Non-precious metal catalysts (NPMC) for proton exchange membrane fuel cells (PEMFC) are explored. Research into NPMCs is motivated by the growing need for cleaner, more efficient energy options. NPMCs are one option to make fuel cells more commercially viable. To this end, the present work studies and simulates the morphology and function of metal-nitrogen-carbon (MNC) oxygen reduction catalysts.A porosity study finds that mesoporosity is critical to high performance of autogenic pressure metal-nitrogen-carbon (APMNC) oxygen reduction catalysts. Various carbon materials are used as precursors to synthesis APMNC catalysts. The catalysts and the associated porous carbon materials are characterized morphologically, chemically, and electrochemically. The results indicated that substrates adsorbing the most nitrogen and iron show the highest activity. Furthermore, a relationship is found between mesoporosity and nitrogen content indicating the importance of transport to active site creation.A correlation is found between surface alkalinity and catalytic activity for APMNC catalysts. The basic site strength and quantity were calculated by two different methods, and it was shown that increased Brønsted- Lowry basicity correlates to more active catalysts. The relationship between alkalinity and catalytic activity could be the result of the impact of alkalinity on the electron density of the metal centers or basic sites could encourage active site formation.It is found that the oxygen reduction reaction (ORR) proceeds both via a direct four-electron pathway to water at high potentials and an indirect peroxide pathway at low potentials on an APMNC catalyst. At higher potential, site availability inhibits peroxide generation causing the direct four-electron reduction pathway to dominate. Oxygen reduction begins to shift to the indirect peroxide pathway due to fast kinetics and higher site availability around 0.6 V vs RHE. The net peroxide generation remains relatively low over the entire range due to reduction of peroxide to water.A PEMFC cathode model is developed for hydrophilic MNC catalysts. Water flooding was studied in terms of its impact on gas-phase transport and electrochemically accessible surface area (ECSA). Fuel cell data is modeled at a variety of pressures and catalyst layer thicknesses. A sensitivity study is performed on the controllable cathode parameters. Sensitivity analysis identified loading and density as critical parameters, and parametric studies indicated that decreased loading would lead to higher catalyst utilization. Also, density and loading of the catalyst layer are optimized for various fuel cell potential regions.

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This dissertation introduces the design, fabrication, and application of acopper-oxide-based memristor for the passive sensing of oxygen and other gases.The device design was as follows: Deposition of copper (Cu) bottom electrodes,(oxygen) vacancy-rich copper oxide (CuxO) switching layers, and tungsten (W) topelectrodes in a crossbar array structure. The CuxO layer was deposited via reactivesputtering of a Cu target with an argon-oxygen (Ar/O2) mixture. A portion of thislayer was extended from each array cell to be exposed for sensing. Memristivedevices of different switching layer thicknesses were initially explored forirreversible sensing of oxygen in ambient air. Results of this first experimentdemonstrated an increase in resistance states upon prolonged exposure toambient air. For the second experiment, memristive devices were fabricated withsub-micron holes that were etched into the W top electrode to better reveal theswitching layer surface. The devices were also subjected to ambient oxygen at 180deg C to induce passive sensing in minutes. Resistance results were consistentwith the first experiment but also revealed a dependence on the surface area ofthe exposed oxide. Finally, memristive devices were investigated in a thirdexperiment for reversible sensing of an oxidizing gas and reducing gas at roomtemperature. This time, changes were not only observed in resistance but also inhysteresis (current versus voltage) depending on the type of gas introduced.Overall, this work demonstrates a step towards the use of the memristor as a gassensor, which we have named “memsensors”, by taking advantage of the device’sability to memorize (or record) historical information.

