理解酶电化学生物传感器非线性过程的理论方法。

IF 2.8 2区 化学 Q3 CHEMISTRY, PHYSICAL
Marimuthu Annamalai, Manimegalai Balu*, Subbiah Alwarappan and Rajendran Lakshmanan*, 
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引用次数: 0

摘要

酶生物传感器的反应可根据非线性微分方程的结果进行监测。为这种基于酶的电化学生物传感器提出的非线性反应-扩散方程包括一个与 Michaelis-Menten 动力学相关的非线性项。在此,我们采用改进的同调扰动法求解了非线性反应-扩散方程系统。对于所有速率常数值,确定了生物传感器的浓度曲线、电流、灵敏度和梯度的近似解析表达式。讨论了酶电化学生物传感器的性能因素,如响应时间、灵敏度、准确性和电阻。比较了分析结果和使用 Matlab 软件进行数值模拟的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Theoretical Approach to Understand the Nonlinear Processes in Enzymatic Electrochemical Biosensors

A Theoretical Approach to Understand the Nonlinear Processes in Enzymatic Electrochemical Biosensors

A Theoretical Approach to Understand the Nonlinear Processes in Enzymatic Electrochemical Biosensors

The enzymatic biosensors’ response can be monitored based on the results of nonlinear differential equations. The nonlinear reaction-diffusion equations proposed for this enzyme-based electrochemical biosensor include a nonlinear term associated with Michaelis–Menten kinetics. Herein, the system of nonlinear reaction-diffusion equations is solved using a modified homotopy perturbation method. For all values of the rate constants, the approximate analytical expressions for the concentration profiles, current, sensitivity, and gradient of biosensor have been determined. Performance factors of an enzymatic electrochemical biosensor, such as response time, sensitivity, accuracy, and resistance, are discussed. The analytical results and numerically simulated outcomes using Matlab software have been compared.

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来源期刊
CiteScore
5.80
自引率
9.10%
发文量
965
审稿时长
1.6 months
期刊介绍: An essential criterion for acceptance of research articles in the journal is that they provide new physical insight. Please refer to the New Physical Insights virtual issue on what constitutes new physical insight. Manuscripts that are essentially reporting data or applications of data are, in general, not suitable for publication in JPC B.
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