Combination of Cu₂O semiconductor with reduced graphene oxide nanocomposites for boosting photocatalytic performance in degradation of organic pollutant

Abstract

This study presents efficient photocatalytic degradation of tetracycline (TC) via impregnation of Cu₂O nanoparticles on TiO₂ nanosheets/reduced graphene oxide nanocomposites. Different techniques such as PXRD, UV–Vis DRS, TEM, FESEM/EDX, Raman spectroscopy and N₂ physisorption were employed to identify synthesized samples. The results of PXRD and Raman analyses indicated that TNs had a pure anatase phase, and graphene oxide was changed to reduced graphene oxide during the hydrothermal procedure. In addition, UV–Vis DRS results proved that modification of TNs with rGO and Cu₂O facilitated the absorption of visible light. The best performance for the degradation of TC was obtained by the CGT(40) sample, which was 71.91% for visible and 83.1% for UV irradiation. The data obtained from degradation tests were modeled by the artificial neural network (ANN) as an intelligent tool. A three-layer network with 20 hidden neurons provided the best performance.

Introduction

The use of medicinal compounds such as antibiotics, hormones and anesthetics in various fields has led to various drugs found in water resources. Antibiotics are the largest group of medicinal compounds used to treat infections in humans and animals, and since they are not fully metabolized in their bodies, they are eventually released into the environment and cause serious problems. Owing to their antibacterial properties, low solubility, and high stability of antibiotics, they cannot be eliminated by routine biological methods used in wastewater treatment [[1], [2], [3]]. Tetracycline (TC) is the second most common group of antibiotics found in effluents of hospital, pharmaceuticals industry, farmhouses and fisheries [ [4,5]]. Numerous physical and chemical processes such as adsorption, liquid phase extraction, ion exchange, membrane processes, and biological and photocatalytic degradation can treat antibiotic-containing effluents depending on environmental conditions [6]. Advanced oxidation processes (AOPs) as a group of oxidation methods can lead to complete mineralization of pollutants to water and carbon dioxide by producing strong radicals. Advanced oxidation methods include ozonation, Fenton, photo Fenton, photolysis and heterogeneous photocatalysis, which the heterogeneous photocatalytic method is particularly important in the degradation of various contaminants. Performing heterogeneous photocatalytic degradation requires activating a semiconductor by the artificial light or the sunlight to produce active radicals. For this reason, titanium dioxide-based photocatalysts are one of the best options for photocatalytic degradation owing to their extraordinary properties [7]. Defects in the bulk and surface of semiconductor act as charge carriers (e⁻-h⁺) trap and improve photocatalytic activity due to charge separation. Therefore, to increase the defects and the specific surface area, diverse structures of titanium dioxide such as nanofibers, nanotubes, nanorods, nanoflowers and nanosheets have been synthesized [8]. Many reports indicate that titanium dioxide nanosheets (TNs) are suitable for photocatalytic degradation reactions owing to their two-dimensional(2D) structure, high specific surface area, low thickness, high percentage of {001} facets, and having transfer channels to reduce recombination of charge carriers. However, large band gap energy (E_g = 3.0–3.2 eV) and high rate of recombination of the charge carriers (e⁻-h⁺), as the two main weaknesses of titanium dioxide, limit light absorption in the visible region and its photocatalytic efficiency [9]. For this reason, to improve the photocatalytic efficiency of titanium dioxide, many efforts have been made in recent years, the most important of which is its combination with narrow band gap semiconductors [10]. Copper oxide (Cu₂O) with narrow band gap energy (E_g = 2.0–2.2 eV) is one of the best options to degrade contaminants under visible light. When titanium dioxide is combined with copper oxide, the electric field created between p-type Cu₂O and n-type TiO₂ reduces the recombination rate of the charge carriers, and the electrons produced under visible light in the copper oxide moves from the conduction band (CB) of Cu₂O to that of TiO₂ [11].

Different derivatives of graphene such as graphene oxide (GO) and reduced graphene oxides (rGO) have been recognized as appropriate candida to boost the performance of degradation processes. rGO can be used in various fields owing to its excellent properties such as high surface area, electron transfer, high thermal conductivity, optical transparency and high Young's modulus. Recent studies have demonstrated that reduced graphene oxide can be obtained from graphene oxide by increasing the temperature, ultraviolet radiation, natural reagents, and bacteria [12]. Reduced graphene oxide due to its ability to trap electrons and promote the separation of charge carriers can play a crucial important role in photocatalytic degradation processes. Therefore, the combination of titanium dioxide with carbon materials can extend the ability of light absorption in the visible region through formation of titanium-carbon bonds in hybrid materials [[13], [14], [15]].

Modeling of a process is obtaining data and information about how the process will treat without further practical experiments. The removal percentage as the main parameter of degradation processes is not available due to prolonged and costly experimental tests. Therefore, it is necessary to simulate the system and predict removal percentage values with various variables. Owing to their learning and generalization ability, artificial neural networks (ANNs) have received considerable attention as an intelligent tool in all areas of science to dissolve and optimize sophisticated issues. ANNs, inspired by the biological nervous system, can be used to solve and simulate many complex experimental systems. The most important components of ANNs are neurons responsible for linking the layers together by weighted connections and processing the information [[16], [17], [18]].

There are some reports on Cu₂O, graphene and various morphologies of TiO₂ nanocomposites, which are synthesized by different procedures and applied in wide applications [[19], [20], [21], [22], [23], [24], [25], [26], [27], [28]]. In this study, we prepared the ternary TiO₂ nanosheets/rGO/Cu₂O (CGT(x)) photocatalytic system containing different quantities of reduced graphene oxide. In the first step, to synthesize the binary photocatalytic system, TNs/rGO (GT(x)), a simple one-step hydrothermal procedure, was applied for the growth of TiO₂ nanosheets on various amounts of multilayered graphene oxide, and then the Cu₂O semiconductor was loaded on GT(x) samples by the impregnation method to synthesize CGT(x) photocatalysts. In this method, graphene oxide (GO) could be well reduced to rGO under hydrothermal conditions. Diverse technical analyses such as XRD, UV–Vis DRS, TEM, FESEM/EDX, Raman spectroscopy and N₂ physisorption were employed to identify different features of the synthesized samples. Photocatalytic performance of the synthesized binary nanocomposites (GT(x)) and ternary nanocomposites (CGT(x)) was evaluated for the photodegradation of tetracycline (TC). To the best of the author's knowledge, the use of hydrothermal and impregnation methods to synthesize CGT(x) photocatalysts and study their efficiency for visible light degradation of tetracycline (TC) antibiotic has not been reported yet. In addition, some parameters such as photocatalyst dosage, initial concentration of TC, different amounts of rGO, existence of different scavengers and chemical oxidants on photodegradation of TC were investigated. Furthermore, in this study, a feed forward neural network with three layers and a backpropagation algorithm was applied to model and predict the photodegradation process. Effective parameters on the photocatalytic process such as illumination time, TC initial concentration, catalyst amount, APS concentration, and rGO amount were tested and optimized.