By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

Add Yahoo as a preferred source to see more of our stories on Google. Although the Nobel Prizes in physics and chemistry are awarded separately, there is a fascinating connection between the winning ...

Six popular machine learning models. (a) Decision tree; (b) feedforward neural network (Trans: transformation; Activ Func: activation functions); (c) convolution neural network (Conv: convolution; ...

Peer-reviewed research finds the company’s novel technology enables faster dataset construction, further shortening Avicenna’s timelines to develop life-saving medicines. “We’re accustomed to hearing ...

A new artificial intelligence framework developed at Cornell can accurately predict the performance of battery electrolytes ...

Machine learning has huge potential as a tool to investigate new materials and new applications of existing materials, as well as to streamline and focus future experimentation through rapid screening ...

In March, a paper in the Journal of the American Chemical Society sparked a heated Twitter debate on the value of machine learning for predicting optimal reaction pathways in synthetic chemistry. The ...

(Nanowerk News) Researchers from Carnegie Mellon University and Los Alamos National Laboratory have used machine learning to create a model that can simulate reactive processes in a diverse set of ...

Machine-learning tools have taken us closer to understanding electrons and how they behave in chemical interactions, following news that UK-based AI company DeepMind, owned by Google’s parent company ...

Orbital-free approach enables precise, stable, and physically meaningful calculation of molecular energies and electron ...