Wavelength-selective metamaterial absorber and emitter

Electromagnetic absorbers and emitters have been attracting interest in lots of fields, which are significantly revitalized because of the novel properties brought by the development of the metamaterials, the artificially designed materials. Metamaterials broadens the approaches to design the electromagnetic absorbers and emitters, making it possible to obtain the perfect absorption or emission at the wavelengths covering a wide range. Metamaterial absorbers and emitters are promising for various applications, including solar thermal-photovoltaics and thermal-photovoltaics for energy harvesting, chemical and biomedical sensors, nanoscale imaging and color printing. This work focuses on three aspects (materials, structures and design methods) to improve the experiment realizations of visible and infrared absorbers and emitters. Firstly, this work investigates simple structures based on aluminum and tungsten materials for the metamaterial absorber and emitter, which results in the realization of the all-metal visible color printing with square resonators and wavelength selective mid-infrared absorber (emitter) with cross resonators, respectively. Secondly, we explore the thermal emission properties of the quasi-periodic metal-dielectric multilayer metamaterials, which show the ability of engineering emissivity by different lattice structures. Finally, this work demonstrates the use of micro-genetic algorithm to realize efficient design and optimization for broadband metasurface absorbers, as well as wavelength-selective metasurfaces with giant circular dichroism. This work is believed to facilitate the development and application of metamaterial absorbers and emitters --Abstract, page iv

Rigorous direct and inverse design of photonic-plasmonic nanostructures

Designing photonic-plasmonic nanostructures with desirable electromagnetic properties is a central problem in modern photonics engineering. As limited by available materials, engineering geometry of optical materials at both element and array levels becomes the key to solve this problem. In this thesis, I present my work on the development of novel methods and design strategies for photonic-plasmonic structures and metamaterials, including novel Green’s matrix-based spectral methods for predicting the optical properties of large-scale nanostructures of arbitrary geometry. From engineering elements to arrays, I begin my thesis addressing toroidal electrodynamics as an emerging approach to enhance light absorption in designed nanodisks by geometrically creating anapole configurations using high-index dielectric materials. This work demonstrates enhanced absorption rates driven by multipolar decomposition of current distributions involving toroidal multipole moments for the first time. I also present my work on designing helical nano-antennas using the rigorous Surface Integral Equations method. The helical nano-antennas feature unprecedented beam-forming and polarization tunability controlled by their geometrical parameters, and can be understood from the array perspective. In these projects, optimization of optical performances are translated into systematic study of identifiable geometric parameters. However, while array-geometry engineering presents multiple advantages, including physical intuition, versatility in design, and ease of fabrication, there is currently no rigorous and efficient solution for designing complex resonances in large-scale systems from an available set of geometrical parameters. In order to achieve this important goal, I developed an efficient numerical code based on the Green’s matrix method for modeling scattering by arbitrary arrays of coupled electric and magnetic dipoles, and show its relevance to the design of light localization and scattering resonances in deterministic aperiodic geometries. I will show how universal properties driven by the aperiodic geometries of the scattering arrays can be obtained by studying the spectral statistics of the corresponding Green’s matrices and how this approach leads to novel metamaterials for the visible and near-infrared spectral ranges. Within the thesis, I also present my collaborative works as examples of direct and inverse designs of nanostructures for photonics applications, including plasmonic sensing, optical antennas, and radiation shaping

Design and Optimisation of Optical Metasurfaces Using Deep Learning

This thesis centres on the design, processing, and fabrication of tunable optical metamaterials. It incorporates physics-based simulation, deep learning (DL), and thin film fabrication techniques to offer a comprehensive exploration of the field of optical metamaterials. Placing stiff resonators on a flexible substrate is a common type of mechanically tunable metasurface, whose optical responses are tuned by dynamically adjusting the spacing between resonators by applying mechanical force. However, the significant modulus mismatch between materials causes stress concentration at the interface, leading to crack propagation and delamination at lower strain levels (20-50%), and limiting the optical tunability of the structure. To address this challenge, we propose two designs to manipulate stress distribution. Under mechanical force, the structure enables localised deformation, redirecting stress from critical areas. This mechanism minimises the accumulation of stress in the interface, thereby diminishing the risk of material failure and improving stretchability up to 120% compared to traditional designs. This extreme stretchability leads to a 143 nm resonance shift, which is almost twice as large as that of conventional geometry. A universal machine learning (ML)-based approach was developed to optimise the metasurface design across three key aspects: geometric parameters, material development, and free-form shape configuration. In design parameters optimisation, a fully connected neural network (FCNN) was developed with a mean absolute error (MAE) of 0.0051, recommending a single geometry with a 104 order of magnitude decrease in computational time when compared to finite element method (FEM) simulations used for data generation. The suggested structure provides extensive coverage of the colour space, encompassing 27.65% of the standard RGB (sRGB) space. For the materials development part, an inverse design (ID) network was combined with effective medium approximation (EMA), navigating infinite materials composition space to identify new compositions for custom applications. The last network was tasked to explore boundless free-form shape space to propose the one for the on-demand optical properties with MAE of 0.21. The accuracy of all networks was experimentally validated

Metamaterial

In-depth analysis of the theory, properties and description of the most potential technological applications of metamaterials for the realization of novel devices such as subwavelength lenses, invisibility cloaks, dipole and reflector antennas, high frequency telecommunications, new designs of bandpass filters, absorbers and concentrators of EM waves etc. In order to create a new devices it is necessary to know the main electrodynamical characteristics of metamaterial structures on the basis of which the device is supposed to be created. The electromagnetic wave scattering surfaces built with metamaterials are primarily based on the ability of metamaterials to control the surrounded electromagnetic fields by varying their permeability and permittivity characteristics. The book covers some solutions for microwave wavelength scales as well as exploitation of nanoscale EM wavelength such as visible specter using recent advances of nanotechnology, for instance in the field of nanowires, nanopolymers, carbon nanotubes and graphene. Metamaterial is suitable for scholars from extremely large scientific domain and therefore given to engineers, scientists, graduates and other interested professionals from photonics to nanoscience and from material science to antenna engineering as a comprehensive reference on this artificial materials of tomorrow