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Description
Walking and mobility are essential aspects of our daily lives, enabling us to engage in various activities. Gait disorders and impaired mobility are widespread challenges faced by older adults and people with neurological injuries, as these conditions can significantly impact their quality of life, leading to a loss of independence and an increased risk of mortality. In response to these challenges, rehabilitation, and assistive robotics have emerged as promising alternatives to conventional gait therapy, offering potential solutions that are less labor-intensive and costly. Despite numerous advances in wearable lower-limb robotics, their current applicability remains confined to laboratory settings. To expand their utility to broader gait impairments and daily living conditions, there is a pressing need for more intelligent robot controllers. In this dissertation, these challenges are tackled from two perspectives: First, to improve the robot's understanding of human motion and intentions which is crucial for assistive robot control, a robust human locomotion estimation technique is presented, focusing on measuring trunk motion. Employing an invariant extended Kalman filtering method that takes sensor misplacement into account, improved convergence properties over the existing methods for different locomotion modes are shown. Secondly, to enhance safe and effective robot-aided gait training, this dissertation proposes to directly learn from physical therapists' demonstrations of manual gait assistance in post-stroke rehabilitation.
Lower-limb kinematics of patients and assistive force applied by therapists to the patient's leg are measured using a wearable sensing system which includes a custom-made force sensing array. The collected data is then used to characterize a therapist's strategies. Preliminary analysis indicates that knee extension and weight-shifting play pivotal roles in shaping a therapist's assistance strategies, which are then incorporated into a virtual impedance model that effectively captures high-level therapist behaviors throughout a complete training session. Furthermore, to introduce safety constraints in the design of such controllers, a safety-critical learning framework is explored through theoretical analysis and simulations. A safety filter incorporating an online iterative learning component is introduced to bring robust safety guarantees for gait robotic assistance and training, addressing challenges such as stochasticity and the absence of a known prior dynamic model.
ContributorsRezayat Sorkhabadi, Seyed Mostafa (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
In the realm of biosensors and nanotechnology, deoxyribonucleic acid (DNA) nanosensors have demonstrated tremendous potential across diverse real-world applications, from environmental monitoring to healthcare diagnostics. Fabrication of nanosensors allows assembling and designing of DNA molecules at nanoscale with high precision and versatility. Such fabricating DNA nanosensors are quite time consuming. Hence it is important to store them in batches. However synthetic DNA molecules can be prone to degradation over time, especially when exposed to various environmental factors like light, heat, or any other chemical contaminants. To address this issue, a shelf life study of DNA nanosensors using various lyoprotectant conditions was carried out to determine the long term stability of such sensors. This study involves fabrication of the dendritic, double - stranded DNA nanosensors involving five strands L1 through L5 conjugated with pHAb fluorophores via N-hydroxysuccinimide ester reaction and acetylcholinesterase (AChE) enzyme, a core component of the sensor. This sensor was originally a fluorescent ACh-selective nanosensors designed to accommodate the BTX ligand, AChE to image the ACh release in the submandibular region of the living mice to report real time quantitative endogenous ACh release triggered by electrical stimulation. AChE enzyme is a good receptor to detect acetylcholine release in the Peripheral Nervous System (PNS). The primary objective of the study was to assess DNA nanosensors with AChE, however due to the intricate interactions, non-specific binding and cost-effectiveness, the shelf life study was carried out separately. The shelf study includes observing DNA nanosensors with different disaccharide lyoprotectants like trehalose and sucrose that were analyzed under different temperature conditions: room temperature (25ºC) and at 50 ºC for different time intervals, over a week time. Also, Observing AChE with various protectants under 50 ºC with and without lyoprotectants for various time intervals like 24 hours and 48 hours. To replicate the real-world transit scenarios, the study also involves test-shipment of the samples with lyoprotectants for 2-3 days to both cross-country and local (in-state). As a result, the use of lyoprotectants, particularly trehalose, has proven to be more resilient and effective in preserving the stability and integrity of DNA nanosensors and Acetylcholinesterase (AChE) enzymes
ContributorsSrinivasan, Nikita (Author) / Clark, Heather A (Thesis advisor) / Ma, Kristine Y (Committee member) / Beeman, Scott (Committee member) / Arizona State University (Publisher)
Created2023
Description
Tire blowout often occurs during driving, which can suddenly disturb vehicle motions and seriously threaten road safety. Currently, there is still a lack of effective methods to mitigate tire blowout risks in everyday traffic, even for automated vehicles. To fundamentally study and systematically resolve the tire blowout issue for automated vehicles, a collaborative project between General Motors (GM) and Arizona State University (ASU) has been conducted since 2018. In this dissertation, three main contributions of this project will be presented. First, to explore vehicle dynamics with tire blowout impacts and establish an effective simulation platform for close-loop control performance evaluation, high-fidelity tire blowout models are thoroughly developed by explicitly considering important vehicle parameters and variables. Second, since human cooperation is required to control Level 2/3 partially automated vehicles (PAVs), novel shared steering control schemes are specifically proposed for tire blowout to ensure safe vehicle stabilization via cooperative driving. Third, for Level 4/5 highly automated vehicles (HAVs) without human control, the development of control-oriented vehicle models, controllability study, and automatic control designs are performed based on impulsive differential systems (IDS) theories.
