Development of reactor model for glucose isomerization catalyzed by whole-cell immobilized glucose isomerase

Vasić-Rački, Đurđa; Pavlović, Nediljko; Čižmek, S.; Dražić, Mensura; Husadžić, B.

doi:10.1007/bf00387415

Cited by 22 publications

(11 citation statements)

References 10 publications

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“…where vm and km are apparent rate constants and both can have negative values [4,5,10]. k~ is a function of temperature and initial substrate concentration So.…”

Section: Vp K S )mentioning

confidence: 99%

“…Effects of glucose fractional conversion and operating time on the optimum operating temperature significant compared to the operating period. But in HFCS industry So is almost constant (about 2.8 mol/1) and also the degree of conversion (45%) [10,12]. Therefore, the operating time can be considered as the main factor in selecting the optimum operating temperature.…”

Section: Effect Of So and X On The Optimum Operating Temperaturementioning

confidence: 99%

“…(14) and (16) were determined using the experimental data available in the literature for temperature range of 60-80 ~ [7,8]. Least squares fit of the *Density of the catalyst particle used in calculations = 304.21 g/1 [10] experimental data showed that the kinetic parameters vary with temperature according to Arrhenius equation. The correlation coefficients of fittings are greater than 99%:…”

Section: Evaluation Of Kinetic Parametersmentioning

confidence: 99%

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Simulation of glucose isomerase reactor: optimum operating temperature

Abu-Reesh

Faqir

1996

Bioprocess Engineering

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“…where vm and km are apparent rate constants and both can have negative values [4,5,10]. k~ is a function of temperature and initial substrate concentration So.…”

Section: Vp K S )mentioning

confidence: 99%

Section: Effect Of So and X On The Optimum Operating Temperaturementioning

confidence: 99%

Section: Evaluation Of Kinetic Parametersmentioning

confidence: 99%

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Simulation of glucose isomerase reactor: optimum operating temperature

Abu-Reesh

Faqir

1996

Bioprocess Engineering

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“…In modeling continuous immobilized enzyme packed bed reactors, the following simplifying assumptions are made (Illanes et al, 1992;Roles and Tilberg, 1979;Vasic-Racki et al, 1991): (1) the¯ow of substrate through the reactor is ideal plug¯ow; (2) the immobilized enzyme eectiveness factor is assumed to be unity (no diusional limitations); (3) the enzyme deactivation is a rather slow process when compared to the mean residence time of reactants; and (4) the residual enzyme activity is considered as a weak function of substrate concentration along the reactor length. Under these assumed conditions the packed bed design equation is given by (Abu-Reesh and Faqir, 1996;Hass et al, 1974) …”

Section: Mathematical Modelmentioning

confidence: 99%

Optimal temperature policy for immobilized enzyme packed bed reactor performing reversible Michaelis–Menten kinetics using the disjoint policy

Faqir¹,

Attarakih²

2001

Biotech & Bioengineering

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The optimal temperature policy that maximizes the time-averaged productivity of a continuous immobilized enzyme packed bed reactor is determined. This optimization study takes into consideration the enzyme thermal deactivation with substrate protection during the reactor operation. The general case of reversible Michaelis-Menten kinetics under constant reactor feed flow rate is assumed. The corresponding nonlinear optimization problem is solved using the calculus of variations by applying the disjoint policy. This policy reduces the optimization problem into a differential-algebraic system, DAE. This DAE system defines completely the optimal temperature-time profiles. These profiles depend on the kinetic parameters, feed substrate concentration, operating period, and the residence time and are characterized by increasing form with time. Also, general analytical expressions for the slopes of the temperature and residual enzyme activity profiles are derived. An efficient solution algorithm is developed to solve the DAE system, which results into a one-dimensional optimization problem with simple bounds on the initial feed temperature. The enzymatic isomerization of glucose into fructose is selected as a case study. The computed productivities are very close to that obtained by numerical nonlinear optimization with simpler problem to solve. Moreover, the computed conversion profiles are almost constant over 90% of the operating periods, thus producing a homogeneous product.

