Electrochemical oxidation of sulfamethoxazole using Ti/SnO2-Sb/Co-PbO2 electrode through ANN-PSO

Abstract

Even in a trace amounts, the presence of antibiotics in aqueous solution is getting more and more attention. Accordingly, appropriate technologies are needed to efficiently remove these compounds from aqueous environments. In this study, we have examined the electrochemical oxidation (EO) of sulfamethoxazole (SMX) on a Co modified PbO 2 electrode. The process of EO of SMX in aqueous solution followed the pseudo-first-order kinetics, and the removal efficiency of SMX reached the maximum value of 95.1 % within 60 min. The effects of major factors on SMX oxidation kinetics were studied in detail by single-factor experiments, namely current density (1-20 mA cm-2), solution pH value (2-10), initial concentration of SMX (10-500 mg L-1) and concentration of electrolytes (0.05-0.4 mol L-1). An artificial neural network (ANN) model was used to simulate this EO process. Based on the obtained model, particle swarm optimization (PSO) was used to optimize the operating parameters. The maximum removal efficiency of SMX was obtained at the optimized conditions (e.g., current density of 12.37 mA cm-2 , initial pH value of 4.78, initial SMX concentration of 74.45 mg L-1 , electrolyte concentration of 0.24 mol L-1 and electrolysis time of 51.49 min). The validation results indicated that this method can ideally be used to optimize the related parameters and predict the anticipated results with acceptable accuracy.

Synthesis and Characterization of New Azo Dye Derived from Sulfamethaxolevia Diazonium Reaction and Study its Abilityas an Acid-base Indicator

“…It is one of many antibiotics [2]. A survey of the literature showed that different techniques have been reported for SMZ analysis, some of which include spectrophotometric methods [1], for instance, HPLC [3], electrochemical methods [4] an solid phase extraction [5]. Diazotization method is simple and inexpensive method.…”

Dye Pollutant Removal from Synthetic Wastewater: A New Modeling and Predicting Approach Based on Experimental Data Analysis, Kriging Interpolation Method, and Computational Intelligence Techniques

“…Considering the complications associated with the relationship of the above-mentioned parameters, it is difficult to explain the accurate relationship between these parameters. On the other hand, it is costly and time-consuming to study different conditions and obtain sufficient experimental data that encompasses most conditions (Wan et al, 2019). Thus, modeling and optimization of wastewater treatment processes utilizing artificial intelligence (AI) due to their unique advantages (like a low number of parameters, low computation time and no need for boundary and initial condition), with a focus on achieving the maximum removal efficiency of various pollutants, especially dye pollutants, has received much attention (Fan et al, 2018;Mossavi et al, 2019).…”

Highly Selective Fluorescence Sensor Based on Graphene Quantum Dots for Sulfamethoxazole Determination

“…This risk renders it necessary to determine the SMZ content in pharmaceutical formulations as well as to test residues of SMZ, which should not exceed the regulatory limit in drinking water or in food originating from animals, such as eggs, milk, and meat [5]. Therefore, various SMZ detection methods including spectrophotometry [6], electrochemical methods [7,8], LC/MS [9], HPLC [10,11], solid-phase extraction [12], and voltammetry [13] have been developed.…”