Three-dimensional vectorial holography based on machine learning inverse design

Vectorial holography over a multimode fiber

Vectorial holography through a strongly scattering medium can facilitate various applications in optics and photonics. However, the realization of vectorial holography with arbitrary distribution of optical intensity is still limited because of experimental noise during the calibration of vectorial transmission matrix (TM) and reconstruction noise during the retrieval of input wavefront for a given holographic target. Herein, we propose and experimentally demonstrate the vectorial holography with arbitrary distribution of optical intensity over a multimode fiber (MMF) using the Tikhonov regularization. By optimizing the noise factor, the performance of vectorial holography over an MMF is improved compared with the conjugate transpose and inverse TM methods. Our results might shed new light on the optical communication and detection mediated by MMFs.

Metafiber transforming arbitrarily structured light

Structured light has proven useful for numerous photonic applications. However, the current use of structured light in optical fiber science and technology is severely limited by mode mixing or by the lack of optical elements that can be integrated onto fiber end-faces for wavefront engineering, and hence generation of structured light is still handled outside the fiber via bulky optics in free space. We report a metafiber platform capable of creating arbitrarily structured light on the hybrid-order Poincaré sphere. Polymeric metasurfaces, with unleashed height degree of freedom and a greatly expanded 3D meta-atom library, were 3D laser nanoprinted and interfaced with polarization-maintaining single-mode fibers. Multiple metasurfaces were interfaced on the fiber end-faces, transforming the fiber output into different structured-light fields, including cylindrical vector beams, circularly polarized vortex beams, and arbitrary vector field. Our work provides a paradigm for advancing optical fiber science and technology towards fiber-integrated light shaping, which may find important applications in fiber communications, fiber lasers and sensors, endoscopic imaging, fiber lithography, and lab-on-fiber technology.

Recent advancements and challenges in emerging applications of biochar-based catalysts

The sustainable utilization of biochar produced from biomass waste could substantially promote the development of carbon neutrality and a circular economy. Due to their cost-effectiveness, multiple functionalities, tailorable porous structure, and thermal stability, biochar-based catalysts play a vital role in sustainable biorefineries and environmental protection, contributing to a positive, planet-level impact. This review provides an overview of emerging synthesis routes for multifunctional biochar-based catalysts. It discusses recent advances in biorefinery and pollutant degradation in air, soil, and water, providing deeper and more comprehensive information of the catalysts, such as physicochemical properties and surface chemistry. The catalytic performance and deactivation mechanisms under different catalytic systems were critically reviewed, providing new insights into developing efficient and practical biochar-based catalysts for large-scale use in various applications. Machine learning (ML)-based predictions and inverse design have addressed the innovation of biochar-based catalysts with high-performance applications, as ML efficiently predicts the properties and performance of biochar, interprets the underlying mechanisms and complicated relationships, and guides biochar synthesis. Finally, environmental benefit and economic feasibility assessments are proposed for science-based guidelines for industries and policymakers. With concerted effort, upgrading biomass waste into high-performance catalysts for biorefinery and environmental protection could reduce environmental pollution, increase energy safety, and achieve sustainable biomass management, all of which are beneficial for attaining several of the United Nations Sustainable Development Goals (UN SDGs) and Environmental, Social and Governance (ESG).

Super-compact universal quantum logic gates with inverse-designed elements

Integrated quantum photonic circuit is a promising platform for the realization of quantum information processing in the future. To achieve the large-scale quantum photonic circuits, the applied quantum logic gates should be as small as possible for the high-density integration on chips. Here, we report the implementation of super-compact universal quantum logic gates on silicon chips by the method of inverse design. In particular, the fabricated controlled-NOT gate and Hadamard gate are both nearly a vacuum wavelength, being the smallest optical quantum gates reported up to now. We further design the quantum circuit by cascading these fundamental gates to perform arbitrary quantum processing, where the corresponding size is about several orders smaller than that of previous quantum photonic circuits. Our study paves the way for the realization of large-scale quantum photonic chips with integrated sources and can have important applications in the field of quantum information processes.

