Research Articles
In Situ TEM for Nanomaterial Analysis: Fundamentals, Methods, and Applications in Biomedicine
This article provides a comprehensive overview of in situ Transmission Electron Microscopy (TEM), a transformative technique enabling real-time, atomic-scale observation of nanomaterial dynamics under realistic microenvironmental conditions.
Optimizing Photoluminescence Quantum Yield with Regression Models: A Machine Learning Guide for Biomedical Materials
This article explores the transformative role of machine learning (ML), particularly regression models, in optimizing the photoluminescence quantum yield (PLQY) of advanced materials for biomedical and clinical applications.
Active Learning for Low-Data Scenarios: A Strategic Guide to Accelerating Reaction Optimization in Drug Discovery
This article provides a comprehensive guide for researchers and drug development professionals on implementing active learning (AL) to overcome data scarcity in reaction optimization.
Transfer Learning for Stereoselectivity Prediction in Catalysis: A Data-Driven Guide for Pharmaceutical Development
The accurate prediction of stereoselectivity is crucial for developing chiral pharmaceuticals and agrochemicals, but traditional methods are often limited by scarce experimental data.
Machine Learning in Heterogeneous Catalysis: From Data-Driven Discovery to Generative Design
This article provides a comprehensive overview of the transformative impact of machine learning (ML) on heterogeneous catalyst design, a cornerstone for sustainable chemical production and energy technologies.
Active Learning in Chemistry Optimization: Accelerating Discovery from Molecules to Materials
Active learning (AL) is transforming computational and experimental chemistry by creating intelligent, self-improving workflows that drastically reduce resource consumption.
From Fixed Constants to Dynamic Ranges: How Modern Periodic Law Corrects Atomic Weights for Advanced Research
This article examines the critical evolution of atomic weights from fixed constants to variable, sample-dependent quantities, a paradigm shift driven by the principles of modern periodic law.
Beyond Mendeleev: Evaluating Periodic Table Designs for Enhanced Chemical Education and Drug Discovery
This article provides a comprehensive assessment of alternative periodic table designs and their specific utility for researchers, scientists, and drug development professionals.
Beyond the Pattern: Navigating Unexpected Chemical Behavior and Deviations from Periodicity in Drug Discovery
This article explores the critical phenomenon of unexpected chemical behavior and deviations from periodicity, a subject of paramount importance for researchers and professionals in drug development.
Anomalous Pairs in the Periodic Table: Resolving Historical Contradictions and Modern Implications for Drug Development
This article provides a comprehensive analysis of anomalous pairs in the periodic table, tracing their journey from historical classification puzzles to their resolution through modern atomic theory.