Currently organic-inorganic hybrid perovskite solar cells (PSCs) is one kind of promising photovoltaic technology due to low production cost, easy fabrication method and high power conversion efficiency. Charge transport layers are found to be critical for device performance and stability. A traditional electron transport layer (ETL), such as TiO2 (Titanium dioxide), is not very efficient for charge extraction at the interface. Compared with TiO2, SnO2 (Tin (IV) Oxide) possesses several advantages such as higher mobility and better energy level alignment. In addition, PSCs with planar structure can be processed at lower temperature compared to PSCs with other structures. In this thesis, planar-structure perovskite solar cells with SnO2 as the electron transport layer are fabricated. The one-step spin-coating method is employed for the fabrication. Several issues are studied such as annealing the samples in ambient air or glovebox, different concentration of solution used for the samples, the impact of using filter for solutions on samples. Finally, a reproducible fabrication procedure for planer-structure perovskite solar cells with an average power conversion efficiency of 16.8%, and a maximum power conversion efficiency of 18.1% is provided.

This thesis presents a new modular structure of the axial flux Switched Reluctance Motor (SRM). The design consists of four stator disks with each adjacent disk rotated 30 degrees apart and four rotor disks connected to a common shaft. The proposed design aims to reduce the unwanted radial force, mitigate the torque ripple, and improve the efficiency. The modular structure distributes the radial force and torque strokes along the axial length of the motor, potentially damping the torque pulsation. In addition, the modular structure would deliver the rating power at a lower current level, reducing the overall ohmic loss. Moreover, if a fault occurs on a motor disk or its control unit, the motor would still operate through other disks, increasing the reliability of the system. To verify the effectiveness of the proposed design, the magneto-static and transient performance of the motor are compared with the conventional single layer structure using 3-D Finite-Element (FE) software tool to see that the proposed motor performs better with lower torque ripple and lower radial force than a conventional single layer structure.

The demand for higher frequency applications is largely driven by bandwidth. The evolution of circuits in the microwave and millimeter frequency ranges always demands higher performance and lower cost as the technology and specification requirements evolve. Thus the development of new processes addressing higher frequencies and bandwidth requirements is essential to the growth of any semiconductor company participating in these markets. There exist processes which can perform in the higher frequency design space from a technical perspective. However, a cost effective solution must complement the technical merits for deployment. Thus a new 0.15 um optical lithography pHEMT process was developed at TriQuint Semiconductor to address this market segment. A 40 GHz power amplifier has been designed to quantify and showcase the capabilities of this new process by leveraging the existing processing knowledge and the implementation of high frequency scalable models. The three stage power amplifier was designed using the TOM4 scalable depletion mode FET model. The TriQuint TQP15 Design Kit also implements microstrip transmission line models that can be used for evaluating the interconnect lines and matching networks. The process also features substrate vias and the thin film resistor and MIM capacitor models which utilize the capabilities of the BCB process flow. During the design stage we extensively used Agilent ADS program for circuit and EM simulation in order to optimize the final design. Special attention was paid to proper sizing of devices, developing matching circuits, optimizing transmission lines and power combining. The final design exhibits good performance in the 40 GHz range using the new TQP15 process. The measured results show a gain of greater than 13 dB under 3 volt drain voltage and a linear output power of greater than 28 dBm at 40 GHz. The 40 GHz power amplifier demonstrates that the new process has successfully leveraged an existing manufacturing infrastructure and has achieved repeatability, high volume manufacturing, and low cost in the millimeter frequency range.

