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- All Subjects: Mechanical Engineering
- Genre: Doctoral Dissertation
- Status: Published
Description
Gallium based room-temperature liquid metals (LMs) have special properties such as metal-like high thermal conductivity while in the liquid state. They are suitable for many potential applications, including thermal interface materials, soft robotics, stretchable electronics, and biomedicine. However, their high density, high surface tension, high reactivity with other metals, and rapid oxidation restrict their applicability. This dissertation introduces two new types of materials, LM foams, and LM emulsions, that address many of these issues. The formation mechanisms, thermophysical properties, and example applications of the LM foams and emulsions are investigated.LM foams can be prepared by shear mixing the bulk LM in air using an impeller. The surface oxide layer is sheared and internalized into the bulk LM as crumpled oxide flakes during this process. After a critical amount of oxide flakes is internalized, they start to stabilize air bubbles by encapsulating and oxide-bridging. This mechanism enables the fabrication of a LM foam with improved properties and better spreadability.
LM emulsions can be prepared by mixing the LM foam with a secondary liquid such as silicone oil (SO). By tuning a few factors such as viscosity of the secondary liquid, composition, and mixing duration, the thermophysical properties of the emulsion can be controlled. These emulsions have a lower density, better spreadability, and unlike the original LM and LM foam, they do not induce corrosion of other metals.
LM emulsions can form by two possible mechanisms, first by the secondary liquid replacing air features in the existing foam pores (replacement mechanism) and second by creating additional liquid features within the LM foam (addition mechanism). The latter mechanism requires significant oxide growth and therefore requires presence of oxygen in the environment. The dominant mechanism can therefore be distinguished by mixing LM foam with the SO in air and oxygen-free environments. Additionally, a comprehensive analysis of foam-to-emulsion density change, multiscale imaging and surface wettability confirm that addition mechanism dominates the emulsion formation. These results provide insight into fundamental processes underlying LM foams and emulsions, and they set up a foundation for preparing LM emulsions with a wide range of fluids and controllable properties.
ContributorsShah, Najam Ul Hassan (Author) / Rykaczewski, Konrad (Thesis advisor) / Wang, Robert (Thesis advisor) / Phelan, Patrick (Committee member) / Green, Matthew D. (Committee member) / Kwon, Beomjin (Committee member) / Arizona State University (Publisher)
Created2023
Description
While wearable soft robots have successfully addressed many inherent design limitations faced by wearable rigid robots, they possess a unique set of challenges due to their soft and compliant nature. Some of these challenges are present in the sensing, modeling, control and evaluation of wearable soft robots. Machine learning algorithms have shown promising results for sensor fusion with wearable robots, however, they require extensive data to train models for different users and experimental conditions. Modeling soft sensors and actuators require characterizing non-linearity and hysteresis, which complicates deriving an analytical model. Experimental characterization can capture the characteristics of non-linearity and hysteresis but requires developing a synthesized model for real-time control. Controllers for wearable soft robots must be robust to compensate for unknown disturbances that arise from the soft robot and its interaction with the user. Since developing dynamic models for soft robots is complex, inaccuracies that arise from the unmodeled dynamics lead to significant disturbances that the controller needs to compensate for. In addition, obtaining a physical model of the human-robot interaction is complex due to unknown human dynamics during walking. Finally, the performance of soft robots for wearable applications requires extensive experimental evaluation to analyze the benefits for the user. To address these challenges, this dissertation focuses on the sensing, modeling, control and evaluation of soft robots for wearable applications. A model-based sensor fusion algorithm is proposed to improve the estimation of human joint kinematics, with a soft flexible robot that requires compact and lightweight sensors. To overcome limitations with rigid sensors, an inflatable soft haptic sensor is developed to enable gait sensing and haptic feedback. Through experimental characterization, a mathematical model is derived to quantify the user's ground reaction forces and the delivered haptic force. Lastly, the performance of a wearable soft exosuit in assisting human users during lifting tasks is evaluated, and the benefits obtained from the soft robot assistance are analyzed.
