Radio Technique Research Articles

4FGL J1544.2−2554: A new spider pulsar candidate

Context. Spider pulsars are millisecond pulsars in tight binary systems in which a low-mass companion star is heated and ablated by the pulsar wind. Observations of these objects allow one to study stellar evolution with the formation of millisecond pulsars and the physics of superdense matter in neutron stars. However, spiders are rare due to difficulties related to their discovery when using typical radio search techniques. The Fermiγ-ray source 4FGL J1544.2−2554 was recently proposed as a pulsar candidate, and its likely X-ray and optical counterparts, with the galactic coordinates l ≈ 344.​​°76, b ≈ 22.​​°59 and the magnitude G ≈ 20.6, were found using the eROSITA and Gaia surveys. Aims. Our goals are to study whether the source is a new spider pulsar and to estimate its fundamental parameters. Methods. We performed the first optical time series multi-band photometry of the object. We used the Lomb-Scargle periodogram to search for its brightness periodicity and fitted its light curves with a model of direct heating of the binary companion by the pulsar wind. Results. The source shows a strong brightness variability with a period of ≈2.724 h and an amplitude of ≳2.5 mag, and its light curves have a single broad peak per period. These features are typical for spider pulsars. The curves are well fitted by the direct heating model, resulting in an orbit inclination of the presumed spider system of ≈83°, a companion mass of ≈0.1 M⊙, ‘day-side’ and ‘night-side’ temperatures of ≈7200 K and ≈3000 K, a Roche lobe filling factor of ≈0.65, and a distance of ≈2.1 kpc. Conclusions. Our findings suggest that 4FGL J1544.2−2554 is a spider pulsar. This result encourages the search for pulsar millisecond pulsations in radio and γ-rays to confirm its nature.

Hybrid Artificial-Intelligence-Based System for Unmanned Aerial Vehicle Detection, Localization, and Tracking Using Software-Defined Radio and Computer Vision Techniques

The proliferation of drones in civilian environments has raised growing concerns about their misuse, highlighting the need to develop efficient detection systems to protect public and private spaces. This article presents a hybrid approach for UAV detection that combines two artificial-intelligence-based methods to improve system accuracy. The first method uses a software-defined radio (SDR) to analyze the radio spectrum, employing autoencoders to detect drone control signals and identify the presence of these devices. The second method is a computer vision module consisting of fixed cameras and a PTZ camera, which uses the YOLOv10 object detection algorithm to identify UAVs in real time from video sequences. Additionally, this module integrates a localization and tracking algorithm, allowing the tracking of the intruding UAV’s position. Experimental results demonstrate high detection accuracy, a significant reduction in false positives for both methods, and remarkable effectiveness in UAV localization and tracking with the PTZ camera. These findings position the proposed system as a promising solution for security applications.

Short-Range Prediction of Squall-Line-Induced Heavy Rainfall: An Added Impact of GPS RO to FY-4A AGRI Data Assimilation

Abstract The GPS radio occultation technique has prompted a new era as GPS receivers are placed onboard traditional polar-orbiting operational environmental satellites and newly emerging commercial small satellite constellations. With high vertical resolutions of a few hundred meters, GPS radio occultation-observed refractivity profiles effectively complement the geostationary satellite observations of infrared brightness temperatures at high horizontal resolutions (∼2 km) for data assimilation in numerical weather prediction. In this study, numerical experiments are performed to assimilate radio occultation (RO) refractivity observations from FY-3D/FY-3E, MetOp-B/MetOp-C, COSMIC-2, SPIRE, and GeoOptics and brightness temperature observations at channels 9 (6.25 μm) and 10 (7.1 μm) from the Advanced Geosynchronous Radiation Imager (AGRI) onboard FY-4A. The benefits of adding the refractivity to the brightness temperature observations for improving quantitative precipitation forecasts (QPFs) of two squall-line cases over eastern China are shown using the Weather Research and Forecasting Model and the Gridpoint Statistical Interpolation analysis system. In the first case, the squall line was caused by a superposition of cold and dry air advection behind an upper-level trough over low-level warm and humid air by a low-level jet. A combined assimilation of the GPS RO and FY-4A AGRI observations produced a skillful forecast of the squall-line distribution, characterized by a warm zone 100–300-km long ahead of a cold front near the ground; this led to more consistent improvements in the forecast of a narrow band of squall-line thunderstorms than those from two separate assimilations. The threat scores of 24-h QPFs associated with both squall-line cases are significantly improved, especially for heavier rainfall events.

