700results about How to "Reduce experiment cost" patented technology

The invention relates to the technical field of metal materials, and provides a medium-and-high-entropy aluminum alloy performance prediction method, system and method and a medium, and the method comprises the following steps: obtaining a characteristic data set for medium-and-high-entropy aluminum alloy performance; constructing an MLP prediction model, and obtaining an optimal hyper-parameter combination of the MLP prediction model through ESOA; training the MLP prediction model according to the feature data set and the optimal hyper-parameter combination; and predicting the performance of the medium-high entropy aluminum alloy according to the trained MLP prediction model. According to the method, the advantages of the ESOA and the MLP prediction model are combined, the accuracy of performance prediction of the medium-high entropy aluminum alloy can be effectively improved, the time and experiment cost can be reduced, the prediction cost and the calculation amount can be reduced through the powerful calculation capacity of the MLP prediction model, the prediction precision and the generalization capacity of the model are enhanced, and the method is suitable for popularization and application. The method is suitable for performance prediction of the medium-high-entropy aluminum alloy material.

The invention relates to an aluminum profile extrusion process energy consumption optimization method based on digital twinning, and the method comprises the steps: building a digital twinning model of an aluminum profile extrusion process, setting the range of extrusion process parameters, importing preset process parameters into the model for simulation, and extracting a quality index and an energy consumption index. The process parameters are optimized through a multi-objective optimization algorithm; the optimized parameters are imported into the model for simulation again, and results before and after optimization are compared to judge whether optimization is achieved or not. If the product quality is qualified and the energy consumption is optimal, applying optimization parameters to actual production; otherwise, continuing to optimize until the preset requirement is met. Through a digital twinning means, the strength and the workload of finding the optimal energy consumption process parameters in the aluminum profile extrusion process only through repeated manual physical experiments are reduced, energy conservation and emission reduction in the aluminum profile extrusion process are achieved, and meanwhile the production efficiency of an enterprise is improved.

The invention discloses a long-distance high-pressure water delivery pipeline water hammer and leakage monitoring and positioning test device, which comprises a water tank, a water outlet side experiment unit, a water return side main path experiment unit and a water return side branch experiment unit, and is characterized in that the water outlet side experiment unit and the water return side branch experiment unit are communicated with the water return side main path experiment unit; the water outlet side experiment unit, the water return side main path experiment unit and the water return side branch path experiment unit are all communicated with the water tank. The device solves the problem that tiny leakage is difficult to monitor in the high-pressure water delivery process in the existing related test experiment technology, and the problems that the water hammer experiment signal precision acquisition is insufficient and the water hammer experiment causes impact damage to equipment. The invention further discloses a using method of the long-distance high-pressure water conveying pipeline water hammer and leakage monitoring and positioning testing device.

The invention provides a residual stress prediction method considering ultrasonic peening process parameters of a welded joint, and the method specifically comprises the following steps: carrying out thermal-mechanical coupling simulation of a welded structure based on a finite element method, obtaining a residual stress field of the welded structure, taking the residual stress field as initial stress, and building an ultrasonic peening processing finite element model; on the basis of a hypercube Latin sampling method, a parameter combination sample is extracted, corresponding residual stress data after ultrasonic peening are obtained through simulation, and a residual stress prediction function model containing an undetermined coefficient is established with ultrasonic peening parameters as independent variables. And based on a particle swarm optimization algorithm, training to obtain an undetermined coefficient value which enables a prediction effect to be optimal, and completing establishment of a prediction function model. Therefore, the optimal process parameter combination of ultrasonic peening can be obtained so as to improve the mechanical property of a welded joint. According to the residual stress prediction method considering the ultrasonic impact process parameters of the welding joint, a basis is provided for improving the service performance of a large-scale thin-wall part welding structure.

