Barium/Cobalt@Polyethylene Glycol Nanocomposites for Dye Removal from Aqueous Solutions.

Dyes are known as one of the most dangerous industrial pollutants which can cause skin diseases, allergy, and provoke cancer and mutation in humans. Therefore, one of the important environmental issues is the effective removal of dyes from industrial wastewater. In the current work, BaFe12O19/CoFe2O4@polyethylene glycol (abbreviated as BFO/CFO@PEG) nanocomposite was synthesized and evaluated regarding its capacity for adsorptive removal of a model dye Acid Blue 92 (denoted as AB92) from aqueous solutions. The characteristics of the prepared nanocomposite was determined by tests such as X-ray diffraction (XRD), scanning electron microscope (SEM), vibration sample magnetization (VSM), and Fourier transform infrared spectroscopy (FTIR). The effects of conditional parameters including pH (2-12), initial concentration of dye (20-100 mg/L), adsorbent dosage (0.02-0.1 g/L) and contact time (0-180 min) on the adsorption of dye were investigated and then optimized. The results indicated that with the increase of the adsorbent dosage from 0.02 to 0.1 g/L, the removal efficiency increased from 74.1% to 78.6%, and the adsorbed amount decreased from 148.25 to 31.44 mg/g. The maximum removal efficiency (77.54%) and adsorption capacity (31.02 mg/g) were observed at pH 2. Therefore, the general optimization conditions revealed that the maximum adsorption efficiency of dye was obtained in condition of initial concentration of 20 mg/L, contact time of 1 h and pH of solution equal 2. The adsorption isotherm and kinetic data were evaluated using a series of models. The pseudo-second order kinetic model and Freundlich isotherm model show the best fitting with experimental data with R2∼0.999.

Acid Dye Removal from Aqueous Solution by Using Neodymium(III) Oxide Nanoadsorbents.

In the current work, neodymium oxide (Nd2O3) nanoparticles were synthesized and characterized by means of X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). The major aim/investigation of this research was to fit/model and optimize the removal of Acid Blue 92 (AB92) dye from synthetic effluents (aqueous solutions) using the adsorption process based on neodymium oxide (Nd2O3) nanoparticles. To optimize the adsorption conditions, central composite design (CCD) based on response surface methodology (RSM) was applied. The effects of pH (3-9), adsorbent dosage (0.1-1 g/L), initial concentration of AB92 (100-300 mg/L), and contact time (10-100 min) on the adsorption process were investigated. Apart from equilibrium and kinetic experiments, thermodynamic evaluation of the adsorption process was also undertaken. The adsorption process was found to have the best fitting to Langmuir isotherm model and pseudo-second-order kinetic equation. Also, the process was found to be spontaneous and favorable with increased temperature. The optimal conditions found were: pH = 3.15, AB92 concentration equal to 138.5 mg/L, dosage of nanoadsorbent equal to 0.83 g/L, and 50 min as contact time, which resulted in 90.70% AB92 removal. High values for the coefficient of determination, R2 (0.9596) and adjusted R2 (0.9220) indicated that the removal of AB92 dye using adsorption can be explained and modeled by RSM. The Fisher's F-value (25.4683) denotes that the developed model was significant for AB92 adsorption at a 95% confidence level.

Environmentally friendly synthesis of Fe2O3@SiO2 nanocomposite: characterization and application as an adsorbent to aniline removal from aqueous solution.

Silica-based nanocomposite syntheses employ many harmful substances, which, in turn, demand the development of new synthetic environmental-friendly routes that meet the principles of green chemistry. In this work, we present a novel magnetic adsorbent, Fe2O3@SiO2 nanocomposite (Fe@SiNp), successfully obtained without surfactant, employing an electrochemical method. We characterized the nanocomposite and then applied it to remove aniline from the water medium. Characterization was carried out by vibrating-sample magnetometry (VSM), X-ray diffraction (XRD), scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FT-IR). The parameters to the adsorptive removal of aniline were successfully optimized, which made possible to remove 71.04 ± 0.06% (126.6 ± 2.0 mg/g) from a 100 mg/L aniline solution at pH 6 and 323 K, by employing around 50 mg of Fe@SiNp, at a contact time of 40 min. The adsorption of aniline by Fe@SiNp is a spontaneous and exothermic process according to the pseudo-second-order kinetic model (r2 = 1 at 20 mg/L aniline concentration) and the Freundlich isotherm model (r2 = 0.9986).

Modeling of adsorption of Methylene Blue dye on Ho-CaWO4 nanoparticles using Response Surface Methodology (RSM) and Artificial Neural Network (ANN) techniques.

