The microelectronics technology has seen a tremendous growth over the past sixty years. The advancements in microelectronics, which shows the capability of yielding highly reliable and reproducible structures, have made the mass production of integrated electronic components feasible. Miniaturized, low-cost, and accurate sensors became available due to the rise of the microelectronics industry. A variety of sensors are being used extensively in many portable applications. These sensors are promising not only in research area but also in daily routine applications.

However, many sensing systems are relatively bulky, complicated, and expensive and main advantages of new sensors do not play an important role in practical applications. Many challenges arise due to intricacies for sensor packaging, especially operation in a solution environment. Additional problems emerge when interfacing sensors with external off-chip components. A large amount of research in the field of sensors has been focused on how to improve the system integration.

This work presents new methods for the design, fabrication, and integration of sensor systems. This thesis addresses these challenges, for example, interfacing microelectronic system to a liquid environment and developing a new technique for impedimetric measurement. This work also shows a new design for on-chip optical sensor without any other extra components or post-processing.

Optical Fibers coupled to laser light sources, and Light Emitting Diodes are the two classes of technologies used for optogenetic experiments. Arizona State University's Flexible Display Center fabricates novel flexible Organic Light Emitting Diodes(OLEDs). These OLEDs have the capability of being monolithically fabricated over flexible, transparent plastic substrates and having power efficient ways of addressing high density arrays of LEDs. This thesis critically evaluates the technology by identifying the key advantages, current limitations and experimentally assessing the technology in in-vivo and in-vitro animal models. For in-vivo testing, the emitted light from a flat OLED panel was directly used to stimulate the neo-cortex in the M1 region of transgenic mice expressing ChR2 (B6.Cg-Tg (Thy1-ChR2/EYFP) 9Gfng/J). An alternative stimulation paradigm using a collimating optical system coupled with an optical fiber was used for stimulating neurons in layer 5 of the motor cortex in the same transgenic mice. EMG activity was recorded from the contralateral vastus lateralis muscles. In vitro testing of the OLEDs was done in primary cortical neurons in culture transfected with blue light sensitive ChR2. The neurons were cultured on a microelectrode array for taking neuronal recordings.

Engineered nanoporous substrates made using materials such as silicon nitride or silica have been demonstrated to work as particle counters or as hosts for nano-lipid bilayer membrane formation. These mechanically fabricated porous structures have thicknesses of several hundred nanometers up to several micrometers to ensure mechanical stability of the membrane. However, it is desirable to have a three-dimensional structure to ensure increased mechanical stability. In this study, circular silica shells used from Coscinodiscus wailesii, a species of diatoms (unicellular marine algae) were immobilized on a silicon chip with a micrometer-sized aperture using a UV curable polyurethane adhesive. The current conducted by a single nanopore of 40 nm diameter and 50 nm length, during the translocation of a 27 nm polystyrene sphere was simulated using COMSOL multiphysics and tested experimentally. The current conducted by a single 40 nm diameter nanopore of the diatom shell during the translocation of a 27 nm polystyrene sphere was simulated using COMSOL Multiphysics (28.36 pA) and was compared to the experimental measurement (28.69 pA) and Coulter Counting theory (29.95 pA).In addition, a mobility of 1.11 x 10-8 m2s-1V-1 for the 27 nm polystyrene spheres was used to convert the simulated current from spatial dependence to time dependence.

To achieve a sensing diameter of 1-2 nanometers, the diatom shells were used as substrates to perform ion-channel reconstitution experiments. The immobilized diatom shell was functionalized using silane chemistry and lipid bilayer membranes were formed. Functionalization of the diatom shell surface improves bilayer formation probability from 1 out of 10 to 10 out of 10 as monitored by impedance spectroscopy. Self-insertion of outer membrane protein OmpF of E.Coli into the lipid membranes could be confirmed using single channel recordings, indicating that nano-BLMs had formed which allow for fully functional porin activity. The results indicate that biogenic silica nanoporous substrates can be simulated using a simplified two dimensional geometry to predict the current when a nanoparticle translocates through a single aperture. With their tiered three-dimensional structure, diatom shells can be used in to form nano-lipid bilayer membranes and can be used in ion-channel reconstitution experiments similar to synthetic nanoporous membranes.

