arXiv subjects

Andrea Fratalocchi

Publications and source records attributed to Andrea Fratalocchi.

At least 19 recordsLinked to original sources

arXiv2025

Towards real-time additive-free dopamine detection at $10^{-8}$ mM with hardware accelerated platform integrated on camera

Tracing physiological neurotransmitters such as dopamine (DA) with detection limits down to $\mathrm{1\times10^{-8}}$ mM is a critical goal in neuroscience for studying brain functions and progressing the understanding of cerebral disease. Addressing this problem requires enhancing the current state-of-the-art additive-free electrochemical workstation methods by over two orders of magnitude. In this work, we implement an ultra-sensitive, additive-free platform exploiting suitably engineered light-scattering membranes and optical accelerators integrated into commercial vision cameras, reporting real-time detection of DA in uric and ascorbic acid below the concentration of $\mathrm{10^{-8}}$ mM. These performances improve the current best technology by over two orders of magnitude in resolution while providing continuous, real-time detection at video rates. This technology also upgrades the bulk form factor of an electrochemical workstation with an imaging camera's compact and portable footprint. The optical accelerator implemented in this work is universal and trainable to detect a wide range of biological analytes. This technology's wide adoption could help enable early disease detection and personalized treatment adjustments while improving the management of neurological, mental, and immune-related conditions.

physics.ins-det↗

arXiv2024

Quantum-activated neural reservoirs on-chip open up large hardware security models for resilient authentication

Quantum artificial intelligence is a frontier of artificial intelligence research, pioneering quantum AI-powered circuits to address problems beyond the reach of deep learning with classical architectures. This work implements a large-scale quantum-activated recurrent neural network possessing more than 3 trillion hardware nodes/cm$^2$, originating from repeatable atomic-scale nucleation dynamics in an amorphous material integrated on-chip, controlled with 0.07 nW electric power per readout channel. Compared to the best-performing reservoirs currently reported, this implementation increases the scale of the network by two orders of magnitude and reduces the power consumption by six, reaching power efficiencies in the range of the human brain, dissipating 0.2 nW/neuron. When interrogated by a classical input, the chip implements a large-scale hardware security model, enabling dictionary-free authentication secure against statistical inference attacks, including AI's present and future development, even for an adversary with a copy of all the classical components available. Experimental tests report 99.6% reliability, 100% user authentication accuracy, and an ideal 50% key uniqueness. Due to its quantum nature, the chip supports a bit density per feature size area three times higher than the best technology available, with the capacity to store more than $2^{1104}$ keys in a footprint of 1 cm$^2$. Such a quantum-powered platform could help counteract the emerging form of warfare led by the cybercrime industry in breaching authentication to target small to large-scale facilities, from private users to intelligent energy grids.

cond-mat.dis-nn↗

arXiv2023

Artificial intelligence optical hardware empowers high-resolution hyperspectral video understanding at 1.2 Tb/s

Foundation models, exemplified by GPT technology, are discovering new horizons in artificial intelligence by executing tasks beyond their designers' expectations. While the present generation provides fundamental advances in understanding language and images, the next frontier is video comprehension. Progress in this area must overcome the 1 Tb/s data rate demanded to grasp real-time multidimensional video information. This speed limit lies well beyond the capabilities of the existing generation of hardware, imposing a roadblock to further advances. This work introduces a hardware-accelerated integrated optoelectronic platform for multidimensional video understanding in real-time. The technology platform combines artificial intelligence hardware, processing information optically, with state-of-the-art machine vision networks, resulting in a data processing speed of 1.2 Tb/s with hundreds of frequency bands and megapixel spatial resolution at video rates. Such performance, validated in the AI tasks of video semantic segmentation and object understanding in indoor and aerial applications, surpasses the speed of the closest technologies with similar spectral resolution by three to four orders of magnitude. This platform opens up new avenues for research in real-time AI video understanding of multidimensional visual information, helping the empowerment of future human-machine interactions and cognitive processing developments.

cs.CV↗

arXiv2023

Pixelated high-Q metasurfaces for in-situ biospectroscopy and AI-enabled classification of lipid membrane photoswitching dynamics

