Photoluminescence properties of Eu-doped WO3-Eu2(WO4)3 composites and single-phase Eu2(WO4)3 powders

The development of highly stable and efficient oxide-based red phosphors is urgently required for next-generation lighting devices. Herein, we report the micro/crystal structures and luminescent properties of single-phase Eu₂(WO₄)₃ and Eu³⁺-doped WO₃-Eu₂(WO₄)₃ composite phosphors prepared by a one-step conventional solid-state reaction method in air atmosphere. As increasing Eu contents in the mixtures of WO₃ and Eu₂O₃, the intensities of the X-ray diffraction peaks of Eu₂(WO₄)₃ increased while that of WO₃ decreased. The photoluminescence intensity of the synthesized phosphors increased with increase in the Eu content when calcined at 900 °C, while it degraded at a higher temperature. Red-emitting single-phase Eu₂(WO₄)₃ powders were successfully obtained when the WO₃ and Eu₂O₃ powders were calcined in the ratio of 3:1. The intensity of the red emission spectra of the Eu₂(WO₄)₃ phosphor was higher than those of the 6, 12, and 24 at.% Eu-added WO₃ composites at excitation wavelengths of 394 and 465 nm. On the other hand, the intensity of emission from the single-phase phosphor was lower than that of the Eu-doped WO₃-Eu₂(WO₄)₃ composites under excitation of UV light at 254 nm. Thus, we propose two prospective phosphors for application as red phosphors at various wavelengths.     

Predicting the mechanical properties of Cu–Al2O3 nanocomposites using machine learning and finite element simulation of indentation experiments

Micromechanics model, finite element (FE) simulation of microindentation and machine learning were deployed to predict the mechanical properties of Cu–Al₂O₃ nanocomposites. The micromechanical model was developed based on the rule of mixture and grain and grain boundary sizes evolution to predict the elastic modulus of the produced nanocomposites. Then, a FE model was developed to simulate the microindentation test. The input for the FE model was the elastic modulus that was computed using the micromechanics model and wide range of yield and tangent stresses values. Finally, the output load-displacement response from the FE model, the elastic modulus, the yield and tangent strengths used for the FE simulations, and the residual indentation depth were used to train the machine learning model (Random vector functional link network) for the prediction of the yield and tangent stresses of the produced nanocomposites. Cu–Al₂O₃ nanocomposites with different Al₂O₃ concentration were manufactured using insitu chemical method to validate the proposed model. After training the model, the microindentation experimental load-displacement curve for Cu–Al₂O₃ nanocomposites was fed to the machine learning model and the mechanical properties were obtained. The obtained mechanical properties were in very good agreement with the experimental ones achieving 0.99 coefficient of determination R2 for the yield strength.     

Hematite crystal growth in high-temperature lead-free multicomponent alkali borosilicate glass frit for red overglaze enamels

To elucidate the crystal growth process of hematite in high-temperature lead-free multicomponent alkali borosilicate glass, which is essentially important to control the color of red overglaze enamels, frit and hematite mixture is heat-treated and subjected to microscopic observations. Hematite particles slightly grew due to sintering at low temperature. Once the glass matrix formed near the softening point of frit, hematite dissolved into glass fluid. Hematite crystal growth concomitantly ensued with decrease in the number of hematite particles via Ostwald ripening as the temperature increased. The grown particles exhibited an anisotropic morphology with straight outlines reflecting crystal planes, the morphology of which is completely different from those grown by sintering and particles prior to heating. These results suggest that comprehensive understanding of frit and hematite from the perspectives of glass science and chemistry as well as powder technology are important to truly control the color of red overglaze enamels.     

Eco-friendly and degradable red phosphorus nanoparticles for rapid microbial sterilization under visible light

Pathogens pose a serious challenge to environmental sanitation and a threat to public health.The frequent use of chemicals for sterilization in recent years has not only caused secondary damage to the environment but also increased pathogen resistance to drugs,which further threatens public health.To address this issue,the use of non-chemical antibacterial means has become a new trend for environmental disinfection.In this study,we developed red phosphorus nanoparticles(RPNPs),a safe and degradable photosensitive material with good photocatalytic and photothermal properties.The red phosphorus nanoparticles were prepared using a template method and ultrasonication.Under the irradiation of simulated sunlight for 20 min,the RPNPs exhibited an efficiency of 99.98%in killing Staphylococcus aureus due to their excellent photocatalytic and photothermal abilities.Transmission electron microscopy and ultraviolet–visible spectroscopy revealed that the RPNPs exhibited degradability within eight weeks.Both the RPNPs and their degradation products were nontoxic to fibroblast cells.Therefore,such RPNPs are expected to be used as a new type of low-cost,efficient,degradable,biocompatible,and eco-friendly photosensitive material for environmental disinfection.     