Disorder-Induced Topological State Transition in the Optical Skyrmion Family

Skyrmions endowed with topological protection have been extensively investigated in various platforms including magnetics, ferroelectrics, and liquid crystals, stimulating applications such as memories, logic devices, and neuromorphic computing. While the optical counterpart has been proposed and realized recently, the study of optical skyrmions is still in its infancy. Among the unexplored questions, the investigation of the topology induced robustness against disorder is of substantial importance on both fundamental and practical sides but remains elusive. In this Letter, we manage to generate optical skyrmions numerically in real space with different topological features at will, providing a unique platform to investigate the robustness of various optical skyrmions. A disorder-induced topological state transition is observed for the first time in a family of optical skyrmions composed of six classes with different skyrmion numbers. Intriguingly, the optical skyrmions produced from a vectorial hologram are exceptionally robust against scattering from a random medium, shedding light on topological photonic devices for the generation and manipulation of robust states for applications including imaging and communication.

Super-resolution image display using diffractive decoders

High-resolution image projection over a large field of view (FOV) is hindered by the restricted space-bandwidth product (SBP) of wavefront modulators. We report a deep learning-enabled diffractive display based on a jointly trained pair of an electronic encoder and a diffractive decoder to synthesize/project super-resolved images using low-resolution wavefront modulators. The digital encoder rapidly preprocesses the high-resolution images so that their spatial information is encoded into low-resolution patterns, projected via a low SBP wavefront modulator. The diffractive decoder processes these low-resolution patterns using transmissive layers structured using deep learning to all-optically synthesize/project super-resolved images at its output FOV. This diffractive image display can achieve a super-resolution factor of ~4, increasing the SBP by ~16-fold. We experimentally validate its success using 3D-printed diffractive decoders that operate at the terahertz spectrum. This diffractive image decoder can be scaled to operate at visible wavelengths and used to design large SBP displays that are compact, low power, and computationally efficient.

Universal Metasurfaces for Complete Linear Control of Coherent Light Transmission

Recent advances in metasurfaces and optical nanostructures have enabled complex control of incident light with optically thin devices. However, it has thus far been unclear whether it is possible to achieve complete linear control of coherent light transmission, that is, independent control of polarization, amplitude, and phase for both input polarization states, with just a single, thin nanostructure array. Here, it is proved possible, and a universal metasurface is proposed, a bilayer array of high-index elliptic cylinders that possesses a complete degree of optical freedom with fully designable chirality and anisotropy. The completeness of achievable light control is mathematically shown with corresponding Jones matrices, new types of 3D holographic schemes that were formerly impossible are experimentally demonstrated, and a systematic way of realizing any input-state-sensitive vector linear optical device is presented. The results unlock previously inaccessible degrees of freedom in light transmission control.

Quantitative and Real-Time Evaluation of Human Respiration Signals with a Shape-Conformal Wireless Sensing System

Respiration signals reflect many underlying health conditions, including cardiopulmonary functions, autonomic disorders and respiratory distress, therefore continuous measurement of respiration is needed in various cases. Unfortunately, there is still a lack of effective portable electronic devices that meet the demands for medical and daily respiration monitoring. This work showcases a soft, wireless, and non-invasive device for quantitative and real-time evaluation of human respiration. This device simultaneously captures respiration and temperature signatures using customized capacitive and resistive sensors, encapsulated by a breathable layer, and does not limit the user's daily life. Further a machine learning-based respiration classification algorithm with a set of carefully studied features as inputs is proposed and it is deployed into mobile clients. The body status of users, such as being quiet, active and coughing, can be accurately recognized by the algorithm and displayed on clients. Moreover, multiple devices can be linked to a server network to monitor a group of users and provide each user with the statistical duration of physiological activities, coughing alerts, and body health advice. With these devices, individual and group respiratory health status can be quantitatively collected, analyzed, and stored for daily physiological signal detections as well as medical assistance.