Nanophotonic devices excel at confining light into intense hot spots of the electromagnetic near fields, creating unprecedented opportunities for light-matter coupling and surface-enhanced sensing. Recently, all-dielectric metasurfaces with ultrasharp resonances enabled by photonic bound states in the continuum have unlocked new functionalities for surface-enhanced biospectroscopy by precisely targeting and reading out molecular absorption signatures of diverse molecular systems. However, BIC-driven molecular spectroscopy has so far focused on endpoint measurements in dry conditions, neglecting the crucial interaction dynamics of biological systems. Here, we combine the advantages of pixelated all-dielectric metasurfaces with deep learning-enabled feature extraction and prediction to realize an integrated optofluidic platform for time-resolved in-situ biospectroscopy. Our approach harnesses high-Q metasurfaces specifically designed for operation in a lossy aqueous environment together with advanced spectral sampling techniques to temporally resolve the dynamic behavior of photoswitchable lipid membranes. Enabled by a software convolutional neural network, we further demonstrate the real-time classification of the characteristic cis and trans membrane conformations with 98% accuracy. Our synergistic sensing platform incorporating metasurfaces, optofluidics, and deep learning opens exciting possibilities for studying multi-molecular biological systems, ranging from the behavior of transmembrane proteins to the dynamic processes associated with cellular communication.

physics.optics↗

arXiv2022

Real-time Hyperspectral Imaging in Hardware via Trained Metasurface Encoders

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.

cs.CV↗

arXiv2021

Paired Ru-O-Mo ensemble for efficient and stable alkaline hydrogen evolution reaction

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 hours without decline. These results could open a new path for designing efficient and stable catalysts.

physics.chem-ph↗

arXiv2020

Broadband vectorial ultra-flat optics with experimental efficiency up to 99% in the visible via universal approximators

Integrating conventional optics into compact nanostructured surfaces is the goal of flat optics. Despite the enormous progress of this technology, there are still critical challenges for real world applications due to a limited efficiency in the visible, on average lower than $60\%$, which originates by absorption losses in wavelength thick ($\approx 500$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 $99\%$) ultra-flat (down to $50$nm thick) optics for vectorial light control and broadband input-output responses on a desired wavefront shape. The approach leverages on a hidden network of universal approximators, which exist in the physical layer of suitably engineered semiconductor nanostructures. Near unity performance results from the ultra-flat nature of these surfaces, which reduces absorption losses to almost negligible values. Experimentally, we discuss polarizing beam splitters, comparing their performances 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 colors by using only two sub-pixels, overcoming the limitations of conventional LCD/OLED technologies that require three sub-pixels for each composite color. Our devices are manufactured with a complementary metal-oxide-semiconductor (CMOS) compatible process, making them scalable for mass production at inexpensive costs.

physics.optics↗

arXiv2019

Experimental investigation of superdiffusion via coherent disordered Quantum Walks

Many disordered systems show a superdiffusive dynamics, intermediate between the diffusive one, typical of a classical stochastic process, and the so called ballistic behaviour, which is generally expected for the spreading in a quantum process. We have experimentally investigated the superdiffusive behaviour of a quantum walk (QW), whose dynamics can be related to energy transport phenomena, with a resolution which is high enough to clearly distinguish between different disorder regimes. By our experimental setup, the region between ballistic and diffusive spreading can be effectively scanned by suitably setting few degrees of freedom and without applying any decoherence to the QW evolution.

quant-ph↗

arXiv2019

Nonradiating Photonics with Resonant Dielectric Nanostructures

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.

physics.optics↗

arXiv2016

Optical force on diseased blood cells: towards the optical sorting of biological matter

By employing a series of massively parallel ab-initio simulations, we study how optical forces act on biological matter subject to morphological disease. As a representative case study, we here consider the case of Plasmodium Falciparum on red blood cells (RBC) illuminated by a monochromatic plane wave. Realistic parameters for the geometry and the refractive index are then taken from published experiments. In our theoretical campaign, we study the dependence of the optical force on the disease stage for different incident wavelengths. We show that optical forces change significantly with the disease, with amplitude variation in the hundreds of pN range. Our results open up new avenues for the design of new optical systems for the treatment of human disease.

physics.optics↗

arXiv2016

Scalable, ultra-resistant structural colors based on network metamaterials

Structural colours have drawn wide attention for their potential as a future printing technology for various applications, ranging from biomimetic tissues to adaptive camouflage materials. However, an efficient approach to realise robust colours with a scalable fabrication technique is still lacking, hampering the realisation of practical applications with this platform. Here we develop a new approach based on large scale network metamaterials, which combine dealloyed subwavelength structures at the nanoscale with loss-less, ultra-thin dielectrics coatings. By using theory and experiments, we show how sub-wavelength dielectric coatings control a mechanism of resonant light coupling with epsilon-near-zero (ENZ) regions generated in the metallic network, manifesting the formation of highly saturated structural colours that cover a wide portion of the spectrum. Ellipsometry measurements report the efficient observation of these colours even at angles of $70$ degrees. The network-like architecture of these nanomaterials allows for high mechanical resistance, which is quantified in a series of nano-scratch tests. With such remarkable properties, these metastructures represent a robust design technology for real-world, large scale commercial applications.

