Chiral plasmonic metasurface assembled by DNA origami.

Chiral materials are essential to perceive photonic devices that control the helicity of light. However, the chirality of natural materials is rather weak, and relatively thick films are needed for noticeable effects. To overcome this limitation, artificial photonic materials were suggested to affect the chiral response in a much more substantial manner. Ideally, a single layer of such a material, a metasurface, should already be sufficient. While various structures fabricated with top-down nanofabrication technologies have already been reported, here we propose to utilize scaffolded DNA origami technology, a scalable bottom-up approach for metamolecule production, to fabricate a chiral metasurface. We introduce a chiral plasmonic metamolecule in the shape of a tripod and simulate its optical properties. By fixing the metamolecule to a rectangular planar origami, the tripods can be assembled into a 2D DNA origami crystal that forms a chiral metasurface. We simulate the optical properties but also fabricate selected devices to assess the experimental feasibility of the suggested approach critically.

Polarization-dependent effects in vibrational absorption spectra of 2D finite-size adsorbate islands on dielectric substrates.

In the last few years, infrared reflection-absorption spectroscopy (IRRAS) has become a standard technique to study vibrational excitations of molecules. These investigations are strongly motivated by potential applications in monitoring chemical processes. For a better understanding of the adsorption mechanism of molecules on dielectrics, the polarization-dependence of an interaction of infrared light with adsorbates on dielectric surfaces is commonly used. Thus, the peak positions in absorption spectra could be different for s- and p-polarized light. This shift between the peak positions depends on both the molecule itself and the dielectric substrate. While the origin of this shift is well understood for infinite two-dimensional adsorbate layers, finite-size samples, which consist of 2D islands of a small number of molecules, have never been considered. Here, we present a study on polarization-dependent finite-size effects in the optical response of such islands on dielectric substrates. The study uses a multi-scale modeling approach that connects quantum chemistry calculations with Maxwell scattering simulations. We distinguish the optical response of a single molecule, a finite number of molecules, and a two-dimensional adsorbate layer. We analyze CO and CO2 molecules deposited on CeO2 and Al2O3 substrates. The evolution of the shift between the polarization-dependent absorbance peaks is first studied for a single molecule, which does not exhibit any shifting at all, and for finite molecular islands, where it increases with increasing island size, as well as for an infinite two-dimensional adsorbate layer. In the latter case, the agreement between the obtained results and the experimental IRRAS data and more traditional three/four-layer model theoretical studies supports the predictive power of the multi-scale approach.

Approximation method for fast calculation of transmission in multi-mode waveguides.

Freeform dielectric waveguides connect optical chips made of different materials in fully integrated photonic devices. With a spatial extent in the order of 100 µm, they constitute a computational challenge and make Maxwell full-wave solvers unhandy for the accelerated design. Therefore, it is of utmost importance to have tools that permit the fast prediction of waveguide loss to enable the rapid optimization of waveguide trajectories. Previously developed methods relied on the assumption that only a single mode propagates in the waveguide. However, the propagation of higher-order modes is not just unavoidable due to the geometry of the waveguides, but also, sometimes, beneficial as it increases the number of channels to transmit information. In this contribution, we present an approximate method for the fast calculation of transmission that accommodates the presence of higher-order waveguide modes, and assess its liability by describing light propagation through selected devices.

A Multi-Scale Approach to Simulate the Nonlinear Optical Response of Molecular Nanomaterials.

Nonlinear optics is essential for many recent photonic technologies. Here, a novel multi-scale approach is introduced to simulate the nonlinear optical response of molecular nanomaterials combining ab initio quantum-chemical and classical Maxwell-scattering computations. In this approach, the first hyperpolarizability tensor is computed with time-dependent density-functional theory and incorporated into a multi-scattering formalism that considers the optical interaction between neighboring molecules. Such incorporation is achieved by a novel object: the Hyper-Transition(T)-matrix. With this object at hand, the nonlinear optical response from single molecules and also from entire photonic devices can be computed, including the full tensorial and dispersive nature of the optical response of the molecules, as well as the optical interaction between different molecules as, for example, in the lattice of a molecular crystal. To demonstrate the applicability of the novel approach, the generation of a second-harmonic signal from a thin film of an Urea molecular crystal is computed and compared to more traditional simulations. Furthermore, an optical cavity is designed, which enhances the second-harmonic response of the molecular film up to more than two orders of magnitude. This approach is highly versatile and accurate and can be the working horse for the future exploration of nonlinear photonic molecular materials in structured photonic environments.

Metasurface-based realization of photonic time crystals.

