Argonne National Laboratory– tag –
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Argonne National Laboratory Successfully Synthesizes First Borophene, a Metallic Single-Atom-Thick Boron, Opening New Era for 2D Materials
Argonne National Laboratory USA Overview Researchers at Argonne National Laboratory have successfully synthesized borophene, a metallic single-atom-thick boron, for the first time. This groundbreaking discovery is hailed as a next-genera... -
Argonne National Laboratory Accelerates AI-Driven Materials Discovery: 18 Promising Battery Candidates Identified from 500,000 Materials in 80 Hours
Facebook (Argonne National Laboratory) USA Overview Argonne National Laboratory dramatically accelerated materials discovery using an AI-driven method, identifying 18 promising battery development candidates from 500,000 stable materials... -
Argonne National Lab’s AI Discovers N2116 Electrolyte in 80 Hours, Enabling Faster Charging, Higher Energy Density Batteries
Argonne National Laboratory USA Overview Argonne National Laboratory researchers have used an AI-driven method to drastically accelerate materials discovery for battery development. The AI identified 18 stable material candidates from 50... -
AI and Autonomous Labs Accelerate New Materials Discovery: DeepMind’s GNoME Reduces Months to Days in Development
Facebook (Argonne National Laboratory / ScienceDaily context) USA Overview Leveraging AI, particularly DeepMind's GNoME model and 'self-driving labs,' the new materials discovery process is being dramatically shortened from months to mer... -
Argonne National Lab Accelerates Materials Discovery by Real-Time X-ray Data Analysis with AI and Robotics
Argonne National Laboratory USA Overview Argonne National Laboratory is dramatically accelerating materials science discovery through its DONUT system, enabling real-time X-ray data analysis. This initiative is central to an autonomous d... -
Argonne Lab’s ‘DONUT’ AI Accelerates X-ray Data Analysis Tenfold for Real-Time Materials Discovery
Argonne National Laboratory News Room USA Overview Argonne National Laboratory has developed DONUT, a physics-aware machine learning tool that enables real-time X-ray data analysis at the Advanced Photon Source (APS). DONUT allows materi... -
Argonne Lab Advocates Physics-Grounded PhysMat AI to Boost Reliability and Accelerate Materials Discovery
arXiv USA Overview An arXiv paper introduces the concept of Physics-Grounded Materials AI (PhysMat AI) to enhance reliability in materials discovery. PhysMat AI integrates physical knowledge as prior knowledge, descriptors, constraints, ... -
Argonne Lab’s Multi-Agent AI System Accelerates New Material Discovery from Months to Days
Argonne National Laboratory USA Overview Argonne National Laboratory researchers have engineered an AI-driven system leveraging multiple AI agents to automate atomistic simulations, slashing the discovery timeline for new materials from ... -
Argonne National Laboratory Accelerates New Materials Discovery from Months to Days Using AI Agents
Argonne National Laboratory USA Overview Researchers at Argonne National Laboratory demonstrated an AI-driven system automating powerful simulation methods for predicting atomic interactions in materials. This system utilizes multiple AI... -
SLAC and Four Institutions Demonstrate AI-Enhanced Catalyst Development for Fuel Production, Highlighting Need for Standardization
Facebook (SLAC National Accelerator Laboratory) USA Overview Researchers from SLAC, Stanford, Penn State, and UC Santa Barbara collaborated to demonstrate AI's potential in developing catalysts for fuel production. However, inconsistenci...