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Thesis Ph. D. Michigan State University. Electrical Engineering 2019

"Robots have been transforming our daily lives by moving from controlled industrial lines to unstructured and dynamic environments such as home, offices, or outdoors working closely with human co-workers. Accordingly, there is an emerging and urgent need for human users to communicate with robots through natural language (NL) due to its convenience and expressibility, especially for the technically untrained people. Nevertheless, two fundamental problems remain unsolved for robots to working in such environments. On one hand, how to control robot behaviors in dynamic environments due to presence of people is still a daunting task. On the other hand, robot skills are usually preprogrammed while an application scenario may require a robot to perform new tasks. How to program a new skill to robots using NL on the fly also requires tremendous efforts. This dissertation tries to tackle these two problems in the framework of supervisory control. On the control aspect, it will be shown ideas drawn from dynamic discrete event systems can be used to model environmental dynamics and guarantee safety and stability of robot behaviors. Specifically, the procedures to build robot behavioral model and the criteria for model property checking will be presented. As there are enormous utterances in language with different abstraction level, a hierarchical framework is proposed to handle tasks lying in different logic depth. Behavior consistency and stability under hierarchy are discussed. On the programming aspect, a novel online programming via NL approach that formulate the problem in state space is presented. This method can be implemented on the fly without terminating the robot implementation. The advantage of such a method is that there is no need to laboriously labeling data for skill training, which is required by traditional offline training methods. In addition, integrated with the developed control framework, the newly programmed skills can also be applied to dynamic environments. In addition to the developed robot control approach that translates language instructions into symbolic representations to guide robot behaviors, a novel approach to transform NL instructions into scene representation is presented for robot behaviors guidance, such as robotic drawing, painting, etc. Instead of using a local object library or direct text-to-pixel mappings, the proposed approach utilizes knowledge retrieved from Internet image search engines, which helps to generate diverse and creative scenes. The proposed approach allows interactive tuning of the synthesized scene via NL. This helps to generate more complex and semantically meaningful scenes, and to correct training errors or bias. The success of robot behavior control and programming relies on correct estimation of task implementation status, which is comprised of robotic status and environmental status. Besides vision information to estimate environmental status, tactile information is heavily used to…

Thesis Ph. D. Michigan State University. Electrical Engineering 2016

Optogenetics is a fast growing neuromodulation technique, which can remotely manipulate the specific activities of genetically-targeted neural cells and associated biological behaviors with millisecond temporal precision through light illumination. Application of optogenetics in neuroscience studies has created an increased need for the development of light sources and the instruments for light delivery. Micro-Light-emitting diodes (μ-LEDs) offer a great option as the light source for optogenetics since they are power-efficient, low-cost and suitable for integration with wireless electronics. Furthermore, arrays of individually addressable μ-LEDs have been developed to accomplish multisite in-vivo stimulation. However, a critical challenge of using μ-LEDs as the light source for optogenetics is their intrinsically low out-coupling efficiency and wide irradiation angles due to the Lambertian emission pattern, which results in a big loss of the radiation. Consequently, μ-LEDs must be driven with high power in order to reach the required light intensity of 1 mW/mm2 and 7 mW/mm2 for effective activation of excitatory and inhibitory opsins at the target site, respectively. However, this is not suitable for wireless operation, and could induce potential thermal interference or damage to tissues due to Joule heating effect. In this thesis, an implantable, micro-lens-coupled LED stimulator has been proposed to be applied as the light source for neural stimulation. A reflector and a microlens were coupled with the μ-LED chip for light collection and collimation, giving rise to a significantly improved light irradiance. A novel microfabrication method, vapor-induced dewetting, was developed to make self-organized SU-8 microlens arrays. It was later involved in the fabrication and integration process of micro-lens-coupled LED stimulators. An optimization on the device structure was carried out using optical simulation in order to attain optimal penetration capabilities of the light. The optimized micro-lens-coupled LED stimulator was microfabricated and measured both in air and in tissue experimentally. Significant improvement of >60% in light intensity was achieved, validating its functionality and potential as the light source for optogenetic neuromodulation in dep cortical layers.

Description based on online resource;

