Readily Reconfigurable Continuous-Stirred Tank Photochemical Reactor Platform

2021 ◽  
Author(s):  
Daniel Francis ◽  
A. John Blacker ◽  
Nikil Kapur ◽  
Stephen P. Marsden
Keyword(s):  
Stirred Tank ◽  
Continuous Stirred Tank

Removal of lead by sulfate-reducing bacteria in anaerobic continuous stirred tank reactors

2016 ◽  
Vol 14 (3) ◽  
pp. 557-561
Author(s):  
Nguyễn Thị Yên ◽  
Kiều Thị Quỳnh Hoa
Keyword(s):  
Sulfate Reducing Bacteria ◽  
Stirred Tank ◽  
Synthetic Wastewater ◽  
Terminal Electron Acceptor ◽  
Stirred Tank Reactors ◽  
Sulfate Reducing ◽  
Sulfide Production ◽  
Continuous Stirred Tank ◽  
Continuous Stirred Tank Reactors ◽  
Reducing Bacteria

Lead contaminated wastewater negatively impacts to living organisms as well as humans. In recent years, a highly promising biological process using the anaerobic production of sulfide ions by sulfate-reducing bacteria has presented itself as an alternative option for the removal of lead. This process is based on microbial utilization of electron donors, such as organic compounds (carbon sources), and sulfate as the terminal electron acceptor for sulfide production. The biogenic hydrogen sulfide reacts with dissolved heavy metals to form insoluble metal sulfide precipitates Removal of lead by an enriched consortium of sulfate-reducing bacteria (DM10) was evaluated sulfate reduction, sulfide production and lead precipitation. Four parallel anaerobic continuous stirred tank reactors (CSTR, V = 2L) (referred as R1 - R4) were fed with synthetic wastewater containing Pb2+ in the concentrations of 0, 100, 150 and 200 mg L-1 of lead and operated with a hydraulic retention time of 5 days for 40 days. The loading rates of each metal in R1- R4 were 0, 20, 30 and 40 mg L-1 d-1, respectively. The results showed that there was no inhibition of SRB growth and that lead removal efficiencies of 99-100% for Pb2+ were achieved in R2 (100 mg L-1) and R3 (150 mg L-1) throughout the experiment. For the highest lead concentration of  200 mg L-1, a decrease in efficiency of removal (from 100 to 96%) was observed at the end of the experiment. The obtained result of this study might help for a better control operation and performance improvements of reactors.

scholarly journals Process Engineering of the Acetone-Ethanol-Butanol (ABE) Fermentation in a Linear and Feedback Loop Cascade of Continuous Stirred Tank Reactors: Experiments, Modeling and Optimization

Fuels ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 108-129
Author(s):  
Katja Karstens ◽  
Sergej Trippel ◽  
Peter Götz
Keyword(s):  
Feedback Loop ◽  
Early Stage ◽  
Formation Rate ◽  
Abe Fermentation ◽  
Operating Conditions ◽  
Stirred Tank ◽  
Second Phase ◽  
Stirred Tank Reactors ◽  
Continuous Stirred Tank ◽  
Continuous Stirred Tank Reactors

The production of butanol, acetone and ethanol by Clostridium acetobutylicum is a biphasic fermentation process. In the first phase the carbohydrate substrate is metabolized to acetic and butyric acid, in the following second phase the product spectrum is shifted towards the economically interesting solvents. Here we present a cascade of six continuous stirred tank reactors (CCSTR), which allows performing the time dependent metabolic phases of an acetone-butanol-ethanol (ABE) batch fermentation in a spatial domain. Experimental data of steady states under four operating conditions—with variations of the pH in the first bioreactor between 4.3 and 5.6 as well as the total dilution rate between 0.042 h−1 and 0.092 h−1—were used to optimize and validate a corresponding mathematical model. Beyond a residence time distribution representation and substrate, biomass and product kinetics this model also includes the differentiation of cells between the metabolic states. Model simulations predict a final product concentration of 8.2 g butanol L−1 and a productivity of 0.75 g butanol L−1 h−1 in the CCSTR operated at pHbr1 of 4.3 and D = 0.092 h−1, while 31% of the cells are differentiated to the solventogenic state. Aiming at an enrichment of solvent-producing cells, a feedback loop was introduced into the cascade, sending cells from a later state of the process (bioreactor 4) back to an early stage of the process (bioreactor 2). In agreement with the experimental observations, the model accurately predicted an increase in butanol formation rate in bioreactor stages 2 and 3, resulting in an overall butanol productivity of 0.76 g L−1 h−1 for the feedback loop cascade. The here presented CCSTR and the validated model will serve to investigate further ABE fermentation strategies for a controlled metabolic switch.

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