Highly sensitive plasmonic sensor based on eccentric-core photonic crystal fibers.

To further reduce the fabrication difficulty of optical fiber sensors and improve the sensing performance, this study introduced the surface plasmon resonance (SPR) effect into optical fiber sensing technology and designed an eccentric-core photonic crystal fiber (EC-PCF). We investigated the characteristics of the two fundamental modes in the fiber core and the surface plasmon polariton (SPP) modes on the surface of the gold film. We also investigated the influence of the structural parameters, such as gold film coating area and thickness, air hole diameter, and eccentricity, on the confinement loss and achieved a refractive index (RI) sensitivity of 31.25 µm RIU-1 in the RI range of 1.29-1.43, corresponding to a figure of merit (FOM) of 521.6 per RIU. When the resolution of the optical spectrum analyzer was 0.1 nm, the EC-PCF could achieve a refractive index resolution of 3.2 × 10-6 RIU. Moreover, we performed tests with two typical sensing types, one in which the sensor was directly in contact with adulterated gasoline to achieve kerosene-concentration detection, and another in which the sensor was coated with a layer of polydimethylsiloxane (PDMS), whose RI is sensitive to the temperature field, to achieve temperature sensing. The EC-PCF demonstrated excellent sensing performance and offers obvious manufacturing advantages, providing a new and easily fabricated structural design idea for optical fiber sensing.

High confidence plasmonic sensor based on photonic crystal fibers with a U-shaped detection channel.

In order to improve the performance of optical fiber sensing and expand its application, a photonic crystal fiber (PCF) plasmonic sensor with a U-shaped channel based on surface plasmon resonance (SPR) is proposed. We have studied the general influence rules of structural parameters such as the radius of the air hole, the thickness of the gold film and the number of U-shaped channels using COMSOL based on the finite element method. The dispersion curves and loss spectrum of the surface plasmon polariton (SPP) mode and the Y-polarization (Y-pol) mode as well as the distribution of the electric field intensity (normE) under various conditions are studied using the coupled mode theory. The maximum refractive index (RI) sensitivity achieved in the RI range of 1.38-1.43 is 24.1 µm RIU-1, which corresponds to a full width at half maximum (FWHM) of 10.0 nm, a figure of merit (FOM) of 2410 RIU-1 and a resolution of 4.15 × 10-6 RIU. The results show that the proposed sensor combines the SPR effect, which is extremely sensitive to changes in the RI of the surrounding medium and realizes real-time detection of the external environment by analyzing the light signal modulated by the sensor. In addition, the detection range and sensitivity can be extended by adjusting the structural parameters. The proposed sensor has a simple structure with excellent sensing performance, which provides a new idea and implementation method for real-time detection, long-range measurement, complex environment monitoring and highly integrated sensing, and has a strong potential practical value.

Dynamically changeable terahertz metamaterial absorbers with intelligent switch and high sensitivity and wide and narrow band perfect absorption.

In this work, we theoretically designed a dynamically changeable terahertz metamaterial absorber with intelligent switch and high sensitivity, wide band and narrow band perfect absorption based on the combination of Dirac semimetal (BDS) and vanadium dioxide (VO2). It features two methods for absorption adjustment: altering the Fermi energy level of BDS to modify the resonant frequency of the absorption peaks and utilizing the phase change of VO2 to regulate the absorption rate of the peaks. In addition, its rotational symmetric design ensures strong polarization-insensitivity. The simulation results demonstrate the presence of two narrowband absorption peaks and one mini-broadband absorption peak within the frequency range of 6.0-9.5 THz, all with absorption rates exceeding 90%. We provide an explanation of the absorption mechanism of the device, employing the relative impedance theory and localized surface plasmon resonance to analyze its electric field distribution. We also defined the refractive index sensitivity (S), which is SI = 378 GHz per RIU and SIII = 204 GHz per RIU. Our device possesses high sensitivity and two methods of adjusting absorption modes, which endow it with advantages in the fields of metamaterial absorbers, intelligent switch, and optical sensors.

On-axis three-dimensional meta-holography enabled with continuous-amplitude modulation of light.