ContributorsQuiñones Yumbla, Emiliano (Author) / Zhang, Wenlong (Thesis advisor) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Marvi, Hamid (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2023
Description
Robotic technology can be broadly categorized into two main approaches based on the compliance of the robot's materials and structure: hard and soft. Hard, traditional robots, with mechanisms to transmit forces, provide high degrees of freedom (DoFs) and precise manipulation, making them commonly used in industry and academic research. The field of soft robotics, on the other hand, is a new trend from the past three decades of robotics that uses soft materials such as silicone or textiles as the body or material base instead of the rigid bodies used in traditional robots. Soft robots are typically pre-programmed with specific geometries, and perform well at tasks such as human-robot interaction, locomotion in complex environments, and adaptive reconfiguration to the environment, which reduces the cost of future programming and control. However, full soft robotic systems are often less mobile due to their actuation --pneumatics, high-voltage electricity or magnetics -- even if the robot itself is at a millimeter or centimeter scale. Rigid or hard robots, on the other hand, can often carry the weight of their own power, but with a higher burden of cost for control and sensing. A middle ground is thus sought, to combine soft robotics technologies with rigid robots, by implementing mechanism design principles with soft robots to embed functionalities or utilize soft robots as the actuator on a rigid robotic system towards an affordable robotic system design. This dissertation showcases five examples of this design principle with two main research branches: locomotion and wearable robotics. In the first research case, an example of how a miniature swimming robot can navigate through a granular environment using compliant plates is presented, compared to other robots that change their shape or use high DoF mechanisms. In the second pipeline, mechanism design is implemented using soft robotics concepts in a wearable robot. An origami-inspired, soft "exo-shell", that can change its stiffness on demand, is introduced. As a follow-up to this wearable origami-inspired robot, a geometry-based, ``near" self-locking modular brake is then presented. Finally, upon combining the origami-inspired wearable robot and brake design, a concept of a modular wearable robot is showcased for the purpose of answering a series of biomechanics questions.
ContributorsLi, Dongting (Author) / Aukes, Daniel M (Thesis advisor) / Sugar, Thomas G (Committee member) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Created2023
Description
An approach for modeling resistance spot welding of thin-gauge, dissimilar metal sheets with high electrical conductivity is presented in this work. In this scenario, the electrical and thermal contact resistances play a dominant role in heat generation and temperature evolution within the workpieces; these interactions ultimately control the weld geometry. Existing models are limited in modeling these interactions, especially for dissimilar and thin-gauge metal sheets, and at higher temperatures when the multiphysics becomes increasingly interdependent. The approach presented here uses resistivity measurements, combined with thermal modeling and known bulk resistance relationships to infer the relationship between electrical contact resistance and temperature for each of the different material interfaces in the welding process. Corresponding thermal contact resistance models are developed using the Wiedemann-Franz law combined with a scaling factor to account for nonmetallic behavior. Experimental and simulation voltage histories and final weld diameter were used to validate this model for a Cu/Al/Cu and a Cu/Al/Cu/Al/Cu stack-ups. This model was then used to study the effect of Ni-P coating on resistance spot welding of Cu and Al sheets in terms of weld formation, mechanical deformation, and contact resistance. Contact resistance and current density distribution are highly dependent on contact pressure and temperature distribution at the Cu/Al interface in the presence of alumina. The Ni-P coating helps evolve a partially-bonded donut shaped weld into a fully-bonded hourglass-shaped weld by decreasing the dependence of contact resistance and current density distribution on contact pressure and temperature distribution at the Cu/Al interface. This work also provides an approach to minimize distortion due to offset-rolling in thin aluminum sheets by optimizing the stiffening feature geometry. The distortion is minimized using particle swarm optimization. The objective function is a function of distortion and smallest radius of curvature in the geometry. Doubling the minimum allowable radius of curvature nearly doubles the reduction in distortion from the stadium shape for a quarter model. Reduction in distortion in the quarter model extends to the full-scale model with the best design performing 5.3% and 27% better than the corresponding nominal design for a quarter and full-scale model, respectively.
ContributorsVeeresh, Pawan (Author) / Oswald, Jay (Thesis advisor) / Carlson, Blair (Committee member) / Hoover, Christian (Committee member) / Rajagopalan, Jagannathan (Committee member) / Solanki, Kiran (Committee member) / Arizona State University (Publisher)
Created2022
Description
This dissertation is focused on the rheology scaling of metal particle reinforced polymermatrix composite made of solid and nanoporous metal powders to enable their
continuous 3D printing at high (>60vol%) metal content. There remained a specific
knowledge gap on how to predict successful extrusion with densely packed metals by
utilizing their suspension melt rheological properties. In the first project, the scaling of
the dynamic viscosity of melt-extrudate filaments made of Polylactic acid (PLA) and
gas-atomized solid NiCu powders was studied as a function of the metal’s volumetric
packing and feedstock pre-mixing strategies and correlated to its extrudability
performance, which fitted well with the Krieger-Dougherty analytical model. 63.4
vol% Filaments were produced by employing solution-mixing strategy to reduce
sintered part porosity and shrinkage. After sintering, the linear shrinkage dropped by
76% compared to the physical mixing. By characterizing metal particle reinforced
polymer matrix composite feedstock via flow-sweep rheology, a distinct extension of
shear-thinning towards high shear rates (i.e. 100 s-1) was observed at high metal content
– a result that was attributed to the improved wall adhesion. In comparison, physically mixed filament failed to sustain more than 10s-1 shear rate proving that they were prone
to wall slippage at a higher shear rate, giving an insight into the onset of extrusion
jamming. In the second project, nanoporous copper made out of electroless chemical
dealloying was utilized as fillers, because of their unique physiochemical properties.
