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One-dimensional nanobelt with inner nanopores has been considered as an ideal electrode material for electric energy storage. Herein iron manganese trioxide (FeMnO3) nanobelts have been prepared by a facile solvothermal approach. The phase, composition, structure and morphology of the as-synthesized sample are characterized by several techniques. Benefiting from the unique structure, the as-prepared FeMnO3 nanobelts achieve a superior lithium storage capacity with 635.7 mAh g−1 after 200 cycles, excellent cyclability and good kinetic properties, as well as a high specific capacitance of 209 F g−1 after 2000 cycles for supercapacitor. These results show a great application in large-scale energy storage.

Mesoporous WS

Metasurfaces provide a new approach for planar optics and thus have realized multifunctional meta-devices with different multiplexing strategies, among which polarization multiplexing has received much attention due to its convenience. At present, a variety of design methods of polarization multiplexed metasurfaces have been developed based on different meta-atoms. However, as the number of polarization states increases, the response space of meta-atoms becomes more and more complex, and it is difficult for these methods to explore the limit of polarization multiplexing. Deep learning is one of the important routes to solve this problem because it can realize the effective exploration of huge data space. In this work, a design scheme for polarization multiplexed metasurfaces based on deep learning is proposed. The scheme uses a conditional variational autoencoder as an inverse network to generate structural designs and combines a forward network that can predict meta-atoms’ responses to improve the accuracy of designs. The cross-shaped structure is used to establish a complicated response space containing different polarization state combinations of incident and outgoing light. The multiplexing effects of the combinations with different numbers of polarization states are tested by utilizing the proposed scheme to design nanoprinting and holographic images. The polarization multiplexing capability limit of four channels (a nanoprinting image and three holographic images) is determined. The proposed scheme lays the foundation for exploring the limits of metasurface polarization multiplexing capability.

The efficient synthesis of quantum materials is becoming a research hotspot as it determines their successful application in the fields of biomedicine, illumination, energy, sensors, information, and communication. Among the quantum materials, it is still a challenge to synthesize quantum wires (QWs) with surfactants due to the inevitable radial growth of QWs in the soft template method. In this paper, amphipathic graphene oxide (GO) was adopted as a macromolecular surfactant to limit the radial growth instead of the commonly used surfactant. GO could roll up under its electrostatic interaction with a cuprous oxide (Cu2O) quantum dot (QD) and then form a tubular template for the growth of the Cu2O QW, which was named herein as the nanoparticle-induced graphene oxide rolling (NIGOR) procedure. The NIGOR procedure was confirmed by the molecular dynamics results by simulating systems consisting of GO and Cu2O nanoparticles. An intermediate with a necklace morphology corresponding to the simulation result was also observed experimentally during the formation of the QW. Meanwhile, the formation mechanism of the QW was demonstrated rationally. Furthermore, increasing the dosage of the reactant, reaction time, and temperature altered the diameter of the QW from 2 to 4 nm and also changed the morphology of the final products from a QD to a QW and then to a bundle of QWs. This was attributed to the aggregation of materials for the lowest surface energy in the system. Additionally, the universality of NIGOR was manifested via the synthesis of other metal oxides as well. The NIGOR strategy provided an alternative, convenient, and mass production method for synthesizing QWs.

Chemiresistive gas sensors have been extensively explored for hazardous gas detection. Currently, an overwheming majority of previous attention was focused on the parameter improvement of sensor performance while the impact of carrier gas species on the performance was severely ignored. Aiming to a deep insight into this issue, in this work we prepared zinc oxide (ZnO) nanowire-network sensor and explored its UV-activated sensing performance toward trace nitrogen dioxide gas (NO2) at room temperature (25 °C) under two carrier gases, i.e., dry nitrogen (N2) and air. Within N2, the sensor exhibited a reversible response of 157 toward 50 ppb NO2 and a sensitivity of 7.8/ppb, which was not only among the best showcases of the existing work, but much larger than those within air (11 and 0.091/ppb, respectively). Moreover, decent selectivity and long-term stability were demonstrated. Far more UV irradiation-induced electrons which reacted with adsorbed NO2 molecules on ZnO surface as well as smaller baseline resistance under N2 than those under air jointly led to the superior response and sensitivity. After long-time UV exposure prior to gas-sensing tests within both carrier gas cases, the remaining oxygen ions (O2−) were weakly bonded on ZnO surface, contributing to the reversible behaviors at room temperature. The interconversion between physisorbed O2 molecules and ionic O2− on ZnO surface was proposed to rationalize the sensing phenomena especially when no continuous oxygen was supplied under N2 atmosphere, which enriched the current transduction mechanisms.

