A machine learning model has been developed that makes optical spectroscopy data easier and quicker to interpret. Researchers from Rice University (TX, USA) have developed a new machine learning ...

Wiley, a global leader in authoritative content and research intelligence, today announced the launch of its spectral ...

image: Researchers at the Institute of Industrial Science, The University of Tokyo, use artificial intelligence to help interpret data generated by material science spectroscopy experiments, which can ...

Infrared (IR) spectroscopy is a precise analytical method that detects molecular vibrations, creating unique spectra for identifying functional groups and structures. It’s used in fields from ...

The proposed method combines a graph neural network with hierarchical clustering to extract key features linking crystal structure to optical spectra, and then groups materials with similar structural ...

This webinar will discuss advanced techniques in NMR spectroscopy, providing descriptions of one-dimensional and two-dimensional NMR experiment types and data interpretation techniques, with examples ...

Organic chemistry, the study of carbon-based molecules, underlies not only the science of living organisms, but is critical for many current and future technologies, such as organic light-emitting ...

A method to interpret artificial intelligence (AI) models used in materials discovery by analyzing their learned features has been developed by researchers from Japan. The method extracts key features ...