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Description
Micro-electro-mechanical systems (MEMS) film bulk acoustic resonator (FBAR) demonstrates label-free biosensing capabilities and is considered to be a promising alternative of quartz crystal microbalance (QCM). FBARs achieve great success in vacuum, or in the air, but find limited applications in liquid media because squeeze damping significantly degrades quality factor (Q) and results in poor frequency resolution. A transmission-line model shows that by confining the liquid in a thickness comparable to the acoustic wavelength of the resonator, Q can be considerably improved. The devices exhibit damped oscillatory patterns of Q as the liquid thickness varies. Q assumes its maxima and minima when the channel thickness is an odd and even multiple of the quarter-wavelength of the resonance, respectively. Microfluidic channels are integrated with longitudinal-mode FBARs (L-FBARs) to realize this design; a tenfold improvement of Q over fully-immersed devices is experimentally verified. Microfluidic integrated FBAR sensors have been demonstrated for detecting protein binding in liquid and monitoring the Vroman effect (the competitive protein adsorption behavior), showing their potential as a promising bio-analytical tool. A contour-mode FBAR (C-FBAR) is developed to further improve Q and to alleviate the need for complex integration of microfluidic channels. The C-FBAR consists of a suspended piezoelectric ring made of aluminum nitride and is excited in the fundamental radial-extensional mode. By replacing the squeeze damping with shear damping, high Qs (189 in water and 77 in human whole blood) are obtained in semi-infinite depth liquids. The C-FBAR sensors are characterized by aptamer - thrombin binding pairs and aqueous glycerine solutions for mass and viscosity sensing schemes, respectively. The C-FBAR sensor demonstrates accurate viscosity measurement from 1 to 10 centipoise, and can be deployed to monitor in-vitro blood coagulation processes in real time. Results show that its resonant frequency decreases as the viscosity of the blood increases during the fibrin generation process after the coagulation cascade. The coagulation time and the start/end of the fibrin generation are quantitatively determined, showing the C-FBAR can be a low-cost, portable yet reliable tool for hemostasis diagnostics.
ContributorsXu, Wencheng (Author) / Chae, Junseok (Thesis advisor) / Phillips, Stephen (Committee member) / Cao, Yu (Committee member) / Kozicki, Michael (Committee member) / Arizona State University (Publisher)
Created2011
Description
Characterization of standard cells is one of the crucial steps in the IC design. Scaling of CMOS technology has lead to timing un-certainties such as that of cross coupling noise due to interconnect parasitic, skew variation due to voltage jitter and proximity effect of multiple inputs switching (MIS). Due to increased operating frequency and process variation, the probability of MIS occurrence and setup / hold failure within a clock cycle is high. The delay variation due to temporal proximity of MIS is significant for multiple input gates in the standard cell library. The shortest paths are affected by MIS due to the lack of averaging effect. Thus, sensitive designs such as that of SRAM row and column decoder circuits have high probability for MIS impact. The traditional static timing analysis (STA) assumes single input switching (SIS) scenario which is not adequate enough to capture gate delay accurately, as the delay variation due to temporal proximity of the MIS is ~15%-45%. Whereas, considering all possible scenarios of MIS for characterization is computationally intensive with huge data volume. Various modeling techniques are developed for the characterization of MIS effect. Some techniques require coefficient extraction through multiple spice simulation, and do not discuss speed up approach or apply models with complicated algorithms to account for MIS effect. The STA flow accounts for process variation through uncertainty parameter to improve product yield. Some of the MIS delay variability models account for MIS variation through table look up approach, resulting in huge data volume or do not consider propagation of RAT in the design flow. Thus, there is a need for a methodology to model MIS effect with less computational resource, and integration of such effect into design flow without trading off the accuracy. A finite-point based analytical model for MIS effect is proposed for multiple input logic gates and similar approach is extended for setup/hold characterization of sequential elements. Integration of MIS variation into design flow is explored. The proposed methodology is validated using benchmark circuits at 45nm technology node under process variation. Experimental results show significant reduction in runtime and data volume with ~10% error compared to that of SPICE simulation.
