2189 results about "Electron microscope" patented technology

The invention provides a defect detection method and system for integrated circuit manufacturing. Wherein in the integrated circuit packaging stage, packaged chips are divided into a first type of chips meeting a preset physical characteristic threshold value and a second type of chips exceeding the physical characteristic threshold value through a pneumatic sorting device; performing scanning electron microscope imaging on the surface of the second type of chip, generating a three-dimensional topological structure by using an image reconstruction technology, and positioning a micron-sized particle defect area by comparing reference type differences; synchronously applying high-frequency electric signal excitation in the sorting process, detecting impedance response of the second type of chips, and recording an abnormal signal sequence exceeding a preset frequency domain range; performing space-time correlation matching on the micron-sized particle defect area and the abnormal signal sequence, and judging that the defect is a multi-layer composite defect when a preset coupling condition is met; and dynamically adjusting the mesh diameter and vibration frequency parameters of the pneumatic sorting device. According to the technical scheme provided by the invention, accurate identification of the multi-layer composite defect of the chip is realized, and the defect interception efficiency is remarkably improved.

In a method, for training an artificial neural network (ANN) to reduce noise and / or artefacts in an electron microscopy image, a plurality of training image pairs is generated. For each pair, an undistorted synthetic specimen image and a distorted image are created by simulating additional noise and / or artefact features. The ANN is trained, in which the distorted images are used as input and the corresponding undistorted images as output. An adversarial training strategy is used in which the ANN is trained, as a generator network, in conjunction with concomitantly training a further ANN, as a discriminator network, to differentiate output produced by the generator network from synthetic images in the training set. In training, parameters of the ANN and further ANN are optimized using a generator loss function and a discriminator loss function, in which a dependency exists between said loss functions to train the networks in an adversarial manner.

The invention provides a preparation method of a transmission electron microscope ultrathin sample with a cross section of an electron beam sensitive material, which comprises the following steps: selecting a specific region as a to-be-extracted sample region for the electron beam sensitive material by adopting an electron beam imaging technology; depositing a protective layer on the surface of the to-be-extracted sample area by adopting an electron beam and / or an ion beam; bombarding a to-be-extracted sample area by utilizing a high-energy ion beam, extracting an electron beam sensitive material cross section sample from the to-be-extracted sample area, and fixing the extracted sample to a metal bracket; performing pre-thinning treatment on the extracted sample by using a focused ion beam to obtain a first thinned sample of which the thickness is reduced to be less than a first thickness; and transferring the first thinned sample into a micro-beam fixed-point ion thinning system, and carrying out multi-time stepped low-energy ion beam fine thinning treatment on the first thinned sample by using inert gas ion micro-beams to obtain a second thinned sample which is clean in surface and free of a surface ion damage layer and has the thickness reduced to be less than a second thickness, and taking the second thinned sample as a transmission electron microscope ultrathin sample.

The invention provides a three-dimensional digital core reconstruction method capable of reflecting real shale pore structure characteristics and meeting pore scale numerical simulation connectivity requirements, which comprises the following steps of: firstly, acquiring a pore structure image according to a scanning electron microscope and a micro-nano CT (Computed Tomography); constructing a shale matrix digital core which is consistent with the porosity, permeability and pore size distribution of a real rock sample by adopting a method of combining a numerical value construction method and a physical experiment method; then establishing a digital core of the shale containing the micro-cracks according to the obtained spatial distribution characteristics of the micro-cracks; a matrix digital core and typical micro-crack distribution are combined to obtain a hole-crack structure digital core for pore scale simulation research. The method is reliable in principle, low in cost and accurate in reconstruction result, and solves the technical problems that a digital core obtained by adopting the prior art is poor in connectivity and cannot reflect typical pore characteristics of shale; the method can be used for researching reconstruction of different types of cores and seepage simulation established on a pore scale, and has a good application prospect.

