The first HyDRA challenge for computational vibrational spectroscopy

Vibrational spectroscopy in supersonic jet expansions is a powerful tool to assess molecular aggregates in close to ideal conditions for the benchmarking of quantum chemical approaches. The low temperatures achieved as well as the absence of environment effects allow for a direct comparison between computed and experimental spectra. This provides potential benchmarking data which can be revisited to hone different computational techniques, and it allows for the critical analysis of procedures under the setting of a blind challenge. In the latter case, the final result is unknown to modellers, providing an unbiased testing opportunity for quantum chemical models. In this work, we present the spectroscopic and computational results for the first HyDRA blind challenge. The latter deals with the prediction of water donor stretching vibrations in monohydrates of organic molecules. This edition features a test set of 10 systems. Experimental water donor OH vibrational wavenumbers for the vacuum-isolated monohydrates of formaldehyde, tetrahydrofuran, pyridine, tetrahydrothiophene, trifluoroethanol, methyl lactate, dimethylimidazolidinone, cyclooctanone, trifluoroacetophenone and 1-phenylcyclohexane-cis-1,2-diol are provided. The results of the challenge show promising predictive properties in both purely quantum mechanical approaches as well as regression and other machine learning strategies

Design and Experiment of NIR Wheat Quality Quick Detection System

International audienceIn this paper, NIR wheat quality quick detection system (NIR-WQDS) was developed on the base of grating technology with a scanning range of 900-1700nm.46 wheat samples were analyzed to compare performance of NIR-WQDS and MPA FT-NIR spectroscopy (MPA). Experiment results of NIR-WQDS show that the coefficient of determination R2 is 94.44%, root mean square error of cross validation RMSECV is 0.3460, ratio of performance to standard deviate RPD is 4.240, and root mean square error of prediction RMSEP is 0.2430, respectively. The model of MPA spectroscopy gave an R2 of 95.95%, a RMSECV of 0.2950, a RPD of 4.970, and an RMSEP of 0.2270 respectively. It is found that spectra of NIR-WQDS have a roughly same changing trend. NIR-WQDS can detect wheat quality with good accuracy, repeatability and stability, which is similar to MPA. The results show that NIR-WQDS can work steadily with a good performance