Performance analysis of IRS-assist dual-hop wireless communication system

The IRS-assist or smart radio environment technique is a widely developing technology that network providers can use to establish sustained connectivity between end-user terminals and central data units for the next-generation wireless standards. This article introduced a simple and more accurate link-switching technique for dual-hop communication: a single link-switching threshold (SLST) algorithm to provide an uninterrupted linkage between the transceiver terminals. Depending on the severity of the communicating channel under a dual-hop system, links can do auto switches between themselves and furnish continuous connectivity between end-user terminals. Due to a discrete number of phase shifts of the IRS elements, phase and quantization errors are induced in the channel; the proposed system can also optimize the phase and quantization errors. Besides, this work investigates improving the physical layer performance of the dual-hop wireless communication system under the combined effect of phase shift and quantization error with the introduction of the SLST method. For this particular, three performance metrics have been encountered: the outage probability (OP), average bit error rate (ABER), and average capacity (bits/s/Hz). A new, more accurate mathematical framework using the Meijer’G function has been constructed to evaluate worthwhile analytical derivation. Under analytical calculation, we have assumed the primary link experienced with common Rayleigh fading and the IRS-assist link (IAL) experienced with Nakagami-m distribution due to a large number of reflecting elements in the system. The proposed dual-hop system furnishes noteworthy benefits for each performance metric rather than individual links. Moreover, the suitable selection of quantization level and a number of reflecting elements confirm the exhibition of satisfactory outcomes and minimize the channel hardness of the system. Additionally, numerical simulation results from MATLAB, using Monte Carlo simulation, have been added to validate the analytical outcomes for every performance measure.

Hybrid Ag-mesh/Ta-doped TiO2 thin film configuration as a visible and near-infrared transparent electrode

This study focuses on the fabrication of a hybrid Ag-mesh/Ta-doped TiO2 (TTO) electrode that has a low sheet resistance and high transparency in the visible and near-infrared region, thereby holding significant commercialization potential. Here, ∼82 nm thick TTO film is deposited on the glass substrate using radio frequency magnetron sputtering technique, over which Ag mesh is carved using the metal aerosol jet printing method. As compared to TTO, sheet resistance of the entire hybrid configuration is found to show a 2-3 order improvement, with the loss of a mere ∼12 % in the visible and ∼8 % in NIR transmittance. The electronic structure of the Ag/TTO interface demonstrates the formation of an ohmic junction, thereby making it suitable for the fabrication of a network-based transparent electrode. Moreover, the overall functionality and preparation route of this electrode makes it more promising as compared to those of the conventional metal mesh and metal-oxide electrodes.

Broad-band, high-gain, low-frequency antennas for radio detection of earth-skimming tau neutrinos

A promising approach to detect high-energy tau neutrinos is through the measurement of impulsive radio emission from horizontal air showers initiated in the Earth's atmosphere. Observations at frequencies between 30 and 80 MHz seem particularly promising — if high-gain antennas focused at the horizon and blocking out as much as possible of the noisy sky are employed. Due to the large wavelengths, however, designing an antenna with the required properties is highly non-trivial at such low frequencies. In this article, we explore suitable antenna designs that provide the desired high gain, possess a smooth beam, are insensitive to ground conditions, are easily impedance-matched over the wide band, and are mechanically simple for deployment in large numbers in inaccessible terrain. In particular, we consider the “rhombus” antenna design for both horizontally and vertically polarized radiation a very attractive option for tau neutrino detection efforts in the atmosphere with the radio technique.

