Mathematical Model and Numerical Simulation of Conductometric Biosensor of Urea

Zouaoui, Fares; Zine, Nadia; Errachid, Abdelhamid; Jaffrézic‐Renault, Nicole

doi:10.1002/elan.202100610

Cited by 8 publications

(1 citation statement)

References 21 publications

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“…In Martsenyuk et al (2022) , this relationship was evidenced for the specific conductance κ ( t ) of conductometric biosensors. Mathematical modeling of conductometric biosensors in terms of conductivity is presented in detail by Zouaoui et al (2022) . Provided fixed potential, we assume the linear dependence of the specific conductance and the current.…”

Section: Methodsmentioning

confidence: 99%

Operational stability study of lactate biosensors: modeling, parameter identification, and stability analysis

Martsenyuk,

Soldatkin,

Klos-Witkowska

et al. 2024

Front. Bioeng. Biotechnol.

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IntroductionThis paper investigates the operational stability of lactate biosensors, crucial devices in various biomedical and biotechnological applications. We detail the construction of an amperometric transducer tailored for lactate measurement and outline the experimental setup used for empirical validation.MethodsThe modeling framework incorporates Brown and Michaelis–Menten kinetics, integrating both distributed and discrete delays to capture the intricate dynamics of lactate sensing. To ascertain model parameters, we propose a nonlinear optimization method, leveraging initial approximations from the Brown model’s delay values for the subsequent model with discrete delays.ResultsStability analysis forms a cornerstone of our investigation, centering on linearization around equilibrium states and scrutinizing the real parts of quasi-polynomials. Notably, our findings reveal that the discrete delay model manifests marginal stability, occupying a delicate balance between asymptotic stability and instability. We introduce criteria for verifying marginal stability based on characteristic quasi-polynomial roots, offering practical insights into system behavior.DiscussionQalitative examination of the model elucidates the influence of delay on dynamic behavior. We observe a transition from stable focus to limit cycle and period-doubling phenomena with increasing delay values, as evidenced by phase plots and bifurcation diagrams employing Poincaré sections. Additionally, we identify limitations in model applicability, notably the loss of solution positivity with growing delays, underscoring the necessity for cautious interpretation when employing delayed exponential function formulations. This comprehensive study provides valuable insights into the design and operational characteristics of lactate biosensors, offering a robust framework for understanding and optimizing their performance in diverse settings.

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Section: Methodsmentioning

confidence: 99%

Operational stability study of lactate biosensors: modeling, parameter identification, and stability analysis

Martsenyuk,

Soldatkin,

Klos-Witkowska

et al. 2024

Front. Bioeng. Biotechnol.

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Mathematical Modeling and Optimization of Enzyme‐Based Amperometric Screen‐Printed Biosensors Using Horseradish Peroxidase as a Model

Garcia Secchi,

da da Rosa Silva,

da Sales da Rocha

et al. 2024

Electroanalysis

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In this study, a mathematical model was formulated to characterize the functioning of third‐generation enzyme‐based amperometric biosensors. This study utilized a horseradish peroxidase (HRP)‐based, screen‐printed biosensor. The model parameters were determined using the Environment for Modeling Simulation and Optimization (EMSO), validated with experimental data, and exhibited high determination coefficients, indicating the accuracy of the models in capturing biosensor behavior. Simulations based on this model emphasize diffusion as a limiting factor. Further sensitivity analysis was conducted using simulated response surfaces and biosensor performance optimization, which confirmed that higher concentrations of HRP in the thinnest polymeric film resulted in enhanced biosensor sensitivity.

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Current progress in the development of biosensors based on nanomaterials for the detection of inorganic arsenic

Zheng,

Li,

Liu

et al. 2024

Int. J. Environ. Sci. Technol.

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Mathematical Model and Numerical Simulation of Conductometric Biosensor of Urea

Cited by 8 publications

References 21 publications

Operational stability study of lactate biosensors: modeling, parameter identification, and stability analysis

Operational stability study of lactate biosensors: modeling, parameter identification, and stability analysis

Mathematical Modeling and Optimization of Enzyme‐Based Amperometric Screen‐Printed Biosensors Using Horseradish Peroxidase as a Model

Current progress in the development of biosensors based on nanomaterials for the detection of inorganic arsenic

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