9503 results about "Metallic materials" patented technology

The invention belongs to the technical field of metal material engineering, and relates to a light high-toughness low-cost aluminum alloy and a preparation method thereof.The alloy comprises, by mass, 7.0%-9.2% of Mg, 2.5%-4.0% of Zn, 0.06%-0.20% of Zr, 0.01%-0.03% of Sb, main impurities including Fe smaller than or equal to 0.15%, Si smaller than or equal to 0.12%, other single impurities smaller than or equal to 0.05%, the total impurity smaller than or equal to 0.15% and the balance Al. Compared with 2xxx series and 7xxx series aluminum alloys, the alloy has certain advantages in the aspects of density, specific strength, ductility, corrosion resistance and the like, and has a remarkable cost advantage compared with a low-density aluminum-lithium alloy, so that the core competitiveness of an alloy product is improved, and the alloy product has the potential of becoming a next-generation commercial aluminum alloy.

The invention belongs to the technical field of material and coating corrosion tests, and relates to a whole sea area atmospheric environment comprehensive simulation test system, which adopts an integrated structural design, and performs integrated coupling of various environmental test simulation capabilities on the basis of a single-function test box. The device has the test capabilities of metal material corrosion acceleration test, organic composite material and coating aging evaluation and the like, can simulate the global marine atmospheric environment and coupling of multiple factors such as air temperature, humidity, salt mist and ultraviolet irradiation, can perform comprehensive test evaluation on the whole-sea-area marine atmospheric environment of typical materials, avoids the problem of inconvenient operation of corrosion tests, and has a wide application prospect. The device can be used for corrosion and ultraviolet aging tests of conventional marine atmospheric environment corrosion media, polar regions, tropical regions and other extreme marine atmospheric environments, and material corrosion tests for simulating marine splash zones, tidal range zones and the like. The device is simple in structure and convenient to operate, and coupling of multiple factors of high and low temperature, humidity, salt mist, ultraviolet illumination and periodic infiltration can be achieved.

The invention belongs to the field of metal materials, and particularly relates to a high-strength hot-rolled pickled steel plate for an automobile chassis and a production method thereof. The steel plate is mainly suitable for manufacturing automobile chassis structural parts. The steel comprises the following chemical components: C, Si, Mn, Al, V, Ni, Cu, Cr, Pt and Y, P is limited to be less than or equal to 0.015%, S is limited to be less than or equal to 0.005%, N is limited to be less than or equal to 0.006%, and the balance is Fe and inevitable impurities. The yield strength of the steel plate ranges from 498 MPa to 552 MPa, the tensile strength ranges from 608 MPa to 643 MPa, the transverse elongation A ranges from 33% to 38%, the steel plate is qualified after transverse cold bending by 180 degrees D = a, the surface quality is good, oxide scale stripes and chromatic aberration defects are avoided, the surface roughness Ra ranges from 1.10 micrometers to 1.35 micrometers, and the steel plate has excellent corrosion resistance.

According to the automobile material visual defect identification method and system provided by the invention, defect risk dynamic grading is realized through a three-dimensional weight matrix, and the safety protection capability is remarkably improved according to differentiated management and control of part positions and process importance. A material self-adaptive processing mechanism is adopted, reflection interference is restrained on the metal surface, tiny defect recognition is enhanced through non-metal fusion texture and frequency domain features, and multiple automobile materials are detected and accurately recognized; deformable convolution is adopted to dynamically adapt to the curvature change of the metal plate curved surface, complex structure defect features are accurately captured, and the false alarm rate is reduced. A block chain evidence storage and generative adversarial network collaborative closed-loop quality tracing system is constructed, defect full-life-cycle tracing and model autonomous evolution are realized, and the accuracy, reliability and system adaptability of defect identification in a multi-material mixed manufacturing scene are comprehensively improved.