Dwarfism-related skeletal dysplasia in Italy. Multi-analytic study of 8th century CE human remains from Azzio (Varese) and biocultural implications of a pathology

Skeletal dysplasias are a broad family of genetic disorders, often challenging to diagnose even in clinical literature without molecular analysis. Some cases of possible skeletal dysplasia have also been identified in osteoarchaeological samples, although achieving a definitive diagnosis is fraught with difficulties. This paper presents the analysis of the osteological remains of AZ-III-3, discovered in the archaeological context of the Church of Sant’Antonio and Eusebio in Azzio (Varese province, Italy). The study aims to demonstrate that even with limited skeletal elements, a diagnosis can be hypothesised using macroscopic morphometric and radio diagnostic techniques. These methods, compared with clinical and paleopathological literature, have allowed for the identification of a rare Italian case of dwarfism-related skeletal dysplasia. This contribution seeks to address the biocultural presence of individuals affected by these skeletal dysplasias, listing and discussing all published Italian cases, including that of AZ-III-3, whose chronological framework was established through both archaeological context analysis and 14C dating.

Empirical Mode Decomposition Based Amplify and Forward Technique for Cooperative Cognitive Radio System

The rapid growth in the mobile industry due to increase in number of users accessing diverse services causes a high demand for radio spectrum. Nonetheless, the radio spectrum allocated for different wireless communication services is restricted. Cooperative Cognitive Radio (CCR) technique with Amplify and Forward (AF) relaying protocol used to address the problem suffers from noise amplification resulting in poor reception at the destination. Hence, in this paper, Empirical Mode Decomposition (EMD) based AF technique for CCR system was carried out to improve the performance of the existing CCR with AF relaying protocol. The transmitted signal from Primary User (PU) was received at the Secondary User (SU) where SU superimposed its own signal using Exclusive OR (XOR) rule. The combined signal from XOR was made to pass through EMD and amplified using AF by multiplying with the relay gain. The amplified signal was radiated to PU and SU receivers during the second hop transmission. The multiple copies of the receive signal at the SU receiver at different number of path (L = 2, 4) were combined at destination using Maximal Ratio Combiner (MRC). Mathematical expression for Bit Error Rate (BER) and Throughput (TP) were derived using the Probability Density Function (PDF) of the Nakagami-m fading distribution. Extensive simulations using MATLAB R2021a were employed to assess the effectiveness of the proposed technique and evaluated using BER and TP by comparing with the existing AF CCR. The EMD based AF technique proposed gave better performance with 75.2% reduction in BER and 21.86% increase in TP over the existing AF technique for CCR. The proposed technique can be deployed to improve the performance of cooperative cognitive radio system.

METHOD OF RECOGNITION OF FPV-UAV RADIO SIGNALS FORMED ACCORDING TO CROSSFIRE AND EXPRESSLRS STANDARDS

Unmanned aerial vehicles (UAVs) with the First Person View (FPV) system are the most common type of attack UAVs used at the tactical level by the armed forces of the russian federation. Timely detection of facts of their using by the enemy and countering them are important tasks solved by units of the Ukrainian Defense Forces. An effective countermeasure way for FPV-UAVs is to create interference in their radio control channels frequency bands. To increase the radio suppression range, it is necessary to use interference matched in frequency and structure, the necessary condition for the formation of which is the presence of a priori information about the structure of the radio signal. Analysis of the available information on the construction of enemy FPV-UAVs shows that their radio control and telemetry channels are usually combined, have time division multiple access, the signals are formed according to CrossFire and ExpressLRS standards and have fixed sets of parameter values that can be used as features in recognition. The proposed FPV-UAV radio signal recognition technique is based on decision tree and minimum metric methods and uses a priori information on frequency, time and modulation parameters of radio signals. The combination of the two decision-making methods made it possible to reduce the computational complexity by eliminating operations for determining the parameters of radio signals that do not correspond to the decisions taken at the previous stages, and provides the possibility of adding new time parameters without changing the developed recognition technique. The method consists of a sequence of operations for estimation radio signal parameters, comparing them with known values, making decisions about the type of standard and command- telemetry radio line operation mode. Only one fragment with a duration of one frequency element is sufficient to recognize the FPV-UAV radio signal, which reduces the technical requirements for detection means in which the method can be used.