ContributorsSubramaniam, Anupama R (Author) / Cao, Yu (Thesis advisor) / Chakrabarti, Chaitali (Committee member) / Roveda, Janet (Committee member) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2012
Description
Scaling of the classical planar MOSFET below 20 nm gate length is facing not only technological difficulties but also limitations imposed by short channel effects, gate and junction leakage current due to quantum tunneling, high body doping induced threshold voltage variation, and carrier mobility degradation. Non-classical multiple-gate structures such as double-gate (DG) FinFETs and surrounding gate field-effect-transistors (SGFETs) have good electrostatic integrity and are an alternative to planar MOSFETs for below 20 nm technology nodes. Circuit design with these devices need compact models for SPICE simulation. In this work physics based compact models for the common-gate symmetric DG-FinFET, independent-gate asymmetric DG-FinFET, and SGFET are developed. Despite the complex device structure and boundary conditions for the Poisson-Boltzmann equation, the core structure of the DG-FinFET and SGFET models, are maintained similar to the surface potential based compact models for planar MOSFETs such as SP and PSP. TCAD simulations show differences between the transient behavior and the capacitance-voltage characteristics of bulk and SOI FinFETs if the gate-voltage swing includes the accumulation region. This effect can be captured by a compact model of FinFETs only if it includes the contribution of both types of carriers in the Poisson-Boltzmann equation. An accurate implicit input voltage equation valid in all regions of operation is proposed for common-gate symmetric DG-FinFETs with intrinsic or lightly doped bodies. A closed-form algorithm is developed for solving the new input voltage equation including ambipolar effects. The algorithm is verified for both the surface potential and its derivatives and includes a previously published analytical approximation for surface potential as a special case when ambipolar effects can be neglected. The symmetric linearization method for common-gate symmetric DG-FinFETs is developed in a form free of the charge-sheet approximation present in its original formulation for bulk MOSFETs. The accuracy of the proposed technique is verified by comparison with exact results. An alternative and computationally efficient description of the boundary between the trigonometric and hyperbolic solutions of the Poisson-Boltzmann equation for the independent-gate asymmetric DG-FinFET is developed in terms of the Lambert W function. Efficient numerical algorithm is proposed for solving the input voltage equation. Analytical expressions for terminal charges of an independent-gate asymmetric DG-FinFET are derived. The new charge model is C-infinity continuous, valid for weak as well as for strong inversion condition of both the channels and does not involve the charge-sheet approximation. This is accomplished by developing the symmetric linearization method in a form that does not require identical boundary conditions at the two Si-SiO2 interfaces and allows for volume inversion in the DG-FinFET. Verification of the model is performed with both numerical computations and 2D TCAD simulations under a wide range of biasing conditions. The model is implemented in a standard circuit simulator through Verilog-A code. Simulation examples for both digital and analog circuits verify good model convergence and demonstrate the capabilities of new circuit topologies that can be implemented using independent-gate asymmetric DG-FinFETs.
ContributorsDessai, Gajanan (Author) / Gildenblat, Gennady (Committee member) / McAndrew, Colin (Committee member) / Cao, Yu (Committee member) / Barnaby, Hugh (Committee member) / Arizona State University (Publisher)
Created2012
Description
Situations of sensory overload are steadily becoming more frequent as the ubiquity of technology approaches reality--particularly with the advent of socio-communicative smartphone applications, and pervasive, high speed wireless networks. Although the ease of accessing information has improved our communication effectiveness and efficiency, our visual and auditory modalities--those modalities that today's computerized devices and displays largely engage--have become overloaded, creating possibilities for distractions, delays and high cognitive load; which in turn can lead to a loss of situational awareness, increasing chances for life threatening situations such as texting while driving. Surprisingly, alternative modalities for information delivery have seen little exploration. Touch, in particular, is a promising candidate given that it is our largest sensory organ with impressive spatial and temporal acuity. Although some approaches have been proposed for touch-based information delivery, they are not without limitations including high learning curves, limited applicability and/or limited expression. This is largely due to the lack of a versatile, comprehensive design theory--specifically, a theory that addresses the design of touch-based building blocks for expandable, efficient, rich and robust touch languages that are easy to learn and use. Moreover, beyond design, there is a lack of implementation and evaluation theories for such languages. To overcome these limitations, a unified, theoretical framework, inspired by natural, spoken language, is proposed called Somatic ABC's for Articulating (designing), Building (developing) and Confirming (evaluating) touch-based languages. To evaluate the usefulness of Somatic ABC's, its design, implementation and evaluation theories were applied to create communication languages for two very unique application areas: audio described movies and motor learning. These applications were chosen as they presented opportunities for complementing communication by offloading information, typically conveyed visually and/or aurally, to the skin. For both studies, it was found that Somatic ABC's aided the design, development and evaluation of rich somatic languages with distinct and natural communication units.
