RSS 1.0PRIMALIGHT Research Group
Recent Submissions
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Enhanced Selectivity in the Electroproduction of H2O2 via F/S Dual-Doping in Metal-Free Nanofibers(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.
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Real-time Hyperspectral Imaging in Hardware via Trained Metasurface Encoders(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.
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Artificial Intelligence Enabled inverse design of metasurfaces: from components to integrated systems for next generation vision(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.
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Waveguiding via Transformation Optics(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.
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Inverse-Designed Metaphotonics for Hypersensitive Detection(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.
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Use of neural networks fro designing robust flat-optics on flexible substrates(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.
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Subwavelength optical waveguiding via inverse designed deformation of reflective surface(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.
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Compact sensor based on inversely designed ultrahigh RI metamaterial(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.
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Advancing statistical learning and artificial intelligence in nanophotonics inverse design(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.
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Large-Scale and Wide-Gamut Coloration at the Diffraction Limit in Flexible, Self-Assembled Hierarchical Nanomaterials(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.
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Highly-efficient flat-optics inverse design platform via fast trained neural predictors(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%.
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The science of harnessing light’s darkness(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.
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Learning framework for unsupervised cellular refractive index and thickness measurement(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.
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High performance silicon flat optics at visible wavelengths(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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Terahertz emission mediated by ultrafast time-varying metasurfaces(Physical Review Research, American Physical Society (APS), 2021-10-18) [Article]Systems with ultrafast time-varying dielectric properties represent an emerging physical framework. We demonstrate here the observation of subcycle dynamics interacting directly with an electromagnetic source comprised of morphologically constrained photoexcited carriers in a surface nanostructure. A transition to a metallic metasurface state occurs on time scales faster than the terahertz-field period, inducing large nonlinear ultrafast phase shifts in the terahertz emission and exposing an interesting physical setting.
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Terahertz Sources Based on Time-Dependent Metasurfaces(IEEE, 2021-09-30) [Conference Paper]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.
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Large-scale, high-resolution, wide-gamut structural coloration of flexible substrate(IEEE, 2021-09-30) [Conference Paper]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] .
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Metasurface design platform for highly efficient wavefront engineering(IEEE, 2021-09-30) [Conference Paper]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.
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Clean Carbon Cycle via High-Performing and Low-Cost Solar-Driven Production of Freshwater(Advanced Sustainable Systems, Wiley, 2021-09-12) [Article]While renewable power available worldwide costs increasingly less than the least expensive option based on fossil fuels, countries continue to increase their coal-fired capacity, which should conversely fall by 80% within a decade to limit global warming effects. To address the challenges to the implementation of such an aim, here, a path is explored that leverages on a previously unrecognized aspect of coal, opening to a new solar-driven carbon cycle that is environmentally friendly. By engineering the porosity matrix of coal into a suitably designed compressed volumetric structure, and by coupling it with a network of cotton fibers, it is possible to create a record performing device for freshwater production, with a desalination rate per raw material cost evaluated at 1.39 kg h −1 $ −1 at one sun intensity. This value is between two and three times higher than any other solar desalination device proposed to date. These results could envision a clean and socially sustainable cycle for carbon materials that, while enabling an enhanced water economy with global access to freshwater and sanitation, poses zero risks of reinjecting 𝐶𝑂2 into the environment through competing economies in the fossil's market.
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Robust and Scalable Flat-Optics on Flexible Substrates via Evolutionary Neural Networks(Advanced Intelligent Systems, Wiley, 2021-08-31) [Article]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.