The role of capillary imbibition of polymers into metal nanopores was investigated to
understand their effect on density, zero-shear viscosity, and shear thinning. It was
observed that, although the polymeric fluid’s transient concentration regulates its
wettability, the polymer chain length ultimately dictates its melt rheology, which consequentially facilitates densification of pores during vacuum annealing. Finally, it
was demonstrated that higher imbibition into nanopores leads to extrusion failure due
to a combined effect of volumetric packing increase and nanoconfinement, providing a
deterministic materials design tool to enable continuous 3D printing. The outcome of
this study might be beneficial to integrate nanoporous metals into binder-based 3D
printing technology to fabricate interdigitated battery electrodes and multifunctional 3D
printed electronics.
ContributorsHasib, Amm (Author) / Azeredo, Bruno (Thesis advisor) / Song, Kenan (Thesis advisor) / Nian, Qiong (Committee member) / Kwon, Beomjin (Committee member) / Li, Xiangjia (Committee member) / Arizona State University (Publisher)
Created2022
Description
Aromatic polymers, with benzene-like rings in their main chains, include materials such as polyurea, an amorphous elastomer capable of dissipating large amounts of energy under dynamic loading, which makes it a promising coating for defensive systems. Although computational research exists that investigates the atomic-level response of polyurea and other amorphous aromatic polymers to extreme conditions, there is little experimental work to validate these models 1) at the atomic-scale and 2) under high pressures characteristic of extreme dynamic loading. Understanding structure-property relationships at the atomic-level is important for polymers, considering many of them undergo pressure and temperature-induced structural transformations, which must be understood to formulate accurate predictive models. This work aims to gain a deeper understanding of the high-pressure structural response of aromatic polymers at the atomic-level, with emphasis into the mechanisms associated with high-pressure transformations. Hence, atomic-level structural data at high pressures was obtained in situ via multiangle energy dispersive X-ray diffraction (EDXD) experiments at the Advanced Photon Source (APS) for polyurea and another amorphous aromatic polymer, polysulfone, chosen as a reference due to its relatively simple structure. Pressures up to 6 GPa were applied using a Paris Edinburgh (PE) hydraulic press at room temperature. Select polyurea samples were also heated to 277 °C at 6 GPa. The resulting structure factors and pair distribution functions, along with molecular dynamics simulations of polyurea provided by collaborators, suggest that the structures of both polymers are stable up to 6 GPa, aside from reductions in free-volume between polymer backbones. As higher pressures (≲ 32 GPa) were applied using diamond anvils in combination with the PE press, indications of structural transformations were observed in both polymers that appear similar in nature to the sp2-sp3 hybridization in compressed carbon. The transformation occurs gradually up to at least ~ 26 GPa in PSF, while it does not progress past ~ 15 GPa in polyurea. The changes are largely reversible, especially in polysulfone, consistent with pressure-driven, reversible graphite-diamond transformations in the absence of applied temperature. These results constitute some of the first in situ observations of the mechanisms that drive pressure-induced structural transformations in aromatic polymers.
