First derivative-supervised pattern recognition for the flow-injection spectrophotometric discrimination of s-triazines in water

Abstract

A new spectrophotometric method is presented for the automated differentiation of chloro-(0.5 to 5.0 g/mL), thio-(0.5 to 5.0 g/mL) and methoxy-triazines (1 to 10 g/mL) in water samples. Classification models obtained by K-nearest neighbours, Soft Independent Modeling of Class Analogy, and Partial Least Squares-Discriminatory Analysis were constructed from zero order and first derivative absorption spectra as independent variables, in the spectral range from 210 to 270 nm. Binary responses were used as classifying variables (with/without certain group of triazines). With this dichotomous structure, parameters related to 2x2 contingency tables were used to evaluate the performance of the models. For tap and well water samples, sensitivity and selectivity values equal or higher than 50 % were obtained from autoscaled first derivative spectra, discriminated by Partial Least Squares-Discriminatory Analysis. TriazinesPattern recognition Water Statistical data analysis s-Triazines Flow-injection

Methylthionine chloride degradation on pilot UV-C reactors: Kinetics of photolytic and heterogeneous photocatalytic reactions

“…Photocatalytic waste water treatments use different reactors where the semiconductor is fixed in a specific place in the system where it receives the UV radiation, which can be artificial by means of a lamp or natural solar, necessary for the reaction to occur (Pantoja-Espinoza et al, 2015;Abreu-Zamora et al, 2016;Núñez-Núñez et al, 2018;Cruz, 2019;González-Burciaga et al, 2020). To monitor the degradation of the pollutant in aqueous solution, the most widely used reactors are those that have TiO 2 supported on an immobile material, as long as the photocatalyst is in a phase of aggregation different from that of the compound to be degraded (De Felipe, 2008;Amador-Hernández et al, 2011).…”