Keith Slinker

High-Resolution Mapping of Thermal History in Polymer Nanocomposites: Gold Nanorods as Microscale Temperature Sensors

A technique is reported for measuring and mapping the maximum internal temperature of a structural epoxy resin with high spatial resolution via the optically detected shape transformation of embedded gold nanorods (AuNRs). Spatially resolved absorption spectra of the nanocomposites are used to determine the frequencies of surface plasmon resonances. From these frequencies the AuNR aspect ratio is calculated using a new analytical approximation for the Mie-Gans scattering theory, which takes into account coincident changes in the local dielectric. Despite changes in the chemical environment, the calculated aspect ratio of the embedded nanorods is found to decrease over time to a steady-state value that depends linearly on the temperature over the range of 100-200 °C. Thus, the optical absorption can be used to determine the maximum temperature experienced at a particular location when exposure times exceed the temperature-dependent relaxation time. The usefulness of this approach is demonstrated by mapping the temperature of an internally heated structural epoxy resin with 10 μm lateral spatial resolution.

Aerodynamic parameters from distributed heterogeneous CNT hair sensors with a feedforward neural network

Distributed arrays of artificial hair sensors have bio-like sensing capabilities to obtain spatial and temporal surface flow information which is an important aspect of an effective fly-by-feel system. The spatiotemporal surface flow measurement enables further exploration of additional flow features such as flow stagnation, separation, and reattachment points. Due to their inherent robustness and fault tolerant capability, distributed arrays of hair sensors are well equipped to assess the aerodynamic and flow states in adverse conditions. In this paper, a local flow measurement from an array of artificial hair sensors in a wind tunnel experiment is used with a feedforward artificial neural network to predict aerodynamic parameters such as lift coefficient, moment coefficient, free-stream velocity, and angle of attack on an airfoil. We find the prediction error within 6% and 10% for lift and moment coefficients. The error for free-stream velocity and angle of attack were within 0.12 mph and 0.37 degrees. Knowledge of these parameters are key to finding the real time forces and moments which paves the way for effective control design to increase flight agility, stability, and maneuverability.

Variable deflection response of sensitive CNT-on-fiber artificial hair sensors from CNT synthesis in high aspect ratio microcavities

Crickets, locusts, bats, and many other animals detect changes in their environment with distributed arrays of flow-sensitive hairs. Here we discuss the fabrication and characterization of a relatively new class of pore-based, artificial hair sensors that take advantage of the mechanical properties of structural microfibers and the electromechanical properties of self-aligned carbon nanotube arrays to rapidly transduce changes in low speed air flow. The radially aligned nanotubes are able to be synthesized along the length of the fibers inside the high aspect ratio cavity between the fiber surface and the wall of a microcapillary pore. The growth self-positions the fibers within the capillary and forms a conductive path between detection electrodes. As the hair is deflected, nanotubes are compressed to produce a typical resistance change of 1-5% per m/s of air speed which we believe are the highest sensitivities reported for air velocities less than 10 m/s. The quasi-static response of the sensors to point loads is compared to that from the distributed loads of air flow. A plane wave tube is used to measure their dynamic response when perturbed at acoustic frequencies. Correlation of the nanotube height profile inside the capillary to a diffusion transport model suggests that the nanotube arrays can be controllably tapered along the fiber. Like their biological counterparts, many applications can be envisioned for artificial hair sensors by tailoring their individual response and incorporating them into arrays for detecting spatio-temporal flow patterns over rigid surfaces such as aircraft.

Three-dimensional machining of carbon nanotube forests using water-assisted scanning electron microscope processing

We demonstrate that vertically aligned carbon nanotubes (CNTs) can be precisely machined in a low pressure water vapor ambient using the electron beam of an environmental scanning electron microscope. The electron beam locally damages the irradiated regions of the CNT forest and also dissociates the water vapor molecules into reactive species including hydroxyl radicals. These species then locally oxidize the damaged region of the CNTs. The technique offers material removal capabilities ranging from selected CNTs to hundreds of cubic microns. We study how the material removal rate is influenced by the acceleration voltage, beam current, dwell time, operating pressure, and CNT orientation. Milled cuts with depths between 0–100 microns are generated, corresponding to a material removal rate of up to 20.1 μm3/min. The technique produces little carbon residue and does not disturb the native morphology of the CNT network. Finally, we demonstrate direct machining of pyramidal surfaces and re-entrant cuts to cre...

