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- All Subjects: engineering
- Creators: Alford, Terry
Description
Ball Grid Array (BGA) using lead-free or lead-rich solder materials are widely used as Second Level Interconnects (SLI) in mounting packaged components to the printed circuit board (PCB). The reliability of these solder joints is of significant importance to the performance of microelectronics components and systems. Product design/form-factor, solder material, manufacturing process, use condition, as well as, the inherent variabilities present in the system, greatly influence product reliability. Accurate reliability analysis requires an integrated approach to concurrently account for all these factors and their synergistic effects. Such an integrated and robust methodology can be used in design and development of new and advanced microelectronics systems and can provide significant improvement in cycle-time, cost, and reliability. IMPRPK approach is based on a probabilistic methodology, focusing on three major tasks of (1) Characterization of BGA solder joints to identify failure mechanisms and obtain statistical data, (2) Finite Element analysis (FEM) to predict system response needed for life prediction, and (3) development of a probabilistic methodology to predict the reliability, as well as, the sensitivity of the system to various parameters and the variabilities. These tasks and the predictive capabilities of IMPRPK in microelectronic reliability analysis are discussed.
ContributorsFallah-Adl, Ali (Author) / Tasooji, Amaneh (Thesis advisor) / Krause, Stephen (Committee member) / Alford, Terry (Committee member) / Jiang, Hanqing (Committee member) / Mahajan, Ravi (Committee member) / Arizona State University (Publisher)
Created2013
Description
The Solid State Transformer (SST) is an essential component in the FREEDM system. This research focuses on the modeling of the SST and the controller hardware in the loop (CHIL) implementation of the SST for the support of the FREEDM system demonstration. The energy based control strategy for a three-stage SST is analyzed and applied. A simplified average model of the three-stage SST that is suitable for simulation in real time digital simulator (RTDS) has been developed in this study. The model is also useful for general time-domain power system analysis and simulation. The proposed simplified av-erage model has been validated in MATLAB and PLECS. The accuracy of the model has been verified through comparison with the cycle-by-cycle average (CCA) model and de-tailed switching model. These models are also implemented in PSCAD, and a special strategy to implement the phase shift modulation has been proposed to enable the switching model simulation in PSCAD. The implementation of the CHIL test environment of the SST in RTDS is described in this report. The parameter setup of the model has been discussed in detail. One of the dif-ficulties is the choice of the damping factor, which is revealed in this paper. Also the grounding of the system has large impact on the RTDS simulation. Another problem is that the performance of the system is highly dependent on the switch parameters such as voltage and current ratings. Finally, the functionalities of the SST have been realized on the platform. The distributed energy storage interface power injection and reverse power flow have been validated. Some limitations are noticed and discussed through the simulation on RTDS.
ContributorsJiang, Youyuan (Author) / Ayyanar, Raja (Thesis advisor) / Holbert, Keith E. (Committee member) / Chowdhury, Srabanti (Committee member) / Arizona State University (Publisher)
Created2014
Description
Organic light emitting diodes (OLEDs) are a promising approach for display and solid state lighting applications. However, further work is needed in establishing the availability of efficient and stable materials for OLEDs with high external quantum efficiency's (EQE) and high operational lifetimes. Recently, significant improvements in the internal quantum efficiency or ratio of generated photons to injected electrons have been achieved with the advent of phosphorescent complexes with the ability to harvest both singlet and triplet excitons. Since then, a variety of phosphorescent complexes containing heavy metal centers including Os, Ni, Ir, Pd, and Pt have been developed. Thus far, the majority of the work in the field has focused on iridium based complexes. Platinum based complexes, however, have received considerably less attention despite demonstrating efficiency's equal to or better than their iridium analogs. In this study, a series of OLEDs implementing newly developed platinum based complexes were demonstrated with efficiency's or operational lifetimes equal to or better than their iridium analogs for select cases.
In addition to demonstrating excellent device performance in OLEDs, platinum based complexes exhibit unique photophysical properties including the ability to form excimer emission capable of generating broad white light emission from a single emitter and the ability to form narrow band emission from a rigid, tetradentate molecular structure for select cases. These unique photophysical properties were exploited and their optical and electrical properties in a device setting were elucidated.
