A research team led by Queensland University of Technology (QUT) discovered a method to control a quantum effect in advanced materials, potentially enabling electronic... -
SCM Releases ‘AMS2026’ Software, Accelerating Materials Chemistry Simulations with ML Potentials and GPU Optimization
SCM (Scientific Computing & Modelling) Netherlands Overview SCM announced the release of 'AMS2026' software, featuring major advancements in machine learning potentials (eSEN, MACE, UMA) that expand chemical coverage for biomolecules, ca... -
International Team, Including Tohoku University, Accelerates Methane Pyrolysis Catalyst Discovery with AI-Driven Platform ‘DigMethpy’
Tohoku University Japan Overview An international research team, including Tohoku University, developed 'DigMethpy,' an AI-driven digital catalyst platform to accelerate methane pyrolysis catalyst discovery. The platform integrates scien... -
London Researchers Dramatically Reduce Qubit Count for Crystalline Material Simulations on Quantum Computers
Quantum Zeitgeist UK Overview Researchers at the London Centre for Nanotechnology (LCN) have developed a 'periodic symmetry-adapted encoding' framework, significantly reducing the number of qubits required for electronic structure simula... -
China Pursues Global Leadership in Advanced Materials via AI for Science Strategy: DeepChem Autonomous Labs, Xiaomi Lightweight Alloys Highlight Progress
UC Institute on Global Conflict and Cooperation China Overview China is aggressively pushing its 'AI for Science (AI4S)' strategy, integrating AI into advanced materials science to achieve global competitive advantage. Domestic firms are... -
Beyond Screening: Generative AI Transforms Materials Discovery with Practical Inverse Design, PatSnap Report Highlights IBM and Fujitsu Patents
PatSnap 多国籍 Overview A new PatSnap report reveals a fundamental shift in materials discovery, propelled by AI-driven generative chemistry from passive screening to active inverse design workflows. This transformation integrates deep g... -
Apoha Raises $36 Million to Scale AI Platform for Designing Proteins, Food Ingredients, and Novel Materials
PPTI News USA Overview AI startup Apoha successfully secured $36 million in funding to expand its AI platform for designing proteins, food ingredients, and new materials. Its 'Liquid State Intelligence' generates data from materials' beh... -
MIT Researchers Introduce Valence Constraints in Generative AI for Inverse Design of Chemically Stable Crystal Structures
YouTube USA Overview Researchers at MIT, led by Mouyang Cheng, have presented a novel approach to integrate stringent constraints into generative AI for inverse materials design. By employing structural motif constraints with diffusion m... -
Topsoe Declares AI the ‘Fifth Paradigm’ for Next-Gen Materials: Accelerating Catalysis, Electrolysis, and Battery Innovation
Topsoe デンマーク Overview Danish chemical catalyst leader Topsoe has officially designated Artificial Intelligence as the 'fifth paradigm' in materials science. This strategic move aims to dramatically accelerate the discovery and desig... -
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...
