Comparative photocatalytic study of two selected pesticide derivatives, indole-3-acetic acid and indole-3-butyric acid in aqueous suspensions of titanium dioxide

Evaluation of machine learning models for predicting TiO2 photocatalytic degradation of air contaminants

The escalation of global urbanization and industrial expansion has resulted in an increase in the emission of harmful substances into the atmosphere. Evaluating the effectiveness of titanium dioxide (TiO2) in photocatalytic degradation through traditional methods is resource-intensive and complex due to the detailed photocatalyst structures and the wide range of contaminants. Therefore in this study, recent advancements in machine learning (ML) are used to offer data-driven approach using thirteen machine learning techniques namely XG Boost (XGB), decision tree (DT), lasso Regression (LR2), support vector regression (SVR), adaBoost (AB), voting Regressor (VR), CatBoost (CB), K-Nearest Neighbors (KNN), gradient boost (GB), random Forest (RF), artificial neural network (ANN), ridge regression (RR), linear regression (LR1) to address the problem of estimation of TiO2 photocatalytic degradation rate of air contaminants. The models are developed using literature data and different methodical tools are used to evaluate the developed ML models. XGB, DT and LR2 models have high R2 values of 0.93, 0.926 and 0.926 in training and 0.936, 0.924 and 0.924 in test phase. While ANN, RR and LR models have lowest R2 values of 0.70, 0.56 and 0.40 in training and 0.62, 0.63 and 0.31 in test phase respectively. XGB, DT and LR2 have low MAE and RMSE values of 0.450 min-1/cm2, 0.494 min-1/cm2 and 0.49 min-1/cm2 for RMSE and 0.263 min-1/cm2, 0.285 min-1/cm2 and 0.29 min-1/cm2 for MAE in test stage. XGB, DT, and LR2 have 93% percent errors within 20% error range in training phase. XGB has 92% and DT, and LR2 have 94% errors with 20% range in test phase. XGB, DT, LR2 models remained the highest performing models and XGB is the most robust and effective in predictions. Feature importances reveal the role of input parameters in prediction made by developed ML models. Dosage, humidity, UV light intensity remain important experimental factors. This study will impact positively in providing efficient models to estimate photocatalytic degradation rate of air contaminants using TiO2.

Photo-Antibacterial Activity of Two-Dimensional (2D)-Based Hybrid Materials: Effective Treatment Strategy for Controlling Bacterial Infection

Bacterial contamination in water bodies is a severe scourge that affects human health and causes mortality and morbidity. Researchers continue to develop next-generation materials for controlling bacterial infections from water. Photo-antibacterial activity continues to gain the interest of researchers due to its adequate, rapid, and antibiotic-free process. Photo-antibacterial materials do not have any side effects and have a minimal chance of developing bacterial resistance due to their rapid efficacy. Photocatalytic two-dimensional nanomaterials (2D-NMs) have great potential for the control of bacterial infection due to their exceptional properties, such as high surface area, tunable band gap, specific structure, and tunable surface functional groups. Moreover, the optical and electric properties of 2D-NMs might be tuned by creating heterojunctions or by the doping of metals/carbon/polymers, subsequently enhancing their photo-antibacterial ability. This review article focuses on the synthesis of 2D-NM-based hybrid materials, the effect of dopants in 2D-NMs, and their photo-antibacterial application. We also discuss how we could improve photo-antibacterials by using different strategies and the role of artificial intelligence (AI) in the photocatalyst and in the degradation of pollutants. Finally, we discuss was of improving the photo-antibacterial activity of 2D-NMs, the toxicity mechanism, and their challenges.

A Novel Machine Learning Model to Predict the Photo-Degradation Performance of Different Photocatalysts on a Variety of Water Contaminants

This paper describes an innovative machine learning (ML) model to predict the performance of different metal oxide photocatalysts on a wide range of contaminants. The molecular structures of metal oxide photocatalysts are encoded with a crystal graph convolution neural network (CGCNN). The structure of organic compounds is encoded via digital molecular fingerprints (MF). The encoded features of the photocatalysts and contaminants are input to an artificial neural network (ANN), named as CGCNN-MF-ANN model. The CGCNN-MF-ANN model has achieved a very good prediction of the photocatalytic degradation rate constants by different photocatalysts over a wide range of organic contaminants. The effects of the data training strategy on the ML model performance are compared. The effects of different factors on photocatalytic degradation performance are further evaluated by feature importance analyses. Examples are illustrated on the use of this novel ML model for optimal photocatalyst selection and for assessing other types of photocatalysts for different environmental applications.