Design and fabrication of micro carbon dioxide sensor based on TiO2 thin film

Abstract A micro-electro-mechanical systems (MEMS)-based micro carbon dioxide sensor is fabricated using conventional photolithography, electron beam evaporation, and radio frequency sputtering techniques. The sensor consists of a titanium dioxide sensing layer, interdigital electrodes (IDEs), a platinum resistance temperature detector (RTD), and an aluminium oxide substrate. Given a working temperature greater than 300°C, the resistance of the titanium dioxide sensing layer increases linearly with an increasing carbon dioxide concentration. Fluctuations in the working temperature are detected by the RTD and compensated using a proportional-integral-derivative (PID) feedback control system implemented in LabVIEW. The temperature detection results reveal that the RTD has a sensitivity of 1.3 mV/°C. The sensor is calibrated using a standard carbon dioxide detector and is used to perform carbon dioxide sensing at working temperatures of 300°C, 350°C, and 400°C, respectively. It is shown that the highest sensitivity of (0.179 MΩ/ppm) and fastest response time (15 seconds) are attained at a working temperature of 350°C.

Energy efficient and reliable data transmission in WBAN using multivariate gradient divergence African buffalo optimization

SummaryWireless body area network (WBAN), a popular radio communication technique, tracks patients' health conditions remotely using small, low‐power, portable sensors positioned on the body to sense vital signs and send data to a control node. To sustain long‐term health monitoring, WBANs require significant energy from the nodes. This research proposes an energy efficient and reliable data transmission using multivariate gradient divergence African buffalo optimization (EEMGDABO) to minimize the delay of critical node data transmission by identifying the optimal path to the control node. The protocol comprises two key processes: winsorized correlative segmented symbolic regression with reinforcement learning (WCS‐SRRL) and the walrus optimization algorithm (WaOA) for accurate priority‐based classification of health data (normal, abnormal, and critical). The second process involves transferring these priority‐based data with reduced energy consumption and delay while increasing throughput by determining the best path from the critical node to the destination (hospital/doctor) using EEMGDABO, which calculates node distance and energy fitness value. Implemented in MATLAB with a health monitoring WBAN dataset, the proposed protocol demonstrates 23% less energy consumption, 12.33% less delay, and 23.44% higher network lifetime compared to existing optimization approaches.

Understanding the Anomalous Thermoelectric Behavior of Fe-V-W-Al-Based Thin Films.

We investigated the thermoelectric and thermal behavior of Fe-V-W-Al-based thin films prepared using the radio frequency magnetron sputtering technique at different oxygen pressures (0.1-1.0 × 10-2 Pa) and on different substrates (n, p, and undoped Si). Interestingly, at lower oxygen pressure, formation of a bcc-type Heusler structure was observed in deposited samples, whereas at higher oxygen pressure, we have noted the development of an amorphous structure in these samples. Our findings indicate that the moderately oxidized Fe-V-W-Al amorphous thin film deposited on the n-Si substrate possesses a large magnitude of S ∼ -1098 ± 100 μV K-1 near room temperature, which is almost double the previously reported value for thin films. Additionally, the power factor (PF) indicated an enormously large value of ∼33.9 mW m-1 K-2 near 320 K. The thermal conductivity of the amorphous thin film is also found to be 2.75 Wm-1 K-1, which is quite lower compared to bulk alloys. As a result, the maximum figure of merit is estimated to be extremely high, i.e., ∼3.9 near 320 K, which is among one of the highest reported values so far. The anomalously large value of Seebeck coefficient and PF has been ascribed to the unusual composite effect of the metallic amorphous oxide phase and insulating substrate possessing a large Seebeck coefficient.

