Modeling and optimization of photocatalytic/photoassisted-electro-Fenton like degradation of phenol using a neural network coupled with genetic algorithm

Sustainable degradation of pollutants, generation of electricity and hydrogen evolution via photocatalytic fuel cells: An Inclusive Review

Environmental pollution and energy crisis have recently become one of the major global concerns. Insincere discharge of massive amount of organic and inorganic wastes into the aqueous bodies causes serious impact on our environment. However, these organic substances are significant sources of carbon and energy that could be sustainably utilized rather than being discarded. Photocatalytic fuel cell (PFC) is a smart and novel energy conversion device that has the ability to achieve dual benefits: degrading the organic contaminants and simultaneously generating electricity, thereby helping in environmental remediation. This article presents a detailed study of the recent advancements in the development of PFC systems and focuses on the fundamental working principles of PFCs. The degradation of various common organic and inorganic contaminants including dyes and antibiotics with simultaneous power generation and hydrogen evolution has been outlined. The impact of various operational factors on the PFC activity has also been briefly discussed. Moreover, it provides an overview of the design guidelines of the different PFC systems that has been developed recently. It also includes a mention of the materials employed for the construction of the photo electrodes and highlights the major limitations and relevant research scopes that are anticipated to be of interest in the days to come. The review is intended to serve as a handy resource for researchers and budding scientists opting to work in this area of PFC devices.

Efficient degradation of 2,4-dichlorophenol in water by sequential electrocatalytic reduction and oxidation with a Pd-MWCNTs/Ni-foam electrode

Our previous study indicated excellent dechlorination efficiency and phenol conversion rate in the electrocatalytic reduction of 2,4-dichlorophenol (2,4-DCP) with a Pd-MWCNTs/Ni-foam electrode; it is deserved to investigate whether this electrode can efficiently degrade phenol in electro-Fenton oxidation (EFO) process and realize the effective mineralization of 2,4-DCP in aqueous solution. In this work, the sequential electrocatalytic reduction and oxidation of 2,4-DCP were studied after examining phenol degradation in the EFO process. The results showed that the removal efficiency of 0.31 mM phenol could reach 96.76% after 90-min degradation with the rate constant of 0.0367 min^-1, and hydroxy radicals (·OH) were the main active species in the EFO process. In the sequential electrocatalytic reduction and oxidation processes, the removal efficiencies of 2,4-DCP, phenol, and total organic carbon (TOC) reached 99.72%, 97.07%, and 61.45%, respectively. The possible degradation mechanism of 2,4-DCP was proposed through monitoring the reaction products, and the stability and reusability of the electrode were also examined. This study suggested that 2,4-DCP in wastewater can be effectively mineralized to realize its efficient degradation through the sequential electrocatalytic reduction and oxidation.

Response surface methodology and artificial neural network for remediation of acid orange 7 using TiO2-P25: optimization and modeling approach

The primary responsibility for continuously discharging toxic organic pollutants into water bodies and open environments is the increase in industrial and agricultural activities. Developing economical and suitable methods to continuously remove organic pollutants from wastewater is highly essential. The aim of the present research was to apply response surface methodology (RSM) and artificial neural networks (ANNs) for optimization and modeling of photocatalytic degradation of acid orange 7 (AO7) by commercial TiO2-P25 nanoparticles (TNPs). Dose of TNPs, pH, and AO7 concentration were selected as investigated parameters. RSM results reveal the reflective rate of AO7 removal of ~ 94.974% was obtained at pH 7.599, TNP dose of 0.748 g/L, and AO7 concentration of 28.483 mg/L. The resulting quadratic model is satisfactory with the highest coefficient of determination (R2) between the predicted and experimental data (R2 = 0.98 and adjusted R2 = 0.954). On the other hand, ANNs were successfully employed for modeling of AO7 degradation process. The proposed ANN model was absolutely fitted with experimental results producing the highest R2. Furthermore, root mean square error (RMSE), mean average deviation (MAD), absolute average relative error (AARE), and mean square error (MSE) were examined more to compare the predictive capabilities of ANN and RSM models. The experimental data was well fitted into pseudo-first-order and pseudo-second-order kinetics with more accuracy. Thermodynamic parameters, namely enthalpy, entropy, Gibbs' free energy, and activation energy, were also evaluated to suggest the nature of the degradation process. The increase of temperature was analyzed to be more suitable for the fast removal of AO7 over TNPs. Graphical abstract.

Modeling the degradation and disinfection of water pollutants by photocatalysts and composites: A critical review

Recently, a series of new photocatalysts have been developed for to combat diverse bio-recalcitrant contaminants and the inactivation of bacteria. Modeling photocatalytic processes is important to assess these materials, and to understand and optimize their performance. In this study, the recent literature is critically reviewed and analyzed to identify and compare methods of modeling photocatalytic performance. The Langmuir-Hinshelwood model (L-H) has been used in many studies to rationalize the degradation kinetics of single contaminants because it is the simplest model including both the adsorption equilibrium and degradation rates. Other studies report the development of more sophisticated variants of the L-H model that include the rates of catalyst excitation, recombination of electron-hole pairs, production of reactive oxygen species (ROS), and formation of by-products. Modified Chick-Watson (CW) and Hom models have been used by many researchers to include lag phases of bacteria in the description of disinfection kinetics. Artificial neural networks (ANNs) have been used to analyze the effects of operational conditions on photocatalyst performance. Moreover, response surface methodology (RSM) has been employed for experimental design, and optimization of operational conditions. We have reviewed and analyzed all available articles that model photocatalytic activity towards water pollution, summarized and put them in context, and recommended future research directions.