CO2 reduction to acetic acid on the greigite Fe3S4{111} surface

Acetic acid (CH3-COOH) is an important commodity chemical widely used in a myriad of industrial processes, whose production still largely depends on homogeneous catalysts based on expensive rare metals. Here, we report a computational study on the formation of CH3-COOH from carbon dioxide (CO2) as an alternative chemical feedstock on the {111} surface of the low-cost greigite Fe3S4 catalyst. We have used density functional theory calculations with a Hubbard Hamiltonian approach and long-range dispersion corrections (DFT+U-D2) to simulate the various stages of the direct combination of C1 species of different composition to produce glyoxylic acid (CHO-COOH) as a key intermediate in the formation of CH3-COOH. Three reaction mechanisms are considered: (i) the main pathway where the direct formation of the C-C bond takes place spontaneously, followed by a step-wise reduction of CHO-CHOO to CH3-COOH; and the competitive pathways for the non-promoted and H-promoted elimination of hydroxy groups (OH) and water (H2O), respectively from (ii) the carboxyl; and (iii) the carbonyl end of the glyoxylate intermediates. The thermodynamic and kinetic profiles show that the energies for the intermediates on the main pathway are very similar for the two catalytic sites considered, although the activation energies are somewhat larger for the exposed tetrahedral iron (FeA) ion. In most cases, the intermediates for the deoxygenation of the carboxylic acid are less stable than the intermediates on the main pathway, which suggests that the molecule prefers to lose the carbonylic oxygen. The suitable surface properties of the Fe3S4{111} surface show that this material could be a promising sustainable catalyst in future technologies for the conversion of CO2 into organic acid molecules of commercial interest.

A generalized predictive model for TiO2-Catalyzed photo-degradation rate constants of water contaminants through artificial neural network

Titanium dioxide (TiO₂) is a well-known photocatalyst in the applications of water contaminant treatment. Traditionally, the kinetics of photo-degradation rates are obtained from experiments, which consumes enormous labor and experimental investments. Here, a generalized predictive model was developed for prediction of the photo-degradation rate constants of organic contaminants in the presence of TiO₂ nanoparticles and ultraviolet irradiation in aqueous solution. This model combines an artificial neural network (ANN) with a variety of factors that affect the photo-degradation performance, i.e., ultraviolet intensity, TiO₂ dosage, organic contaminant type and initial concentration in water, and initial pH of the solution. The molecular fingerprints (MF) were used to interpret the organic contaminants as binary vectors, a format that is machine-readable in computational linguistics. A dataset of 446 data points for training and testing was collected from the literature. This predictive model shows a good accuracy with a root mean square error (RMSE) of 0.173.

The unexpected concentration-dependent response of periphytic biofilm during indole acetic acid removal

Due to its extensive application in agriculture as a germinating agent and growth promoter, indole acetic acid (IAA) is present in a variety of aquatic ecosystems. To explore the response of microbial aggregates to exogenous IAA in aquatic ecosystems, periphytic biofilm, a typical microbial aggregate, was exposed to IAA at different concentrations. Results reveal an unexpected concentration-dependent effect of IAA on periphytic biofilm. Concentrations of IAA less than 10 mg/L inhibit periphytic growth, but stimulate growth when the IAA concentration exceeds 50 mg/L. Periphytic biofilm adapts to different IAA concentrations by antioxidant enzyme activation, community structure optimization and carbon-metabolism pattern change, and promotes bioremediation of IAA contaminated water in the process. The removal rates of IAA reached up to 95%-100%. This study reveals the capacity of periphytic biofilm for IAA removal in practice.

