Biohydrogen production via green silver nanoparticles synthesized through biomass of Ulva lactuca bloom. (July 2023)

• Record Type: Journal Article
• Authors: Dogmaz, Sema; Cavas, Levent
• Is Part Of: Bioresource technology. Volume 379(2023)
• Publication Date: 2023-07
• Subjects: Artificial neural network -- Green synthesis -- Green chemistry -- Nanotechnology -- Seaweed; Biomass -- Periodicals; Biomass energy -- Periodicals; Bioremediation -- Periodicals; Agricultural wastes -- Periodicals; Factory and trade waste -- Periodicals; Organic wastes -- Periodicals; Bioénergie -- Périodiques; Déchets agricoles -- Périodiques; Déchets industriels -- Périodiques; Déchets organiques -- Périodiques; Déchets (Combustible) -- Périodiques; 662.88
• DOI: 10.1016/j.biortech.2023.129028
• Languages: English
• ISSNs: 0960-8524

Abstract

Graphical abstract: Highlights: Ulva lactuca is a green marine seaweed in the Mediterranean Sea. Biohydrogen was successfully produced using green-synthesized AgNPs based on Ulva lactuca . In the study, 94.4 mL of biohydrogen was produced at the conditions of 50 °C, 250 rpm, 150 mM NaBH4 concentration and pH 7. Artificial neural network was used to model the data related to biohydrogen production. The proposed methodology provides an alternative solution to utilize algal bio-waste. Abstract: Ulva lactuca is a marine green seaweed. Its bloom based biomass accumulated in the İzmir bay and is collected by local authorities. In this investigation, an alternative solution was proposed to utilize the biomass of U. lactuca to produce biohydrogen via green synthesized silver nanoparticles. According to the results, the optimum conditions related to silver nanoparticle production such as pH, temperature, biomass concentration, silver nitrate concentrations, and incubation time were determined to be 11, 25 °C, 10 mg/mL, 4 mM, and 3 days, respectively. Effective conditions for biohydrogen production such as pH, temperature, agitation rate, and sodium borohydride concentration were found to be 7, 50 °C, 250 rpm and 150 mM, respectively. These parameters are also modelled with an artificial neural network. The data presented here provide recommendations for producing biohydrogen from waste algae and helping reduce carbon emissions for better environment and future.