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幂律模型及其渗流指数在含石墨烯体系电导率方面的进展,该体系作为乳腺癌生物传感中的一个组件。

Advancement of the Power-Law Model and Its Percolation Exponent for the Electrical Conductivity of a Graphene-Containing System as a Component in the Biosensing of Breast Cancer.

作者信息

Zare Yasser, Rhee Kyong Yop, Park Soo Jin

机构信息

Biomaterials and Tissue Engineering Research Group, Department of Interdisciplinary Technologies, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran 1125342432, Iran.

Department of Mechanical Engineering (BK21 Four), College of Engineering, Kyung Hee University, Yongin 17104, Korea.

出版信息

Polymers (Basel). 2022 Jul 28;14(15):3057. doi: 10.3390/polym14153057.

Abstract

The power-law model for composite conductivity is expanded for graphene-based samples using the effects of interphase, tunnels and net on the effective filler fraction, percolation start and "b" exponent. In fact, filler dimensions, interphase thickness, tunneling distance and net dimension/density express the effective filler fraction, percolation start and "b" exponent. The developed equations are assessed by experimented values from previous works. Additionally, the effects of all parameters on "b" exponent and conductivity are analyzed. The experimented quantities of percolation start and conductivity confirm the predictability of the expressed equations. Thick interphase, large tunneling distance, high aspect ratio and big nets as well as skinny and large graphene nano-sheets produce a low "b" and a high conductivity, because they improve the conduction efficiency of graphene nets in the system. Graphene-filled nanocomposites can be applied in the biosensing of breast cancer cells and thus the developed model can help optimize the performance of biosensors.

摘要

利用界面相、隧道效应和网络对有效填料分数、渗流起始点和“b”指数的影响,将复合电导率的幂律模型扩展到基于石墨烯的样品。实际上,填料尺寸、界面相厚度、隧道距离和网络尺寸/密度决定了有效填料分数、渗流起始点和“b”指数。通过先前工作的实验值对所推导的方程进行了评估。此外,分析了所有参数对“b”指数和电导率的影响。渗流起始点和电导率的实验数据证实了所推导方程的可预测性。厚界面相、大隧道距离、高纵横比和大网络以及薄而大的石墨烯纳米片会产生低“b”值和高电导率,因为它们提高了系统中石墨烯网络的传导效率。石墨烯填充的纳米复合材料可应用于乳腺癌细胞的生物传感,因此所开发的模型有助于优化生物传感器的性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cefc/9370558/fa660ddaa5eb/polymers-14-03057-g001.jpg

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