A rational design of a carbon black percolation network glass fibers for modeling an in situ self-reporting composite

Abstract

The study proposed in this manuscript is aimed at developing a novel real-time monitoring system using carbon black (CB) as the primary sensing material which is nontoxic, highly sensitive, easily synthesizable, and durable at harsh environments. The percolation network characteristics are studied in order to determine a better approach to the existing prototypal model. Varying percentages of CB such as 5, 10, 15, and 20 wt% were added to a 10 wt% of surfactant solution. The solution is coated on a glass fiber (GF) strand and embedded in GF laminate to form a self-monitoring composite. A novel approach is developed where a pre-programmed setup is used to read out electrical resistance directly. The average resistance is found to be 227, 390, 589, and 842 kΩ for varying percentages of CB. 5wt% CB exhibits a higher gauge factor compared to the remaining proportions. It is characterized by studying the percolation network where many of the conductive pathways seemed to become disconnected on the application of load. The XRD characteristics confirmed the phase change in the material at (100) and (101/111) at 2θ = 24.45o and 2θ = 44.47o. A mathematical model is established using which stress in computed using the electrical resistance values obtained from the data acquisition module. This is used to continuously monitor the in situ behavior of any model subjected to external disturbances by self-reporting the data that is necessary for fault diagnosis.