Influence of Se and Te substitutions at Tl-site of Tl(Ba,Sr)CaCu2O7 superconductor on the AC susceptibility and electrical properties

The Sr and Ba bearing Tl-1212 phase, Tl(Ba,Sr)CaCu₂O₇ is an interesting superconductor. The Sr only bearing TlSr₂CaCu₂O₇ is not easily prepared in the superconducting form. The Ba only bearing TlBa₂CaCu₂O₇ on the other hand does not show improvement in the transition temperature with elemental substitution. In this work the influence of multivalent Se (non-metal) and Te (metalloid) substitutions at the Tl-site of Tl_1-xM_x(Ba,Sr)CaCu₂O₇ (M = Se or Te) superconductors for x = 0–0.6 was studied. The samples were prepared via the conventional solid-state reaction method. XRD patterns showed a single Tl-1212 phase for x = 0 and 0.1 Se substituted samples. The critical current density at the peak temperature, T_p of the imaginary (χ”) part of the AC susceptibility (χ = χ’ +χ”), J_c-inter(T_p) for all samples was between 15 and 21 A cm⁻². The highest superconducting transition temperature was shown by the x = 0.3 Se-substituted sample (T_c-onset = 104 K, T_c-zero = 89 K, T_cχ’ = 104 K and T_p = 80 K). Te suppressed the superconductivity of Tl-1212 phase. The order of highest transition temperatures are as follows: Tl_1-xTe_x(Ba,Sr)CaCu₂O₇<Tl(Ba,Sr)CaCu₂O₇<Tl_1-xSe_x(Ba,Sr)CaCu₂O₇. This work showed that Se was better than Te in improving the transition temperature and flux pinning of the Tl-1212 phase. The roles of ionic radius of Se and Te on the superconductivity of Tl(Ba,Sr)CaCu₂O₇ are discussed in this paper.     

Progressive NO2 Sensors with Rapid Alarm and Persistent Memory-Type Responses for Wide-Range Sensing Using Antimony Triselenide Nanoflakes

Antimony triselenide (Sb₂Se₃) nanoflake-based nitrogen dioxide (NO₂) sensors exhibit a progressive bifunctional gas-sensing performance, with a rapid alarm for hazardous highly concentrated gases, and an advanced memory-type function for low-concentration (<1 ppm) monitoring repeated under potentially fatal exposure. Rectangular and cuboid shaped Sb₂Se₃ nanoflakes, comprising van der Waals planes with large surface areas and covalent bond planes with small areas, can rapidly detect a wide range of NO₂ gas concentrations from 0.1 to 100 ppm. These Sb₂Se₃ nanoflakes are found to be suitable for physisorption-based gas sensing owing to their anisotropic quasi-2D crystal structure with extremely enlarged van der Waals planes, where they are humidity-insensitive and consequently exhibit an extremely stable baseline current. The Sb₂Se₃ nanoflake sensor exhibits a room-temperature/low-voltage operation, which is noticeable owing to its low energy consumption and rapid response even under a NO₂ gas flow of only 1 ppm. As a result, the Sb₂Se₃ nanoflake sensor is suitable for the development of a rapid alarm system. Furthermore, the persistent gas-sensing conductivity of the sensor with a slow decaying current can enable the development of a progressive memory-type sensor that retains the previous signal under irregular gas injection at low concentrations.     

Multiobjective PSO based adaption of neural network topology for pixel classification in satellite imagery

The proposed work involves the multiobjective PSO based adaption of optimal neural network topology for the classification of multispectral satellite images. It is per pixel supervised classification using spectral bands (original feature space). This paper also presents a thorough experimental analysis to investigate the behavior of neural network classifier for given problem. Based on 1050 number of experiments, we conclude that following two critical issues needs to be addressed: (1) selection of most discriminative spectral bands and (2) determination of optimal number of nodes in hidden layer. We propose new methodology based on multiobjective particle swarm optimization (MOPSO) technique to determine discriminative spectral bands and the number of hidden layer node simultaneously. The accuracy with neural network structure thus obtained is compared with that of traditional classifiers like MLC and Euclidean classifier. The performance of proposed classifier is evaluated quantitatively using Xie-Beni and β indexes. The result shows the superiority of the proposed method to the conventional one.     