No Drone’s Sky: Full Spectrum Drone Surveillance and Neutralisation Concept for Enhanced Counter-UAS Framework

Unmanned Aircraft Systems (UAS), commonly known as drones, have witnessed substantial global proliferation in the past decade. Their constructive applications hold the promise of being a useful, yet critical component in creating a more efficient society with the enhancement of safety, efficiency, and facilitating advancements in various domains, ultimately contributing to our modern daily lives. However, the escalating dependence on computer and communication technologies renders, especially small, UAS susceptible to various threats, posing risks to public safety, national security, and individual privacy. Addressing these concerns necessitates the development of innovative technologies designed to detect, track, identify, and eliminate UAS in a manner that upholds safety, security, and privacy. A Counter-Unmanned Aircraft System (C-UAS) is defined as a system or apparatus capable of legally and securely incapacitating, disrupting, or assuming control over an UAS. Recent years have witnessed significant research endeavours aimed at detecting and eliminate drone threats. Detection methodologies encompass acoustic, visual, passive radio frequency, radar, and data fusion techniques, while neutralisation strategies encompass physical capture and jamming approaches. This paper, delving into the realm of small drone surveillance, is the opening segment of a three-part series aims to envision a C-UAS framework; it provides an exhaustive review of existing literature in the domain of UAS surveillance, delineating the challenges associated with countering unauthorised or unsafe drone operations, and evaluating the trajectory of detection to prepare against UAS-induced threats. Therefore, the fundamental objective of this paper is to offer a comprehensive surveillance baseline for a structured vision to a C-UAS framework, thus fostering a research community dedicated to the secure integration of drones into the airspace system.

A cognitive communication jamming strategy based on Transformer and Deep Reinforcement Learning

The advent of sophisticated communication technologies, such as cognitive radio and anti-jamming techniques, has significantly elevated the challenge of disrupting enemy communications. Nevertheless, the inherent openness of wireless communications remains a vulnerability that can be exploited to interfere with them. Some contemporary Reinforcement Learning (RL)-based jamming strategies examine methods for rapidly identifying the optimal jamming strategy for a specific modulated signal. However, such algorithms lack the flexibility and responsiveness required to effectively counter the enemy’s evolving communication strategies. To address this issue, we propose a Transformer and Deep Reinforcement Learning (DRL)-based jamming strategy that can be trained to identify jamming methods for multiple digital and analog signals. In particular, the Transformer Encoder is employed as a network for DRL to process the state information pertaining to the enemy communication. Subsequently, the decision module of the Double Deep Q Network (DDQN) is utilized to select the jamming action based on the processed information. Furthermore, we have devised a reward function and constructed an invalid jamming list, with the objective of selecting an action that requires low power consumption and enhances the convergence speed of the algorithm. The experimental results demonstrate that the algorithm proposed in this paper exhibits notable performance advantages in comparison to other networks and DRL algorithms.

Experimental and Theoretical Analysis of Rayleigh and Leaky-Sezawa Waves Propagating in ZnO/Fused Silica Substrates.

Piezoelectric c-axis oriented zinc oxide (ZnO) thin films, from 1.8 up to 6.6 µm thick, have been grown by the radio frequency magnetron sputtering technique onto fused silica substrates. A delay line consisting of two interdigital transducers (IDTs) with wavelength λ = 80 µm was photolithographically implemented onto the surface of the ZnO layers. Due to the IDTs' split-finger configuration and metallization ratio (0.5), the propagation of the fundamental, third, and ninth harmonic Rayleigh waves is excited; also, three leaky surface acoustic waves (SAWs) were detected travelling at a velocity close to that of the longitudinal bulk wave in SiO2. The acoustic waves' propagation in ZnO/fused silica was simulated by using the 2D finite-element method (FEM) technique to identify the nature of the experimentally detected waves. It turned out that, in addition to the fundamental and harmonic Rayleigh waves, high-frequency leaky surface waves are also excited by the harmonic wavelengths; such modes are identified as Sezawa waves under the cut-off, hereafter named leaky Sezawa (LS). The velocities of all the modes was found to be in good agreement with the theoretically calculated values. The existence of a low-loss region in the attenuation vs. layer thickness curve for the Sezawa wave below the cut-off was theoretically predicted and experimentally assessed.