Co-simulations Matlab/Simulink® and CarSim® are conducted to validate performances of all models and control designs proposed in this dissertation. Moreover, a scaled test vehicle at ASU and a full-size test vehicle at GM are well instrumented for data collection and control implementation. Various tire blowout experiments for different scenarios are conducted for more rigorous validations. Consequently, the proposed high-fidelity tire blowout models can correctly and more accurately describe vehicle motions upon tire blowout. The developed shared steering control schemes for PAVs and automatic control designs for HAVs can effectively stabilize a vehicle to maintain path following performance in the driving lane after tire blowout.
In addition to new research findings and developments in this dissertation, a pending patent for tire blowout detection is also generated in the tire blowout project. The obtained research results have attracted interest from automotive manufacturers and could have a significant impact on driving safety enhancement for automated vehicles upon tire blowout.
ContributorsLi, Ao (Author) / Chen, Yan (Thesis advisor) / Berman, Spring (Committee member) / Kannan, Arunachala Mada (Committee member) / Liu, Yongming (Committee member) / Lin, Wen-Chiao (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2023
Description
Urease, an amidohydrolase, is an essential ingredient in the emerging engineering technique of biocementation. When free urease enzyme is used this carbonate precipitation process is often referred to as enzyme induced carbonate precipitation (EICP). To date, most engineering applications of EICP have used commercially available powdered urease. However, the high cost of commercially available urease is a major barrier to adoption of engineering applications of EICP in practice. The objective of this dissertation was to develop a simple and inexpensive enzyme production technique using agricultural resources. The specific objectives of this dissertation were (i) to develop a simple extraction process to obtain urease from common agricultural resources and identify a preferred agricultural resource for further study, (ii) to reduce the cost of enzyme production by eliminating the use of a buffer, centrifugation, and dehusking of the beans during the extraction process, (iii) investigate the stability of the extracted enzyme both in solution and after reduction to a powder by lyophilization (freeze-drying), and (iv) to study the kinetics of the extracted enzyme.
The results presented in this dissertation confirmed that inexpensive crude extracts of urease from agricultural products, including jack beans, soybeans, and watermelon seeds, are effective at catalyzing urea hydrolysis for carbonate precipitation. Based upon unit yield, jack beans were identified as the preferred agricultural resource for urease extraction. Results also showed that the jack bean extract retained its activity even after replacing the buffer with tap water and eliminating acetone fractionation, centrifugation, and dehusking. It was also found that the lyophilized crude extract maintained its activity during storage for at least one year and more effectively than either the crude extract solution or rehydrated commercial urease. The kinetics of the extracted enzyme was studied to gain greater insight into the optimum concentration of urea in engineering applications of EICP. Results showed higher values for the half-saturation coefficient of the crude extract compared to the commercial enzymes.
The results presented in this dissertation demonstrate the potential for a significant reduction in the cost of applying EICP in engineering practice by mass production of urease enzyme via a simple extraction process.
ContributorsJavadi, Neda (Author) / Kavazanjian, Edward (Thesis advisor) / Khodadadi Tirkolaei, Hamed (Committee member) / Hamadan, Naser (Committee member) / Delgado, Anca (Committee member) / Arizona State University (Publisher)
Created2021
The Intercoupling of Thermal Transport and Mechanical Properties in Colloidal Nanocrystal Assemblies
Description
Colloidal nanocrystals (NCs) are promising candidates for a wide range of applications (electronics, optoelectronics, photovoltaics, thermoelectrics, etc.). Mechanical and thermal transport property play very important roles in all of these applications. On one hand, mechanical robustness and high thermal conductivity are desired in electronics, optoelectronics, and photovoltaics. This improves thermomechanical stability and minimizes the temperature rise during the device operation. On the other hand, low thermal conductivity is desired for higher thermoelectric figure of merit (ZT). This dissertation demonstrates that ligand structure and nanocrystal ordering are the primary determining factors for thermal transport and mechanical properties in colloidal nanocrystal assemblies. To eliminate the mechanics and thermal transport barrier, I first propose a ligand crosslinking method to improve the thermal transport across the ligand-ligand interface and thus increasing the overall thermal conductivity of NC assemblies. Young’s modulus of nanocrystal solids also increases simultaneously upon ligand crosslinking. My thermal transport measurements show that the thermal conductivity of the iron oxide NC solids increases by a factor of 2-3 upon ligand crosslinking. Further, I demonstrate that, though with same composition, long-range ordered nanocrystal superlattices possess higher mechanical and thermal transport properties than disordered nanocrystal thin films. Experimental measurements along with theoretical modeling indicate that stronger ligand-ligand interaction in NC superlattice accounts for the improved mechanics and thermal transport. This suggests that NC/ligand arranging order also plays important roles in determining mechanics and thermal transport properties of NC assemblies. Lastly, I show that inorganic ligand functionalization could lead to tremendous mechanical enhancement (a factor of ~60) in NC solids. After ligand exchange and drying, the short inorganic Sn2S64- ligands dissociate into a few atomic layers of amorphous SnS2 at room temperature and interconnects the neighboring NCs. I observe a reverse Hall-Petch relation as the size of NC decreases. Both atomistic simulations and analytical phase mixture modeling identify the grain boundaries and their activities as the mechanic bottleneck.
