Florida State University chemists have created a machine learning tool that can identify the chemical composition of dried ...

A web application for use by experimental chemists created by us. Uploading a file calculated with commercially available software, and the electronic state can be analyzed. We are working on creating ...

Researchers from Imperial and its spinout company SOLVE Chemistry have presented a chemical dataset at the prestigious AI conference NeurIPS that could help accelerate the use of machine learning to ...

Researchers have used machine learning to create a model that simulates reactive processes in organic materials and conditions. Researchers from Carnegie Mellon University and Los Alamos National ...

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 ...

Machine learning model provides quick method for determining the composition of solid chemical mixtures using only photographs of the sample. Machine learning model provides quick method for ...

Polymer-based dielectrics are widely used in different electrical and electronic devices like capacitors, power transmission cables, and microchips. To adapt to different working conditions, a range ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

A simulation demonstrates the reactions that the ANI-1xnr can produce. ANI-1xnr can simulate reactive processes for organic materials, such as as carbon, using less computing power and time than ...