Low temperature carbonized mesoporous graphitic carbon for tetracycline adsorption: Mechanistic insight and adaptive neuro-fuzzy inference system modeling

Abstract

Tetracycline (TC) contamination is prevalent in aquatic systems due to its uncontrolled and excessive use for medical, livestock, and veterinary purposes. Herein, we produced low-temperature carbonized mesoporous activated carbon (AC) from rubber fig leaves for TC removal. AC surface was coarse, patchy, and covered with flakes possessing uneven pores. Statistical physics model was employed to explore the TC adsorption mechanism wherein the double-layer model with two energies outperformed the others. The adsorption energies were <40.0 kJ/mol which suggested physisorption, and the results were consistent with thermodynamic studies as well. The number of molecules attached per site (n) was 2.11 which attested multi-molecular adsorption. The adsorption capacity at saturation (Qm) was estimated as 149.31 mg/g significantly higher than a few of the reported values. Later, the adsorption dataset was successfully modeled by adaptive neuro-fuzzy inference system modeling (ANFIS) – an artificial intelligent tool to predict the adsorption process.