Conventional three-dimensional (3D) holography based on recording interference fringes on a photosensitive material usually has unavoidable zero-order light, which merges with the holographic image and blurs it. Off-axis design is an effective approach to avoid this problem; however, it in turn leads to the waste of at least half of the imaging space for holographic reconstruction. Herein, we propose an on-axis 3D holography based on Malus-assisted metasurfaces, which can eliminate the zero-order light and project the holographic image in the full transmission space. Specifically, each nanostructure in the metasurface acts as a nano-polarizer, which can modulate the polarization-assisted amplitude of incident light continuously, governed by Malus law. By carefully choosing the orientation angles of nano-polarizers, the amplitude can be both positive and negative, which can be employed to extinct zero-order light without affecting the intensity modulation for holographic recording. We experimentally demonstrate this concept by projecting an on-axis 3-layer holographic images in the imaging space and all experimental results agree well with our prediction. Our proposed metasurface carries unique characteristics such as ultracompactness, on-axis reconstruction, extinction of zero-order light and broadband response, which can find its market in ultracompact and high-density holographic recording for 3D objects.

Full-space metasurface holograms in the visible range.

Conventional metasurface holography is usually implemented in either transmission space or reflection space. Herein, we show a dielectric metasurface that can simultaneously project two independent holographic images in the transmission and reflection spaces, respectively, merely with a single-layer design approach. Specifically, two types of dielectric nanobricks in a nanostructured metasurface are employed to act as half-wave plates for geometric phase modulation. One type of nanobrick is designed to reflect most of incident circularly-polarized light into reflection space, enabled with magnetic resonance, while another type of nanobrick transmits it into transmission space, without resonance involved. By controlling the orientation angles and randomly interleaving the two types of nanobricks to form a metasurface, a full-space metasurface hologram can be established. We experimentally demonstrate this trans-reflective meta-holography by encoding the geometric phase information of two independent images into a single metasurface, and all observed holographic images agree well with our predictions. Our research expands the field-of-view of metasurface holography from half- to full-space, which can find its markets in optical sensing, image displays, optical storages and many other potential applications.

Non-orthogonal-polarization multiplexed metasurfaces for tri-channel gray-imaging.

Metasurface based polarization multiplexing is usually conducted in two orthogonal-polarization states, e.g., linearly polarized along x/y axes, left/right-handed circularly polarized states, etc. Herein, we show metasurfaces can be employed to implement tri-channel polarization multiplexing in three non-orthogonal-polarization states, merely with a single-size nanostructure design approach. Specifically, nanostructured metasurfaces acting as nano-polarizer arrays can modulate the incident light intensity pixel-by-pixel by controlling the orientation angles of nanostructures, governed by Malus's law. Hence, by inserting a metasurface between a bulk-optic polarizer and an analyzer, and elaborately controlling their polarization combinations, we show that the Malus-assisted metasurface can simultaneously record a continuous gray-image and two independent binary-patterns in three different information channels. We experimentally demonstrate this concept by recording three independent gray-images right at the metasurface surface. With the advantages of high information density, high security, high compatibility and ultracompactness, the proposed gray-imaging meta-device can play a significant role in the field of optical storage, anti-counterfeiting, and information multiplexing, etc.

Single-celled multifunctional metasurfaces merging structural-color nanoprinting and holography.

Nanostructured metasurfaces applied in structural-color nanoprinting and holography have been extensively investigated in the past several years. Recently, merging them together is becoming an emerging approach to improve the information capacity and functionality of metasurfaces. However, current approaches, e.g., segmenting, interleaving and stacking schemes for function merging, suffer from crosstalk, low information density, design and fabrication difficulties. Herein, we employ a single-celled approach to design and experimentally demonstrate a high-density multifunctional metasurface merging nanoprinting and holography, i.e., each nanostructure in the metasurface can simultaneously manipulate the spectra (enabled with varied dimensions of nanostructures) and geometric phase (enabled with varied orientation angles of nanostructures) of incident light. Hence, with different decoding strategies, a structural-color nanoprinting image emerges right at the metasurface plane under white light illumination, while a holographic image is reconstructed in the Fraunhofer diffraction zone under circularly polarized laser light incidence. And the two images have no crosstalk since they are independently designed and presented at different distances. Our proposal suggests a space-multiplexing scheme to develop advanced metasurfaces and one can find their markets in high-density information storage, optical information encryption, multi-channel image display, etc.

Structural-color nanoprinting with hidden watermarks.

