2026– date –
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LLNL Pioneers New Electrolyte Design for Sodium and Lithium Batteries, Boosting Performance and Thermal Stability with AI and Molecular Simulations
Commonwealth Union USA Overview Scientists at Lawrence Livermore National Laboratory (LLNL) have integrated molecular dynamics simulations with physics-informed machine learning to yield groundbreaking insights into electrolyte design fo... -
CuspAI Secures $450M Series B, Reaching $2.6B Valuation and Launching AI Materials Foundry with Industry Titans
Sifted UK Overview Cambridge-based AI materials discovery startup CuspAI has raised $450 million in Series B funding, pushing its valuation to $2.6 billion. Concurrently, the company launched the "AI Materials Foundry," a global consorti... -
Chinese Researchers Review AI-Driven Electrolyte Chemistry: Mechanisms, Progress, and Strategic Perspectives for Lithium-Ion Battery Design Revolution
Energy & Environmental Science China Overview This review paper details the transformative role of AI in designing next-generation electrolytes for lithium-ion batteries (LIBs). AI integrates experimental data, quantum chemical descripto... -
MIT Researchers Uncover Critical Role of Coverage-Dependent Lateral Interactions in High-Entropy Alloy Electrocatalytic Activity for Oxygen Reduction Reaction via MLIPs
PubMed USA Overview MIT researchers developed a framework utilizing Machine Learning Interatomic Potentials (MLIPs) to model the oxygen reduction reaction (ORR) within the compositional space of Ag-Ir-Ru-Pd-Pt-Cu-Rh-Re high-entropy alloy... -
UNCC Research Group Develops ‘PyXtal_FF’ for ML Interatomic Potential Generation, Dramatically Reducing Computational Cost of Atomic Simulations
University of North Carolina at Charlotte USA Overview Researchers at the University of North Carolina at Charlotte (UNCC) have developed 'PyXtal_FF,' a package for generating Machine Learning Interatomic Potentials (MLIAP). MLIAPs enabl... -
Q-CTRL Unveils Fire Opal Quantum-Dynamics Simulator, Solving Complex Materials Science Problems 3,000x Faster than Classical Computers
Q-CTRL Australia Overview Q-CTRL has launched 'Fire Opal,' quantum computer performance management software that significantly enhances its ability to simulate complex quantum mechanical interactions in materials science. A demonstration... -
Argonne National Lab and University of Chicago Propose ‘ORCHESTRA’ Framework for Perovskite Oxide Inverse Design with LLM Agents and Chemical DSL
arXiv USA Overview Researchers from Argonne National Laboratory and the University of Chicago have proposed 'ORCHESTRA,' a novel framework enabling inverse design of perovskite oxides using symbolic predicate-guided language agents. This... -
World Fund Analyzes European AI Materials Discovery Ecosystem: DeepMind, Meta AI Models Accelerate Novel Material Development
World Fund Europe Overview World Fund has released an analysis of AI-driven materials discovery, highlighting opportunities in Europe, noting significant advancements since AlphaFold. Emerging AI models like M3GNet, DeepMind's GNoME, Mic... -
Matmerize Launches AI-Driven PolymRize Platform to Accelerate Polymer Design for Gas Separation Membranes and More
Matmerize (Halo) USA Overview Matmerize has introduced 'PolymRize,' a cloud-based AI and machine learning polymer informatics platform. This platform instantly predicts and designs polymers with tailored gas permeability and selectivity,... -
Johns Hopkins and West Virginia Universities Develop ‘AtomBench’ to Evaluate AI’s Inverse Material Design Performance
Johns Hopkins University USA Overview Researchers at Johns Hopkins and West Virginia Universities have developed 'AtomBench,' a benchmark to compare the performance of AI models in the growing field of 'inverse material design.' This app...