Partial-Redox-Promoted Mn Cycling of Mn(II)-Doped Heterogeneous Catalyst for Efficient H2O2-Mediated Oxidation

The development of a heterogeneous catalyst with high catalytic activity and durability for H₂O₂-mediated oxidation is one of the most important industrial and environmental issues. In this study, a Mn(II)-doped TiO₂ heterogeneous catalyst was developed for H₂O₂-mediated oxidation. The TiO₂ substrate-dependent partial-redox behavior of Mn was identified on the basis of our density functional theory simulations. This unique redox cycle was induced by a moderate electron transfer from Ti to Mn, which compensated for the electron loss of Mn and finally resulted in a high-efficiency cycling of Mn between its oxidized and reduced forms. In light of the theoretical results, a Mn(II)-doped TiO₂ composite with well-defined morphology and large surface area (153.3 m² g^-1) was elaborately fabricated through incorporating Mn(II) ions into a TiO₂ nanoflower, and further tested as the catalyst for oxidative degradation of organic pollutants in the presence of H₂O₂. Benefiting from the remarkable textural features and excellent Mn cycling property, this composite exhibited superior catalytic performance for organic pollutant degradation. Moreover, it could retain 98.40% of its initial activity even in the fifth cycle. Our study provides an effective strategy for designing heterogeneous catalytic systems for H₂O₂-mediated oxidations.

Development of an empirical kinetic model for sonocatalytic process using neodymium doped zinc oxide nanoparticles

The degradation of Acid Blue 92 (AB92) solution was investigated using a sonocatalytic process with pure and neodymium (Nd)-doped ZnO nanoparticles. The nanoparticles were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS). The 1% Nd-doped ZnO nanoparticles demonstrated the highest sonocatalytic activity for the treatment of AB92 (10 mg/L) with a degradation efficiency (DE%) of 86.20% compared to pure ZnO (62.92%) and sonication (45.73%) after 150 min. The results reveal that the sonocatalytic degradation followed pseudo-first order kinetics. An empirical kinetic model was developed using nonlinear regression analysis to estimate the pseudo-first-order rate constant (kapp) as a function of the operational parameters, including the initial dye concentration (5-25 mg/L), doped-catalyst dosage (0.25-1 g/L), ultrasonic power (150-400 W), and dopant content (1-6% mol). The results from the kinetic model were consistent with the experimental results (R(2)=0.990). Moreover, DE% increases with addition of potassium periodate, peroxydisulfate, and hydrogen peroxide as radical enhancers by generating more free radicals. However, the addition of chloride, carbonate, sulfate, and t-butanol as radical scavengers declines DE%. Suitable reusability of the doped sonocatalyst was proven for several consecutive runs. Some of the produced intermediates were also detected by GC-MS analysis. The phytotoxicity test using Lemna minor (L. minor) plant confirmed the considerable toxicity removal of the AB92 solution after treatment process.

Sonocatalytic degradation of Acid Blue 92 using sonochemically prepared samarium doped zinc oxide nanostructures

Pure and Sm-doped ZnO nanoparticles were synthesized applying a simple sonochemical method. The nanocatalysts were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS) techniques which confirmed the successful synthesis of the doped sonocatalyst. The sonocatalytic degradation of Acid Blue 92 (AB92), a model azo dye, was more than that with sonolysis alone. The 6% Sm-doped ZnO nanoparticles had a band gap of 2.8 eV and demonstrated the highest activity. The degradation efficiency (DE%) of sonolysis and sonocatalysis with undoped ZnO and 6% Sm-doped ZnO was 45.73%, 63.9%, and 90.10%, after 150 min of treatment, respectively. Sonocatalytic degradation of AB92 is enhanced with increasing the dopant amount and catalyst dosage and with decreasing the initial AB29 concentration. DE% declines with the addition of radical scavengers such as chloride, carbonate, sulfate, and tert-butanol. However, the addition of enhancers including potassium periodates, peroxydisulfate, and hydrogen peroxide improves DE% by producing more free radicals. The results show adequate reusability of the doped sonocatalyst. Degradation intermediates were recognized by gas chromatography-mass spectrometry (GC-MS). Using nonlinear regression analysis, an empirical kinetic model was developed to estimate the pseudo-first-order constants (kapp) as a function of the main operational parameters, including the initial dye concentration, sonocatalyst dosage, and ultrasonic power.

Kinetic modeling of nalidixic acid degradation by clinoptilolite nanorod-catalyzed ozonation process

The removal of nalidixic acid (NAD) through the clinoptilolite nanorod (CN)-catalyzed ozonation process was modeled by three types of kinetic approaches.