Design and Fabrication of Biomass Derived Black Carbon Modified g-C3N4/FeIn2S4 Heterojunction as Highly Efficient Photocatalyst for Wastewater Treatment.

The environmental deterioration caused by dye wastewater discharge has received considerable attention in recent decades. One of the most promising approaches to addressing the aforementioned environmental issue is the development of photocatalysts with high solar energy consumption efficiency for the treatment of dye-contaminated water. In this study, a novel low-cost π-π biomass-derived black carbon modified g-C3N4 coupled FeIn2S4 composite (i.e., FeInS/BC-CN) photocatalyst is successfully designed and fabricated that reveals significantly improved photocatalytic performance for the degradation of Eosin Yellow (EY) dye in aqueous solution. Under dark and subsequent visible light irradiation, the amount optimized composite reveals 99% removal performance for EY dye, almost three-fold compared to that of the pristine FeInS and BC-CN counterparts. Further, it is confirmed by means of the electron spin resonance spectrometry, quenching experiments, and density functional theory (DFT) calculations, that the hydroxyl radicals (•OH) and superoxide radicals (•O2 -) are the dominant oxidation species involved in the degradation process of EY dye. In addition, a systematic photocatalytic degradation route is proposed based on the resultant degradation intermediates detectedduring liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis. This work provides an innovative idea for the development of advanced photocatalysts to mitigate water pollution.

Research on Multi-Object Sorting System Based on Deep Learning.

As a complex task, robot sorting has become a research hotspot. In order to enable robots to perform simple, efficient, stable and accurate sorting operations for stacked multi-objects in unstructured scenes, a robot multi-object sorting system is built in this paper. Firstly, the training model of rotating target detection is constructed, and the placement state of five common objects in unstructured scenes is collected as the training set for training. The trained model is used to obtain the position, rotation angle and category of the target object. Then, the instance segmentation model is constructed, and the same data set is made, and the instance segmentation network model is trained. Then, the optimized Mask R-CNN instance segmentation network is used to segment the object surface pixels, and the upper surface point cloud is extracted to calculate the normal vector. Then, the angle obtained by the normal vector of the upper surface and the rotation target detection network is fused with the normal vector to obtain the attitude of the object. At the same time, the grasping order is calculated according to the average depth of the surface. Finally, after the obtained object posture, category and grasping sequence are fused, the performance of the rotating target detection network, the instance segmentation network and the robot sorting system are tested on the established experimental platform. Based on this system, this paper carried out an experiment on the success rate of object capture in a single network and an integrated network. The experimental results show that the multi-object sorting system based on deep learning proposed in this paper can sort stacked objects efficiently, accurately and stably in unstructured scenes.

Optical bistability in gap-plasmon metasurfaces in consideration of classical nonlocal effects.

Optical bistability of linear reflectance and third-harmonic generation is investigated in a metasurface consisting of metallic grating coupled with metallic film spaced with nonlinear dielectric material. Linear optical reflectance and electric field enhancement are achieved for gaps <20 nm in the presence of classical nonlocality in metallic nanostructures. Enlarged thresholds from the higher to lower reflectance states are observed from 140 kW/cm2 for the local model to 300 kW/cm2 for the nonlocal model for 0.5-nm gaps. Though the linear reflectance almost overlaps for local and nonlocal models for 20-nm gaps, the optical bistability hysteresis loops retain large differences because local field differences are amplified owing to the relation of nonlinear refraction with square of local field and historical evolution of the optical bistability.

Tunable photonic-like modes in graphene-coated nanowires.

In this study, the dispersion equations of a graphene-coated nanowire (GN) are solved. It is found that in this waveguide, besides the surface plasmon polaritons (SPPs), there is another branch of guided modes, called photonic-like modes. The propagation distances of the photonic-like modes can be five orders of magnitude longer than those of the SPPs. Moreover, they can be modulated in the range of 10-4 to 1 m by changing the chemical potential of graphene. In particular, the mode field distributions remain nearly unchanged during the modulation. Based on the analysis performed using COMSOL Multiphysics, we further demonstrated that the propagation losses of the photonic-like modes are dependent on not only the chemical potential of graphene, but also the mode power proportion inside graphene. The photonic-like modes have tremendous potential to be used in optical switches, modulators, and switches in magnetic fields at the nanoscale.

Graphene-coated nanowires with a drop-shaped cross section for 10 nm confinement and 1 mm propagation.

Strong confinement and long-range propagation of electromagnetic energy are longed for when designing efficient miniaturized photonic devices. Here, a graphene-coated nanowire with a drop-shaped cross section is proposed for guiding graphene surface plasmon polaritons to demonstrate an extremely long propagation length (1 mm) with ultra-strong mode confinement (10 nm), which results from the distinctive mode field distribution caused by both the top and bottom arcs of the waveguide. The combination of nanoconcentration and long-range propagation makes the waveguide very useful in nanophotonics, bio-photonics, and highly integrated photonic circuits.

