Achieving thermally stable and anti-hydrolytic Sr2Si5N8:Eu2+ phosphor via a nanoscale carbon deposition strategy

Chemical stability of phosphors is critical to the efficiency and lifetime of the white light-emitting diodes. Therefore, many strategies have been adopted to improve the stability of phosphors. However, it is still lack of report on the improvement of thermal stability and hydrolysis resistance of phosphors by a single layer coating. Due to the high transmittance and high chemical inertness of graphene, it was coated on the surface of Sr₂Si₅N₈:Eu²⁺ phosphor by chemical vapor deposition, aiming to improve its thermal stability and hydrolysis resistance. The chemical composition and microstructure of the coating were characterized and analyzed. A nanoscale carbon layer was attached on the surface of Sr₂Si₅N₈:Eu²⁺ phosphor particles in an amorphous state. In coated Sr₂Si₅N₈:Eu²⁺ phosphor, the oxidation degree of Eu²⁺ to Eu³⁺ was significantly suppressed. At the same time, the surface of Sr₂Si₅N₈:Eu²⁺ particle turned from hydrophilic to hydrophobic after carbon coating, and consequently the hydrolysis resistance of Sr₂Si₅N₈:Eu²⁺ phosphor was greatly improved. After tests at 85 °C and 85% humidity for 200 h, the carbon coated Sr₂Si₅N₈:Eu²⁺ phosphor still maintained about 95% of its initial luminous intensity as compared with 35% of the uncoated. By observing the in-situ microstructure evolution of coated phosphor in air-water vapor environment, remained presence of the carbon layer even at 500 °C explained the excellent chemical stability of carbon coated Sr₂Si₅N₈:Eu²⁺ phosphor in complex environment. These results indicate that a nanoscale carbon layer can be used to provide superior thermal stability and hydrolysis resistance of (oxy) nitrides phosphors.     

Fabrication and characterizations of Cr3+-doped ZnGa2O4 transparent ceramics with persistent luminescence

0.5 at.% Cr:ZnGa₂O₄ precursor was synthesized by the co-precipitation method with nitrates as raw materials, using ammonium carbonate as the precipitant. Low-agglomerated Cr:ZnGa₂O₄ powders with an average particle size of 43 nm were obtained by calcining the precursor at 900℃ for 4 h. Using the powders as starting materials, 0.5 at.% Cr:ZnGa₂O₄ ceramics with an average grain size of about 515 nm were prepared by presintering at 1150℃ for 5 h in air and HIP post-treatment at 1100℃ for 3 h under 200 MPa Ar. The in-line transmittance of 0.5 at.% Cr:ZnGa₂O₄ ceramics with a thickness of 1.3 mm reaches 59.5% at the wavelength of 700 nm. The Cr:ZnGa₂O₄ ceramics can be effectively excited by visible light and produce persistent luminescence at 700 nm. For Cr:ZnGa₂O₄ transparent ceramics, the brightness of afterglow was larger than 0.32 mcd/m² after 30 min, which is far superior to that of Cr:ZnGa₂O₄ persistent luminescence powders.     

A Tradeoff Between Accuracy and Speed for K-Means Seed Determination

With a sharp increase in the information volume, analyzing and retrieving this vast data volume is much more essential than ever. One of the main techniques that would be beneficial in this regard is called the Clustering method. Clustering aims to classify objects so that all objects within a cluster have similar features while other objects in different clusters are as distinct as possible. One of the most widely used clustering algorithms with the well and approved performance in different applications is the k-means algorithm. The main problem of the k-means algorithm is its performance which can be directly affected by the selection in the primary clusters. Lack of attention to this crucial issue has consequences such as creating empty clusters and decreasing the convergence time. Besides, the selection of appropriate initial seeds can reduce the cluster’s inconsistency. In this paper, we present a new method to determine the initial seeds of the k-mean algorithm to improve the accuracy and decrease the number of iterations of the algorithm. For this purpose, a new method is proposed considering the average distance between objects to determine the initial seeds. Our method attempts to provide a proper tradeoff between the accuracy and speed of the clustering algorithm. The experimental results showed that our proposed approach outperforms the Chithra with 1.7% and 2.1% in terms of clustering accuracy for Wine and Abalone detection data, respectively. Furthermore, achieved results indicate that comparing with the Reverse Nearest Neighbor (RNN) search approach, the proposed method has a higher convergence speed.     

A comprehensive review of image analysis methods for microorganism counting: from classical image processing to deep learning approaches

Microorganisms such as bacteria and fungi play essential roles in many application fields, like biotechnique, medical technique and industrial domain. Microorganism counting techniques are crucial in microorganism analysis, helping biologists and related researchers quantitatively analyze the microorganisms and calculate their characteristics, such as biomass concentration and biological activity. However, traditional microorganism manual counting methods, such as plate counting method, hemocytometry and turbidimetry, are time-consuming, subjective and need complex operations, which are difficult to be applied in large-scale applications. In order to improve this situation, image analysis is applied for microorganism counting since the 1980s, which consists of digital image processing, image segmentation, image classification and suchlike. Image analysis-based microorganism counting methods are efficient comparing with traditional plate counting methods. In this article, we have studied the development of microorganism counting methods using digital image analysis. Firstly, the microorganisms are grouped as bacteria and other microorganisms. Then, the related articles are summarized based on image segmentation methods. Each part of the article is reviewed by methodologies. Moreover, commonly used image processing methods for microorganism counting are summarized and analyzed to find common technological points. More than 144 papers are outlined in this article. In conclusion, this paper provides new ideas for the future development trend of microorganism counting, and provides systematic suggestions for implementing integrated microorganism counting systems in the future. Researchers in other fields can refer to the techniques analyzed in this paper.