Photonic time crystals are artificial materials whose electromagnetic properties are uniform in space but periodically vary in time. The synthesis of these materials and experimental observation of their physics remain very challenging because of the stringent requirement for uniform modulation of material properties in volumetric samples. In this work, we extend the concept of photonic time crystals to two-dimensional artificial structures-metasurfaces. We demonstrate that time-varying metasurfaces not only preserve key physical properties of volumetric photonic time crystals despite their simpler topology but also host common momentum bandgaps shared by both surface and free-space electromagnetic waves. On the basis of a microwave metasurface design, we experimentally confirmed the exponential wave amplification inside a momentum bandgap and the possibility to probe bandgap physics by external (free-space) excitations. The proposed metasurface serves as a straightforward material platform for realizing emerging photonic space-time crystals and as a realistic system for the amplification of surface-wave signals in future wireless communications.

Activating Electroluminescence of Charged Naphthalene Diimide Complexes Directly Adsorbed on a Metal Substrate.

Electroluminescence from single molecules adsorbed on a conducting surface imposes conflicting demands for the molecule-electrode coupling. To conduct electrons, the molecular orbitals need to be hybridized with the electrodes. To emit light, they need to be decoupled from the electrodes to prevent fluorescence quenching. Here, we show that fully quenched 2,6-core-substituted naphthalene diimide derivative in a self-assembled monolayer directly deposited on a Au(111) surface can be activated with the tip of a scanning tunneling microscope to decouple the relevant frontier orbitals from the metallic substrate. In this way, individual molecules can be driven from a strongly hybridized state with quenched luminescence to a light-emitting state. The emission performance compares in terms of quantum efficiency, stability, and reproducibility to that of single molecules deposited on thin insulating layers. Quantum chemical calculations suggest that the emitted light originates from the singly charged cationic pair of the molecules.

Optically tunable bianisotropy in a sphere made from an epsilon-near-zero material.

Bianisotropic media can be used to engineer absorbance, scattering, polarization, and dispersion of electromagnetic waves. However, the demonstration of a tunable light-induced bianisotropy at optical frequencies is still lacking. Here, we propose an experimentally feasible concept for a light-induced tunable bianisotropic response in a homogeneous sphere made of an epsilon-near-zero (ENZ) material. By exploiting the large linear absorption and the large possible intensity-dependent changes in the permittivity of ENZ materials, the direction-dependent scattering and absorption cross sections could be obtained. Our findings pave the way for further studies and applications in the optical regime requiring full dynamic control of the bianisotropic behavior.

Exploiting geometric biases in inverse nano-optical problems using artificial neural networks.

Solving the inverse problem is a major challenge in contemporary nano-optics. However, frequently not just a possible solution needs to be found but rather the solution that accommodates constraints imposed by the problem at hand. To select the most plausible solution for a nano-optical inverse problem additional information can be used in general, but how to specifically formulate it frequently remains unclear. Here, while studying the reconstruction of the shape of an object using the electromagnetic field in its proximity, we show how to take advantage of artificial neural networks (ANNs) to produce solutions consistent with prior assumptions concerning the structures. By preparing suitable datasets where the specific shapes of possible scatterers are defined, the ANNs learn the underlying scatterer present in the datasets. This helps to find a plausible solution to the otherwise non-unique inverse problem. We show that topology optimization, in contrast, can fail to recover the scatterer geometry meaningfully but a hybrid approach that is based on both, ANNs and a topology optimization, eventually leads to the most promising performance. Our work has direct implications in fields such as optical metrology.

Modeling four-dimensional metamaterials: a T-matrix approach to describe time-varying metasurfaces.

Exploring the interaction of light with materials periodically structured in space and time is intellectually rewarding and, simultaneously, a computational challenge. Appropriate computational tools are urgently needed to explore how such upcoming photonic materials can control light on demand. Here, we introduce a semi-analytical approach based on the transition matrix (also known as T-matrix) to analyze the optical response of a spatiotemporal metasurface. The metasurface consists of a periodic arrangement of time-varying scattering particles. In our approach, we depart from an individual scatterer's T-matrix to construct the effective T-matrix of the metasurface. From that effective T-matrix, all observable properties can reliably be predicted. We verify our semi-analytical approach with full-wave numerical simulations. We demonstrate a speed-up with our approach by a factor of more than 500 compared to a finite-element simulation. Finally, we exemplify our approach by studying the effect of time modulation on a Huygens' metasurface and discuss some emerging observable features.

Inverse design of core-shell particles with discrete material classes using neural networks.