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“…Lortie and Pelletier [2] have shown that plug-flow reactor model with external mass-transfer resistance can represent adequately a fixed-bed IME reactor for moderate or low dispersion. Axial dispersed plug flow model showed to be superior in predicting the performance of packed bed reactor for isomerization of glucose to fructose [3,4,5]. The value of Pe number is a measure of the degree of dispersion.…”

Section: List Of Symbolsmentioning

confidence: 99%

Predicting the performance of immobilized enzyme reactors using reversible Michaelis–Menten kinetics

Abu-Reesh

1997

Bioprocess Engineering

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A general mathematical model is developed in the present work for predicting the steady state performance of immobilized enzyme reactor performing reversible Michaelis -Menten kinetics. The model takes into account the effect of external diffusional limitations, the axial dispersion and the equilibrium constant on reactor performance quantified as relative substrate conversion and yield.The performance of reactor is characterized using the dimensionless parameters of Damkohler number, Stanton number, Peclet number, the equilibrium constant and the dimensionless input substrate concentration.The reactor performance is described for the two extreme cases of plug flow reactor (PFR) and continuous stirred tank reactor (CSTR) in addition to the intermediate case of dispersed plug flow reactor (DPFR).The performance of reactor is compared for the two cases of zero order and reversible first order kinetics. List of symbolsC [-] dimensionless substrate concentration S=K m D z m 2 = h axial dispersion coefficient E mg=l concentration of active enzyme F l=h flow rate K h ÿ 1 pseudo-first order reaction rate constant V m = K m K e [-] equilibrium constant K L a h ÿ 1 mass transfer coefficient in liquid film K m mole=l apparent Michaelis constant K p mole=l Michaelis constant for product K s mole=l Michaelis constant for substrate k ÿ 1 ; k 2 h ÿ 1 rate constants k 1 ; k ÿ 2 1=mg:h rate constants L m reactor length P mole=l product concentration RS mole=l:h reaction rate S mole=l substrate concentration u m=h interstitial liquid velocity V l reactor volume V m mole=l:h maximum apparent reaction rate V p mole=l:h maximum reaction rate for product V s mole=l:h maximum reaction rate for substrate x [-] dimensionless axial coordinate z=L x 0 [-] dimensionless axial coordinate 1 ÿ x X [-] substrate conversion X r [-] relative substrate conversion X=Xe Y [-] dimensionless substrate concentration C ÿ C e = C o ÿ C e z m axial coordinate in reactor Dimensionless numbers Da [-] Damkohler number V m = K m : K L a Pe [-] Peclet number uL=D z St [-] Stanton number K L a:L=u for PFR, K L a:V=F for CSTR Subscripts 0 inlet substrate concentration e equilibrium substrate concentration i interfacial substrate concentration j the number of steps in the axial direction L effluent substrate concentration IntroductionEnzyme immobilization offers a number of advantages over enzymes in suspension. Immobilization permits the reuse of the enzyme and may provide a better environment for catalyst activity and also it reduces the cost of downstream processing in addition to good product quality. Most of the cases, enzyme immobilization is accompanied by mass transfer limitations which is present even in laboratory scale reactors. Different factors have to be taken into consideration in the modeling of immobilized enzyme (IME) reactors such as: (i) mass transfer limitation; (ii) the dispersion effects; (iii) the stability of the enzyme; (iv) the heat transfer effects; and (v) the kinetics of the enzyme reaction. Quantitative knowledge of the effect of t...

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Development of reactor model for glucose isomerization catalyzed by whole-cell immobilized glucose isomerase

Cited by 22 publications

References 10 publications

Simulation of glucose isomerase reactor: optimum operating temperature

Simulation of glucose isomerase reactor: optimum operating temperature

Optimal temperature policy for immobilized enzyme packed bed reactor performing reversible Michaelis–Menten kinetics using the disjoint policy

Predicting the performance of immobilized enzyme reactors using reversible Michaelis–Menten kinetics

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