Efficacy of spent tea waste as chemically impregnated adsorbent involving ortho-phosphoric and sulphuric acid for abatement of aqueous phenol-isotherm, kinetics and artificial neural network modelling

Predictive modeling for the adsorptive and photocatalytic removal of phenolic contaminants from water using artificial neural networks

Numerous harmful phenolic contaminants are discharged into water that pose a serious threat to environment where two of the most important purification methodologies for the mitigation of phenolic contaminants are adsorption and photocatalysis. Besides cost, each process has drawbacks in terms of productivity, environmental impact, sludge creation, and the development of harmful by-products. To overcome these limitations, the modeling and optimization of water treatment methods is required. Artificial Intelligence (AI) is employed for the interpretation of treatment-based processes due to powerful learning, simplicity, high estimation accuracy, effectiveness, and improvement of process efficiency where artificial neural networks (ANNs) are most frequently employed for predicting and analyzing the efficiency of processes applied for the mitigation of these phenolic contaminants from water. ANNs are superior to conventional linear regression models because the latter are incapable of dealing with non-linear systems. ANNs can also reduce the operational cost of treating phenol-contaminated water. A correlation coefficient of >0.99 can be achieved using ANN with enhanced phenol mitigation percentage accuracy generally ranging from 80 % to 99.99 %. Using ANN optimization, the maximum phenol mitigation efficiencies achieved were 99.99 % for phenol, 99.93 % for bisphenol A, 99.6 % for nonylphenol, 97.1 % for 2-nitrophenol, 96.6 % for 4-chlorophenol and 90 % for 2,6-dichlorophenol. In numerous ANN models, Levenberg-Marquardt backpropagation algorithm for training was employed using MATLAB software. This study overviews their employment and application for optimization and modeling of removal processes and explicitly discusses the important input and output parameters necessary for better performance of the system. The comparison of ANNs with other AI techniques revealed that ANNs have better predictability for mitigation of most of the phenolic contaminants. Furthermore, several challenges and future prospects have also been discussed.

Insights into kinetics, thermodynamics, and mechanisms of chemically activated sunflower stem biochar for removal of phenol and bisphenol-A from wastewater

This study synthesized a highly efficient KOH-treated sunflower stem activated carbon (KOH-SSAC) using a two-step pyrolysis process and chemical activation using KOH. The resulting material exhibited exceptional properties, such as a high specific surface area (452 m2/g) and excellent adsorption capacities for phenol (333.03 mg/g) and bisphenol A (BPA) (365.81 mg/g). The adsorption process was spontaneous and exothermic, benefiting from the synergistic effects of hydrogen bonding, electrostatic attraction, and stacking interactions. Comparative analysis also showed that KOH-SSAC performed approximately twice as well as sunflower stem biochar (SSB), indicating its potential for water treatment and pollutant removal applications. The study suggests the exploration of optimization strategies to further enhance the efficiency of KOH-SSAC in large-scale scenarios. These findings contribute to the development of improved materials for efficient water treatment and pollution control.

Effective utilization of discarded reverse osmosis post-carbon for adsorption of dyes from wastewater

In this study, the deployment of post Reverse Osmosis (RO)-carbon as a adsorbent for dye removal from water has been investigated. The post RO-carbon was thermally activated (RO900), and the material thus obtained exhibited high surface area viz. 753 m2/g. In the batch system, the efficient Methylene Blue (MB) and Methyl Orange (MO) removal was obtained by using 0.08 g and 0.13 g/50 mL adsorbent dosage respectively. Moreover, 420 min was the optimized equilibration time for both the dyes. The maximum adsorption capacities of RO900 for MB and MO dyes were 223.29 and 158.14 mg/g, respectively. The comparatively higher MB adsorption was attributed to the electrostatic attraction between adsorbent and MB. The thermodynamic findings revealed the process as spontaneous, endothermic, and accompanied by entropy increment. Additionally, simulated effluent was treated, and >99% dye removal efficiency was achieved. To mimic an industrial perspective, MB adsorption onto RO900 was also carried out in continuous mode. The initial dye concentration and effluent flow rate were among the process parameters that were optimized using the continuous mode of operation. Further, the experimental data of continuous mode was fitted with Clark, Yan, and Yoon-Nelson models. Py-GC/MS investigation revealed that dye-loaded adsorbents could be pyrolyzed to produce valuable chemicals. The cost and low toxicity associated benefits of discarded RO-carbon over other adsorbents reveal the significance of the present study.