Utilizing the unique properties of a tridentate Pt complex, Pt-16, a highly efficient white device employing a single emissive layer exhibited a peak EQE of over 20% and high color quality with a CRI of 80 and color coordinates CIE(x=0.33, y=0.33). Furthermore, by employing a rigid, tetradentate platinum complex, PtN1N, with a narrow band emission into a microcavity organic light emitting diode (MOLED), significant enhancement in the external quantum efficiency was achieved. The optimized MOLED structure achieved a light out-coupling enhancement of 1.35 compared to the non-cavity structure with a peak EQE of 34.2%. In addition to demonstrating a high light out-coupling enhancement, the microcavity effect of a narrow band emitter in a MOLED was elucidated.
In addition to demonstrating excellent device performance in OLEDs, platinum based complexes exhibit unique photophysical properties including the ability to form excimer emission capable of generating broad white light emission from a single emitter and the ability to form narrow band emission from a rigid, tetradentate molecular structure for select cases. These unique photophysical properties were exploited and their optical and electrical properties in a device setting were elucidated.
Utilizing the unique properties of a tridentate Pt complex, Pt-16, a highly efficient white device employing a single emissive layer exhibited a peak EQE of over 20% and high color quality with a CRI of 80 and color coordinates CIE(x=0.33, y=0.33). Furthermore, by employing a rigid, tetradentate platinum complex, PtN1N, with a narrow band emission into a microcavity organic light emitting diode (MOLED), significant enhancement in the external quantum efficiency was achieved. The optimized MOLED structure achieved a light out-coupling enhancement of 1.35 compared to the non-cavity structure with a peak EQE of 34.2%. In addition to demonstrating a high light out-coupling enhancement, the microcavity effect of a narrow band emitter in a MOLED was elucidated.
ContributorsEcton, Jeremy David (Author) / Li, Jian (Thesis advisor) / Adams, James (Committee member) / Alford, Terry (Committee member) / Arizona State University (Publisher)
Created2014
Description
For decades, microelectronics manufacturing has been concerned with failures related to electromigration phenomena in conductors experiencing high current densities. The influence of interconnect microstructure on device failures related to electromigration in BGA and flip chip solder interconnects has become a significant interest with reduced individual solder interconnect volumes. A survey indicates that x-ray computed micro-tomography (µXCT) is an emerging, novel means for characterizing the microstructures' role in governing electromigration failures. This work details the design and construction of a lab-scale µXCT system to characterize electromigration in the Sn-0.7Cu lead-free solder system by leveraging in situ imaging.
In order to enhance the attenuation contrast observed in multi-phase material systems, a modeling approach has been developed to predict settings for the controllable imaging parameters which yield relatively high detection rates over the range of x-ray energies for which maximum attenuation contrast is expected in the polychromatic x-ray imaging system. In order to develop this predictive tool, a model has been constructed for the Bremsstrahlung spectrum of an x-ray tube, and calculations for the detector's efficiency over the relevant range of x-ray energies have been made, and the product of emitted and detected spectra has been used to calculate the effective x-ray imaging spectrum. An approach has also been established for filtering `zinger' noise in x-ray radiographs, which has proven problematic at high x-ray energies used for solder imaging. The performance of this filter has been compared with a known existing method and the results indicate a significant increase in the accuracy of zinger filtered radiographs.
The obtained results indicate the conception of a powerful means for the study of failure causing processes in solder systems used as interconnects in microelectronic packaging devices. These results include the volumetric quantification of parameters which are indicative of both electromigration tolerance of solders and the dominant mechanisms for atomic migration in response to current stressing. This work is aimed to further the community's understanding of failure-causing electromigration processes in industrially relevant material systems for microelectronic interconnect applications and to advance the capability of available characterization techniques for their interrogation.
