Recent Submissions

  • Laser-Induced Engineering of Nanomaterial Phase and Shape for 3D Light Control at the Nanoscale

    Elizarov, Maxim; Li, Ning; Fratalocchi, Andrea (IEEE, 2023-06-26) [Presentation]
    The control of light at the nanoscale through new nanofabrication techniques has garnered significant attention in research [1]. Recent advancements in fabrication methodologies have focused on processing specific geometrical patterns in a given material. However, a technique that allows point-to-point control over both material phase and geometrical shape is currently unavailable. Addressing this problem can open new pathways for controlling materials' optical response, leading to new levels of performance of photonic devices.
  • Metasurface Light Encoders Enable Real-Time Hyperspectral Imaging and Video Understanding

    Makarenko, Maksim; Burguete-Lopez, A.; Wang, Qizhou; Getman, Fedor; Giancola, Silvio; Ghanem, Bernard; Fratalocchi, Andrea (IEEE, 2023-06-26) [Presentation]
    Hyperspectral imaging has emerged as a powerful tool for identifying and remotely sensing complex materials in a wide range of applications, including medical diagnostics, security, food safety, and precision agriculture [1], [2]. Despite significant advances in this field, there remain a number of challenges that must be addressed in order to fully realize the potential of hyperspectral imaging in real-world applications. One major challenge is the high cost and slow acquisition time of current state-of-the-art hyperspectral imaging systems, which can exceed 20.000 USD for a single camera and take up to a minute to acquire a single image[3]. Additionally, existing systems are often limited by low spatial resolution and require large amounts of memory storage.
  • Machine Learning Empowers Large-Scale Optical Sensors for Ultrasensitive Detection

    Li, Ning; Wang, Qizhou; He, Zhao; Burguete-Lopez, A.; Xiang, Fei; Fratalocchi, Andrea (IEEE, 2023-06-26) [Presentation]
    Optical sensors are stirring broad interests in disease diagnostics, food safety, and environment monitoring [1]––[3]. Several criteria assess the performance of a sensor, including the analytical detection speed, cost, sensitivity, and reproducibility [4], [5]. Traditionally, optical sensing leverages localized spectral features such as e.g., resonance peaks shift, intensity variations, and widths. This approach, while straightforward in implementation, results in a weak detection limit for analytes, and needs improvement for enabling practical applications. Recent pioneering work focuses on artificial intelligence (AI) to address this issue, leveraging sparse features in broad amounts of data to enhance the sensor detection sensitivity [6]. However, most of these approaches rely on post-processing data collected with complex equipment, such as spectrum analyzers. These systems are significantly expensive, not integrated, and compete poorly with traditional sensing based on localized features.
  • Record Efficient and Stable Si-Based Photoanodes Enabled by Ultrathin Transition-Metal Alloy Film for Solar-Assisted Water Splitting

    Xiang, Fei; Li, Ning; Burguete-Lopez, A.; He, Zhao; Elizarov, Maxim; Fratalocchi, Andrea (IEEE, 2023-06-26) [Presentation]
    Photoelectrochemical (PEC) water splitting is attracting tremendous research interest as a promising energy conversion and storage route to ease the reliance on fossil fuels and contribute to sustainable development [1]–[3]. It produces clean hydrogen fuels from solar energy and water with zero carbon emissions and requires much less external bias input than the traditional pure electrolyzing system [4], [5]. Since the sluggish kinetics of water oxidation reaction at the anode side bottleneck the overall performance of the entire device, current research focuses on enhancing the catalytic performance at the photoanodes [4], [6].
  • Metrology System Based on Metasurface Implementation of Artificial Inteligence

    Burguete-Lopez, A.; Makarenko, Maksim; Wang, Qizhou; Getman, Fedor; Fratalocchi, Andrea (IEEE, 2023-06-26) [Presentation]
    Optical instrumentation is ubiquitous across scientific disciplines and industrial settings for its ability to deliver non-destructive and high accuracy mesurements [1]. However, as global manufacturing transitions an automated industry paradigm, the need for highly integrated metrology systems for autonomous machines cannot be addressed traditional bulk optics based equipment [2]. Metasurfaces provide a possible solution to this challenge, enabling near-arbitrary light control functionality in a compact form factor [3]–[5].
  • Enhanced Selectivity in the Electroproduction of H2O2 via F/S Dual-Doping in Metal-Free Nanofibers