The invention discloses an analysis method and system for a dynamic recrystallization structure form of a titanium alloy based on machine learning and a medium, and belongs to the technical field of metal material microstructure quantitative characterization, a Gleeble thermal compression test is processed on a titanium alloy to be tested, multi-modal data is collected, a DRX probability graph is output based on a DRX segmentation model, and then the characteristics of DRX are extracted. And respectively inputting the DRX features into the first-level classifier, carrying out PCA dimension reduction processing, splicing and fusing the prediction probability and the features after dimension reduction, and inputting the spliced and fused features into a second-level classifier to output a two-dimensional DRX segmentation map. Based on the FIB-SEM tomography sequence image, reconstructing a three-dimensional model of the DRX crystal grain so as to carry out consistency verification on the two-dimensional DRX segmentation image; and evaluating a correlation coefficient of the three-dimensional model and the two-dimensional DRX model, and finally carrying out three-dimensional visualization on the space aggregation of the DRX crystal grains. According to the method, the automation degree and efficiency of dynamic recrystallization proportion and type identification are remarkably improved.

The invention belongs to the field of metal materials, and particularly relates to a 448 MPa grade hot-rolled pickled steel plate for an automobile and a production method of the 448 MPa grade hot-rolled pickled steel plate. The steel plate is mainly suitable for manufacturing automobile chassis structural parts. The steel comprises the following chemical components: C, Si, Mn, Al, Nb, Ta, Zr and Y, P is limited to be less than or equal to 0.015%, S is limited to be less than or equal to 0.005%, N is limited to be less than or equal to 0.003%, and the balance is Fe and inevitable impurities. The yield strength of the steel plate is larger than or equal to 308 MPa, the tensile strength is larger than or equal to 448 MPa, the transverse elongation A is larger than or equal to 42%, the hole expansion rate is larger than or equal to 125%, transverse cold bending is conducted by 180 degrees, D = a, the steel plate is qualified, the surface quality is good, oxide scale stripes and chromatic aberration defects are avoided, the surface roughness Ra is 1.00-1.40 micrometers, and the steel plate has good corrosion resistance.

The invention relates to the technical field of metal material detection, in particular to a titanium alloy bar machining quality detection method and system, and the method specifically comprises the steps: carrying out the superpixel segmentation of the section of a titanium alloy bar, constructing a mirror image edge texture saliency value of a superpixel block based on the proportion of edge points in the superpixel block and the edge gradient, and carrying out the detection of the machining quality of the titanium alloy bar. Constructing the mirror image texture intensity of the titanium alloy bar by combining the gray level distribution concentration characteristics of the titanium alloy bar, and performing image segmentation on the section of the titanium alloy bar; and in each segmented region, based on the edge line fuzzy degree difference and the pixel gray level difference of each super-pixel block and the rest of super-pixel blocks, combining a mirror image edge texture saliency value to construct a segregation evaluation value of each super-pixel block, and based on the segregation evaluation value, carrying out titanium alloy bar segregation quality defect detection. The titanium alloy bar segregation defect identification capability is enhanced, the titanium alloy bar segregation defect detection accuracy under the titanium alloy bar mirror image scene is improved, potential problems can be found earlier, missing detection is avoided, and the defective rate is reduced.

The invention provides a titanium plate performance analysis method and system, and relates to the technical field of metal material detection.The method comprises the steps that an optical scanner is adopted to establish a three-dimensional structure on the surface of a titanium plate, and test areas are divided; synchronously acquiring stress, hardness and conductivity data of a test point by using a multi-probe collaborative detection device; constructing a dual-branch feature extraction network, wherein the dual-branch feature extraction network comprises a surface topography feature branch and a physical feature branch; performing statistical integration on the features in the test area, calculating distribution features and determining a weight coefficient; and generating a performance analysis result through feature fusion and a multi-task output layer, and finally determining the performance grade of the titanium plate. According to the method, deep fusion of morphology information and physical characteristics is realized, and the accuracy and reliability of titanium plate performance evaluation are improved.