This work explores how flexible electronics and display technology can be applied to develop new biomedical devices for medical, biological, and life science applications. It demonstrates how new biomedical devices can be manufactured by only modifying or personalizing the upper layers of a conventional thin film transistor (TFT) display process. This personalization was applied first to develop and demonstrate the world's largest flexible digital x-ray detector for medical and industrial imaging, and the world's first flexible ISFET pH biosensor using TFT technology. These new, flexible, digital x-ray detectors are more durable than conventional glass substrate x-ray detectors, and also can conform to the surface of the object being imaged. The new flexible ISFET pH biosensors are >10X less expensive to manufacture than comparable CMOS-based ISFETs and provide a sensing area that is orders of magnitude larger than CMOS-based ISFETs. This allows for easier integration with area intensive chemical and biological recognition material as well as allow for a larger number of unique recognition sites for low cost multiple disease and pathogen detection.

The flexible x-ray detector technology was then extended to demonstrate the viability of a new technique to seamlessly combine multiple smaller flexible x-ray detectors into a single very large, ultimately human sized, composite x-ray detector for new medical imaging applications such as single-exposure, low-dose, full-body digital radiography. Also explored, is a new approach to increase the sensitivity of digital x-ray detectors by selectively disabling rows in the active matrix array that are not part of the imaged region. It was then shown how high-resolution, flexible, organic light-emitting diode display (OLED) technology can be used to selectively stimulate and/or silence small groups of neurons on the cortical surface or within the deep brain as a potential new tool to diagnose and treat, as well as understand, neurological diseases and conditions. This work also explored the viability of a new miniaturized high sensitivity fluorescence measurement-based lab-on-a-chip optical biosensor using OLED display and a-Si:H PiN photodiode active matrix array technology for point-of-care diagnosis of multiple disease or pathogen biomarkers in a low cost disposable configuration.

Continuous monitoring in the adequate temporal and spatial scale is necessary for a better understanding of environmental variations. But field deployments of molecular biological analysis platforms in that scale are currently hindered because of issues with power, throughput and automation. Currently, such analysis is performed by the collection of large sample volumes from over a wide area and transporting them to laboratory testing facilities, which fail to provide any real-time information. This dissertation evaluates the systems currently utilized for in-situ field analyses and the issues hampering the successful deployment of such bioanalytial instruments for environmental applications. The design and development of high throughput, low power, and autonomous Polymerase Chain Reaction (PCR) instruments, amenable for portable field operations capable of providing quantitative results is presented here as part of this dissertation. A number of novel innovations have been reported here as part of this work in microfluidic design, PCR thermocycler design, optical design and systems integration. Emulsion microfluidics in conjunction with fluorinated oils and Teflon tubing have been used for the fluidic module that reduces cross-contamination eliminating the need for disposable components or constant cleaning. A cylindrical heater has been designed with the tubing wrapped around fixed temperature zones enabling continuous operation. Fluorescence excitation and detection have been achieved by using a light emitting diode (LED) as the excitation source and a photomultiplier tube (PMT) as the detector. Real-time quantitative PCR results were obtained by using multi-channel fluorescence excitation and detection using LED, optical fibers and a 64-channel multi-anode PMT for measuring continuous real-time fluorescence. The instrument was evaluated by comparing the results obtained with those obtained from a commercial instrument and found to be comparable. To further improve the design and enhance its field portability, this dissertation also presents a framework for the instrumentation necessary for a portable digital PCR platform to achieve higher throughputs with lower power. Both systems were designed such that it can easily couple with any upstream platform capable of providing nucleic acid for analysis using standard fluidic connections. Consequently, these instruments can be used not only in environmental applications, but portable diagnostics applications as well.

