Atenolol sequestration using activated carbon derived from gasified Glyricidia sepium

Activated carbon (AC) derived from gasified Glyricidia sepium woodchip (GGSWAC) was prepared using KOH and CO₂ activation via microwave radiation technique to remove atenolol (ATN) from aqueous solution. The surface area (S_BET) and total pore volume (TPV) of GGSWAC were 483.07 m²/g and 0.255 cm³, respectively. The n-BET model fits well with the isothermal data indicating a multilayer adsorption with the saturation capacity of 121, 143 and 163 mg/g at 30, 45 and 60 °C, respectively. The kinetic study showed that ATN adsorption followed Avrami model equation (R² ≅ 0.99). Based on the thermodynamic parameters, the adsorption of ATN onto GGSWAC was endothermic (ΔH_S = 234.17 kJ/mol) in the first layer of adsorption and exothermic in the subsequent layer (ΔH_L = −165.62 kJ/mol). The ATN adsorption was controlled by both diffusion and chemisorption. In continuous operation, the Thomas (R² = 0.9822) and Yoon–Nelson (R² = 0.9817) models successfully predicted the ATN adsorption.     

Green synthesis of copper oxide nanoparticles CuO NPs from Eucalyptus Globoulus leaf extract: Adsorption and design of experiments

The study is concerned with synthesizing copper oxide nanoparticles with leaf extract Eucalyptus Globoulus. The results of scanning electron microscopy (SEM) and dynamic light scattering (DLS) revealed that the green synthesized copper oxide nanoparticles are spherical and have a mean particle size of 88 nm, with a negative zeta potential of ?16.9 mV. The XRD graph showed the crystalline and monoclinic phases of CuO nanoparticles. The average crystalline size around 85.80 nm was observed by the Debye–Scherrer formula. The adsorption characteristics of the nano-adsorbents were investigated using methyl orange, and the adsorption efficiency at room temperature attained 95 mg/g. Copper oxide nanoparticles (CuO NPs) adsorb methyl orange dye most effectively at pH 4.5 when the dye is applied in quantities of 0.04 g/50 mL. Box–Behnken design (BBD) in response surface methodology (RSM) was used to optimize various process parameters, such as pH solution (X₁: 2 – 11), adsorbing dose (X₂: 0.01 – 0.08 g/L), [MO] dye concentration (X₃: 10 – 80 mg/L). Overall, the adjusted coefficient of determination (R²) value of 0.99 demonstrated that the used model was quite appropriate, and the chosen RSM was effective in optimization the decolorization conditions of MO.     

Adsorptive scavenging of cationic dyes from aquatic phase by H3PO4 activated Indian jujube (Ziziphus mauritiana) seeds based activated carbon: Isotherm,kinetics, and thermodynamic study

In the present work, a cost-effective Indian jujube seeds derived activated carbon (IJSAC) prepared via o-phosphoric acid chemical activation, is studied for the sequestration of acriflavine (AF) and Victoria blue B (VB) from the aquatic environment. The activated carbon is characterized by Fourier transform infrared spectroscopy, N₂-adsorption/desorption isotherm, scanning electron microscopy techniques and point of zero-charge measurement. The specific surface area (S_BET) of 571 m²/g with a pore radius of 22.45 Å specifies mesoporous nature of the IJSAC. The implication of operational conditions on the adsorption of both dyes onto IJSAC assessed by batch methodology, establish the optimal conditions as dosage (1.5 and 2.5 g/L), contact time (60 min), pH (8 and 10), and initial concentration (130 and 140 mg/L) for AF and VB uptake, respectively. The Freundlich adsorption isotherm model (R² = 0.99) appropriates the equilibrium data suggesting multilayer adsorption onto heterogeneous surface sites, while pseudo-second order (R² = 0.95–0.99) is the best fit kinetic model. The liquid film and intraparticle diffusion modelling demonstrate that the adsorption process of these dyes is governed by both the steps. Maximum Langmuir adsorption capacity is 113.6 mg/g for acriflavine and 92.78 mg/g for Victoria blue B. Thermodynamic studies indicate endothermic and spontaneous adsorption of dyes. The adsorption mechanism for the uptake of AF and VB by IJSAC most probably involves hydrogen bonding, electrostatic and π-π interactions. Based on its high adsorption capacity, relatively faster kinetics, and reusability, IJSAC can be perceived as a proficient and effective adsorbent for cationic dyes removal from the liquid waste.     

