Towards better understanding of near-infrared spectroscopy

Near-infrared spectroscopy (NIRS) has grown to become a powerful tool in modern analytical chemistry. It is non-invasive, on-site capable, inexpensive and fast, and widely applicable to a variety of samples and materials. By allowing simultaneous quantification of multiple components in the sample NIRS offers a substantial decrease of the time and cost factors in the analytical routine. In the present decade the technique wide-spreads in the field of analysis of natural samples (i.e. plant medicine, food). NIRS fits both laboratory and industrial environment, and introduction of miniaturized equipment has further enhanced its potential to fill the role of a major analytical technique of the future. NIR spectra are intrinsically complex; this is one of the strength of the technique as it delivers rich information on the sample. On the other hand the complexity often hinders our ability to comprehend NIR spectra and the plentiful information needs to be processed with advanced tools of statistical analysis (so called chemometrics) to correlate it with the sample properties of our interest such as its content. Despite analytical effectiveness this approach does not provide any insights into the molecular or vibrational properties of the sample; effectively it works as a black-box and analytical NIRS remains largely detached from its physicochemical roots. Recent advances in NIR spectra simulation by quantum mechanical (QM) calculations have brought an opportunity to close the emerged gap by providing an independent insight. This project aims at bringing decisive answers on how the molecular background relates to the chemometric models, which vibrational modes tend to be the relevant ones in quantification procedures and what is the role of intermolecular interaction of the quantified constituent and its chemical environment. The objects of the study involve samples which are highly relevant for human health; plant medicines, food constituents and adulterants. The project will be conducted with supervision of Professor Christian W. Huck (University of Innsbruck) and Professor Yukihiro Ozaki (Kwansei Gakuin University and University of Innsbruck); both are worldwide recognized experts and have extensive experience in the projects field. The results of the project will bring new knowledge in the area between basic and applied NIRS with strong prospects for further adoption in refining the analytical data processing.

"Towards better understanding of near-infrared spectroscopy" Near-infrared spectroscopy (NIRS) is a potent tool in modern analytical chemistry. It is highly valued for non-destructive analysis of molecular composition, and it is on-site capable, inexpensive and fast, and widely applicable to a variety of samples and materials. By allowing simultaneous quantification of multiple components in the sample NIRS offers a substantial decrease of the time and cost factors in the analytical routine. NIRS fits both laboratory and industrial environment, and introduction of miniaturized equipment has further enhanced its potential to fill the role of a major analytical technique of the future. NIR spectra are intrinsically complex; this is one of the strengths of the technique as it delivers rich information on the sample. On the other hand, this complexity often hinders our ability to comprehend NIR spectra and the plentiful information needs to be processed with advanced tools of machine learning (so called chemometrics) to correlate it with the sample properties of our interest such as its content. Effectively, it is "black-box" approach in which molecular and physicochemical origins of the analyzed information are not explored. This project conducted under supervision of the PI, Professor Christian W. Huck (University of Innsbruck) employed innovative methods of computer simulation of NIR spectra by quantum mechanical (QM) methods in combination with machine learning and miniaturized spectrometers. The results of the project brought new knowledge in the area between basic and applied science. Among others key findings, the project brought decisive answers on how the molecular background is expressed in the chemometric models, which vibrational modes tend to be the relevant ones in quantification procedures and what is the role of intermolecular interaction of the quantified constituent and its chemical environment. The objects of the study involved samples which are highly relevant for key sectors of public interest; ingredients of natural medicines, food constituents and adulterants.