We describe a nitrogen-specific detector (NSD) for aqueous mobile phase-based high performance liquid chromatography (HPLC). It is based by means of total hydrophilic organic nitrogen detection. Separated analytes are photooxidized online and converted to nitrate, followed by an ultravilet absorbance detector. It features response dependant on the product of nitrogen number in the molecule and its molar concentration, no matter what is ultravilet-absorbing or not. The HPLC equipped with NSD can quantify nitrogen-containing analytes via a sole standard of potassium nitrate for calibration. This results in identical calibration curve for all nitrogen-containing analytes, obviating individual calibration. The limit of detection of NSD is 4.3 μM N/L, and its linear range is up to 4 mM N/L.

Low-dimensional semiconductor nanostructures, particularly in the form of nanowire configurations with large surface-to-volume-ratio, offer intriguing optoelectronic properties for the advancement of integrated photonic technologies. Here, a bias-controlled, superior dual-functional broadband light detecting/emitting diode enabled by constructing the aluminum-gallium-nitride-based nanowire on the silicon-platform is reported. Strikingly, the diode exhibits a stable and high responsivity (R) of over 200 mAW-1 covering an extremely wide operation band under reverse bias conditions, ranging from deep ultraviolet (DUV: 254 nm) to near-infrared (NIR: 1000 nm) spectrum region. While at zero bias, it still possesses superior DUV light selectivity with a high off-rejection ratio of 106. When it comes to the operation of the light-emitting mode under forward bias, it can achieve large spectral changes from UV to red simply by coating colloid quantum dots on the nanowires. Based on the multifunctional features of the diodes, this study further employs them in various optoelectronic systems, demonstrating outstanding applications in multicolor imaging, filterless color discrimination, and DUV/NIR visualization. Such highly responsive broadband photodetector with a tunable emitter enabled by III-V nanowire on silicon provides a new avenue toward the realization of integrated photonics and holds great promise for future applications in communication, sensing, imaging, and visualization.

X-ray detectors have numerous applications in medical imaging, industrial inspection, and crystal structure analysis. Gallium oxide (Ga2O3) shows potential as a material for high-performance X-ray detectors due to its wide bandgap, relatively high mass attenuation coefficient, and resistance to radiation damage. In this study, we present Sn-doped Ga2O3 microwire detectors for solar-blind and X-ray detection. The developed detectors exhibit a switching ratio of 1.66 × 102 under X-ray irradiation and can operate stably from room temperature to 623 K, which is one of the highest reported operating temperatures for Ga2O3 X-ray detectors to date. These findings offer a promising new direction for the design of Ga2O3-based X-ray detectors.

Perovskite CsPbBr3 semiconductors exhibit unusually high defect tolerance leading to outstanding and unique optoelectronic properties, demonstrating strong potential for γ-radiation and X-ray detection at room temperature. However, the total dose effects of the perovskite CsPbBr3 must be considered when working in a long-term radiation environment. In this work, the Schottky type of perovskite CsPbBr3 detector was fabricated. Their electrical characteristics and γ-ray response were investigated before and after 60Co γ ray irradiation with 100 and 200 krad (Si) doses. The γ-ray response of the Schottky-type planar CsPbBr3 detector degrades significantly with the increase in total dose. At the total dose of 200 krad(Si), the spectral resolving ability to γ-ray response of the CsPbBr3 detector has disappeared. However, with annealing at room temperature for one week, the device\'s performance was partially recovered. Therefore, these results indicate that the total dose effects strongly influence the detector performance of the perovskite CsPbBr3 semiconductor. Notably, it is concluded that the radiation-induced defects are not permanent, which could be mitigated even at room temperature. We believe this work could guide the development of perovskite detectors, especially under harsh radiation conditions.

Due to the large distance or weak electronic conjugation between adjacent Bi-I octahedrons, the charge transport in the low-dimensional bismuth-based hybrid perovskites is impeded and thus hinders their future developments. In this work, A-site cation engineering by monoamine BZA (benzylamine) and diamine 3-AMP (3-(aminomethyl)pyridine) has been demonstrated as an efficient strategy to regulate the corresponding activation energy of ionic migration and carrier transport capacity. Given the higher polarity of 3-AMP than BZA, producing a more efficient dielectric screening effect, it gives rise to obtaining the small exciton binding energy (50 meV) and low defect states (3.53×109  cm-3 ). The reduced distance of adjacent Bi-I octahedrons by the bilateral anchoring of the 3-AMP2+ diamine cation enhances both electronic conjugation and charge transport performance. Therefore, the photodetector for (3-AMP)BiI5 SC shows a 243-fold increase in on/off ratio compared with the (BZA)3 BiI6 SC.

This paper researches mean-square bounded consensus for a nonlinear multi-agent system subjected to randomly occurring deception attack, process and measurement noises. Considering the measurement tampered by the attacker, an estimator is presented to obtain relative accurate state estimation, where the gain is acquired by a recursive algorithm. On this basis, a type of centralized controller is designed combined with cloud computing system. Moreover, from perspective of the defender, a detector is proposed at the side of agent to detect whether the current actuator input is attacked. Using linear matrix inequality, sufficient conditions are given for achieving mean-square bounded consensus and an upper boundary is derived. Finally, validity of the proposed method is illustrated via two simulation examples.