ContributorsMcDaniel, Troy Lee (Author) / Panchanathan, Sethuraman (Thesis advisor) / Davulcu, Hasan (Committee member) / Li, Baoxin (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2012
Description
Engineering an object means engineering the process that creates the object. Today, software can make the task of tracking these processes robust and straightforward. When engineering requirements are strict and strenuous, software custom-built for such processes can prove essential. The work for this project was developing ICDB, an inventory control and build management system created for spacecraft engineers at ASU to record each step of their engineering processes. In-house development means ICDB is more precisely designed around its users' functionality and cost requirements than most off-the-shelf commercial offerings. By placing a complex relational database behind an intuitive web application, ICDB enables organizations and their users to create and store parts libraries, assembly designs, purchasing and location records for inventory items, and more.
ContributorsNoss, Karl Friederich (Author) / Davulcu, Hasan (Thesis director) / Rios, Ken (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Hardware implementation of deep neural networks is earning significant importance nowadays. Deep neural networks are mathematical models that use learning algorithms inspired by the brain. Numerous deep learning algorithms such as multi-layer perceptrons (MLP) have demonstrated human-level recognition accuracy in image and speech classification tasks. Multiple layers of processing elements called neurons with several connections between them called synapses are used to build these networks. Hence, it involves operations that exhibit a high level of parallelism making it computationally and memory intensive. Constrained by computing resources and memory, most of the applications require a neural network which utilizes less energy. Energy efficient implementation of these computationally intense algorithms on neuromorphic hardware demands a lot of architectural optimizations. One of these optimizations would be the reduction in the network size using compression and several studies investigated compression by introducing element-wise or row-/column-/block-wise sparsity via pruning and regularization. Additionally, numerous recent works have concentrated on reducing the precision of activations and weights with some reducing to a single bit. However, combining various sparsity structures with binarized or very-low-precision (2-3 bit) neural networks have not been comprehensively explored. Output activations in these deep neural network algorithms are habitually non-binary making it difficult to exploit sparsity. On the other hand, biologically realistic models like spiking neural networks (SNN) closely mimic the operations in biological nervous systems and explore new avenues for brain-like cognitive computing. These networks deal with binary spikes, and they can exploit the input-dependent sparsity or redundancy to dynamically scale the amount of computation in turn leading to energy-efficient hardware implementation. This work discusses configurable spiking neuromorphic architecture that supports multiple hidden layers exploiting hardware reuse. It also presents design techniques for minimum-area/-energy DNN hardware with minimal degradation in accuracy. Area, performance and energy results of these DNN and SNN hardware is reported for the MNIST dataset. The Neuromorphic hardware designed for SNN algorithm in 28nm CMOS demonstrates high classification accuracy (>98% on MNIST) and low energy (51.4 - 773 (nJ) per classification). The optimized DNN hardware designed in 40nm CMOS that combines 8X structured compression and 3-bit weight precision showed 98.4% accuracy at 33 (nJ) per classification.
ContributorsKolala Venkataramanaiah, Shreyas (Author) / Seo, Jae-Sun (Thesis advisor) / Chakrabarti, Chaitali (Committee member) / Cao, Yu (Committee member) / Arizona State University (Publisher)
Created2018
Description
Over decades, scientists have been scaling devices to increasingly smaller feature sizes for ever better performance of complementary metal-oxide semiconductor (CMOS) technology to meet requirements on speed, complexity, circuit density, power consumption and ultimately cost required by many advanced applications. However, going to these ultra-scaled CMOS devices also brings some drawbacks. Aging due to bias-temperature-instability (BTI) and Hot carrier injection (HCI) is the dominant cause of functional failure in large scale logic circuits. The aging phenomena, on top of process variations, translate into complexity and reduced design margin for circuits. Such issues call for “Design for Reliability”. In order to increase the overall design efficiency, it is important to (i) study the impact of aging on circuit level along with the transistor level understanding (ii) calibrate the theoretical findings with measurement data (iii) implementing tools that analyze the impact of BTI and HCI reliability on circuit timing into VLSI design process at each stage. In this work, post silicon measurements of a 28nm HK-MG technology are done to study the effect of aging on Frequency Degradation of digital circuits. A novel voltage controlled ring oscillator (VCO) structure, developed by NIMO research group is used to determine the effect of aging mechanisms like NBTI, PBTI and SILC on circuit parameters. Accelerated aging mechanism is proposed to avoid the time consuming measurement process and extrapolation of data to the end of life thus instead of predicting the circuit behavior, one can measure it, within a short period of time. Finally, to bridge the gap between device level models and circuit level aging analysis, a System Level Reliability Analysis Flow (SyRA) developed by NIMO group, is implemented for a TSMC 65nm industrial level design to achieve one-step reliability prediction for digital design.
