Closed-loop– tag –
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Self-Driving Labs: Exploring the Feasibility of Closed-Loop Experimentation in Pharma R&D, Addressing XRD Data Challenges
Sakara Digital USA Overview This article discusses the feasibility of autonomous closed-loop experimentation in pharmaceutical R&D, identifying criteria for suitability and practical bottlenecks. The A-Lab team emphasizes demonstrati... -
Tohoku University Unveils AI-Powered ‘Self-Driving Lab’ for Accelerated Polymer Discovery
Tohoku University (WPI-AIMR) Japan Overview Researchers at Tohoku University's WPI-AIMR have developed an integrated, closed-loop AI system that dramatically accelerates the discovery of new polymer materials. By seamlessly linking polym... -
ChemCopilot Q3 2026 Report Highlights ELLIS Finland and Acceleration Consortium Leading Chemical AI and Autonomous Labs
ChemCopilot USA Overview ChemCopilot released its Q3 2026 report on chemical AI, autonomous labs, and digital R&D transformation, spotlighting ELLIS Institute Finland for its expertise in predictive signal extraction in low-data envi... -
Texas A&M Receives $24.9M Grant for Autonomous Robotic Metallurgist Materials Innovation Platform (ARM-MIP): Robots and AI to Test, Analyze New Alloys 24/7
Facebook (Texas A&M University) USA Overview Texas A&M University secured a $24.9 million grant to establish the Autonomous Robotic Metallurgist Materials Innovation Platform (ARM-MIP), an autonomous metal discovery lab. This state-o... -
Energy & Environmental Science: AI Optimizes Li-Ion Battery Electrolytes via Data-Driven Methods, Accelerating Discovery of Novel Solvents, Salts, and Solid Electrolytes
Energy & Environmental Science UK Overview A review in Energy & Environmental Science highlights AI's transformative impact on Li-ion battery electrolyte research, leveraging data-driven prediction, mechanistic analysis, and intellig... -
MDPI Review: AI Revolutionizes Li-ion Battery Development with Closed-Loop Discovery, State Prediction, and Trustworthy Management
MDPI Switzerland Overview A review published in MDPI reveals AI is transforming lithium-ion battery (LIB) research into a closed-loop paradigm integrating data-driven prediction, mechanistic interpretation, and experimental validation. T... -
Preprints.org Publishes Review on High-Entropy Alloy Design: ML Addresses Combinatorial Explosion in Discovery
Preprints.org Unknown Overview A review paper published on Preprints.org explores the convergence of physical metallurgy and data-driven methods in high-entropy alloy (HEA) design. The paper details how AI and machine learning (ML) addre... -
Princeton University and Collaborators Awarded $19.5 Million by NSF to Establish Open-Access Autonomous Chemistry Laboratory
UCLA Chemistry USA Overview Professor Abigail Doyle of Princeton University and collaborators have secured a $19.5 million National Science Foundation (NSF) award to establish an open-access, AI-enabled autonomous chemistry laboratory. T... -
Autonomous Materials Discovery Labs Slash Development Time from Decades to Weeks through Closed-Loop ML and Robotic Experimentation
Scifiniti International Overview The paper 'AI-Guided Self-Driving Laboratories for Advanced Materials Discovery' proposes that autonomous materials discovery platforms, integrating closed-loop machine learning and robotic experimentatio... -
Review Paper on AI-Driven Inverse Design of Functional Materials Forecasts Broad Applications from Energy Catalysis to Structural Materials
Scientific Research Publishing (SCIRP) International Overview A Scientific Research Publishing (SCIRP) paper provides a systematic review of progress and challenges in 'AI-enabled reverse design' of functional materials. The study analyz...