The invention discloses a metal fatigue life prediction method under laser shock peening, and relates to the technical field of metal material fatigue life prediction. The invention discloses a metal fatigue life prediction method under laser shock peening. The metal fatigue life prediction method comprises the following steps of roughness model construction, roughness evolution simulation, roughness value calculation, material attribute endowing and fatigue life prediction. According to the method, the real surface is subjected to laser shock peening, the roughness evolution condition of the metal surface subjected to laser shock peening is accurately predicted, and then the fatigue life is predicted by adopting a method of combining a Basic-Manson-Coffin formula and continuous damage mechanics. The method fully considers the local complex stress-strain state under the evolution of the roughness surface microstructure after laser shock peening, truly simulates the fatigue progressive damage process of the sample after comprehensive consideration of laser shock peening, and can effectively improve the prediction precision of the fatigue life of the metal after laser shock peening.

The invention relates to the technical field of semiconductors, in particular to a device integrated with a deep trench isolation structure and a preparation method of the device. The preparation method comprises the steps that a semiconductor structure is provided, the semiconductor structure comprises a substrate, a gate material layer stacked on the surface of the substrate and a mask layer stacked on the gate material layer, and a functional element of the semiconductor device is formed in the substrate; forming a deep trench in the semiconductor structure, wherein the deep trench penetrates through the mask layer and the gate material layer and goes deep into the substrate; the deep trench is filled to form a deep trench isolation structure, the deep trench isolation structure comprises a filling structure, the filling structure is not higher than the surface of the substrate, and the material of the filling structure is a conductive non-metal material; patterning and etching the gate material layer to form a gate structure; and removing the mask layer. According to the invention, the preparation process of the deep trench isolation structure can be integrated into the standard process for preparing the gate structure of devices such as a BCD, the integration process of deep trench isolation is simplified, and the preparation cost is reduced.

The invention belongs to the field of metal materials, and particularly relates to high-elongation and high-forming passenger car steel and a production method thereof.The steel plate is mainly suitable for manufacturing passenger car structural parts, the steel comprises the following chemical components of C, Si, Mn, Al, V, Ta, Bi, Sb, Ni, Pt and Y, P is limited to be smaller than or equal to 0.015%, S is limited to be smaller than or equal to 0.005%, N is limited to be smaller than or equal to 0.006%, and the balance Fe and inevitable impurities. The steel plate is obtained by adopting hot rolling, EPS, continuous annealing and finishing processes, the processes of pickling and cold rolling are reduced, the production process is simplified, the production cost is reduced, and the environment is not polluted.

The invention relates to the technical field of metal material heat treatment quality detection, in particular to a metal material rapid annealing effect detection method based on acoustic response, which comprises the following steps: step 1, acoustic excitation and synchronous acquisition; step 2, multi-physics field coupling compensation: calculating the phase compensation amount of the vibration signal based on the temperature distribution data and the acoustic characteristic temperature dependence of the material; the method comprises the following steps: acquiring an environment vibration frequency spectrum through a production line mechanical vibration monitoring device, and separating an excitation response component from an original vibration signal by adopting adaptive filtering; 3, annealing sensitive feature extraction; 4, dynamic quality mapping and control: inputting the real-time feature vector into a pre-trained machine learning model, and outputting a recrystallization proportion and a grain size; and when the output parameter exceeds the process threshold value, the control parameter adjustment of the annealing furnace is triggered. Through a non-destructive and accurate acoustic monitoring technology, the annealing effect of the metal material can be efficiently and accurately monitored in a high-speed, high-noise and strong-interference industrial environment.

The invention discloses a metallographic detection method and system based on image recognition, and belongs to the technical field of metallographic detection. The detection method comprises the following steps: image acquisition and preprocessing: acquiring a metal metallographic image by an optical microscope, performing median filtering and denoising, and extracting a grain boundary by adaptive binarization; and field-of-view and scale calibration: selecting a corresponding scale according to the shooting magnification. The multi-parameter automatic measurement comprises grain size analysis, grain size rating, second phase analysis and intelligent report generation, a report is automatically generated based on a preset template and comprises an original image, a binary image, measurement data and a histogram, and report fonts and layout can be adjusted in real time through a visual control. According to the detection method disclosed by the invention, the efficiency, the precision and the reliability of metallographic structure analysis of the metal material are remarkably improved through the full-process design of image acquisition standardization, preprocessing intellectualization, data analysis automation and report generation templating.