Artificial Hair Sensors: Electro-Mechanical Characterization

Performance demands of future unmanned air vehicles will require rapid autonomous responses to changes in environment. Towards this goal, we expect that the next generation flight control systems will include advanced sensors beyond the contemporary array. One promising scenario correlates measurements of flow footprints over aircraft surfaces with aerodynamic data to aid navigation and feedback control algorithms. As a sensor for this concept, we construct artificial hair sensors (AHSs) based on glass microfibers enveloped in an annular, radially-aligned piezoresistive carbon nanotube (CNT) forest to measure air flow in boundary layers. This study includes an analysis of the sensitivity based on laboratory scale electromechanical testing.The sensors in this work utilize nine micron diameter S2 glass fibers as the sensing mechanism for coupling to boundary layer air flows. The annular CNT forest resides in a fused silica microcapillary with electrodes at the entrance. The sensor electrical transduction mechanism relies on the resistance change of the CNT forest due to changes in both the bulk and contact resistance as a function of mechanical loading on the fiber. For the electromechanical analysis, the sensors are controllably loaded to measure both the force and moment acting at the base of the hair and the resulting deflection of the CNT forest inside of the microcapillary is measured to estimate the stress on the forest and the pressure between the forest and the electrode. The electrical responses of the sensors are compared to the mechanical state of the CNT forest. This work represents the development of a characterization tool to better understand and control the response of CNT based AHSs.Copyright

Experimental Mechanics for Multifunctional Composites and Next Generation UAVs

Low-cost unmanned aircraft that use affordable manufacturing and have limited service life can enable mission concepts in which there is a higher tolerance for aircraft loss, or attrition. Because of their higher risk tolerance, these low-cost attritable aircraft could also integrate emerging technology which may have previously been considered too risky for integration into expensive and long life aircraft. Light-weight multifunctional structural composites have the potential to integrate additional functions and enable mission agility without significantly adding weight or reducing payload capacity. However, design and development of these material systems are often difficult because of the traditional “building block” development approach used for traditional composites, the large option space available for structural and functional properties, and the potential complexity of the multiscale and multiphysics coupling. To realize integrated functionality, new multi-scales and multi-physical experimental mechanical characterization techniques should be merged with maturing integrated materials models. We discuss this need using examples of a reconfigurable liquid metal Structurally Embedded Vascular Antenna (SEVA), a plasmonic nanoparticle based method for measuring internal temperature gradients, and embedded micro-cantilever carbon-nanotube based sensors. The latter of these is also used to discuss the potential to accelerate development of multifunctional structural concepts by provide air flow measurement and structural feedback during testing of complex structures. This could, in turn, eliminate some testing of intermediate elements in the slow and expensive traditional “building block” approach.

Shear sensing in bonded composites with cantilever beam microsensors and dual-plane digital image correlation

Understanding the shear strain, viscoelastic response, and onset of damage within bonded composites is critical to their design, processing, and reliability. This presentation will discuss the multidisciplinary research conducted which led to the conception, development, and demonstration of two methods for measuring the shear within a bonded joint – dualplane digital image correlation (DIC) and a micro-cantilever shear sensor. The dual plane DIC method was developed to measure the strain field on opposing sides of a transparent single-lap joint in order to spatially quantify the joint shear strain. The sensor consists of a single glass fiber cantilever beam with a radially-grown forest of carbon nanotubes (CNTs) within a capillary pore. When the fiber is deflected, the internal radial CNT array is compressed against an electrode within the pore and the corresponding decrease in electrical resistance is correlated with the external loading. When this small, simple, and low-cost sensor was integrated within a composite bonded joint and cycled in tension, the onset of damage prior to joint failure was observed. In a second sample configuration, both the dual plane DIC and the hair sensor detected viscoplastic changes in the strain of the sample in response to continued loading.