In order to enhance the attenuation contrast observed in multi-phase material systems, a modeling approach has been developed to predict settings for the controllable imaging parameters which yield relatively high detection rates over the range of x-ray energies for which maximum attenuation contrast is expected in the polychromatic x-ray imaging system. In order to develop this predictive tool, a model has been constructed for the Bremsstrahlung spectrum of an x-ray tube, and calculations for the detector's efficiency over the relevant range of x-ray energies have been made, and the product of emitted and detected spectra has been used to calculate the effective x-ray imaging spectrum. An approach has also been established for filtering `zinger' noise in x-ray radiographs, which has proven problematic at high x-ray energies used for solder imaging. The performance of this filter has been compared with a known existing method and the results indicate a significant increase in the accuracy of zinger filtered radiographs.
The obtained results indicate the conception of a powerful means for the study of failure causing processes in solder systems used as interconnects in microelectronic packaging devices. These results include the volumetric quantification of parameters which are indicative of both electromigration tolerance of solders and the dominant mechanisms for atomic migration in response to current stressing. This work is aimed to further the community's understanding of failure-causing electromigration processes in industrially relevant material systems for microelectronic interconnect applications and to advance the capability of available characterization techniques for their interrogation.
ContributorsMertens, James Charles Edwin (Author) / Chawla, Nikhilesh (Thesis advisor) / Alford, Terry (Committee member) / Jiao, Yang (Committee member) / Neithalath, Narayanan (Committee member) / Arizona State University (Publisher)
Created2015
Description
In this thesis, a novel silica nanosphere (SNS) lithography technique has been developed to offer a fast, cost-effective, and large area applicable nano-lithography approach. The SNS can be easily deposited with a simple spin-coating process after introducing a N,N-dimethyl-formamide (DMF) solvent which can produce a highly close packed SNS monolayer over large silicon (Si) surface area, since DMF offers greatly improved wetting, capillary and convective forces in addition to slow solvent evaporation rate. Since the period and dimension of the surface pattern can be conveniently changed and controlled by introducing a desired size of SNS, and additional SNS size reduction with dry etching process, using SNS for lithography provides a highly effective nano-lithography approach for periodically arrayed nano-/micro-scale surface patterns with a desired dimension and period. Various Si nanostructures (i.e., nanopillar, nanotip, inverted pyramid, nanohole) are successfully fabricated with the SNS nano-lithography technique by using different etching technique like anisotropic alkaline solution (i.e., KOH) etching, reactive-ion etching (RIE), and metal-assisted chemical etching (MaCE).
In this research, computational optical modeling is also introduced to design the Si nanostructure, specifically nanopillars (NPs) with a desired period and dimension. The optical properties of Si NP are calculated with two different optical modeling techniques, which are the rigorous coupled wave analysis (RCWA) and finite-difference time-domain (FDTD) methods. By using these two different optical modeling techniques, the optical properties of Si NPs with different periods and dimensions have been investigated to design ideal Si NP which can be potentially used for thin c-Si solar cell applications. From the results of the computational and experimental work, it was observed that low aspect ratio Si NPs fabricated in a periodic hexagonal array can provide highly enhanced light absorption for the target spectral range (600 ~ 1100nm), which is attributed to (1) the effective confinement of resonant scattering within the Si NP and (2) increased high order diffraction of transmitted light providing an extended absorption length. From the research, therefore, it is successfully demonstrated that the nano-fabrication process with SNS lithography can offer enhanced lithographical accuracy to fabricate desired Si nanostructures which can realize enhanced light absorption for thin Si solar cell.
In this research, computational optical modeling is also introduced to design the Si nanostructure, specifically nanopillars (NPs) with a desired period and dimension. The optical properties of Si NP are calculated with two different optical modeling techniques, which are the rigorous coupled wave analysis (RCWA) and finite-difference time-domain (FDTD) methods. By using these two different optical modeling techniques, the optical properties of Si NPs with different periods and dimensions have been investigated to design ideal Si NP which can be potentially used for thin c-Si solar cell applications. From the results of the computational and experimental work, it was observed that low aspect ratio Si NPs fabricated in a periodic hexagonal array can provide highly enhanced light absorption for the target spectral range (600 ~ 1100nm), which is attributed to (1) the effective confinement of resonant scattering within the Si NP and (2) increased high order diffraction of transmitted light providing an extended absorption length. From the research, therefore, it is successfully demonstrated that the nano-fabrication process with SNS lithography can offer enhanced lithographical accuracy to fabricate desired Si nanostructures which can realize enhanced light absorption for thin Si solar cell.
