The modelling of a capacitive microsensor for biosensing applications

Abstract

Microsensing is a leading field in technology due to its wide application potential, not only in bio-engineering, but in other fields as well. Microsensors have potentially low-cost manufacturing processes, while a single device type can have various uses, and this consequently helps with the ever-growing need to provide better health conditions in rural parts of the world. Capacitive biosensors detect a change in permittivity (or dielectric constant) of a biological material, usually within a parallel plate capacitor structure which is often implemented with integrated electrodes of an inert metal such as gold or platinum on a microfluidic substrate typically with high dielectric constant. There exist parasitic capacitance components in these capacitive sensors, which have large influence on the capacitive measurement. Therefore, they should be considered for the development of sensitive and accurate sensing devices. An analytical model of a capacitive sensor device is discussed, which accounts for these parasitic factors. The model is validated with a laboratory device of fixed geometry, consisting of two parallel gold electrodes on an alumina (Al(sub2)O(sub3)) substrate mounted on a glass microscope slide, and with a windowed cover layer of poly-dimethyl-siloxane (PDMS). The thickness of the gold layer is 1µm and the electrode spacing is 300µm. The alumina substrate has a thickness of 200µm, and the high relative permittivity of 11.5 is expected to be a significantly contributing factor to the total device capacitance. The 155µm thick PDMS layer is also expected to contribute substantially to the total device capacitance since the relative permittivity for PDMS is 2.7. The wideband impedance analyser evaluation of the laboratory device gives a measurement result of 2pF, which coincides with the model results; while the handheld RLC meter readout of 4pF at a frequency of 10kHz is acceptable within the measurement accuracy of the instrument. This validated model will now be used for the geometric design and simulation of efficient capacitive sensors in specific biological detection applications.