The application relates to a method for preparing a deformable reinforcing metal matrix composite material by a pressure infiltration technology, and relates to a method for preparing a metal matrix composite material. In order to solve the problems of poor plasticity of the metal matrix composite material and difficulty in preparing a deformable reinforcing aluminum matrix composite material by a self-exhaustion pressure infiltration technology, the application mixes reinforcing body powder with polysilazane, and then sintering, the polysilazane is cracked at high temperature and a ceramic skeleton is generated, the structural strength of the preform in a high-temperature state is improved, and the success rate of the self-exhaustion pressure infiltration process for preparing the deformable reinforcing metal matrix composite material is effectively improved. The application realizes the function of preparing a heterogeneous aluminum alloy by the pressure infiltration technology, and has better strength-plasticity matching compared with a homogeneous alloy with the same composition.
The invention discloses a lignin-based lithiumion battery silicon-carbon negative electrode material and a preparation method and application thereof, comprising the following steps: (1) adding nano siliconpowder and a surfactant to water, ultrasonicating and drying to obtain positively charged nano siliconpowder; (2) adding lignin to a low eutectic solvent, stirring for 2-8 hours, and obtaining a lignin solution; (3) mixing and stirring the positively charged nano siliconpowder and the lignin solution, so that the nano silicon powder is completely and evenly dispersed in the lignin solution, and the obtained mixed solution is calcined at high temperature under a protective atmosphere to obtain a lignin-based silicon-carbon composite material; (4) ball milling the lignin-based silicon-carbon composite material with graphite, and calcining at high temperature again to obtain a lignin-based lithiumion battery silicon-carbon negative electrode material. The invention solves the problem that the volume expansion of silicon as a negative electrode material for lithiumion batteries causes the electrode material to collapse easily and has poor conductivity, and improves the specific capacity, first coulomb efficiency and rate performance of lithium ion batteries.
The invention relates to a preparation method of hyaluronic acidoligosaccharide with controllable polymerization degree and a derivative thereof. The invention firstly provides a method for preparing the hyaluronic acid oligosaccharides and the derivatives thereof through cooperation of chondroitin synthase AuCS, hyaluronic acid synthase PmHAS and chondroitinlyase ODV-E66, the hyaluronic acid oligosaccharides or the derivatives thereof with any polymerization degree can be obtained, the defects of traditional physical or chemical degradation and enzymolysis methods are overcome, the diversity of oligosaccharide structures is enriched, and the application prospect is wide. And a foundation is laid for research on functions and characteristics of the hyaluronic acid oligosaccharides with different polymerization degrees and the derivatives of the hyaluronic acid oligosaccharides. Then, on the basis of the method, the hyaluronic acid oligosaccharide and the derivative thereof are prepared by utilizing a chondroitin synthase AuCS mutant, a hyaluronic acid synthase PmHAS mutant and chondroitin lyase ODV-E66, so that the synthesis efficiency and the yield of the product are greatly improved, and rapid, safe and large-scale preparation of the hyaluronic acid oligosaccharide and the derivative thereof is realized.
The application discloses a semantic segmentation method based on phase profile constraint and belongs to the technical field of computer vision. The method uses a calibrated camera-projectorsystem to collect a two-dimensional texture image and a deformed fringe image of a to-be-measured scene under the same field of view; the deformed fringe image is solved through multi-step phase shifting and Gray code technology to obtain an absolute phase distribution and calculate a gradient field; according to a preset mutation condition, a physical edge profile reflecting the depth change of an object is extracted from the gradient field; the physical edge profile is mapped into the two-dimensional texture image based on the corresponding relationship of pixel coordinates to accurately define the semantic object area, the corresponding category label is given, and finally a semantic labelmask image is generated. The application uses physical phase information to correct the uncertainty of visual texture edges, effectively solves the edge extraction problem under a complex light scene, realizes the automatic generation of semantic segmentation data, and improves the training precision and robustness of a semantic segmentation model.