scholarly journals Model-Based Optimization of Mannitol Production by Using a Sequence of Batch Reactors for a Coupled Bi-Enzymatic Process—A Dynamic Approach

Dynamics ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 134-154
Author(s):  
Gheorghe Maria ◽  
Ioana Mirela Peptănaru

Multi-enzymatic reactions can successfully replace complex chemical syntheses, using milder reaction conditions, and generating less waste. The present model-based analysis compares the performances of several optimally operated Batch Reactors (BR) with those of an optimally operated serial Sequence of BRs (SeqBR). In multi-enzymatic systems, SeqBR could be more advantageous and flexible, allowing the optimization of costly enzymes amounts used in each BR in the series. Exemplification was made for the bi-enzymatic reduction of D-fructose to mannitol by using MDH (mannitol dehydrogenase) and the NADH cofactor, with the in situ continuous regeneration of NADH at the expense of formate degradation in the presence of FDH (formate dehydrogenase). For such coupled enzymatic systems, the model-based engineering evaluations are difficult tasks, because they must account for the common species’ initial levels, their interaction, and their dynamics. The determination of optimal operating modes of sole BR or of a SeqBR turns into a multi-objective optimization problem with multiple constraints to be solved for every particular system. The study presents multiple elements of novelty: (i) the proof of higher performances of an optimal SeqBR (including N-BRs) compared to a sole optimal BR operated for N-number of runs and (ii) the effect of using a multi-objective optimization criteria on SeqBR adjustable dynamics.

2017 ◽  
Vol 68 (9) ◽  
pp. 2196-2203 ◽  
Author(s):  
Mara Crisan ◽  
Gheorghe Maria

Novel coupled enzymatic systems reported important applications in the industrial bio-catalysis. Multi-enzymatic reactions can successfully replace complex chemical syntheses, using milder reaction conditions, and generating less waste. For such systems acting simultaneously, the model-based engineering calculations (design, reactor operation optimization) are difficult tasks, because they must account for interacting reactions, differences in enzymes optimal activity domains and deactivation kinetics. The determination of the optimal operating mode (enzyme ratios, enzyme feeding policy, temperature, pH) often turns into a difficult multi-objective optimization problem with multiple constraints to be solved for every particular system. The paper focuses on applying a modular screening procedure that can identify the optimal operating policy of an enzymatic reactor, which minimizes the enzyme consumption, given the process kinetic model, and an imposed production capacity. Following an optimization procedure, the process effectiveness is evaluated in a systematic approach, by including simple batch reactor (BR), batch with intermittent addition of the key-enzyme following certain optimal policies (BRP). Exemplification is made for the case of the enzymatic reduction of D-fructose to mannitol by using suspended MDH (mannitol dehydrogenase) and NADH (Nicotinamide adenine dinucleotide) cofactor, with the in-situ continuous regeneration of the cofactor by the expense of formate degradation in the presence of suspended FDH (Formate dehydrogenase).


Processes ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 839
Author(s):  
Ibrahim M. Abu-Reesh

Microbial fuel cells (MFCs) are a promising technology for bioenergy generation and wastewater treatment. Various parameters affect the performance of dual-chamber MFCs, such as substrate flow rate and concentration. Performance can be assessed by power density ( PD ), current density ( CD ) production, or substrate removal efficiency ( SRE ). In this study, a mathematical model-based optimization was used to optimize the performance of an MFC using single- and multi-objective optimization (MOO) methods. Matlab’s fmincon and fminimax functions were used to solve the nonlinear constrained equations for the single- and multi-objective optimization, respectively. The fminimax method minimizes the worst-case of the two conflicting objective functions. The single-objective optimization revealed that the maximum PD ,   CD , and SRE were 2.04 W/m2, 11.08 A/m2, and 73.6%, respectively. The substrate concentration and flow rate significantly impacted the performance of the MFC. Pareto-optimal solutions were generated using the weighted sum method for maximizing the two conflicting objectives of PD and CD in addition to PD and SRE   simultaneously. The fminimax method for maximizing PD and CD showed that the compromise solution was to operate the MFC at maximum PD conditions. The model-based optimization proved to be a fast and low-cost optimization method for MFCs and it provided a better understanding of the factors affecting an MFC’s performance. The MOO provided Pareto-optimal solutions with multiple choices for practical applications depending on the purpose of using the MFCs.


PLoS ONE ◽  
2016 ◽  
Vol 11 (3) ◽  
pp. e0152057 ◽  
Author(s):  
Qing-chun Meng ◽  
Xiao-xia Rong ◽  
Yi-min Zhang ◽  
Xiao-le Wan ◽  
Yuan-yuan Liu ◽  
...  

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