Improving the luminescence properties and powder morphologies of red-emitting Sr0.8Ca0.19AlSiN3:0.01Eu2+ phosphors for high CRIs white LEDs by adding fluxes

Red-emitting Sr_0.8Ca_0.19AlSiN₃:0.01Eu²⁺ phosphor with halide fluxes for use in the production of white light-emitting diodes (white LEDs) with high-colour rendering indices (CRIs) was prepared through the high-temperature solid-state method. Fluoride (NaF, SrF₂, BaF₂, CaF₂, AlF₃·3H₂O and CeF₃), chloride (NH₄Cl, BaCl₂, MgCl₂, NaCl and LiCl) and composite fluxes (NaF + SrF₂, SrF₂+NH₄Cl and NaF + NH₄Cl) were applied in the phosphors. NaF, SrF₂, NH₄Cl and NaF + SrF₂ fluxes had prominent effects on the characteristics of Sr_0.8Ca_0.19AlSiN₃:0.01Eu²⁺ phosphors. Sr_0.8Ca_0.19AlSiN₃:0.01Eu²⁺ phosphors with various powder morphologies can be obtained through the addition of fluxes, which are conducive for phosphor formation. The powder morphologies of phosphors incorporated with NaF + SrF₂ were preferable to those of powders incorporated with other fluxes. This result indicated that the incorporation of NaF + SrF₂ into Sr_0.8Ca_0.19AlSiN₃:0.01Eu²⁺ yielded phosphors with high luminescent intensity and quantum efficiency, excellent thermal stability, narrow full widths at half-maximum (FWHM, 75.2 nm), uniform rod-like morphologies with large particle sizes (D₅₀ = 16.99 μm) and good particle dispersion. White LEDs with high CRIs were obtained by combining prepared phosphors (NaF + SrF₂ additive) with the commercial green-emitting phosphors Y₃(Al,Ga)₅O₁₂:Ce³⁺ and (Sr,Ba)₂SiO₄:Eu²⁺. White LEDs with Y₃(Al,Ga)₅O₁₂:Ce³⁺ and (Sr,Ba)₂SiO₄:Eu²⁺ phosphors had correlated colour temperatures (CCTs) of 3064 and 3023 K, respectively, and CRIs of 81.8 and 92.4, respectively. Therefore, NaF + SrF₂ can be used as a favourable flux for the production of Sr_0.8Ca_0.19AlSiN₃:0.01Eu²⁺.     

基于深度学习的彩色以及近红外图像去马赛克

单传感器捕获的彩色-近红外（RGB-NIR）图像存在光谱干扰，从而导致重建出的标准彩色图像（RGB）图像与近红外（NIR）图像存在色彩失真以及细节信息模糊。针对这个问题提出一种基于深度学习的去马赛克方法，通过引入跳远连接与稠密连接解决了梯度消失和梯度弥散问题，使得网络更容易训练，并且提升了网络的拟合能力。首先，用浅层特征提取层提取了马赛克图像的像素相关性以及通道相关性等低级特征；然后，将得到的浅层特征图输入到连续多个的残差稠密块以提取专门针对去马赛克的高级语义特征；其次，为充分利用低级特征与高级特征，将多个残差稠密块提取到的特征进行组合；最后，通过全局跳远连接恢复最终的RGB-NIR图像。在深度学习框架Tensorflow上使用公共的图像与视觉表示组（IVRG）数据集、有植被的户外多光谱图像（OMSIV）数据集和森林（Forest）三个公开数据集进行实验。实验结果表明，所提方法优于基于多级自适应残差插值、基于卷积卷积和神经神经网络以及基于深度残差U型网络的主流的RGB-NIR图像去马赛克方法。     