The invention belongs to the field of metal materials, and particularly relates to a high-elongation 288MPa-grade hot-rolled pickled steel plate for an automobile and a production method thereof. The steel plate is mainly suitable for manufacturing automobile chassis structural parts. The steel comprises the chemical components of C, Si, Mn, Al, Ti, Zr, Ni, Pt and Y, P is limited to be smaller than or equal to 0.015%, S is limited to be smaller than or equal to 0.005%, N is limited to be smaller than or equal to 0.003%, and the balance is Fe and inevitable impurities. The steel plate has excellent mechanical properties, the yield strength of the steel plate is larger than or equal to 238 MPa, the tensile strength is larger than or equal to 288 MPa, the transverse elongation A is larger than or equal to 48%, the hole expansion rate is larger than or equal to 132%, transverse cold bending is conducted by 180 degrees, D = a, the steel plate is qualified, the surface quality is good, oxide scale stripes and chromatic aberration defects are avoided, the surface roughness Ra is 1.08-1.48 micrometers, and the steel plate has good corrosion resistance.

The invention relates to a data-driven deformation nickel-based superalloy multi-objective performance reverse design optimization method, which belongs to the technical field of metal material design and development, and comprises the following steps: calculating a stable high-strength deformation nickel-based superalloy system based on a first principle, and on this basis, calculating a deformation nickel-based superalloy system; constructing a deformed nickel-based superalloy component design space based on the knowledge of the nickel-based superalloy field; based on a deformed nickel-based superalloy component design space, the deformed nickel-based superalloy component design space is reduced by adopting an empirical formula in combination with thermodynamic high-throughput calculation to obtain the reduced deformed nickel-based superalloy component design space, and based on the reduced deformed nickel-based superalloy component design space, based on machine learning and a genetic algorithm, the deformation nickel-based superalloy component design space is obtained. And a deformed nickel-based high-temperature alloy reverse design model is established, and the deformed nickel-based high-temperature alloy with the target performance is screened. Compared with the prior art, the oriented development method for the high-strength and high-toughness nickel-based high-temperature alloy is achieved by fusing cross-scale calculation, domain knowledge constraint and machine learning reverse design.

A charging inlet (1) comprises: a rear case (40) that is connected to an inlet housing (20) retaining a plurality of terminals (10); and a filling section (80). The rear case (40) comprises a rear case body (40a) that has a housing section (41) housing at least base sections (12) of the plurality of terminals (10) and a plurality of inner terminals (70), and fins (46) that are provided so as to be exposed to the outside of the rear case body (40a). The filling section (80) is molded or formed from an insulating filler material with which the remaining portion of the housing section (41) is filled. The material of the rear case (40a) is an electrically insulating, thermally conductive resin resulting from filling a thermoplastic resin with a carbon-based or ceramic-based filler. The fins (46) are formed from a metal material, and are integrated with the rear case body (40a) by insert molding.

The present application relates to the field of metal material manufacturing, and in particular to a GH4151 alloy bar and a preparation method therefor and a use thereof. The method comprises the following steps: (1) carrying out homogenization heat treatment on a GH4151 alloy cast ingot to obtain a heat treated bar; (2) forging the heat treated bar to obtain a forged bar; (3) carrying out hot rolling treatment on the forged bar to obtain a hot rolled bar; (4) carrying out solution treatment on the hot rolled bar to obtain a solid solution bar; (5) carrying out cold drawing treatment on the solid solution bar to obtain a cold drawn bar; and (6) carrying out aging treatment on the cold drawn bar to obtain a GH4151 alloy bar. According to the GH4151 alloy bar prepared in the present application, grains can be effectively refined, the surface dimensional precision is improved, and the tensile strength of the prepared GH4151 alloy bar is improved, so that the GH4151 alloy bar has excellent mechanical properties.