Nanostructured metasurfaces can manipulate the spectrum and polarization of incident light at the nanoscale, which suggests a new integration of color nanoprints and polarizing-related components. Herein, we design and experimentally demonstrate a structural-color nanoprint carrying hidden watermarks, enabled with the polarization-assisted spectrum manipulation of light. Specifically, under unpolarized white light, the watermarks are concealed and a structural-color nanoprinting-image occupies the metasurface plane. Meanwhile, once linearly polarized white light is incident on the same metasurface, the hidden information can be decoded, and the same nanoprinting-image covered with watermarks appears. The proposed metasurface represents a paradigm for displaying color nanoprinting-images with or without watermarks, showing a flexible switch between the two operating modes and providing an easily camouflaged scheme for anticounterfeiting, encryption, information multiplexing, high-density optical storage, etc.

Learning for a Robot: Deep Reinforcement Learning, Imitation Learning, Transfer Learning.

Dexterous manipulation of the robot is an important part of realizing intelligence, but manipulators can only perform simple tasks such as sorting and packing in a structured environment. In view of the existing problem, this paper presents a state-of-the-art survey on an intelligent robot with the capability of autonomous deciding and learning. The paper first reviews the main achievements and research of the robot, which were mainly based on the breakthrough of automatic control and hardware in mechanics. With the evolution of artificial intelligence, many pieces of research have made further progresses in adaptive and robust control. The survey reveals that the latest research in deep learning and reinforcement learning has paved the way for highly complex tasks to be performed by robots. Furthermore, deep reinforcement learning, imitation learning, and transfer learning in robot control are discussed in detail. Finally, major achievements based on these methods are summarized and analyzed thoroughly, and future research challenges are proposed.

A Time Sequence Images Matching Method Based on the Siamese Network.

The similar analysis of time sequence images to achieve image matching is a foundation of tasks in dynamic environments, such as multi-object tracking and dynamic gesture recognition. Therefore, we propose a matching method of time sequence images based on the Siamese network. Inspired by comparative learning, two different comparative parts are designed and embedded in the network. The first part makes a comparison between the input image pairs to generate the correlation matrix. The second part compares the correlation matrix, which is the output of the first comparison part, with a template, in order to calculate the similarity. The improved loss function is used to constrain the image matching and similarity calculation. After experimental verification, we found that it not only performs better, but also has some ability to estimate the camera pose.

Multiplexed Anticounterfeiting Meta-image Displays with Single-Sized Nanostructures.

Metasurfaces have recently been used for multichannel image displays with pixel-size lower than a wavelength, which indicates the potential application in ultracompact anticounterfeiting with high-density and hidden information. However, current multichannel metasurfaces applied in anticounterfeiting are based on the sophisticated nanostructure design or at the cost of giving up some controls on the optical transmission matrix to encode multiple information channels. That is, the overall degrees of freedom offered by these metasurfaces are a "zero-sum game". Here, inspired by the orientation degeneracy indicated in Malus law, we propose a multiplexed anticounterfeiting metasurface consisting of single-sized nanostructures, which provide a new degree of freedom to increase the information capacity of anticounterfeiting without burdening the nanostructure design and fabrication. Specifically, the proposed metasurfaces can record a continuous grayscale image (channel 1) multiplexed with a totally/partially independent, interrelated, or watermarked anticounterfeiting pattern (channel 2). The two channels can be readily switched by polarization control. All experimental metasurface-images (meta-images) with high fidelity agree well with our design. With advantages such as ultracompactness, high-density information, multichannel displays, and strong concealment, the anticounterfeiting metasurfaces can empower advanced research and applications of metasurfaces in high-end optical anticounterfeiting and many other related fields.

An Interactive Image Segmentation Method in Hand Gesture Recognition.

In order to improve the recognition rate of hand gestures a new interactive image segmentation method for hand gesture recognition is presented, and popular methods, e.g., Graph cut, Random walker, Interactive image segmentation using geodesic star convexity, are studied in this article. The Gaussian Mixture Model was employed for image modelling and the iteration of Expectation Maximum algorithm learns the parameters of Gaussian Mixture Model. We apply a Gibbs random field to the image segmentation and minimize the Gibbs Energy using Min-cut theorem to find the optimal segmentation. The segmentation result of our method is tested on an image dataset and compared with other methods by estimating the region accuracy and boundary accuracy. Finally five kinds of hand gestures in different backgrounds are tested on our experimental platform, and the sparse representation algorithm is used, proving that the segmentation of hand gesture images helps to improve the recognition accuracy.

Simultaneous Calibration: A Joint Optimization Approach for Multiple Kinect and External Cameras.