Thesis Ph. D. Michigan State University. Electrical Engineering 2016

"Underwater creatures, especially fish, have received significant attention over the past several decades because of their fascinating swimming abilities and behaviors, which have inspired engineers to develop robots that propel and maneuver like real fish. This dissertation is focused on the role of flexibility in robotic fish performance, including the design, dynamic modeling, and experimental validation of flexible pectoral fins, flexible passive joints for pectoral fins, and fins with actively controlled stiffness. First, the swimming performance and mechanical efficiency of flexible pectoral fins, connected to actuator shafts via rigid links, are studied, where it is found that flexible fins demonstrate advantages over rigid fins in speed and efficiency at relatively low fin-beat frequencies, while the rigid fins outperform the flexible fins at higher frequencies. The presented model offers a promising tool for the design of fin flexibility and swimming gait, to achieve speed and efficiency objectives for the robotic fish. The traditional rigid joint for pectoral fins requires different speeds for power and recovery strokes in order to produce net thrust and consequently results in control complexity and low speed performance. To address this issue, a novel flexible passive joint is presented where the fin is restricted to rowing motion during both power and recovery strokes. This joint allows the pectoral fin to sweep back passively during the recovery stroke while it follows the prescribed motion of the actuator during the power stroke, which results in net thrust even under symmetric actuation for power and recovery strokes. The dynamic model of a robotic fish equipped with such joints is developed and validated through extensive experiments. Motivated by the need for design optimization, the model is further utilized to investigate the influences of the joint length and stiffness on the robot locomotion performance and efficiency. An alternative flexible joint for pectoral fins is also proposed, which enables the pectoral fin to operate primarily in the rowing mode, while undergoing passive feathering during the recovery stroke to reduce hydrodynamic drag on the fin. A dynamic model, verified experimentally, is developed to examine the trade-off between swimming speed and mechanical efficiency in the fin design. Finally, we investigate flexible fins with actively tunable stiffness, enabled by electrorheological (ER) fluids. The tunable stiffness can be used in optimizing the robotic fish speed or maneuverability in different operating regimes. Fins with tunable stiffness are prototyped with ER fluids enclosed between layers of liquid urethane rubber (Vytaflex 10). Free oscillation and base-excited oscillation behaviors of the fins are measured underwater when different electric fields are applied for the ER fluid, which are subsequently used to develop a dynamic model for the stiffness-tunable fins." – Pages ii-iii.

Description…

Thesis Ph. D. Michigan State University. Electrical Engineering - Doctor of Philosophy 2014.

Graphene has attracted research interest since its discovery in 2004 and professor Geim's receipt of the Nobel prize in 2010. It has been used for constructing a variety of electronics and sensors due to its unique electrical, mechanical, thermal, and optical properties.In this dissertation, we developed several technologies to control the electronic properties of graphene, which will pave the way for the future development of graphene nanoelectronics. First, since graphene properties vary depending on its number of layers, we identified a method for engineering the number of graphene layers using fine-tuned oxygen plasma etching. With this technique a single layer of graphene can be removed at a time. In addition, we demonstrated a template-less nanofabrication technique for batch production of graphene nanomeshes and multiribbons, and explored the feasibility of using these nanopatterns to construct field effect transistors (FETs). By introducing nanopatterns into pristine graphene, we could effectively open the band gap of graphene and convert it from semimetal into semiconductor. Furthermore, we studied a doping method for making n-type graphene with long-term chemical stability in air and stability at wide range of temperature. Highly stable n-type graphene with minimal defects was achieved using photo acid generator (PAG) mixed with SU-8 epoxy resin as an effective electron dopant and encapsulation. The electronic properties of the as-doped n-type graphene were confirmed by measuring its current transport characteristics and Fermi level shifts.Building on the aforementioned engineering techniques, we proposed a new Metal-SU8-graphene (MSG) technology, which is compatible with the conventional CMOS fabricationtechnology. MSG FETs were fabricated on both rigid and flexible substrates. A graphene invertor was also constructed as a proof of concept.Finally, we explored the potential applications of graphene in nanosensors, including chemical, temperature and flow sensors. We studied the possibility of using inter-layer graphene nano configuration to detect the absorption/desorption of different chemical molecules. Our results show a remarkable enhancement in graphene surface sensitivity, which can be attributed to extra edges and inter-sheet tunneling effects. We also demonstrated the capability of using graphene nanowires in temperature and flowrate sensing.

Description based on online resource;

Thesis M.S. Michigan State University. Electrical Engineering 2014.