The design and development of analog/mixed-signal (AMS) integrated circuits (ICs) is becoming increasingly expensive, complex, and lengthy. Rapid prototyping and emulation of analog ICs will be significant in the design and testing of complex analog systems. A new approach, Programmable ANalog Device Array (PANDA) that maps any AMS design problem to a transistor-level programmable hardware, is proposed. This approach enables fast system level validation and a reduction in post-Silicon bugs, minimizing design risk and cost. The unique features of the approach include 1) transistor-level programmability that emulates each transistor behavior in an analog design, achieving very fine granularity of reconfiguration; 2) programmable switches that are treated as a design component during analog transistor emulating, and optimized with the reconfiguration matrix; 3) compensation of AC performance degradation through boosting the bias current. Based on these principles, a digitally controlled PANDA platform is designed at 45nm node that can map AMS modules across 22nm to 90nm technology nodes. A systematic emulation approach to map any analog transistor to PANDA cell is proposed, which achieves transistor level matching accuracy of less than 5% for ID and less than 10% for Rout and Gm. Circuit level analog metrics of a voltage-controlled oscillator (VCO) emulated by PANDA, match to those of the original designs in 90nm nodes with less than a 5% error. Voltage-controlled delay lines at 65nm and 90nm are emulated by 32nm PANDA, which successfully match important analog metrics. And at-speed emulation is achieved as well. Several other 90nm analog blocks are successfully emulated by the 45nm PANDA platform, including a folded-cascode operational amplifier and a sample-and-hold module (S/H)

Over the past fifty years, the development of sensors for biological applications has increased dramatically. This rapid growth can be attributed in part to the reduction in feature size, which the electronics industry has pioneered over the same period. The decrease in feature size has led to the production of microscale sensors that are used for sensing applications, ranging from whole-body monitoring down to molecular sensing. Unfortunately, sensors are often developed without regard to how they will be integrated into biological systems. The complexities of integration are underappreciated. Integration involves more than simply making electrical connections. Interfacing microscale sensors with biological environments requires numerous considerations with respect to the creation of compatible packaging, the management of biological reagents, and the act of combining technologies with different dimensions and material properties. Recent advances in microfluidics, especially the proliferation of soft lithography manufacturing methods, have established the groundwork for creating systems that may solve many of the problems inherent to sensor-fluidic interaction. The adaptation of microelectronics manufacturing methods, such as Complementary Metal-Oxide-Semiconductor (CMOS) and Microelectromechanical Systems (MEMS) processes, allows the creation of a complete biological sensing system with integrated sensors and readout circuits. Combining these technologies is an obstacle to forming complete sensor systems. This dissertation presents new approaches for the design, fabrication, and integration of microscale sensors and microelectronics with microfluidics. The work addresses specific challenges, such as combining commercial manufacturing processes into biological systems and developing microscale sensors in these processes. This work is exemplified through a feedback-controlled microfluidic pH system to demonstrate the integration capabilities of microscale sensors for autonomous microenvironment control.

In this thesis two methodologies have been proposed for evaluating the fault response of analog/RF circuits. These proposed approaches are used to evaluate the response of the faulty circuit in terms of specifications/measurements. Faulty response can be used to evaluate important test metrics like fail probability, fault coverage and yield coverage of given measurements under process variations. Once the models for faulty and fault free circuit are generated, one needs to perform Monte Carlo sampling (as opposed to Monte Carlo simulations) to compute these statistical parameters with high accuracy. The first method is based on adaptively determining the order of the model based on the error budget in terms of computing the statistical metrics and position of the threshold(s) to decide how precisely necessary models need to be extracted. In the second method, using hierarchy in process variations a hybrid of heuristics and localized linear models have been proposed. Experiments on LNA and Mixer using the adaptive model order selection procedure can reduce the number of necessary simulations by 7.54x and 7.03x respectively in the computation of fail probability for an error budget of 2%. Experiments on LNA using the hybrid approach can reduce the number of necessary simulations by 21.9x and 17x for four and six output parameters cases for improved accuracy in test statistics estimation.