Efficient and robust blue InGaN multiple quantum well (MQW) light emitters have become ubiquitous; however, they still have unattained theoretical potential. It is widely accepted that “localization” of carriers due to indium fluctuations theoretically enhance their efficiency by moderating defect-associated nonradiative recombination. To help develop a complete understanding of localization effects on carrier dynamics, this thesis explores degree of localization in InGaN MQWs and its dependence on well thickness and number of wells, through temperature and power dependent photoluminescence measurements. Additionally, silicon-compatible, nontoxic, colloidally synthesizable 2-5 nm Ge1-xSnx alloy quantum-dots (QDs) are explored for potential visible to near-IR optoelectronic applications. While bulk Ge is an indirect gap material, QD confinement allows enhanced direct transitions, and alloying with Sn improves transition oscillator strengths. Temperature dependent steady-state and time-resolved photoluminescence reveal relaxation pathways involving bright/dark excitons and surface states in Ge1-xSnx QDs, showing their great potential for future use.

Nanomagnetic devices have been projected as an alternative to transistor-based switching devices due to their non-volatility and potentially superior energy-efficiency. The energy efficiency is enhanced by the use of straintronics which involves the application of a voltage to a piezoelectric layer to generate a strain which is ultimately transferred to an elastically coupled magnetostrictive nanomaget, causing magnetization rotation. The low energy dissipation and non-volatility characteristics make straintronic nanomagnets very attractive for both Boolean and non-Boolean computing applications. There was relatively little research on straintronic switching in devices built with real nanomagnets that invariably have defects and imperfections, or their adaptation to non-Boolean computing, both of which have been studied in this work. Detailed studies of the effects of nanomagnet material fabrication defects and surface roughness variation (found in real nanomagnets) on the switching process and ultimately device performance of those switches have been performed theoretically. The results of these studies place the viability of straintronics logic (Boolean) and/or memory in question. With a view to analog computing and signal processing, analog spin wave based device operation has been evaluated in the presence of defects and it was found that defects impact their performance, which can be a major concern for the spin wave based device community. Additionally, the design challenge for low barrier nanomagnet which is the building block of binary stochastic neurons based probabilistic computing device in case of real nanomagnets has also been investigated. This study also cast some doubt on the efficacy of probabilistic computing devices. Fortunately, there are some non-Boolean applications based on the collective action of array of nanomagnets which are very forgiving of material defects. One example is image processing using dipole coupled nanomagnets which is studied here and it showed promising result for noise correction and edge enhancement of corrupted pixels in an image. Moreover, a single magneto tunnel junction based microwave oscillator was proposed for the first time and theoretical simulations showed that it is capable of better performance compared to traditional microwave oscillators. The experimental part of this work dealt with spin wave modes excited by surface acoustic waves, studied with time resolved magneto optic Kerr effect (TR-MOKE). New hybrid spin wave modes were observed for the first time. An experiment was carried out to emulate simulated annealing in a system of dipole coupled magnetostrictive nanomagnets where strain served as the simulated annealing agent. This was a promising outcome and it is the first demonstration of the hardware variant of simulated annealing of a many body system based on magnetostrictive nanomagnets. Finally, a giant spin Hall effect actuated surface acoustic wave antenna was demonstrated experimentally. This is the first observation of photon to phonon conversion using spin-orbit torque and although the observed conversion efficiency was poor (1%), it opened the pathway for a new acoustic radiator. These studies complement past work done in the area of straintronics.

We studied the possibility of achieving an order of magnitude reduction in the energy dissipation needed to write bits in perpendicular magnetic tunnel junctions (p-MTJs) by simulating the magnetization dynamics under a combination of resonant surface acoustic waves (r-SAW) and spin-transfer-torque (STT). The magnetization dynamics were simulated using the Landau-Lifshitz-Gilbert equation under macrospin assumption with the inclusion of thermal noise. We studied such r-SAW assisted STT switching of nanomagnets for both in-plane elliptical and circular perpendicular magnetic anisotropy (PMA) nanomagnets and show that while thermal noise affects switching probability in in-plane nanomagnets, the PMA nanomagnets are relatively robust to the effect of thermal noise. In PMA nanomagnets, the resonant magnetization dynamics builds over few 10s of cycles of SAW application that drives the magnetization to precess in a cone with a deflection of ~45⁰ from the perpendicular direction. This reduces the STT current density required to switch the magnetization direction without increasing the STT application time or degrading the switching probability in the presence of room temperature thermal noise. This could lead to a pathway to achieve energy efficient switching of spin-transfer-torque random access memory (STT-RAM) based on p-MTJs whose lateral dimensions can be scaled aggressively despite using materials with low magnetostriction by employing resonant excitation to drive the magnetization away from the easy axis before applying spin torque to achieve a complete reversal.

