Density Functional Theory– tag –
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Symmetry-Guided AI Model SG-CDVAE Identifies Four Stable Novel Antiferromagnets for Spintronics Applications
AZoM International Overview A novel symmetry-guided AI model, SG-CDVAE, has identified four stable candidate antiferromagnets specifically for spintronics applications. This generative deep learning framework significantly accelerates th... -
NUS Designs Catalyst for Urea Fertilizer Production from CO2 and Waste Nitrates, Integrating LLMs, DFT, and Experimentation
NUS Faculty of Science Singapore Overview Researchers at the National University of Singapore (NUS) developed a computationally guided strategy, integrating Large Language Models (LLMs), Density Functional Theory (DFT), and experimental ... -
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... -
ResearchGate: NequIP GNN Predicts Amorphous Material Many-Body Interactions at 10,000x Lower Cost than DFT
ResearchGate Unknown Overview Recent research applied NequIP, an equivariant message passing graph neural network (GNN), to predict many-body interactions in model soft glasses of solvent-free polymer-grafted nanoparticles (PGNs). NequIP... -
ASM International Highlights Accelerated Computational Materials Design Integrating CALPHAD, DFT, MLIPs, and AI Agents
ASM International USA Overview An ASM International webinar showcased recent advancements in accelerating computational materials design by integrating CALPHAD, Density Functional Theory (DFT), Machine Learning Interatomic Potentials (ML... -
arXiv: BiMat-ML Advances Stacked 2D Material Property Prediction via Multimodal Learning and GNNs
arXiv Unknown Overview A new research paper on arXiv proposes "BiMat-ML," a multimodal learning approach for property prediction in stacked two-dimensional (2D) materials. This method utilizes graph neural networks (GNNs) to process mole... -
AI and Simulation Transform Materials Design in Europe, Supercharging Green and Digital Transitions
MaX ヨーロッパ Overview Europe is fundamentally reshaping its approach to materials design by integrating simulation and artificial intelligence, significantly bolstering its competitiveness in green and digital transitions. Generative A...
