Researchers have developed a new machine learning algorithm that excels at interpreting optical spectra, potentially enabling faster and more precise medical diagnoses and sample analysis. Researchers ...

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 ...

Workflow of the proposed AI-based approach interpreting X-ray absorption spectroscopy (XAS) data (IMAGE) ...

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 ...

Carbon materials, such as carbon fibers and activated carbons, are essential across a wide variety of fields, encompassing everything from aerospace engineering to fuel cells and thermal insulation.

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 ...