The invention discloses an ultrahigh-temperature tensile and tensile creep test clamp applied to a bar-shaped sample, and belongs to the field of high-temperature mechanical testing. Comprising force application positioning modules, a testing auxiliary module and a positioning auxiliary module, the force application positioning modules are arranged at the two ends of a rod-shaped sample and used for transmitting loading force of a testing machine loading mechanism to the two ends of the rod-shaped sample, and the rod-shaped sample is subjected to axial tensile deformation; the test auxiliary module is connected to the test section of the rod-shaped sample and is used for transmitting the tensile deformation amount to the deformation measurement equipment; and the positioning auxiliary module is used for assisting the positioning of the rod-shaped sample in the mounting groove of the force application positioning module, so that the uniformity of the clamping force on the rod-shaped sample can be ensured. According to the invention, the problem that the sample and the clamp are easy to adhere at ultrahigh temperature is solved; when damage occurs, only the gasket needs to be replaced generally, so that the test cost is reduced; the two ends of the sample are positioned by being embedded into the grooves of the chucks, thread fixation is not needed, and the problem that the rod-shaped sample is difficult to install is solved.

The invention belongs to the technical field of solid fuel cells, and particularly relates to a hybrid-driven SOFC (Solid Oxide Fuel Cell) combined heat and power system service life prediction method, which comprises establishment of an SOFC system dynamic attenuation model and establishment of a hybrid-driven SOFC system service life prediction model. The service life of the system is predicted by simulating the dynamic attenuation of the SOFC combined heat and power system and performing machine learning, so that the performance of the whole SOFC combined heat and power system is predicted, and the influence of the interaction of each component on the service life of the system under the long-time operation of the system is analyzed. The method is short in test time and high in accuracy, the cost is saved, and the research and development progress is accelerated; an important reference basis is provided for long-life operation of the system, the influence of BOP parts on the whole life of the system can be clearly analyzed, and a direction is pointed out for the long-life operation of the system; and a machine learning method is utilized to avoid accidental results possibly existing in single simulation, so that the results have universality.

The invention discloses an in-vitro diagnosis liquid level detection method based on a 60GHz on-chip antenna millimeter wave radar, and relates to the technical field of liquid level detection in the IVD field, and the method comprises the steps: receiving a reflection signal through a sensor, and carrying out the preprocessing; extracting liquid level position data from the reflected signal through a machine learning algorithm; a temperature compensation and calibration mechanism is used for monitoring the temperature in real time and compensating and calibrating a measurement result; a friendly user interface is constructed and developed to feed back the system operation state in real time. The device can be accurate to a micron level, can accurately detect the liquid level height change in a micro cup or a reagent bottle, provides an extremely accurate reference for reagent addition, is greatly enhanced in reliability, is not influenced by factors such as liquid color, transparency, container material and shape, and can be used in a complex and changeable laboratory environment. The device can work stably and accurately under the conditions of temperature, humidity, electromagnetic interference and the like, and effectively avoids measurement errors caused by interference of external factors.

The invention relates to the technical field of optical fiber communication, in particular to an optical fiber optical frequency transmission field optical fiber link noise simulation method and system, and the method comprises the steps: dividing laser generated by a laser into reference light and simulation light; modulating the analog light, performing field optical fiber transmission, and performing optical frequency processing on the analog light and the reference light to obtain a radio frequency signal; performing phase processing on the radio frequency signal to obtain continuous phase information and frequency conversion data; the method comprises the following steps: constructing an optical fiber optical frequency transmission field optical fiber noise simulation model, converting phase information and frequency conversion data into voltage data by using the noise simulation model, setting a modulation depth parameter according to the voltage data, performing modulation according to the modulation depth parameter, and adjusting the length of a laboratory winding optical fiber according to a modulation result to realize noise simulation. According to the method, different types and different magnitudes of field optical fiber link noise can be simulated.