Thymol@activated Carbon Nanohybrid for Low-Density Polyethylene-Based Active Packaging Films for Pork Fillets' Shelf-Life Extension

Τhe replacement of food packaging additives and preservatives with bio-based antioxidant/antibacterial compounds has been a common practice in recent years following the trend of bioeconomy and nanotechnology. Such bio-additives are often enclosed in nanocarriers for a controlled release process. Following this trend in this work, a thymol (TO)-rich activated carbon (AC) nanohybrid was prepared and characterized physicochemically with various techniques. This TO@AC nanohybrid, along with the pure activated carbon, was extruded with low-density polyethylene (LDPE) to develop novel active packaging films. The codenames used in this paper were LDPE/xTO@AC and LDPE/xAC for the nanohybrid and the pure activated carbon, respectively. X-ray diffractometry, Fourier-transform infrared spectroscopy, and scanning electron microscopy measurements showed high dispersity of both the TO@AC nanohybrid and the pure AC in the LDPE matrix, resulting in enhanced mechanical properties. The active film with 15 wt.% of the TO@AC nanohybrid (LDPE/15TO@AC) exhibited a 230% higher water/vapor barrier and 1928% lower oxygen permeability than the pure LDPE film. For this active film, the highest antioxidant activity referred to the DPPH assay (44.4%), the lowest thymol release rate (k₂ ≈ 1.5 s^-1), and the highest antibacterial activity were recorded, resulting in a 2-day extension of fresh pork fillets' shelf-life.

Black Tea Waste as Green Adsorbent for Nitrate Removal from Aqueous Solutions

The aim of the study was to prepare effective low-cost green adsorbents based on spent black tea leaves for the removal of nitrate ions from aqueous solutions. These adsorbents were obtained either by thermally treating spent tea to produce biochar (UBT-TT), or by employing the untreated tea waste (UBT) to obtain convenient bio-sorbents. The adsorbents were characterized before and after adsorption by Scanning Electron Microscopy (SEM), Energy Dispersed X-ray analysis (EDX), Infrared Spectroscopy (FTIR), and Thermal Gravimetric Analysis (TGA). The experimental conditions, such as pH, temperature, and nitrate ions concentration were studied to evaluate the interaction of nitrates with adsorbents and the potential of the adsorbents for the nitrate removal from synthetic solutions. The Langmuir, Freundlich and Temkin isotherms were applied to derive the adsorption parameters based on the obtained data. The maximum adsorption intakes for UBT and UBT-TT were 59.44 mg/g and 61.425 mg/g, respectively. The data obtained from this study were best fitted to the Freundlich adsorption isotherm applied to equilibrium (the values R² = 0.9431 for UBT and R² = 0.9414 for UBT-TT), this assuming the multi-layer adsorption onto a surface with a finite number of sites. The Freundlich isotherm model could explain the adsorption mechanism. These results indicated that UBT and UBT-TT could serve as novel biowaste and low-cost materials for the removal of nitrate ions from aqueous solutions.

Agricultural waste materials for adsorptive removal of phenols, chromium (VI) and cadmium (II) from wastewater: A review

Management of basic natural resources and the spent industrial and domestic streams to provide a sustainable safe environment for healthy living is a magnum challenge to scientists and environmentalists. The present remedial approach to the wastewater focuses on recovering pure water for reuse and converting the contaminants into a solid matrix for permanent land disposal. However, the ground water aquifers, over a long period slowly leach the contaminants consequently polluting the ground water. Synthetic adsorbents, mainly consisting of polymeric resins, chelating agents, etc. are efficient and have high specificity, but ultimate disposal is a challenge as most of these materials are non-biodegradable. In this context, it is felt appropriate to review the utility of adsorbents based on natural green materials such as agricultural waste and restricted to few model contaminants: phenols, and heavy metals chromium(VI), and cadmium(II) in view of the vast amount of literature available. The article discusses the features of the agricultural waste material-based adsorbents including the mechanism. It is inferred that agricultural waste materials are some of the common renewable sources available across the globe and can be used as sustainable adsorbents. A discussion on challenges for industrial scale implementation and integration with advanced technologies like magnetic-based approaches and nanotechnology to improve the removal efficiency is included for future prospects.

