Aerospace mechanical structures encounter various forms of damage throughout their operation due to mechanical stimuli. Structural health monitoring (SHM) is suggested as a way to actively check the integrity of a component by using a system of sensors. However, these conventional sensors can often require external power that is not always readily available in aerospace, thus the development of self-powered sensors could prove beneficial for SHM applications. In this study, the design of multifunctional mechano-luminescent-optoelectronic (MLO) composites strain sensor is suggested. The MLO composites sensor is composed of two transformative materials: 1) mechano-luminescent (ML) copper-doped zinc sulfide (ZnS:Cu) and 2) mechano-optoelectronic (MO) poly(3-hexylthiophene) (P3HT). ML ZnS:Cu emits light in response to mechanical stimuli. MO P3HT showed self-sensing capability by generating direct current (DC) sensor signal under light. First, ZnS:Cu ML crystals will be embedded in polydimethylsiloxane (PDMS) matrix to fabricate ZnS:Cu/PDMS elastomeric composites. ML light emission characteristics of ZnS:Cu/PDMS will be studied by subjecting the ZnS:Cu/PDMS to cyclic tensile strain loadings while videos are recorded of the light emission. The data are analyzed using a statistical factorial methodology so that a regression model to predict light emission based on loading strain and frequency can be calculated. Second, MO P3HT-based self-sensing thin films will be fabricated on glass slides using a spin-coating technique. Last, self-powered sensing capability of the MLO composites strain sensor will be validated by measuring DC voltage (DCV) in close proximity of the ZnS:Cu/PDMS subjected to cyclic tensile loadings.
- Aerospace Division
Multifunctional Mechano-Luminescent-Optoelectronic Composites for Self-Powered Strain Sensing
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Pulliam, E, Hoover, G, & Ryu, D. "Multifunctional Mechano-Luminescent-Optoelectronic Composites for Self-Powered Strain Sensing." Proceedings of the ASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 2: Modeling, Simulation and Control of Adaptive Systems; Integrated System Design and Implementation; Structural Health Monitoring. Snowbird, Utah, USA. September 18–20, 2017. V002T05A010. ASME. https://doi.org/10.1115/SMASIS2017-3977
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