Research Articles
Active Learning for On-the-Fly ML Potentials: A Complete Guide for Materials & Drug Discovery Researchers
This article provides a comprehensive overview of active learning (AL) for training machine learning interatomic potentials (MLIPs) on-the-fly during molecular dynamics simulations.
From Virtual Screening to Real Solutions: How Active Learning Accelerates Inverse Materials Design
This article provides a comprehensive guide for researchers and drug development professionals on the application of active learning (AL) to the challenge of inverse materials design.
Active Learning in Materials Synthesis: Accelerating Discovery of Next-Generation Biomedical Compounds
This article provides a comprehensive guide for researchers on implementing active learning (AL) cycles for experimental materials synthesis, with a focus on biomedical applications.
Self-Driving Science: How Active Learning is Revolutionizing Autonomous Materials Labs for Biomedical Research
This article provides a comprehensive guide for researchers on the implementation and impact of active learning in autonomous materials laboratories.
Mastering Homogeneous Mixing in Mesoreactors: A Guide for Scaling Up Lab Reactions
This article provides a comprehensive guide for researchers and drug development professionals seeking to achieve homogeneous mixing in mesoscale reactors.
Achieving Electrical Neutrality in Salt Mixtures: A Critical Guide for Analytical Accuracy in Pharmaceutical Research
This article provides a comprehensive guide for researchers and drug development professionals on the critical principle of electrical neutrality in salt mixture analysis.
Balancing Act: How to Select the Right DFT Functional for Accuracy vs. Computational Cost in Drug Discovery
This article provides a comprehensive guide for researchers and drug development professionals on navigating the critical trade-off between accuracy and computational cost when selecting Density Functional Theory (DFT) functionals.
Beyond Random Forests: A Complete Guide to Accuracy Assessment for Extra-Trees Models in Materials Property Prediction
This comprehensive article provides a structured framework for researchers and materials scientists to rigorously evaluate the predictive accuracy of Extra-Trees (Extremely Randomized Trees) models.
Unlocking the Power of Public High-Throughput Data: A Researcher's Guide to Accelerating Drug Discovery
This guide provides a comprehensive roadmap for researchers and drug development professionals to effectively navigate, access, and leverage major public high-throughput experimental materials databases.
Beyond Trial-and-Error: AI, Automation, and High-Throughput Strategies for Accelerating Functional Thin Film Discovery
This article provides a comprehensive guide for researchers and development professionals on modern strategies to accelerate the discovery of functional thin films.