Dynamic Modeling of a Fermentation Process with Ex situ Butanol Recovery (ESBR) for Continuous Biobutanol Production

Abstract

A dynamic model for a fermentation process equipped with an ex situ butanol recovery (termed “ESBR” hereafter) system is proposed for continuous production of biobutanol. Since the proposed ESBR system integrates a fermenter with a stirred-tank-type adsorption column, the dynamic model includes kinetic models for both the fermentation (the Monod/Luedeking-Piret model) and the adsorption (the extended Langmuir model). Parameters in the kinetic models are initially determined using data from batch and fed-batch fermentation experiments with in situ butanol recovery (ISBR). The initially developed model is then used to find a feasible operating condition for an experimental ESBR system, and its parameter values are further tuned using experimental data from the proposed ESBR system for accurate predictions in the butanol and glucose concentration range seen in the ESBR operation. The approach to improving the model accuracy consists of two steps: (1) identifying the critical parameters by performing a sensitivity analysis and (2) re-estimating the selected parameters using data obtained during cyclic operation of the proposed ESBR system. Accordingly, the developed model based on the kinetics for both fermentation and adsorption can describe and predict the behavior of the proposed ESBR system. Thus, the proposed systematic approach provides a reliable platform for the optimal scale-up design and control studies of the ESBR system.

Kinetic study of butanol production from mixtures of glucose and xylose and investigation of different pre-growth strategies

“…Parameter estimates for all 4 datasets given in Table 2 were interpreted to illustrate the effects of different pre-growth strategies on the fermentation kinetics. [27] and estimations in modeling studies [24]. Further experimental evidence confirms that the inhibitory effects of butanol on C. acetobutylicum were more pronounced in xylose-grown cells than in glucose-grown cells, and glucose and xylose permease were inhibited when butanol concentration reached 12 and 8 g/l, respectively [14].…”

“…The bounds for yield coefficients were determined using stoichiometric relations between the components [16,26]. The rest of the parameter bounds was taken from literature [24,29]. The optimization problem was initialized with the initial points, which were the middle points between the upper and lower bounds of the parameters.…”

“…Despite their rich information content, the complexity level in the models of Shinto et al (2007Shinto et al ( , 2008) is high and they require larger experimental datasets for estimation of larger number of parameters necessary to construct the models. On the contrary, traditional unstructured models are simpler and easier to interpret, thus they are still actively being used for describing butanol production by fermentation [24].…”

Butanol production by Clostridium acetobutylicumATCC 824 using electro‐fermentation in culture medium supplemented with butyrate and neutral red

“…Lim et al 26 . and Eom et al 27 . modeled the butanol produced by a recombinant strain of C. acetobutylicum .…”

Increased Butanol Yields through Cosubstrate Fermentation of Jerusalem Artichoke Tubers and Crude Glycerol by Clostridium pasteurianum DSM 525

“…4,5 However, in the past decade, the interest in butanol fermentation has been revived, which led multiple studies on strain development, fermentation improvement, and in situ product removal technologies. 6−9 This has resulted in a major reduction of product toxicity to the respective microorganisms, improved substrate utilization, as well as the overall performance of the bioreactors. Nevertheless, the high cost and seasonal availability of conventional substrates (corn, molasses) are still a disadvantage for fermentative butanol processes compared to petroleum-based production.…”