The invention belongs to the field of advanced inorganic non-metallic materials, and relates to a 3D special-shaped glass bending tempering forming method and system, which comprises the following steps: according to initial stress distribution data, partitioning a glass curved surface by adopting a k-means clustering algorithm, determining an independent temperature control parameter required by each partition, generating a multi-mode temperature field partitioning scheme, partition temperature control data is obtained; according to the stable temperature distribution data, a non-contact electromagnetic suspension technology is adopted to control the distance between the glass and the mold, electromagnetic field intensity distribution data is generated, the stress state of the glass is calculated through finite element analysis, and contact stress reduction data is obtained; and aiming at the optimized mechanical property data, integrating the temperature field, the deformation rate and the stress distribution data by adopting a data fusion algorithm, generating a process parameter database for bending and tempering forming of the 3D special-shaped glass, and determining final production control parameters.

The invention relates to a connecting device (1) for electrically connecting at least two terminals, comprising: - at least one connecting element (2) designed for conducting current between the at least two terminals, with at least two contact areas (2a, 2b) for electrical and mechanical connection to the respective terminal, wherein the connecting element (2) comprises a metallic material (3) and a passivation layer (4) that forms at least in one fault condition and encloses the metallic material (3), and - a flux (8) that can be thermally activated by heat input due to a fault condition, which is designed to remove the passivation layer (4) in order to cut through the connecting element (2) in the molten area (2c) in the case of a fault condition that melts only the metallic material (3).

The invention belongs to the field of metal materials, and provides a hard alloy wear-resistant steel ball suitable for mine ore grinding and a preparation method thereof.The hard alloy wear-resistant steel ball is prepared from waste steel pig iron as a basic raw material and chemical components including 2.1%-2.2% of C, 9.8%-10.0% of Cr, 0.10%-0.20% of V and 0.03%-0.06% of Ti; a core-shell precipitated phase microstructure design with MN / MCN as a hard core and chromium carbonitride as a gradient self-passivation shell layer is formed through medium-frequency induction furnace smelting, controlled nitrogen introduction establishment of a V-Ti-C-N microalloy system, bottom pouring solidification and austenitizing quenching and tempering heat treatment processes, and the performance indexes that the surface hardness is HRC60-63 and the core hardness is HRC54-58 are achieved; the average particle size of a core-shell precipitated phase is in dispersed distribution of 20-200nm, the shell thickness is 5-50nm, and the alloy steel ball has excellent wear resistance and corrosion resistance under the high-impact and high-wear working conditions of wet ore grinding, solves the problem of insufficient wear resistance and corrosion resistance of a traditional alloy steel ball, and has wide mine ore grinding application value.

According to an embodiment of the present invention, provided is a dropper cap which can be detached from a container part accommodating contents and which suctions or discharges the contents. The dropper cap comprises; an inner cap which can be detached from the container part; and an outer cap coupled to the inner cap so as to encompass at least a part of the inner cap, wherein the inner cap and the outer cap can be formed from a metal material.

A semiconductor process provides a semiconductor substrate including a plurality of pads and a passivation layer. The passivation layer has a plurality of openings to expose the pads. Forming a ball bottom metal material layer on the connecting pad and the passivation layer; a bump is formed on the under-ball metal material layer by electroplating and overlaps the pad and a portion of the passivation layer in an orthographic projection direction. A patterned photoresist layer is formed on the bumps. The patterned photoresist layer completely covers the bump and extends towards the outer periphery of the bump to cover the ball bottom metal material layer. A first part of the ball bottom metal material layer is formed at the part covered by the patterned photoresist layer, and a second part of the ball bottom metal material layer is formed at the part not covered by the patterned photoresist layer. And removing a second part, which is not covered by the patterned photoresist layer and the bumps, of the under-ball metal material layer. And removing the patterned photoresist layer to expose the first part which is originally covered by the patterned photoresist layer. And removing the first part on the passivation layer by adopting dry etching to form a ball bottom metal layer. And the side wall of the ball bottom metal layer is flush with the side wall of the bump.