The design of scatterers on demand is a challenging task that requires the investigation and development of novel and flexible approaches. In this paper, we propose a machine learning-assisted optimization framework to design multi-layered core-shell particles that provide a scattering response on demand. Artificial neural networks can learn to predict the scattering spectrum of core-shell particles with high accuracy and can act as fully differentiable surrogate models for a gradient-based design approach. To enable the fabrication of the particles, we consider existing materials and introduce a novel two-step optimization to treat continuous geometric parameters and discrete feasible materials simultaneously. Moreover, we overcome the non-uniqueness of the problem and expand the design space to particles of varying numbers of shells, i.e., different number of optimization parameters, with a classification network. Our method is 1-2 orders of magnitudes faster than conventional approaches in both forward prediction and inverse design and is potentially scalable to even larger and more complex scatterers.

Transformation-optics modeling of 3D-printed freeform waveguides.

Multi-photon lithography allows us to complement planar photonic integrated circuits (PIC) by in-situ 3D-printed freeform waveguide structures. However, design and optimization of such freeform waveguides using time-domain Maxwell's equations solvers often requires comparatively large computational volumes, within which the structure of interest only occupies a small fraction, thus leading to poor computational efficiency. In this paper, we present a solver-independent transformation-optics-(TO-) based technique that allows to greatly reduce the computational effort related to modeling of 3D freeform waveguides. The concept relies on transforming freeform waveguides with curved trajectories into equivalent waveguide structures with modified material properties but geometrically straight trajectories, that can be efficiently fit into rather small cuboid-shaped computational volumes. We demonstrate the viability of the technique and benchmark its performance using a series of different freeform waveguides, achieving a reduction of the simulation time by a factor of 3-6 with a significant potential for further improvement. We also fabricate and experimentally test the simulated waveguides by 3D-printing on a silicon photonic chip, and we find good agreement between the simulated and the measured transmission at λ = 1550 nm.

Multiscale Modeling of Broadband Perfect Absorbers Based on Gold Metallic Molecules.

The modeling of functional photonic devices that rely on molecular materials continues to be a major contemporary challenge. It is a challenge because, in the Maxwell equations, which govern the light-matter interaction, material properties are primarily introduced on phenomenological grounds and not from first principles. To overcome such limitations, we outline a multiscale modeling approach that bridges multiple length scales. We can predict with our approach the optical response of a photonic device that exploits in its design molecular materials whose properties were determined using time-dependent density functional theory. The specifically considered device is a broadband perfect absorber that uses in part a thin film comprising gold molecules made from 144 atoms. Our methodology discloses various chemical and physical effects that define such a device's response. Our methodology is versatile, and a larger number of applications will profit from this development.

Tuneable helices of plasmonic nanoparticles using liquid crystal templates: molecular dynamics investigation of an unusual odd-even effect in liquid crystalline dimers.

Liquid crystalline (LC) dimers formed helical nanofilaments depending on the parity of the alkyl linker, revealing an unusual odd-even effect. Molecular dynamics simulations were used to investigate the observed tendency. Elongation of the linker translates to an increase of the pitch of the helices, which allows achieving tuneable helical assemblies of Au nanoparticles doped to the LC matrix. The impact of the tuneable pitch of helices on the chiral optical properties of composites was investigated with full-wave simulations based on the T-matrix method.

A Multi-Scale Approach for Modeling the Optical Response of Molecular Materials Inside Cavities.

The recent fabrication advances in nanoscience and molecular materials point toward a new era where material properties are tailored in silico for target applications. To fully realize this potential, accurate and computationally efficient theoretical models are needed for: a) the computer-aided design and optimization of new materials before their fabrication; and b) the accurate interpretation of experiments. The development of such theoretical models is a challenging multi-disciplinary problem where physics, chemistry, and material science are intertwined across spatial scales ranging from the molecular to the device level, that is, from ångströms to millimeters. In photonic applications, molecular materials are often placed inside optical cavities. Together with the sought-after enhancement of light-molecule interactions, the cavities bring additional complexity to the modeling of such devices. Here, a multi-scale approach that, starting from ab initio quantum mechanical molecular simulations, can compute the electromagnetic response of macroscopic devices such as cavities containing molecular materials is presented. Molecular time-dependent density-functional theory calculations are combined with the efficient transition matrix based solution of Maxwell's equations. Some of the capabilities of the approach are demonstrated by simulating surface metal-organic frameworks -in-cavity and J-aggregates-in-cavity systems that have been recently investigated experimentally, and providing a refined understanding of the experimental results.

Modeling and measuring plasmonic excitations in hollow spherical gold nanoparticles.

