Studies of carbon nanotube (CNT) based composites have been unable to translate the extraordinary load-bearing capabilities of individual CNTs to macroscale composites such as yarns. A key challenge lies in the lack of understanding of how properties of filaments and interfaces across yarn hierarchical levels govern the properties of macroscale yarns. To provide insight required to enable the development of superior CNT yarns, we investigate the fabrication-structure-mechanical property relationships among CNT yarns prepared by different techniques and employ a Monte Carlo based model to predict upper bounds on their mechanical properties. We study the correlations between different levels of alignment and porosity and yarn strengths up to 2.4 GPa. The uniqueness of this experimentally informed modeling approach is the model's ability to predict when filament rupture or interface sliding dominates yarn failure based on constituent mechanical properties and structural organization observed experimentally. By capturing this transition and predicting the yarn strengths that could be obtained under ideal fabrication conditions, the model provides critical insights to guide future efforts to improve the mechanical performance of CNT yarn systems. This multifaceted study provides a new perspective on CNT yarn design that can serve as a foundation for the development of future composites that effectively exploit the superior mechanical performance of CNTs.

Understanding the complicated failure mechanisms of hierarchical composites such as fiber yarns is essential for advanced materials design. In this study, we developed a new Monte Carlo model for predicting the mechanical properties of fiber yarns that includes statistical variation in fiber strength. Furthermore, a statistical shear load transfer law based on the shear lag analysis was derived and implemented to simulate the interactions between adjacent fibers and provide a more accurate tensile stress distribution along the overlap distance. Simulations on two types of yarns, made from different raw materials and based on distinct processing approaches, predict yarn strength values that compare favorably with experimental measurements. Furthermore, the model identified very distinct dominant failure mechanisms for the two materials, providing important insights into design features that can improve yarn strength.

Near-field optical techniques exploit light-matter interactions at small length scales for mechanical sensing and actuation of nanomechanical structures. Here, we study the optical interaction between two mechanical oscillators—a plasmonic nanofocusing probe-tip supported by a low frequency cantilever, and a high frequency nanomechanical resonator—and leverage their interaction for local detection of mechanical vibrations. The plasmonic nanofocusing probe provides a confined optical source to enhance the interaction between the two oscillators. Dynamic perturbation of the optical cavity between the probe-tip and the resonator leads to nonlinear modulation of the scattered light intensity at the sum and difference of their frequencies. This double-frequency demodulation scheme is explored to suppress unwanted background and to detect mechanical vibrations with a minimum detectable displacement sensitivity of 0.45 pm/Hz1/2, which is limited by shot noise and electrical noise. We explore the demodulation scheme for imaging the bending vibration mode shape of the resonator with a lateral spatial resolution of 20 nm. We also demonstrate the time-resolved aspect of the local optical interaction by recording the ring-down vibrations of the resonator at frequencies of up to 129 MHz. The near-field optical technique is promising for studying dynamic mechanical processes in individual nanostructures.

where she received her PhD in Mechanical Engineering in 2008. Since then she has taught required and elective courses covering a wide range of topics in the undergraduate Mechanical Engineering curriculum. In her work with MTEI she co-leads teaching workshops for new faculty and assists with other teaching excellence initiatives. Her main teaching interests include solid mechanics and engineering mathematics.

No abstract