Thin-wall tubes for coupling terahertz waves to metal wires.

Bare metal wires are among the most promising waveguides for guiding terahertz (THz) surface plasmon polaritons. In this study, a thin-wall tube is proposed for coupling THz waves to a metal wire with ultrahigh efficiency, which results from three high mode matchings for the two waveguides: field distributions, polarization directions, and wave vectors. According to the mode-overlap calculation, the coupling efficiency can be always between 84% and 94% when the frequency of THz waves is in the range of 0.2-3 THz and the metal wire radius is 0.5 mm. The maximum efficiency is as high as 94% at 0.5 THz, which is much higher than that obtained by the previous methods. We further conclude that the optimal coupling efficiency can be obtained when the outer tube radius is equal to the wire radius and simultaneously the real propagation constants of modes in the two waveguides are the same.

Drivers' Visual Behavior-Guided RRT Motion Planner for Autonomous On-Road Driving.

This paper describes a real-time motion planner based on the drivers' visual behavior-guided rapidly exploring random tree (RRT) approach, which is applicable to on-road driving of autonomous vehicles. The primary novelty is in the use of the guidance of drivers' visual search behavior in the framework of RRT motion planner. RRT is an incremental sampling-based method that is widely used to solve the robotic motion planning problems. However, RRT is often unreliable in a number of practical applications such as autonomous vehicles used for on-road driving because of the unnatural trajectory, useless sampling, and slow exploration. To address these problems, we present an interesting RRT algorithm that introduces an effective guided sampling strategy based on the drivers' visual search behavior on road and a continuous-curvature smooth method based on B-spline. The proposed algorithm is implemented on a real autonomous vehicle and verified against several different traffic scenarios. A large number of the experimental results demonstrate that our algorithm is feasible and efficient for on-road autonomous driving. Furthermore, the comparative test and statistical analyses illustrate that its excellent performance is superior to other previous algorithms.

THz wave in double-metal-film waveguides and the application of wavelength analysis.

We propose the double-metal-film waveguides for terahertz (THz) wave guiding. The loss and field features are analyzed. In the application of wavelength analysis, the formula of the wavelength has been derived, and it can be used to analyze the wavelength of the THz sources according to mode field distribution in the dielectric-substrate slab. The penetrating capability of the THz wave is also discussed for different structures. When there is more energy in the dielectric-substrate slab, it will be better for wavelength analysis.

Terahertz wave transmission within metal-clad antiresonant reflecting hollow waveguides.

We present the transmission characteristics of THz waves in metal-clad antiresonant reflecting hollow waveguides. We have derived the equation for the blueshift of the resonance frequency. The effects of the waveguide structure on the blueshift of the resonance frequency are studied comprehensively. In particular, we find that the blueshift of the resonance frequency is strongly affected by the interval between two dielectric slabs. By changing the interval, we find that the maximum frequency-tuning range is up to 2030 GHz and the maximum sensitivity of the resonance frequency shift is up to 6950 GHz/mm at the resonance order of m=1. When the THz wave is at the near-zero loss frequency, both the loss and the dispersion of the guide modes are very low.

A Framework for Applying Point Clouds Grabbed by Multi-Beam LIDAR in Perceiving the Driving Environment.

The quick and accurate understanding of the ambient environment, which is composed of road curbs, vehicles, pedestrians, etc., is critical for developing intelligent vehicles. The road elements included in this work are road curbs and dynamic road obstacles that directly affect the drivable area. A framework for the online modeling of the driving environment using a multi-beam LIDAR, i.e., a Velodyne HDL-64E LIDAR, which describes the 3D environment in the form of a point cloud, is reported in this article. First, ground segmentation is performed via multi-feature extraction of the raw data grabbed by the Velodyne LIDAR to satisfy the requirement of online environment modeling. Curbs and dynamic road obstacles are detected and tracked in different manners. Curves are fitted for curb points, and points are clustered into bundles whose form and kinematics parameters are calculated. The Kalman filter is used to track dynamic obstacles, whereas the snake model is employed for curbs. Results indicate that the proposed framework is robust under various environments and satisfies the requirements for online processing.

Broadband terahertz transmission within the symmetrical plastic film coated parallel-plate waveguide.

We report on the broadband terahertz (THz) transmission within a symmetrical plastic film coated parallel-plate waveguide. We theoretically study the antiresonant reflecting mechanism of the waveguide, and we find that the broadband THz wave can transmit in this waveguide with ultralow loss. The loss of the TM mode in this waveguide can be 4 orders of magnitude lower than the uncoated parallel-plate waveguide. The transmission bandwidth of this waveguide is up to 5.12 THz. We further show the mode field distributions which explain the loss mechanism.

