In a review published in Engineering, scientists explore the burgeoning field of machine learning (ML) and its applications in chemistry. Titled "Machine Learning for Chemistry: Basics and ...

Carbon dioxide (CO2) is a primary driver of climate change in Earth's atmosphere. At the State University of New York at ...

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 ...

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 ...

Machine learning has emerged as a transformative tool in quantum chemistry, offering unprecedented speed and scalability while retaining near–ab initio accuracy. At its core, modern approaches employ ...

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 ...

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 ...

(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 ...

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 ...

Researchers say they have come up with two new antibiotic peptide candidates using a combination of machine learning, molecular dynamics, and experiments(Nat. Biomed. Eng. 2021, DOI: ...

Making high-performance proteins for medicines or consumer products can take trial after trial of tweaks, experiments and fine-tuning. A new machine learning framework squeezes all that into a single ...