Sensitivity analysis of the photoactivity of Cu–TiO2/ZnO during advanced oxidation reaction by Adaptive Neuro-Fuzzy Selection Technique

Khaki, Mohammad Reza Delsouz; Sajjadi, Baharak; Raman, Abdul Aziz Abdul; Daud, Wan Mohd Ashri Wan; Shmshirband, Shahaboddin

doi:10.1016/j.measurement.2015.07.004

Cited by 24 publications

(4 citation statements)

References 45 publications

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“…The differences in UV intensity between the UV lamp and UV radiation from the sunlight during the photocatalytic assays, 281 W/m 2 from UV lamps and 894 W/m 2 under sunlight radiation, explain the differences in degradation efficiencies. The results show that larger intensities lead to improved degradation efficiencies due to the activation of a higher number of electron/hole pairs [39]. This relationship is consistent with previous studies using TiO2 for photocatalytic applications under sunlight irradiation [16,69].…”

Section: Photocatalytic Degradation Of Metronidazolesupporting

confidence: 91%

“…In this context, an adaptive neuro-fuzzy inference system (ANFIS) allows for the prediction of water quality parameters, as has been previously demonstrated [37,38]. Additionally, the application of an ANFIS model has been reported to evaluate wastewater treatment processes, namely in the elimination of organic dyes [39,40], oily wastewater [41], chemical additives [36], antibiotics [42] and heavy metals [43,44].…”

Section: Introductionmentioning

confidence: 92%

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Reusable Ag@TiO2-Based Photocatalytic Nanocomposite Membranes for Solar Degradation of Contaminants of Emerging Concern

et al. 2021

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Two significant limitations of using TiO2 nanoparticles for water treatment applications are reduced photocatalytic activity under visible radiation and difficulty recovering the particles after use. In this study, round-shaped Ag@TiO2 nanocomposites with a ≈21 nm diameter and a bandgap energy of 2.8 eV were synthesised by a deposition-precipitation method. These nanocomposites were immobilised into a porous poly (vinylidene fluoride-hexafluoropropylene) (PVDF-HFP) matrix and well-distributed within the pores. The photocatalytic activity of Ag@TiO2/PVDF-HFP against metronidazole (MNZ) under solar radiation was evaluated. Further, an adaptive neuro-fuzzy inference system (ANFIS) was applied to predict the effect of four independent variables, including initial pollutant concentration, pH, light irradiation intensity, and reaction time, on the photocatalytic performance of the composite membrane on MNZ degradation. The 10% Ag@TiO2/PVDF-HFP composite membrane showed a maximum removal efficiency of 100% after 5 h under solar radiation. After three use cycles, this efficiency remained practically constant, demonstrating the membranes’ reusability and suitability for water remediation applications.

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Section: Photocatalytic Degradation Of Metronidazolesupporting

confidence: 91%

Section: Introductionmentioning

confidence: 92%

Reusable Ag@TiO2-Based Photocatalytic Nanocomposite Membranes for Solar Degradation of Contaminants of Emerging Concern

et al. 2021

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“…In the TiO 2 semiconductors, the potential energy levels of the conduction and valance band of TiO 2 and ZnO lie above the CuOcb and CuOvb levels. Accordingly, the ultraviolet irradiation induces both the e − transfer and h + transfer from TiO 2 and ZnO to CuO [21]. The combination of TiO 2 with the doped metallic oxide results in the generation of Ti 3+ .…”

Section: Characterization Of Photocatalystsmentioning

confidence: 99%

Effects of metal ion-doping on the characteristics and photocatalytic activities of TiO<sub>2</sub> nanotubes

Wang¹

2018

Funct.Mater.

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Ion-doped TiO 2 nanotubes were synthesized via a hydrothermal method and characterized by transmission electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy and specific surface areas. The binding energies of Cu 2+ , V 2+ , and Zn 2+ indicated that the doping ions existed as Cu 2+ , V 5+ , and Zn 2+ , respectively. With the increase of the calcination temperature, the intensity of the anatase phase decreased and the BET surface area decreased. The extent of anatase phase increased with the increasing the calcination temperature, and then decreased. The highest catalytic activity for the un-doped TiO 2 nanotubes was observed at a calcination temperature of 500 °C, with a Rhodamine B (RB) removal efficiency of 98.1%. The removal efficiency of RB was 98.2% when Cu 2+-doped catalyst calcined at 450 °C was added, 0.1% higher than the un-doped TiO 2 nanotubes. The highest photocatalytic activity was obtained in the presence of Zn 2+-doped catalyst calcined at 550 °C, where 98.7% of RB was removed.

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“…Despite the impact of ANFIS, ANFIS-GA, and ANFIS-PSO models, they are not used widely in modeling the physical properties. There are not enough studies on this concern [32][33][34][35].…”

Section: Introductionmentioning

confidence: 99%

Modeling the electrical properties of heterojunctions using ANFIS, ANFIS-GA and ANFIS-PSO Models

Mohamed

2023

Phys. Scr.

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The present research introduces a theoretical study that aims to utilize ANFIS in estimating and predicting the electrical behavior of heterojunctions. For this purpose, five different heterojunctions were chosen. The experimental datasets that represent the electrical behavior of the chosen heterojunctions were extracted and employed in ANFIS as targets. To enhance the ANFIS performance two hybrid heuristic algorithms, genetic algorithm (GAs) and particle swarm optimization (PSO) were combined with ANFIS. The major contribution of the current research is to predict the electric characteristics of heterojunctions using ANFIS and increase the modeling accuracy of ANFIS by optimizing the premise and consequent parameters using (GAs) and (PSO). Also, compare the proportion of enhancement produced by using ANFIS-GA and ANFIS-PSO to decide which of them is more powerful under the study conditions. However, to the author’s knowledge, the presented goals have not been investigated before for heterojunctions. The mean squared error (MSE), the correlation coefficient (R2), and the standard deviation error (Std. error) were calculated for all trained models. The modeling errors of ANFIS-GA and ANFIS-PSO were compared to the error values produced by ANFIS. According to modeling results, simulation ANFIS outputs follow the experimental data patterns in excellent response. Predictions of electrical characteristics for heterojunctions using the trained models provide acceptable results where the MSE values obtained by training ANFIS-PSO are lower than their values obtained by ANFIS and ANFIS-GA models. The improvements in average percentages in ANFIS performance when combined with GA and PSO are equal to 2.2% and 3%, respectively. Consequently, the proposed ANFIS-PSO model is more accurate in predicting the electrical behavior of heterojunctions under the study conditions.

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Sensitivity analysis of the photoactivity of Cu–TiO2/ZnO during advanced oxidation reaction by Adaptive Neuro-Fuzzy Selection Technique

Cited by 24 publications

References 45 publications

Reusable Ag@TiO2-Based Photocatalytic Nanocomposite Membranes for Solar Degradation of Contaminants of Emerging Concern

Reusable Ag@TiO2-Based Photocatalytic Nanocomposite Membranes for Solar Degradation of Contaminants of Emerging Concern

Effects of metal ion-doping on the characteristics and photocatalytic activities of TiO<sub>2</sub> nanotubes

Modeling the electrical properties of heterojunctions using ANFIS, ANFIS-GA and ANFIS-PSO Models

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