ContributorsChoi, JeaYoung (Author) / Honsberg, Christiana (Thesis advisor) / Alford, Terry (Thesis advisor) / Goodnick, Stephen (Committee member) / Arizona State University (Publisher)
Created2015
Description
Parkinson's disease is a neurodegenerative condition diagnosed on patients with
clinical history and motor signs of tremor, rigidity and bradykinesia, and the estimated
number of patients living with Parkinson's disease around the world is seven
to ten million. Deep brain stimulation (DBS) provides substantial relief of the motor
signs of Parkinson's disease patients. It is an advanced surgical technique that is used
when drug therapy is no longer sufficient for Parkinson's disease patients. DBS alleviates the motor symptoms of Parkinson's disease by targeting the subthalamic nucleus using high-frequency electrical stimulation.
This work proposes a behavior recognition model for patients with Parkinson's
disease. In particular, an adaptive learning method is proposed to classify behavioral
tasks of Parkinson's disease patients using local field potential and electrocorticography
signals that are collected during DBS implantation surgeries. Unique patterns
exhibited between these signals in a matched feature space would lead to distinction
between motor and language behavioral tasks. Unique features are first extracted
from deep brain signals in the time-frequency space using the matching pursuit decomposition
algorithm. The Dirichlet process Gaussian mixture model uses the extracted
features to cluster the different behavioral signal patterns, without training or
any prior information. The performance of the method is then compared with other
machine learning methods and the advantages of each method is discussed under
different conditions.
clinical history and motor signs of tremor, rigidity and bradykinesia, and the estimated
number of patients living with Parkinson's disease around the world is seven
to ten million. Deep brain stimulation (DBS) provides substantial relief of the motor
signs of Parkinson's disease patients. It is an advanced surgical technique that is used
when drug therapy is no longer sufficient for Parkinson's disease patients. DBS alleviates the motor symptoms of Parkinson's disease by targeting the subthalamic nucleus using high-frequency electrical stimulation.
This work proposes a behavior recognition model for patients with Parkinson's
disease. In particular, an adaptive learning method is proposed to classify behavioral
tasks of Parkinson's disease patients using local field potential and electrocorticography
signals that are collected during DBS implantation surgeries. Unique patterns
exhibited between these signals in a matched feature space would lead to distinction
between motor and language behavioral tasks. Unique features are first extracted
from deep brain signals in the time-frequency space using the matching pursuit decomposition
algorithm. The Dirichlet process Gaussian mixture model uses the extracted
features to cluster the different behavioral signal patterns, without training or
any prior information. The performance of the method is then compared with other
machine learning methods and the advantages of each method is discussed under
different conditions.
ContributorsDutta, Arindam (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Holbert, Keith E. (Committee member) / Bliss, Daniel W. (Committee member) / Arizona State University (Publisher)
Created2015
Description
The subject of this thesis is distribution level load management using a pricing signal in a smart grid infrastructure. The project relates to energy management in a spe-cialized distribution system known as the Future Renewable Electric Energy Delivery and Management (FREEDM) system. Energy management through demand response is one of the key applications of smart grid. Demand response today is envisioned as a method in which the price could be communicated to the consumers and they may shift their loads from high price periods to the low price periods. The development and deployment of the FREEDM system necessitates controls of energy and power at the point of end use.
In this thesis, the main objective is to develop the control model of the Energy Management System (EMS). The energy and power management in the FREEDM system is digitally controlled therefore all signals containing system states are discrete. The EMS is modeled as a discrete closed loop transfer function in the z-domain. A breakdown of power and energy control devices such as EMS components may result in energy con-sumption error. This leads to one of the main focuses of the thesis which is to identify and study component failures of the designed control system. Moreover, H-infinity ro-bust control method is applied to ensure effectiveness of the control architecture. A focus of the study is cyber security attack, specifically bad data detection in price. Test cases are used to illustrate the performance of the EMS control design, the effect of failure modes and the application of robust control technique.