Photocatalytic degradation of yellow 2G dye using titanium dioxide/ultraviolet A light through a Box-Behnken experimental design: Optimization and kinetic study

Yellow 2G (Y2G), a type of anionic, synthetic monoazo dye that is widely used in household applications, textiles, and food industries, has been found to have cardiovascular and neurological effects on all living beings. In the present study, heterogeneous photocatalytic degradation of commercial Y2G was conducted using pure titanium dioxide (TiO₂) in a batch reactor system under ultraviolet A (UVA) light for 180 min. TiO₂ dosage, pH, and initial Y2G concentration were the three experimental parameters selected and studied to obtain preliminary information about the photocatalytic activities within a specified range. The Box-Behnken design method (BBD) was used to determine optimal values of the results using the above parameters of Y2G photocatalysis under response surface methodology (RSM). The optimum conditions were 0.914 g L^-1 TiO_2, pH 3.45, and an initial Y2G concentration of 20 mg L^-1. The Y2G degradation efficiency was 96.19% using a second-order polynomial equation with R² ≈ 0.999. The experimental results also showed that the photocatalytic process could be successfully explained using the modified Langmuir-Hinshelwood model, where k_c and K_LH were 0.787 mg L^-1 min and 0.010 L mg^-1, respectively.

Enhancement of nano titanium dioxide coatings by fullerene and polyhydroxy fullerene in the photocatalytic degradation of the herbicide mesotrione

The surface modification of commercial TiO₂ Hombikat (TiO₂) using nanoparticles of fullerene C₆₀ with tetrahydrofuran (THF-nC₆₀), as well as fullerenol C₆₀(OH)₂₄ nanoparticles (FNP) was investigated in this study. Characterization of THF-nC₆₀, FNP, TiO₂, TiO₂/THF-nC₆₀, and TiO₂/FNP was studied by using DES, ELS, TEM, SEM, DRS and BET measurements and their photoactivity has been examined on the mesotrione degradation under simulated sunlight. It was found that FNP in self-assembled nanocomposite TiO₂/FNP increased negatively charge, as well as catalytic surface of TiO₂. In addition, TiO₂/FNP exhibits a shift of band gap energy to lower values compared to TiO₂ and TiO₂/THF-nC₆₀. BET surface area has not showed significant differences among catalysts. Furthermore, it was found that the highest photoactivity was obtained for TiO₂/FNP system. Besides, influence of different concentrations of electron acceptors (H₂O₂ and KBrO₃), as well as scavengers on the kinetics of mesotrione removal in aqueous solution with/without TiO₂ and FNP under simulated sunlight was investigated. Namely, addition of mentioned electron acceptors has resulted in higher mesotrione degradation efficiency compared to O₂ alone. Besides, in the first period substrate degradation probably takes place via hydroxyl radicals and after 60 min of irradiation the reaction mechanism proceeds mainly via holes. The most efficient system for mesotrione degradation and mineralization were TiO₂/7 mM KBrO₃ and TiO₂/7 mM KBrO₃/40 μl FNP, respectively.

A chemiluminescence resonance energy transfer for the determination of indolyl acetic acid using luminescent nitrogen-doped carbon dots as acceptors

A CRET method was fabricated for the determination of IAA using Ce(iv)–Na₂SO₃ as the donor and N-CDs as the acceptor.

Photocatalytic pathway toward degradation of environmental pharmaceutical pollutants: structure, kinetics and mechanism approach

During the last few years, the presence of pharmaceuticals in the aquatic environment, classified as so-called emerging contaminants, has attracted attention from the scientific community.

Triplet state quenching of phenosafranine dye by indolic compounds studied by transient absorption spectroscopy

The interaction of the triplet state of the synthetic dye phenosafranine (3,7-diamino-5-phenylphenazinium chloride) with indolic compounds of biological relevance was investigated in water by means of laser flash photolysis.

Titanium Dioxide-Mediated Photcatalysed Degradation of Two Herbicide Derivatives Chloridazon and Metribuzin in Aqueous Suspensions

The aim of this paper is to find out the optimal degradation condition for two potential environmental pollutants, chloridazon and metribuzin (herbicide derivatives), employing advanced oxidation process using TiO2photocatalyst in aqueous suspensions. The degradation/mineralization of the herbicide was monitored by measuring the change in pollutant concentration and depletion in TOC content as a function of time. A detailed degradation kinetics was studied under different conditions such as types of TiO2(anatase/anatase-rutile mixture), catalyst concentration, herbicide concentration, initial reaction pH, and in the presence of electron acceptors (hydrogen peroxide, ammonium persulphate, potassium persulphate) in addition to atmospheric oxygen. The photocatalyst, Degussa P25, was found to be more efficient catalyst for the degradation of both herbicides as compared with two other commercially available TiO2powders like Hombikat UV100 and PC500. Chloridazon (CHL) was found to degrade more efficiently under acidic condition, whereas metribuzin (MET) degraded faster under alkaline medium. All three electron acceptors tested in this study were found to enhance the degradation rate of both herbicides.