Mixed phase Fe2O3/Mn3O4 magnetic nanocomposite for enhanced adsorption of methyl orange dye: Neural network modeling and response surface methodology optimization

In this research, a novel magnetic mesoporous adsorbent with mixed phase of Fe₂O₃/Mn₃O₄ nanocomposite was prepared by a facile precipitating method and characterized extensively. The prepared nanocomposite was used as adsorbent for toxic methyl orange (MO) dye removal from aqua matrix considering its high surface area (178.27 m²/g) with high saturation magnetization (23.07 emu/g). Maximum dye adsorption occurs at solution pH 2.0 and the electrostatic attraction between anionic form of MO dye molecules and the positively charged nanocomposite surface is the main driving force behind this adsorption. Response surface methodology (RSM) was used for optimizing the process variables and maximum MO removal of 97.67% is obtained at optimum experimental condition with contact time, adsorbent dose and initial MO dye concentration of 45 min, 0.87 g/l and 116 mg/l, respectively. Artificial neural network (ANN) model with optimum topology of 3–5–1 was developed for predicting the MO removal (%), which has shown higher predictive ability than RSM model. Maximum adsorption capacity of this nanocomposite was found to be 322.58 mg/g from Langmuir isotherm model. Kinetic studies reveal the applicability of second‐order kinetic model with contribution of intra‐particle diffusion in this process.     

Optimization of multiple parameters for treatment of coking wastewater using Fenton oxidation

Present study deals with the treatment of coking wastewater (CWW) using Fenton oxidation process for the degradation of pollutants containing chemical oxygen demand (COD), phenol and cyanide. The experiments were performed in batch mode to study the effect of operating parameters like initial pH (pH_i), temperature (T), oxidant H₂O₂ amount, catalyst mass loading (Cw) and treatment time (t_R). The response surface methodology (RSM) gave optimum value of pH, H₂O₂, Cw and t_R as 3, 0.3 M, 1.85 g/L (0.0266 M) and 1.52 h. At this optimum operating condition maximum 84.66% COD, 88.46% phenol and 79.34% cyanide reduction were achieved from initial value of COD (COD_i) = 2810.0 mg/L, phenol_i = 283.0 mg/L and cyanide_i = 18.88 mg/L. Results reflect that Fenton oxidation is an effective process for the reduction of pollutants present in CWW. The CWW treated by Fenton oxidation having average value COD = 590.0 mg/L, phenol = 39.49 mg/L and cyanide = 5.2 mg/L was further treated by adsorption process as second stage treatment, and these values were reached to COD = 199.0 mg/L, phenol = 0.0 mg/L and cyanide = 2.36 mg/L. The response surface methodology (RSM) was used for the designing and optimization of the experiments. Analysis of variance (ANOVA) suggested the high regression coefficient R² = 0.999 and 0.993 for COD and phenol removal respectively. The two stage treated CWW can be recycled and reused in same industry for various purpose.     

Thermodynamics of the Cu(II) adsorption on thin vanillin-modified chitosan membranes

In this work, low-density vanillin-modified thin chitosan membranes were synthesized and characterized. The membranes were utilized as adsorbent for the removal of Cu(II) from aqueous solutions. The experimental data obtained in batch experiments at different temperatures were fitted to the Langmuir and Freundlich isotherms to obtain the characteristic parameters of each model. The adsorption equilibrium data fitted well with the Langmuir model (average R² > 0.99). Interactions thermodynamic parameters (Δ_intH, Δ_intG, and Δ_intS), as well as the interaction thermal effects (Q_int) were determined from T = (298 to 333) K. The thermodynamic parameters, the Dubinin–Radushkevick equation and the comparative values of Δ_intH for some Cu(II)–adsorbent interactions suggested that the adsorption of Cu(II) ions to vanillin-chitosan membranes show average results for both the diffusional (endothermic) and chemical bonding (exothermic) processes in relation to the temperature range studied.     