ContributorsWang, Zhongyong (Author) / Wang, Robert RW (Thesis advisor) / Wang, Liping LW (Committee member) / Newman, Nathan NN (Committee member) / Arizona State University (Publisher)
Created2021
Description
A well-insulated dark conventional rooftop can be hotter than any other urban surface, including pavements. Since rooftops cover around 20 – 25% of most urban areas, their role in the urban heat island effect is significant. In general, buildings exchange heat with the surroundings in three ways: heat release from the cooling/heating system, air exchange associated with exfiltration and relief air, and heat transfer between the building envelope and surroundings. Several recent studies show that the building envelope generates more heat release into the environment than any other building component.Current advancements in material science have enabled the development of materials and coatings with very high solar reflectance and thermal emissivity, and that can alter their radiative properties based on surface temperature. This dissertation is an effort to quantify the impact of recent developments in such technologies on urban air. The current study addresses three specific unresolved topics: 1) the relative importance of rooftop solar reflectance and thermal emissivity, 2) the role of rooftop radiative properties in different climates, and 3) the impact of temperature-adaptive exterior materials/coatings on building energy savings and urban cooling. The findings from this study show that the use of rooftop materials with solar reflectance above 0.9 maintain the surface temperature below ambient air temperature most of the time, even when the materials have conventional thermal emissivity (0.9). This research has demonstrated that for hot cities, rooftops with high solar reflectance and thermal emittance maximize building energy savings and always cool the surrounding air. For moderate climate regions, high solar reflectance and low thermal emittance result in the greatest building energy cost savings. This combination of radiative properties cools the air during the daytime and warms it at night. Finally, this research found that temperature-adaptive materials could play a significant role in reducing utility costs for poorly insulated buildings, but that they heat the surrounding air in the winter, irrespective of the rooftop insulation.
Through the detailed analysis of building façade radiative properties, this dissertation offers climate-specific design guidance that can be used to simultaneously optimize energy costs while minimizing adverse warming of the surrounding environment.
ContributorsPrem Anand Jayaprabha, Jyothis Anand (Author) / Sailor, David (Thesis advisor) / Phelan, Patrick (Thesis advisor) / Huang, Huei-Ping (Committee member) / Wang, Liping (Committee member) / Yeom, Dongwoo Jason (Committee member) / Arizona State University (Publisher)
Created2022
Description
Integrating advanced materials with innovative manufacturing techniques has propelled the field of additive manufacturing into new frontiers. This study explores the rapid 3D printing of reduced graphene oxide/polymer composites using Micro-Continuous Liquid Interface Production (μCLIP), a cutting-edge technology known for its speed and precision. A printable ink is formulated with reduced graphene oxide for μCLIP-based 3D printing. The research focuses on optimizing μCLIP parameters to fabricate reduced graphene composites efficiently. The study encompasses material synthesis, ink formulation and explores the resulting material's structural and electrical properties. The marriage of graphene's unique attributes with the rapid prototyping capabilities of μCLIP opens new avenues for scalable and rapid production in applications such as energy storage, sensors, and lightweight structural components. This work contributes to the evolving landscape of advanced materials and additive manufacturing, offering insights into the synthesis, characterization, and potential applications of 3D printed reduced graphene oxide/polymercomposites.