Influence of parameters on the heterogeneous photocatalytic degradation of pesticides and phenolic contaminants in wastewater: a short review

In recent years, the application of heterogeneous photocatalytic water purification processes has gained wide attention due to its effectiveness in degrading and mineralizing the recalcitrant organic compounds as well as the possibility of utilizing the solar UV and visible-light spectrum. This paper aims to review and summarize the recent works on the titanium dioxide (TiO(2)) photocatalytic oxidation of pesticides and phenolic compounds, predominant in storm and wastewater effluents. The effects of various operating parameters on the photocatalytic degradation of pesticides and phenols are discussed. Results reported here suggest that the photocatalytic degradation of organic compounds depends on the type and composition of the photocatalyst and, light intensity, initial substrate concentration, amount of catalyst, pH of the reaction medium, ionic components in water, solvent types, oxidizing agents/electron acceptors, catalyst application mode, and calcination temperature in the water environment. A substantial amount of research has focused on the enhancement of TiO(2) photocatalysis by modification with metal, non-metal and ion doping. Recent developments in TiO(2) photocatalysis for the degradation of various pesticides and phenols are also highlighted in this review. It is evident from the literature survey that photocatalysis has good potential to remove a variety of organic pollutants. However, there is still a need to determine the practical utility of this technique on a commercial scale.

Studies on UV/NaOCl/TiO2/Sep photocatalysed degradation of Reactive Red 195

The photocatalytic degradation of Reactive Red 195 (RR195) has been investigated in aqueous suspensions by using ultraviolet (UV), sodium hypochlorite (NaOCl) and TiO(2)/Sep nanoparticles together. To get the TiO(2)/Sep nanoparticle, the nanocrystalline TiO(2) anatase phase on sepiolite was obtained using a sufficient thermal treatment by gradually increasing the temperature from 300, 400 and 500 degrees C for 3h. Then, TiO(2)/Sep materials were characterized using different spectral and technical structural analyses with scanning electron microscopy (SEM) and X-ray diffraction (XRD). The influence of pH, catalyst amount, oxidant and initial dye concentration was investigated in all the experiments. Maximum colour and chemical oxygen demand (COD) removal were 99.9% and 78% respectively, at a dye concentration of 250 mg L(-1), NaOCl dosage of 50.37 mM, 0.1 g L(-1) weight of TiO(2)/Sep and pH of 5.45 in 3h. In addition, the pseudo-first order model was applied and r(2) values were noted from 0.92 to 0.99.

Removal of AOX, total nitrogen and chlorinated lignin from bleached Kraft mill effluents by UV oxidation in the presence of hydrogen peroxide utilizing TiO(2) as photocatalyst

BACKGROUND, AIM, AND SCOPE

The pulp and paper industry is the sixth largest polluter discharging a variety of gaseous, liquid, and solid wastes into the environment. Effluents from bleached Kraft mill effluents (BKME) are polluting waters to a great extent These effluents cause considerable damage to the receiving waters if discharged untreated since they have high levels of biological oxygen demand (BOD), chemical oxygen demand (COD), chlorinated compounds (measured as AOX), suspended solids (mainly fibers), fatty acids, tannins, resin acids, lignin and its derivatives, sulfur and sulfur compounds, etc. This study aimed to remove adsorbed organic halogen (AOX), total nitrogen, and lignin-degrading products in the wastewater (4,500 m(3)/h) from the paper mill in the pulp and paper industry, which is discharged to sea from a plant located in western Turkey.

MATERIALS AND METHODS

The photocatalytic degradation of AOX, total nitrogen, and chlorinated lignin in BKME have been investigated in different parameters, such as time, H(2)O(2) and TiO(2) concentration. In addition, for investigating the effect of chlorine on the removal of lignin, pure lignin solution was prepared in equal amounts to chlorinated lignin degradation products found in BKME. The same experiments were conducted for this solution. Experiments were carried out in photocatalytic reactor made of Pyrex glass. The mercury lamp was used as a radiation source. All irradiation was carried out under constant stirring. The existence of dissolved O(2) is an important factor which increases the photocatalytic degradation. Hence, we used an air pump for the aeration of the wastewater solutions. The temperature of the wastewater was controlled and adjusted to 25 degrees C by thermostat pump in conjunction with a cooler. At the end of all experiments, AOX, total nitrogen and lignin concentrations were analyzed according to standard methods. All experiments were performed in duplicate and average values were used.

