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Nanophotonics inverse design is a rapidly expanding research field whose goal is to focus users on defining complex, high-level optical functionalities while leveraging machines to search for the required material and geometry configurations in sub-wavelength structures. The journey of inverse design begins with traditional optimization tools such as topology optimization and heuristics methods, including simulated annealing, swarm optimization, and genetic algorithms. Recently, the blossoming of deep learning in various areas of data-driven science and engineering has begun to permeate nanophotonics inverse design intensely. This review discusses state-of-the-art optimizations methods, deep learning, and more recent hybrid techniques, analyzing the advantages, challenges, and perspectives of inverse design both as a science and an engineering.

Electrocatalytic two-electron oxygen reduction (2e

We cordially thank all the authors for their valuable contributions to this special issue, and also extend a special thank to Tara Dorrian and Dennis Couwenberg for suggesting and supporting this special issue.

Integrating conventional optics into compact nanostructured surfaces is the goal of flat optics. Despite the enormous progress in this technology, there are still critical challenges for real-world applications due to the limited operational efficiency in the visible region, on average lower than 60%, which originates from absorption losses in wavelength-thick (≈ 500 nm) structures. Another issue is the realization of on-demand optical components for controlling vectorial light at visible frequencies simultaneously in both reflection and transmission and with a predetermined wavefront shape. In this work, we developed an inverse design approach that allows the realization of highly efficient (up to 99%) ultrathin (down to 50 nm thick) optics for vectorial light control with broadband input–output responses in the visible and near-IR regions with a desired wavefront shape. The approach leverages suitably engineered semiconductor nanostructures, which behave as a neural network that can approximate a user-defined input–output function. Near-unity performance results from the ultrathin nature of these surfaces, which reduces absorption losses to near-negligible values. Experimentally, we discuss polarizing beam splitters, comparing their performance with the best results obtained from both direct and inverse design techniques, and new flat-optics components represented by dichroic mirrors and the basic unit of a flat-optics display that creates full colours by using only two subpixels, overcoming the limitations of conventional LCD/OLED technologies that require three subpixels for each composite colour. Our devices can be manufactured with a complementary metal-oxide-semiconductor (CMOS)-compatible process, making them scalable for mass production at low cost.

Funding: C.C. acknowledges funding from Horizon 2020 Framework Programme QuantERA grant QUOMPLEX, by National Research Council (CNR), Grant agreement ID731473. Physical unclonable functions (PUFs) are complex physical objects that aim at overcoming the vulnerabilities of traditional cryptographic keys, promising a robust class of security primitives for different applications. Optical PUFs present advantages over traditional electronic realizations, namely, a stronger unclonability, but suffer from problems of reliability and weak unpredictability of the key. We here develop a two-step PUF generation strategy based on deep learning, which associates reliable keys verified against the National Institute of Standards and Technology (NIST) certification standards of true random generators for cryptography. The idea explored in this work is to decouple the design of the PUFs from the key generation and train a neural architecture to learn the mapping algorithm between the key and the PUF. We report experimental results with all-optical PUFs realized in silica aerogels and analyzed a population of 100 generated keys, each of 10,000 bit length. The key generated passed all tests required by the NIST standard, with proportion outcomes well beyond the NIST’s recommended threshold. The two-step key generation strategy studied in this work can be generalized to any PUF based on either optical or electronic implementations. It can help the design of robust PUFs for both secure authentications and encrypted communications. Publisher PDF

