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Title: Nanoscale BioFETs for ultrasensitive pH and biomolecular detection
Author(s): Reddy, Bobby
Director of Research: Bashir, Rashid
Doctoral Committee Chair(s): Bashir, Rashid
Doctoral Committee Member(s): Cunningham, Brian T.; Jain, Kanti; Alam, Muhammad A.
Department / Program: Electrical & Computer Eng
Discipline: Electrical & Computer Engr
Degree Granting Institution: University of Illinois at Urbana-Champaign
Degree: Ph.D.
Genre: Dissertation
Subject(s): nanowire
biosensor
fet
isfet
pH
cancer
Abstract: In the last decade, nanoscale field-effect transistor biosensors have proven to be powerful, ultra-sensitive, label-free electrical detectors of relevant molecules ranging from solution pH to proteins to nucleic acids. Such sensors are highly amenable to scale-up and mass production and are easily integrated with necessary external electronics for point-of-care diagnostic devices, or lab-on-a-chip systems. In particular, nanowire FET sensors have been demonstrated to be much more sensitive to analytes, extending sensing capabilities to as low as attomolar concentrations without the need for labels. These devices have the potential to far surpass many current clinical alternatives in many important criteria, such as sensitivity, detection time, sample volumes, need for a label, and selectivity. However, in recent years it has become apparent that the technology has been suffering from lack of reliability, robustness, and repeatability of the devices in fluidic environments. These issues are the primary barriers preventing the maturation of the technology. Towards resolving some of these issues, this dissertation presents an iterative process of increasing the performance characteristics of nanoscale field-effect transistor biosensors. A top-down baseline silicon dioxide process with silicon-on-insulator wafers is presented, including methods for defining the biosensors at the nanoscale. This baseline process is then demonstrated for the detection of changes in pH and for detection of pyrophosphate. The CMOS compatible process presented allows for mass scale-up and for seamless integration with existing platforms. The next iteration of devices utilizes an atomic layer deposited high-k gate dielectric, aluminum oxide, for increased gate oxide capacitance. A high-k gate dielectric allows for similar electrical gate oxide thicknesses with higher physical oxide thicknesses, which results in lower leakages in fluid. This process is compared to the baseline silicon dioxide process. These process improvements result in increased sensitivity to pH, increased robustness in fluid, and reduced noise. The last device iteration replaces the aluminum oxide gate dielectric with hafnium oxide. HfO2 has a higher dielectric constant than Al2O3, is less susceptible to ion incorporation in fluid, has higher pH sensitivity, and is highly resistant to all forms of etching after annealed. This allows for the use of a wet etch of the fluid passivation layer, removing the possibility of damaging the fragile gate dielectric layer by dry etches such as reactive ion etching. Several critical steps were added for better characterization of gate dielectric layer, with special attention to the insulator-silicon interface. The HfO2 devices exhibited near Nernstian pH response with very low noise and good repeatability. Two of these stable devices were then employed simultaneously in a novel scheme that greatly amplifies pH response. Using the drastic differences in source-drain current for a 2 micron wide nanoplate device compared to a 100 nm wide nanowire device, the pH amplification scheme was shown to theoretically enable the detection of extremely low pH changes, down to 0.002 pH units. The devices were then used for the detection of microRNA analogues, short 20-25 base pair nucleotide molecules that have found use in the last decade as cancer biomarkers, down to 100 fM concentration levels. The process improvements in this work demonstrate significant progress towards catalyzing the transformation of such nanoscale bioFETs from mere proofs of concept into powerful, robust, and reliable tools for point-of-care diagnostics.
Issue Date: 2012-05-22
URI: http://hdl.handle.net/2142/31138
Rights Information: Copyright 2012 Bobby Reddy, Jr.
Date Available in IDEALS: 2012-05-22
Date Deposited: 2012-05


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