Optogenetics is a fast growing neuromodulation technique which can remotely manipulate the specific activities of targeted neurons with irradiation of light. It benefits exploration of neuron network dynamics and also clinical studies such as retinal prosthesis. Light emitting diode (LED) offers a great option as the light source for optogenetics because it is small, reliable and easy to control. Especially, arrays of LEDs have been developed to enable multisite stimulation. A major drawback of LED is its intrinsically low out-coupling efficiency of light as a result of a large emitting angle around 90° to 120°. In this thesis, the employment of μ-lens array has been proposed to couple with LED and target the improvement of light out-coupling efficiency, which will lead to a higher spatial resolution for optical neural stimulation. A number of techniques, including surface tension modification, soft lithography, thermal reflow, and self-organized dewetting, have been studied to fabricate the array of μ-lenses on a flexible polymer substrate. Surface morphology of such μ-lens array has been analyzed both experimentally and theoretically. Experiment in the medium of gelatin has been carried out to mimic the light irradiation property in the natural tissue.

Description based on online resource; title from PDF t.p. (viewed on July 11, 2017)

Thesis Ph. D. Michigan State University. Electrical Engineering 2016

As a sensing device in nano-scale, scanning probe microscopy (SPM) is a powerful tool for exploring nano world. Nevertheless two fundamental problems tackle the development and application of SPM based imaging and measurement: slow imaging/measurement speed and inaccuracy of motion or position control. Usually, SPM imaging/properties measuring speed is too slow to capture a dynamic observation on sample surface. In addition, Both SPM imaging and properties measurement always experience positioning inaccuracy problems caused by hysteresis and creep of the piezo scanner. This dissertation will try to solve these issues and proposed a SPM based real-time multimodal sensing system which can be used in nano/bio environment. First, a compressive sensing based video rate fast SPM imaging system is shown as an efficient method to dynamically capture the sample surface change with the imaging speed 1.5 frame/s with the scan size of 500 nm * 500 nm. Besides topography imaging, a new additional modal of SPM: vibration mode, will be introduced, and it is developed by us to investigate the subsurface mechanical properties of the elastic sample such as cells and bacteria. A followed up study of enzymatic hydrolysis will demonstrate the ability of in situ observation of single molecule event using video rate SPM. After that we will introduce another modal of this SPM sensing system: accurate electrical properties measurement. In this electrical properties measurement mode, a compressive feedbacks based non-vector space control approach is proposed in order to improve the accuracy of SPM based nanomanipulations. Instead of sensors, the local images are used as both the input and feedback of a non-vector space closed-loop controller. A followed up study will also be introduced to shown the important role of non-vector space control in the study of conductivity distribution of multi-wall carbon nanotubes. At the end of this dissertation, some future work will be also proposed to fulfill the development and validation of this real-time multimodal sensing system.

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Thesis M.S. Michigan State University. Electrical Engineering 2012.

A structured light based single-direction 3-D navigation system consists of a projector, a camera, and an infrared light filter. The system serves as a navigation sensor to help robot to perform the task of grabbing an object in front of the robot. It uses a unique algorithm to calculate 3-D wold coordinates of each point viewed by the camera from the pixel information obtained from the camera. The 3-D information of the wold coordinates generated by this camera system can be further applied in a variety of different applications, such as industrial quality inspection, mobile robot navigation, robot remote control, etc. As a navigation system, fast, accurate, real-time response is very important. Through experiments, the computation time of the existing algorithm of this navigation system is relative long. To improve the system, optimization needs to be applied. The motivation of this research paper is to optimize this existing algorithm to have significant fast computation speed and maintain the accuracy. There are nine functions executed in the existing algorithm. Compared the processing time of each function, decoding is the one takes more than half of the entire program's computation time. Therefore, in order to speed up the entire system, optimizing the decoding function is a necessary step. The existing decoding algorithm in the single-directional 3-D navigation system is designed and implemented using CPU. The computation arithmetic is a sequential serial computing algorithm. Nowadays, GPU's (Graphics processing unit) unique parallel architecture starts to be introduced to a wide range of studies to speed up computation time. However, how to modify and redesign the serial computing algorithm to efficiently utilize the GPU's parallel architecture is a challenge. In order to optimize the single-directional 3-D navigation system with faster processing speed and still maintain the same accuracy, re-design the serial decoding algorithm is necessary. In this paper, we are going to present a parallel decoding algorithm using CUDA-based GPU to accelerate the existing serial decoding algorithm more than 2000 times.

Description based on online resource; title from PDF t.p. (ProQuest, viewed on Jan. 8, 2013)

Thesis M.S. Michigan State University. Electrical Engineering 2011.

