Optimization of lithium adsorption from seawater via aluminum chloride as adsorbent using response surface methodology

Use of bran oil in various edible and nonedible industries is very common. In this research work, efficient and optimized methodology for the recovery of rice bran oil has been investigated. The present statistical study includes parametric optimization, based on experimental results of rice bran oil extraction. In this study, three solvents, acetone, ethanol and solvent mixture (SM) [acetone: ethanol (1:1 v/v)] were employed in extraction investigations. Response surface methodology (RSM), an optimization technique, was exploited for this purpose. A five level central composite design (CCD) consisting four operating parameter, like temperature, stirring rate, solvent-bran ratio and contact time were examined to optimize rice bran oil extraction. Experimental results showed that oil recovery can be enhanced from 71% to 82% when temperature, solvent-bran ratio, stirring rate and contact time were kept at 55°C, 6:1, 180 rpm and 45 minutes, respectively while fixing the pH of the mixture at 7.1.

Statistical analysis and optimization of ammonia removal from landfill leachate by sequential microwave/aeration process using factorial design and response surface methodology

This research article presents a study on the potential use of oil-based ferrofluid for the efficient removal of microplastics from water. The targeted analyte, micro-polystyrene (micro-PS), was chosen along with palm oil as the carrier liquid. Fourier Transform Infrared (FTIR) analysis was conducted to identify the main peaks in the ferrofluid, including carboxyl group (1542 cm-1), C-H bonding (1022 cm-1), CH2 bonding (2941 cm-1), CH3 bonding (3461 cm-1), C=C bonding (1255 cm-1), and Fe-O (597.34 cm-1). A comprehensive investigation of the synergistic effect of six variables was performed: volume of oil (4-15 mL), weight of magnetite nanoparticles (0.1-0.2 g), stirring rate (132-468 rpm), contact time (3-12 min), pH value of water samples (pH 6-8), and effect on ionic strength (0-16 g/L). Response surface methodology, including 26-Plackett-Burman and 24-central composite design, were employed to establish the relationship between the variables. The optimum operational settings proposed by the model were as follows: volume of oil (14.6 mL), weight of magnetite nanoparticles (0.1 g), stirring rate (216 rpm), contact time (3.29 min), pH value of water samples (pH 6-6.5), and effect on ionic strength (16 g/L), resulting in a remarkable removal efficiency of 91.09 ± 0.99%. The method exhibited desirable figures of merit, including a low bias (%RSD) of below 5% and the ability to reuse the ferrofluids for up to five cycles. Additionally, an analytical greenness metric was employed to assess the environmental impact of the sample preparation process, with a green score of 0.69/1.0 (indicating a light green colour). Future work in this field could focus on the scalability of the developed method and its applicability to real-wastewater treatment.

The adsorption capacities of new biomaterials derived from lemon leaf (Citrus sp.) toward fluoride ions have been explored by varying different physicochemical parameters such as pH, initial concentration, adsorbent dose, contact time, stirring rate and temperature. The entire study was done through batch process. Maximum fluoride adsorption of 96.9% - 98.8% was achieved with an initial concentration of 10 mg/L. Langmuir isotherm model well expressed fluoride ad- sorption onto LLD-1, LLD-2 and LLD-3. According to correlation coefficient, the fluoride adsorption onto these 3 ad- sorbents was correlated well with pseudo-second-order kinetic model. From thermodynamic study, the spontaneous nature and feasibility of the adsorption process with negative enthalpy (&#916H0) value also supported the exothermic nature were shown. The rate of fluoride adsorption was mathematically described as a function of experimental parameters and was modeled through Box-Behnken (Response surface methodology). The results showed that the responses of fluoride adsorption were significantly affected by the quadratic term of pH, initial concentration, contact time and temperature and the statistical analysis was performed by ANOVA which indicated good correlation of experimental parameters.

Magnesium-aluminium hydrogenphosphate layered double hydroxide that synthesized by used of co-precipitation and followed by hydrothermal (MAHP4) method was used as an adsorbent to remove copper ions from aqueous solutions. The effects of various optimization parameters such as contact time, adsorbent dosage and lead ion concentrations were investigated by used of Response surface methodology (RSM). The Response surface methodology (RSM) based on a four-level-three variables Central Composite Rotatable Design (CCRD) was employed to evaluate the interactive effects of the various optimization parameters. The parameters were contact time (2-6 h), adsorbent dosage (0.01 0.05 g) and copper ion concentrations (50 100 mg/l). Simultaneously by increasing contact time and amount of dosage of MAHP4 used, the percentage of lead ion removal from aqueous solution was increased. However, the percentage removal decreases with an increase in concentrations of copper ion. The experimental percentage removal recorded under optimum conditions was compared well with the maximum predicted value from the RSM which suggest that fractional factorial design of RSM can be used to study the removal of copper from aqueous solution by used of magnesium-aluminium hydrogenphosphate layered double hydroxide as an adsorbent.