ContributorsRavishankar, Chayaank Bangalore (Author) / Chen, Xiangfan (Thesis advisor) / Bhate, Dhruv (Committee member) / Azeredo, Bruno (Committee member) / Arizona State University (Publisher)
Created2024
Description
The complex network of the immune system defends the human body against infection, providing protection from pathogens. This work aims to improve preparation and structural knowledge of two proteins on opposite sides of the immune system spectrum. The first protein, secreted autotransporter toxin (Sat) is a class I serine protease autotransporter of Enterobacteriaceae (SPATE) that has cytotoxic and immunomodulatory effects on the host. Previous studies on Sat show its ability to aid in bacterial colonization and evasion of the immune system. This work improves the stability of Sat by making mutations to the active serine protease motif (GDSGS) while inhibiting remaining activity with reversible and irreversible serine protease inhibitors. Characterization of Sat by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), and size-exclusion chromatography led to the first structural studies of Sat by x-ray crystallography and cryo-EM. Human leukocyte antigen class I proteins play an important role in the adaptive immune system by presenting endogenous viral peptides at the cell surface for CD8+ T cell recognition. In vitro production of HLA-I proteins is a difficult task without endoplasmic reticulum chaperones as present in vivo. Disulfide bond formation, folded light chain and a peptide bound are all key to refolding the HLA-I heavy chain for complex formation. The work presented in this dissertation represents systematic studies aimed at improving the production of HLA-I proteins in vitro in bacterial expression systems. Optimization of every step of the preparation was investigated providing higher expression yields, quality of inclusion bodies, and refolding improvements. With further improvements in the future, this work forms the basis for a more efficient small and large-scale production of HLA-I molecules for functional and structural studies.
ContributorsKiefer, Dalton (Author) / Anderson, Karen (Thesis advisor) / Fromme, Petra (Thesis advisor) / Chiu, Po-Lin (Committee member) / Mazor, Yuval (Committee member) / Arizona State University (Publisher)
Created2024
Description
The thylakoid membranes of oxygenic photosynthetic organisms contain four large membrane complexes vital for photosynthesis: photosystem II and photosystem I (PSII and PSI, respectively), the cytochrome b6f complex and ATP synthase. Two of these complexes, PSII and PSI, utilize solar energy to carry out the primary reaction of photosynthesis, light induced charge separation. In vivo, both photosystems associate with multiple antennae to increase their light absorption cross section. The antennae, Iron Stress Induced A (IsiA), is expressed in cyanobacteria as part of general stress response and forms a ring system around PSI. IsiA is a member of a large and relatively unexplored antennae family prevalent in cyanobacteria. The structure of the PSI-IsiA super-complex from the cyanobacteria Synechocystis sp. PCC 6803 was resolved to high resolution, revealing how IsiA interacts with PSI as well as the chlorophyll organization within this antennae system. Despite these structural insights, the basis for the binding between 18 IsiA subits and PSI is not fully resolved. Several IsiA mutants were constructed using insights from the atomic structure of PSI-IsiA, revealing the role of the C-terminus of IsiA in its interaction with PSI.
ContributorsLi, Jin (Author) / Mazor, Yuval (Thesis advisor) / Chiu, Po-Lin (Committee member) / Mills, Jeremy (Committee member) / Arizona State University (Publisher)
Created2024
Description
When solving analysis, estimation, and control problems for Partial Differential Equations (PDEs) via computational methods, one must resolve three main challenges: (a) the lack of a universal parametric representation of PDEs; (b) handling unbounded differential operators that appear as parameters; and (c), enforcing auxiliary constraints such as Boundary conditions and continuity conditions. To address these challenges, an alternative representation of PDEs called the `Partial Integral Equation' (PIE) representation is proposed in this work. Primarily, the PIE representation alleviates the problem of the lack of a universal parametrization of PDEs since PIEs have, at most, $12$ Partial Integral (PI) operators as parameters. Naturally, this also resolves the challenges in handling unbounded operators because PI operators are bounded linear operators. Furthermore, for admissible PDEs, the PIE representation is unique and has no auxiliary constraints --- resolving the last of the $3$ main challenges. The PIE representation for a PDE is obtained by finding a unique unitary map from the states of the PIE to the states of the PDE. This map shows a PDE and its associated PIE have equivalent system properties, including well-posedness, internal stability, and I/O behavior. Furthermore, this unique map also allows us to construct a well-defined dual representation that can be used to solve optimal control problems for a PDE. Using the equivalent PIE representation of a PDE, mathematical and computational tools are developed to solve standard problems in Control theory for PDEs. In particular, problems such as a test for internal stability, Input-to-Output (I/O) $L_2$-gain, $\hinf$-optimal state observer design, and $\hinf$-optimal full state-feedback controller design are solved using convex-optimization and Lyapunov methods for linear PDEs in one spatial dimension. Once the PIE associated with a PDE is obtained, Lyapunov functions (or storage functions) are parametrized by positive PI operators to obtain a solvable convex formulation of the above-stated control problems. Lastly, the methods proposed here are applied to various PDE systems to demonstrate the application.
ContributorsShivakumar, Sachin (Author) / Peet, Matthew (Thesis advisor) / Nedich, Angelia (Committee member) / Marvi, Hamidreza (Committee member) / Platte, Rodrigo (Committee member) / Berman, Spring (Committee member) / Arizona State University (Publisher)
Created2024