The invention provides an electric arc additive manufacturing weld bead morphology prediction method based on three-dimensional scanning point cloud. The method comprises the following steps that firstly, a weld bead of an electric arc additive manufacturing stainless steel weldment is obtained through an electric arc additive manufacturing stainless steel experiment; 2, a three-dimensional point cloud model of the stainless steel welding beads manufactured through the electric arc additive is obtained through a handheld three-dimensional scanner, and each welding bead is cut and straightened; thirdly, the straightened uniform arc additive manufacturing stainless steel weld bead is subjected to slice projection in the Y direction, and the average shape of the weld bead is obtained and serves as a data set; 4, determining input, output and the number of hidden neurons, and establishing a neural network model suitable for a weld bead morphology data set; 5, training the neural network, and predicting the weld bead morphology of the target process parameters; and 6, comparing the weld bead morphology predicted by the neural network with the verified weld bead morphology, and calculating a prediction error and precision. The method has the characteristics of high speed and high precision.

The invention relates to the technical field of mechanical cutting machining, and discloses a method for constructing a milling force prediction model for milling a variable-curvature part based on RIME-SVM, and the method comprises the following steps: S1, obtaining prediction model data; s2, building an RIME-SVM milling force prediction model based on a support vector machine; s3, constructing a cutting force prediction model for machining a conventional straight surface by the end mill; s4, verifying the precision of the cutting force prediction model of the end mill for processing the conventional straight surface; s5, constructing a cutting force prediction model for machining different geometrical characteristics of the end mill; and S6, verifying the precision of the cutting force prediction model for processing different geometrical characteristics by the end mill. The RIME-SVM model combines the advantages of SVM processing nonlinear regression and the high efficiency of the RIME optimization process. According to the RIME-SVM model, the prediction precision is improved, the experiment cost is reduced, the generalization ability is high, unseen data can be accurately predicted, and the method is suitable for practical engineering application.

The invention discloses a full-automatic intelligent multifunctional high-order nonlinear fluorescence dynamics testing method and device, and relates to the field of nonlinear optics and nano photonics. An optical testing device composed of an exciting light generation module, an automatic power regulation module, an exciting light modulation module, a sample scanning module, a data acquisition and analysis module and an intelligent control module is established, and under the excitation of incident laser, based on the overall coordination of the intelligent control module, the optical testing device is established. Other modules are driven to complete the dynamic response test of a nonlinear fluorescence sample, and full-automatic intelligent, multifunctional, high-precision, simple, efficient, low-cost and universal fluorescence dynamic test analysis is realized. The problems that traditional manual operation wastes time and labor and the testing precision is low are solved. In addition, the multifunctional integration of the fluorescence response curve, the fluorescence rise time, the fluorescence lifetime and the fluorescence imaging effectively improves the test efficiency and the application scene, and greatly reduces the system cost.

The invention relates to a CFD numerical simulation-based pressure-bearing loose combustible material oxidation spontaneous combustion simulation method, and belongs to the technical field of combustible material oxidation spontaneous combustion simulation. Physicochemical property testing is carried out on combustible materials, oxidation experiments are carried out on the loose combustible materials under different pressure-bearing conditions, and physical parameters are collected; temperature, gas concentration and pressure parameters of combustible materials are collected in real time, and pressure-bearing oxidation spontaneous combustion parameters are calculated; fitting a function relationship between the oxidation spontaneous combustion parameter and the combustible body temperature; establishing a CFD numerical simulation model of multi-physics field coupling; according to the geometric dimension of the simulation model, dividing calculation grids, setting simulation boundary conditions and initial conditions, and performing CFD numerical simulation calculation; and outputting a three-dimensional dynamic distribution diagram of the temperature field, the heat conductivity coefficient field, the permeability field, the heat release intensity field and the gas concentration field in the simulation process, and analyzing a simulation result to obtain the oxidative spontaneous combustion characteristics of the pressure-bearing loose combustible.

