Theory and simulation of subwavelength high contrast gratings and their applications in vertical-cavity surface-emitting laser devices

This work intends to fully explore the qualities and applications of subwavelength gratings. Subwavelength gratings are diffraction gratings with physical dimensions less than the wavelength of incident light. It has been found that by tailoring specific dimension parameters, a number of different reflection profiles can be attained by these structures including high reflectivity or low reflectivity with broad and narrow spectral responses. In the course of this thesis the physical basis for this phenomenon will be presented as well as a mathematical derivation. After discussion of the mechanics of the reflection behavior, the methods used in modeling subwavelength gratings and designing them for specific functions will be explored. Following this, the fundamentals of vertical-cavity surface-emitting lasers (VCSELs) will be discussed, and the applications of subwavelength gratings when used with these lasers will follow. Several devices, both theoretical proposals and fabricated examples, will be presented in addition to the available performance measurements. Finally, the fabrication challenges that restrict subwavelength gratings from adoption as standard components in VCSEL design will be considered with regard to ongoing fabrication research

Inverse Design of Three-Dimensional Frequency Selective Structures and Metamaterials using Multi-Objective Lazy Ant Colony Optimization

With the rise of big data and the “internet of things,” wireless signals permeate today’s environment more than ever before. As the demand for information and security continues to expand, the need for filtering a crowded signal space will become increasingly important. Although existing devices can achieve this with additional components, such as in-line filters and low noise amplifiers, these approaches introduce additional bulk, cost and complexity. An alternative, low-cost solution to filtering these signals can be achieved through the use of Frequency Selective Surfaces (FSSs), which are commonly used in antennas, polarizers, radomes, and intelligent architecture. FSSs typically consist of a doubly-periodic array of unit cells, which acts as a spatial electromagnetic filter that selectively rejects or transmits electromagnetic waves, based on the unit cell’s geometry and material properties. Unlike traditional analog filters, spatial filters must also account for the polarization and incidence angle of signals; thus, an ideal FSS maintains a given frequency response for all polarizations and incidence angles. Traditional FSS designs have ranged from planar structures with canonical shapes to miniaturized and multi-layer designs using fractals and other space-filling geometries. More recently, FSS research has expanded into three-dimensional (3D) designs, which have demonstrated enhanced fields of view over traditional planar and multi-layer designs. To date, nearly all FSSs still suffer from significant shifts in resonant frequencies or onset of grating lobes at incidence angles beyond 60 degrees in one or more polarizations. Additionally, while recent advances in additive manufacturing techniques have made fully 3D FSS designs increasingly popular, design tools to exploit these fabrication methods to develop FSSs with ultra-wide Fields of View (FOV) do not currently exist. In this dissertation, a Multi-Objective Lazy Ant Colony Optimization (MOLACO) scheme will be introduced and applied to the problem of 3D FSS design for extreme FOVs. The versatility of this algorithm will further be demonstrated through application to the design of meander line antennas, optical antennas, and phase-gradient metasurfaces

Design, Analysis, And Optimization Of Diffractive Optical Elements Under High Numerical Aperture Focusing

The demand for high optical resolution has brought researchers to explore the use of beam shaping diffractive optical elements (DOEs) for improving performance of high numerical aperture (NA) optical systems. DOEs can be designed to modulate the amplitude, phase and/or polarization of a laser beam such that it focuses into a targeted irradiance distribution, or point spread function (PSF). The focused PSF can be reshaped in both the transverse focal plane and along the optical axis. Optical lithography, microscopy and direct laser writing are but a few of the many applications in which a properly designed DOE can significantly improve optical performance of the system. Designing DOEs for use in high-NA applications is complicated by electric field depolarization that occurs with tight focusing. The linear polarization of off-axis rays is tilted upon refraction towards the focal point, generating additional transverse and longitudinal polarization components. These additional field components contribute significantly to the shape of the PSF under tight focusing and cannot be neglected as in scalar diffraction theory. The PSF can be modeled more rigorously using the electromagnetic diffraction integrals derived by Wolf, which account for the full vector character of the field. In this work, optimization algorithms based on vector diffraction theory were developed for designing DOEs that reshape the PSF of a 1.4-NA objective lens. The optimization techniques include simple exhaustive search, iterative optimization (Method of Generalized Projections), and evolutionary computation (Particle Swarm Optimization). DOE designs were obtained that can reshape either the transverse PSF or the irradiance distribution along the optical axis. In one example of transverse beam shaping, all polarization components were simultaneously reshaped so their vector addition generates a focused flat-top square irradiance pattern. Other designs were obtained that can be used to narrow the axial irradiance distribution, giving a focused beam that is superresolved relative to the diffraction limit. In addition to theory, experimental studies were undertaken that include (1) fabricating an axially superresolving DOE, (2) incorporating the DOE into the optical setup, (3) imaging the focused PSF, and (4) measuring aberrations in the objective lens to study how these affect performance of the DOE

Artificial intelligence in nanotechnology

This is the author’s version of a work that was accepted for publication in Nanotechnology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Nanotechnology 24.45 (2013): 452002During the last decade there has been an increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial intelligence based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines