Abstract

Homogeneous and heterogeneous catalysts for biodiesel production are facing challenges such as corrosion, leaching of active sites, and separation difficulties. Herein, a safe, chemically stable, and high-recoverable heterogeneous solid acid catalyst was fabricated and successfully evaluated in the catalytic transesterification of sludge-derived lipids. To this end, sludge-based granular activated carbon (SBGAC) was prepared and arylated with 4-sulfobenzenediazonium chloride in a reducing agent-free reaction. Hybrid models of the adaptive neuro-fuzzy inference system (ANFIS) with evolutionary algorithms such as the genetic algorithm (GA-FIS), particle swarm optimization (PSO-FIS), and ant colony optimization (ACO-FIS) were developed to model and optimize the empirical relationship between arylation parameters. The highest PhSO3H density (1.36 mmol/g) was obtained at 70 °C, 7.6 min arylation time, and a mass ratio of acid to SBGAC of 9.83 using the PSO-FIS model, which was ∼26% more than the value obtained without optimization. Loading 20 wt% of this catalyst in the transesterification of sludge-originated lipid at 70 °C yielded 17.34% (w/w dry sludge) biodiesel after 14 h. Coating the catalyst granules on the polystyrene grains was significantly enhanced its recoverability from the reaction mixture. Moreover, the spent catalyst exhibited good chemical stability and reusability after the ninth transesterification cycle.