FeS-biochar and Zn(0)-biochar for remediation of redox-reactive contaminants

Artificial intelligence-enabled optimization of Fe/Zn@biochar photocatalyst for 2,6-dichlorophenol removal from petrochemical wastewater: A techno-economic perspective

While numerous studies have addressed the photocatalytic degradation of 2,6-dichlorophenol (2,6-DCP) in wastewater, an existing research gap pertains to operational factors' optimization by non-linear prediction models to ensure a cost-effective and sustainable process. Herein, we focus on optimizing the photocatalytic degradation of 2,6-DCP using artificial intelligence modeling, aiming at minimizing initial capital outlay and ongoing operational expenses. Hence, Fe/Zn@biochar, a novel material, was synthesized, characterized, and applied to harness the dual capabilities of 2,6-DCP adsorption and degradation. Fe/Zn@biochar exhibited an adsorption energy of -21.858 kJ/mol, effectively capturing the 2,6-DCP molecules. This catalyst accumulated photo-excited electrons, which, upon interaction with adsorbed oxygen and/or dissolved oxygen generated •O2-. The •OH radicals could also be produced from h+ in the Fe/Zn@biochar valence band, cleaving the C-Cl bonds to Cl- ions, dechlorinated byproducts, and phenols. An artificial neural network (ANN) model, with a 4-10-1 topology, "trainlm" training function, and feed-forward back-propagation algorithm, was developed to predict the 2,6-DCP removal efficiency. The ANN prediction accuracy was expressed as R2 = 0.967 and mean squared error = 5.56e-22. The ANN-based optimized condition depicted that over 90% of 2,6-DCP could be eliminated under C0 = 130 mg/L, pH = 2.74, and catalyst dosage = 168 mg/L within ∼4 h. This optimum condition corresponded to a total cost of $7.70/m3, which was cheaper than the price estimated from the unoptimized photocatalytic system by 16%. Hence, the proposed ANN could be employed to enhance the 2,6-DCP photocatalytic degradation process with reduced operational expenses, providing practical and cost-effective solutions for petrochemical wastewater treatment.

Two-step ball milling-assisted synthesis of N-doped biochar loaded with ferrous sulfide for enhanced adsorptive removal of Cr(Ⅵ) and tetracycline from water

Nitrogen-doped biochar loaded with FeS (FeS@NBC_BM) was synthesized by two-step ball milling processes. Characterization results revealed that N-doping process successfully introduced pyridinic, pyrrolic, and graphitic N structures, and FeS was subsequently embedded in N-doped biochar (NBC_BM). The resultant FeS@NBC_BM presented predominant adsorption capacity for Cr(VI) (194.69 mg/g) and tetracycline (TC, 371.29 mg/g) compared with BC (27.28 and 37.89 mg/g) and NBC_BM (71.26 and 81.26 mg/g). In addition, the Cr(VI)/TC elimination process by FeS@NBC_BM was basically stable with multiple co-existing ions with slight decrease on adsorption performance after three desorption-regeneration cycles. Most importantly, FeS@NBC_BM was found to achieve Cr(VI) elimination not only by electrostatic attraction, ion exchange and complexation, but also by electrons-triggered reduction provided by different species of N, Fe²⁺ as well as S(Ⅱ). Meantime, pore filling, hydrogen bonding, and π-π stacking interactions were demonstrated to contribute to TC adsorption. These results suggested the co-modification of N-doping and FeS loading by ball milling as an innovative decorating method for biochar to adsorptive purification of Cr(VI) and TC-contaminated water.