Graphene oxide-sulfated lanthanum oxy-carbonate nanocomposite as an adsorbent for the removal of malachite green from water samples with application of statistical optimization and machine learning computations

Sulfated lanthanum oxy-carbonate nanorods (S-La2O2(CO3) NRs) was synthesized by the reverse micelle microemulsion method and then used to modify graphene oxide nanosheets to synthesize of graphene oxide-sulfated lanthanum oxy-carbonate (GO-S-La2O2(CO3)) nanocomposite. By characterization of SLa2O2(CO3) NRs and GO-S-La2O2(CO3) nanocomposite by the Fourier Transform-Infrared (FT-IR) Spectrophotometry, Field Emission-Scanning Electron Microscopy (FE-SEM), Energy-dispersive X-ray spectroscopy (EDS), Transmission Electron Microscopy (TEM) and X-ray diffraction analysis (XRD), GOS-La2O2(CO3) was used for treatment of malachite green (MG). To find the optimum removal percentage (RP), influencing parameters were investigated by the response surface methodology based on central composite design (RSM-CCD). Adsorption mechanism was evaluated by Dubinin-Radushkevich (D-R), Langmuir, Temkin, Freundlich (two parameter equations) and Sips (Three parameter equations) isotherms and based on the results the adsorption of MG into the GO-S-La2O2(CO3) nanocomposite obeyed by the Freundlich isotherm with the maximum adsorption capacity of 555.5 mg g(-1). Also, the results of kinetic analysis show that the adsorption of MG onto the GO-S-La2O2(CO3) nanocomposite followed by the pseudo second order kinetic model. For estimation of adsorption behavior, different machine learning techniques are used and based on the results; ANFIS model has the confidential operation because of fuzzy procedure and flexibility of data mining in distributed adsorption data. (C) 2022 The Society of Powder Technology Japan. Published by Elsevier BV and The Society of Powder Technology Japan. All rights reserved.