Matching Items (4)
Filtering by
- Genre: Doctoral Dissertation
Description
Energy harvesting from ambient is important to configuring Wireless Sensor Networks (WSN) for environmental data collecting. In this work, highly flexible thermoelectric generators (TEGs) have been studied and fabricated to supply power to the wireless sensor notes used for data collecting in hot spring environment. The fabricated flexible TEGs can be easily deployed on the uneven surface of heated rocks at the rim of hot springs. By employing the temperature gradient between the hot rock surface and the air, these TEGs can generate power to extend the battery lifetime of the sensor notes and therefore reduce multiple batteries changes where the environment is usually harsh in hot springs. Also, they show great promise for self-powered wireless sensor notes. Traditional thermoelectric material bismuth telluride (Bi2Te3) and advanced MEMS (Microelectromechanical systems) thin film techniques were used for the fabrication. Test results show that when a flexible TEG array with an area of 3.4cm2 was placed on the hot plate surface of 80°C in the air under room temperature, it had an open circuit voltage output of 17.6mV and a short circuit current output of 0.53mA. The generated power was approximately 7mW/m2.
On the other hand, high pressure, temperatures that can reach boiling, and the pH of different hot springs ranging from <2 to >9 make hot spring ecosystem a unique environment that is difficult to study. WSN allows many scientific studies in harsh environments that are not feasible with traditional instrumentation. However, wireless pH sensing for long time in situ data collection is still challenging for two reasons. First, the existing commercial-off-the-shelf pH meters are frequent calibration dependent; second, biofouling causes significant measurement error and drift. In this work, 2-dimentional graphene pH sensors were studied and calibration free graphene pH sensor prototypes were fabricated. Test result shows the resistance of the fabricated device changes linearly with the pH values (in the range of 3-11) in the surrounding liquid environment. Field tests show graphene layer greatly prevented the microbial fouling. Therefore, graphene pH sensors are promising candidates that can be effectively used for wireless pH sensing in exploration of hot spring ecosystems.
On the other hand, high pressure, temperatures that can reach boiling, and the pH of different hot springs ranging from <2 to >9 make hot spring ecosystem a unique environment that is difficult to study. WSN allows many scientific studies in harsh environments that are not feasible with traditional instrumentation. However, wireless pH sensing for long time in situ data collection is still challenging for two reasons. First, the existing commercial-off-the-shelf pH meters are frequent calibration dependent; second, biofouling causes significant measurement error and drift. In this work, 2-dimentional graphene pH sensors were studied and calibration free graphene pH sensor prototypes were fabricated. Test result shows the resistance of the fabricated device changes linearly with the pH values (in the range of 3-11) in the surrounding liquid environment. Field tests show graphene layer greatly prevented the microbial fouling. Therefore, graphene pH sensors are promising candidates that can be effectively used for wireless pH sensing in exploration of hot spring ecosystems.
ContributorsHan, Ruirui (Author) / Yu, Hongyu (Thesis advisor) / Jiang, Hanqing (Committee member) / Yu, Hongbin (Committee member) / Garnero, Edward (Committee member) / Li, Mingming (Committee member) / Arizona State University (Publisher)
Created2018
Description
Recently, nanostructured metamaterials have attracted lots of attentions due to its tunable artificial properties. In particular, nanowire
anohole based metamaterials which are known of the capability of large area fabrication were intensively studied. Most of the studies are only based on the electrical responses of the metamaterials; however, magnetic response, is usually neglected since magnetic material does not exist naturally within the visible or infrared range. For the past few years, artificial magnetic response from nanostructure based metamaterials has been proposed. This reveals the possibility of exciting resonance modes based on magnetic responses in nanowire
anohole metamaterials which can potentially provide additional enhancement on radiative transport. On the other hand, beyond classical far-field radiative heat transfer, near-field radiation which is known of exceeding the Planck’s blackbody limit has also become a hot topic in the field.
This PhD dissertation aims to obtain a deep fundamental understanding of nanowire
anohole based metamaterials in both far-field and near-field in terms of both electrical and magnetic responses. The underlying mechanisms that can be excited by nanowire
anohole metamaterials such as electrical surface plasmon polariton, magnetic hyperbolic mode, magnetic polariton, etc., will be theoretically studied in both far-field and near-field. Furthermore, other than conventional effective medium theory which only considers the electrical response of metamaterials, the artificial magnetic response of metamaterials will also be studied through parameter retrieval of far-field optical and radiative properties for studying near-field radiative transport. Moreover, a custom-made AFM tip based metrology will be employed to experimentally study near-field radiative transfer between a plate and a sphere separated by nanometer vacuum gaps in vacuum. This transformative research will break new ground in nanoscale radiative heat transfer for various applications in energy systems, thermal management, and thermal imaging and sensing.
