Trained on quantum data, a new model makes computations more accurate while keeping computer costs low ...
Reiher was referring to work published earlier this year by Meta, the owner of Facebook and Instagram. Meta released its open molecule dataset or OMol25 – the largest ever dataset of quantum chemistry ...
Techno-Science.net on MSN
⚡ A new method to predict high-temperature superconductors
Electricity flows through our cables, but some energy is lost as heat. These losses could be avoided thanks to superconductors: materials capable of carrying current without ...
Scientists use quantum many-body data and machine learning to boost density functional theory accuracy for chemistry and ...
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Building better batteries with amorphous materials and machine learning
Lithium-ion batteries power most electronics, but they have limited energy density—they can store only a certain amount of ...
A generative AI framework predicts stable antiferromagnets, identifying semiconductors and metals with properties suited for ...
INTRODUCTION: Density functional theory (DFT) is a widely used method for calculating the electronic properties of materials. The method is based on the idea of approximating the many-electron wave ...
The photocatalytic carbon dioxide reduction technology is regarded as a core method in this field due to its environmentally friendly characteristics. However, the primary carrier of this ...
4d
IISc researchers use machine learning and amorphous materials to build high energy density batteries
The Indian Institute of Science (IISc) researchers, in a new study using a machine learning model and amorphous materials, ...
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