Novel Analysis Methods of Nano-Fiber Sensors Used in Biomedical Applications
The ability to measure motion, especially motion of the human body, in an unobtrusive way is critical in the biomedical field. A promising method of making such measurements is through strain gauges composed of an electrically insolating polymer and conductive nano-particles, such as nickle nano-fibers or nickel coated carbon nano-fibers. These materials have the advantage of having low power requirements, resistance to corrosion, and the ability to measure a large range of strain (prior work has shown strains of 50% can be measured with such sensors). These strain gauges display a piezo-resistive effect, meaning that when the composite is placed under strain, the gaps between individual nano-fibers change, thus changing the effective electrical resistance of the entire composite.
Such materials could be employed to unobtrusively measure motion such as that of the spine or knees throughout daily activities. Other applications are also possible, such as measuring frequency and intensity of contractions in pregnant women. Improved analysis methods would allow sensors to be optimized for the range of strain that will be measured in each application. A more accurate model of how these sensors work will also improve the ability to accurately interpret measurement results.
The key to more effective design of these sensors for biological instrumentation is based on correctly modeling the method of charge transfer through these composites. Prior work has shown that charge transfer across the composite occurs by electron tunneling between the conductive particles, a phenomenon that causes resistance between two particles to increase exponentially with increasing gap distance. Currently, this continuous gap distance/resistance curve is divided into a “on” and “off” region, and the percentage of “on” and “off” junctions in the composite are used as inputs into a percolation model that predicts the effective resistance across the entire network.
In this work a mathematical simulation is developed to mimic a composite in which charge transport occurs through electron tunneling. Results from the simulation were used to analyze the validity of dividing the continuous resistance curve into “on” and “off” regions. Results suggest that this assumption does not lead to an accurate prediction of the composites properties. A novel multistate percolation approach, originally developed by Chen and Schuh for the analysis of grain boundary diffusion [1], is adapted to this problem. This method divides the continuous resistance curve into any number of divisions that can more closely approximate the continuous nature of the resistance curve.
With a sufficient number of divisions, the predictions given by this method showed extremely high agreement with the simulation results. Optimal methods of select how to divide the curve are also discussed.
With this improved analysis method, the functionality of compliant biosensors can be better understood. This improved methodology will allow for design of sensors that are more optimized to make specific measurements needed in the biotechnology field.
1. Chen, Y. and C.A. Schuh, Diffusion on grain boundary networks: Percolation theory and effective
medium approximations. Acta Materialia, 2006. 54(18): p. 4709-4720.