A Comprehensive Survey on Deep Learning-Based LoRa Radio Frequency Fingerprinting Identification.

LoRa enables long-range communication for Internet of Things (IoT) devices, especially those with limited resources and low power requirements. Consequently, LoRa has emerged as a popular choice for numerous IoT applications. However, the security of LoRa devices is one of the major concerns that requires attention. Existing device identification mechanisms use cryptography which has two major issues: (1) cryptography is hard on the device resources and (2) physical attacks might prevent them from being effective. Deep learning-based radio frequency fingerprinting identification (RFFI) is emerging as a key candidate for device identification using hardware-intrinsic features. In this paper, we present a comprehensive survey of the state of the art in the area of deep learning-based radio frequency fingerprinting identification for LoRa devices. We discuss various categories of radio frequency fingerprinting techniques along with hardware imperfections that can be exploited to identify an emitter. Furthermore, we describe different deep learning algorithms implemented for the task of LoRa device classification and summarize the main approaches and results. We discuss several representations of the LoRa signal used as input to deep learning models. Additionally, we provide a thorough review of all the LoRa RF signal datasets used in the literature and summarize details about the hardware used, the type of signals collected, the features provided, availability, and size. Finally, we conclude this paper by discussing the existing challenges in deep learning-based LoRa device identification and also envisage future research directions and opportunities.

Tuning the Topo-Morphological properties of ITO Films using Al-Ag interlayer for Low-Resistance Optoelectronics Devices

Indium tin oxide (ITO) is recently attracting intense attention for application as transparent conducting electrode in different optoelectronic devices including solar cells, liquid crystal displays and organic light emitting diodes. This is attributed to their high optical transmittance in the visible region and good electrical conductivity. In this work, surface topological-morphological (topo-morphological) and electrical properties of ITO based multilayer films with aluminum-silver (Al-Ag) metal interlayer (ITO/Al-Ag/ITO) are investigated after post annealing treatment at 300-500oC by atomic force microscopic (AFM), field emission scanning electron microscopy (FESEM), four-point probe and hall-effect techniques respectively. The ITO/Al-Ag/ITO films are deposited by direct current and radio frequency magnetron sputtering techniques on p-type Si at room temperature. The results showed a smooth surface topology by as-deposited film with films smoothness improving after post annealing treatment as analyzed by AFM method. Sharp crystallites peaks were obtained by all the films with smaller peaks diffusing and recombining to form larger films with increasing post-annealing temperature. The films root means square roughness increased as the temperature increases with film annealed at 500oC showing a superior and enhanced microstructure. Compared to as-deposited film, careful observation shows that surface morphology smoothness increased with increase in temperature with films annealed at 400oC and 500oC showing highest increasing surface smoothness pattern as determined by FESEM technique. Similarly, higher grain sizes are observed especially by films annealed at 400oC and 500oC due to the heat absorption which causes the particles to expand thereby narrowing the grain boundaries and subsequently improve the surface smoothness. These FESEM findings are consistent with AFM measurements confirming the high surface property and enhanced grain size with increasing post annealing temperature. The films exhibit decreased electrical resistivity and sheet resistance while carrier concentration and Hall mobility increased with increasing post annealing treatment indicating highest corresponding values of...

