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.

The ability to monitor electrophysiological signals from the sentient brain is requisite to decipher its enormously complex workings and initiate remedial solutions for the vast amount of neurologically-based disorders. Despite immense advancements in creating a variety of instruments to record signals from the brain, the translation of such neurorecording instrumentation to real clinical domains places heavy demands on their safety and reliability, both of which are not entirely portrayed by presently existing implantable recording solutions. In an attempt to lower these barriers, alternative wireless radar backscattering techniques are proposed to render the technical burdens of the implant chip to entirely passive neurorecording processes that transpire in the absence of formal integrated power sources or powering schemes along with any active circuitry. These radar-like wireless backscattering mechanisms are used to conceive of fully passive neurorecording operations of an implantable microsystem. The fully passive device potentially manifests inherent advantages over current wireless implantable and wired recording systems: negligible heat dissipation to reduce risks of brain tissue damage and minimal circuitry for long term reliability as a chronic implant. Fully passive neurorecording operations are realized via intrinsic nonlinear mixing properties of the varactor diode. These mixing and recording operations are directly activated by wirelessly interrogating the fully passive device with a microwave carrier signal. This fundamental carrier signal, acquired by the implant antenna, mixes through the varactor diode along with the internal targeted neuropotential brain signals to produce higher frequency harmonics containing the targeted neuropotential signals. These harmonics are backscattered wirelessly to the external interrogator that retrieves and recovers the original neuropotential brain signal. The passive approach removes the need for internal power sources and may alleviate heat trauma and reliability issues that limit practical implementation of existing implantable neurorecorders.

To uncover the neural correlates to go-directed behavior, single unit action potentials are considered fundamental computing units and have been examined by different analytical methodologies under a broad set of hypotheses. Using a behaving rat performing a directional choice learning task, we aim to study changes in rat's cortical neural patterns while he improved his task performance accuracy from chance to 80% or higher. Specifically, simultaneous multi-channel single unit neural recordings from the rat's agranular medial (AGm) and Agranular lateral (AGl) cortices were analyzed using joint peristimulus time histogram (JPSTHs), which effectively unveils firing coincidences in neural action potentials. My results based on data from six rats revealed that coincidences of pair-wise neural action potentials are higher when rats were performing the task than they were not at the learning stage, and this trend abated after the rats learned the task. Another finding is that the coincidences at the learning stage are stronger than that when the rats learned the task especially when they were performing the task. Therefore, this coincidence measure is the highest when the rats were performing the task at the learning stage. This may suggest that neural coincidences play a role in the coordination and communication among populations of neurons engaged in a purposeful act. Additionally, attention and working memory may have contributed to the modulation of neural coincidences during the designed task.

Learning by trial-and-error requires retrospective information that whether a past action resulted in a rewarded outcome. Previous outcome in turn may provide information to guide future behavioral adjustment. But the specific contribution of this information to learning a task and the neural representations during the trial-and-error learning process is not well understood. In this dissertation, such learning is analyzed by means of single unit neural recordings in the rats' motor agranular medial (AGm) and agranular lateral (AGl) while the rats learned to perform a directional choice task. Multichannel chronic recordings using implanted microelectrodes in the rat's brain were essential to this study. Also for fundamental scientific investigations in general and for some applications such as brain machine interface, the recorded neural waveforms need to be analyzed first to identify neural action potentials as basic computing units. Prior to analyzing and modeling the recorded neural signals, this dissertation proposes an advanced spike sorting system, the M-Sorter, to extract the action potentials from raw neural waveforms. The M-Sorter shows better or comparable performance compared with two other popular spike sorters under automatic mode. With the sorted action potentials in place, neuronal activity in the AGm and AGl areas in rats during learning of a directional choice task is examined. Systematic analyses suggest that rat's neural activity in AGm and AGl was modulated by previous trial outcomes during learning. Single unit based neural dynamics during task learning are described in detail in the dissertation. Furthermore, the differences in neural modulation between fast and slow learning rats were compared. The results show that the level of neural modulation of previous trial outcome is different in fast and slow learning rats which may in turn suggest an important role of previous trial outcome encoding in learning.

Surface plasmon resonance (SPR) has emerged as a popular technique for elucidating subtle signals from biological events in a label-free, high throughput environment. The efficacy of conventional SPR sensors, whose signals are mass-sensitive, diminishes rapidly with the size of the observed target molecules. The following work advances the current SPR sensor paradigm for the purpose of small molecule detection. The detection limits of two orthogonal components of SPR measurement are targeted: speed and sensitivity. In the context of this report, speed refers to the dynamic range of measured kinetic rate constants, while sensitivity refers to the target molecule mass limitation of conventional SPR measurement. A simple device for high-speed microfluidic delivery of liquid samples to a sensor surface is presented to address the temporal limitations of conventional SPR measurement. The time scale of buffer/sample switching is on the order of milliseconds, thereby minimizing the opportunity for sample plug dispersion. The high rates of mass transport to and from the central microfluidic sensing region allow for SPR-based kinetic analysis of binding events with dissociation rate constants (kd) up to 130 s-1. The required sample volume is only 1 μL, allowing for minimal sample consumption during high-speed kinetic binding measurement. Charge-based detection of small molecules is demonstrated by plasmonic-based electrochemical impedance microscopy (P-EIM). The dependence of surface plasmon resonance (SPR) on surface charge density is used to detect small molecules (60-120 Da) printed on a dextran-modified sensor surface. The SPR response to an applied ac potential is a function of the surface charge density. This optical signal is comprised of a dc and an ac component, and is measured with high spatial resolution. The amplitude and phase of local surface impedance is provided by the ac component. The phase signal of the small molecules is a function of their charge status, which is manipulated by the pH of a solution. This technique is used to detect and distinguish small molecules based on their charge status, thereby circumventing the mass limitation (~100 Da) of conventional SPR measurement.

This dissertation proposes a miniature FIR filter that works at microwave frequencies, whose filter response can ideally be digitally programmed. Such a frequency agile device can find applications in cellular communications and wireless networking. The basic concept of the FIR filter utilizes a low loss acoustic waveguide of appropriate geometry that acts as a traveling wave tapped-delay line. The input RF signal is applied by an array of capacitive transducers at various locations on the acoustic waveguide at one end that excites waves of a propagating acoustic mode with varying spatial delays and amplitudes which interfere as they propagate. The output RF signal is picked up at the other end of the waveguide by another array of capacitive transducers. Tuning of the FIR filter coefficients is realized by controlling the DC voltage profile applied to the individual transducers which essentially shapes the overall filter response. Equivalent circuit modeling of the capacitive transducer, acoustic waveguide and transducer-line coupling is presented in this dissertation. A theoretical model for the filter is developed from a general theory of an array of transducers exciting a waveguide and is used to obtain a set of filter design equations. A MATLAB based circuit simulator is developed to simulate the filter responses. Design parameters and simulation results obtained for an example waveguide structure are presented and compared to the values estimated by the theoretical model. A waveguide structure utilizing the Rayleigh-like mode of a ridge is then introduced. A semi-analytical method to obtain propagating elastic modes of such a ridge waveguide etched in an anisotropic crystal is presented. Microfabrication of a filter based on ridges etched in single crystal Silicon is discussed along with details of the challenges faced. Finally, future work and a few alternative designs are presented that can have a better chance of success. Analysis and modeling work to this point has given a good understanding of the working principles, performance tradeoffs and fabrication pitfalls of the proposed device. With the appropriate acoustic waveguide structure, the proposed device could make it possible to realize miniature programmable FIR filters in the GHz range.

