An efficient heterogeneous solid acid catalyst derived from sewage sludge for the catalytic transformation of sludge into biodiesel: Preparation, characterization, and arylation process modeling

• Published in: Journal of cleaner production Vol. 355; p. 131809
• Main Authors: Hatami, Behnam, Ebrahimi, Ali Asghar, Ehrampoush, Mohammad Hassan, Salmani, Mohammad Hossein, Tamaddon, Fatemeh, Mokhtari, Mehdi
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 25.06.2022
• Subjects: Artificial intelligence; Arylation; Biodiesel; Hybrid model; Mesoporous solid acid catalyst; Sewage sludge; Arylation; Hybrid model; Mesoporous solid acid catalyst; Biodiesel; Sewage sludge; Artificial intelligence
• ISSN: 0959-6526; 1879-1786
• DOI: 10.1016/j.jclepro.2022.131809

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. Sewage sludge was converted to granular activated carbon and then arylated with 4-sulfophenyl groups in a reducing agent-free reaction. Hybrid models of the adaptive neuro-fuzzy inference system (ANFIS) with evolutionary algorithms were used to model and optimize the arylation parameters. The catalyst granules were coated on the polystyrene grains to enhance the chemical stability, reusability, and recoverability. The catalytic performance of the obtained solid acid catalyst in the transesterification of sludge-derived lipids was evaluated. [Display omitted] •Hazardous sludge was simultaneously converted to an acidic catalyst and biodiesel.•Optimizing the arylation parameters by PSO-FIS enhanced the PhSO3H density (∼26%).•Coating the catalyst on the polystyrene grains greatly improved its recoverability.•The coating method ensured the high chemical stability and reusability of catalyst.•A 17.34% of biodiesel yield showed excellent catalytic activity of the catalyst.