Neural networks for predicting air gap membrane distillation performance

The hollow fiber air gap membrane distillation (AGMD) has recently attracted tremendous attention for desalination and wastewater treatment due to its high packing density, low conductive heat loss, and latent heat recovery capability. Utilizing fast and accurate modeling tools to predict MD performance can result in the further development of desalination technologies. However, simple and time-saving prediction models to assess the AGMD performance were not abundant. Herein, AGMD performance, including permeate flux (J) and gained output ratio (GOR) was predicted through multiple linear regression (MLR) model, back propagation neural network (BP ANN) and radial basis function neural network (RBF ANN) under different hot temperatures (T_h), coolant temperatures (T_c), feed flow rates (F), and feed concentration (c). A total of 30 sets of data were used to train the proposed models, the other 10 external validation datasets not used for training the models were applied to validate the prediction accuracy. The results depicted that RBF ANN (SPREAD = 30, N = 30) showed greatest prediction performance (R² = 0.99–1) compared with BP ANN and MLR models (R² = 0.98–0.99; R² = 0.89–0.97). The computing time consumption of RBF ANN was higher than BP ANN. According to the Mean impact value (MIV) analysis, T_h had the strongest effect on J and GOR. Increasing T_h and decreasing c both had positive impacts on J and GOR, but increasing T_c or F resulted in a trade-off influence. A genetic algorithm (GA) was employed to optimize J and GOR simultaneously, the optimum J and GOR could reach 6.00 kg/m²·h and 7.70 respectively. In this study, the three prediction models proved their abilities to predict AGMD performance and further provide guidance in the actual membrane distillation water treatment process.     

Optimized adsorption and effective disposal of Congo red dye from wastewater: Hydrothermal fabrication of MgAl-LDH nanohydrotalcite-like materials

The effectiveness of Congo red (CR) adsorption from aqueous solutions onto MgAl-layered double hydroxide (MgAl-LDH) nanosorbents was examined in this study. MgAl-LDH was synthesized using the hydrothermal method, and physicochemical characterization was performed via powdered X-ray diffraction, high-resolution transmission electron microscopy, Fourier transform infrared analysis, and zeta potential measurements. For optimum adsorption of CR onto the synthesized MgAl-LDH nanosorbent, the adsorption process was employed in batch experiments. Adsorption parameters, such as the adsorbent dosage, solution pH, contact time, and initial adsorbate concentration, vary with the adsorption kinetics and isotherm mechanism. The results of the batch experiments indicated rapid adsorption of CR dye from aqueous solutions onto MgAl-LDH during the first 30 min until equilibrium was achieved at 180 min with a dye concentration of 50 mg/100 mL and MgAl-LDH adsorbent dosage of 0.05 g. The experimental adsorption data fit adequately with the monolayer coverage under the Langmuir isotherm model (R² = 0.9792), and showed the best fit with the pseudo-second-order kinetic model (R² = 0.996). The change in zeta potential confirmed the effective adsorption interaction between the positively charged MgAl-LDH and the negatively charged CR molecules with electrostatic interactions. This work is distinguished by the successful hydrothermal preparation of MgAl-LDH in the form of homogenous nanoscale particles (～100 nm). The prepared MgAl-LDH showed a high adsorption capacity toward anionic CR dye with a maximum adsorption capacity of 769.23 mg/g. This capacity is higher than those reported for other adsorbents in previous research.     