Robust superconductivity and the suppression of charge-density wave in the quasi-skutterudites Ca3(Ir1−xRhx)4Sn13 single crystals at ambient pressure

Single crystals of the quasi-skutterudite compounds Ca3(Ir1-xRhx)4Sn13 (3–4–13) were synthesized by flux growth and characterized by x-ray diffraction, energy dispersive x-ray spectroscopy, magnetization, resistivity, and radio frequency magnetic susceptibility techniques. The coexistence and competition between the charge density wave (CDW) and superconductivity was studied by varying the Rh/Ir ratio. The superconducting transition temperature, Tc , varies from 7 K in pure Ir (x = 0) to 8.3 K in pure Rh (x = 1). Temperature-dependent electrical resistivity reveals monotonic suppression of the CDW transition temperature, T CDW(x). The CDW starts in pure Ir, x = 0, at T CDW ≈ 40 K and extrapolates roughly linearly to zero at xc≈ 0.53–0.58 under the superconducting dome. Magnetization and transport measurements show a significant influence of CDW on superconducting and normal states. Meissner expulsion is substantially reduced in the CDW region, indicating competition between the CDW and superconductivity. The low-temperature resistivity is higher in the CDW part of the phase diagram, consistent with the reduced density of states due to CDW gapping. Its temperature dependence just above Tc shows signs of non-Fermi liquid behavior in a cone-like composition pattern. We conclude that the Ca3(Ir1-xRhx)4Sn13 alloy is a good candidate for a composition-driven quantum critical point at ambient pressure.

Ar/NH3 Plasma Etching of Cobalt-Nickel Selenide Microspheres Rich in Selenium Vacancies Wrapped with Nitrogen Doped Carbon Nanotubes as Highly Efficient Air Cathode Catalysts for Zinc-Air Batteries.

This work utilizes defect engineering, heterostructure, pyridine N-doping, and carbon supporting to enhance cobalt-nickel selenide microspheres' performance in the oxygen electrode reaction. Specifically, microspheres mainly composed of CoNiSe2 and Co9Se8 heterojunction rich in selenium vacancies (VSe·) wrapped with nitrogen-doped carbon nanotubes (p-CoNiSe/NCNT@CC) are prepared by Ar/NH3 radio frequency plasma etching technique. The synthesized p-CoNiSe/NCNT@CC shows high oxygen reduction reaction (ORR) performance (half-wave potential (E1/2) = 0.878V and limiting current density (JL) = 21.88mA cm-2). The JL exceeds the 20wt% Pt/C (19.34mA cm-2) and the E1/2 is close to the 20wt% Pt/C (0.881V). It also possesses excellent oxygen evolution reaction (OER) performance (overpotential of 324 mV@10mA cm-2), which even exceeds that of the commercial RuO2 (427 mV@10mA cm-2). The density functional theorycalculation indicates that the enhancement of ORR performance is attributed to the synergistic effect of plasma-induced VSe· and the CoNiSe2-Co9Se8 heterojunction. The p-CoNiSe/NCNT@CC electrode assembled Zinc-air batteries (ZABs) show a peak power density of 138.29mW cm-2, outperforming the 20wt% Pt/C+RuO2 (73.9mW cm-2) and other recently reported catalysts. Furthermore, all-solid-state ZAB delivers a high peak power density of 64.83mW cm-2 and ultra-robust cycling stability even under bending.

Highly aligned pyrolytic graphite blades for neutron monochromatization

Highly aligned pyrolytic graphite blades for neutron monochromatization have been fabricated successfully from smaller commercial highly oriented pyrolytic graphite (HOPG) crystals. These blades of a large coverage area, 136 mm wide × 2 mm high, are achieved with minimum increase of the mosaic over that of the original HOPG crystal. A specialized crystal cleavage device and soldering device are developed for the fabrication process. Furthermore, an optimized intermittent mode of the radio frequency magnetron sputtering technique is employed to deposit indium on HOPG crystals. The devices and procedure reported here could be applied to the development of the focusing monochromators and analyzers in neutron scattering instruments using a sizable neutron beam.