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In this paper, the formation principle of hydrophobic phenomenon, the preparation and applications of hydrophobic materials are introduced. The super-hydrophobic material is a novel material with wide application and prospect. The application of status of super-hydrophobic materials in industrial and agricultural production, medical and health fields and people's daily life, in recent years, which was studied, and the prospect of development was systematically summarized.

This paper reviews the definition and excellent properties of metal glass briefly. And it lists the preparation methods of metal glass. Furthermore, the urgent problems and the main research directions of metal glass are summarized, the development history of metal glass is reviewed, and the application direction of metal glass is sorted.

As a consequence of multi-components, the high entropy alloys embodied serious cocktail party effect and lattice distortion. So high entropy alloys have high strength and hardness possess many comprehensive properties such as thermostability and corrosion resistance. Because of excellent mechanical properties and chemical properties, high entropy alloys have immeasurable potential of development. This paper mainly introduces the properties, preparations and applications of high entropy alloys, and finally summarizes them.

The helical insertion behavior of poly(para-phenylene) (PP) chains into confined cylindrical slits constructed by two carbon nanotubes (CNTs) with different diameters is studied by molecular dynamics simulations. The contribution of system energy and each energy component to helical self-assembly is discussed to further explain the conditions, driving force and mechanism. The width and length of the slit, the diameter of the outer tube and the temperature have a great impact on the helical insertion of PP chains. Two equations are proposed to confirm the diameter and the distances between the PP helix and the inner and outer walls of the given CNTs. The helical self-assembly of PP with different numbers of chains inserted into the slits is further studied. This study has a great benefit in understanding the conformational behavior of polymers, even biological macromolecules in confinements. [ABSTRACT FROM AUTHOR]

This technical correspondence presents a multiple-feature and multiple-kernel support vector machine (MFMK-SVM) methodology to achieve a more reliable and robust segmentation performance for humanoid robot. The pixel wise intensity, gradient, and C1 SMF features are extracted via the local homogeneity model and Gabor filter, which would be used as inputs of MFMK-SVM model. It may provide multiple features of the samples for easier implementation and efficient computation of MFMK-SVM model. A new clustering method, which is called feature validity-interval type-2 fuzzy C-means (FV-IT2FCM) clustering algorithm, is proposed by integrating a type-2 fuzzy criterion in the clustering optimization process to improve the robustness and reliability of clustering results by the iterative optimization. Furthermore, the clustering validity is employed to select the training samples for the learning of the MFMK-SVM model. The MFMK-SVM scene segmentation method is able to fully take advantage of the multiple features of scene image and the ability of multiple kernels. Experiments on the BSDS dataset and real natural scene images demonstrate the superior performance of our proposed method. [ABSTRACT FROM PUBLISHER]