Hydrogen sulfide (H2S) is a colorless gas with a smell of rotten eggs which poses great threat on human health and environmental protection. Traditional metal oxide based H2S sensors always suffer from undesirable selectivity and elevated operation temperature. To overcome these obstacles, in this report cuprous oxide nanowires/nanoparticles (Cu2O) anchored onto reduced graphene oxide nanosheets (rGO) were prepared to serve as the sensing layer. Multiple characterization techniques such as SEM, TEM, FTIR, and XRD were utilized to explore the sensor performance toward H2S gas. Compared to the partial recovery at 25 °C, the prepared rGO/Cu2O sensor showed a response of 20% toward 1 ppm H2S at 40 °C, together with full restoration, excellent repeatability, long-term stability and selectivity. Favorable film porosity, highly conductive rGO nanosheets and nanometer size effect of Cu2O materials were responsible for these inspiring results, paving the avenue for future trace H2S detection in the aspects of higher sensitivity and lower power-consumption.

The efficient synthesis of quantum materials is becoming a research hotspot as it determines their successful application in the fields of biomedicine, illumination, energy, sensors, information, and communication. Among the quantum materials, it is still a challenge to synthesize quantum wires (QWs) with surfactants due to the inevitable radial growth of QWs in the soft template method. In this paper, amphipathic graphene oxide (GO) was adopted as a macromolecular surfactant to limit the radial growth instead of the commonly used surfactant. GO could roll up under its electrostatic interaction with a cuprous oxide (Cu

This paper considers the secrecy outage performance of a multiple-relay assisted non-orthogonal multiple access (NOMA) network over Nakagami- $m$ fading channels. Two time slots are utilized to transmit signals from the base station to destination. At the first time slot, the base station broadcasts the superposition signal of the two users to all decode-and-forward relays by message mapping strategy. Subsequently, the selected relay transmits superposition signal to the two users via power-domain NOMA technology. Three relay selection schemes, i.e., optimal single relay selection (OSRS) scheme, two-step single relay selection (TSRS) scheme, and optimal dual relay selection (ODRS) scheme are proposed and the secrecy outage performance is analyzed. As a benchmark, we also examine the secrecy outage performance of the NOMA systems with traditional multiple relay forwarding (TMRF) scheme in which all the relay that successfully decode signals from the source forward signals to the NOMA users with equal power. Considering the correlation between the secrecy capacity of two users and different secrecy requirement for two NOMA users, the analytical expressions for the security outage probability (SOP) of the proposed OSRS, TSRS, and ODRS schemes along with the TMRF scheme are derived and validated via simulations. To get more insights, we also derive the analytical expressions for the asymptotic SOP for all the schemes with fixed and dynamic power allocations. Furthermore, the secrecy diversity order (SDO) and secrecy array gain of cooperative NOMA systems are obtained. The results demonstrate that our proposed schemes can significantly enhance the secrecy performance compared to the TMRF scheme and that all the schemes with fixed power allocation obtain zero SDO and the OSRS scheme with dynamic power allocation obtains the same SDO as TMRF.

In order to address the parameter estimation problem of pulse coupled neural network (PCNN) in the infrared human segmentation, this paper proposes an improved search method of optimal parameters. First, based on a simple PCNN model, the cuckoo search (CS) algorithm, instead of the existing swarm intelligent methods, is introduced to deal with this multi-parameter optimization problem. Next, the Kent chaotic map is applied to the local search process of CS algorithm, so as to enhance search precision. Furthermore, to cope with the search blindness, a guidance mechanism by the k dimensional-tree (KD-Tree) is presented to accelerate the convergence speed of parameter search based on the current search history. The proposed method is applied to a set of benchmark test functions and a series of infrared human segmentation experiments, and the experimental results demonstrate that the simple PCNN Model with this proposed parameter optimization method is superior to other PCNN segmentation models with existing swarm intelligent optimization algorithms both in the visual segmentation effect and the objective quantitative evaluations of accuracy and computing speed.