Recyclable methodology over bimetallic zero-valent Mg:Zn composition for hexavalent chromium remediation via batch and flow systems in industrial wastewater: an experimental design

The study on the biosorption of copper ions using raw eggshells as an adsorbent is presented in this paper. The influence of different process parameters, such as: initial pH value of the solution, initial Cu2+ ions concentration, initial mass of the adsorbent, and stirring rate, on the biosorption capacity was evaluated. The SEM-EDS analysis was performed before and after the biosorption process. SEM micrographs indicate a change in the morphology of the sample after the biosorption process. The obtained EDS spectra indicated that K, Ca, and Mg were possibly exchanged with Cu2+ ions during the biosorption process. The equilibrium analysis showed that the Langmuir isotherm model best describes the experimental data. Four kinetic models were used to analyze the experimental data, and the results revealed that the pseudo-first order kinetic model is the best fit for the analyzed data. Calculated thermodynamic data indicated that the biosorption process is spontaneous, and that copper ions are possibly bound to the surface of the eggshells by chemisorption. The biosorption process was optimized using Response Surface Methodology (RSM) based on the Box-Behnken Design (BBD), with the selected factors: adsorbent mass, initial metal ion concentration, and contact time.

In this paper, we evaluate the performance of molecular-imprinted polymer (MIP) and dispersive liquid-liquid microextraction (DLLME) methods for extraction and separation of Fenpyroximate (Fen) pesticide from aqueous samples. The effective parameters for pesticide microextraction such as adsorbent dose, pH, contact time, stirring rate, to achieve high removal percentage were studied using the response surface method. The effect of influencing factors on microextraction, such as type and volume ratio of dispersive and extractive solvents, salt concentration, pH, and extraction time were investigated and optimized. The maximum recovery) 94 %( of the pesticide was obtained using 0.55 wt. % MIP as an adsorbent in pesticide solution with pH 5.9 at 512 rpm on 58 minutes. However, the recovery efficiency (93%) was achieved by DLLME with an extraction solvent-to- dispersive volume ratio of 25 /75, the salt concentration of 3.5 wt. %, and pH 6.0, during 72 seconds of extraction time. This high separation efficiency is achieved in a very short time. The reason is the structure of this method, because in DLLME the transfer level of aqueous and organic phases reaches its maximum value, and as a result, the largest extraction will be achieved. The results showed that both extraction methods have high potential to effectively reduce pesticides from aqueous solutions, but, DLLME method is suggested to has higher priority due to the very short separation time.

The release of dye containing effluent is a great threat to the world today. The purpose of this study is to optimize the removal of Reactive Blue 19 (RB19) dye from aqueous solutions using advanced oxidation process (AOP). Magnesium oxide nanoparticles (MgO NPs) and hydrogen peroxide (H2O2) were used as the catalyst and oxidizer, respectively. Central composite design (CCD) based on response surface methodology (RSM) was applied for optimization of the AOP process. The effects of pH (3–7), molar H2O2/MgO NPs ratio (1–3), initial concentration of RB19 (20–80 mg/L), and contact time (30–90 min) were investigated on the oxidation process. The CCD was applied to determine the interactive effects of the process parameters and their optimum conditions. One-way analysis of variance (ANOVA) was applied for statistical data analysis. A quadratic model was generated by the CCD to represent the AOP on RB19 degradation. The experimental values obtained for percentage RB19 decolorization were found to be very close to the predicted response values. Based on the design, optimum conditions of pH 3, contact time of 60 min, RB19 concentration of 80 mg/L and H2O2/MgO NPs molar ratio of 3 were obtained which resulted in 93.77% RB19 removal. High value for the coefficient of determination, R2 (0.912) and adjusted R2 (0.805) showed that the removal of RB19 dye using AOP can be described by the RSM. The ANOVA results showed that the quadratic model developed from the RSM was statistically significant for RB19 decolorization. From the study, it could be concluded that the RSM can be a useful tool for optimization and moderation of the process parameters to maximize RB19 dye removal from aqueous solutions and the advanced H2O2/MgO NPs oxidation process.

