Pypiezo-GO: A software tool for processing electromechanical measurements of piezoelectric reduced graphene oxide-cement composites

Abstract

Self-diagnostic composites have become increasingly popular for structural health monitoring due to their ability to develop load-bearing strain sensors. Piezoelectric cement composites, in particular, represent an emerging area of research with vast potential for developing innovative self-powered or ultra-low power consumption sensors. In this context, this paper presents Pypiezo-GO, a software tool designed for the electromechanical characterization of reduced graphene oxide (rGO)-cement composites. The software tool, developed as an online cloud computing platform, accesses a database organized into DataFrame structures. The database contains the measurements from a set of experiments conducted on rGO-cement samples, including open circuit potential, cyclic voltammetry, and compressive testing. On this basis, Pypiezo-GO allows extracting the electrical properties of the samples, including their capacitance and piezoelectric factors. Furthermore, the platform enables the comparison of experimental time series with numerical predictions from a lumped circuit model implemented in MATLAB/Simulink, which is also included in this contribution. The presented software code is intended to represent a valuable tool for the development of new piezoelectric cement composites for strain self-sensing applications.

Keywords

• Cyclic voltammetry
• DataFrame
• Open circuit potential
• Piezoelectricity
• Python language
• Reduced graphene oxide