To provide: a transistor with favorable electrical characteristics; a transistor with a high on-state current; a transistor with low parasitic capacitance; or a transistor, a semiconductor device, or a memory device which can be miniaturized or highly integrated.SOLUTION: There is provided a transistor including an oxide semiconductor layer, a semiconductor device, or a memory device. The oxide semiconductor layer includes a first region, a second region over the first region, and a third region over the second region. The first region is located in a range from a surface on which the oxide semiconductor layer is to be formed to greater than or equal to 0 nm to less than or equal to 3 nm in a direction substantially perpendicular to the surface. In cross-sectional observation of the oxide semiconductor layer using a transmission electron microscope, bright spots arranged in a layered manner in a direction parallel to the surface on which the oxide semiconductor layer is to be formed are observed in each of the first region, the second region, and the third region.SELECTED DRAWING: Figure 1

The present invention relates to a catalyst for ortho-parahydrogen conversion suitable for a wide range of low-temperature conditions and a preparation method thereof. The catalyst is a fiber magnetic catalyst FeMnOx doped with Fe atoms in an orderly manner; the base material of the catalyst is α-MnO2, the α-MnO2 belongs to the tetragonal system, the unit cell parameter is #imgabs0#, the crystal structure is composed of 2×2 octahedral chains with shared edges, the XRD characteristic diffraction peaks are 2θ=12.8°, 18.1°, 25.7°, 37.5°, 49.8°, 56.3°, and the specific surface area measured by the BET test method is 100-150m 2 / g, and transmission electron microscopy shows that its microstructure is a fibrous structure with a diameter of 2 to 5nm and a length of 100nm to 500nm; when the catalyst is used for the ortho-parahydrogen conversion reaction, the ortho-parahydrogen conversion efficiency is more than 95%, and the catalyst life is more than 1400h; the wide range of low temperature conditions is 23K-77K. The coordination of Fe atoms with lattice oxygen in α-MnO2 can effectively avoid the deactivation of the catalyst caused by the change of the valence state of the metal component, thereby enhancing the stability and life of the catalyst, and is suitable for industrial-scale production.

The invention provides a pore-fracture-based shale reservoir classification evaluation method and system, and relates to the technical field of oil and gas geology, and the method comprises the steps: S1, scanning an electron microscope image of a shale reservoir to be classified and evaluated, and recognizing different types of reservoir spaces of the shale reservoir; s2, reservoir space parameters of the shale reservoir are extracted according to the recognition result of the reservoir space; s3, calculating evaluation parameters of the shale reservoir based on the reservoir space parameters and a pre-obtained view field area of the shale reservoir; s4, inputting the evaluation parameters and the pre-calculated weight value of each evaluation parameter into a pre-constructed classification evaluation model, and calculating to obtain an evaluation coefficient of the shale reservoir; and S5, based on the evaluation coefficient, performing classification evaluation on the shale reservoir. According to the method, quantitative evaluation can be carried out on the shale reservoir on the microcosmic aspect, and compared with a traditional shale reservoir evaluation method, the shale reservoir evaluation is more visual and accurate on the basis of the microcosmic characteristics of the pore fractures.

The invention provides an electron microscope automatic focusing method and system based on a deep learning model, and relates to the technical field of electron microscope automatic focusing, and the method comprises the steps: collecting a plurality of images at different focusing distances through an electron microscope, and recording the focusing distance of each image; calculating the characteristic value of each collected image, combining the focusing distance and the characteristic value of the image into a characteristic vector, and generating a characteristic sequence according to the characteristic vectors obtained under different focusing distances; training a pre-constructed neural network model by using the feature sequence to obtain a trained neural network model; and inputting a to-be-tested image into the trained neural network model, calculating a difference value between the predicted optimal focusing distance and the focusing distance of the collected image, and judging whether the difference value is within a set range or not. According to the invention, the microscopic image acquisition efficiency and quality are obviously improved.

The invention relates to a TEM (Transmission Electron Microscope) detection method for a damaged layer of a silicon wafer, which belongs to the technical field of surface defect analysis of semiconductor silicon wafers and comprises the following steps of: depositing a protective layer on the surface of a wafer, and protecting the surface structure of the wafer during ion beam cutting by using a focused ion beam machine; therefore, the influence of the deformation of the surface structure of the TEM sample on the detection result of the TEM sample is avoided. A relatively flat area is selected in a deposition protection layer, a Pt layer protection layer is uniformly deposited on the surface of the area, and a focused ion beam is used for etching and marking in a target area. A thinning technology is utilized, so that the thickness meets the requirement of TEM observation; the copper net is used as the metal conductive net, so that the basic conductive performance can be met, the stable physical property is achieved, and the effect of supporting and fixing the sample is achieved. And the morphology of the damaged layer is clearly observed by utilizing the high-resolution characteristic of the TEM, so that the quality and success rate of surface damaged layer analysis are improved.