As a key parameter in the adsorption process, removal rate is not available under most operating conditions due to the time and cost of experimental testing. To address this issue, evaluation of the efficiency of NH4+ removal from stormwater by coal-based granular activated carbon (CB-GAC), a novel approach, the response surface methodology (RSM), back-propagation artificial neural network (BP-ANN) coupled with genetic algorithm (GA), has been applied in this research. The sorption process was modeled based on Box-Behnben design (BBD) RSM method for independent variables: Contact time, initial concentration, temperature, and pH; suggesting a quadratic polynomial model with p-value < 0.001, R2 = 0.9762. The BP-ANN with a structure of 4-8-1 gave the best performance. Compared with the BBD-RSM model, the BP-ANN model indicated better prediction of the response with R2 = 0.9959. The weights derived from BP-ANN was further analyzed by Garson equation, and the results showed that the order of the variables’ effectiveness is as follow: Contact time (31.23%) > pH (24.68%) > temperature (22.93%) > initial concentration (21.16%). The process parameters were optimized via RSM optimization tools and GA. The results of validation experiments showed that the optimization results of GA-ANN are more accurate than BBD-RSM, with contact time = 899.41 min, initial concentration = 17.35 mg/L, temperature = 15 °C, pH = 6.98, NH4+ removal rate = 63.74%, and relative error = 0.87%. Furthermore, the CB-GAC has been characterized by Scanning electron microscopy (SEM), X-ray diffraction (XRD) and Brunauer-Emmett-Teller (BET). The isotherm and kinetic studies of the adsorption process illustrated that adsorption of NH4+ onto CB-GAC corresponded Langmuir isotherm and pseudo-second-order kinetic models. The calculated maximum adsorption capacity was 0.2821 mg/g.

Response surface methodology was applied to optimize the processing parameters (dosage of NaOH, dosage of H2O2, reaction temperature, liquid-to-solid ratio, stirring rate, and reaction time) that affected the leaching process of vanadium and chromium. The results indicated that the leaching process of vanadium was significantly affected by the dosage of NaOH and dosage of H2O2 used in the experiments, whereas the processing parameters affected the leaching efficiency of chromium in the following order: dosage of H2O2 (F) > reaction temperature (C) > dosage of NaOH (A) > reaction time (B) > stirring rate (D) > liquid-to-solid ratio (E). Almost 98.60% of vanadium and 79.82% of chromium were leached out during the leaching process.

This study sheds light on the adsorption process for the removal of nitrate ions from synthetic aqueous solutions. This contaminant pose a potential risk to the environment and can cause health effects including cancers and methemoglobinemia in infants. When the adsorption process is carried out, the effect by the several operating parameters such as initial nitrate concentration, pH, mass of activated carbon, and contact time becomes apparent. The essential process variables are optimized using response surface methodology (RSM) based on the central composite design (CCD) experiments. For this purpose 31 experimental results are required to determine the optimum conditions. The optimum conditions for the removal of nitrates is found to be: initial nitrate concentration = 15 mg/L; initial pH 4.0; mass of activated carbon = 25 mg, and contact time = 70 min. At these optimized conditions, the maximum removal of nitrates is found to be 96.59%.

Groundwater fluoride removal by novel activated carbon/aluminium oxide composite derived from raffia palm shells: Optimization of batch operations and field-scale point of use system evaluation

Optimization of packed bed electrolysis of zinc anode casing of spent dry cell batteries

The aim of this study is to optimize the adsorption of pentachlorophenol (PCP) using an organo-clay under the response surface methodology. The adsorbent was selected from a montmorillonite exchanged by various cations, such as Fe3+, Al3+, Zn2+, Mg2+, Na+, and modified by bromide cetyltrimethylammonium (CTAB) as surfactant. The obtained organo-montmorillonite was characterized using several techniques, such as Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), scanning electron microscopy (SEM), and nitrogen adsorption, performed at −196 °C. The results showed an increase in basal space from 1.65 to 1.88 nm and a decrease in the specific surface and pore volume, with an increase in pore diameter, including the presence of characteristic bands of -CH2- and -CH3- groups at 2926 and 2854 cm−1 in the FTIR spectrum after the modification. The optimization of PCP removal by clay adsorbents is achieved using the response surface methodology (RSM) with a four-factor central composite model, including pH of solution, mass of adsorbent, contact time, and initial concentration. The results proved the validity of the regression model, wherein the adsorption capacity reaches its maximum value of 38 mg/g at a lower adsorbent mass of 20 mg, pH of 6, contact time (tc) of 5 h, and initial concentration of 8 mg/L.