Prediction of breakthrough curves for multicomponent adsorption in a fixed-bed column using logistic and Gompertz functions

In order to facilely predict the multicomponent breakthrough curves and avoid the complicated numerical solution, this work proposes two empirical models based on the logistic and Gompertz functions. The S-shaped and bell-like curves correspond to the adsorption and displacement processes respectively. The equilibrium loading of each component can be calculated by integration of the measured breakthrough curves. The effects of the model parameters on the breakthrough curves are investigated. The applicability of the two empirical models is validated by three binary and four ternary adsorption systems, including the gas–solid and liquid–solid adsorption. The residual plot and coefficient of determination (R²) are used to evaluate their fitting quality. The results indicate that the fitting curves agree well with the experimental data and all of the residuals are distributed randomly. The five model parameters (k, τ, k*, τ* and c) are easily obtained by the nonlinear regression. For example, the fitting results are k = 1.37 × 10^?2 min^?1, τ = 292 min, k* = 1.25 × 10^?2 min^?1, τ* = 453 min and c = 85.3 for adsorption of n-butyl acetate and p-xylene on granular activated carbon. On the whole, the Gompertz model is superior to the logistic model in terms of the fitting accuracy. The significance of this work is to provide a simple and practical method for prediction of the multicomponent breakthrough curves.     

Biosorption of lead (II) from aqueous solution using Cellulose-based Bio-adsorbents prepared from unripe papaya (Carica papaya) peel waste: Removal Efficiency,Thermodynamics, kinetics and isotherm analysis

This work focuses on the removal of lead from contaminated aqueous solutions using unripe papaya peel based bio-adsorbents (PP). Response surface methodology (RSM) based on Box-Behnken design (BBD) is employed to determine the independent variables. Optimum conditions proved to be 96.5 mg/L of initial lead concentration in solution, at pH 4 of aqueous solution, having adsorbent dosage of 14.6 g/L and contact time (3 h) which subsequently yielded the predicted and actual lead removal efficiencies of 100% and 97.54%, respectively. Adsorption isotherms and kinetics of lead adsorption using unripe papaya peel followed the Freundlich and pseudo-second-order models, indicating that the process of chemisorption occurred. The magnitude of the adsorption capacity of the pseudo-second-order model (q_e,cal = 6.25 mg/g) was found to be comparable to the value obtained experimentally (q_e,cal = 6.45 mg/g). Thermodynamic parameters were calculated in order to identify the phenomena of adsorption. The values of ΔH° and ΔS° are found to be 13.61 J/mol and 54.30 J/mol?K, respectively. The characteristics of unripe papaya peel bio-adsorbents, analyzed via SEM/EDX, FTIR and BET, are also presented. Thus, the O-H and C-O functional groups contained in the unripe papaya peel waste were found to effectively adsorb lead from the aqueous medium. The average pore diameters, average pore volumes and average surface area of bio-adsorbents prepared from unripe papaya peel waste proved to be 9.046 nm, 0.0012 cm³/g and 0.755 m²/g, respectively.     

Synthesis and asymmetric catalytic application of chiral imidazolium–phosphines derived from (1R,2R)-trans-diaminocyclohexane

Reaction between a chiral imidazole–amine precursor derived from (1R,2R)-trans-diaminocyclohexane and P¹Cl (where P¹ = PPh₂, P(1,3,5-Me₃C₆H₃)₂, P(2,2′-O,O′-(1,1′-biphenyl), P((R)-(2,2′-O,O′-(1,1′-binaphthyl))) and P((S)-(2,2′-O,O′-(1,1′-binaphthyl)))) followed by RX (where R = ⁿPr, ⁱPr, CHPh₂, X = Br; R = ⁱPr, X = I), respectively, gives a selection of chiral imidazolium–phosphine compounds. Deprotonation of the imidazolium salt gives the corresponding NHC–P ligands that can be used in metal-mediated asymmetric catalytic applications. Catalytic reactions show that NHC–P ligands give a significantly greater rate of reaction for a palladium catalysed allylic substitution reaction in comparison to analogous di-NHC or NHC–imine ligands and that NHC–P hybrids are also effective for iridium catalysed transfer hydrogenation.     