physics.optics↗

arXiv2016

Achieving ultrahigh carrier mobility and photo-responsivity in solution-processed perovskite/carbon nanotubes phototransistors

Organolead trihalide perovskites have drawn substantial interest for applications in photovoltaic and optoelectronic devices due to their low processing cost and remarkable physical properties. However, perovskite thin films still suffer from low carrier mobility, limiting their device performance and application potential. Here we report that embedding single-walled carbon nanotubes into halide perovskite films can significantly enhance the hole and electron mobilities to record-high values of 595.3 and 108.7 cm2 V-1 s-1, respectively. In the ambipolar phototransistors with such hybrid channels, photo-carriers generated in the light-absorbing perovskite matrix are transported by the carbon nanotubes, leading to ultrahigh detectivity of 6 * 1014 Jones and responsivity of 1 * 104 A W-1. We find that the perovskite precursor in dimethylformamide solution serve as an excellent stabilizer for the dispersion of carbon nanotubes, which potentially extend the scope of applications of perovskites in solution-processed functional composites. The unprecedented high performances underscore the perovskite/carbon nanotubes hybrids as an emerging class of functional materials in optoelectronic and other applications.

cond-mat.mtrl-sci↗

arXiv2012

Suppression of transverse instabilities of dark solitons and their dispersive shock waves

We investigate the impact of nonlocality, owing to diffusive behavior, on transverse instabilities of a dark stripe propagating in a defocusing cubic medium. The nonlocal response turns out to have a strongly stabilizing effect both in the case of a single soliton input and in the regime where dispersive shock waves develop "multisoliton regime". Such conclusions are supported by the linear stability analysis and numerical simulation of the propagation.

physics.optics↗

arXiv2010

Molecular imaging with X-ray free electron lasers: dream or reality?

X-ray Free Electron Lasers (XFEL) are revolutionary photons sources, whose ultrashort, brilliant pulses are expected to allow single molecule diffraction experiments providing structural information on the atomic length scale. This ultimate goal, however, is currently hampered by several challenging questions basically concerning sample damage, Coulomb explosion and the role of nonlinearity. By employing an original \emph{ab-initio} approach, as well as exceptional resources of parallel computing, we address these issues showing that accurate XFEL-based single molecule imaging will be only possible with ultrashort pulses of half of femtosecond, due to significant radiation damage and the formation of preferred multi-soliton clusters which reshape the overall electronic density of the molecular system at the femtosecond scale.

physics.optics↗

arXiv2010

Signatures of the Anderson localization excited by an optical frequency comb

We investigate Anderson localization of light as occurring in ultra-short excitations. A theory based on time dependent coupled-mode equations predicts universal features in the spectrum of the transmitted pulse. In particular, the process of strong localization of light is shown to correspond to the formation of peaks in both the amplitude and in the group delay of the transmitted pulse. Parallel ab-initio simulations made with Finite-Difference Time Domain codes and molecular dynamics confirm theoretical predictions, while showing that there exist an optimal degree of disorder for the strong localization.

physics.optics↗

arXiv2008

Ultrashort pulse propagation and the Anderson localization

We investigate the dynamics of a 10 fs light pulse propagating in a random medium by the direct solution of the 3D Maxwell equations. Our approach employs molecular dynamics to generate a distribution of spherical scatterers and a parallel finite-difference time-domain code for the vectorial wave propagation. We calculate the disorder-averaged energy velocity and the decay time of the transmitted pulse Versus the localization length for an increasing refractive index.

physics.optics↗

arXiv2008

Observation of a gradient catastrophe generating solitons

We investigate the propagation of a dark beam in a defocusing medium in the strong nonlinear regime. We observe for the first time a shock fan filled with non-interacting one-dimensional grey solitons that emanates from a gradient catastrophe developing around a null of the optical intensity. Remarkably this scenario turns out to be very robust, persisting also when the material nonlocal response averages the nonlinearity over dimensions much larger than the emerging soliton filaments.

physics.optics↗

arXiv2008

Condensation in disordered lasers: theory, 3D+1 simulations and experiments

The complex processes underlying the generation of a coherent-like emission from the multiple-scattering of photons and wave-localization in the presence of structural disorder are still mostly un-explored. Here we show that a single nonlinear Schroedinger equation, playing the role of the Schawlow-Townes law for standard lasers, quantitatively reproduces experimental results and three-dimensional time-domain parallel simulations of a colloidal laser system.

physics.optics↗