Fast response electrically controlled liquid crystal lens array for high resolution 2D/3D switchable display

A fast response electrically controlled liquid crystal (LC) lens array is revealed. In order to realize the fast response, a double LC layer structure is adopted. The fabricated LC lens array has a small pitch of 310µm and LC layer with a thickness of 50μm. Experimental results show that the focal length of the LC lens array can be continuously adjusted by low driving voltage (∼6.5V_rms), and the shortest focal length is 0.5mm. The switching between 2D display and 3D display is realized by controlling the voltage off and on state of the LC lens array. Experimental result shows that the 2D/3D switchable display has a fast response time of 16ms. The short pitch LC lens array is expected to be used in high-resolution 2D/3D switchable display.

Basis function approach for diffractive pattern generation with Dammann vortex metasurfaces

In mathematics, general functions can be decomposed into a linear combination of basis functions. This principle can be used for creating an infinite number of distinct geometric patterns based on a finite number of basis patterns. Here, we propose a Dammann vortex metasurface (DVM) for optically generating an array of diverse, diffraction-multiplexed vortex patterns, based on three custom-defined basis patterns. The proposed DVM, with its capability of quantitatively correlating phase and intensity distribution in different diffraction orders, opens up doors for various applications including orbital angular momentum encryptions and quantum entanglement.

Homeostatic neuro-metasurfaces for dynamic wireless channel management

The physical basis of a smart city, the wireless channel, plays an important role in coordinating functions across a variety of systems and disordered environments, with numerous applications in wireless communication. However, conventional wireless channel typically necessitates high-complexity and energy-consuming hardware, and it is hindered by lengthy and iterative optimization strategies. Here, we introduce the concept of homeostatic neuro-metasurfaces to automatically and monolithically manage wireless channel in dynamics. These neuro-metasurfaces relieve the heavy reliance on traditional radio frequency components and embrace two iconic traits: They require no iterative computation and no human participation. In doing so, we develop a flexible deep learning paradigm for the global inverse design of large-scale metasurfaces, reaching an accuracy greater than 90%. In a full perception-decision-action experiment, our concept is demonstrated through a preliminary proof-of-concept verification and an on-demand wireless channel management. Our work provides a key advance for the next generation of electromagnetic smart cities.

Flexible Image Reconstruction in the Orbital Angular Momentum Holography with Binarized Airy Lens

The orbital angular momentum (OAM) holography has been marked a path to achieving ultrahigh capacity holographic information systems. However, the practical applicability of the OAM holography is limited by the complicated optical setup and unadjustable image intensity and position. Here, a decoding method is proposed by using a binarized phase map derived from an autofocusing Airy beam. By adjusting the parameters of the phase map, the position and intensity distribution of the reconstructed image become flexibly adjustable. In addition, the cross-talk between different image channels can be effectively reduced thanks to the abruptly autofocusing capability of the Airy beams. As a result, the quality and practicability of the OAM holography can be greatly enhanced.

Tunable liquid crystal grating based holographic 3D display system with wide viewing angle and large size

As one of the most ideal display approaches, holographic 3-dimensional (3D) display has always been a research hotspot since the holographic images reproduced in such system are very similar to what humans see the actual environment. However, current holographic 3D displays suffer from critical bottlenecks of narrow viewing angle and small size. Here, we propose a tunable liquid crystal grating-based holographic 3D display system with wide viewing angle and large size. Our tunable liquid crystal grating, providing an adjustable period and the secondary diffraction of the reconstructed image, enables to simultaneously implement two different hologram generation methods in achieving wide viewing angle and enlarged size, respectively. By using the secondary diffraction mechanism of the tunable liquid crystal grating, the proposed system breaks through the limitations of narrow viewing angle and small size of holographic 3D display. The proposed system shows a viewing angle of 57.4°, which is nearly 7 times of the conventional case with a single spatial light modulator, and the size of the reconstructed image is enlarged by about 4.2. The proposed system will have wide applications in medical diagnosis, advertising, education and entertainment and other fields.