The EMS was represented by a linear z-domain model. The transfer function be-tween the pricing signal and the demand response was designed and used as a test bed. EMS potential failure modes were identified and studied. Three bad data detection meth-odologies were implemented and a voting policy was used to declare bad data. The run-ning mean and standard deviation analysis method proves to be the best method to detect bad data. An H-infinity robust control technique was applied for the first time to design discrete EMS controller for the FREEDM system.
In this thesis, the main objective is to develop the control model of the Energy Management System (EMS). The energy and power management in the FREEDM system is digitally controlled therefore all signals containing system states are discrete. The EMS is modeled as a discrete closed loop transfer function in the z-domain. A breakdown of power and energy control devices such as EMS components may result in energy con-sumption error. This leads to one of the main focuses of the thesis which is to identify and study component failures of the designed control system. Moreover, H-infinity ro-bust control method is applied to ensure effectiveness of the control architecture. A focus of the study is cyber security attack, specifically bad data detection in price. Test cases are used to illustrate the performance of the EMS control design, the effect of failure modes and the application of robust control technique.
The EMS was represented by a linear z-domain model. The transfer function be-tween the pricing signal and the demand response was designed and used as a test bed. EMS potential failure modes were identified and studied. Three bad data detection meth-odologies were implemented and a voting policy was used to declare bad data. The run-ning mean and standard deviation analysis method proves to be the best method to detect bad data. An H-infinity robust control technique was applied for the first time to design discrete EMS controller for the FREEDM system.
ContributorsMusani, Aatif (Author) / Heydt, Gerald (Thesis advisor) / Ayyanar, Raja (Committee member) / Holbert, Keith E. (Committee member) / Arizona State University (Publisher)
Created2014
Description
Due to increasing integration of renewable resources in the power grid, an efficient high power transmission system is needed in the near future to transfer energy from remote locations to the load centers. Gas Insulated Transmission Line (GIL) is a specialized high power transmission system, designed by Siemens, for applications requiring direct burial or vertical installation of the transmission line. GIL uses SF6 as an insulating medium. Due to unavoidable gas leakages and high global warming potential of SF6, there is a need to replace this insulating gas by some other possible alternative. Insulating foam materials are characterized by excellent dielectric properties as well as their reduced weight. These materials can find their application in GIL as high voltage insulators. Syntactic foam is a polymer based insulating foam. It consists of a large number of microspheres embedded in a polymer matrix.
The work in this thesis deals with the development of the selection proce-dure for an insulating foam for its application in GIL. All the steps in the process are demonstrated considering syntactic foam as an insulator. As the first step of the procedure, a small representative model of the insulating foam is built in COMSOL Multiphysics software with the help of AutoCAD and Excel VBA to analyze electric field distribution for the application of GIL. The effect of the presence of metal particles on the electric field distribution is also observed. The AC voltage withstand test is performed on the insulating foam samples according to the IEEE standards. The effect of the insulating foam on electrical parameters as well as transmission characteristics of the line is analyzed as the last part of the thesis. The results from all the simulations and AC voltage withstand test are ob-served to predict the suitability of the syntactic foam as an insulator in GIL.
The work in this thesis deals with the development of the selection proce-dure for an insulating foam for its application in GIL. All the steps in the process are demonstrated considering syntactic foam as an insulator. As the first step of the procedure, a small representative model of the insulating foam is built in COMSOL Multiphysics software with the help of AutoCAD and Excel VBA to analyze electric field distribution for the application of GIL. The effect of the presence of metal particles on the electric field distribution is also observed. The AC voltage withstand test is performed on the insulating foam samples according to the IEEE standards. The effect of the insulating foam on electrical parameters as well as transmission characteristics of the line is analyzed as the last part of the thesis. The results from all the simulations and AC voltage withstand test are ob-served to predict the suitability of the syntactic foam as an insulator in GIL.