The purpose of this research is to build and test a haptic rendering system using skin surface electro-tactile stimulation for a fingertip interface. A new driver output stage for delivering tactile signals is implemented to improve power inefficiency and reduce circuit area relative to traditional open-loop constant current driver (CCD)-based haptic renders. This will be realized in a constant voltage driver (CVD) method for haptic rendering. The challenge will be to make the system aware of the skin impedance loading conditions and to use this information to introduce a closed-loop solution that is necessary due to implementing this type of driver.The system will be made load-aware by identifying parameters of a proposed electronic impedance model of skin that is done online and in real-time with customized software and hardware. Output sensors will be used to measure the voltage and current at the loaded output. An extended least squares algorithm will identify the parameters from the measurements. The paper will introduce a model reference adaptive control law, using the direct method, with nonlinear feedback to test a closed-loop CVD design. To aid in determining normal operating conditions, and validating parameter estimation and simulated closed-loop control, related experiments will be carried out. This work is based on an older version electro-tactile haptic rendering system used in the laboratory.

Description based on online resource; title from PDF t.p. (viewed on Feb. 28, 2012)

Thesis M.S. Michigan State University, Electrical Engineering 2013.

Nanoscale force sensors are finding widespread applications in atomic and biological force sensing where forces involved range from zeptonewtons to several nanonewtons. Different methods of nanoscale force sensing based on optical, electrical or purely mechanical schemes have been reported. However, each technique is limited by factors such as large size, low resolution, slow response, force range and alignment issues. In this research, a new device structure which could overcome the above mentioned constraints is studied theoretically and experimentally for the possibility of its application in nano-scale force sensing.

Description based on online resource; title from PDF t.p. (ProQuest, viewed on Sept. 23, 2014)

Thesis M.S. Michigan State University. Electrical Engineering 2014.

ABSTRACTIMPROVING THE CAPACITY VALUE OF WIND POWER WITH ENERGY STORAGE INTEGRATIONByElicia A. Sashington Wind power generation is a steadily growing renewable energy resource. However, the integration of wind power to the power grid poses reliability issues because wind is variable and unpredictable. One of the reliability issues is the mismatch between the system's load and generation. A solution to alleviating this issue is to combine wind power with energy storage systems. This combination will reduce the variability of wind power generation output and improve the capacity value. Capacity value can be defined as the amount of additional load that can be served due to the addition of a generator, while maintaining the existing levels of reliability [1]. For planning and reliability purposes, the capacity contribution of wind power with energy storage systems must be estimated. This will transform wind power from an energy resource to a capacity resource. In this thesis, an analysis of systems with wind power and wind power with energy storage were performed using reliability methods. In addition, a descriptive analysis and comparison was completed on different types of energy storage systems. The objectives of this thesis were to show the improvement of capacity values when energy storage systems are combined with wind power and energy storage systems that are most suitable for the system being analyzed.

Description based on online resource; title from PDF t.p. (viewed on August 2, 2017)

