High-throughput Screening– tag –
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Osaka University Develops AI-Designed Super-Adhesive Hydrogel with Self-Healing and High Mechanical Strength Underwater
The Times of India Japan Overview Researchers at Osaka University and collaborating Japanese institutions have developed a novel AI-designed super-adhesive hydrogel that exhibits superior underwater adhesion, self-healing capabilities, a... -
Self-Driving Labs, Integrating AI and Automated Experimentation, Accelerate Chemical and Materials Discovery
ResearchGate (Review) Global Overview Autonomous self-driving labs (SDLs), which integrate machine learning with automated experimental platforms, are dramatically accelerating the pace of molecular and materials discovery in chemistry a... -
Select Science Introduces Gri3D® Hydrogel Microcavity Plates: Achieving High Reproducibility and Scalability in Standardized Organoid Culture
Select Science UK Overview Select Science has highlighted the Gri3D® Hydrogel Microcavity Plates, which dramatically improve the reproducibility and scalability of organoid culture. This system utilizes PEG-based hydrogel microcavities t... -
Johns Hopkins and Toyota TRI Accelerate Next-Gen Fluoride-Ion Battery Electrolyte Development with AI and Automated Experiments
Johns Hopkins University, Department of Chemical and Biomolecular Engineering USA Overview A joint team from Johns Hopkins University and Toyota Research Institute (TRI) announced a breakthrough approach combining AI and high-throughput ... -
Gyros Protein Technologies Streamlines Biotherapeutic Impurity Testing with Automated Immunoassay Platform: Enhancing Reproducibility and Throughput
Bioprocess International (via Gyros Protein Technologies webcast summary) USA Overview Gyros Protein Technologies is addressing impurity testing challenges in biotherapeutic development with its Gyrolab automated immunoassay platform. Th... -
Automation & AI Scale Organoid Workflows to Accelerate Drug Discovery, Improving 3D Model Reproducibility
News-Medical.net UK Overview Automation, AI, and advanced organoid technologies are transforming early drug discovery by improving the scalability, reproducibility, and quality control of 3D cell models. Automated workflows and AI-driven... -
Berkeley Lab’s EcoBOT: An Autonomous Lab for Reproducible, AI-Driven Bioenergy Discovery
Berkeley Lab USA Overview Researchers at Lawrence Berkeley National Laboratory (Berkeley Lab) have unveiled EcoBOT, an autonomous laboratory designed to overcome long-standing reproducibility issues in plant-microbe interaction research ... -
AI and Machine Learning Drive Breakthroughs in Sustainable Catalyst Design, Expanding Applications from CO2 Conversion to Polymer Recycling
MDPI Switzerland Overview The integration of Artificial Intelligence (AI) and Machine Learning (ML) is fundamentally transforming catalyst design and sustainable chemical process development. These technologies accelerate new catalyst di... -
Frontiers Launches Research Topic on “High-Throughput AI-Driven Materials Discovery for High-Rate Batteries,” Accelerating Next-Gen Energy Storage
Frontiers Switzerland Overview Frontiers has initiated a new research topic, "High-Throughput AI-Driven Materials Discovery and Design for High-Rate Batteries," aiming to revolutionize battery material development through machine learnin... -
Oxford Academic: Machine Learning and LLM Synergy Uncovers High-Entropy Alloy Electrocatalytic Activity, Enabling High-Throughput Discovery
National Science Review (Oxford Academic) China Overview Research published in Oxford Academic combined machine learning (including GNNs) with an LLM-driven collaborative framework to unveil correlations between high-entropy alloy (HEA) ...