Pixel-level Bayer-type colour router based on metasurfaces

The three primary colour model, i.e., red, green, and blue model, based on the colour perception of the human eye, has been widely used in colour imaging. The most common approach for obtaining colour information is to use a Bayer colour filter, which filters colour light with four pixels of an imaging sensor to form an effective colour pixel. However, its energy utilization efficiency and colour collection efficiency are limited to a low level due to the three-channel filtering nature. Here, by employing an inverse-design method, we demonstrate a pixel-level metasurface-based Bayer-type colour router that presents peak colour collection efficiencies of 58%, 59%, and 49% for red, green and blue light, and an average energy utilization efficiency as high as 84% over the visible region (400 nm–700 nm), which is twice as high as that of a commercial Bayer colour filter. Furthermore, by using a 200 µm × 200 µm metasurface-based colour router sample working with a monochromatic imaging sensor, colour imaging is further realized, obtaining an image intensity twice that achieved by a commercial Bayer colour filter. Our work innovates the mechanism of high-efficiency spectrum information acquisition, which is expected to have promising applications in the development of next-generation imaging systems.

Though metasurface-based 3D colour routers are attractive for next-generation colour imaging systems, their complex fabrication and poor performance remain a bottleneck. Here, the authors use the inverse-design method to realize high performance metasurface-based Bayer-type colour routers.

Nonlinear vectorial holography with quad-atom metasurfaces

Vectorial optical holography represents a solution to control the polarization and amplitude distribution of light in the Fourier space. While vectorial optical holography has been experimentally demonstrated in the linear optical regime, its nonlinear counterpart, which can provide extra degrees of freedom of light-field manipulation through the frequency conversion processes, remains unexplored. Here, we experimentally demonstrate the nonlinear vectorial holography through the second harmonic generation process on a quad-atom plasmonic metasurface. The quad-atom metasurface consists of gold meta-atoms with threefold rotational symmetry. Based on the concept of nonlinear geometric phase, we can simultaneously manipulate the phase and amplitude of the left and right circularly polarized second harmonic waves generated from the quad-atom metasurface. By superposing the two orthogonal polarization components, the quad-atom metasurface can produce nonlinear holographic images with vectorial polarization distributions. The proposed metasurface platform may have important applications in vectorial polarization nonlinear optical source, high-capacity optical information storage, and optical encryption.

Artificial intelligence to bring nanomedicine to life

The technology of drug delivery systems (DDSs) has demonstrated an outstanding performance and effectiveness in production of pharmaceuticals, as it is proved by many FDA-approved nanomedicines that have an enhanced selectivity, manageable drug release kinetics and synergistic therapeutic actions. Nonetheless, to date, the rational design and high-throughput development of nanomaterial-based DDSs for specific purposes is far from a routine practice and is still in its infancy, mainly due to the limitations in scientists' capabilities to effectively acquire, analyze, manage, and comprehend complex and ever-growing sets of experimental data, which is vital to develop DDSs with a set of desired functionalities. At the same time, this task is feasible for the data-driven approaches, high throughput experimentation techniques, process automatization, artificial intelligence (AI) technology, and machine learning (ML) approaches, which is referred to as The Fourth Paradigm of scientific research. Therefore, an integration of these approaches with nanomedicine and nanotechnology can potentially accelerate the rational design and high-throughput development of highly efficient nanoformulated drugs and smart materials with pre-defined functionalities. In this Review, we survey the important results and milestones achieved to date in the application of data science, high throughput, as well as automatization approaches, combined with AI and ML to design and optimize DDSs and related nanomaterials. This manuscript mission is not only to reflect the state-of-art in data-driven nanomedicine, but also show how recent findings in the related fields can transform the nanomedicine's image. We discuss how all these results can be used to boost nanomedicine translation to the clinic, as well as highlight the future directions for the development, data-driven, high throughput experimentation-, and AI-assisted design, as well as the production of nanoformulated drugs and smart materials with pre-defined properties and behavior. This Review will be of high interest to the chemists involved in materials science, nanotechnology, and DDSs development for biomedical applications, although the general nature of the presented approaches enables knowledge translation to many other fields of science.

Tunable structured light with flat optics

Flat optics has emerged as a key player in the area of structured light and its applications, owing to its subwavelength resolution, ease of integration, and compact footprint. Although its first generation has revolutionized conventional lenses and enabled anomalous refraction, new classes of meta-optics can now shape light and dark features of an optical field with an unprecedented level of complexity and multifunctionality. Here, we review these efforts with a focus on metasurfaces that use different properties of input light-angle of incidence and direction, polarization, phase distribution, wavelength, and nonlinear behavior-as optical knobs for tuning the output response. We discuss ongoing advances in this area as well as future challenges and prospects. These recent developments indicate that optically tunable flat optics is poised to advance adaptive camera systems, microscopes, holograms, and portable and wearable devices and may suggest new possibilities in optical communications and sensing.

