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Inertial sensing technologies, including accelerometers and gyroscopes, have been invaluable in numerous fields ranging from consumer electronics to healthcare and clinical practices. Inertial measurement units, specifically accelerometers, represent the most widely used microelectromechanical systems (MEMS) devices with excellent and reliable performance. Although MEMS-based accelerometers have many attractive attributes, such as their tiny footprint, high sensitivity, high reliability, and multiple functionalities, they are limited by their complex and expensive microfabrication processes and cumbersome, fragile structures that suffer from mechanical fatigue over time. Moreover, the rigid nature of beams and spring-like structures of conventional accelerometers limit their applications for wearable devices and soft-human machine interfaces where physical compliance that is compatible with human skin is a priority. In this dissertation, the development of novel practical resistive and capacitive-type inertial sensors using liquid metal as a functional proof mass material is presented. Utilizing the unique electromechanical properties of liquid metal, the novel inertial sensor design confines a graphene-coated liquid metal droplet inside tubular and 3D architectures, enabling motion sensing in single and multiple directions. Combining the graphene-coated liquid metal droplet with printed sensing elements offers a robust fatigue-free alternative material for rigid, proof mass-based accelerometers. Resistive and capacitive sensing mechanisms were both developed, characterized, and evaluated. Emerging rapid fabrication technologies such as direct laser writing and 3D printing were mainly adopted, offering a scalable fabrication strategy independent of advanced microfabrication facilities. The developed inertial sensor was integrated with a programmable system on a chip (PSoC) to function as a stand-alone system and demonstrate its application for real-time- monitoring of human health/ physical activity and for soft human-machine interfaces. The developed inertial sensor architecture and materials in this work offer a new paradigm for manufacturing these widely used sensors that have the potential to complement the performance of their silicon-based counterparts and extend their applications.

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The growth of Fe₃O₄ and FeOOH crystals was investigated. Growth modifiers were used to alter the formation of iron oxides from ferrous hydroxide precipitates. Multifunctional carboxylic acids were found to have a strong influence on morphology of FeOOH. Dicarboxylic acids, containing two and seven carbons, changed the characteristics of α-FeOOH. These changes included alteration of the isoelectic point of the particulates and changes in particle size and shape. EDTA was found to alter the phase of FeOOH formation, favoring the synthesis of γ-FeOOH over α-FeOOH at temperatures below 50°C. The effects of multifunctional carboxylic acids were dependent upon the time of addition, and the presence of other growth modifiers. The changes in FeOOH formation were postulated to occur due to interaction between the acid molecules and Green Rust II, a common intermediate in iron oxide growth. The growth of Fe₃O₄ was found to be sensitive to solution pH, and the form of the iron starting materials. Examination of reaction intermediates by x-ray diffraction showed that other Crystalline phases formed prior to the production of Fe₃O₄. Different intermediate phases occurred depending on the amount of hydroxide in the reaction, and differences in Fe³⁺ starting materials. The production of different intermediate phases affected the morphology of Fe₃O₄. Early precipitation of Fe₃O₄ led to small particles, while formation of crystalline Fe(OH)₂ led to large crystals. Formation of a mixture of Green Rust II and Fe(OH)₂ early in the oxidation process led to formation of multiple nuclei, and produced smaller average particles with a wide particle size distribution. Fe₃O₄ particles prepared from α-FeOOH seed crystals were spherical, while Fe₃O₄ particles prepared from FeSO₄ alone were octahedral crystals. / Ph. D.