ContributorsPendse, Harshada Ganesh (Author) / Karady, George G. (Thesis advisor) / Holbert, Keith E. (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2014
Description
Ever reducing time to market, along with short product lifetimes, has created a need to shorten the microprocessor design time. Verification of the design and its analysis are two major components of this design cycle. Design validation techniques can be broadly classified into two major categories: simulation based approaches and formal techniques. Simulation based microprocessor validation involves running millions of cycles using random or pseudo random tests and allows verification of the register transfer level (RTL) model against an architectural model, i.e., that the processor executes instructions as required. The validation effort involves model checking to a high level description or simulation of the design against the RTL implementation. Formal techniques exhaustively analyze parts of the design but, do not verify RTL against the architecture specification. The focus of this work is to implement a fully automated validation environment for a MIPS based radiation hardened microprocessor using simulation based approaches. The basic framework uses the classical validation approach in which the design to be validated is described in a Hardware Definition Language (HDL) such as VHDL or Verilog. To implement a simulation based approach a number of random or pseudo random tests are generated. The output of the HDL based design is compared against the one obtained from a "perfect" model implementing similar functionality, a mismatch in the results would thus indicate a bug in the HDL based design. Effort is made to design the environment in such a manner that it can support validation during different stages of the design cycle. The validation environment includes appropriate changes so as to support architecture changes which are introduced because of radiation hardening. The manner in which the validation environment is build is highly dependent on the specifications of the perfect model used for comparisons. This work implements the validation environment for two MIPS simulators as the reference model. Two bugs have been discovered in the RTL model, using simulation based approaches through the validation environment.
ContributorsSharma, Abhishek (Author) / Clark, Lawrence (Thesis advisor) / Holbert, Keith E. (Committee member) / Shrivastava, Aviral (Committee member) / Arizona State University (Publisher)
Created2011
Description
Soft magnetic alloys play a significant role for magnetic recording applications and highly sensitivity magnetic field sensors. In order to sustain the magnetic areal density growth, development of new synthesis techniques and materials is necessary. In this work, the effect of oxygen incorporation during electrodeposition of CoFe alloys on magnetic properties, magnetoresistance and structural properties has been studied. Understanding the magnetic properties often required knowledge of oxygen distribution and structural properties of the grown films. Transmission electron microscopy (TEM) was a powerful tool in this study to correlate the oxygen-distribution nanostructure to the magnetic properties of deposited films. Off-axis electron holography in TEM was used to measure magnetic domain wall width in the deposited films. Elemental depth profiles of Fe, Co, O were investigated by secondary ion mass spectroscopy (SIMS). Magnetic properties have been determined by superconducting quantum interference device (SQUID) measurements. Oxygen content in the CoFe deposited films was controlled by electrolyte composition. Films were deposited on Si 100 substrates and on other substrates such as Cu and Al. However, a good film quality was achieved on Si substrate. Electron energy loss and x-ray spectroscopies showed that the low oxygen films contained intragranular Fe2+ oxide (FeO) particles and that the high oxygen films contained intergranular Fe3+ (Fe2O3) along grain boundaries. The films with oxide present at the grain boundary had significantly increased coercivity, magnetoresistance and reduced saturation magnetization relative to the lower oxygen content films with intragranular oxide. The differences in magnetic properties between low oxygen and high oxygen concentration films were attributed to stronger mobile domain wall interactions with the grain boundary oxide layers. The very high magnetoresistance values were achieved for magnetic devices with nanocontact dimension < 100 nm and oxide incorporation in this nanoconfined geometry. The content of oxide phase in nanocontact was controlled by concentration of the Fe3+ ions in the electrodeposition solution. Magnetic device integrity was improved by varying amount of additive into plating solution. These results indicated that electrodeposited CoFe nanocontact is a novel class of materials with large application for magnetic field sensors.
ContributorsElhalawaty, Shereen (Author) / Carpenter, Ray (Thesis advisor) / Chamberlin, Ralph (Committee member) / McCartney, Martha (Committee member) / Alford, Terry (Committee member) / Arizona State University (Publisher)
Created2012