Discovery of the Linear Region of Near Infrared Diffuse Reflectance Spectra Using the Kubelka-Munk Theory

Enhanced photocatalytic ammonia oxidation activity and nitrogen selectivity over Ag/AgCl/N-TiO2 photocatalyst

The removal of ammonia (NH3) emitted from agricultural and industrial activities is of great significance to protect human health and ecological environment. Photocatalytic NH3 oxidation to N2 under mild conditions is a promising strategy. However, developing visible light photocatalysts for NH3 oxidation is still in its infancy. Here, we fabricate N-TiO2 and Ag/AgCl/N-TiO2 photocatalysts by sol-gel and photodeposition methods, respectively. The introduction of N not only endows TiO2 with visible light response (absorption edge at 460 nm) but also results in the formation of heterophase junction (anatase and rutile). Thus, N-TiO2 shows 2.0 and 1.8 times higher than those over anatase TiO2 and commercial TiO2 for NH3 oxidation under full spectrum irradiation. Meanwhile, surface modification of Ag can simultaneously enhance visible light absorption (generating localized surface plasmon resonance effect) and charge separation efficiency. Therefore, the photocatalytic activity of Ag/AgCl/N-TiO2 is further improved. Furthermore, the presence of N and Ag also enhances the selectivity of N2 product owing to the change of reaction pathway. This work simultaneously regulates photocatalytic conversion efficiency and product selectivity, providing some guidance for developing highly efficient photocatalysts for NH3 elimination.

Application of visible-near infrared spectroscopy in tandem with multivariate analysis for the rapid evaluation of matcha physicochemical indicators

Consumer preference for matcha is heavily influenced by its physicochemical properties. The visible-near infrared (Vis-NIR) spectroscopy technology coupled with multivariate analysis was investigated for rapid and non-invasive evaluation of particle size and the ratio of tea polyphenols to free amino acids (P/F ratio) of matcha. The multivariate selection algorithms such as synergy interval (Si), variable combination population analysis (VCPA), competitive adaptive reweighted sampling (CARS), and interval combination population analysis (ICPA) were compared, and eventually, the variable selection strategy of ICPA and CARS hybridization was firstly proposed for selecting the characteristic wavelengths from Vis-NIR spectra to build partial least squares (PLS) models. Results indicated that the ICPA-CARS-PLS models achieved satisfactory performance for the evaluation of matcha particle size (Rp = 0.9376) and P/F ratio (Rp = 0.9283). Hence the rapid, effectual, and nondestructive online monitoring, Vis-NIR reflectance spectroscopy in tandem with chemometric models is significant for the industrial production of matcha.