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In this paper a novel method for fabrication of TiB2 coatings on graphite substrates by electrophoretic deposition of TiB2 nanoparticles in NaF-AlF3 melt at 980°C has been explored. With an applied cell voltage of 1.2 V (i.e. electric field 0.6 V/cm), a flat and dense TiB2 coating with a thickness of around 50 μm has been prepared. It was found that the surface consisted of TiB2 flakes with a nanoscale size. In addition, the average value of hardness of the TiB2 coating was determined as 3585 ± 139 HV0.1 (36.6 ± 1.4GPa) measured by a Vickers micro-hardness tester.

In order to investigate the effect and underlying mechanism of deacetylated konjac glucomannan (DKGM) on the structure and gel properties of pork myofibrillar protein (MP), the changes in the gel strength, water retention, water distribution, microstructure, secondary and tertiary structures and gel molecular forces of MP were analyzed after the addition of DKGM at different levels (0%, 0.125%, 0.25%, 0.5% and 1%). The results showed that the gel strength of MP increased with the increase of DKGM addition, reaching the maximum at an addition level of 0.25%, which was 1.55 times higher than that of the control group. The addition of DKGM could retard the flow of water, thus improving the gel water-holding capacity. Cold-field scanning electron microscopy revealed that the addition of DKGM could promote the formation of more uniform and dense network structures in MP gels. The structure and force analysis showed that the addition of an appropriate amount of DKGM could promote the unfolding of MP molecules and the exposure of hydrophobic groups, increase the content of active sulfhydryl groups, induce α-helix-to-β-fold transition, enhance the hydrophobic interactions and disulfide bonds of MP gels, and thus improve the gel strength and water-holding capacity.

Objective: A BP neural network model was established to accurately determine the maturity of dough fermentation. Methods: Used machine vision technology to collect and process the pictures of bread fermentation process, obtained the quantitative information of the pictures, and a prediction model was established for bread fermentation degree based on BP neural network. Taking the time, area, instantaneous velocity, expansion rate, gray value energy, gray value relationship, gray value uniformity and gray value contrast as the input neurons, the regression model of relevant parameters was established. Results: The correlation between the above characteristic parameters and the fermentation process of bread was determined, which can effectively characterize the fermentation degree of bread; The results show that the accuracy of the prediction model based on BP neural network is 88.41%. Conclusion: The model can accurately determine the degree of bread fermentation and effectively improve the quality consistency in industrial bread production.

Konjac glucomannan (KGM) is a water-soluble natural plant polysaccharide from Konjac tubers, a special resource in China. It has good water absorption and thickening properties. Due to the complex structure, large molecular weight, and strong hydrophilicity of the characteristic acetyl group, KGM-based materials have poor moisture barrier properties and poor mechanical properties, further limiting their applications. In the early stage, it was found that the rigidity and flexibility of Konjac glucomannan particle molecular chain may affect the mechanical stability of its grain state. This strange molecular rigidity and flexibility may be due to the dynamic change of molecular chain to form stable KGM particles. It is speculated that the change of molecular rigid and flexible structure can improve the stability of molecular chain of KGM particles and obtain KGM particles with good mechanical properties. This paper will deeply analyze the research process of "KGM particle molecular rigidity and flexible structure → effect of molecular rigidity and flexible structure on KGM particle mechanical stability → molecular dynamics simulation interactive visual analysis → experimental verification and model evaluation → strengthening the mechanical properties of KGM based materials". The mechanical stability mechanism of Konjac glucomannan particle state structure formation and its molecular rigidity and flexible regulation behavior were revealed. The dynamic regulation was carried out by computer simulation to explore the relationship between them. The purpose is to reveal the mechanical stability mechanism of Konjac glucomannan particle state and lay a theoretical foundation for the bottleneck problem faced by Konjac refined powder in the processing process and its molecular stiffness and flexibility regulation.