Optical surface waves, highly localized modes bound to the of media, enable manipulation light at nanoscale, thus impacting a wide range areas in nanoscience. By applying metamaterials, artificially designed optical materials, as contacting media interface, we can significantly ameliorate wave propagation and even generate new types waves. Here, demonstrate that high aspect ratio (1:20) grating structures with plasmonic lamellas deep nanoscale trenches, whose pitch is 1/10–1/35 wavelength,...

High aspect ratio titanium nitride (TiN) grating structures are fabricated by the combination of deep reactive ion etching (DRIE) and atomic layer deposition (ALD) techniques.TiN is deposited at 500 • C on a silicon trench template.Silicon between vertical TiN layers selectively etched to fabricate high trenches with pitch 400 nm height around 2.7 µm.Dielectric functions films different thicknesses 18 -105 post-annealing temperatures 700 -900 characterized an ellipsometer.We found that...

Neural operators have emerged as a powerful tool for solving partial differential equations in the context of scientific machine learning. Here, we implement and train modified Fourier neural operator surrogate solver electromagnetic scattering problems compare its data efficiency to existing methods. We further demonstrate application gradient-based nanophotonic inverse design free-form, fully three-dimensional scatterers, an area that has so far eluded deep-learning techniques.

Mid-infrared spectroscopy offers unique sensing schemes to detect target molecules thanks the absorption of infrared light at specific wavelengths chemical compositions. Due mismatch mid-infrared wavelength on order micron and nanometer size molecules, interaction between them is typically weak, resulting in small signatures absorption. Plasmonics can play an important role, enhancing photon–matter interactions by localization volumes or areas. Thus, it enables increase providing higher...

Having an artificial neural network that solves Maxwell’s equations in a general setting is intellectual challenge and great utility. Recently, there have been multiple successful attempts to use networks predict electromagnetic fields, given specific source interacting material distribution. However, many of these are limited domain size restricted object shapes similar the learned ones. Here, we overcome restrictions by using graph (GNNs) adapt propagation scheme finite-difference...

Black aluminum is a material characterized by high surface porosity due to columnar growth and exhibits unique optical properties that make it attractive for applications such as light trapping, infrared detection, passive thermal radiation cooling. In this study, we correlate the structural of black comparing with conventional reflective layers. These layers varying thicknesses were deposited on fused silica substrates, their analyzed. COMSOL simulations, supported experimental data, reveal...

Interest in electroluminescence of single molecules is stimulated by the prospect possible applications novel light emitting devices. Recent studies provide valuable insights into mechanisms leading to molecule electroluminescence. Concrete information on how boost intensity emitted light, however, rare. By combining scanning tunnelling microscopy (STM) and quantum chemical calculations, we show that emission efficiencies an individual hydrogen-phthalocyanine can be increased a factor ≈19...

We propose a device for subwavelength optical imaging based on metal-dielectric multilayer hyperlens designed in such way that only large-wavevector (evanescent) waves are transmitted while all propagating (small-wavevector) from the object area blocked by hyper-lens. numerically demonstrate as result of filtering, image plane contains scattered light features objects and is completely free background illumination. Similar spirit to conventional dark-field microscopy, proposed shown enhance...

We propose using deep neural networks for the fast retrieval of effective properties metamaterials based on their angular-dependent reflection and transmission spectra from thin slabs. While we noticed that non-uniqueness is an issue a successful application, as solution automatic algorithm to subdivide entire parameter space. Then, in each sub-space, mapping between optical response (complex coefficients) corresponding material parameters (dielectric permittivity permeability) unique. show...

Noble metal nanoparticles are prospective of enhancement light trapping, absorption and overall efficency in solar cells. Light induced plasmonic electric field concentrated near such particles can support process the absorber layer cell. In spite clarity this general principle, discussions about most effective size, shape placement cell structure still under discussion. Here we report calculations inside CdTe doped by nanospheres effects caused phenomena. COMSOL 3D finite element...

We theoretically analyze directional surface electromagnetic waves supported at an interface between isotropic medium and anisotropic metal with effective uniaxial negative permittivity. identify two types of wave solutions, resulting in unique hyperbolic dispersion the wavevector space. Such can be realized by alternating dielectric metallic layers deep subwavelength thicknesses or nanowires host. systems serve as a platform for many applications nanophotonics.