    Xiang, Fei; Zhao, Xuhong; Yang, Jian; Li, Ning; Gong, Wenxiao; Liu, Yizhen; Burguete-Lopez, A.; Li, Yulan; Niu, Xiaobin; Fratalocchi, Andrea (Advanced Materials, Wiley, 2022-11-30) [Article]
    Electrocatalytic two-electron oxygen reduction (2e- ORR) to hydrogen peroxide (H2 O2 ) is attracting broad interest in diversified areas including paper manufacturing, wastewater treatment, production of liquid fuels, and public sanitation. Current efforts focus on researching low-cost, large-scale, and sustainable electrocatalysts with high activity and selectivity. Here we engineer large-scale H2 O2 electrocatalysts based on metal-free carbon fibers with a fluorine and sulfur dual-doping strategy. Optimized samples yield with a high onset potential of 0.814 V versus reversible hydrogen electrode (RHE), an almost an ideal 2e- pathway selectivity of 99.1%, outperforming most of the recent reported carbon-based or metal-based electrocatalysts. First principle theoretical computations and experiments demonstrate that the intermolecular charge transfer coupled with electron spin redistribution from fluorine and sulfur dual-doping is the crucial factor contributing to the enhanced performances in 2e- ORR. This work opens the door to the design and implementation of scalable, earth-abundant, highly selective electrocatalysts for H2 O2 production and other catalytic fields of industrial interest.
  • Real-time Hyperspectral Imaging in Hardware via Trained Metasurface Encoders

    Makarenko, Maksim; Burguete-Lopez, A.; Wang, Qizhou; Getman, Fedor; Giancola, Silvio; Ghanem, Bernard; Fratalocchi, Andrea (IEEE, 2022-09-27) [Conference Paper]
    Hyperspectral imaging has attracted significant attention to identify spectral signatures for image classification and automated pattern recognition in computer vision. State-of-the-art implementations of snapshot hyperspectral imaging rely on bulky, non-integrated, and expensive optical elements, including lenses, spectrometers, and filters. These macroscopic components do not allow fast data processing for, e.g. real-time and high-resolution videos. This work introduces Hyplex™, a new integrated architecture addressing the limitations discussed above. Hyplex™ is a CMOS-compatible, fast hyperspectral camera that replaces bulk optics with nanoscale metasurfaces inversely designed through artificial intelligence. Hyplex™ does not require spectrometers but makes use of conventional monochrome cameras, opening up the possibility for real-time and high-resolution hyperspectral imaging at inexpensive costs. Hyplex™ exploits a model-driven optimization, which connects the physical metasurfaces layer with modern visual computing approaches based on end-to-end training. We design and implement a prototype version of Hyplex™ and compare its performance against the state-of-the-art for typical imaging tasks such as spectral reconstruction and semantic segmentation. In all benchmarks, Hyplex™ reports the smallest reconstruction error. We additionally present what is, to the best of our knowledge, the largest publicly available labeled hyperspectral dataset for semantic segmentation.
  • Artificial Intelligence Enabled inverse design of metasurfaces: from components to integrated systems for next generation vision

    Fratalocchi, Andrea (IEEE, 2022-08-17) [Conference Paper]
    In this invited I will review our research activity in the field of inverse designed metasurfaces and artificial intelligent hardware for next generation vision and high performing optical systems.
  • Waveguiding via Transformation Optics

    Elizarov, Maxim; Fratalocchi, Andrea (IEEE, 2022-08-09) [Conference Paper]
    We demonstrate that it is possible to surpass current limitations of nanophotonics and plasmonics by designing an artificial material which can emulate user-defined spatial refractive index distribution. The effective optical property of the material is engineered through the deformation of reflective substrate via transformation optics approach. We provide one of possible applications - subwavelength optical waveguide coupler device based on this technique.
  • Inverse-Designed Metaphotonics for Hypersensitive Detection

    Elizarov, Maxim; Kivshar, Yuri; Fratalocchi, Andrea (ACS Nanoscience Au, American Chemical Society (ACS), 2022-07-25) [Article]
    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. 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 ultrahigh refractive index of n = 100 in diverse profiles. These structures support the 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 ultrahigh refractive index. Leveraging this feature, we report an optical sensor with sensitivity two times higher than the closest competitor with a similar micrometer footprint. Inversely designed reflective metaphotonics offers a flexible technology for controlling broadband light, supporting optoelectronics’ integration with large bandwidths in circuitry with miniaturized footprints.
  • Use of neural networks fro designing robust flat-optics on flexible substrates

    Getman, Fedor; Makarenko, M.; Wang, Q.; Burguete-Lopez, A.; Fratalocchi, Andrea (Optica Publishing Group (formerly OSA), 2022-01-01) [Conference Paper]
    We present an inverse design platform that enables the fast design of flexible flat-optics that maintain high performance under deformations. The platform is based on evolutionary large-scale optimizers, and neural network predictors.
  • Subwavelength optical waveguiding via inverse designed deformation of reflective surface