The strain and damage sensing abilities of randomly oriented multi-walled carbon nanotubes (MWCNTs) dispersed in the polymer binder of energetic composites were experimentally investigated. Ammonium perchlorate (AP) crystals served as the inert energetic and atomized aluminum as the metallic fuel, both of which were combined to create a representative fuel-oxidizer filler often used for aerospace propulsive applications. MWCNTs were dispersed within an elastomer binder of polydimethylsiloxane (PDMS), and hybrid energetics were fabricated from it, with matrix material comprised of the identified fillers. The nanocomposites were characterized based on their stress-strain response under monotonic uniaxial compression to failure, allowing for the assessment of effects of MWCNTs and aluminum powder on average compressive elastic modulus, peak stress, and strain to failure. The piezoresistive response was measured as the change in impedance with applied monotonic strain in both the mesoscopic and microscopic strain regimes of mechanical loading for each material system, as well as under ten cycles of applied compressive loading within those same strain regimes. Gauge factors were calculated to quantify the magnitude of strain and damage sensing in MWCNT-enhanced material systems. Electrical response of single-cycle thermal loading was explored with epoxy in place of the elastomer binder of the previously discussed studies. Piezoresistive response due to microscale damage from thermal expansion was observed exclusively in material systems enhanced by MWCNTs. The results discussed herein validate structural health monitoring (SHM) applications for embedded carbon nanotube sensing networks in polymer-based energetics under unprecedented cyclic loads. / Master of Science / The ability to characterize both deformation and damage in real time within materials of high energetic content, such as solid rocket propellant, is of great interest in experimental mechanics. Common energetic ammonium perchlorate, in the fonn of crystal particles, was embedded in polymer binders (ie PDMS and epoxy) and investigated under a variety of me­chanical and thermal loads. Carbon nanotubes, conductive tube-shaped molecular structures of carbon atoms, have been demonstrated in prior proofs of concept to induce substantial electrical response change when dispersed in composites which are experiencing strain. With the introduction of carbon nanotubes in the energetic composites investigated herein, the electrical response of the material systems was measured as a change in impedance with applied strain. Elastomer-bonded energel.ks were t.esl.ed under monotonic compression and cyclic compression, and expanded exploration was done on these material systems with the additional particulate of aluminum powder, allowing for varied particulate sizes and conductivity enhancement of the overall composite. The magnitude of the resulting piezoresistive change due to strain and microscale damage was observed to increase dramatically in material systems enhanced by MWCNT networks. Local heating was used to explore thermal loading on epoxy-bonded energetic material systems, and sensing of permanent damage to the­ material through its CNT network was proven through a permanent change in the electrical response which was exclusive to the CNT-enhanced material systems. These results demon­strate valid structural health monitoring (SHM) applications for embedded carbon nanotube sensing networks in particulate energetic composites, under a variety of load cases.

This thesis presents the design of multifunctional structures through the optimal placement of nanomaterial additives. Varying the concentration of Carbon Nanotubes (CNTs) in a polymer matrix affects its local effective properties, including mechanical stiffness, electrical conductivity, and piezoresistivity. These local properties in turn drive global multifunctional performance objectives. A topology optimization algorithm determines the optimal distribution of CNTs within an epoxy matrix in an effort to design a set of structures that are capable of performing some combination of mechanical, electrical, or peizoresistive functions. A Pareto-Based Restart Method is introduced and may be used within a multi-start gradient based optimization to obtain well defined multiobjective Pareto Fronts. A linear design variable filter is used to limit the influence of checkerboarding. The algorithm is presented and applied to the design of beam cross-sections and 2D plane stress structures. It is shown that tailoring the location of even a small amount of CNT (as low as 2 percent and as high as 10 percent, by volume) can have significant impact on stiffness, electrical conductivity, and strain-sensing performance. Stiffness is maximized by placing high concentrations of CNT in locations that either maximize the bending rigidity or minimize stress concentrations. Electrical conductivity is maximized by the formation of highly conductive paths between electrodes. Strain-sensing is maximized via location of percolation volume fractions of CNTs in high strain areas, manipulation of the strain field to increase the strain magnitude in these areas, and by avoiding negative contributions of piezoresistivity from areas with differing net signed strains. It is shown that the location of the electrodes can affect sensing performance. A surrogate model for simultaneous optimization of electrode and topology is introduced and used to optimize a 2D plane stress structure. This results in a significant increase in sensing performance when compared to the fixed-electrode topology optimization. / Ph. D. / This dissertation presents a method that allows for the best placement of a limited amount of filler material within a base matrix material to form an optimal composite structure. Adding filler material, in this case Carbon Nanotubes, can change the effective behavior of the composite structure, enhancing the capabilities of the base matrix material by adding structural stiffness, electrical conductivity, and even the ability for the structure to measure its own strains. The degree to which these changes occur is dependent on the amount of filler material present in any given subsection of the structure. The method then is focused on determining how much of the filler to place in different subsections of the structure to maximize several measures of performance. These measures pertain to structural performance, electrical conductivity, and the structure’s ability to sense strains. Steps are taken within the method to remove non-physical designs and also to find the overall best design, called the global minima. The method is applied to several test structures of varying complexity, and it is shown that the optimization method can heavily influence performance by tailoring the filler material distribution. Further electrical and sensing performance gains can be obtained by properly selecting where the electrodes are located on the structure. This is demonstrated by including electrode placement in the design method along with the filler distribution.