A vision inspection system is developed for detecting surface damages on cables in long-span cable-stayed bridges. The system consists of a climbing robot, an image processing platform, and 4 fixed cameras. While the climbing robot loads the whole system and ascends along the cables, 4 cameras can continuously acquire cable surface images. Then, image processing techniques can be employed to achieve defect identification. In our optical system, a single image may only collect a part of the whole defect because of the field of view (FOV) of each camera. In order to obtain the morphology of the whole defect, we present an efficient scale-invariant feature transform (SIFT) algorithm to achieve the multi-image mosaic with partially overlapped regions in different defect images. Experimental results demonstrate that the proposed vision inspection technologies are suitable for application to the bridge cables for defect detection and condition assessment.

Visible-infrared compatible camouflage is significant to enhance the equipment survivability through counteracting the modern detecting and surveillance systems. However, there are still great challenges in simultaneously achieving multispectral camouflage with high transmittance in visible, low emissivity in the atmospheric windows and high emissivity in the non-atmospheric window, which can be attributed to the mutual influence and restriction within these characteristics. Here, we proposed an optically transparent infrared selective emitter (OTISE) composed of three Ag-ZnO-Ag disk sub-cells with anti-reflection layers, which can synchronously improve the visible transmittance and widen absorption bandwidth in the non-atmospheric window by enhancing and merging resonance response of multi-resonators. Test results reveal that low emissivity in infrared atmospheric windows, high emissivity in the 5-8 µm non-atmospheric window and high optical transparency have been obtained. In addition, the radiative flux of OTISE in 3-5 µm and 8-14 µm are respectively 34.2% and 9.3% of that of blackbody and the energy dissipation of OTISE is 117% of that of chromium film. Meanwhile, it keeps good optical transparency due to the ultrathin Ag film. This work provides a novel strategy to design the optically transparent selective emissive materials, implying a promising application potential in visible and infrared camouflage technology.

Surmounting the issues of high-sensitivity and room-temperature detection toward trace NO2 gas is of paramount importance in the fields of human health and ultralow emission. Recently, black phosphorus (BP), a novel two-dimensional material, has gained considerable interest to achieve this goal. However, related work is far from satisfactory due to sluggish response, insufficient recovery, and fragile stability. In this scenario, we report on an inspiring NO2 sensor featuring composite film of few-layer BP nanosheets and zinc oxide (ZnO) nanowires serving as the sensing layer. Compared with BP-only counterpart, BP-ZnO sensor exhibited enhanced performance including boosted response (74% vs. 37.7% toward 50 ppb, which was among the best performances of BP involved NO2 sensors), accelerated response speed, better long-term stability, and strengthened humidity-repelling properties. In addition, excellent selectivity toward trace NO2 gas was revealed. These improvements could be ascribed into porous film, abundant sorption sites, numerous p-n heterojunctions, and passivation effect of ZnO nanowires on BP nanosheets. Furthermore, the proposed basic-solution assisted BP exfoliation favored film deposition, and enabled versatile composition design involving BP nanosheets in the future. In brief, the as-prepared BP-ZnO NO2 sensors paved the avenue for further BP applications and enriched its underlying transduction mechanism in gas sensing.

Odometer is a good information source for land vehicle navigation because it can detect the velocity or mileage of a vehicle. Odometer scale factor, misalignment, and level arm with inertial measurement unit are the three sources of integration inaccuracy. However, they are difficult to be calibrated using a single procedure as they vary with many factors, such as the environment temperature, loading, and mounting factors. The online calibration method of the total odometer error and the odometer-aided inertial navigation system algorithm based on Coriolis Law were derived in this study. Vehicle test results indicated that the proposed calibration method can perform a good estimation of total odometer error. Navigation accuracy can be improved significantly with the calibrated odometer when the Global Positioning System declares loss-of-lock, which is approximately 1‰ of the mileage.

