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

Machine learning-based neural network potentials often cannot describe long-range interactions. Here the authors present an approach for building neural network potentials that can describe the ...

Researchers at Stony Brook University’s Materials Science and Chemical Engineering Department have been using computers that are capable of learning to recognize various steps in the complex movement ...

Catalysts play an indispensable role in modern manufacturing. More than 80% of all manufactured products, from pharmaceuticals to plastics, rely on catalytic processes at some stage of production.

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 ...

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 ...

Artificial intelligence, building-block chemistry and a molecule-making machine teamed up to find the best general reaction conditions for synthesizing chemicals important to biomedical and materials ...

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 ...

Imagine you’re a materials scientist and your job is to discover a new material, a combination of atoms no one has ever made. Maybe you’re looking for a metal-organic framework (MOF). They have a lot ...

(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 ...

Achieving ultra-low friction at macroscopic scales is highly desirable. In this work molecular dynamics simulations of graphitic contacts incorporating corrugated grain boundaries reveal an unusual ...