One of the shared, fundamental goals of most chemistry researchers is the need to predict a molecule's properties, such as its boiling or melting point. Once researchers can pinpoint that prediction, ...

Scanning electron microscopy image (left) shows the surface of a porous asymmetric UF membrane created at Cornell by mixing chemically distinct block copolymer micelles. Machine-learning segmentation ...

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 ...

In recent years, the integration of machine learning and robotics technologies in chemical analysis has transformed the landscape of scientific research and industry practices. This revolution is not ...

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 ...

Validating drug production processes need not be a headache, according to AI researchers who say machine learning (ML) could be a single answer to biopharma’s multivariate problem. The FDA defines ...

Forensic science plays a vital role in identifying, characterizing, and quantifying physical and biological traces recovered from crime scenes — a task that ...

The human brain, with its billions of interconnected neurons giving rise to consciousness, is generally considered the most powerful and flexible computer in the known universe. Yet for decades ...

(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 ...