QD433 : Study of Angelica and Gypsophila performance (as natural sorbents) in the removal of dye pollutants and removal proesses optimization using chemometrics methods
Thesis > Central Library of Shahrood University > Chemistry > PhD > 2023
Authors:
Nasrin Mehmandost [Author], Naser Goudarzi[Supervisor], Mansour Arab Chamjangali[Supervisor], Ghadamali Bagherian Dehaghi[Advisor]
Abstarct: Due to their low cost, availability, and environmental friendliness, biosorbents derived from renewable sources are appropriate for wastewater treatment. On the other hand, synthetic dyes can be hazardous to the ecosystem, even at low concentrations in the effluent. In the first part of this thesis, the Terminacatalpa plant magnetized with Fe3O4 nanoparticles was synthesized and used as an adsorbent for the simultaneous removal of crystal violet and methylene blue dyes. The adsorbent was characterized by FT-IR, FESEM, BET, and XRF analysis techniques. The Box-Behnken design was used in conjunction with the surface response methodology (RSM) to optimize the crystal violet and methylene blue absorption processes. The maximum adsorption capacity for the simultaneous removal of crystal violet and methylene blue dyes was 28.51 and 27.68 mg/g, respectively. Under the optimum conditions of pH (6.7), an adsorbent amount of (69 mg), a crystal violet concentration (30 mg L−1), methylene blue concentration (26 mg L−1), and contact time (6 min), 92.61% and 90.89% of the crystal violet and methylene blue absorption efficiencies were observed. The development of isotherms in binary solution revealed that the Extended Langmuir multicomponent isotherm best described the adsorption process and was also consistent with quasi-quadratic kinetics. The biosorbent capacity does not reduce after five regeneration cycles and is still efficient. The reaction mechanism shows that electrostatic forces play the main role in the adsorption process. In the second part of this thesis, the Heracleum persicum stems adsorbent magnetized with Fe3O4 nanoparticles for the simultaneous removal of crystal violet and methylene blue dyes from binary aqueous solutions was investigated investigated in a batch method under the influence of different parameters. Examination of the empirical result was investigated by using two approaches (multiple linear regressions (MLR) and random forest (RF) models. The result indicates that RF is a powerful tool for predicting crystal violet and methylene blue adsorption in binary aqueous solutions on applying the Heracleum persicum stems-Fe3O4 adsorption. The adsorbent was characterized by applying FESEM-EDX, FESEM, and FTIR. Various isotherm and kinetics models for the simultaneous adsorption of crystal violet and methylene blue were investigated in aqueous solutions. The adsorption isotherm and kinetics studies explain that the extended Langmuir model and pseudo-second-order models are best suited for crystal violet and methylene blue in the binary solution. The exothermic adsorption was achieved in the temperature range of 5-450 C. In third work of thesis, the Gypsophila aretioides stem is used as a biosorbent to remove crystal violet by the static and dynamic systems from aqueous solutions. The effects of different operating parameters such as pH, biosorbent dosage, and initial concentration of crystal violet and time for the batch method and the bed height, inlet crystal violet concentration, and flow rate on the breakthrough curves for the continuous method is investigated. The result of CV adsorption onto Gypsophila aretioides stem using the batch method indicates that the model fits Freundlich > Temkin > Langmuir > R-D, respectively. A pseudo-second-order model is recommended to describe the adsorption kinetics. The Thomas and Yoon-Nelson models were analyzed to study the adsorption kinetics. The random forest model shows an excellent ability to predict the parameters involved in the crystal violet adsorption process with appropriate accuracy and useable for large data, robust against noise.
Keywords:
#Dye removal #Crystal violet #Methylene blue #Biosorbent #Response Surface Methodology #Artificial Neural Network #Random Forest Keeping place: Central Library of Shahrood University
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