This dissertation explores the different ways to create thin film-based biosensors that are capable of rapid and label-free detection of cortisol, a non-specific biomarker closely linked to stress, within the physiological range of 10pM to 10 uM. Increased cortisol levels have been linked to stress-related diseases, such as chronic fatigue syndrome, irritable bowel syndrome, and post-traumatic stress disorder. It also plays a role in the suppression of the immune system as well. Therefore, accurate measurement of cortisol in saliva, serum, plasma, urine, sweat, and hair, is clinically significance to predict physical and mental diseases. In this dissertation, thin film-based electrochemical immunosensors were fabricated using a self-assembled monolayer (SAM) functionalized by cortisol specific antibodies to detect cortisol at 10 pM level sensitivities in the presence of a redox probe. The fabricated electrochemical cortisol immunosensors were able to detect cortisol in human saliva samples and the outcomes were validated using the standard Enzyme Linked Immuno Sorbent Assay (ELISA) technique. With the aim of improving signal amplification and label-free cortisol detection, copper nanoparticles were incorporated on screen-printed carbon electrodes (SPCE) for the fabrication of electrochemical cortisol immunosensor. This SPCE-based sensor showed a sensitivity of 4.21µA/M and the limit of detection 6.6nM. Both the SAM and SPCE-based immunosensors were not thermally stable due to the instability of antibodies at room temperature. To address this issue, an antibody-free immunosensor was fabricated. Molecular Imprinted Polymer (MIP) was used to template the target cortisol molecule. The MIP-based sensing platform was prepared using polypyrrole, a thermally stable conducting polymer. The conductivity of the polymer ensured good electrical performance. The polypyrrole-based MIP was synthesized by means of electrochemical polymerization and was used to detect cortisol within the physiological range at room temperature. MIP-based sensors exhibited the detection limit of 1 pM, and were cost-effective, easy to fabricate, temperature stable, and reusable. The sensing performance of the resulting sensors was comparable to those of commercially available technologies, such as ELISA. Aiming to perform cortisol sensing at point-of-care (POC), an Extended Gate Field Effect Transistor (EGFET) was integrated with a developed MIP cortisol sensor. The as developed MIP-EGFET sensor was used to detect the cortisol concentration in the range of 1 pM to 100 nM. A few of the major advantages of the developed sensor are its ability to provide a direct readout and simpler electronic systems, which are necessary for miniaturized Point of Care devices.