Controlling the flow of broadband electromagnetic energy at the nanoscale remains a critical challenge in optoelectronics. Surface plasmon polaritons (or plasmons) provide subwavelength localization of light, but are affected by significant losses. On the contrary, dielectrics lack a sufficiently robust response in the visible to trap photons similar to metallic structures. Overcoming these limitations appears elusive, as it implies devising a path to circumvent causality in the quantum-mechanical form of matter. Here we demonstrate that addressing this problem is possible if we employ a novel approach based on suitably deformed reflective metaphotonic structures. The complex geometrical shape engineered in these reflectors emulates nondispersive index responses, which can be inverse-designed following arbitrary form factors. We discuss the realization of essential components such as resonators with an ultra-high refractive index of $n=100$ in diverse profiles. These structures support localization of light in the form of bound states in the continuum (BIC), fully localized in air, in a platform in which all refractive index regions are physically accessible. We discuss our approach to sensing applications, designing a class of sensors where the analyte directly contacts areas of ultra-high refractive index. Leveraging this feature, we report differential sensitivities up to $350$~nm/RIU in structures with footprints of approximately one micron. These performances are two times better than the closest competitor with a similar form factor. Inversely designed reflective metaphotonics offers a flexible technology for controlling broadband light, supporting optoelectronics' integration with large bandwidths in circuitry with miniaturized footprints., 24 pages, 6 figures, submitted

We demonstrate subwavelength waveguiding device based on the artificial material with ultra-high refractive index. Material is engineered through the deformation of reflective substrate via transformation optics approach which allows to achieve arbitrary refractive index distribution.

We propose optical RI sensor with sensitivity of 350 nm/RIU for the micrometer footprint. It is based on artificial material which can emulate non-dispersive ultra-high refractive index (n ≈ 100) by geometrical deformation of reflective substrate.

We introduce a universal design platform for the development of highly-efficient wavefront engineering structures. To validate this methodology, we fabricated many different optical devices with an experimental efficiency exceeding 99%.

In the past 20 years, flat‐optics has emerged as a promising light manipulation technology, surpassing bulk optics in performance, versatility, and miniaturization capabilities. As of today, however, this technology is yet to find widespread commercial applications. One of the challenges is obtaining scalable and highly efficient designs that can withstand the fabrication errors associated with nanoscale manufacturing techniques. This problem becomes more severe in flexible structures, in which deformations appear naturally when flat‐optics structures are conformally applied to, for example, biocompatible substrates. Herein, an inverse design platform that enables the fast design of flexible flat‐optics that maintain high performance under deformations of their original geometry is presented. The platform leverages on suitably designed evolutionary large‐scale optimizers, equipped with fast‐trained neural network predictors based on encoder decoder architectures. This approach supports the implementation of flexible flat‐optics robust to both fabrication errors or user‐defined perturbation stress. This method is validated by a series of experiments in which broadband flexible light polarizers, which maintain an average polarization efficiency of 80% over 200 nm bandwidths when measured under large mechanical deformations, are realized. These results could be helpful for the realization of a robust class of flexible flat‐optics for biosensing, imaging, and biomedical devices.

V.M. and M.B. contributed equally to this work. The authors acknowledge the financial support of PERA Complexity and the advisory support of co-founder Quelita Moreno. The authors acknowledge the support of the mechanical workshop of the Physics Department at University of Zurich (UZH) and of Prof. David Tilley and all the members of his research group at the Department of Chemistry of the University of Zurich (UZH).

Electrocatalytic hydrogen evolution reaction (HER) in alkaline media is a promising electrochemical energy conversion strategy. Ruthenium (Ru) is an efficient catalyst with a desirable cost for HER, however, the sluggish H2O dissociation process, due to the low H2O adsorption on its surface, currently hampers the performances of this catalyst in alkaline HER. Herein, we demonstrate that the H2O adsorption improves significantly by the construction of Ru–O–Mo sites. We prepared Ru/MoO2 catalysts with Ru–O–Mo sites through a facile thermal treatment process and assessed the creation of Ru–O–Mo interfaces by transmission electron microscope (TEM) and extended X-ray absorption fine structure (EXAFS). By using Fourier-transform infrared spectroscopy (FTIR) and H2O adsorption tests, we proved Ru–O–Mo sites have tenfold stronger H2O adsorption ability than that of Ru catalyst. The catalysts with Ru–O–Mo sites exhibited a state-of-the-art overpotential of 16 mV at 10 mA cm–2 in 1 M KOH electrolyte, demonstrating a threefold reduction than the previous bests of Ru (59 mV) and commercial Pt (31 mV) catalysts. We proved the stability of these performances over 40 h without decline. These results could open a new path for designing efficient and stable catalysts.

