Effectiveness and Characterization of Novel Mineral Clay in Cd2+ Adsorption Process: Linear and Non-Linear Isotherm Regression Analysis

Abstract

The excellent adsorption properties of clay minerals make the optimization of heavy metal removal the subject of numerous research projects. In the present study, ASLAVITAL cosmetic clay (ACC) powder was applied for the removal of Cd2+ from water. The main deposit of ACC clay is the Pădurea Craiului Mountains in Romania. A wide range of morpho-structural approaches (SEM, EDX, FTIR, Raman, XRD) were used to characterize the morphology and elemental composition of the adsorbent. As expected for clay minerals, Al (wt(%) = 11.4 ± 0.9) and Si (wt(%) = 13.7 ± 1.4) are the main constituents of ACC. After adsorption, wt(%) = 0.2 ± 0.01 Cd2+ was detected in the sample. As proved before, the initial metal concentration is the primary influencing factor; therefore, batch adsorption of 10–160 mg/L Cd2+ was investigated. After 190 min, an efficiency of 99% was reached, and the quantity in equilibrium increased from 1–8 mg/g. The best fit in linear form was obtained for the Langmuir II. model, where R2 = 0.954 (RL = 0.037–0.027). Based on linear isotherm models, physical bonds formed between ACC and Cd2+ during the favorable adsorption. For the non-linear fits, the Liu model proved to be the best R2 = 0.965, χ2 = 1.101. Pseudo-II-order kinetic model described the experimental data R2 = 0.988–0.999; qexp and qcalc were almost identical (the differences ranged 0.03–0.34).

Linear and Nonlinear Regression Analysis for the Adsorption of Remazol Dye by Romanian Brewery Waste By-Product, Saccharomyces cerevisiae

“…Recently, one of the most widely used methods has been linear regression analysis, which reveals the best-fitting models. The linear regression method helps in quantifying the distribution of adsorbed substances, analyzing the adsorption system and checking the consistency of the theoretical assumptions about the adsorption isotherm model [ 46 ]. To calculate or predict the parameters of the models, the equations for each model were converted to linear form using the linear least squares method.…”

“…In this study, nonlinear versions of the two-parameter Langmuir, Freundlich, Temkin and Dubinin–Radushkevich and three-parameter Liu, Toth, Kahn, Sips, Redlich–Peterson and Radke–Prausnitz isotherm models were investigated with the help of OriginPro 8.5 software. The performances of these model predictions and the robustness of the results obtained were validated using statistical measures (namely, residual sum of squares error (ERRSQ/SSE), Chi-square (χ2), coefficient of determination (R 2 ), average relative error (ARE), hybrid fractional error function (HYBRID), Marquardt’s percent standard deviation (MPSD) and root mean square error (RMSE, polynomial p: the number of terms)) [ 41 , 42 , 46 ].…”

Statistical Optimization of Operational Parameters on Congo Red Adsorption Using Upscaled Polystyrene

“…The variable 'n' signifies the number of experiments done. Adsorption capabilities (mg/g) estimated by the model and the experiment are denoted by qe,cal and qe,exp, respectively [55].…”

Methods to prepare biosorbents and magnetic sorbents for water treatment: a review

“…The adsorption of different heavy metal cations, including trivalent chromium, hexavalent chromium (Essebaai et al 2022;Mdlalose et al 2021), lead (Jabłońska 2021;Jiang et al 2021a;Sun et al 2023a), zinc (Jabłońska 2021;Jiang et al 2021a), nickel (Jabłońska 2021), cadmium (Szewczuk-Karpisz et al 2022;Tonk et al 2022;Zeng et al 2023), and barium (Atun and Bascetin 2003;Mundim et al 2022) have been reported. The efficiency of clay and clay minerals in heavy metal adsorption has been linked to the clay's high cation exchange capacity, high specific surface area, and high swelling properties (Essebaai et al 2022).…”