The present invention discloses a hydrodynamic performance test device for a flexible umbilical cable of a wave glider, comprising: a connecting frame, used to connect the device to a crossbeam of a towing tank vehicle; a slide rail, installed at the lower part of the connecting frame; a horizontal slide, slidably arranged on the slide rail; an umbilical cable to be tested, the first end of which is connected to the connecting frame through a two-degree-of-freedom conversion device and a three-component force sensor, and the second end is connected to the horizontal slide through a two-degree-of-freedom conversion device and a single-component force sensor; a pre-tension adjustment device, installed on the crossbeam, and the pre-tension adjustment device is connected to the horizontal slide; an image acquisition device, arranged on the connecting frame above the umbilical cable to be tested, for recording the motion state of the umbilical cable to be tested. The present invention can restore the real state of the flexible umbilical cable to the greatest extent, eliminate the influence of other components of the wave glider on the hydrodynamic characteristics of the flexible umbilical cable, and directly obtain the hydrodynamic characteristics of the flexible umbilical cable.

The invention discloses a high-temperature and high-pressure well cementation interface shear cementing strength measuring device and method, and belongs to the field of oil and gas well cementation. The device comprises a kettle body, an oil storage tank, a hydraulic pump, an electric control system, a display, a supporting frame and a base, wherein the kettle body comprises a top cover, an upper kettle, a lower kettle, a bottom cover, a simulation sleeve, a simulation stratum, a positioning steel cylinder, a piston cylinder body, an inner piston, an outer piston and a floating bearing plate. The method comprises the following steps: pouring cement paste into an annular space between a simulation casing and a simulation stratum; curing the cement paste at constant temperature and constant pressure; slowly increasing the pressure of the inner cavity of the piston, and enabling the inner piston to move downwards until the simulation sleeve is separated from the cement sheath; the pressure of the inner cavity of the piston is continuously increased, and the outer piston moves downwards under the pushing action of the inner piston until the cement sheath is separated from the simulated stratum. The test process is controllable, the test result conforms to the underground environment, and an important technical means is provided for optimizing the cement slurry performance and well cementation process parameters and further improving the well cementation quality of an oil and gas well.

The invention relates to a small molecule virtual screening method and system based on a graph convolutional neural network, and the method comprises the steps: firstly obtaining the data of an active compound and a bait compound of a target spot, carrying out the preprocessing of the obtained data, constructing a graph convolutional neural network model, carrying out the training and evaluation of the model through a preprocessed data set, and obtaining a small molecule virtual screening result. And then scoring the small molecule compound data obtained in the compound database by using the trained graph convolutional neural network model, retaining the small molecule compound with high prediction score, and finally obtaining the known drug molecule data of the target spot. And performing compound similarity search on the small molecule compounds with high prediction scores and known drug molecules to obtain the small molecule compounds with similarity with the known drug molecules. Compared with the prior art, the method has the advantages that virtual screening is utilized, the drug research and development process is accelerated, the experiment cost is reduced, compound similarity search is combined on the basis, the screening accuracy is further improved, and the screening result range is narrowed.

The invention belongs to the field of image spectrum detection, and particularly relates to a high-precision detection device and method for a liquid meniscus contour in a capillary tube. Comprising a telecentric lens, an industrial camera, a displacement platform, a light source, a capillary tube and a culture dish, the industrial camera, the capillary tube and the culture dish are installed on different displacement platforms respectively, the light source is provided with a rotary telescopic rod and can move in all directions, when the liquid meniscus contour in the capillary tube is shot, the light source, the meniscus of the capillary tube and the industrial camera are adjusted to be aligned to the same horizontal plane, and on the basis of the telecentric imaging principle, according to the light refraction principle, the liquid meniscus contour in the capillary tube is obtained. And deriving a distortion correction function of the meniscus contour in the capillary tube. According to the invention, the industrial camera and the telecentric lens are matched for use, the problem of shape distortion caused by object distance change is avoided, and the difficulty of image distortion correction is reduced. The meniscus contour distortion correction function derived based on the telecentric imaging principle can accurately calculate the actual value of the meniscus contour and restore the actual meniscus contour.

