首页|Southern Federal University Reports Findings in Machine Learning (Machine Learning for Quantitative Structural Information from Infrared Spectra: The Case of Palladium Hydride)
Southern Federal University Reports Findings in Machine Learning (Machine Learning for Quantitative Structural Information from Infrared Spectra: The Case of Palladium Hydride)
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NETL
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Wiley
New research on Machine Learning is the subject of a report. According to news originating from Rostov on Don, Russia, by NewsRx correspondents, research stated, “Infrared spectroscopy (IR) is a widely used technique enabling to identify specific functional groups in the molecule of interest based on their characteristic vibrational modes or the presence of a specific adsorption site based on the characteristic vibrational mode of an adsorbed probe molecule. The interpretation of an IR spectrum is generally carried out within a fingerprint paradigm by comparing the observed spectral features with the features of known references or theoretical calculations.” Our news journalists obtained a quote from the research from Southern Federal University, “This work demonstrates a method for extracting quantitative structural information beyond this approach by application of machine learning (ML) algorithms. Taking palladium hydride formation as an example, Pd-H pressure-composition isotherms are reconstructed using IR data collected in situ in diffuse reflectance using CO molecule as a probe.”
Rostov on DonRussiaEurasiaCyborgsEmerging TechnologiesMachine LearningPalladiumTransition Elements
NETL
NSTL
Wiley
