A COMPUTATIONAL STUDY OF STRAIN SENSING VIA 3D-PRINTED CNF-MODIFIED PLA STRAIN GAUGES

Additive manufacturing technologies and products have seen significant growth in the last decade but have the potential to see greater advancement with the addition of functional material properties in filaments, vastly expanding the product range. Polylactic acid (PLA) is a common fused deposition modeling (FDM) material used for additive manufacturing. Currently, filament materials are limited in terms of electrical properties with the majority of filaments being dielectric. Imparting electrical properties via nanofiller modification of traditionally insulating PLA is an exciting direction for multi-functional additive manufacturing. The work presented in this manuscript computationally explores the piezoresistive strain sensing performance of multi functional PLA. Specifically, we use experimental conductivity data collected from carbon nanofiber (CNF)-modified PLA to calibrate a computational piezoresistivity model. This computational model is then used to simulate the resistance change-strain relationship of a representative additively manufactured sensor shape. This study shows that the CNF/PLA sensor exhibits a non-linear response with a strain-dependent gauge factor ranging from 15.0 in compression to up to approximately 33.2 in tension. Computational tools such as the ones presented herein are important for further development of additively manufactured sensors since it allows researchers to explore a wide design space (e.g. shape, material type, etc.) without resorting to trial and error experimentation. This allows the incredible versatility of additive manufacturing to be more thoroughly leveraged.