    Elizarov, Maxim; Fratalocchi, Andrea (Optica Publishing Group (formerly OSA), 2022-01-01) [Conference Paper, Presentation]
    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.
  • Compact sensor based on inversely designed ultrahigh RI metamaterial

    Elizarov, Maxim S.; Fratalocchi, Andrea (Optica Publishing Group, 2022) [Conference Paper, Presentation]
    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 (≈ 100) by geometrical deformation of reflective substrate.
  • Experimental Demonstration of Deformation Robust Flexible Flat Optics for the Visible

    Burguete-Lopez, A.; Makarenko, Maksim; Wang, Qizhou; Getman, Fedor; Fratalocchi, Andrea (Optica Publishing Group, 2022) [Conference Paper]
    We present experimentally realized flexible flat optics polarizers for the visible range. We show that upon curving the devices, their polarization efficiency is maintained within 5% with an 85% maximum efficiency.
  • Advancing statistical learning and artificial intelligence in nanophotonics inverse design

    Wang, Qizhou; Makarenko, Maksim; Burguete-Lopez, A.; Getman, Fedor; Fratalocchi, Andrea (Nanophotonics, Walter de Gruyter GmbH, 2021-12-22) [Article]
    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.
  • Large-Scale and Wide-Gamut Coloration at the Diffraction Limit in Flexible, Self-Assembled Hierarchical Nanomaterials

    Li, Ning; Xiang, F.; Elizarov, M. S.; Makarenko, M.; Lopez, A. B.; Getman, Fedor; Bonifazi, Marcella; Mazzone, Valerio; Fratalocchi, Andrea (Advanced Materials, Wiley, 2021-12-17) [Article]
    Unveiling physical phenomena that generate controllable structural coloration are at the center of significant research efforts due to the platform potential for the next generation of printing, sensing, displays, wearable optoelectronics components, and smart fabrics. Colors based on e-beam facilities possess high resolutions above 100K DPI, but limit manufacturing scales up to 4.37 cm2 , while requiring rigid substrates that are not flexible. State-of-art scalable techniques, on the contrary, provide either narrow gamuts or small resolutions. A common issue of current methods is also a heterogeneous resolution, which typically changes with the color printed. Here we demonstrate a structural coloration platform with broad gamuts exceeding the red, green, and blue (RGB) spectrum in inexpensive, thermal resistant, flexible and metallic-free structures at constant 101600 DPI (at the diffraction limit), obtained via mass-production manufacturing. This platform exploits a previously unexplored physical mechanism, which leverages the interplay between strong scattering modes and optical resonances excited in fully three-dimensional dielectric nanostructures with suitably engineered longitudinal profiles. The colors obtained with this technology are scalable to any area, demonstrated up to the single wafer (4-inch). These results open real-world applications of inexpensive, high-resolution, large-scale structural colors with broad chromatic spectra. This article is protected by copyright. All rights reserved.
  • Highly-efficient flat-optics inverse design platform via fast trained neural predictors

    Makarenko, Maksim; Burguete-Lopez, A.; Getman, Fedor; Fratalocchi, Andrea (SPIEOptica Publishing Group, 2021-11-19) [Conference Paper]
    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%.
  • The science of harnessing light’s darkness

    Bogdanov, Andrey A.; Fratalocchi, Andrea; Kivshar, Yuri (Nanophotonics, Walter de Gruyter GmbH, 2021-11-12) [Article]
    Nonradiative sources of light such as anapoles and bound states in the continuum (BICs) were initially proposed in quantum mechanics and astrophysics, and they did not attract much attention in photonics for a long time. However, primarily due to the rapid development of metamaterials and metaphotonics, it was recognized that such states are very prospective for efficient trapping of light, amplification of local fields, control of scattering, and also nonlinear manipulation of light at the nanoscale. Metaphotonics provides a broad variety of resonant dielectric structures, including optical gratings, metasurfaces, photonic crystals, and single resonators for a precise engineering of high values of quality factor (Q-factor) of the resonant states and their optical response. In the last ten years, nonradiating states matured from pure conceptual fundamental works to experimental demonstrations and original applications in photonics and radiophysics. They promised functional tools for controlling electromagnetic radiation of different spectral ranges from visible light to microwaves.
  • Learning framework for unsupervised cellular refractive index and thickness measurement

    Makarenko, Maksim; Burguete-Lopez, A.; Getman, Fedor; Fratalocchi, Andrea (OSA, 2021-11-01) [Conference Paper, Poster]
    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.
  • High performance silicon flat optics at visible wavelengths

    Burguete-Lopez, A.; Makarenko, Maksim; Getman, Fedor; Fratalocchi, Andrea (The Optical Society, 2021-10-29) [Conference Paper]
    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.

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