Graphite-enhanced GNP/PVA composite piezoresistors with in-house data collection and prediction algorithm for structural health monitoring

Carbonous polymer matrix composites (PMCs) are considered among the potent candidates for piezoresistive sensing with their high gauge factor, high resolution, and applicability over large areas. However, non-linearity of their gauge factor at high strains and loss of sensitivity under cycling loading limit their widespread use. We produced a graphite-enhanced graphene nanoplatelet (GNP)/polyvinyl alcohol (PVA) composite piezoresistor to stabilize the gauge factor under various loading conditions. As a highly conductive ubiquitous material, graphite provided a backbone conduction pattern. GNPs in conjunction with the PVA matrix, on the other hand, introduced piezoresistivity to the composite paste. GNP/PVA piezoresistor pastes with graphite loadings from 5 wt.% to 40wt.% were tested both free standing and as applied on a plexiglass substrate. We report reliable and repeatable responses at a gauge factor of up to 40 and without sensitivity loss under cycling loading. The graphite enhanced GNP/PVA combining it with structural health monitoring (SHM) provided a failure prediction without the requirement of big data storage or high computational capability. We developed an in-house read-out circuit that was a low-cost replica of commercial multimeter to measure the change in resistance. We also developed an algorithm that determined the failure of a brittle material 350 s (first warning) and 10 s (second warning) before the actual failure.