ABSTRACT This work seeks to develop a practical solution for short range ultrasonic communications and produce an integrated array of acoustic transmitters on a flexible substrate. This is done using flexible thin film transistor (TFT) and micro electromechanical systems (MEMS). The goal is to develop a flexible system capable of communicating in the ultrasonic frequency range at a distance of 10 - 100 meters. This requires a great deal of innovation on the part of the FDC team developing the TFT driving circuitry and the MEMS team adapting the technology for fabrication on a flexible substrate. The technologies required for this research are independently developed. The TFT development is driven primarily by research into flexible displays. The MEMS development is driving by research in biosensors and micro actuators. This project involves the integration of TFT flexible circuit capabilities with MEMS micro actuators in the novel area of flexible acoustic transmitter arrays. This thesis focuses on the design, testing and analysis of the circuit components required for this project.

Power supply management is important for MEMS (Micro-Electro-Mechanical-Systems) bio-sensing and chemical sensing applications. The dissertation focuses on discussion of accessibility to different power sources and supply tuning in sensing applications. First, the dissertation presents a high efficiency DC-DC converter for a miniaturized Microbial Fuel Cell (MFC). The miniaturized MFC produces up to approximately 10µW with an output voltage of 0.4-0.7V. Such a low voltage, which is also load dependent, prevents the MFC to directly drive low power electronics. A PFM (Pulse Frequency Modulation) type DC-DC converter in DCM (Discontinuous Conduction Mode) is developed to address the challenges and provides a load independent output voltage with high conversion efficiency. The DC-DC converter, implemented in UMC 0.18µm technology, has been thoroughly characterized, coupled with the MFC. At 0.9V output, the converter has a peak efficiency of 85% with 9µW load, highest efficiency over prior publication. Energy could be harvested wirelessly and often has profound impacts on system performance. The dissertation reports a side-by-side comparison of two wireless and passive sensing systems: inductive and electromagnetic (EM) couplings for an application of in-situ and real-time monitoring of wafer cleanliness in semiconductor facilities. The wireless system, containing the MEMS sensor works with battery-free operations. Two wireless systems based on inductive and EM couplings have been implemented. The working distance of the inductive coupling system is limited by signal-to-noise-ratio (SNR) while that of the EM coupling is limited by the coupled power. The implemented on-wafer transponders achieve a working distance of 6 cm and 25 cm with a concentration resolution of less than 2% (4 ppb for a 200 ppb solution) for inductive and EM couplings, respectively. Finally, the supply tuning is presented in bio-sensing application to mitigate temperature sensitivity. The FBAR (film bulk acoustic resonator) based oscillator is an attractive method in label-free sensing application. Molecular interactions on FBAR surface induce mass change, which results in resonant frequency shift of FBAR. While FBAR has a high-Q to be sensitive to the molecular interactions, FBAR has finite temperature sensitivity. A temperature compensation technique is presented that improves the temperature coefficient of a 1.625 GHz FBAR-based oscillator from -118 ppm/K to less than 1 ppm/K by tuning the supply voltage of the oscillator. The tuning technique adds no additional component and has a large frequency tunability of -4305 ppm/V.

This work demonstrates the integration of a wearable particulate detector and a wireless chemical sensor into a single portable system. The detection philosophy of the chemical sensor is based on highly selective and sensitive microfabricated quartz tuning fork arrays and the particle detector detects the particulate level in real-time using a nephelometric (light scattering) approach. The device integration is realized by carefully evaluating the needs of flow rate, power and data collection. Validation test has been carried out in both laboratory and in field trials such as parking structures and highway exits with high and low traffic emissions. The integrated single portable detection system is capable of reducing the burden for a child to carry multiple devices, simplifying the task of researchers to synchronize and analyze data from different sensors, and minimizing the overall weight, size, and cost of the sensor. It also has a cell phone for data analysis, storage, and transmission as a user-friendly interface. As the chemical and particulate levels present important exposure risks that are of high interests to epidemiologists, the integrated device will provide an easier, wearable and cost effective way to monitor it.

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.