Camera calibration is a crucial problem in many applications, such as 3D reconstruction, structure from motion, object tracking and face alignment. Numerous methods have been proposed to solve the above problem with good performance in the last few decades. However, few methods are targeted at joint calibration of multi-sensors (more than four devices), which normally is a practical issue in the real-time systems. In this paper, we propose a novel method and a corresponding workflow framework to simultaneously calibrate relative poses of a Kinect and three external cameras. By optimizing the final cost function and adding corresponding weights to the external cameras in different locations, an effective joint calibration of multiple devices is constructed. Furthermore, the method is tested in a practical platform, and experiment results show that the proposed joint calibration method can achieve a satisfactory performance in a project real-time system and its accuracy is higher than the manufacturer's calibration.

The Effect of Height Error on Performance of Propagation Phase-Based Metalens.

Metalenses, as a new type of planar optical device with flexible design, play an important role in miniaturized and integrated optical devices. Propagation phase-based metalenses, known for their low loss and extensive design flexibility, are widely utilized in optical imaging and optical communication. However, fabrication errors introduced by thin-film deposition and etching processes inevitably result in variations in the height of the metalens structure, leading to the fabricated devices not performing as expected. Here, we introduce a reflective TiO2 metalens based on the propagation phase. Then, the relationship between the height variation and the performance of the metalens is explored by using the maximum phase error. Our results reveal that the height error of the unit structure affects the phase rather than the amplitude. The focusing efficiency of our metalens exhibits robustness to structural variations, with only a 5% decrease in focusing efficiency when the height varies within ±8% of the range. The contents discussed in this paper provide theoretical guidance for the unit design of the propagation phase-based metalens and the determination of its allowable fabrication error range, which is of great significance for low-cost and high-efficiency manufacturing.

Simultaneous Passivation of Perovskite Interfaces at Multiple Active Sites Improves Device Performance: Combining Theory and Experiment.

A multisite interface passivation material named 2-mercapto-4-methyl-5-thiazoleacetic acid (MMTA) is used to optimize the perovskite film top interface. DFT calculations and experiments show that MMTA can effectively passivate interface defects. Finally, the champion device's photoelectric conversion efficiency reached 23.44%, which possessed long-term stability.

Grasping detection of dual manipulators based on Markov decision process with neural network.

With the development of artificial intelligence, robots are widely used in various fields, grasping detection has been the focus of intelligent robot research. A dual manipulator grasping detection model based on Markov decision process is proposed to realize the stable grasping with complex multiple objects in this paper. Based on the principle of Markov decision process, the cross entropy convolutional neural network and full convolutional neural network are used to parameterize the grasping detection model of dual manipulators which are two-finger manipulator and vacuum sucker manipulator for multi-objective unknown objects. The data set generated in the simulated environment is used to train the two grasping detection networks. By comparing the grasping quality of the detection network output the best grasping by the two grasping methods, the network with better detection effect corresponding to the two grasping methods of two-finger and vacuum sucker is determined, and the dual manipulator grasping detection model is constructed in this paper. Robot grasping experiments are carried out, and the experimental results show that the proposed dual manipulator grasping detection method achieves 90.6% success rate, which is much higher than the other groups of experiments. The feasibility and superiority of the dual manipulator grasping detection method based on Markov decision process are verified.

Global and local feature extraction based on convolutional neural network residual learning for MR image denoising.

Objective.Given the different noise distribution information of global and local magnetic resonance (MR) images, this study aims to extend the current work on convolutional neural networks that preserve global structure and local details in MR image denoising tasks.Approach.This study proposed a parallel and serial network for denoising 3D MR images, called 3D-PSNet. We use the residual depthwise separable convolution block to learn the local information of the feature map, reduce the network parameters, and thus improve the training speed and parameter efficiency. In addition, we consider the feature extraction of the global image and utilize residual dilated convolution to process the feature map to expand the receptive field of the network and avoid the loss of global information. Finally, we combine both of them to form a parallel network. What's more, we integrate reinforced residual convolution blocks with dense connections to form serial network branches, which can remove redundant information and refine features to further obtain accurate noise information.Main results.The peak signal-to-noise ratio, structural similarity index measure, and root mean square error metrics of 3D-PSNet are as high as 47.79%, 99.81%, and 0.40%, respectively, achieving competitive denoising effect on three public datasets. The ablation experiments demonstrated the effectiveness of all the designed modules regarding all the evaluated metrics in both datasets.Significance.The proposed 3D-PSNet takes advantage of multi-scale receptive fields, local feature extraction and residual dense connections to more effectively restore the global structure and local fine features in MR images, and is expected to help doctors quickly and accurately diagnose patients' conditions.