We investigate molecular plasmonic excitations sustained in hollow spherical gold nanoparticles using time-dependent density functional theory (TD-DFT). Specifically, we consider Au60 spherical, hollow molecules as a toy model for single-shell plasmonic molecules. To quantify the plasmonic character of the excitations obtained from TD-DFT, the energy-based plasmonicity index is generalized to the framework of DFT, validated on simple systems such as the sodium Na20 chain and the silver Ag20 compound, and subsequently successfully applied to more complex molecules. We also compare the quantum mechanical TD-DFT simulations to those obtained from a classical Mie theory that relies on macroscopic electrodynamics to model the light-matter interaction. This comparison allows us to distinguish those features that can be explained classically from those that require a quantum-mechanical treatment. Finally, a double-shell system obtained by placing a C60 buckyball inside the hollow spherical gold particle is further considered. It is found that the double-shell, while increasing the overall plasmonic character of the excitations, leads to significantly lowered absorption cross sections.

Toward Perfect Optical Diffusers: Dielectric Huygens' Metasurfaces with Critical Positional Disorder.

Conventional optical diffusers, such as thick volume scatterers (Rayleigh scattering) or microstructured surface scatterers (geometric scattering), lack the potential for on-chip integration and are thus incompatible with next-generation photonic devices. Dielectric Huygens' metasurfaces, on the other hand, consist of 2D arrangements of resonant dielectric nanoparticles and therefore constitute a promising material platform for ultrathin and highly efficient photonic devices. When the nanoparticles are arranged in a random but statistically specific fashion, diffusers with exceptional properties are expected to come within reach. This work explores how dielectric Huygens' metasurfaces can implement wavelength-selective diffusers with negligible absorption losses and nearly Lambertian scattering profiles that are largely independent of the angle and polarization of incident waves. The combination of tailored positional disorder with a carefully balanced electric and magnetic response of the nanoparticles is shown to be an integral requirement for the operation as a diffuser. The proposed metasurfaces' directional scattering performance is characterized both experimentally and numerically, and their usability in wavefront-shaping applications is highlighted. Since the metasurfaces operate on the principles of Mie scattering and are embedded in a glassy environment, they may easily be incorporated in integrated photonic devices, fiber optics, or mechanically robust augmented reality displays.

Artificial neural networks used to retrieve effective properties of metamaterials.

We propose using deep neural networks for the fast retrieval of effective properties of metamaterials based on their angular-dependent reflection and transmission spectra from thin slabs. While we noticed that non-uniqueness is an issue for a successful application, we propose as a solution an automatic algorithm to subdivide the entire parameter space. Then, in each sub-space, the mapping between the optical response (complex reflection and transmission coefficients) and the corresponding material parameters (dielectric permittivity and permeability) is unique. We show that we can easily train one neural network per sub-space. For the final parameter retrieval, predictions from the different sub-networks are compared, and the one with the smallest error expresses the desired effective properties. Our approach allows a significant reduction in run-time, compared to more traditional least-squares fitting. Using deep neural networks to retrieve effective properties of metamaterials is a significant showcase for the application of AI technology to nanophotonic problems. Once trained, the nets can be applied to retrieve properties of a larger number of different metamaterials.

Annual energy yield of mono- and bifacial silicon heterojunction solar modules with high-index dielectric nanodisk arrays as anti-reflective and light trapping structures.

While various nanophotonic structures applicable to relatively thin crystalline silicon-based solar cells were proposed to ensure effective light in-coupling and light trapping in the absorber, it is of great importance to evaluate their performance on the solar module level under realistic irradiation conditions. Here, we analyze the annual energy yield of relatively thin (crystalline silicon (c-Si) wafer thickness between 5 µm and 80 µm) heterojunction (HJT) solar module architectures when optimized anti-reflective and light trapping titanium dioxide (TiO2) nanodisk square arrays are applied on the front and rear cell interfaces, respectively. Our numerical study shows that upon reducing c-Si wafer thickness down to 5 µm, the relative increase of the annual energy yield can go up to 23.3 %rel and 43.0 %rel for mono- and bifacial solar modules, respectively, when compared to the reference modules with flat optimized anti-reflective coatings of HJT solar cells.

Self-stabilizing curved metasurfaces as a sail for light-propelled spacecrafts.

Laser-driven spacecrafts are promising candidates for explorations to outer space. These spacecrafts should accelerate to a fraction of the speed of light upon illumination with earth-based laser systems. There are several challenges for such an ambitious mission that needs to be addressed yet. A matter of utmost importance is the stability of the spacecraft during the acceleration. Furthermore, the spacecraft sails should effectively reflect the light without absorptive-overheating. To address these requirements, we propose the design of a lightweight, low-absorbing, high-reflective, and self-stabilizing curved metasurface made from c-Si nanoparticles. A method to determine the stability is presented and, based on the multipole expansion method, the rotational stability of the curved metasurfaces is examined and the optimal operating regime is identified. The curvature is shown to be beneficial for the overall stability of the metasurface. The validity of the method is verified through numerical simulations of the time evolution of the trajectory of an identified metasurface. The results show that curved metasurfaces are a promising candidate for laser-driven spacecrafts.