Benefiting from advances in nanofabrication technology, emerging metasurfaces are promising for compact and wearable multicolor meta-holograms with large fields of view. However, due to the inherent electromagnetic properties of the structures that are used, current multicolor meta-holograms are often sensitive to the incident light polarization, which greatly restricts the application of meta-holography. Here, we took advantage of the amplitude properties of metasurfaces and the off-axis illumination method to carry out experiments involving polarization-insensitive colorful meta-holography with anisotropic nanostructures. With red, green and blue lasers illuminating the meta-hologram along different angles, a polarization-insensitive colorful holographic image was achieved and the disturbance from zero-order diffraction light was essentially eliminated. To the best of our knowledge, the current work was the first time that a polarization-insensitive colorful meta-hologram with anisotropic nanostructures was experimentally demonstrated. We expect our approach to provide promising prospects for the use of metasurfaces in applications such as flat meta-lenses, data storage and virtual/augmented reality.

In this paper, we presented a new method to directly fabricate 3D microlens array (MLA) without the pattern transfer and substrate reshaping process. Gas-assist deformed concave Polydimethylsiloxane (PDMS) film was used as the molding template. The template was fixed on the curved micro-hole array with a micro cavity during the injection molding process. The curved micro-hole array was fabricated by 3D printing in order to avoid the interference from microlens nearby. In addition, the micro-hole array is detachable, thus allowing it to be assembled onto the MLA automatically. Less than few minutes, the formation of 3D MLA can be realized by which the polymeric lens material is capable of being cured within dozens of seconds. Multi-focusing MLA was designed to reduce the defocus. And the focal length of each microlens varied according to the different diameter of micro-holes. This novel method is time-saving, cost-effective and precision. A single microlens has a radius of 250–500 μm, and the accuracy can reach 30 μm. Performance of the 3D MLA has been optically characterized. The introduction of micro-holes array can effectively reduce the crosstalk between the eyes and the influence of stray light. The curved MLA have has a FOV over 70°.

This paper puts forward a novel method for fabrication of sandwich-structured BCE using a detachable micro-hole array (MHA) prepared by 3D printing. Compared with most traditional methods, 3D print...

Nitrogen dioxide (NO2) is a hazardous gas species that could impose a great threat on environmental protection and human health even at very low doses. Thus, it is of great importance to selectively detect trace NO2 gas below the ppm level. This has been a serious challenge so far, especially in the presence of other interfering gases. Herein, we report ultrasensitive, room-temperature and UV light-assisted NO2 gas sensing based on few-layer MoS2 nanosheet/ZnO nanowire composites serving as the sensing layer. A series of characterization techniques, such as scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), X-ray powder diffraction (XRD), Raman, energy-dispersive X-ray spectroscopy (EDS), UV-Visual and ultraviolet photoelectron spectroscopy (UPS), were employed to explore the componential and structural properties of the obtained sensitive materials. Initially, the as-prepared MoS2/ZnO composites showed a tiny response (40%) and an incomplete recovery to 10 ppm NO2 gas in dark condition. While under UV illumination, the sensing response attained 8.4 and 188, toward 50 ppb and 200 ppb NO2 with a full recovery. Meanwhile, a sensitivity of 0.93 ppb−1, a detection limit of 50 ppq (10−15), and excellent repeatability and selectivity were also achieved. The experimental results were better than most previous work on NO2 detection to the best of our knowledge. Two main aspects are responsible for the outstanding performance. One is that a mass of photo-excited electron–hole pairs participated in the reaction with NO2 molecules under UV illumination. The other lies in numerous p–n MoS2/ZnO nanojunctions, favorable for the extension of the depletion region and the separation of the charge carrier. Additionally, long-term stability, as well as the effect of film thickness and carrier gas species on sensor performance, were simply investigated. We combined p–n nanojunctions with the UV illumination method, providing an alternative strategy to realize room-temperature operation and high sensitivity in the field of gas sensors.