anohole based metamaterials which are known of the capability of large area fabrication were intensively studied. Most of the studies are only based on the electrical responses of the metamaterials; however, magnetic response, is usually neglected since magnetic material does not exist naturally within the visible or infrared range. For the past few years, artificial magnetic response from nanostructure based metamaterials has been proposed. This reveals the possibility of exciting resonance modes based on magnetic responses in nanowire
anohole metamaterials which can potentially provide additional enhancement on radiative transport. On the other hand, beyond classical far-field radiative heat transfer, near-field radiation which is known of exceeding the Planck’s blackbody limit has also become a hot topic in the field.
This PhD dissertation aims to obtain a deep fundamental understanding of nanowire
anohole based metamaterials in both far-field and near-field in terms of both electrical and magnetic responses. The underlying mechanisms that can be excited by nanowire
anohole metamaterials such as electrical surface plasmon polariton, magnetic hyperbolic mode, magnetic polariton, etc., will be theoretically studied in both far-field and near-field. Furthermore, other than conventional effective medium theory which only considers the electrical response of metamaterials, the artificial magnetic response of metamaterials will also be studied through parameter retrieval of far-field optical and radiative properties for studying near-field radiative transport. Moreover, a custom-made AFM tip based metrology will be employed to experimentally study near-field radiative transfer between a plate and a sphere separated by nanometer vacuum gaps in vacuum. This transformative research will break new ground in nanoscale radiative heat transfer for various applications in energy systems, thermal management, and thermal imaging and sensing.
ContributorsChang, Jui-Yung (Author) / Wang, Liping (Thesis advisor) / Phelan, Patrick (Committee member) / Wang, Robert (Committee member) / Yu, Hongbin (Committee member) / Hildreth, Owen (Committee member) / Arizona State University (Publisher)
Created2017
Description
The structural and electronic properties of compositionally complex semiconductors have long been of both theoretical interest and engineering importance. As a new class of materials with an intrinsic compositional complexity, medium entropy alloys (MEAs) are immensely studied mainly for their excellent mechanical properties. The electronic properties of MEAs, however, are less well investigated. In this thesis, various properties such as electronic, spin, and thermal properties of two three-dimensional (3D) and two two-dimensional (2D) compositionally complex semiconductors are demonstrated to have promising various applications in photovoltaic, thermoelectric, and spin quantum bits (qubits).3D semiconducting Si-Ge-Sn and C3BN alloys is firstly introduced. Density functional theory (DFT) calculations and Monte Carlo simulations show that the Si1/3Ge1/3Sn1/3 MEA exhibits a large local distortion effect yet no chemical short-range order. Single vacancies in this MEA can be stabilized by bond reformations while the alloy retains semiconducting. DFT and molecular dynamics calculations predict that increasing the compositional disorder in SiyGeySnx MEAs enhances their electrical conductivity while weakens the thermal conductivity at room temperature, making the SiyGeySnx MEAs promising functional materials for thermoelectric devices. Furthermore, the nitrogen-vacancy (NV) center analog in C3BN (NV-C3BN) is studied to explore its applications in quantum computers. This analog possesses similar properties to the NV center in diamond such as a highly localized spin density and strong hyperfine interactions, making C3BN suitable for hosting spin qubits. The analog also displays two zero-phonon-line energies corresponding to wavelengths close to the ideal telecommunication band width, useful for quantum communications.
2D semiconducting transition metal chalcogenides (TMCs) and PtPN are also investigated. The quaternary compositionally complex TMCs show tunable properties such as in-plane lattice constants, band gaps, and band alignment, using a high through-put workflow from DFT calculations in conjunction with the virtual crystal approximation. A novel 2D semiconductor PtPN of direct bandgap is also predicted, based on pentagonal tessellation.
The work in the thesis offers guidance to the experimental realization of these novel semiconductors, which serve as valuable prototypes of other compositionally complex systems from other elements.
2D semiconducting transition metal chalcogenides (TMCs) and PtPN are also investigated. The quaternary compositionally complex TMCs show tunable properties such as in-plane lattice constants, band gaps, and band alignment, using a high through-put workflow from DFT calculations in conjunction with the virtual crystal approximation. A novel 2D semiconductor PtPN of direct bandgap is also predicted, based on pentagonal tessellation.
The work in the thesis offers guidance to the experimental realization of these novel semiconductors, which serve as valuable prototypes of other compositionally complex systems from other elements.