Motion planning for autonomous vehicle based on radial basis function neural network in unstructured environment.

The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the requirement of real-time planning, and the nonholonomic constraints of vehicle. This paper presents a motion planning method, based on the Radial Basis Function (RBF) neural network, to guide the autonomous vehicle in unstructured environments. The proposed algorithm extracts the drivable region from the perception grid map based on the global path, which is available in the road network. The sample points are randomly selected in the drivable region, and a gradient descent method is used to train the RBF network. The parameters of the motion-planning algorithm are verified through the simulation and experiment. It is observed that the proposed approach produces a flexible, smooth, and safe path that can fit any road shape. The method is implemented on autonomous vehicle and verified against many outdoor scenes; furthermore, a comparison of proposed method with the existing well-known Rapidly-exploring Random Tree (RRT) method is presented. The experimental results show that the proposed method is highly effective in planning the vehicle path and offers better motion quality.

A bionic camera-based polarization navigation sensor.

Navigation and positioning technology is closely related to our routine life activities, from travel to aerospace. Recently it has been found that Cataglyphis (a kind of desert ant) is able to detect the polarization direction of skylight and navigate according to this information. This paper presents a real-time bionic camera-based polarization navigation sensor. This sensor has two work modes: one is a single-point measurement mode and the other is a multi-point measurement mode. An indoor calibration experiment of the sensor has been done under a beam of standard polarized light. The experiment results show that after noise reduction the accuracy of the sensor can reach up to 0.3256°. It is also compared with GPS and INS (Inertial Navigation System) in the single-point measurement mode through an outdoor experiment. Through time compensation and location compensation, the sensor can be a useful alternative to GPS and INS. In addition, the sensor also can measure the polarization distribution pattern when it works in multi-point measurement mode.

Optically Controlling Broadband Terahertz Modulator Based on Layer-Dependent PtSe2 Nanofilms.

In this paper, we propose an optically controlling broadband terahertz modulator of a layer-dependent PtSe2 nanofilm based on a high-resistance silicon substrate. Through optical pump and terahertz probe system, the results show that compared with 6-, 10-, and 20-layer films, a 3-layer PtSe2 nanofilm has better surface photoconductivity in the terahertz band and has a higher plasma frequency ωp of 0.23 THz and a lower scattering time τs of 70 fs by Drude-Smith fitting. By the terahertz time-domain spectroscopy system, the broadband amplitude modulation of a 3-layer PtSe2 film in the range of 0.1-1.6 THz was obtained, and the modulation depth reached 50.9% at a pump density of 2.5 W/cm2. This work proves that PtSe2 nanofilm devices are suitable for terahertz modulators.

Progress on two-dimensional binary oxide materials.

Two-dimensional van der Waals (2D vdW) materials have attracted much attention because of their unique electronic and optical properties. Since the successful isolation of graphene in 2004, many interesting 2D materials have emerged, including elemental olefins (silicene, germanene, etc.), transition metal chalcogenides, transition metal carbides (nitrides), hexagonal boron, etc. On the other hand, 2D binary oxide materials are an important group in the 2D family owing to their high structural diversity, low cost, high stability, and strong adjustability. This review systematically summarizes the research progress on 2D binary oxide materials. We discuss their composition and structure in terms of vdW and non-vdW categories in detail, followed by a discussion of their synthesis methods. In particular, we focus on strategies to tailor the properties of 2D oxides and their emerging applications in different fields. Finally, the challenges and future developments of 2D binary oxides are provided.

Oxygen Vacancy Engineering of MOF-Derived Zn-Doped Co3O4 Nanopolyhedrons for Enhanced Electrochemical Nitrogen Fixation.

Introducing oxygen vacancy (Vo) has been considered as an effective and significant method to accelerate the sluggish electrocatalytic nitrogen reduction reaction (NRR). In this work, a series of bimetallic zeolitic imidazolate frameworks based on ZIF-67 and ZIF-8 with varied ratios of Co/Zn have been applied as precursors to prepare Vo-rich Zn-doped Co3O4 nanopolyhedrons (Zn-Co3O4) by a low-temperature oxidation strategy. Zn-Co3O4 presents an ammonia yield of 22.71 µg h-1 mgcat.-1 with a high faradaic efficiency of 11.9% for NRR under ambient conditions. The remarkable catalytic performances are believed to result from the plentiful Vo as the Lewis acid sites and electron-rich Co sites to promote the adsorption and dissociation of N2 molecules. Remarkably, Zn-Co3O4 also demonstrates a high electrochemical stability. This work presents a guiding method for developing a stable and efficient electrocatalyst for the NRR.