Improved phase hologram generation of multiple 3D objects

We demonstrate the generation of phase holograms of multiple 3D objects at different axial positions without cross talk and significant improvements in performance over conventional methods. We first obtain the phase hologram of two 3D objects, each one comprising 50 layers, using the global Gerchberg-Saxton algorithm. Then, we discuss and demonstrate a propagation approach based on the singular value decomposition of the Fresnel impulse response function that enables fast computation of small distance propagations. Finally, we propose a new iterative hologram generation algorithm, to the best of our knowledge, that takes advantage of this propagation approach and use it to make the hologram of the same scene previously obtained with the global Gerchberg-Saxton algorithm. We perform numerical and experimental reconstructions to compare both methods, demonstrating that our proposal achieves 4 times faster computation, as well as improved reconstruction quality.

Sub-50 nm control of light at 405 nm with planar Si nanolens

We studied the super-resolution light modulation capability of Si nanodisks, a flat semi-transparent high index nanolens in the visible spectral range. A Laguerre-Gaussian beam-based optimization algorithm was developed to synthesize desired field distributions. Focused spots below 45 nm (< λ/9) were successfully achieved with 405 nm light over the whole center area of the nanolens. This superb light nano-focusing capability allows us to synthesize complex nano-patterns by simply superposing several focus spots together, making the Si nanolens a promising tool for super-resolution photolithography.

Biocompatible Nanotomography of Tightly Focused Light

Tightly focusing a spatially modulated laser beam lays the foundations for advanced optical techniques, such as a holographic optical tweezer and deterministic super-resolution imaging. Precisely mapping the subwavelength features of those highly confined fields is critical to improving the spatial resolution, especially in highly scattering biotissues. However, current techniques characterizing focal fields are mostly limited to conditions such as under a vacuum and on a glass surface. An optical probe with low cytotoxicity and resistance to autofluorescence is the key to achieving in vivo applications. Here, we use a newly emerging quantum reference beacon, the nitrogen-vacancy (NV) center in the nanodiamond, to characterize the focal field of the near-infrared (NIR) laser focus in Caenorhabditis elegans (C. elegans). This biocompatible background-free focal field mapping technique has the potential to optimize in vivo optical imaging and manipulation.

Optical diffractive deep neural network-based orbital angular momentum mode add-drop multiplexer

Vortex beams have application potential in multiplexing communication because of their orthogonal orbital angular momentum (OAM) modes. OAM add-drop multiplexing remains a challenge owing to the lack of mode selective coupling and separation technologies. We proposed an OAM add-drop multiplexer (OADM) using an optical diffractive deep neural network (ODNN). By exploiting the effective data-fitting capability of deep neural networks and the complex light-field manipulation ability of multilayer diffraction screens, we constructed a five-layer ODNN to manipulate the spatial location of vortex beams, which can selectively couple and separate OAM modes. Both the diffraction efficiency and mode purity exceeded 95% in simulations and four OAM channels carrying 16-quadrature-amplitude-modulation signals were successfully downloaded and uploaded with optical signal-to-noise ratio penalties of ∼1 dB at a bit error rate of 3.8 × 10^-3. This method can break through the constraints of conventional OADM, such as single function and poor flexibility, which may create new opportunities for OAM multiplexing and all-optical interconnection.

Multidimensional phase singularities in nanophotonics

[Figure: see text].

