Abstarct: In the first section of this thesis, magnetite walnut shell was synthesized via a chemical method, and its surface characterization was carried out using different techniques. Then the performance of this composite, which possessed the adsorption features of walnut shell and the magnetic property of Fe_۳O_۴, was investigated for the removal of methyl violet and Rhodamine ۶G from single component aqueous solutions. The effects of different experimental variables such as the initial sample solution pH, adsorbent dosage, dye concentration, and contact time on the removal efficiency of the cited dyes were examined. Then these variables were used as the inputs in order to generate linear and non-linear models such as the multiple linear regression (MLR), random forest (RF), and artificial neural network (ANN) in order to predict the removal efficiency of these dye species at different experimental conditions. The validation studies of these models were performed using the test set (۱۰۸ data), which was not present in the modeling procedure. The results obtained showed that the ANN model (as a non-linear model) had a higher ability to predict the adsorption process for both dyes under different experimental conditions. The simultaneous removal of these two cationic dyes using the proposed adsorbent was also studied. The results obtained showed that due to the competitive effect of the understudied dyes, the removal percentage in solutions containing a mixture of these two dyes decreases compared to the solutions containing only one of the dyes. In the second section of this thesis, a new carboxylate–functionalized pine cone was prepared using isopropylidene malonate in a solvent-free reaction. Then it was characterized by different techniques. The performance of the modified adsorbent was investigated for the removal of the safranin-O (SO) and methyl violet (MV) dyes from the single and binary solutions. The maximum adsorption capacity for SO and MV in the single solution was ۲۰۸.۰ and ۲۲۵.۰ mg/g, respectively, whereas these values were, respectively, ۱۱۲.۳۰ and ۱۱۶.۷ mg/g for the binary solution. In continuation, the experimental factors involving the initial sample solution pH, adsorbent dosage, dye concentration, and contact time were used as the input variables to ANN and RF models to predict the removal percentage of SO and MV in their binary mixture. The validation of these models was tested using a test set (۸۱ data point). The statistical parameters calculated in the prediction of the removal percentage of the test set confirmed that the ANN model had a substantially better and more accurate prediction with respect to the RF model. In the third section of this thesis, the silica nanoparticles were extracted from stem sweep. The structural and morphological analysis of nanosilica was performed by the FT-IR, SEM, and BET techniques. The results obtained confirmed the presence of silica spherical nanoparticles with an average particle size of less than ۱۰۰ nm and a surface area of ۱۵۲ m²/g. For the first time, the performance of these nanoparticles (as an affordable and available absorbent) was studied for the simultaneous removal of crystal violet and methylene blue from aqueous solutions. The effects of different experimental parameters such as pH, adsorbent dose, initial concentration and contact time on the simultaneous removal of two dyes were studied and the optimal values were obtained. In the next step, the modeling of the absorption process in different conditions was performed using RF and MLR methods. The results obtained showed that the RF model had a better predictive power. Finally, in the last section of this thesis, walnut shell was modified using isopropylidine malonate in a solvent-free reaction. Using different techniques, the presence of carboxylic acid groups on the adsorbent surface was confirmed. The efficiency of the modified adsorbent for the simultaneous removal of methylene blue and lead was also studied. Optimization of the experimental parameters was carried out using the Box-Behnken design. The maximum adsorption capacity for removal of lead ions and methylene blue from bicomponent solutions was ۱۰۰.۴۰ and ۵۵.۷۸ mg/g, respectively. The reaction mechanism showed that the electrostatic forces play a major role in the adsorption process of lead, while for the adsorption of methylene blue on the adsorbent surface, the π-π interactions and hydrogen bonding play more important roles.