Research Articles
Machine Learning for Catalysis Informatics: The Smart Search for Tomorrow's Catalysts
Explore how machine learning is revolutionizing catalyst discovery and design through catalysis informatics, with applications across heterogeneous catalysis, biocatalysis, and electrochemistry.
The Invisible Engineers: How Machine Learning is Revolutionizing the Science of Surfaces
Exploring how machine learning is transforming computational surface science and enabling breakthroughs in materials design
Cracking the Surface Code: How Machine Learning is Revolutionizing Material Design
Discover how Machine Learning Interatomic Potentials are transforming material science by accurately predicting inorganic surface behaviors with unprecedented speed and precision.
Bridging the Complexity Gap in Computational Heterogeneous Catalysis with Machine Learning
Explore how machine learning is revolutionizing catalyst design by bridging the gap between computational accuracy and efficiency in heterogeneous catalysis.
Decoding Nature's Blueprint: How Machine Learning Reveals the Hidden World of Silicon-Oxygen Materials
Explore how active machine learning is revolutionizing our understanding of silicon-oxygen materials at atomic and nanoscale levels, enabling breakthroughs in energy storage and materials science.