Nonradiating sources of energy have traditionally been studied in quantum mechanics and astrophysics, while receiving a very little attention in the photonics community. This situation has changed recently due to a number of pioneering theoretical studies and remarkable experimental demonstrations of the exotic states of light in dielectric resonant photonic structures and metasurfaces, with the possibility to localize efficiently the electromagnetic fields of high intensities within small volumes of matter. These recent advances underpin novel concepts in nanophotonics, and provide a promising pathway to overcome the problem of losses usually associated with metals and plasmonic materials for the efficient control of the light-matter interaction at the nanoscale. This review paper provides the general background and several snapshots of the recent results in this young yet prominent research field, focusing on two types of nonradiating states of light that both have been recently at the center of many studies in all-dielectric resonant meta-optics and metasurfaces: optical {\em anapoles} and photonic {\em bound states in the continuum}. We discuss a brief history of these states in optics, their underlying physics and manifestations, and also emphasize their differences and similarities. We also review some applications of such novel photonic states in both linear and nonlinear optics for the nanoscale field enhancement, a design of novel dielectric structures with high-$Q$ resonances, nonlinear wave mixing and enhanced harmonic generation, as well as advanced concepts for lasing and optical neural networks., 22 pages, 9 figures, review article

Manipulating the interaction between light and matter for generating colors is becoming a hot spot of research in photonics, revolutionizing many areas, such as holographic data storage [1] , light filtering [2] , high resolution displays [3] , security [4] , and integrated opto-electronics components [5] .

Novel metamaterial platforms exhibiting time-dependent electromagnetic properties enable the investigation of previously unexplored light-matter interactions [1] - [2] . A variation in the dielectric function on a timescale shorter than the electric field period is perceived as an ultrafast temporal boundary [3] , thus resulting in a time-dependent "Snell’s law" which connects the polarisation field frequency before and after the transition [4] , [5] . The onset of a frequency shift therefore enables the engineering of exotic nonlinear phenomena such as time refraction and photon acceleration [5] - [7] , with key fundamental and practical implications [8] . In one scheme, a temporal boundary is induced via photoexcitation of semiconducting metamaterials excited by ultrashort optical pulses. Above-bandgap photons drive an ultrafast transition from a dielectric to a metallic state. Temporal-boundaries-mediated nonlinearities become relevant for transition times shorter than the wave-period timescale, a challenging regime in optics. This condition is achieved in a hybrid approach, exploiting the interaction of terahertz (THz) fields and ultrafast photo-excited transients. The peculiar advantage of THz Time-Domain-Spectroscopy techniques is that they allow the agile reconstruction of full-field dynamics with sub-wave-period resolution. In addition, in all the considered schemes, terahertz waves impinge from vacuum onto a positionally static transient, in other words a large velocity mismatch always exists. An unexplored physical scenario is then when the transient is applied directly to a source where the transient exists in the same positional reference as the THz wave.

In this work, we propose a universal design platform for the development of wavefront engineering structures. We demonstrate this approach's efficiency by producing a series of highly efficient common optical devices.

Flat optics allow the production of integrated, lightweight, portable and wearable optical devices. In this work we propose a flat optics design platform that employs concepts from evolutionary algorithms to deep learning with convolutional neural networks, and demonstrate a general design framework that can furnish an arbitrarily designed system response in as little as 50nm of silicon. The proposed framework is fundamental for our most recent experimental paper, in which we present a plethora of high efficiency devices, including, but not limited to: polarizing beam splitters, dichroic mirrors and metasurfaces for a novel 2-pixel display technology.