The invention relates to the technical field of battery thermal performance measurement, in particular to a method for measuring the specific heat capacity of an energy storage battery. The theoretical model is calibrated by monitoring the cooling curve of the battery so as to ensure that the heat transfer characteristic of the battery is accurately reflected. Then, constant-power heating is adopted, so that the thermal field of the battery reaches a quasi-steady state, and in the steady state, the temperature change is gradually consistent; and recording a temperature change curve in real time through a temperature acquisition instrument, and calculating the specific heat capacity of the battery in combination with the calibrated model and a constant power input condition. According to the method, only the voltage-stabilized power supply and the temperature acquisition instrument are needed, so that the cost is greatly reduced; the measurement precision is improved through temperature change curve analysis after model calibration, and the problems that in a traditional method, environmental interference is large, and precision is insufficient are solved; the time for reaching the quasi-steady state is shortened through constant-power heating, and the measurement process is accelerated. The method is suitable for various energy storage batteries, can meet the requirements of industries such as electric automobiles and electric energy storage on the thermal performance of the batteries, and has wide popularization value.

The invention provides a temperature damage detection method based on an optimized vacuum sintering furnace and a temperature measuring device, and belongs to the related field of heat transfer science, and the method comprises the following steps: optimizing a vacuum sintering furnace structure by adopting different thermal insulation structures, and deducing a one-dimensional performance simulation model of a carbon felt thermal insulation layer; according to the one-dimensional performance simulation model of the carbon felt thermal insulation layer, the temperature rise curve and the workpiece temperature, the value range of the thickness of the carbon felt thermal insulation layer at different sintering temperatures is calculated by utilizing a reverse simulation principle, and then the optimal thickness of the carbon felt thermal insulation layer is obtained in the value range of the thickness of the carbon felt thermal insulation layer at different sintering temperatures by utilizing forward simulation; and the optimal thickness of the carbon felt heat preservation layer is adopted as the length of the temperature measuring device, the temperature measuring device of the vacuum sintering furnace is constructed, the temperature of the vacuum sintering furnace is measured through the multiple temperature measuring devices, and a temperature damage detection result is obtained according to the measurement result. According to the method, the problem that the temperature in the effective heating area after structure optimization cannot be directly measured due to too high temperature is solved.

The invention discloses a metal structure material service behavior evaluation method and system based on a large-model multi-modal analysis technology, belongs to the technical field of metal structure materials, and solves the problem of obvious limitation in coping with a complex and changeable service environment. Comprising the steps of selecting a proper data source, determining a data crawling target, cleaning and labeling crawled data, performing training by using a deep learning model, and constructing a knowledge base; designing an experiment, collecting experiment data, combining the experiment data with other data through an intelligent agent, and carrying out multi-modal data fusion analysis; comparing a multi-modal data fusion analysis result with experimental data, calibrating a prediction model, and optimizing an analysis process; an intelligent decision support system is constructed, an experiment scheme is automatically generated, the experiment process is optimized, and suggestions are provided. The dynamic change of the material in the service process can be responded in real time, the prediction model is automatically adjusted, and the adaptability and real-time performance of the system in a complex environment are ensured.

The invention discloses a GIS equipment electromechanical state and typical defect simulation test platform and a GIS equipment electromechanical state and typical defect simulation test method, relates to the field of electrical equipment electromechanical state and typical defect simulation tests, and solves the problem of simulation and research of electromechanical states and defect characteristics of gas insulated switchgear (GIS) under different operation conditions. Wherein the test platform comprises an AC voltage source, a GIS scaling model, a vibration table and an excitation power amplifier, defects are preset in the GIS scaling model, the GIS scaling model is provided with a transparent observation window used for observing the internal condition of the model, and the GIS scaling model is fixedly installed on the vibration table; an alternating-current voltage source is loaded on a GIS scaling model bus to simulate distribution of an electric field in a GIS, and vibration is applied to the GIS scaling model through a vibration table and an excitation power amplifier to simulate GIS vibration caused by current.