"Through this thesis proposal, the author has demonstrated a variety of electronic and optoelectronic nanodevices including ultrascaled transistors, heterostructure diodes, chemical sensors, photodetectors and single-pixel infrared cameras using atomically thin two-dimensional (2D) materials such as graphene, molybdenum disulfide (MoS2) and black phosphorus (BP). As the scaling of the silicon-based transistor approaches its physical limit, exploratory research is needed to develop alternative channel materials for future sub-5 nm gate length devices. For such an ultrascaled electronic device, short channel effects would severely limit its performance and operation. In order to suppress the short channel effects at extreme scaling limits, the thickness of the channel material needs to be less than roughly one-third of the gate length in order to allow the gate to retain its effective electrostatic control of channel carrier concentration. However, for conventional bulk semiconductors such as silicon, germanium and gallium arsenide, the rough surface of the ultrathin body (a few atomic layers) would lead to severe surface scattering for carriers, resulting in severely degraded carrier mobility. In this regard, atomically thin 2D layered materials are excellent candidates for future ultimately scaled electronic and optoelectronic device applications. Compared with 3D bulk materials, 2D materials exhibit many exceptional properties. First, quantum confinement effect in the direction perpendicular to the 2D plane leads to many novel electronic and optical properties that are dramatically different from their bulk counterparts. Second, their surfaces are atomically smooth and free of dangling bonds and defect states, which lead to intrinsically low surface scattering and make it easy to integrate 2D films with photonic structures. It is also possible to construct heterostructures using different 2D materials without the conventional lattice mismatch issues. Third, despite being atomically thin nature, many 2D materials interact strongly with light and cover a very broad range of electromagnetic spectrum. Finally, these atomically thin 2D materials are immune to short channel effects owing to their small thickness. In this thesis, we will discuss the electronic and optoelectronic device applications using atomically thin 2D materials including graphene, MoS2 and BP. We mainly discuss the 2D BP which is the most stable and least reactive form of element phosphorus, and was discovered in bulk form 100 years ago. Unlike zero bandgap graphene, BP is a direct bandgap semiconductor with a thickness-dependent bandgap ranging from 0.3 eV (bulk) to 2.0 eV (monolayer). Few-layer BP flakes have been used as channel materials in field-effect transistors (FETs). Such BP FETs exhibit high on-off current ratios of 104 -105 . And, the room temperature field-effect mobility of BP FETs is up to 1000 cm2V-1 s -1 which is much higher than that of 2D MoS2 based FETs." – Pages ii-iii.

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Thesis Ph. D. Michigan State University. Materials Science and Engineering 2019

"Nano-structured materials often exhibit very different mechanical properties comparing with their bulk counterpart and are more sensitive and active to chemical interactions with the environments due to the large surface-to-volume ratio. In this thesis, predictive modeling techniques including density functional theory (DFT) and reactive molecular dynamics method (MD) are designed and applied to understand the deformation mechanisms of complex nano-structured material and describe chemical-mechanical coupled interactions. Three technologically important materials are investigated, to understanding the high strain rate toughening mechanism in nacre, predicting the formation and fracture of aluminum oxide bifilms in aluminum castings, and revealing the lithium growth morphology as a function of oxygen partial pressure. For nacre, its hierarchical structure and toughening mechanisms have inspired many materials developments. Recently, a new toughening mechanism, deformation twins was observed in nacre after dynamic loading (103 s – 1). The deformation twinning tendency and the competition between fracture and deformation twinning were revealed by DFT calculations. We discovered that the ratio of the unstable and the stable stacking fault energy in aragonite is hitherto the highest in a broad range of metallic and oxide materials and the bonding nature for this high ratio is explained. Both aluminum and lithium have high oxygen affinity. Their interaction with the oxygen environment affects the mechanical properties and vice versa. During casting of aluminum, it has long been proposed that the entrapped alumina "bifilms" are detrimental to the fatigue properties of the cast product. However, its properties have never been measured due to experimental limitations. Therefore, a ReaxFF based MD protocol was designed to simulate aging, folding, and fracture of oxide bifilms. The predicted fracture energy, fracture location, and differences between old and young oxides are explained a series of experimental observations. To illustrate the Li-growth mechanism in a solid-state-battery testing platform, we modeled the morphology of Li nano-structure growth in oxygen environment via ReaxFF-based MD. The simulation revealed that the competition of the Li growth rate and oxidation rate leads to the sphere-nanowire-sphere morphology transition with increasing oxygen partial pressure. Understanding the impact of chemical reaction on Li dendrite growth mechanisms and morphology evolution provided insights on the formation of the solid electrolyte interface (SEI) layer in a Li-ion battery. Finally, a shortcoming of the current charge transfer scheme (qEq) used in the ReaxFF MD simulation is discussed. It is demonstrated that qEq method will lead to overductile ionic materials in the MD simulation. A new Force field method and new parameters are proposed to mitigate this problem." – Pages ii-iii.

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Thesis M.S. Michigan State University. Electrical Engineering 2012.