     

Effect of malondialdehyde oxidation on structure and physicochemical properties of amandin

Oil, accounting for 45% of almonds, is easily oxidised and can further induce the protein oxidation to reduce their quality. Structure and physicochemical properties of amandin, the main water-soluble protein in almonds, inducing oxidation by malondialdehyde (MDA) were investigated. The results showed that the content of carbonyl group increased from 5.23 to 33.25 nmol mg⁻¹ of protein with the increase in MDA concentration (P < 0.05). However, the sulphydryl content, surface hydrophobicity, particle size and the absolute value of ζ-potential first increased and then decreased. Fourier-transformed infrared spectroscopy (FT-IR) confirmed that the structure of amandin changed from order to disorder. Fluorescence spectroscopic analysis revealed that mild oxidation (0–0.1 mmol L⁻¹ MDA) exposed hydrophobic groups of the protein. Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) suggested that protein oxidation promoted crosslinking between protein molecules. Furthermore, protein oxidation markedly declined the total amino acid content of amandin (P < 0.05). In conclusion, MDA oxidation changed the structure and amino acid content of amandin, and caused the protein aggregate and crosslink through hydrophobic interaction and electrostatic interaction.     

Total Focusing Method Approach of Ultrasonic Phased Array Based on Compressed Sensing

Russian Journal of Nondestructive Testing - Nondestructive testing and evaluation technology of the total focusing method (TFM) based on full matrix capture (FMC) is a hot spot in the current array...     

A review on direct synthesis of dimethoxymethane

Polyoxymethylene dimethyl ethers are recognized as the prospective diesel additive to decrease the pollutant emission from the light-duty vehicles, which can be polymerize form the monomer of dimethoxymethane (DMM). The industrial synthesis of DMM is mainly involved two-step process: methanol is oxidized to form the formaldehyde in fixed bed reactor and then reacted with the generated formaldehyde through acetalization in continuous stirred-tank reactor. Due to huge energy consumption, this typical synthesis route of DMM needs to be upgraded and more green routes should be determined. In this review, four state-of-the-art one-step direct synthetic routes, including two upgrading routes (methanol direct oxidation and direct dehydrogenation) and two green routes (methanol diethyl ether direct oxidation and carbon oxides direct hydrogenation), have been summarized and compared. Combination with the reaction mechanism and catalytic performance on the different catalysts, the challenges and opportunities for every synthetic route are proposed. The relationships between catalyst structure and property in different synthesis strategy are also investigated and then the suggestions of the design of catalyst are given about future research directions that efforts should be made in. Hopefully, this review can bridge the gap between newly developed catalysts and synthesis technology to realize their commercial applications in the near future.     

钕铁硼化学镀防护及在模拟海洋大气环境中的腐蚀行为

采用化学镀方法在钕铁硼表面分别制备Ni-P合金镀层、Ni-Mo-P合金镀层、Ni-P/PTFE复合镀层和Ni-Mo-P/PTFE复合镀层,并研究了不同化学镀层在模拟海洋大气环境中的腐蚀行为。结果表明:Ni-P合金镀层、Ni-Mo-P合金镀层、Ni-P/PTFE复合镀层和Ni-Mo-P/PTFE复合镀层都完整覆盖钕铁硼表面,它们的粗糙度差别不大,在模拟海洋大气环境中的腐蚀失重都低于钕铁硼的腐蚀失重,容抗弧半径增大且电荷转移电阻有不同程度的提高。与Ni-P合金镀层和Ni-Mo-P合金镀层相比,Ni-P/PTFE复合镀层和Ni-Mo-P/PTFE复合镀层具有优良的耐腐蚀性能,原因在于PTFE颗粒较均匀的沉积在镀层表面增加一道屏蔽层,也起到阻碍腐蚀介质渗透腐蚀的作用。尤其是Ni-Mo-P/PTFE复合镀层,其表面更致密,PTFE颗粒沉积更均匀,能更有效延缓腐蚀介质与钕铁硼接触,显著提高钕铁硼在模拟海洋大气环境中的耐腐蚀性能。     

Co?N graphene encapsulated cobalt catalyst for H2O2 decomposition under acidic conditions

Hydrogen peroxide (H₂O₂) has been listed as one of the 100 most important chemicals in the world. However, huge amount of residual H₂O₂ is hard to timely decomposed into O₂ and H₂O under acidic condition, easily resulting in explosion hazard. Here, we reported a core–shell structure catalyst, that is graphene with Co N structure encapsulated Co nanoparticles. Co N graphene shell serves as the active site for the H₂O₂ decomposition, and Co core further enhance this decomposition. Benefiting from it, the H₂O₂ decomposition were close to 100% after 6 cycles without pH adjustment, which increased 6 orders of magnitude compared with no catalyst. At the same time, the O₂ generation reached 99.67% in 2 h with little metal leaching, and ·OH has been greatly inhibited to only 0.08%. This work can cleanly remove H₂O₂ with little deep oxidation and protect the process of H₂O₂ utilization to achieve a safer world.