Process simulation and optimization for enhanced biophotolytic hydrogen production from green algae using the sulfur deprivation method. (19th April 2021)

• Record Type: Journal Article
• Authors: Bechara, Rami; Azizi, Fouad; Boyadjian, Cassia
• Is Part Of: International journal of hydrogen energy. Volume 46:Number 27(2021)
• Page Start: 14096
• Page End: 14108
• Publication Date: 2021-04-19
• Subjects: Green algae -- Hydrogen -- Sulfur controlled -- Simulation -- Optimization -- Logistic regression; Hydrogen as fuel -- Periodicals; Hydrogène (Combustible) -- Périodiques; Hydrogen as fuel; Periodicals; 665.81
• DOI: 10.1016/j.ijhydene.2021.01.115
• Languages: English
• ISSNs: 0360-3199

Abstract

Abstract: This article explores the modeling, simulation and optimization of a biophotolytic cyclic process for enhanced hydrogen production from microalgae, employing the sulfur deprivation method. To achieve sulfur deprivation, each process cycle contained two temporally separated steps of sulfur-controlled algae growth and sulfur-deprived anaerobic hydrogen production. Reaction kinetics were modeled via an empirical logistic model. Reaction times, sulfate concentrations, and medium pH levels of each cycle were controlled to optimize the rate and yield of hydrogen production. Consequently, 65% and 23% improved values were obtained, respectively, with a smaller total process time (−11%), higher ratio of algae growth-to-hydrogen production time (29% vs. 21%), buffered pH (7.8), controlled sulfate injection and intermediary algae concentrations. Two- and 15-times higher hydrogen yields were obtained for 2- and 12-times lower initial algae concentrations. The proposed method is a significant tool for the design and optimization of a process for enhanced hydrogen production from microalgae. Graphical abstract: Image 1 Highlights: First-time process simulation and optimization for hydrogen production from algae. Sulfur deprivation achieved via temporal separation of algae growth/H2 production. Embedded logistic kinetic model validated with experimental results. Optimization of reaction variables: reaction time, sulfate concentration and pH. Improved hydrogen yield (54%) and production rate (17%) by optimized variables.