The microstructure of buccal cavity and alimentary canal of Siganus rivulatus: Scanning electron microscope study

The microstructure of the oral cavity and alimentary canal of herbivorous fish Siganus rivulatus collected from the Red Sea were investigated by using scanning electron microscope (SEM). The results showed that S. rivulatus has three types of teeth, tri‐cusped, bi‐cusped, and papilliform. A taste bud (Type I) was recorded in the oropharyngeal cavity. Characteristic styles of microridges on the cell's surface inside the buccal cavity were recorded. Also, the distribution of the mucous cells in the lining of the mouth cavity, alimentary canal was observed. Mucosal folds along the distinct parts of alimentary canal, showed characteristic pattern which was complex in the intestinal mucosa. The results concluded that there are characteristic microstructures according to feeding habitat compared with other bony fishes.     

Hydrocracking and hydrodesulfurization of diesel over zeolite beta-containing NiMo supported on activated red mud

NiMo nanocatalysts supported on activated red mud with different zeolite beta contents were successfully prepared by impregnation technique. Their hydrocracking and hydrodesulfurization activities were evaluated with two different kinds of diesel feed (iso diesel and heavy diesel) in a fixed bed reactor at ambient pressure and 500 °C. Physico-chemical properties of synthesized samples were characterized using the methods of XRF, XRD, FESEM, BET, FTIR and NH₃-TPD. The results indicated that zeolite incorporation resulted in a significant increase in specific surface area (BET result) and acidic strength (TPD result) of nanocatalysts. FESEM analysis confirmed that the particles size of zeolite-containing NiMo/ARM was less than 100 nm and the average size of particles was about 30 nm. Hydrocracking results illustrated that incorporation of zeolite beta improved cracking activity considerably. In addition, NiMo nanocatalyst containing 37.5 wt% of zeolite had the highest yields of desirable products (naphtha, kerosene and diesel) and the highest conversion. Moreover, the flash point and viscosity of the liquid product decreased notably the nanocatalysts with 37.5 wt% and 12.5 wt% of zeolite were able to remove approximately 96% and 72% of the sulfur content of iso diesel and heavy diesel, respectively.     

Relatedness between numerically small Dutch Red dairy cattle populations and possibilities for multibreed genomic prediction

Red dairy breeds are a valuable cultural and historical asset, and often a source of unique genetic diversity. However, they have difficulties competing with other, more productive, dairy breeds. Improving competitiveness of Red dairy breeds, by accelerating their genetic improvement using genomic selection, may be a promising strategy to secure their long-term future. For many Red dairy breeds, establishing a sufficiently large breed-specific reference population for genomic prediction is often not possible, but may be overcome by adding individuals from another breed. Relatedness between breeds strongly decides the benefit of adding another breed to the reference population. To prioritize among available breeds, the effective number of chromosome segments (M_e) can be used as an indicator of relatedness between individuals from different breeds. The M_e is also an important parameter in determining the accuracy of genomic prediction. The M_e can be estimated both within a population and between 2 populations or breeds, as the reciprocal of the variance of genomic relationships. We investigated relatedness between 6 Dutch Red cattle breeds, Groningen White Headed (GWH), Dutch Friesian (DF), Meuse-Rhine-Yssel (MRY), Dutch Belted (DB), Deep Red (DR), and Improved Red (IR), focusing primarily on the M_e, to predict which of those breeds may benefit from including reference animals of the other breeds. All of these breeds, except MRY, are under high risk of extinction. Our results indicated high variability of M_e, especially between M_e ranging from ～3,500 to ～17,400, indicating different levels of relatedness between the breeds. Two clusters are especially important, one formed by MRY, DR, and IR, and the other comprising DF and DB. Although relatedness between breeds within each of these 2 clusters is high, across-breed genomic prediction is still limited by the current number of genotyped individuals, which for many breeds is low. However, adding MRY individuals would increase the reference population of DR substantially. We estimated that between 11 and 133 individuals from other breeds are needed to achieve accuracy of genomic prediction equivalent to using one additional individual from the same breed. Given the variation in size of the breeds in this study, the benefit of a multibreed reference population is expected to be lower for larger breeds than for the smaller ones.