Tunable bandwidth terahertz perfect absorption device based on vanadium dioxide phase transition control.

Utilizing the phase transition principle of VO2, this paper presents a tunable ultra-wideband terahertz perfect absorption device with simple structure and tunability. The proposed broadband terahertz perfect absorption device is a three-layer structure with a metal reflective layer, a silicon dioxide dielectric layer and a VO2 layer from bottom to top. It was found that the terahertz perfect absorption device's absorption could be dynamically adjusted from 1.2% to 99.9% when changing from an insulated to a metallic state. With the VO2 in the metallic state, the terahertz perfect absorption device has an absorption efficiency of more than 90% in 4.00 to 10.08 THz's ultra-broadband range and near-perfect absorption is achieved in the ranges of 4.71 THz to 5.16 THz and 7.74 THz to 8.06 THz. To explain the working principle of this terahertz perfect absorption device, this paper utilizes wave interference's principle, theory of impedance matching and electric field analysis. Compared to previously reported terahertz metamaterial devices, the vanadium dioxide device proposed in this paper is significantly optimized in terms of tunable range and absorption bandwidth. In addition, the terahertz perfect absorption device is polarization insensitive and maintains good absorptivity over a wide-angle incidence range. This tunable ultra-wideband terahertz perfect absorption device could have applications in the fields of modulation, stealth devices, and thermal emission devices.

Multi-view fusion network-based gesture recognition using sEMG data.

sEMG(surface electromyography) signals have been widely used in rehabilitation medicine in the past decades because of their non-invasive, convenient and informative features, especially in human action recognition, which has developed rapidly. However, the research on sparse EMG in multi-view fusion has made less progress compared to high-density EMG signals, and for the problem of how to enrich sparse EMG feature information, a method that can effectively reduce the information loss of feature signals in the channel dimension is needed. In this paper, a novel IMSE (Inception-MaxPooling-Squeeze- Excitation) network module is proposed to reduce the loss of feature information during deep learning. Then, multiple feature encoders are constructed to enrich the information of sparse sEMG feature maps based on the multi-core parallel processing method in multi-view fusion networks, while SwT (Swin Transformer) is used as the classification backbone network. By comparing the feature fusion effects of different decision layers of the multi-view fusion network, it is experimentally obtained that the fusion of decision layers can better improve the classification performance of the network. In NinaPro DB1, the proposed network achieves 93.96% average accuracy in gesture action classification with the feature maps obtained in 300ms time window, and the maximum variation range of action recognition rate of individuals is less than 11.2%. The results show that the proposed framework of multi-view learning plays a good role in reducing individuality differences and augmenting channel feature information, which provides a certain reference for non-dense biosignal pattern recognition.

Ultra-Wideband High-Efficiency Solar Absorber and Thermal Emitter Based on Semiconductor InAs Microstructures.

Since the use of chemical fuels is permanently damaging the environment, the need for new energy sources is urgent for mankind. Given that solar energy is a clean and sustainable energy source, this study investigates and proposes a six-layer composite ultra-wideband high-efficiency solar absorber with an annular microstructure. It achieves this by using a combination of the properties of metamaterials and the quantum confinement effects of semiconductor materials. The substrate is W-Ti-Al2O3, and the microstructure is an annular InAs-square InAs film-Ti film combination. We used Lumerical Solutions' FDTD solution program to simulate the absorber and calculate the model's absorption, field distribution, and thermal radiation efficiency (when it is used as a thermal emitter), and further explored the physical mechanism of the model's ultra-broadband absorption. Our model has an average absorption of 95.80% in the 283-3615 nm band, 95.66% in the 280-4000 nm band, and a weighted average absorption efficiency of 95.78% under AM1.5 illumination. Meanwhile, the reflectance of the model in the 5586-20,000 nm band is all higher than 80%, with an average reflectance of 94.52%, which has a good thermal infrared suppression performance. It is 95.42% under thermal radiation at 1000 K. It has outstanding performance when employed as a thermal emitter as well. Additionally, simulation results show that the absorber has good polarization and incidence angle insensitivity. The model may be applied to photodetection, thermophotovoltaics, bio-detection, imaging, thermal ion emission, and solar water evaporation for water purification.