ContributorsBansal, Ankita (Author) / Cao, Yu (Thesis advisor) / Seo, Jae sun (Committee member) / Barnaby, Hugh (Committee member) / Arizona State University (Publisher)
Created2016
Description
One of the most remarkable outcomes resulting from the evolution of the web into Web 2.0, has been the propelling of blogging into a widely adopted and globally accepted phenomenon. While the unprecedented growth of the Blogosphere has added diversity and enriched the media, it has also added complexity. To cope with the relentless expansion, many enthusiastic bloggers have embarked on voluntarily writing, tagging, labeling, and cataloguing their posts in hopes of reaching the widest possible audience. Unbeknown to them, this reaching-for-others process triggers the generation of a new kind of collective wisdom, a result of shared collaboration, and the exchange of ideas, purpose, and objectives, through the formation of associations, links, and relations. Mastering an understanding of the Blogosphere can greatly help facilitate the needs of the ever growing number of these users, as well as producers, service providers, and advertisers into facilitation of the categorization and navigation of this vast environment. This work explores a novel method to leverage the collective wisdom from the infused label space for blog search and discovery. The work demonstrates that the wisdom space can provide a most unique and desirable framework to which to discover the highly sought after background information that could aid in the building of classifiers. This work incorporates this insight into the construction of a better clustering of blogs which boosts the performance of classifiers for identifying more relevant labels for blogs, and offers a mechanism that can be incorporated into replacing spurious labels and mislabels in a multi-labeled space.
ContributorsGalan, Magdiel F (Author) / Liu, Huan (Thesis advisor) / Davulcu, Hasan (Committee member) / Ye, Jieping (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2015
Description
Access to real-time situational information including the relative position and motion of surrounding objects is critical for safe and independent travel. Object or obstacle (OO) detection at a distance is primarily a task of the visual system due to the high resolution information the eyes are able to receive from afar. As a sensory organ in particular, the eyes have an unparalleled ability to adjust to varying degrees of light, color, and distance. Therefore, in the case of a non-visual traveler, someone who is blind or low vision, access to visual information is unattainable if it is positioned beyond the reach of the preferred mobility device or outside the path of travel. Although, the area of assistive technology in terms of electronic travel aids (ETA’s) has received considerable attention over the last two decades; surprisingly, the field has seen little work in the area focused on augmenting rather than replacing current non-visual travel techniques, methods, and tools. Consequently, this work describes the design of an intuitive tactile language and series of wearable tactile interfaces (the Haptic Chair, HaptWrap, and HapBack) to deliver real-time spatiotemporal data. The overall intuitiveness of the haptic mappings conveyed through the tactile interfaces are evaluated using a combination of absolute identification accuracy of a series of patterns and subjective feedback through post-experiment surveys. Two types of spatiotemporal representations are considered: static patterns representing object location at a single time instance, and dynamic patterns, added in the HaptWrap, which represent object movement over a time interval. Results support the viability of multi-dimensional haptics applied to the body to yield an intuitive understanding of dynamic interactions occurring around the navigator during travel. Lastly, it is important to point out that the guiding principle of this work centered on providing the navigator with spatial knowledge otherwise unattainable through current mobility techniques, methods, and tools, thus, providing the \emph{navigator} with the information necessary to make informed navigation decisions independently, at a distance.
ContributorsDuarte, Bryan Joiner (Author) / McDaniel, Troy (Thesis advisor) / Davulcu, Hasan (Committee member) / Li, Baoxin (Committee member) / Venkateswara, Hemanth (Committee member) / Arizona State University (Publisher)
Created2020