A constriction resistance model of conjugated polymer based piezoresistive sensors for electronic skin applications. Issue 18 (1st April 2016)

• Record Type: Journal Article
• Authors: Khalili, N.; Naguib, H. E.; Kwon, R. H.
• Is Part Of: Soft matter. Volume 12:Issue 18(2016)
• Page Start: 4180
• Page End: 4189
• Publication Date: 2016-04-01
• Subjects: Soft condensed matter -- Periodicals; 530.413
• DOI: 10.1039/c6sm00204h
• Languages: English
• ISSNs: 1744-683X

Abstract

Abstract : Human intervention can be replaced through the development of tools resulting from utilizing sensing devices possessing a wide range of applications including humanoid robots or remote and minimally invasive surgeries. Abstract : Human intervention can be replaced through the development of tools resulting from utilization of sensing devices possessing a wide range of applications including humanoid robots or remote and minimally invasive surgeries. Similar to the five human senses, sensors interface with their surroundings to stimulate a suitable response or action. The sense of touch which arises in human skin is among the most challenging senses to emulate due to its ultra high sensitivity. This has brought forth novel challenging issues to consider in the field of biomimetic robotics. In this work, using a multiphase reaction, a polypyrrole (PPy) based hydrogel is developed as a resistive type pressure sensor with an intrinsically elastic microstructure stemming from three dimensional hollow spheres. It is shown that the electrical conductivity of the fabricated PPy based piezoresistive sensors is enhanced as a result of adding conductive fillers and therefore, endowing the sensors with a higher sensitivity. A semi-analytical constriction resistance based model accounting for the real contact area between the PPy hydrogel sensors and the electrode along with the dependency of the contact resistance change on the applied load is developed. The model is then solved using a Monte Carlo technique and its corresponding sensitivity is obtained. Comparing the results with their experimental counterparts, the proposed modeling methodology offers a good tracking ability.