The invention discloses a defect-containing material life prediction method based on an M integral physical information neural network, and the method comprises the steps: constructing a damage parameter, namely an equivalent damage area, of a defect-containing metal material according to an energy equivalent method based on a classical fracture mechanical parameter M integral; establishing an M integral fatigue model according to a power-law relationship between the equivalent damage area and the M integral, and constructing a physical loss function; constructing a mixed loss function by adopting the physical loss function and the data related loss function, and constructing a physical information neural network based on the mixed loss function; optimizing hyper-parameters of the physical information neural network to obtain an optimal life prediction model; and evaluating the fatigue life of the defect-containing metal material by using the prediction model. According to the method, the influence of multi-defect features on fatigue failure is considered, the life prediction result meets the correlation between the fatigue data and conforms to the physical law, the dependence on the fatigue data is reduced, and the prediction precision and the analysis efficiency are remarkably improved.

The invention discloses a graphite piece silicon carbide coating and a preparation method thereof, and belongs to the technical field of inorganic non-metallic materials. The method comprises the following steps: firstly, carrying out surface polishing, cleaning and drying pretreatment on a graphite piece; then a solution containing phosphinazine functionalized silazane and a boron-silicon carlamide compound is adopted for spraying the pretreated graphite piece, drying and curing are conducted, and a surface modification layer is formed; and finally, placing the surface-modified graphite piece in chemical vapor deposition equipment, and depositing at specific temperature, pressure and atmosphere to form the silicon carbide coating. According to the method, uniform nucleation and crystallization of the silicon carbide coating are effectively promoted through unique surface modification treatment, and the compactness and uniformity of the coating and the binding force of the coating and a matrix are remarkably improved. The obtained coating graphite piece has excellent thermal corrosion resistance, oxidation resistance and mechanical property, the service life and the use frequency of the coating graphite piece in semiconductor epitaxial equipment are remarkably prolonged, the whole preparation process is environmentally friendly, and the coating graphite piece is suitable for coating treatment of a large graphite base material.

The invention discloses a construction method and device of a metal material performance prediction model, equipment and a medium. The method comprises the following steps: constructing an initial graph neural network; acquiring a three-dimensional volume element structure of the specified metal material and mechanical property data corresponding to the three-dimensional volume element structure; describing the three-dimensional volume element structure as an undirected graph structure; constructing a target data set by using the undirected graph structure and the mechanical property data; and performing iterative training on the initial graph neural network through the target data set to obtain a metal material performance prediction model. Therefore, the undirected graph structure of the three-dimensional volume element structure is used as a bridge, the metal material performance prediction model between the complex three-dimensional volume element structure and the mechanical performance data is established through the graph neural network, the model can rapidly and precisely predict the macroscopic performance of the metal material, the cost is low, and the method is easy to implement. And the requirements of rapid iteration and real-time feedback of the macroscopic performance of the material in engineering design can be met.

The invention belongs to the field of robot polishing and metal material processing and manufacturing, and discloses a steel plate surface defect detection and self-adaptive polishing system and method, and the system comprises a surface defect detection system, a three-dimensional contour detection system, a roller bed control system, a robot polishing system and a server; the surface defect detection system is used for acquiring types and position information of defects; the three-dimensional contour detection system is used for accurately measuring depth information of the defect; the roller bed control system is used for controlling the movement of the roller bed to transfer the steel plate; the server is used for data interaction and storage among the surface defect detection system, the three-dimensional contour detection system, the roller bed control system and the robot grinding system; and the robot polishing system accurately polishes the surface defects of the steel plate according to the defect position and depth data in the server. The full-process intelligent operation of steel plate surface defect detection, defect three-dimensional contour scanning and robot self-adaptive grinding is achieved, and the automation level and the production efficiency of a production line are effectively improved.

