Design and analysis of antiresonant reflecting optical waveguide vertical cavity surface emitting lasers and amplifiers

In the past two decades, semiconductor optoelectronic devices (i.e. semiconductor lasers and amplifiers, etc) have played important roles in numerous application areas, especially in telecommunication systems. With the rapid growth of telecommunication market, these devices have been attracting great research interests to improve their single-mode high-power characteristics. Vertical cavity surface emitting lasers (VCSELs) and amplifiers (VCSOAs) are of the most promising devices that have been significantly improved the single-mode high-power performance of semiconductor lasers and amplifiers. Higher operating stability is found to be achievable by implementing antiresonant reflecting optical waveguide (ARROW) to VCSELs and VCSOAs. This doctoral thesis studies the optical characteristics of ARROW VCSELs and VCSOAs through computer modeling and simulation. The main factors (i.e. multi-transverse mode competition, polarization switching, external optical feedback etc.) that may impair the stability of ARROW VCSELs and VCSOAs’ high-power single-mode operation are analyzed numerically. Based on these analyses, design optimization methods are proposed to improve the single-mode high-power performance of ARROW VCSELs and VCSOAs.DOCTOR OF PHILOSOPHY (EEE

Optimizing OPC data sampling based on "orthogonal vector space"

ABSTRACT With shrinking feature sizes and error budgets in OPC models, effective pattern coverage and accurate measurement become more and more challenging. The goal of pattern selection is to maximize the efficiency of gauges used in model calibration. By optimizing sample plan for model calibration, we can reduce the metrology requirement and modeling turn-around time, without sacrificing the model accuracy and stability. With the Tachyon pattern-selection-tool, we seek to parameterize the patterns, by assessing dominant characteristics of the surroundings of the point of interest. This allows us to represent each pattern with one vector in a finite-dimensional space, and the entire patterns pool with a set of vectors. A reduced but representative set of patterns can then be automatically selected from the original full set sample data, based on certain coverage criteria. In this paper, we prove that the model built with 56% reduced wafer data could achieve comparable quality as the model built with full set data

Technology Roadmap for Flexible Sensors

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity