Simulation– tag –
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Chinese Researchers Develop End-to-End AI-Guided Inverse Design Framework for Perovskite Photovoltaic Devices with Deep Generative Modeling
Frontiers in Artificial Intelligence China Overview Chinese researchers have developed an end-to-end framework integrating deep generative modeling and AI to enable AI-guided 'inverse design' of perovskite solar cell (PSC) devices. This ... -
Meta FAIR and Stanford Researchers Successfully Fine-Tune UMA Model for High-Precision Simulation of WS2 Oxygen Plasma Interactions
arXiv USA Overview Researchers from Meta FAIR and Stanford University successfully fine-tuned the UMA universal machine-learned interatomic potential (MLIP) model specifically for oxygen plasma interactions with WS2. This study addresses... -
Duke University Team Secures DOE Funding for AI Platform to Design DNA-Based Energy Materials
Duke University USA Overview A Duke University research team has received funding from the DOE's Genesis Project to develop an AI platform for designing DNA-based materials. This AI framework automatically designs DNA origami building bl... -
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... -
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... -
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... -
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 ... -
Active Learning for MACE-MP-0 Foundation MLFFs Achieves Full Data Accuracy with Significantly Fewer Labeled Training Examples
arXiv International Overview This study demonstrates an innovative active learning strategy for fine-tuning machine-learning force fields (MLFFs), specifically focusing on foundation models like MACE-MP-0, to achieve full-data accuracy w...
