Butterfly pea flower as a stabilizer for shear exfoliated graphene: Green material for motion monitoring and morse code sensor

A thin flm-based strain sensor can be used for monitoring subtle and routine human activity due to its smaller dimension and portability. It could also be tailored to ft body contours. For the frst time ever in this work, few-layer graphene was produced by shear exfoliation of graphite in butterfy pea extract before being layer–layer deposited as strain/acoustic sensitive coating on nylon flm. The quality of the graphene produced in this study is refected by the low defect (ID/IG: 0.25) observed under Raman spectroscopy and a C/O ratio of 4.75. The fabricated sensor can detect a wide human activity range such as eyes blinking and released/closed fst action while being equally sensitive to throat movement during drinking, laughing, nodding, and coughing besides the conventional tensile/compressive bending. The measured gauge factor is 39.37 and 21.93 for tensile and compressive, respectively, while the response and recovery time was recorded at about 1 s each. The durability of the fabricated flm sensor was evidenced by the absence of mass loss despite complete immersion in water for 24 h Next, we demonstrated the potential application of this sensor for the evaluation of fnger gestures during the transmission of Morse code (“dot”, “dash”, and “space”) from the recorded electrical resistance using machine learning classifcation. Impressively, it was found that the performance of ML models for datasets obtained from our developed graphene/nylon sensor is tolerably above 90% overall, which strongly suggests the potential of the developed sensor as a tool for IoT or Big Data applications in the future.