The invention discloses a motor bearing voltage simulation device and method for a bearing electrocorrosion test, and relates to the field of new energy automobiles. The problems that in the prior art, the disassembly and replacement process of a bearing in an intrusive measurement method is tedious and time-consuming, and deep research on the damage condition of the bearing under different operation conditions and key parameters is greatly limited are solved. The simulation device comprises a BUCK voltage regulating circuit, a three-bridge-arm inverter, a common-mode voltage output loop, a high-pass filtering loop, a bearing voltage simulation loop and a bearing voltage output loop. By utilizing a bearing voltage generation mechanism and combining cooperative work of the three-bridge-arm inverter and the rear-end bearing voltage simulation loop, the waveform of the bearing voltage can be reproduced completely, and the waveform can be adjusted according to needs, so that high flexibility and accuracy are provided for research and test. The method is also suitable for the field of actual motor bearing voltage simulation.

The invention discloses an SERS (Surface Enhanced Raman Scattering) sensor for detecting diabetic retinopathy serum biomarkers miR-21 and miR-152 as well as a preparation method and application of the SERS sensor, and belongs to the technical field of biomedicine. The preparation method comprises the following steps: self-assembling AuNHs through an oil-water interface to obtain an AuNHs array, and modifying an aptamer chain cDNA on the surface of the array to obtain an SERS (Surface Enhanced Raman Scattering) substrate; the method comprises the following steps: modifying a Raman signal molecule 4-MBA and a nucleic acid aptamer complementary chain H1 to the surface of AuNTs to obtain an SERS probe 1; a Raman signal molecule DTNB and a nucleic acid aptamer complementary chain H2 are modified to the surface of AuNTs, and an SERS probe 2 is obtained; and combining the prepared SERS probe with a complementary basic group in the nucleic acid aptamer chain cDNA on the SERS substrate, and fixing on the AuNHs array to construct the SERS sensor.

The invention relates to a digital core resistivity numerical simulation and saturation model construction method under deep overpressure and high temperature conditions, and relates to the technical field of oil-gas exploration, and the method comprises the steps: constructing a digital core under the overpressure condition, calculating the clay conductivity and formation water conductivity under the high temperature condition, and obtaining an overpressure and high temperature equivalent digital core model; based on an overpressure and high-temperature equivalent digital core model, through an electrical numerical simulation algorithm, the resistivity and the stratum factor F of water-saturated cores with different porosities phi are calculated, and an F-phi cross plot is constructed; and calculating digital core resistivity and resistivity increase coefficient RI of different water saturation Sw by using a numerical simulation algorithm, and constructing an RI-Sw cross plot. According to the method, a saturation model under the deep actual temperature and pressure conditions can be constructed through equivalence of pressure and temperature by utilizing a digital rock core numerical simulation technology.

The invention provides a standardized experiment method and device for a rock mechanics experiment, and the method comprises the steps: collecting a plurality of conventional rock mechanics experiment schemes, determining a plurality of experiment characteristics of each experiment, and splitting links of each conventional rock mechanics experiment according to the plurality of experiment characteristics; according to the standard format corresponding to each experiment feature, storing each experiment feature of each experiment into a corresponding storage file to generate a standardized description of the rock mechanics experiment; performing matching analysis on each experiment characteristic of the target sample and the standardized description, and determining a target experiment type corresponding to the target sample; and extracting a corresponding experiment scheme from the standardized description according to the target experiment type, and performing an automatic experiment on the target sample to obtain the mechanical index of the target sample. The method is based on standardized experimental scheme description, can carry out batch and automatic rock mechanics experiments, improves the experiment efficiency, and reduces the experiment cost.

The invention discloses a deep mutation scanning method based on protein-protein interaction in bacterial cells and a binding affinity prediction method. In the invention, split dCas9 proteins (SEQ ID NO.1 and SEQ ID NO.2) are respectively subjected to fusion expression with a receptor and a ligand with binding affinity to be detected, and are combined with a toxic sgRNA guide sequence (SEQ ID NO.3), and when PPI occurs, a toxic dCas9: sgRNA complex is formed to inhibit bacterial growth, so that a PPI affinity size signal is converted into a bacterial cell generation speed signal, and the signal can be quantified into a copy number value through next-generation sequencing. The invention further designs a deep learning binding affinity prediction model, high-affinity sequences can be screened from theoretical mutation space, the workload and cost of experimental verification are remarkably reduced, and a reliable basis is provided for subsequent protein function optimization and design.

