Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...
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Researchers at the Indian Institute of Science (IISc), with collaborators at University College London, have developed ...
When experiments are impractical, density functional theory (DFT) calculations can give researchers accurate approximations of chemical properties. The mathematical equations that underpin the ...
Chinese Journal of Catalysis is co-sponsored by Dalian Institute of Chemical Physics, Chinese Academy of Sciences and Chinese Chemical Society, and it is currently published by Elsevier group. This ...
Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...
Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries? Theoretical ...
Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests. Systems controlled by next-generation computing ...
The creative new approach could lead to more energy-efficient machine-learning hardware. On a table in his lab at the University of Pennsylvania, physicist Sam Dillavou has connected an array of ...
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