RESULTS AND DISCUSSION

When the effect of H(2)O(2) and time were investigated, it was observed that the AOX concentration increased from 3.0 to 11.0 mg/L by only UV. However, when H(2)O(2) was added, AOX concentration decreased from approximately 3.0 to 0.0 mg/L. The optimal conditions for the removal of AOX appear to be an initial H(2)O(2) concentration of 20.0 mL/L and reaction time of 50 min. In addition, at the same experiment conditions, it was seen that the total nitrogen concentration decreased from 23.0 to 15.0 mg/L by only UV and by increasing H(2)O(2) concentration, the concentration of 20.0 mL/L H(2)O(2) appears to be optimal (9.0 mg/L). The AOX, total nitrogen and lignin degradation products and pure lignin go through a minimum when the concentration of H(2)O(2) and TiO(2) increases at constant pH and UV intensity. The kinetics for the degradation of AOX, total nitrogen and lignin degradation products followed a pseudo-first order law with respect to the products, and the degradation rates (min(-1)) for the UV/TiO(2)/H(2)O(2) system were higher than that of the corresponding values for the UV/H(2)O(2) system.

CONCLUSIONS

The AOX, total nitrogen and lignin concentration go through a minimum when the concentration of H(2)O(2) and TiO(2) increases at constant pH and UV intensity. It was found that the UV/TiO(2)/H(2)O(2) system has proved capable of the degradation of total nitrogen as well as chlorinated and degraded lignin in BKME.

RECOMMENDATIONS AND PERSPECTIVES

The photocatalytic process can be considered a suitable alternative for the remove of some compounds from the BKME. Nevertheless, further studies should be carried out to confirm the practical feasibility of BKME. Another result obtained from the study is that pre-purification carried out with UV/TiO(2)/H(2)O(2) photocatalytic process may constitute an important step for further purification processes such as adsorption, membrane processes, etc.

Heterogeneous photocatalytic degradation of monochlorobenzene in water

This investigation evaluated the photocatalytic degradation of monochlorobenzene (MCB) in an aqueous TiO(2) suspension. In accordance with the experimental results, the degradation of MCB was a function of the initial substrate concentration, incident light intensity, and TiO(2) dosage. However, the solution pH had insignificant effect on the degradation efficiency. The heterogeneous photocatalytic degradation of MCB followed the Langmuir-Hinshelwood kinetics. The adsorption coefficient of MCB (K) and the observed degradation rate constant (k) were calculated as 13.4 mM(-1) and 0.0054 mM min(-1), respectively. In addition, a 0.255 dependency of the initial degradation rate on the light intensity revealed the considerable adverse effect of e(-)-h(+) pair recombination. Both mineralization and dechlorination occurred during the photocatalytic degradation of MCB. Under the operating condition of initial MCB concentration of 0.1mM, light intensity of 5.68 microEinsteins(-1), TiO(2) dosage of 1.0 g L(-1), and solution pH of 7, about 93.7% of MCB was mineralized after 240 min of irradiation. Nevertheless, 64.3% of the stoichiometric amount of Cl(-) ions was released into the bulk solution. The simulation results derived from the X-ray photoelectron spectroscopy (XPS) analysis was suggested that the interaction between Cl(-) ions and TiO(2) surface tended to lower the released amount of Cl(-) ions.

Photocatalytic ozonation of phenolic wastewaters: Syringic acid, tyrosol and gallic acid

The photocatalytic ozonation of a mixture of 3 phenols (gallic acid, tyrosol and syringic acid) has been conducted under different operating conditions. The individual adsorption of the phenol type compounds onto titanium dioxide (photocatalyst) has been first evaluated. Equilibrium conditions are attained in less than an hour while the isotherm curves reveal that adsorption intensity increases in order: syringic acid < tyrosol < gallic acid. When the photocatalytic ozonation is applied, an optimum in titanium dioxide concentration is experienced (1.5 g L(-1)). Direct comparison of the photocatalytic ozonation to other less sophisticated oxidation systems (i.e., single ozonation, catalytic ozonation, photo-ozonation, etc.) indicates a higher efficiency of the former in terms of ozone uptake.