用于发光温度传感的金属有机框架材料

金属有机框架(Metal organic frameworks,MOFs)由于其显著的结构多样性和可调的发光性能,为制备不同种类的发光传感器提供了良好契机。近年来,利用发光MOFs探测温度传感技术受到了人们的广泛关注。结合对发光测温的描述后,总结了发光型MOF温度计的最新研究进展,重点介绍了双发射型MOF在温度传感领域中的广泛应用。     

Y4.67Si3O13-based phosphors: Structure,morphology and upconversion luminescence for optical thermometry

How to improve the sensitivity of the temperature-sensing luminescent materials is one of the most important objects currently. In this work, to obtain high sensitivity and learn the corresponding mechanism, the rare earth (RE) ions doped Y_4.67Si₃O₁₃ (YS) phosphors were developed by solid-state reaction. The phase purity, structure, morphology and luminescence characteristics were evaluated by XRD, TEM, emission spectra, etc. The change of the optical bandgaps between the host and RE-doped phosphors was found, agreeing with the calculation results based on density-functional theory. The temperature-dependence of the upconversion (UC) luminescence revealed that a linear relationship exists between the fluorescence intensity ratio of Ho³⁺ and temperature. The theoretical resolution was evaluated. High absolute (0.083 K⁻¹) and relative (3.53% K⁻¹ at 293 K) sensitivities have been gained in the YS:1%Ho³⁺, 10%Yb³⁺. The effect of the Yb³⁺ doping concentration and pump power on the sensitivities was discussed. The pump-power–dependence of the UC luminescence indicated the main mechanism for high sensitivities in the YS:1%Ho³⁺, 10%Yb³⁺. Moreover, the decay-lifetime based temperature sensing was also evaluated. The above results imply that the present phosphors could be promising candidates for temperature sensors, and the proposed strategies are instructive in exploring other new temperature sensing luminescent materials.     

Chitosan Microspheres as Carriers for pH‐Indicating Species in Corrosion Sensing

Chitosan microspheres containing bromocresol green, cresol red, and phenolphthalein for corrosion detection, through pH change, are synthesized in order to be used in protective coatings for aluminium alloys. Microspheres containing corrosion detection species are characterized morphologically (SEM) and physico‐chemically (FTIR, TGA). Release studies (UV–vis) are performed in corrosion‐promoting conditions (pH, NaCl), and detection studies by immersion in media associated with corrosion activity while microspheres' sensing activity is evaluated visually. Electrochemical characterization of AA2024 substrates in the presence of chitosan spheres is performed to understand material performance, and a color change is observed as a result of local pH increase in cathodic areas when corrosion takes place. These findings can be correlated with the results from release studies and seem a promising approach for corrosion sensing purposes, not only because pH increase is possible to detect due to corrosion, but also because chitosan is considered an environmentally friendly material.     

Road Extraction from High Resolution Remote Sensing Image based on Shape Analysis with Gestalt Theory

Simulating the psychological experience of human vision，a road extraction model based on the format tower is proposed to extract the road in the high resolution remote sensing image from the perspective of morphology.Firstly，based on the spectral and texture information，the suspected road targets are extracted by using segmentation technology.Then these targets are classified according to their reliability and extract the road targets for each category.Finally，three types of identified road information are verified and merged，and the continuous smooth road extraction results are obtained.Experiments on real high resolution images show that the results are consistent with the visual perception of the human eye，and the overall classification accuracy is higher，indicating that the algorithm is effective and feasible and has good use value.     

Durable,Sensitive, and Wide‐Range Wearable Pressure Sensors Based on Wavy‐Structured Flexible Conductive Composite Film

Flexible pressure sensors have potential applications in human motion monitoring and electronic skins. To satisfy the practical applications, pressure sensors with a high sensitivity, a low detection limit, a broad response range, and an excellent stability are highly needed. Here, a piezoresistive pressure sensor based on wavy‐structured single‐walled carbon nanotube/graphite flake/thermoplastic polyurethane (SWCNT/GF/TPU) composite film is fabricated by a prestretching process. Due to the random wavy structure, high conductivity, and good flexibility, the prepared sensor displays a low detection limit of 2 Pa, a wide sensing range of 0–60 kPa, and a high sensitivity of 5.49 kPa^?1 for 0–50 Pa. Furthermore, the sensor shows a remarkable repeatability of over 1.1 × 10⁴, 9.0 × 10³, and 2.0 × 10³ pressure loading/unloading cycles at 50 Pa, 500 Pa, and 30 kPa, respectively, and a fast responsibility of 100–150 ms of loading response time and 400–600 ms of relaxation time. Therefore, the pressure sensor is successfully adopted to monitor both the large‐scale human activities (e.g., walk and jump) and the small‐scale signals (e.g., wrist pulse). Furthermore, a sensor array is assembled to map the weight and shape of an object, indicating its various potential applications including human–machine interactions, human health monitoring, and other wearable electronics.     

储层泥浆侵入深度预测方法研究

泥浆侵入半径的确定尚缺乏严格的验证标准.以油水两相渗流理论和离子扩散方程为基础,结合储集层特点,研究了不同储层参数下泥浆滤液对地层的侵入特性.数值模拟侵入时间选取10 d和20 d.数值模拟结果表明,侵入半径在渗透率不变的情况下随孔隙度的增大而减小,在孔隙度不变的情况下随渗透率的增大而增大;当渗透率和孔隙度都发生变化时,泥浆侵入半径一般随孔隙度的增加呈幂函数增加.依据这种关系对测井资料约束处理,得到的泥浆侵入半径较客观地反映了地层的真实情况.