ContributorsEastmond, Tyler (Author) / Peralta, Pedro (Thesis advisor) / Hoover, Christian (Committee member) / Hrubiak, Rostislav (Committee member) / Mignolet, Marc (Committee member) / Oswald, Jay (Committee member) / Arizona State University (Publisher)
Created2022
Description
Thermal management of electronics is critical to meet the increasing demand for high power and performance. Thermal interface materials (TIMs) play a key role in dissipating heat away from the microelectronic chip and hence are a crucial component in electronics cooling. Challenges persist with overcoming the interfacial boundary resistance and filler particle connectivity in TIMs to achieve thermal percolation while maintaining mechanical compliance. Gallium-based liquid metal (LM) capsules offer a unique set of thermal-mechanical characteristics that make them suitable candidates for high-performance TIM fillers. This dissertation research focuses on resolving the fundamental challenges posed by integration of LM fillers in polymer matrix. First, the rupture mechanics of LM capsules under pressure is identified as a key factor that dictates the thermal connectivity between LM-based fillers. This mechanism of oxide “popping” in LM particle beds independent of the matrix material provides insights in overcoming the particle-particle connectivity challenges. Second, the physical barrier introduced due to the polymer matrix needs to be overcome to achieve thermal percolation. Matrix fluid viscosity impacts thermal transport, with high viscosity uncured matrix inhibiting the thermal bridging of fillers. In addition, incorporation of solid metal co-fillers that react with LM fillers is adopted to facilitate popping of LM oxide in uncured polymer to overcome this matrix barrier. Solid silver metal additives are used to rupture the LM oxide, form inter-metallic alloy (IMC), and act as thermal anchors within the matrix. This results in the formation of numerous thermal percolation paths and hence enhances heat transport within the composite. Further, preserving this microstructure of interconnected multiphase filler system with thermally conductive percolation pathways in a cured polymer matrix is critical to designing high-performing TIM pads. Viscosity of the precursor polymer solution prior to curing plays a major role in the resulting thermal conductivity. A multipronged strategy is developed that synergistically combines reactive solid and liquid fillers, a polymer matrix with low pre-cure viscosity, and mechanical compression during thermal curing. The results of this dissertation aim to provide fundamental insights into the integration of LMs in polymer composites and give design knobs to develop high thermally conducting soft composites.
ContributorsUppal, Aastha (Author) / Rykaczewski, Konrad (Thesis advisor) / Wang, Robert (Thesis advisor) / Kwon, Beomjin (Committee member) / Choksi, Gaurang (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2022
Description
Autonomous systems inevitably must interact with other surrounding systems; thus, algorithms for intention/behavior estimation are of great interest. This thesis dissertation focuses on developing passive and active model discrimination algorithms (PMD and AMD) with applications to set-valued intention identification and fault detection for uncertain/bounded-error dynamical systems. PMD uses the obtained input-output data to invalidate the models, while AMD designs an auxiliary input to assist the discrimination process. First, PMD algorithms are proposed for noisy switched nonlinear systems constrained by metric/signal temporal logic specifications, including systems with lossy data modeled by (m,k)-firm constraints. Specifically, optimization-based algorithms are introduced for analyzing the detectability/distinguishability of models and for ruling out models that are inconsistent with observations at run time. On the other hand, two AMD approaches are designed for noisy switched nonlinear models and piecewise affine inclusion models, which involve bilevel optimization with integer variables/constraints in the inner/lower level. The first approach solves the inner problem using mixed-integer parametric optimization, whose solution is included when solving the outer problem/higher level, while the second approach moves the integer variables/constraints to the outer problem in a manner that retains feasibility and recasts the problem as a tractable mixed-integer linear programming (MILP). Furthermore, AMD algorithms are proposed for noisy discrete-time affine time-invariant systems constrained by disjunctive and coupled safety constraints. To overcome the issues associated with generalized semi-infinite constraints due to state-dependent input constraints and disjunctive safety constraints, several constraint reformulations are proposed to recast the AMD problems as tractable MILPs. Finally, partition-based AMD approaches are proposed for noisy discrete-time affine time-invariant models with model-independent parameters and output measurement that are revealed at run time. Specifically, algorithms with fixed and adaptive partitions are proposed, where the latter improves on the performance of the former by allowing the partitions to be optimized. By partitioning the operation region, the problem is solved offline, and partition trees are constructed which can be used as a `look-up table' to determine the optimal input depending on revealed information at run time.
ContributorsNiu, Ruochen (Author) / Yong, Sze Zheng S.Z. (Thesis advisor) / Berman, Spring (Committee member) / Ren, Yi (Committee member) / Zhang, Wenlong (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2022
Description
Achieving a viable process for advanced manufacturing of ceramics and metal-ceramic composites is a sought-after goal in a wide range of fields including electronics and sensors for harsh environments, microelectromechanical devices, energy storage materials, and structural materials, among others. In this dissertation, the processing, and manufacturing of ceramics and ceramic composites are addressed, specifically, a process for three-dimensional (3D) printing of polymer-derived ceramics (PDC), and a process for low-cost manufacturing as well as healing of metal-ceramic composites is demonstrated.Three-dimensional printing of ceramics is enabled by dispensing the preceramic polymer at the tip of a moving nozzle into a gel that can reversibly switch between fluid and solid states, and subsequently thermally cross-linking the entire printed part “at once” while still inside the same gel was demonstrated. The solid gel converts to fluid at the tip of the moving nozzle, allowing the polymer solution to be dispensed and quickly returns to a solid state to maintain the geometry of the printed polymer both during printing and the subsequent high-temperature (160 °C) cross-linking. After retrieving the cross-linked part from the gel, the green body is converted to ceramic by high-temperature pyrolysis. This scalable process opens new opportunities for low-cost and high-speed production of complex three-dimensional ceramic parts and will be widely used for high-temperature and corrosive environment applications, including electronics and sensors, microelectromechanical systems, energy, and structural applications.
