ANN Modeling for Rhodamine B Adsorption Using Pristine and NaOH-Activated Mesoporous Sewage Sludge Biochars: Kinetic, Isotherm, Thermodynamic, and Regeneration Studies

Abstract

Synthetic dyes are discharged into acequias, resulting in pernicious effects on ecological and human health, and their remediation to accomplish the United Nations Sustainable Development Goals (SDG3, 6) is imperative. As a corollary, the present research highlights the synthesis of pristine sewage sludge biochar (SSB) and NaOH-functionalized sewage sludge-based biochar (NaOH-SSB) adsorbents for the decolorization of Rhodamine B (RhB) dyeing wastewater. NaOH-SSB exhibited maximum adsorption capacity values of 8.72 mg g^–1, twice that of SSB (4.29 mg g^–1) at RhB concentrations of 15 mg L^–1. The adsorption process was modeled using the Levenberg–Marquardt Back Propagation Algorithm optimized by Genetic Algorithm to train the Artificial Neural Network and predict RhB removal using biochar adsorbents. The comparison of ANN predictions with experimental batch adsorption studies yielded higher coefficients of determination (R²- SSB: 0.983, NaOH-SSB: 0.9944) and lower mean square errors (MSE- SSB: 0.4352, NaOH-SSB: 0.2999), demonstrating favorable predictability for multifactor adsorption.