Materials Informatics– category –
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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... -
Notre Dame University Develops AI Polymer Discovery Platform to Overcome Data Scarcity, Accelerating Novel Material Exploration
Notre Dame Research USA Overview Notre Dame University's AI & Materials Initiative developed a framework leveraging multiple information sources to overcome data scarcity in polymer informatics. They created ADEPT, an automated molec... -
ML Interatomic Potentials Uncover Order-Disorder Transition and Non-Monotonic Stiffness in (MoCrTi)$_{100-x}$Al$_x$ Refractory High-Entropy Alloys
arXiv International Overview This research leverages universal machine learning interatomic potentials combined with hybrid Monte Carlo and molecular dynamics simulations to investigate the chemical ordering and mechanical properties of ... -
AI Revolutionizes Biomaterial Design for Tissue Engineering, Overcoming Empirical Limitations in Property Prediction, Inverse Design, and Manufacturing Optimization
IntechOpen Croatia Overview This comprehensive review highlights AI's transformative applications in biomaterial design for tissue engineering, encompassing machine learning, deep learning, and generative models. AI provides data-driven ...
