Adsorption Mechanism of Bentonite with Dispersed Chitosan for Cadmium Ions

Preparation of Amphiphilic Chitosan-Loaded Bentonite Adsorbent and Its Performance in Removing Organic Matter from Coking Wastewater

An amphiphilic chitosan-loaded bentonite adsorbent (C18CTS-BT) was prepared for the efficient removal of organic matter from coking wastewater. The structure and surface morphology of adsorbents were characterized by FT-IR, XRD, and SEM. The removal of those organics by C18CTS-BT was investigated by comparing the adsorption performances of C18CTS-BT with bentonite (BT) and chitosan-loaded bentonite (CTS-BT). The results showed that compared with BT and CTS-BT, C18CTS-BT showed the performance advantages of having a low dosage, wide pH range, and short adsorption equilibrium time. The optimized treatment process was as follows: the adsorbent dosage was 1.5 g·L^-1, the adsorption time was 60 min, and the pH of the system was 7.0. The chemical oxygen demand (COD) of the coking wastewater treated with BT, CTS-BT, and C18CTS-BT decreased from 342 mg·L^-1 in the raw water to 264 mg·L^-1, 218 mg·L^-1, and 146 mg·L^-1, corresponding to COD removal rates of 22.81%, 36.26%, and 57.31%, respectively. The results of GC-MS analysis also confirmed that C18CTS-BT could remove most of the organic compounds in coking wastewater, especially long-chain alkanes and their derivatives. The hydrophobic modification of the adsorbent material can effectively improve the removal performance of organic compounds from coking wastewater.

Comparative Studies of RSM, RSM–GA and ANFILS for Modeling and Optimization of Naphthalene Adsorption on Chitosan–CTAB–Sodium Bentonite Clay Matrix

The aim of this article was to compare the predictive abilities of the optimization techniques of response surface methodology (RSM), the hybrid of RSM–genetic algorithm (RSM–GA) and adaptive neuro-fuzzy interference logic system (ANFILS) for design responses of % removal of naphthalene and adsorption capacity of the synthesized composite nanoparticles of chitosan–cetyltrimethylammonium bromide (CTAB)–sodium bentonite clay.  The process variables considered were surfactant concentration, , activation time, ,  activation temperature, , and chitosan dosage, .  The ANFILS models showed better modeling abilities of the adsorption data on the synthesized composite adsorbent than those of ANN for reason of lower % mean absolute deviation, lower % error value, higher coefficient of determination, , amongst others and lower error functions’ values than those obtained using ANN for both responses.  When applied RSM, the hybrid of RSM–genetic algorithm (RSM–GA) and ANFILS 3–D surface pot optimization technique to determine the optimal conditions for both responses, ANFILS was adjudged the best.  The ANFILS predicted optimal conditions were = 116.00 mg/L, = 2.06 h, = 81.2oC and = 5.20 g.  Excellent agreements were achieved between the predicted responses of 99.055% removal of naphthalene and 248.6375 mg/g adsorption capacity and their corresponding experimental values of 99.020% and 248.86 mg/g with % errors of -0.0353 and 0.0894 respectively.  Hence, in this study, ANFILS has been successfully used to model and optimize the conditions for the treatment of industrial wastewater containing polycyclic aromatic compounds, especially naphthalene and is hereby recommended for such and similar studies.