γ-CuI from ionic liquid/poly(ionic liquid)s precursors with controllable morphologies and improved photocatalytic performance.

γ-phase copper(I) iodide (abbreviated to CuI hereafter) with different morphologies is realized through a one-step redox process from I-containing ionic liquid (IL) or poly(ionic liquid)s (PILs) precursors at room temperature. The phase composition, morphology, and electronic states of the synthesized CuI samples are characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS). The resulting CuI products exhibit three different types of morphologies, namely nanocrystals, with an average size of 0.8 ± 0.2 µm, nanoplates, with a thickness of 35.8 ± 0.9 nm, and nanoflowers, with petals with a thickness of 12.2 ± 0.8 nm. Moreover, the as-synthesized CuI samples exhibit gradually diminishing bandgaps and improved photocatalysis performance for the photodegradation of rhodamine B (RhB) under visible light irradiation as the thickness decreases. XPS measurements confirm that IL/PILs coupled to the CuI surface, resulting in a further charge transfer between Cu and I. These results conclusively prove that IL/PILs serve as both the reducing agents and assemble as orientation templates in the formation of the CuI nanostructures, and also successfully mediate the functional properties of the samples by changing the surface electronic structures.

Graphene Nanoribbon Gap Waveguides for Dispersionless and Low-Loss Propagation with Deep-Subwavelength Confinement.

Surface plasmon polaritons (SPPs) have been attracting considerable attention owing to their unique capabilities of manipulating light. However, the intractable dispersion and high loss are two major obstacles for attaining high-performance plasmonic devices. Here, a graphene nanoribbon gap waveguide (GNRGW) is proposed for guiding dispersionless gap SPPs (GSPPs) with deep-subwavelength confinement and low loss. An analytical model is developed to analyze the GSPPs, in which a reflection phase shift is employed to successfully deal with the influence caused by the boundaries of the graphene nanoribbon (GNR). It is demonstrated that a pulse with a 4 µm bandwidth and a 10 nm mode width can propagate in the linear passive system without waveform distortion, which is very robust against the shape change of the GNR. The decrease in the pulse amplitude is only 10% for a propagation distance of 1 µm. Furthermore, an array consisting of several GNRGWs is employed as a multichannel optical switch. When the separation is larger than 40 nm, each channel can be controlled independently by tuning the chemical potential of the corresponding GNR. The proposed GNRGW may raise great interest in studying dispersionless and low-loss nanophotonic devices, with potential applications in the distortionless transmission of nanoscale signals, electro-optic nanocircuits, and high-density on-chip communications.

Broadband and Ultra-Low Threshold Optical Bistability in Guided-Mode Resonance Grating Nanostructures of Quasi-Bound States in the Continuum.

We model optical bistability in all-dielectric guide-mode resonance grating (GMR) nanostructures working at quasi-bound states in the continuum (BICs). The complementary metal-oxide-semiconductor (CMOS) compatible material silicon nitride (SiN) is used for the design of nanostructures and simulations. The ultra-low threshold of input intensity in the feasible nanostructure for nanofabrication is obtained at the level of ~100 W/cm2 driven by quasi-BICs. Additionally, the resonance wavelength in the GMR nanostructure can be widely tuned by incident angles with the slightly changed Q-factor that enables the optical bistable devices to work efficiently over a wide spectrum. The impact of the defects of grating that may be introduced in the fabrication process on the optical properties is discussed, and the tolerance of the defects to the optical performance of the device is confirmed. The results indicate that the GMR nanostructures of broadband and ultra-low threshold optical bistability driven by quasi-BICs are promising in the application of all-optical devices.

Graphene Plasmon Resonances for Electrically-Tunable Sub-Femtometer Dimensional Resolution.

A coupled graphene structure (CGS) is proposed to obtain an electrically tunable sub-femtometer (sub-fm) dimensional resolution. According to analytical and numerical investigations, the CGS can support two branches of localized surface plasmon resonances (LSPRs), which park at the dielectric spacer between two pieces of graphene. The coupled efficiencies of the odd-order modes are even four orders of magnitude higher than that of the even-order modes. In particular, a sub-fm resolution for detecting the change in the spacer thickness can be reached using the lowest order LSPR mode. The LSPR wavelength and the dimensional differential resolution can be electrically-tuned from 9.5 to 33 µm and from 4.3 to 15 nm/pm, respectively, by modifying the chemical potential of the graphene via the gate voltage. Furthermore, by replacing the graphene ribbon (GR) at the top of the CGS with multiple GRs of different widths, a resonant frequency comb in the absorption spectrum with a tunable frequency interval is generated, which can be used to detect the changes in spacer thicknesses at different locations with sub-fm resolution.