Cellulose from Tamarix aphylla’s stem via acetocell for cadmium adsorption

This study emphasized the efficiency of unconventional delignification treatment “Acetocell” as a basic pretreatment to isolate cellulose fiber from Tamarix aphylla’s stem. Chemical proprieties of obtained cellulose were determined and its efficiency for cadmium ions adsorption was evaluated subsequently. Fourier transform infrared spectroscopy (FTIR), X-ray diffraction analysis, thermogravimetric analysis (TGA), Scanning Electron Microscopy (SEM), fluorescence microscope and Morfi were used to analyze the thermochemical and morphological characteristics of the fibers before and after treatment. Cellulose was used as a biosorbent to remove cadmium ions from polluted water. The effects of many parameters on the efficiency removal of cadmium were investigated; the amount of cellulose, the contact time, pH and the initial concentration of cadmium ions. The optimum conditions were 45 mg of adsorbent, 45 mg L^?1, 1200 min and pH 8 which provide best adsorption capacity equal to 44.21 mg g^?1. The energy value E = 6.65 kJ mol^?l which confirm the physical interaction between cellulose-cadmium ions.Then Langmuir, Freundlich, Temkin and Dubinin-Radushkevich models were followed for modeling adsorption. Langmuir isotherm and the pseudo-second order model seems the most suitable which describe better the adsorption of cadmium ions with best R² values which equal to 0.9937 and 0.9979, respectively.     

Adsorption of thorium (IV) by amorphous silica; response surface modelling and optimization

The amorphous SiO₂ (200–300 nm) was synthesized as an absorbent and thorium adsorption of SiO₂ was investigated using experimental and RSM method. The SiO₂ particles were made for the adsorption of thorium from aqueous solutions, and characterized by particle size measurement, XRD and SEM. The adsorption of thorium process was optimized with RSM method. The correlation between four variables was modeled and studied. Under optimum conditions, the adsorption capacity of SiO₂ particles was found to be 134.4 mg/g, the correlation coefficient (R²) and the F value was obtained 0.96 and 1.98?×?10^?6, respectively. In addition, the adsorption isotherms were examined.     

CoFe2O4@Methylcellulose/AC as a New,Green, and Eco-friendly Nano-magnetic adsorbent for removal of Reactive Red 198 from aqueous solution

Methylcellulose (MC) is the most common commercial cellulose ether and the most attractive biopolymer due to its cheap cost of biodegradability, biocompatibility, hydrophilicity, and lack of toxicity. In this study, CoFe₂O₄@MC/activated carbon (AC) was synthesized as a unique magnetic nano-adsorbent in the presence of MC biopolymer for Reactive Red 198 (RR198) dye removal. The nano-magnetic adsorbent was characterized by FESEM (Field emission scanning electron microscopy), EDS (Energy-dispersive X-ray spectroscopy), Mapping, Linescan, BET (Brunauer–Emmett–Teller), FTIR (Fourier Transform Infrared Spectroscopy), XRD (X-Ray Diffraction), and VSM (Vibrating-Sample magnetometer). For simple separation by external magnetic fields, the Ms value was 57.91 emu/g. According to XRD analysis, the nano-adsorbent maintains its crystal structure, with an average crystal size of 11 nm. The maximum removal efficiencies of RR198 for synthetic and real wastewater samples under optimal conditions (an initial concentration of 10 mg/L, pH 3, contact time of 10 min, nanocomposite dose of 1.5 g/L, and a temperature of 25 °C) were 92.2% and 78%, respectively. The adsorption experiments were fitted well with the Freundlich isotherm (R² = 0.989) and pseudo-second-order kinetic (R² = 0.995). The values of entropy changes (ΔS = 35.087 kJ/mol.k), enthalpy changes (ΔH = -9.862 kJ/mol), and negative Gibbs free energy changes (ΔG) showed that the adsorption process was exothermic. Finally, the reusability findings showed that after six recovery cycles, the efficiency decreased slightly (90.1%). In the end, it can be concluded that the prepared CoFe₂O₄@Methylcellulose/AC can be used as an efficient adsorbent for the removal of RR198 from an aqueous solution.     