The characterization and fabrication of active matrix thin film transistors (TFTs) has been studied for an addressable microfluidic electrowetting channel device as application. A new transparent semiconductor material, Amorphous Indium Gallium Zinc Oxide (a-IGZO), is used for TFT, which shows high electrical performance rather than amorphous silicon based TFT; higher mobility and even higher transparency. The purpose of this dissertation is to optimize each TFT process including the optimization of a-IGZO properties to achieve robust device for application. To minimize hysteresis of TFT curves, the gate dielectric is discussed extensively in this dissertation. By optimizing gas ratio of NH3SiH4, it is found that the TFT with NH3 rich SiNx gate dielectric deposited with NH3/SiH4 =5.1 and stoichiometric SiO2 demonstrates best condition to reduce hysteresis. a-IGZO films is investigated as a function of power and substrate bias effect which affects to electrical performance; the higher power and substrate bias increase the carrier density in the film and mainly cause threshold voltage(VT) to shift in the negative gate voltage direction and mobility to increase, respectively. In addition, the powerful method to estimate the electrical properties of a-IGZO is proposed by calculating O2 and IGZO flux during sputtering in which the incorporation ratio with O2/IGZO ≈1 demonstrates the optimized a-IGZO film for TFT. It is confirmed that both physical and chemical adsorption affects the electrical property of a-IGZO channel by studying TFT-IV characteristics with different pressure and analyzing X-ray photoelectron spectroscopy (XPS), which mainly affects the VT instability. The sputtered SiO2 passivation shows better electrical performance. To achieve electrically compatible (lower back channel current) a-IGZO film to SiO2 sputter passivated device, a-IGZO TFTs require oxygen rich a-IGZO back channel by employing two step a-IGZO deposition process (2nd 10nm a-IGZO with PO2 = 1.5mTorr on 1st 40nm a-IGZO with PO2=1mTor). Electrowetting microfluidic channel device as application using a-IGZO TFTs is studied by doing preliminary test. The electrowetting channel test using polymer post device platform is candidate for addressable electrowetting microfluidic channel device driven by active matrix type a-IGZO TFT.

Accurate demand forecasting is a key capability for a manufacturing organization, more so, a semiconductor manufacturer. Many crucial decisions are based on demand forecasts. The semiconductor industry is characterized by very short product lifecycles (10 to 24 months) and extremely uncertain demand. The pace at which both the manufacturing technology and the product design changes, induce change in manufacturing throughput and potential demand. Well known methods like exponential smoothing, moving average, weighted moving average, ARMA, ARIMA, econometric methods and neural networks have been used in industry with varying degrees of success. We propose a novel forecasting technique which is based on Support Vector Regression (SVR). Specifically, we formulate ν-SVR models for semiconductor product demand data. We propose a 3-phased input vector modeling approach to comprehend demand characteristics learnt while building a standard ARIMA model on the data. Forecasting Experimentations are done for different semiconductor product demand data like 32 & 64 bit CPU products, 32bit Micro controller units, DSP for cellular products, NAND and NOR Flash Products. Demand data was provided by SRC(Semiconductor Research Consortium) Member Companies. Demand data was actual sales recorded at every month. Model performance is judged based on different performance metrics used in extant literature. Results of experimentation show that compared to other demand forecasting techniques ν-SVR can significantly reduce both mean absolute percentage errors and normalized mean-squared errors of forecasts. ν-SVR with our 3-phased input vector modeling approach performs better than standard ARIMA and simple ν-SVR models in most of the cases.

In semiconductor manufacturing, wafers are grouped into lots and sent to a separate facility for assembly and test (AT) before being shipped to the customer. Up to a dozen operations are required during AT. The facility in which these operations are performed is a reentrant flow shop consisting of several dozen to several hundred machines and up to a thousand specialized tools. Each lot follows a specific route through the facility, perhaps returning to the same machine multiple times. Each step in the route is referred to as a "pass." Lots in work in process (WIP) that have more than a single step remaining in their route are referred to as multi-pass lots. The multi-pass scheduling problem is to determine machine setups, lot assignments and lot sequences to achieve optimal output, as measured by four objectives related to key device shortages, throughput, machine utilization, and makespan, prioritized in this order. The two primary goals of this research are to develop a new formulation for the multipass problem and to design a variety of solution algorithms that can be used for both planning and real-time control. To begin, the basic AT model considering only single-pass scheduling and the previously developed greedy randomized adaptive search procedure (GRASP) along with its extensions are introduced. Then two alternative schemes are proposed to solve the multipass scheduling problem. In the final phase of this research, an efficient procedure is presented for prioritizing machine changeovers in an AT facility on a periodic basis that provides real-time support. In daily planning, target machine-tooling combinations are derived based on work in process, due dates, and backlogs. As machines finish their current lots, they need to be reconfigured to match their targets. The proposed algorithm is designed to run in real time. / text