Terahertz (0.3~10THz) technologies have been proven to be useful in many areas. There is significant push in miniaturization of THz systems and components especially detectors since they are the key components. However, low-cost large-area compatible detector fabrication is difficult to achieve.In this thesis, a CNTs Schottky diode THz detector featured with low-cost large area compatibility is simulated and fabricated.Simulations are carried out that considers critical parameters. To overcome huge impedance mismatch between antenna and CNT Schottky diode, multi-CNTs aligned devices were simulated and analyzed. The simulation results show that NEP of approximately 5.5pW/Hz^0.5 or better can be achieved.For realizing low-cost large area processing of such device, organic polymer substrates were studied and down selected. Furthermore, an effective novel nano-fabrication process was first developed to avoid using e-beam lithography. Device critical gap sizes of 1μm or smaller have been demonstrated using this process.Measurements results showed strong non-linear rectifying behavior and NEP of 61.3 and 111pW/Hz^0.5 at 18GHz and 1THz. Those can be decreased by using higher quality and optimized numbers of CNTs in a single device.

Description based on online resource; title from PDF t.p. (ProQuest, viewed Dec. 4, 2013)

Thesis Ph. D. Michigan State University. Electrical Engineering 2018

"Deployment of energy storage systems (ESSs) is gaining significant momentum due to economic incentives, power system regulation requirements, and integration of renewable energy resources. This dissertation covers three aspects of grid-connected ESSs: benefits, planning, and operation. First, the benefits and use cases of ESSs are reviewed and a comprehensive evaluation method for estimating stacked revenue of ESSs is proposed. The stacked revenue from an ESS cannot be calculated by merely aggregating the benefits from various applications (e.g., energy arbitrage, frequency regulation, and outage mitigation) as the ESS may not be available for all types of applications during the same time interval. A model incorporating component reliability, power system operation constraints, and storage system operation constraints is developed to evaluate the composite revenue generated from the applications. Second, for planning purposes, a model to estimate the capacity value of ESSs is developed and a sensitivity guided approach to ESS siting is proposed. In contrast to conventional generators with the capability to provide energy upon demand, ESSs are energy-limited resources. In addition, it is possible that the availability of an ESS is low when it is needed to provide its capacity to maintain system reliability due to low state of charge. Thus, the work presented here proposes a method to evaluate the actual capacity contribution of ESSs, considering the energy-limited characteristic and the availability uncertainty. Also, it is necessary to determine suitable locations so as to maximize the benefit of ESSs. This dissertation proposes a sensitivity guided approach which aims at finding the optimal location of ESSs to reduce the peak hour generation cost. The last part of this dissertation proposes a model to determine the operation strategy of battery ESSs. This algorithm not only attempts to maximize the financial benefits but also considers the cycling behavior and its impact on the longevity of battery energy storage systems." – Page ii.

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Thesis Ph. D. Michigan State University. Electrical Engineering 2016

Infrared (IR) sensor has extended imaging from submicron visible spectrum to tens of microns wavelength, which has been widely used for military and civilian application. The conventional bulk semiconductor materials based IR cameras suffer from low frame rate, low resolution, temperature dependent and highly cost, while the unusual Carbon Nanotube (CNT), low dimensional material based nanotechnology has been made much progress in research and industry. The unique properties of CNT lead to investigate CNT based IR photodetectors and imaging system, resolvingthe sensitivity, speed and cooling difficulties in state of the art IR imagings.The reliability and stability is critical to the transition from nano science to nano engineering especially for infrared sensing. It is not only for the fundamental understanding of CNT photoresponse induced processes, but also for the development of a novel infrared sensitive material with unique optical and electrical features. In the proposed research, the sandwich-structured sensor was fabricated within two polymer layers. The substrate polyimide provided sensor with isolation to background noise, and top parylene packing blocked humid environmental factors. At the same time, the fabrication process was optimized by real time electrical detection dielectrophoresis andmultiple annealing to improve fabrication yield and sensor performance. The nanoscale infrared photodetector was characterized by digital microscopy and precise linear stage in order for fully understanding it. Besides, the low noise, high gain readout system was designed together with CNT photodetector to make the nano sensor IR camera available.To explore more of infrared light, we employ compressive sensing algorithm into light field sampling, 3-D camera and compressive video sensing. The redundant of whole light field, including angular images for light field, binocular images for 3-D camera and temporal information of video streams, are extracted and expressed in compressive approach. The following computational algorithms are applied to reconstruct images beyond 2D static information. The super resolution signal processing was then used to enhance and improve the image spatial resolution. The whole camera system brings a deeply detailed content for infrared spectrum sensing.

