Jin Xin, Bandodkar Amay J, Fratus Marco, Asadpour Reza, Rogers John A, Alam Muhammad A
Department of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, 47906, USA.
Center for Bio-Integrated Electronics, Querrey Simpson Institute for Bioelectronics, Northwestern University, Evanston,, IL 60208, USA.
Biosens Bioelectron. 2020 Nov 15;168:112493. doi: 10.1016/j.bios.2020.112493. Epub 2020 Aug 5.
Enzymatic biofuel cell (EBFC)-based self-powered biochemical sensors obviate the need for external power sources thus enabling device miniaturization. While recent efforts driven by experimentalists illustrate the potential of EBFC-based sensors for real-time monitoring of physiologically relevant biochemicals, a robust mathematical model that quantifies the contributions of sensor components and empowers experimentalists to predict sensor performance is missing. In this paper, we provide an elegant yet simple equivalent circuit model that captures the complex, three-dimensional interplay among coupled catalytic redox reactions occurring in an EBFC-based sensor and predicts its output signal with high correlations to experimental observations. The model explains the trade-off among chemical design parameters such as the surface density of enzymes, various reaction constants as well as electrical parameters in the Butler-Volmer relationship. The model shows that the linear dynamic range and sensitivity of the EBFC-based sensor can be independently fine-tuned by changing the surface density of enzymes and electron mediators at the anode and by enhancing reductant concentrations at the cathode. The mathematical model derived in this work can be easily adapted to understand a wide range of two-electrode systems, including sensors, fuel cells, and energy storage devices.
基于酶生物燃料电池（EBFC）的自供电生化传感器无需外部电源，从而实现了设备的小型化。尽管实验人员最近的努力展示了基于EBFC的传感器在实时监测生理相关生化物质方面的潜力，但缺少一个强大的数学模型来量化传感器组件的贡献并使实验人员能够预测传感器性能。在本文中，我们提供了一个简洁而简单的等效电路模型，该模型捕捉了基于EBFC的传感器中发生的耦合催化氧化还原反应之间复杂的三维相互作用，并预测其输出信号，与实验观察结果具有高度相关性。该模型解释了化学设计参数（如酶的表面密度、各种反应常数）以及Butler-Volmer关系中的电学参数之间的权衡。该模型表明，通过改变阳极处酶和电子介质的表面密度以及提高阴极处还原剂的浓度，可以独立地微调基于EBFC的传感器的线性动态范围和灵敏度。这项工作中推导的数学模型可以很容易地适用于理解广泛的双电极系统，包括传感器、燃料电池和储能设备。