Removal of Anionic and Cationic Dyes from Wastewater Using Activated Carbon from Palm Tree Fiber Waste

This study focuses on using a facile method for the green preparation of activated carbon (AC) from palm tree fiber (PTF) waste. The synthesized cost-effective AC was investigated for the removal of an anionic dye (Congo red, CR) and a cationic dye (Rhodamine B, RhB) from wastewater. The morphological and structural characterization of the synthesized AC were performed by scanning electron microscopy (SEM), transmission electron microscopy (TEM), surface area, Fourier transform infrared spectroscopy (FTIR), total pore volume, average pore diameter and pore size distribution, zeta potential, and zero-point charge. To investigate the adsorption efficiency, different parameters such as adsorbent dosage, solution pH, initial dye concentration, and duration were applied using the batch experiments. Various adsorption isotherm and kinetics models were applied to study the adsorption mechanism and dynamics. The results showed that chemical activation with a weak acid (H3PO4) at 400 °C for 30 min is a fast method for the activation of each precursor and produces a high yield. The result of analysis showed an increase in the adsorption capacity at pH 2. The maximum adsorption capacity was 9.79 and 26.58 mg g−1 at 30 min for CR dye and RhB dye, respectively. The optimum adsorbent dosage for the activated carbon from palm tree fiber (PTFAC) was 0.15 g with a high percentage removal of CR (98.24%) and RhB (99.86%) dyes. The adsorption isotherm and kinetic studies were found to be favorable and feasible for assessing the adsorption of dyes with the Langmuir model and pseudo-second-order reaction, respectively. In addition, the AC showed reusability up to five cycles. The results showed that the synthesized AC was environmentally friendly and successfully removed dyes from wastewater.

Artificial neural network modeling for Congo red adsorption on microwave-synthesized akaganeite nanoparticles: optimization, kinetics, mechanism, and thermodynamics

This work aims to synthesize akaganeite nanoparticles (AKNPs) by using microwave and use them to adsorb Congo red dye (CR) from the aqueous solution. The AKNPs with an average particle size of about 50 nm in width and 100 nm in length could be fabricated in 20 min. The effects of pH, CR initial concentration, adsorption time, and adsorbent dosage on the adsorption process were investigated and the artificial neural network (ANN) was used to analyze the adsorption data. The various ANN structures were examined in training the data to find the optimal model. The structure with training function, TRAINLM; adaptation learning function, LARNGDM; transfer function, LOGSIG (in hidden layer) and PURELIN (in output layer); and 10 neutrons in hidden layer having the highest correlation (R² = 0.996) and the lowest MSE (4.405) is the optimal ANN structure. The consistency between the experimental data and the data predicted by the ANN model showed that the behavior of the adsorption process of CR onto AKNPs under different conditions can be estimated by the ANN model. The adsorption kinetics was studied by fitting the data into pseudo-first-order, pseudo-second-order, Elovich, and intraparticle diffusion models. The results showed that the adsorption kinetics obeyed the pseudo-second-order model and governed by several steps. The adsorption isotherms at the different temperatures were studied by fitting the data to Langmuir, Freundlich, and Temkin isotherm models. The R² obtained from the Langmuir model was above 0.9 and the highest value in three of four temperatures, suggesting that the adsorption isotherms were the best fit to the Langmuir model and the maximum adsorption capacity was estimated to be more than 150 mg/g. Thermodynamic studies suggested that the adsorption of CR onto AKNPs was a spontaneous and endothermic process and physicochemical adsorption. The obtained results indicated the potential application of microwave-synthesize AKNPs for removing organic dyes from aqueous solutions.

Facile Synthesis of Cauliflower Leaves Biochar at Low Temperature in the Air Atmosphere for Cu(II) and Pb(II) Removal from Water

In this study, a facile and low-cost method for biochar (CLB) preparation from vegetable waste (cauliflower leaves) was developed at a low temperature (120 °C) in the air atmosphere. The prepared mechanism, adsorption mechanism, and performance of CLB for Cu(II) and Pb(II) sorption were investigated using Scanning electron microscopy- energy dispersive X-ray spectroscopy(SEM-EDS), X-ray diffraction(XRD), Fourier transform infrared spectroscopy(FTIR), and a series of sorption experiments. Then the CLB was subjected to single and double element sorption studies to examine the effect of pH value on the Cu(II)/Pb(II) sorption capacities and then competitive sorption priority. There are both more hydroxyl (–OH) and carboxyl (–COOH) functional groups on the surface of CLB compared to those from control (without H₃PO₄ impregnation), resulting in more ion exchanges and complexation reaction for CLB with Cu(II) and Pb(II). Besides, the phosphorus-containing groups (e.g., P = OOH, P = O.), which newly formed with H₃PO₄ impregnation, could also enhance sorption, especially for Pb(II), this way leaded to its adsorption and precipitation as Pb₅(PO₄)₃OH crystals. The performance of maximum adsorption capacities of CLB toward Cu(II) and Pb(II) were 81.43 and 224.60 mg/g, respectively. This sorption was slightly pH-dependent, except that the sorption capacity improved significantly as the pH value of the solution increased from 2 to 4. Competitive sorption experiment confirmed that Pb(II) had a higher sorption priority than Cu(II).