The aim of this study is to evaluate the applicability of Ho-CaWO4 nanoparticles prepared using the hydrothermal method for the removal of Methylene Blue (MB) from aqueous solution using adsorption process. The effects of contact time, Ho-CaWO4 nanoparticles dose and initial MB concentration on the removal of MB were studied using the central composite design (CCD) method. Response Surface Methodology (RSM) and Artificial Neural Network (ANN) modeling techniques were applied to model the process and their performance and predictive capabilities of the response (removal efficiency) was also examined. The adsorption process was optimized using the RSM and the optimum conditions were determined. The process was also modelled using the adsorption isotherm and kinetic models. The ANN and RSM model showed adequate prediction of the response, with absolute average deviation (AAD) of 0.001 and 0.320 and root mean squared error (RMSE) of 0.119 and 0.993, respectively. The RSM model was found to be more acceptable since it has the lowest RMSE and AAD compared to the ANN model. Optimum MB removal of 71.17% was obtained at pH of 2.03, contact time of 15.16 min, Ho-CaWO4 nanoparticles dose of 1.91 g/L, and MB concentration of 100.65 mg/L. Maximum adsorption capacity (qm ) of 103.09 mg/g was obtained. The experimental data of MB adsorption on Ho-CaWO4 nanoparticles followed the Freundlich isotherm and pseudo-second-order kinetic models than the other models. It could be concluded that the prepared Ho-CaWO4 nanoparticles can be used efficiently for the removal of MB and also, the process can be optimized to maximize the removal of MB. •Synthesis and characterization of Ho-CaWO4 nanoparticles.•Modelling and optimization of Methylene Blue removal onto Ho-CaWO4 using Response Surface Methodology (RSM) and Artificial neural network (ANN).•Evaluation of the isotherm and kinetic parameters of the adsorption process.

Degradation of aniline by the combined process of ultrasound and hydrogen peroxide (US/H2O2).

Aniline is an aromatic hydrocarbon discharged into the environment through certain industrial effluents, which thereby contaminate water resources. In this study, the performance of an oxidizing agent, hydrogen peroxide (H2O2) with ultrasound (US) for the removal of aniline from its aqueous solution was examined. The treatability of contaminated effluent using US/H2O2 with a frequency of 50 Hz for the treatment of aniline-contaminated water was investigated. The effects of operational parameters such as H2O2 concentration (0.01-0.07 mol/L), initial aniline concentration (20-120 mg/L), contact time (15-90 min) and pH (3-11) on the degradation of aniline was examined. Optimal H2O2 concentration, initial aniline concentration and contact time were obtained as 0.01 mol/L, 20 mg/L, and 45 min. The degradation process was more efficient at pH of 3. Removal efficiency of 95.91% was achieved at these optimum conditions. The results indicate that the combined US and H2O2 process at optimal conditions can be applied for the degradation of aniline with great efficiency.

Data on the removal of fluoride from aqueous solutions using synthesized P/γ-Fe2O3 nanoparticles: A novel adsorbent.

High concentration of fluoride above the optimum level can lead to dental and skeletal fluorosis. The data presents a method for its removal from fluoride-containing water. P/γ-Fe2O3 nanoparticles was applied as an adsorbent for the removal of fluoride ions from its aqueous solution. The structural properties of the P/γ-Fe2O3 nanoparticles before and after fluoride adsorption using the Fourier transform infrared (FTIR) technique were presented. The effects of pH (2-11), contact time (15-120 min), initial fluoride concentration (10-50 mg/L) and P/γ-Fe2O3 nanoparticles dosage (0.01-0.1 g/L) on the removal of F- on P/γ-Fe2O3 nanoparticles were presented with their optimum conditions. Adsorption kinetics and isotherm data were provided. The models followed by the kinetic and isotherm data were also revealed in terms of their correlation coefficients (R2 ).

Survey dataset on the externalizing self-esteem and gender effects on self-esteem subscales of students in Zabol University of Medical Sciences, Iran.

The data presents the self-esteem examination of undergraduate students studying in Zabol University of Medical Sciences, Iran in 2017 and its relationship with gender. The total number of participants was 100 (49% female and 51% male). The 100 students were selected through random sampling method. The average age of participants was 21.61 years while the youngest and the oldest participants were 19 and 32 years old, respectively. The data were collected using the Coopersmith Self-Esteem Inventory (CSEI) and analyzed by descriptive statistics (frequency, mean, standard deviation, minimum and maximum) using SPSS version 22 (statistical package for Social Sciences). The detailed dataset is presented in this paper.