Modelling and optimization of crude oil removal from surface water via organic acid functionalized biomass using machine learning approach

Banana peel fiber adsorbent (BPF) with well-arranged substructure of pores was fabricated via esterification reaction with organic acid and biomass. The emerged adsorbent (BPF) was employed in taking away crude oil from water surface. Three machine learning tools such as RSM, ANN and ANFIS was employed for the modelling and optimization of the process. From results, the optimal oil layer removal of 98.2% was achieved at oil water ratio of 0.2 g /100 cm³. For now, BPF displayed high adsorptive prospect at a very low pH of 4 with 96.8% oil removal. On the other hand, the activation energy, enthalpy change and entropy change of the system are (18.56, 25.44, ?0.751 KJ/mols) and (25.77, 29.16, ?0.813 KJ/mols) designating a non-spontaneous system. The process of removal by BPF really matched the Langmuir isotherm model as proved by statistical error analysis with highest adsorption capacity of 49.33 mg/g as shown through equilibrium modeling. RSM displayed the optimum conditions of the key variables such as temperature, oil concentration, adsorbent dosage, pH and time as 100 °C, 0.2 g/100 cm³, 1.5 g, 2 and 75 mins, respectively. Analysis of the three generic algorithm indicated significant oil removal prediction with quite remarkably similar coefficient of correlation of 0.999. Additional statistical analysis suggested that RSM was marginally better than ANN and ANFIS for the modelling of crude oil removal via esterified banana peels fiber.     

Isotherm modelling and optimization of oil layer removal from surface water by organic acid activated plantain peels fiber

This research aimed to optimize and model the adsorption process of oil layer removal using activated plantain peels fiber (PPF), a biomass-based material. The adsorbent was activated by thermal and esterification methods using human and environmentally friendly organic acid. Effects of process parameters were examined by one factor at a time (OFAT) batch adsorption studies, revealing optimal conditions for oil removal. Also, RSM, ANN and ANFIS were used to adequately predict the oil removal with correlation coefficient > 0.98. RSM modelling revealed the best conditions as 90 °C, 0.2 mg/l, 1.5 g, 6 and 75 mins, for temperature, oil–water ratio, adsorbent dosage, pH and contact time respectively. Under these simulated conditions, the predicted oil removal was 96.88 %, which was experimentally validated as 97.44 %. Thermodynamic studies revealed the activation energy, change in enthalpy and change in entropy for irreversible pseudo-first order and pseudo-second order model as (15.82, 24.17, ?0.614 KJ/mols) and (33.21,40.31, ?0.106 KJ/mols) respectively, indicating non-spontaneous process; while modeling studies revealed that the adsorption process was highly matched to Langmuir’s isotherm, with maximum adsorption capacity of 50.34 mg/g. At the end of the overall statistical modelling, ANFIS performed marginally better than the ANN and RSM. It can be concluded from these results that our biomass-based material is an efficient, economically viable and sustainable adsorbent for oil removal, and has potentials for commercialization since the process of adsorption highly matched with standard models, and its capacity or percentage oil removal also compares favorably to that of commercially available adsorbents.     

An approach utilizing the Response Surface Methodology (RSM) to optimize Adsorption-Desorption of Natural Saudi Arabian Diatomite- with the Box- Behnken Design Technique

Saudi Arabian’s natural diatomite samples were subjected to physical adsorption–desorption characterizations using Brunauer-Emmet-Teller (BET) and the Barrett-Joyner-Halenda (BJH), performed under heating of 140 °C for different periods of hours: 6, 12, 18, and 24 h, to create a central optimization design with surface areas and total pore distributions. Seventeen experimental runs resulted in the primary composite factor design. The surface response describes 100 % variability with a determination coefficient of 1, signifying the quadratic model with an expected correlation coefficient (R²) is satisfied with a standard deviation of 0.2322, demonstrating the high predictability of the model. Moreover, the RSM results have been validated using the t-test with the observed R² value and adjusted R². The model selected with higher F and p values showed<0.0001, which subsequently described the significance of the developed model. The independent components were explained with the help of 3D surface and contour plots that compare the heating time, elapsed time, pressure, and relative pressure against the dependent variable. The plots revealed that the adsorbed quantities well depended on heating time, elapsed time, pressure, relative pressure for isotherm, BET surface area, Langmuir surface area, and t-plot Micropore area.