A light emitting device includes: a first electrode and a second electrode with a surface facing the first electrode; an emission layer disposed between the first electrode and the second electrode and including a quantum dot (e.g., a plurality of quantum dots); and an electron auxiliary layer disposed between the emission layer and the second electrode. The electron auxiliary layer includes a first layer including a first metal oxide, and a second layer disposed on the first layer and including a second metal oxide. A roughness of an interface between the second layer and the second electrode is less than about 10 nm as determined by an electron microscopy analysis. An absolute value of a difference between a conduction band edge energy level of the second layer and a work function of the second electrode may be less than or equal to about 0.5 eV, and a conduction band edge energy level of the first layer may be less than the conduction band edge energy level of the second layer.

A composite electrode material, method for its production and use of the material are provided. The composite electrode material comprises: i) a current collector material layer exhibiting a surface roughness value selected from at least one of the following: —an Sdr value of more than 40%; and —an Sdq value of more than 1.0; each value being determined by white light interferometry according to standard method ISO 25178; ii) optionally, a first silicon layer positioned on the current collector material layer, wherein the first silicon layer has a porosity of less than 30%, as determined by electron microscopy; and iii) at least a second silicon layer positioned on either the optional first silicon layer or the current collector material layer, wherein the second silicon layer has a porosity ranging from a porosity higher than the porosity of the optional first layer, to a porosity of less than 80%, as determined by electron microscopy.

The invention provides a double-space fatigue electron microscope test system, which is applied to the technical field of material analysis, and comprises an electron microscope module, a fatigue loading module and a vacuum isolation damping module, the vacuum isolation damping module controls two spaces of the electron microscope module and the fatigue loading module to be communicated or independent; the fatigue loading module comprises a hydraulic loading actuator, an electromechanical loading actuator, a loading rod and a fixing clamp, the fixing clamp is used for clamping a to-be-tested sample, and the loading rod is used for stretching or extruding the to-be-tested sample; and the fatigue loading module is driven by the moving mechanism to reciprocate along the X axis to adjust the position of the to-be-tested sample or rotate along the X axis to realize switching of different stations. According to the double-space fatigue electron microscope test system, combined use or independent use of the electron microscope module and the fatigue loading module is realized, and adverse factors such as vibration and pulse generated by the fatigue loading module during electron microscope observation are improved; in-situ compensation is achieved by means of cooperation of loading force and displacement of the fatigue loading module, and the observation effect of the electron microscope is improved.

A transmission electron microscope sample rod (100) and a sample testing method. The transmission electron microscope sample rod (100) comprises a heating element (10) and a testing mechanism (20), wherein the heating element (10) is configured to heat a sample, the testing mechanism (20) is constructed with a plurality of connecting arms (21) which are arranged at intervals in a circumferential direction of the testing mechanism (20), an accommodating space (23) is defined by means of the plurality of connecting arms (21), one side of each connecting arm (21) facing the accommodating space is defined as an output end (202), the plurality of output ends (202) jointly clamp the sample, each connecting arm (21) can extend and retract in an extension direction of the output end (202), and each connecting arm (21) is connected to the heating element (10).

The invention relates to the technical field of semiconductors, and discloses a semiconductor sample defect detection system which comprises an imaging module, a data acquisition module, a data processing module, an automation and integration module and a user interface module. According to the defect detection system and method for the semiconductor sample, by integrating the imaging modules of the optical microscope, the electron microscope, the X-ray diffractometer and the super-resolution microscope, details of the semiconductor sample can be comprehensively captured from macroscopic to microscopic and from the surface to a crystal structure, so that precise recognition of tiny or deep defects is ensured; the application of the deep learning model further improves the accuracy of image processing, through feature extraction and intelligent identification, even defects difficult to perceive by naked eyes have no place to hide, and the high-precision detection capability greatly reduces the risk that quality problems are only found in subsequent production links, reduces the possibility of reworking and scrapping, and improves the production efficiency. Therefore, the product quality and the production yield are improved.