Metal-ceramic composites are technologically significant as structural and functional materials and are among the most expensive materials to manufacture and repair. Hence, technologies for self-healing metal-ceramic composites are important. Here, a concept to fabricate and heal co-continuous metal-ceramic composites at room temperature were demonstrated. The composites were fabricated by infiltration of metal (here Copper) into a porous alumina preform (fabricated by freeze-casting) through electroplating; a low-temperature and low-cost process for the fabrication of such composites. Additionally, the same electroplating process was demonstrated for healing damages such as grooves and cracks in the original composite, such that the healed composite recovered its strength by more than 80%. Such technology may be expanded toward fully autonomous self-healing structures.
ContributorsMahmoudi, Mohammadreza (Author) / Minary-Jolandan, Majid (Thesis advisor) / Rajagopalan, Jagannathan (Committee member) / Cramer, Corson (Committee member) / Kang, Wonmo (Committee member) / Bhate, Dhruv (Committee member) / Arizona State University (Publisher)
Created2022
Description
The application of novel visualization and modeling methods to the study of cardiovascular disease is vital to the development of innovative diagnostic techniques, including those that may aid in the early detection and prevention of cardiovascular disorders. This dissertation focuses on the application of particle image velocimetry (PIV) to the study of intracardiac hemodynamics. This is accomplished primarily though the use of ultrasound based PIV, which allows for in vivo visualization of intracardiac flow without the requirement for optical access, as is required with traditional camera-based PIV methods.
The fundamentals of ultrasound PIV are introduced, including experimental methods for its implementation as well as a discussion on estimating and mitigating measurement error. Ultrasound PIV is then compared to optical PIV; this is a highly developed technique with proven accuracy; through rigorous examination it has become the “gold standard” of two-dimensional flow visualization. Results show good agreement between the two methods.
Using a mechanical left heart model, a multi-plane ultrasound PIV technique is introduced and applied to quantify a complex, three-dimensional flow that is analogous to the left intraventricular flow. Changes in ventricular flow dynamics due to the rotational orientation of mechanical heart valves are studied; the results demonstrate the importance of multi-plane imaging techniques when trying to assess the strongly three-dimensional intraventricular flow.
The potential use of ultrasound PIV as an early diagnosis technique is demonstrated through the development of a novel elasticity estimation technique. A finite element analysis routine is couple with an ensemble Kalman filter to allow for the estimation of material elasticity using forcing and displacement data derived from PIV. Results demonstrate that it is possible to estimate elasticity using forcing data derived from a PIV vector field, provided vector density is sufficient.
The fundamentals of ultrasound PIV are introduced, including experimental methods for its implementation as well as a discussion on estimating and mitigating measurement error. Ultrasound PIV is then compared to optical PIV; this is a highly developed technique with proven accuracy; through rigorous examination it has become the “gold standard” of two-dimensional flow visualization. Results show good agreement between the two methods.
Using a mechanical left heart model, a multi-plane ultrasound PIV technique is introduced and applied to quantify a complex, three-dimensional flow that is analogous to the left intraventricular flow. Changes in ventricular flow dynamics due to the rotational orientation of mechanical heart valves are studied; the results demonstrate the importance of multi-plane imaging techniques when trying to assess the strongly three-dimensional intraventricular flow.
The potential use of ultrasound PIV as an early diagnosis technique is demonstrated through the development of a novel elasticity estimation technique. A finite element analysis routine is couple with an ensemble Kalman filter to allow for the estimation of material elasticity using forcing and displacement data derived from PIV. Results demonstrate that it is possible to estimate elasticity using forcing data derived from a PIV vector field, provided vector density is sufficient.
ContributorsWesterdale, John Curtis (Author) / Adrian, Ronald (Thesis advisor) / Belohlavek, Marek (Committee member) / Squires, Kyle (Committee member) / Trimble, Steve (Committee member) / Frakes, David (Committee member) / Arizona State University (Publisher)
Created2015