In this work, we introduce a technique capable of recovering both the refractive index and thickness maps of a cell using a single measurement in the form of a color photograph of the sample. Our method exploits the appearance of thin-film interference colors on a cell when placed on top of a suitable surface. An inverse search algorithm is used to map these colors to the refractive index and thickness values of each pixel in the image. Experimentally, we show the technique can achieve a 10-2 RIU sensitivity, sufficient to differentiate between cellular organelles.

In this work, we develop a framework to experimentally extract thickness and refractive index maps from biological cells using AI-driven inverse search from RGB photographs.

We present a platform for the inverse design of flat optics that are robust to fabrication errors and mechanical deformation. Experimentally, we show flexible polarizers that maintain 80% efficiency when curved over a 200 nm bandwidth.

We developed an inexpensive structural color technique achieving full gamut at 127000 DPI on 4-inch rigid and flexible wafers via wet-chemistry of self-assembled three- dimensional dielectric nanostructures with complex hierarchical features.

Physical unclonable functions (PUFs) are complex physical objects that aim at overcoming the vulnerabilities of traditional cryptographic keys, promising a robust class of security primitives for different applications. Optical PUFs present advantages over traditional electronic realizations, namely, a stronger unclonability, but suffer from problems of reliability and weak unpredictability of the key. We here develop a two-step PUF generation strategy based on deep learning, which associates reliable keys verified against the National Institute of Standards and Technology (NIST) certification standards of true random generators for cryptography. The idea explored in this work is to decouple the design of the PUFs from the key generation and train a neural architecture to learn the mapping algorithm between the key and the PUF. We report experimental results with all-optical PUFs realized in silica aerogels and analyzed a population of 100 generated keys, each of 10,000 bit length. The key generated passed all tests required by the NIST standard, with proportion outcomes well beyond the NIST's recommended threshold. The two-step key generation strategy studied in this work can be generalized to any PUF based on either optical or electronic implementations. It can help the design of robust PUFs for both secure authentications and encrypted communications.

We present a platform for the design of high efficiency flat optics. Experimentally, we show common components such as polarizers, dichroics, and color filters with over 99% efficiency in the visible in 50nm of silicon.

We discuss a technique enabling the recovery of refractive index and thickness maps of cells using bright-field microscopy and a suitably designed ultra-dark membrane. We show spatial resolutions as low as 50 nm, enabling organelle differentiation.

We present a bio-imaging technique that exploits thin film interference on cells placed on top of a nanostructured broadband light coupling metasurface. Initial results show a 10 − 2 refractive index sensitivity and 50 nm spatial resolution.

We demonstrate structural colors with gamut exceeding the red green and blue (RGB) spectrum, on inexpensive, metal-free, and thermal resistant structures with resolution of 127000 dots per inches (DPI) on 4-inch wafers beyond.

The development of compact and energy-efficient miniaturised lasers is a critical challenge in integrated non-linear photonics. Current research focuses on the integration of subwavelength all-dielectric lasers in CMOS compatible platforms. These systems provide a viable alternative to state-of-the-art nanoplasmonic sources, whose practicality is often hindered by high metal losses. The efficiency of dielectric nanolasers, however, is affected by the diffraction limit of light, which restricts the degree of localisation achievable with standard resonator modes. The recent development of new types of radiationless states has brought a sharp innovation in the field of subwavelength dielectric lasers. Radiationless states are exotic electromagnetic solutions that originate from the complex superposition and interaction of several resonator modes. They are associated with a high degree of near-field localisation which makes them particularly advantageous for non-linear photonics applications. In this work, we provide an overview of the most recent theoretical and experimental efforts toward the development of integrated lasers and ultrafast sources based on the amplification of exotic radiationless states. In particular, we focus our attention on two specific types of radiationless states: optical anapoles and Bound States in the Continuum (BIC). By discussing their differences and similarities, we provide a unifying view of these distinct research areas and outline possible future directions for these innovative platforms.