Performance evaluation of basalt fiber-reinforced geopolymer composites with various contents of nano CaCO3

High carbon footprint of cement production is the major drawback of plain cement concrete resulting in environmental pollution. Geopolymer composites paste can be effectively used as an alternative to Portland cement in the construction industry for a sustainable environment. The demand for high-performance composites and sustainable construction is increasing day by day. Therefore, the present experimental program has endeavored to investigate the mechanical performance of basalt fiber-reinforced fly ash-based geopolymer pastes with various contents of nano CaCO₃. The content of basalt fibers was fixed at 2% by weight for all specimens while the studied contents of nano CaCO₃ were 0%, 1%, 2%, and 3%, respectively. The compressive strength, compressive stress-strain response, flexural strength, bending stress-strain response, elastic modulus, toughness modulus, toughness indices, fracture toughness, impact strength, hardness, and microstructural analysis of all four geopolymer composite pastes with varying contents of nano CaCO₃ using scanning electron microscopy (SEM) were evaluated. The results revealed that the use of 3% nano CaCO₃ in basalt fiber-reinforced geopolymer paste presented the highest values of compressive strength and hardness while the use of 2% nano CaCO₃ showed the highest values of flexural strength, impact strength, and fracture toughness of composite paste. The SEM results indicated that the addition of nano CaCO₃ improved the microstructure and provided a denser geopolymer paste by refining the interfacial zones and accelerating the geopolymerization reaction.     

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.     

Compressive properties of pristine and SiC-Te-added MgB2 powders,green compacts and spark-plasma-sintered bulks

Pristine and (SiC+Te)-added MgB₂ powders, green and spark plasma sintered (SPS) compacts were investigated from the viewpoint of quasi-static and dynamic (Split-Hopkinson Pressure Bar, SHPB) compressive mechanical properties The amount of the additive (SiC+Te) was selected to be the optimum one for maximization of the superconducting functional parameters. Pristine and added MgB₂ show very similar compressive parameters (tan δ, fracture strength, Vickers hardness, others) and fragment size in the SHPB test. However, for the bulk SPSed samples the ratio of intergranular to transgranular fracturing changes, the first one being stronger in the added sample. This is reflected in the quasi-static K_IC that is higher for the added sample. Despite this result, sintered samples are brittle and have roughly similar fragmentation behavior as for brittle engineering ceramics. In the fragmentation process, the composite nature of our samples should be considered with a special focus on MgB₂ blocks (colonies) that show the major contribution to fracturing. The Glenn-Chudnovsky model of fracturing under dynamic load provides the closest values to our experimental fragment size data.     

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.