Using magnetron sputtering, we produced black aluminum samples with varying surface morphology. Here, developed a finite-element model to reproduce and gain additional insight into experimentally measured optical properties.

fs-Laser pulses can be used to locally alter the morphology and optical properties of semi-continuous metal films in a simple laser writing process.

The design of scatterers on demand is a challenging task that requires the investigation and development novel flexible approaches. In this paper, we propose machine learning-assisted optimization framework to multi-layered core-shell particles provide scattering response demand. Artificial neural networks can learn predict spectrum with high accuracy act as fully differentiable surrogate models for gradient-based approach. To enable fabrication particles, consider existing materials...

A photonic surface wave, a propagating optical mode localized at the interface of two media, can play significant role in controlling flow light nanoscale. Among various types such waves, waves with hyperbolic dispersion or simply supported on anisotropic metal interfaces be exploited to effectively control propagation lightwaves. We used semi-analytical and numerical methods study nature several configurations three-layers metal–dielectric–metal systems including isotropic cases where...

Abstract Recently it has been shown that plasmonic effects in hyperbolic metamaterials may facilitate overcoming the diffraction limit and enhance contrast function of an image by filtering background radiation. Unfortunately, such a dark‐field hyperlens degrades deep‐subwavelength regime. We push forward concept revival subwavelength imaging introduction proper phase difference between coherent sources. To study this effect we develop simplified theory wave propagation through metamaterial...

Light emission from the gap cavity formed by tip of a scanning tunneling microscope (STM) and flat metallic sample allows us to probe dielectric response metals at atomic scale presents way distinguish between different materials. The excitation mechanism charge carrier oscillations, which ultimately decay into light, is linked inelastic electron as opposed mostly semiclassical picture electromagnetic resonance cavity. Thus, observed light does not only reflect but also involves electronic...

Nonlocal constitutive relations promise to homogenize metamaterials even though the ratio of period over operational wavelength is not much smaller than unity. However, this ability has yet been verified, as frequently only discrete structures were considered. This denies a systematic variation relevant ratio. Here, we explore, using example an electric dipolar lattice, superiority nonlocal local relation when tends be comparable wavelength. Moreover, observe breakdown metamaterial at...

Hyperbolic metamaterials (HMMs) are the cornerstone of hyperlens, which brings superresolution effect from near-field to far-field zone. For effective application hyperlens it should operate in so-called canalization regime, where phase advancement propagating fields is maximally suppressed and thus field broadening minimized. conventional hyperlenses relatively straightforward achieve by tuning anisotropic permittivity tensor. However, for a dark-field designed image weak scatterers...

Superresolution is an important feature needed for modern optical microscopy. It can be achieved by using the transmission of evanescent waves in hyperbolic metamaterials. However, such devices suffer from material losses. Here we investigate a recently proposed metamaterial solid immersion lens---an assembly dielectric nanoparticles. Using multiple-scattering theory reveal conversion to propagating under conditions coherent scattering. efficiency rather low as confirmed fields couple point...

By now superresolution imaging using hyperbolic metamaterial (HMM) structures – hyperlenses has been demonstrated both theoretically and experimentally. The hyperlens operation relies on the fact that HMM allows propagation of waves with very large transverse wavevectors, which would be evanescent in common isotropic media (thus giving rise to diffraction limit). However, nearly all proposed so far have suitable only for strong scatterers such as holes a metal film. When weaker scatterers,...

We explore by theoretical means an extreme renormalisation of the eigenmodes a dimer dipolar meta-atoms due to strong light-matter interactions. Firstly, tuning height enclosing photonic cavity, we can lower energy level symmetric `bright' mode underneath that anti-symmetric `dark' mode. This is possible polaritonic nature mode, shares simultaneously its excitation with cavity and dimer. For heterogeneous dimer, show polariton modes be smoothly tuned from anti-symmetric, resulting in...

Neural operators have emerged as a powerful tool for solving partial differential equations in the context of scientific machine learning. Here, we implement and train modified Fourier neural operator surrogate solver electromagnetic scattering problems compare its data efficiency to existing methods. We further demonstrate application gradient-based nanophotonic inverse design free-form, fully three-dimensional scatterers, an area that has so far eluded deep learning techniques.

Solving the inverse problem is a major challenge in contemporary nano-optics. However, frequently not just possible solution needs to be found but rather that accommodates constraints imposed by at hand. To select most plausible for nano-optical additional information can used general, how specifically formulate it remains unclear. Here, while studying reconstruction of shape an object using electromagnetic field its proximity, we show take advantage artificial neural networks (ANNs) produce...