The invention provides a medical packaging composite film and a preparation method thereof. The preparation method of the medical composite membrane comprises the following steps: S100, coating a first surface of an aluminum foil layer with an adhesive, attaching the first surface to a barrier material, and sequentially carrying out primary drying treatment and calendering treatment to obtain a barrier layer, an adhesive layer and the aluminum foil layer; s200, the second surface of the aluminum foil layer is coated with heat sealing slurry, secondary drying treatment is conducted, and the medical packaging composite film is obtained. The medical packaging composite film has excellent barrier property, biological safety, mechanical property and heat sealing property, and can provide reliable packaging protection for medical drugs.

The invention provides a fluid critical heat flux prediction method and device, equipment and a storage medium. The method comprises the steps that a first simulation model of the in-channel boiling heat transfer process of a target channel is acquired; a plurality of heat flow densities are sequentially input into the first simulation model, and the maximum wall surface superheat degree and the maximum wall surface void fraction corresponding to each heat flow density are obtained; the heat flow density with the change rate of the corresponding maximum wall surface superheat degree larger than or equal to a first threshold value in the multiple heat flow densities is determined as the first heat flow density; comparing a wall surface maximum void fraction corresponding to the first heat flux with a wall surface boundary void fraction; and under the condition that the wall surface maximum void fraction corresponding to the first heat flow density is larger than or equal to the wall surface boundary void fraction, the critical heat flow density is determined according to the first heat flow density. According to the prediction method for the critical heat flux of the fluid, efficient and accurate prediction of the critical heat flux can be realized.

The invention relates to the technical field of silicon-based anode materials, in particular to a method for reducing structural deformation and damage in the circulation process of a silicon-based anode. The preparation method comprises the following steps: adopting Ti < 3 > C < 2 > T < x > MXeneamp; the SGC composite material is used as a silicon-based anode active material; the Ti < 3 > C < 2 > T < x > M < X > eneamp; the preparation method of the SGC composite material comprises the following steps: (1) dispersing nano silicon into phenolic resin, then enabling the nano silicon and graphene oxide to be adsorbed and self-assembled to form gel by utilizing a surface charge adsorption effect, and then performing freeze drying, grinding, carbonization treatment and CVD treatment to obtain the SGC composite material; (2) the surface of the SGC composite material is coated with the Ti < 3 > C < 2 > T < x > MXene nanosheets in a vacuum suction filtration mode, and Ti < 3 > C < 2 > T < x > MXene amp is obtained; the invention discloses an SGC composite material.

The invention relates to a pathological pulmonary fibrosis model and a construction method and application thereof. The pathological pulmonary fibrosis model provided by the invention is good in stability and controllability and high in maturity, not only can better simulate the function and structural characteristics of pulmonary alveoli-capillary barrier, but also has the pathological characteristics and immune microenvironment of pulmonary fibrosis lesions, has the advantage of high simulation degree, and has good application prospects in simulation and research of pulmonary fibrosis diseases. Good application prospects are realized in the aspects of drug detection, screening, evaluation, research and development and the like.

The invention belongs to the field of chemical medicine analysis, and particularly relates to a method for determining the content of impurities in phloroglucinol trimethyl ether. According to the method provided by the invention, the excessive methylation impurities (2, 4, 6-trimethoxytoluene, 2, 4, 6-trimethoxyxylene and 2, 4, 6-trimethoxytrimethylbenzene) generated in the methylation process can be detected, and the excessive methylation impurities are prevented from being further transferred and existing in a phloroglucinol trimethyl ether raw material medicine and a final product phloroglucinol injection preparation. Researches on specificity, accuracy, precision, limit of detection, limit of quantitation, linear range, durability and the like of the method prove that the method is suitable for measuring the content of the over-methylated impurities in the phloroglucinol trimethyl ether.