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Performance features for urea hydrolysis in a CSTR with microencapsulated urease

K B Lee1, D K Boadi, R J Neufeld

  • 1Department of Chemical Engineering, McGill University, Montreal, Quebec

Artificial Cells, Blood Substitutes, and Immobilization Biotechnology
|January 1, 1995
PubMed
Summary

This study investigated factors affecting continuous stirred-tank reactor (CSTR) performance with microencapsulated urease. Including pH, product inhibition, and substrate depletion limitations in the model resulted in lower urea conversion but maintained higher substrate concentrations.

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Area of Science:

  • Biochemical Engineering
  • Chemical Reaction Engineering

Background:

  • Continuous stirred-tank reactor (CSTR) operations are crucial for processes like dialysate regeneration.
  • Microencapsulated enzymes offer advantages in stability and reusability for such applications.

Purpose of the Study:

  • To analyze factors influencing steady-state performance of CSTR with microencapsulated urease.
  • To evaluate the impact of enzyme activity, microcapsule size, pH, product inhibition, and substrate depletion on urea conversion and effectiveness factor.

Main Methods:

  • Development and application of a theoretical model for CSTR performance.
  • Simulation of eight case studies examining individual and combined limiting factors.
  • Analysis of microcapsule diameter effects (5 and 500 microns) on reaction kinetics.

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Main Results:

  • The base case model, incorporating all limiting factors, predicted the lowest urea conversion.
  • Effectiveness factor varied with enzyme activity, with Michaelis-Menten kinetics alone showing highest factors at low activities (<1 mM/s).
  • High enzyme activities (>1 mM/s) led to lower effectiveness factors due to substrate depletion below Km,o, though overall conversion could be higher than the base case.

Conclusions:

  • Limiting factors significantly impact CSTR performance and urea conversion.
  • Microcapsule diameter and enzyme activity are critical parameters affecting the effectiveness factor.
  • Accounting for limitations like pH, product inhibition, and substrate depletion is essential for accurate modeling and process optimization.