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Thesis Ph. D. Michigan State University. Electrical Engineering 2014.

We developed the Atomic Force Microscopy (AFM) based nanorobot in combination with other nanomechanical sensors for the investigation of cell signaling pathways. The AFM nanorobotics hinge on the superior spatial resolution of AFM in imaging and extends it into the measurement of biological processes and manipulation of biological matters. A multiple input single output control system was designed and implemented to solve the issues of nanomanipulation of biological materials, feedback, response frequency and nonlinearity. The AFM nanorobotic system therefore provide the human-directed position, velocity and force control with high frequency feedback, and more importantly it can feed the operator with the real-time imaging of manipulation result from the fast-imaging based local scanning. The use of the system has taken the study of cellular process at the molecular scale into a new level.The cellular response to the physiological conditions can be significantly manifested in cellular mechanics. Dynamic mechanical property has been regarded as biomarkers, sometimes even regulators of the signaling and physiological processes, thus the name mechanobiology. We sought to characterize the relationship between the structural dynamics and the molecular dynamics and the role of them in the regulation of cell behavior. We used the AFM nanorobotics to investigate the mechanical properties in real-time of cells that are stimulated by different chemical species. These reagents could result in similar ion channel responses but distinctive mechanical behaviors. We applied these measurement results to establish a model that describes the cellular stimulation and the mechanical property change, a ``two-hit" model that comprises the loss of cell adhesion and the initiation of cell apoptosis. The first hit was verified by functional experiments: depletion of Calcium and nanosurgery to disrupt the cellular adhesion. The second hit was tested by a labeling of apoptotic markers that were revealed by flow cytometry. The model would then be able to decipher qualitatively the molecular dynamics infolded in the regulation of cell behavior.To decipher the signaling pathway quantitatively, we employed a nanomechanical sensor at the bottom of the cell, quartz crystal microbalance with energy dissipation monitoring (QCM-D) to monitor the change at the basal area of the cell. This would provide the real time focal adhesion information and would be used in accordance with the AFM measurement data on the top of the cell to build a more complete mechanical profile during the antibody induced signaling process. We developed a model from a systematic control perspective that considers the signaling cascade at certain stimulation as the controller and the mechanical and structural interaction of the cell as the plant. We firstly derived the plant model based on QCM-D and AFM measurement processes. A signaling pathway model was built on a grey box approach where part of the…

Thesis Ph. D. Michigan State University. Electrical Engineering - Doctor of Philosophy 2015.

Nano-robotic end-effectors have promising applications for nano-fabrication, nano-manufacturing, nano-optics, nano-medical, and nano-sensing; however, low performances of the conventional end-effectors have prevented the widespread utilization of them in various fields. There are two major difficulties in developing the end-effectors: their nano-fabrication and their advanced characterization in the nanoscale. Here we introduce six types of end-effectors: the nanotube fountain pen (NFP), the super-fine nanoprobe, the metal-filled carbon nanotube ([email protected])-based sphere-on-pillar (SOP) nanoantennas, the tunneling nanosensor, and the nanowire-based memristor. The investigations on the NFP are focused on nano-fluidics and nano-fabrications. The NFP could direct write metallic "inks" and fabricating complex metal nanostructures from 0D to 3D with a position servo control, which is critically important to future large-scale, high-throughput nanodevice production. With the help of NFP, we could fabricate the end-effectors such as super-fine nanoprobe and [email protected] SOP nanoantennas. Those end-effectors are able to detect local flaws or characterize the electrical/mechanical properties of the nanostructure. Moreover, using electron-energy-loss-spectroscopy (EELS) technique during the operation of the SOP optical antenna opens a new basis for the application of nano-robotic end-effectors. The technique allows advanced characterization of the physical changes, such as carrier diffusion, that are directly responsible for the device's properties. As the device was coupled with characterization techniques of scanning-trasmission-electron-microscopy (STEM), the development of tunneling nanosensor advances this field of science into quantum world. Furthermore, the combined STEM-EELS technique plays an important role in our understanding of the memristive switching performance in the nanowire-based memristor. The developments of those nano-robotic end-effectors expend the study abilities in investigating the in situ nanotechnology, providing efficient ways in in situ nanostructure fabrication and the advanced characterization of the nanomaterials.

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