This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

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Description
Biosensors aiming at detection of target analytes, such as proteins, microbes, virus, and toxins, are widely needed for various applications including detection of chemical and biological warfare (CBW) agents, biomedicine, environmental monitoring, and drug screening. Surface Plasmon Resonance (SPR), as a surface-sensitive analytical tool, can very sensitively respond to minute

Biosensors aiming at detection of target analytes, such as proteins, microbes, virus, and toxins, are widely needed for various applications including detection of chemical and biological warfare (CBW) agents, biomedicine, environmental monitoring, and drug screening. Surface Plasmon Resonance (SPR), as a surface-sensitive analytical tool, can very sensitively respond to minute changes of refractive index occurring adjacent to a metal film, offering detection limits up to a few ppt (pg/mL). Through SPR, the process of protein adsorption may be monitored in real-time, and transduced into an SPR angle shift. This unique technique bypasses the time-consuming, labor-intensive labeling processes, such as radioisotope and fluorescence labeling. More importantly, the method avoids the modification of the biomarker’s characteristics and behaviors by labeling that often occurs in traditional biosensors. While many transducers, including SPR, offer high sensitivity, selectivity is determined by the bio-receptors. In traditional biosensors, the selectivity is provided by bio-receptors possessing highly specific binding affinity to capture target analytes, yet their use in biosensors are often limited by their relatively-weak binding affinity with analyte, non-specific adsorption, need for optimization conditions, low reproducibility, and difficulties integrating onto the surface of transducers. In order to circumvent the use of bio-receptors, the competitive adsorption of proteins, termed the Vroman effect, is utilized in this work. The Vroman effect was first reported by Vroman and Adams in 1969. The competitive adsorption targeted here occurs among different proteins competing to adsorb to a surface, when more than one type of protein is present. When lower-affinity proteins are adsorbed on the surface first, they can be displaced by higher-affinity proteins arriving at the surface at a later point in time. Moreover, only low-affinity proteins can be displaced by high-affinity proteins, typically possessing higher molecular weight, yet the reverse sequence does not occur. The SPR biosensor based on competitive adsorption is successfully demonstrated to detect fibrinogen and thyroglobulin (Tg) in undiluted human serum and copper ions in drinking water through the denatured albumin.
ContributorsWang, Ran (Author) / Chae, Junseok (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Tsow, Tsing (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2015
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Description
The aging process due to Bias Temperature Instability (both NBTI and PBTI) and Channel Hot Carrier (CHC) is a key limiting factor of circuit lifetime in CMOS design. Threshold voltage shift due to BTI is a strong function of stress voltage and temperature complicating stress and recovery prediction. This poses

The aging process due to Bias Temperature Instability (both NBTI and PBTI) and Channel Hot Carrier (CHC) is a key limiting factor of circuit lifetime in CMOS design. Threshold voltage shift due to BTI is a strong function of stress voltage and temperature complicating stress and recovery prediction. This poses a unique challenge for long-term aging prediction for wide range of stress patterns. Traditional approaches usually resort to an average stress waveform to simplify the lifetime prediction. They are efficient, but fail to capture circuit operation, especially under dynamic voltage scaling (DVS) or in analog/mixed signal designs where the stress waveform is much more random. This work presents a suite of modelling solutions for BTI that enable aging simulation under all possible stress conditions. Key features of this work are compact models to predict BTI aging based on Reaction-Diffusion theory when the stress voltage is varying. The results to both reaction-diffusion (RD) and trapping-detrapping (TD) mechanisms are presented to cover underlying physics. Silicon validation of these models is performed at 28nm, 45nm and 65nm technology nodes, at both device and circuit levels. Efficient simulation leveraging the BTI models under DVS and random input waveform is applied to both digital and analog representative circuits such as ring oscillators and LNA. Both physical mechanisms are combined into a unified model which improves prediction accuracy at 45nm and 65nm nodes. Critical failure condition is also illustrated based on NBTI and PBTI at 28nm. A comprehensive picture for duty cycle shift is shown. DC stress under clock gating schemes results in monotonic shift in duty cycle which an AC stress causes duty cycle to converge close to 50% value. Proposed work provides a general and comprehensive solution to aging analysis under random stress patterns under BTI.

Channel hot carrier (CHC) is another dominant degradation mechanism which affects analog and mixed signal circuits (AMS) as transistor operates continuously in saturation condition. New model is proposed to account for e-e scattering in advanced technology nodes due to high gate electric field. The model is validated with 28nm and 65nm thick oxide data for different stress voltages. It demonstrates shift in worst case CHC condition to Vgs=Vds from Vgs=0.5Vds. A novel iteration based aging simulation framework for AMS designs is proposed which eliminates limitation for conventional reliability tools. This approach helps us identify a unique positive feedback mechanism termed as Bias Runaway. Bias runaway, is rapid increase of the bias voltage in AMS circuits which occurs when the feedback between the bias current and the effect of channel hot carrier turns into positive. The degradation of CHC is a gradual process but under specific circumstances, the degradation rate can be dramatically accelerated. Such a catastrophic phenomenon is highly sensitive to the initial operation condition, as well as transistor gate length. Based on 65nm silicon data, our work investigates the critical condition that triggers bias runaway, and the impact of gate length tuning. We develop new compact models as well as the simulation methodology for circuit diagnosis, and propose design solutions and the trade-offs to avoid bias runaway, which is vitally important to reliable AMS designs.
ContributorsSutaria, Ketul (Author) / Cao, Yu (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Chakrabarti, Chaitali (Committee member) / Yu, Shimeng (Committee member) / Arizona State University (Publisher)
Created2014