Fabrication and Characterization of Electrically Conductive 3D Printable TPU/MWCNT Filaments for Strain Sensing in Large Deformation Conditions
Behrad Koohbor, Wei Xue, Kazi Zahir Uddin, George Youssef, Daniel Nerbetski, B. Steiger, Joseph Kenney, Dana Yarem
- 发表年份
- 2024
- 引用次数
- 4
- 访问权限
- 开放获取
摘要
Abstract This study investigates the development of thermoplastic polyurethane (TPU) filaments incorporating multi‐walled carbon nanotubes (MWCNT) to enhance strain‐sensing capabilities. Various MWCNT reinforcement ratios are used to produce customized feedstock for fused filament fabrication (FFF) 3D printing. Mechanical properties and the piezoresistive response of samples printed with these multifunctional filaments are concurrently evaluated. Surface morphology and microstructural observations reveal that higher MWCNT weight percentages increase filament surface roughness and rigidity. The microstructural modifications directly influence the tensile strength and strain energy of the printed samples. The study identifies an apparent percolation threshold within the 10–12 wt.% MWCNT range, indicating the formation of a conductive network. At this threshold, higher gauge factors are achieved at lower strains. A newly introduced Electro‐Mechanical Sensitivity Ratio (ESR) parameter enables the classification of composite behaviors into two distinct zones, offering the ability to tailor self‐sensing structures with on‐demand properties. Finally, flexible structures with proven application in soft robotics and shape morphing are fabricated and tested at different loading conditions to demonstrate the potential applicability of the custom filaments produced. The results highlight a pronounced piezoresistive response and superior load‐bearing performance in the examined structures.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992