ContributorsWang, Duo (Author) / Zhuang, Houlong (Thesis advisor) / Singh, Arunima (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2020
Description
Movement disorders are becoming one of the leading causes of functional disability due to aging populations and extended life expectancy. Diagnosis, treatment, and rehabilitation currently depend on the behavior observed in a clinical environment. After the patient leaves the clinic, there is no standard approach to continuously monitor the patient and report potential problems. Furthermore, self-recording is inconvenient and unreliable. To address these challenges, wearable health monitoring is emerging as an effective way to augment clinical care for movement disorders.
Wearable devices are being used in many health, fitness, and activity monitoring applications. However, their widespread adoption has been hindered by several adaptation and technical challenges. First, conventional rigid devices are uncomfortable to wear for long periods. Second, wearable devices must operate under very low-energy budgets due to their small battery capacities. Small batteries create a need for frequent recharging, which in turn leads users to stop using them. Third, the usefulness of wearable devices must be demonstrated through high impact applications such that users can get value out of them.
This dissertation presents solutions to solving the challenges faced by wearable devices. First, it presents an open-source hardware/software platform for wearable health monitoring. The proposed platform uses flexible hybrid electronics to enable devices that conform to the shape of the user’s body. Second, it proposes an algorithm to enable recharge-free operation of wearable devices that harvest energy from the environment. The proposed solution maximizes the performance of the wearable device under minimum energy constraints. The results of the proposed algorithm are, on average, within 3% of the optimal solution computed offline. Third, a comprehensive framework for human activity recognition (HAR), one of the first steps towards a solution for movement disorders is presented. It starts with an online learning framework for HAR. Experiments on a low power IoT device (TI-CC2650 MCU) with twenty-two users show 95% accuracy in identifying seven activities and their transitions with less than 12.5 mW power consumption. The online learning framework is accompanied by a transfer learning approach for HAR that determines the number of neural network layers to transfer among uses to enable efficient online learning. Next, a technique to co-optimize the accuracy and active time of wearable applications by utilizing multiple design points with different energy-accuracy trade-offs is presented. The proposed technique switches between the design points at runtime to maximize a generalized objective function under tight harvested energy budget constraints. Finally, we present the first ultra-low-energy hardware accelerator that makes it practical to perform HAR on energy harvested from wearable devices. The accelerator consumes 22.4 microjoules per operation using a commercial 65 nm technology. In summary, the solutions presented in this dissertation can enable the wider adoption of wearable devices.
Wearable devices are being used in many health, fitness, and activity monitoring applications. However, their widespread adoption has been hindered by several adaptation and technical challenges. First, conventional rigid devices are uncomfortable to wear for long periods. Second, wearable devices must operate under very low-energy budgets due to their small battery capacities. Small batteries create a need for frequent recharging, which in turn leads users to stop using them. Third, the usefulness of wearable devices must be demonstrated through high impact applications such that users can get value out of them.
This dissertation presents solutions to solving the challenges faced by wearable devices. First, it presents an open-source hardware/software platform for wearable health monitoring. The proposed platform uses flexible hybrid electronics to enable devices that conform to the shape of the user’s body. Second, it proposes an algorithm to enable recharge-free operation of wearable devices that harvest energy from the environment. The proposed solution maximizes the performance of the wearable device under minimum energy constraints. The results of the proposed algorithm are, on average, within 3% of the optimal solution computed offline. Third, a comprehensive framework for human activity recognition (HAR), one of the first steps towards a solution for movement disorders is presented. It starts with an online learning framework for HAR. Experiments on a low power IoT device (TI-CC2650 MCU) with twenty-two users show 95% accuracy in identifying seven activities and their transitions with less than 12.5 mW power consumption. The online learning framework is accompanied by a transfer learning approach for HAR that determines the number of neural network layers to transfer among uses to enable efficient online learning. Next, a technique to co-optimize the accuracy and active time of wearable applications by utilizing multiple design points with different energy-accuracy trade-offs is presented. The proposed technique switches between the design points at runtime to maximize a generalized objective function under tight harvested energy budget constraints. Finally, we present the first ultra-low-energy hardware accelerator that makes it practical to perform HAR on energy harvested from wearable devices. The accelerator consumes 22.4 microjoules per operation using a commercial 65 nm technology. In summary, the solutions presented in this dissertation can enable the wider adoption of wearable devices.
ContributorsBhat, Ganapati (Author) / Ogras, Umit Y. (Thesis advisor) / Chakrabarti, Chaitali (Committee member) / Nedić, Angelia (Committee member) / Marculescu, Radu (Committee member) / Arizona State University (Publisher)
Created2020