Applications of analytical electron microscopy to guide the design of boron carbide

Compositional analysis of boron carbide on nanometer length scales to examine or interpret atomic mechanisms, for example, solid-state amorphization or grain-boundary segregation, is challenging. This work reviews advancements in high-resolution microanalysis to characterize multiple generations of boron carbide. First, ζ-factor microanalysis will be introduced as a powerful (scanning) transmission electron microscopy ((S)TEM) analytical framework to accurately characterize boron carbide. Three case studies involving the application of ζ-factor microanalysis will then be presented: (1) accurate stoichiometry determination of B-doped boron carbide using ζ-factor microanalysis and electron energy loss spectroscopy, (2) normalized quantification of silicon grain-boundary segregation in Si-doped boron carbide, and (3) calibration of a scanning electron microscope X-ray energy-dispersive spectroscopy (XEDS) system to measure compositional homogeneity differences of B/Si-doped arc-melted boron carbides in the as-melted and annealed conditions. Overall, the improvement and application of advanced analytical tools have helped better understand processing–microstructure–property relationships and successfully manufacture high-performance ceramics.     

Evolution and stability of 2-mercaptobenzimidazole inhibitor film upon Al alloy 6061

Journal of Applied Electrochemistry - Organic corrosion inhibitors have become competent alternatives to hazardous chrome conversion coatings due to their rapid adsorption over metal surfaces in...     

Subdivision based isogeometric analysis for geometric flows

We present a new isogeometric analysis (IGA) approach based on extended Loop subdivision scheme for solving various geometric flows defined on subdivision surfaces. The studied flows include the second-order, fourth-order, and sixth-order geometric flows, such as averaged mean curvature flow, constant mean curvature flow, and minimal mean-curvature-variation flow, which are generally derived by minimizing the associate energy functionals with $L^2$-gradient flow respectively. The geometric flows are discretized by means of subdivision based IGA, where the finite element space is formulated by the limit form of the extended Loop subdivision for different initial control meshes. The basis functions, consisting of quartic box-splines corresponding to each subdivided control mesh, are utilized to represent the geometry exactly. For the cases of the evolution of open surfaces with any shape boundary, high-order continuous boundary conditions derived from the mixed variational forms of the geometric flows should be implemented to be consistent with the isogeometric concept. For time discretization, we adopt an adaptive semi-implicit Euler scheme. By several numerical experiments, we study the convergence behaviors of the proposed approach for solving the geometric flows with high-order boundary conditions. Moreover, the numerical results also show the accuracy and efficiency of the proposed method.     

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.

     

Measuring the disparity among scientific disciplines using Library of Congress Subject Headings

Scientometrics - Examining the relationships among scientific disciplines is important today, but existing methods are limited by the contents and structure of their bibliographic databases. We...     

Ferulic acid and EGCG alter the structural characteristics of ovalbumin and its application in mineral loading

This study aims to fabricate mineral-loading nanocarriers using natural materials. The interaction patterns between ovalbumin (OVA) and four water-soluble polyphenols, namely ferulic acid (FA), (-)-Epigallo-catechin 3-gallate (EGCG), gallic acid (GA) and epicatechin (EC), were investigated. Results showed that the optimised conditions for preparing stable OVA–polyphenol complexes are at the OVA–polyphenol ratio of 4:1 at pH 6, under which OVA–FA and OVA–EGCG showed the highest stability and mineral-loading capacity among four OVA–polyphenol complexes. The fluorescence results indicated that the addition of EGCG and FA induced a significant fluorescence quenching to OVA. The interaction between OVA and polyphenols involved hydrogen bonding, hydrophobic interaction and electrostatic interaction. Fourier transform infrared spectroscopy (FTIR) analysis suggested that both FA and EGCG enhanced the stability and orderliness of the structure of OVA. The transmission electron microscopy images also exhibited the spherical structure of OVA after the addition of FA and EGCG. Furthermore, scanning electron microscope–energy dispersive X-ray spectrum results suggested that OVA–FA and OVA–EGCG complexes were better mineral carriers than OVA–GA and OVA–EC. This study may serve as the theoretical support for the promising application of OVA in the fabrication of mineral-loading nanocarriers in functional food and pharmaceutic.