Deep learning: an efficient method for plasmonic design of geometric nanoparticles

Plasmons of noble metal nanoparticles have played an important role in energy transfer research, biomedical sensing, drug preparation and photocatalysis in recent years. The scattering spectra of nanoparticles are dramatically affected by numerous complex parameters, such as morphology, material, and volumes, making the parameters design a necessary step before the experiment. However, the plasmonic design is limited by several difficulties, such as the high degree of freedom, expensive trial and error costs. Herein, a plasmonic design method based on dual strategy deep learning is proposed, which can provide the design proposals according to the required spectrum. To make the model closer to the real experimental situation, the boundary element method was used to build a scattering spectra dataset of geometric nanoparticles (>1200 000 samples). Driven by the above data, the artificial intelligence (AI) model learns the relationship between spectral features and design parameters. Then, the performance statistics of the model were implemented from multiple dimensions, and a high design precision of over 90% was achieved in testing cases (testing samples >120 000). Moreover, to verify the realizability of the proposed model, the scattering spectra of nanoparticles designed by AI were constructed using a dark-field microscope system. The experimental results showed that the deviation between the target and the actual spectra was very small and within the acceptable range. This proves the realizability of the AI model proposed in this paper, and sheds light on the application of AI in plasmonic design.

Metasurface Holography in the Microwave Regime

Hologram technology has attracted a great deal of interest in a wide range of optical fields owing to its potential use in future optical applications, such as holographic imaging and optical data storage. Although there have been considerable efforts to develop holographic technologies using conventional optics, critical issues still hinder their future development. A metasurface, as an emerging multifunctional device, can manipulate the phase, magnitude, polarization and resonance properties of electromagnetic fields within a sub-wavelength scale, opening up an alternative for a compact holographic structure and high imaging quality. In this review paper, we first introduce the development history of holographic imaging and metasurfaces, and demonstrate some applications of metasurface holography in the field of optics. We then summarize the latest developments in holographic imaging in the microwave regime. These functionalities include phase- and amplitude-based design, polarization multiplexing, wavelength multiplexing, spatial asymmetric propagation, and a reconfigurable mechanism. Finally, we conclude briefly on this rapidly developing research field and present some outlooks for the near future.

Broadband generation of perfect Poincaré beams via dielectric spin-multiplexed metasurface

The term Poincaré beam, which describes the space-variant polarization of a light beam carrying spin angular momentum (SAM) and orbital angular momentum (OAM), plays an important role in various optical applications. Since the radius of a Poincaré beam conventionally depends on the topological charge number, it is difficult to generate a stable and high-quality Poincaré beam by two optical vortices with different topological charge numbers, as the Poincaré beam formed in this way collapses upon propagation. Here, based on an all-dielectric metasurface platform, we experimentally demonstrate broadband generation of a generalized perfect Poincaré beam (PPB), whose radius is independent of the topological charge number. By utilizing a phase-only modulation approach, a single-layer spin-multiplexed metasurface is shown to achieve all the states of PPBs on the hybrid-order Poincaré Sphere for visible light. Furthermore, as a proof-of-concept demonstration, a metasurface encoding multidimensional SAM and OAM states in the parallel channels of elliptical and circular PPBs is implemented for optical information encryption. We envision that this work will provide a compact and efficient platform for generation of PPBs for visible light, and may promote their applications in optical communications, information encryption, optical data storage and quantum information sciences.

Well-controlled Poincaré beams are potentially useful in optical communications applications. Here, the authors present phase-only metasurfaces that generate broadband, perfect Poincaré beams in the visible, with radius independent of the topological number.

Smart Doppler Cloak Operating in Broad Band and Full Polarizations

Invisibility cloaks, a class of attractive devices that can hide objects from external observers, have become practical reality owing to the advent of metamaterials. In previous cloaking schemes, almost all demonstrated cloaks are time-invariant and are investigated in the system that is motionless, and hence they are limited to hide stationary objects. In addition, the current cloaks are typically static or require manual operation to achieve dynamic cloaking. Here, a smart Doppler cloak operating in broadband and full polarizations is reported, which consists of a time-modulated reflective metasurface and a sensing-feedback time-varying electronic control system. Experimental results show that the smart Doppler cloak is able to respond self-adaptively and rapidly to the ever-changing velocity of moving objects and then cancel different Doppler shifts in real time, without any human intervention. Moreover, the wideband and polarization-insensitive features enable the cloak to be more robust and practical. To illustrate the capabilities of the proposed approach, the smart Doppler cloak is measured in three scenarios with two different groups of linearly-polarized incidences at 3.3 and 4.9 GHz, and one group circularly-polarized incidences at 6.0 GHz, respectively.