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Highlights Non-carbonate components of BG11 media impact TIC calculation on average 4.00 mg/L at high pH. BG11 media non-carbonate alkalinity (NCA) varies with pH: NCA (meq/L) = 0.0393×e0.2075×pH+ (2.086×10-9)e1.860×pH.Monod kinetic constants with CO2, HCO3-, and CO32-as inorganic carbon sources are improved from a previous report.Kinetic constants continue to be the only known reports considering multiple inorganic carbon sources.Algal stoichiometric reactions are developed that account for variation in cell content and carbon source. Abstract.Due to increasing atmospheric CO2, algal growth systems at high pH are of interest to support enhanced diffusion and carbon capture. Given the interactions between algal growth, pH, and alkalinity, data from Watson and Drapcho (2016) were re-examined to determine the impact of the non-carbonate constituents in BG11 media on estimates of Monod kinetic parameters, biomass yield, and cell stoichiometry. Based on a computational method, non-carbonate alkalinity (NCA) in BG11 media varies with pH according to: NCA (meq/L) = 0.0393×e0.2075×pH + (2.086×10-9)e1.860×pH (R2 = 0.999) over the pH range of 10.3 – 11.5. Updated maximum specific growth rates were determined to be 0.060, 0.057, and 0.051 hr-1 for CO2, HCO3, and CO3, respectively. Generalizable stoichiometric algal growth equations that consider variable nutrient ratios and multiple inorganic carbon species were developed. Improved kinetic and stoichiometric parameters will serve as the foundation for a dynamic mathematical model to support the design of high pH algal carbon capture systems. Keywords: Algae, Alkalinity, Carbon Abatement, Carbon Capture, Kinetics, Stoichiometry, Total Inorganic Carbon.
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Analytical solution for a hybrid Logistic‐Monod cell growth model in batch and continuous stirred tank reactor culture
Abstract Monod and Logistic growth models have been widely used as basic equations to describe cell growth in bioprocess engineering. In the case of the Monod equation, the specific growth rate is governed by a limiting nutrient, with the mathematical form similar to the Michaelis–Menten equation. In the case of the Logistic equation, the specific growth rate is determined by the carrying capacity of the system, which could be growth‐inhibiting factors (i.e., toxic chemical accumulation) other than the nutrient level. Both equations have been found valuable to guide us build unstructured kinetic models to analyze the fermentation process and understand cell physiology. In this work, we present a hybrid Logistic‐Monod growth model, which accounts for multiple growth‐dependent factors including both the limiting nutrient and the carrying capacity of the system. Coupled with substrate consumption and yield coefficient, we present the analytical solutions for this hybrid Logistic‐Monod model in both batch and continuous stirred tank reactor (CSTR) culture. Under high biomass yield (Yx/s) conditions, the analytical solution for this hybrid model is approaching to the Logistic equation; under low biomass yield condition, the analytical solution for this hybrid model converges to the Monod equation. This hybrid Logistic‐Monod equation represents the cell growth transition from substrate‐limiting condition to growth‐inhibiting condition, which could be adopted to accurately describe the multi‐phases of cell growth and may facilitate kinetic model construction, bioprocess optimization, and scale‐up in industrial biotechnology.
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- Award ID(s):
- 1805139
- PAR ID:
- 10126082
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Biotechnology and Bioengineering
- Volume:
- 117
- Issue:
- 3
- ISSN:
- 0006-3592
- Format(s):
- Medium: X Size: p. 873-878
- Size(s):
- p. 873-878
- Sponsoring Org:
- National Science Foundation
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