The invention discloses a heat-resistant aluminum rare earth alloy wire containing a two-phase nanostructure and a preparation method of the heat-resistant aluminum rare earth alloy wire, and belongs to the field of non-ferrous metal materials. According to the alloy, aluminum serves as a matrix, and the alloy further comprises, by mass, 0.005%-0.2% of Ce, 0.05%-0.25% of Er, 0.05%-0.25% of Yb, 0.1%-0.2% of Zr and 0.05%-0.2% of Fe. The alloy wire prepared by combining two-stage homogenization, hot extrusion and cold drawing processes contains an Al3 (RE, Zr) nano precipitated phase and a nanoscale Al13Fe4 dispersed phase, the inner layer of the Al3 (RE, Zr) nano precipitated phase is Al3RE, and the outer layer of the Al3 (RE, Zr) nano precipitated phase is Al3Zr; and the nanoscale Al13Fe4 dispersed phase is a nano precipitated phase formed by sequentially coating the outer layer of an Al13Fe4 phase with an Al3RE structure and an Al3Zr structure. The alloy provided by the invention has excellent strength, high-temperature service stability and conductivity.

The invention discloses a plasma surface activation pre-bonding-femtosecond laser connection integrated process, belongs to the technical field of advanced dissimilar material precision connection, and particularly relates to a multi-material interface efficient connection method based on plasma surface activation pre-bonding and femtosecond laser processing. The method is suitable for high-strength and low-thermal-damage heterogeneous bonding of transparent materials (such as glass, quartz and sapphire) and transparent materials or metal materials (such as titanium alloy, stainless steel and invar alloy). According to the method, interface atomic-scale cleaning and chemical activity regulation and control are achieved through plasma activation, interface connection of the two materials is induced by combining the femtosecond laser ultrafast nonlinear effect, and the bottlenecks that in a traditional connection technology, optical contact depends on a mechanical clamp, and heat input is uncontrollable are broken through; and an innovative solution is provided for cross-material interface functional manufacturing in the fields of photoelectric device packaging, optical-electronic integrated systems and the like.

The invention relates to a Fe-Si-Nb-B-Cu-Er amorphous alloy and a preparation method and application thereof, and belongs to the technical field of metal materials. The atomic percent expression of the Fe-Si-Nb-B-Cu-Er amorphous alloy disclosed by the invention is (Fe < 83 > Si < 3 > Nb < 4 > B < 9 > Cu < 1 >) < 100-x > Er < x >, wherein x is equal to 3.5 to 4.5. The rare earth element Er is added to optimize the soft magnetic performance of a Fe-Si-Nb-B-Cu amorphous alloy system, the coercive force of the Fe-Si-Nb-B-Cu amorphous alloy system is reduced, the preparation method is simple and easy to implement, and the Fe-based amorphous alloy with the excellent soft magnetization performance is obtained. The magnetization intensity of the amorphous alloy is sharply increased along with increase of a magnetic field under a low magnetic field and then gradually reaches saturation, typical soft magnetic performance is presented, and the amorphous alloy has wide application space in the field of magnetic materials.

The invention relates to the technical field of metal material heat treatment, in particular to a gradient temperature control method for a stainless steel cold rolling annealing process. Comprising the steps that an annealing furnace is divided into independent temperature control sections in the strip steel conveying direction, each temperature section is provided with an electric heating wire set, a forced convection cooling air duct and a high-precision infrared temperature measurement array, temperature data are collected in real time, and a target gradient temperature curve is generated; constructing a phase change power-temperature correlation model, and outputting a theoretical gradient temperature curve; a three-stage MPC is adopted to cooperatively control and output a control signal; and the heating power and the cooling strength are adjusted in real time according to the control signal, if the temperature fluctuation exceeds the limit, the power is compensated through a PID algorithm, the strip steel speed is adjusted, and closed-loop feedback is formed. Through multi-section independent temperature control, thickness-temperature dynamic modeling and a three-level cooperative control framework, accurate tracking of a gradient temperature curve is achieved, and the quality and efficiency of the annealing process are improved.