Water surface object detection is one of the most significant tasks in autonomous driving and water surface vision applications. To date, existing public large-scale datasets collected from websites do not focus on specific scenarios. As a characteristic of these datasets, the quantity of the images and instances is also still at a low level. To accelerate the development of water surface autonomous driving, this paper proposes a large-scale, high-quality annotated benchmark dataset, named Water Surface Object Detection Dataset (WSODD), to benchmark different water surface object detection algorithms. The proposed dataset consists of 7,467 water surface images in different water environments, climate conditions, and shooting times. In addition, the dataset comprises a total of 14 common object categories and 21,911 instances. Simultaneously, more specific scenarios are focused on in WSODD. In order to find a straightforward architecture to provide good performance on WSODD, a new object detector, named CRB-Net, is proposed to serve as a baseline. In experiments, CRB-Net was compared with 16 state-of-the-art object detection methods and outperformed all of them in terms of detection precision. In this paper, we further discuss the effect of the dataset diversity (e.g., instance size, lighting conditions), training set size, and dataset details (e.g., method of categorization). Cross-dataset validation shows that WSODD significantly outperforms other relevant datasets and that the adaptability of CRB-Net is excellent.

Diodes fabricated using a blend of poly(3-hexylthiophene) and phenyl-C61-butyric acid methyl ester (6-80 μm thick) as an organic semiconductor component achieved consistent 4 MeV α particle detection. Current-voltage characteristics and current-time measurements were obtained under α irradiation and in its absence. Steady-state and transient (time-of-flight) photoconduction measurements were additionally performed. Low-bias (<20 V) α particle detection gain-efficiency products of order 10-2 were measured. The α particle detection was achieved reproducibly, reversibly, and repeatably in different devices of varying organic semiconductor layer thicknesses using both the steady-state and time-dependent (dynamic) diode responses. Conductive gain, due to trapped electrons, increased the α particle gain-efficiency product in both forward and reverse bias conditions as well as increasing steady-state photoconduction. The device thickness was optimized to maximize the gain-efficiency product by matching the penetration depth of the α particle, obtained by modeling, to the organic semiconductor layer thickness. Very high confidence α particle detection was achieved (with signal-to-noise ratios exceeding 20) under optimized device dimensions and drive conditions. Hecht function fitting of the gain-efficiency product versus electric field data returns mobility-lifetime products of order 10-6-10-7 cm2 V-1. This work demonstrates that solution-processed organic semiconductor diodes are viable for low-voltage α particle detection.

In view of the shortcomings of the current abnormal data detection system of the protein gene library, such as low detection rate and high error detection rate, the abnormal data detection system of the protein gene library based on data mining technology is designed. The protein gene enters the firewall module of the system, and enters the immune module when it does not match the firewall rules; the memory detector in the immune module presents the protein gene, if the memory detector does not match the protein gene, the mature detector presents the protein gene, if the mature detector does not match the protein gene, it is determined as the normal protein gene data package, if it matches, it is considered that The abnormal data of protein gene was processed by the collaborative stimulation module, and the control module controlled by C8051F060 chip to detect the abnormal data of protein gene library. The immune module generates new protein gene sequences through an immature detector, simulates the immune mechanism of protein gene through a mature detector module, and simulates the secondary response in the abnormal data detection system of protein gene library through memory detector. The system introduces data mining technology into the detection and uses a two-level dynamic optimization algorithm to calculate the ASG similarity value of protein gene secondary structure arrangement. According to this value, the abnormal data detection of the protein gene library is realized by randomly generating protein genes, negative selection, clone selection and copying memory cells through gene expression. The experimental results show that the system can quickly detect abnormal data of the protein gene library, ensure the detection efficiency, and the detection accuracy reaches 97.1%. The system can reduce the error rate of normal protein gene detection as an abnormal protein gene.

The authors describe a strategy for ozone-induction coupling with plasma assistance (O3-I/PA) to enhance cataluminescence (CTL) based sensing of volatile organic compounds (VOCs). A homemade O3-I/PA CTL sensor system was constructed based on this strategy. O3-I/PA can significantly enhance the CTL response to many compounds that were hardly detectable previously with adequate sensitivity. Without any preconcentration, the limits of detection (for S/N = 3) are 20 μg.m-3 (= 5 ppbv) for toluene and 8 μg.m-3 (6.4 ppbv) for formaldehyde. VOCs including benzene, alkanes, halohydrocarbons, alkenes alcohols, aldehydes, ketones and ethers are found to produce a strong response when using this sensor system. Mechanistic studies showed that the synergistic effect of ozone-induction and plasma assistance promote the oxidation of the VOCs under formation of CO2. This strongly favors CTL emission. The sensor system can be used as a direct-reading detector for on-line and real-time monitoring of total VOCs. It also can be used as a detector in gas chromatography for the identification of individual VOCs. It is perceived that this work paves the way to both a new kind of vapor sensor and to a detection scheme in gas chromatography. Graphical abstract The synergistic effect of ozone-induction and plasma assistance promote the deep oxidation of the VOCs into CO2, which strongly favors cataluminescence emission.