Machine learning interatomic potentials (MLIPs) have become an essential tool to enable long-time scale simulations of materials and molecules at unprecedented accuracies. The aim of this collection ...
Electro- and photocatalytic materials are central to enabling sustainable energy conversion processes such as water splitting, CO2 reduction, oxygen ...
Key TakeawaysThe Materials Project is the most-cited resource for materials data and analysis tools in materials science.The ...
Shanghai, August 21, 2025 — Nuclear energy is widely recognized as one of the most promising clean energy sources for the future, but its safe and efficient use depends critically on the development ...
Researchers from China University of Petroleum (East China), in collaboration with international partners, have reported a comprehensive review of ...
When experiments are impractical, density functional theory (DFT) calculations can give researchers accurate approximations of chemical properties. The mathematical equations that underpin the ...
Discover how a new machine learning method can help scientists predict which MOF structures are good candidates for advanced ...
Computational Chemistry is the study of complex chemical problems using a combination of computer simulations, chemistry theory and information science. Also called cheminformatics, this field enables ...
The human brain, with its billions of interconnected neurons giving rise to consciousness, is generally considered the most powerful and flexible computer in the known universe. Yet for decades ...
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