High-throughput Screening– tag –
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AI-Assisted Multiobjective High-Throughput Screening of GPE Accelerates Safer Lithium Battery Development
ACS Publications USA Overview An ACS Publications paper reports a method accelerating the development of safer lithium batteries through AI-assisted multiobjective high-throughput screening and prioritization of gel polymer electrolytes ... -
Fine-Tuned MACE Foundation Model Develops Transferable MLP Predicting Water Adsorption in 420 Al-MOFs with DFT Accuracy
ACS Publications USA Overview This paper successfully developed a transferable machine learning potential (MLP) by fine-tuning a MACE foundation model to accurately predict water adsorption behavior in Metal-Organic Frameworks (MOFs). Tr... -
ArXiv Paper: Closed-Loop Autonomous Perovskite Thin-Film Synthesis Framework Developed Integrating LLMs and Bayesian Optimization, Demonstrates Novel Rb3BiI6
arXiv International Overview A closed-loop framework for automating the synthesis of computationally predicted materials has been introduced. This system integrates Large Language Model (LLM)-driven extraction of synthesis knowledge from... -
Machine-Learned Interatomic Potential Developed for Tungsten-Boron Surface Sputtering via tabGAP Framework, Guiding MXene Defect Engineering
arXiv International Overview A machine-learned interatomic potential (MLIP) has been developed using the tabGAP framework to simulate sputtering behavior of tungsten-boron (W-B) surfaces at large scales. Trained with density functional t... -
Era of AI-Driven Biocatalyst Design: Advances in High-Throughput Sequencing, Modeling, and Machine Learning Revolutionize Enzyme Engineering
(Scientific journal/review) Unknown Overview A new review discusses the evolution of enzyme engineering from classical strategies to AI-driven biocatalyst design. Advancements in high-throughput sequencing, modeling, and machine learning... -
Royal Society of Chemistry Unveils Open-Source Software Platform for Automating Massively Parallel Battery Cycling Experiments
The Royal Society of Chemistry UK Overview The Royal Society of Chemistry has announced a scalable open-source software platform for managing and automating massively parallel battery cycling experiments. This platform accelerates new ma... -
ACS Publications: OMol25-Trained MLIPs Enable High-Accuracy, High-Throughput Na-ion Battery Electrolyte Solvation Structure Prediction with Experimental Verification
ACS Publications USA Overview An ACS Publications paper demonstrates that OMol25-trained machine learning interatomic potentials (MLIPs) provide an efficient and accurate route to predictive, high-throughput electrolyte simulations for n... -
Automat Solutions Unveils Integrated AI-Robotic Platform to Accelerate Battery Material Innovation, Leverages LLM
Automat Solutions USA Overview Automat Solutions has launched an integrated AI-Robotic Platform designed to accelerate battery materials innovation. This platform combines AI, high-throughput robotic experimentation, automated electroche... -
AI Drives Strategic Advancement in Biopharmaceutical Development: From Antibody Design to Quality Control, Backed by Indian Government Initiatives
Press Information Bureau, Government of India India Overview AI is strategically transforming biopharmaceutical development, from target identification and multispecific antibody design to automated quality control. India is significantl... -
Cerebral Organoids Enter Industrial Era: Automation Drives Standardization and High-Throughput Scaling for Neuroscience Innovation
Newfund Capital USA Overview Cerebral organoid production is undergoing a transformative industrialization, driven by automated platforms for iPSC generation, expansion, and differentiation. This technological leap standardizes manufactu...