The invention discloses an in-situ identification analysis method for superfine non-metallic inclusions in steel, and mainly solves the technical problems that the superfine non-metallic inclusions in the existing steel are difficult to identify and extract and the microstructure and phase composition of the inclusions are difficult to characterize. According to the technical scheme, the method for detecting and analyzing the small-size non-metallic inclusions in the steel by using the scanning electron microscope comprises the following steps: (1) preparing a metallographic sample; 2) preparing a transmission electron microscope sample, and determining an area where the inclusion of the metallographic sample is located by using a scanning electron microscope; carrying out accurate positioning and in-situ micro-nano thinning and cutting on the area where the inclusion of the metallographic sample is located by using a focused ion beam double-beam electron microscope system, and extracting the superfine non-metallic inclusion; and 3) analyzing the ultrafine non-metallic inclusions in the transmission electron microscope sample, and detecting the grain orientation of the ultrafine inclusions by using a transmission-type electron back scattering diffractometer. The method provided by the invention can accurately identify and extract the superfine non-metallic inclusions and the phase composition, components and grain orientation thereof in situ.

The invention relates to the technical field of transmission electron microscope in-situ experiments, in particular to a transmission electron microscope in-situ multi-field coupling experiment platform which comprises a sample rod, a carrying table, a thermoelectric chip, a magnetic field generating device and a flexible circuit board. A first mounting groove and a second mounting groove are formed in the carrying table; the thermoelectric chip is arranged in the first mounting groove, and a carrying part, an electrical control unit and a temperature control unit are arranged on the thermoelectric chip; the magnetic field generating device is arranged in the second mounting groove and can generate a controllable magnetic field on the carrying part; the carrying part is used for carrying a sample, the electrical control unit is configured to load and measure an electrical signal of the sample, the temperature control unit is configured to control and measure the temperature of the carrying part, and the transmission electron microscope in-situ multi-field coupling experiment platform provided by the invention realizes cooperative application and accurate control of an electric field, a magnetic field and a temperature field.

The invention discloses a pre-detection system and a pre-detection method for an electronic gun. The pre-detection system comprises a deflection lens cone, a measurement lens cone and a control module, the measuring lens cone and the deflection lens cone are respectively and electrically connected with the control module; during pre-detection, the to-be-detected electron gun lens cone is installed right above the deflection lens cone, and the control module is electrically connected with the electron gun lens cone. The control module is used for controlling the electron gun to emit an electron beam and controlling the electron beam to deflect in a first direction and a second direction through the deflection lens cone, so that the electron beam performs point-by-point scanning on a first scanning range; an electron beam collecting device in the measuring barrel lens is used for collecting a current value corresponding to each scanning point, and the control module is further used for generating a grayscale image based on the current values and adjusting the position of the electron gun according to the position of a hot spot in the grayscale image until the center of the hot spot coincides with the center of the image. The maintenance efficiency of the electron microscope equipment can be improved, the maintenance difficulty is reduced, and the downtime is shortened.

The magnetic tape includes a non-magnetic support, and a magnetic layer containing a ferromagnetic powder. The ferromagnetic powder is a hexagonal ferrite powder, tilt cos θ of the hexagonal ferrite powder with respect to a surface of the magnetic layer, which is acquired by cross-sectional observation performed using a scanning transmission electron microscope, is 0.85 or more and 1.00 or less, and standard deviation σ of the cos θ in a width direction of the surface of the magnetic layer is 0.03 or less.

The invention relates to a powder coating particle size automatic analysis method, which comprises the following steps: obtaining a powder coating particle image shot by an electron microscope, carrying out feature extraction on the particle image to obtain a plurality of feature maps, dividing each feature map into image blocks with the same size, obtaining areas of the image blocks on the particle image, obtaining a foreground score of the image block by using the average gray value and the contour line length of the region; selecting a plurality of target image blocks from each feature map according to the foreground score and particle size distribution information in the particle image, calculating the attention of the target image blocks at each layer of the encoder, and then calculating the attention of the target image blocks and the filtered image blocks based on the average gray value; and obtaining an output corresponding to the target image block in the encoder, taking the output as an input of a decoder, obtaining a particle frame in the particle image through the decoder, and obtaining particle size information of the powder coating according to the particle frame.

The invention discloses a method and device for identifying organic matter pores in a shale electron microscope scanning image, and the method comprises the steps: obtaining a shale scanning electron microscope original image, carrying out the manual marking, and generating an original image and mask image data set; performing synchronous data enhancement on the data set and dividing a training set and a verification set; constructing an improved U-Net model containing a multi-scale feature fusion input module, a residual attention module and a wavelet domain feature enhancement center module; training the model by adopting a dynamic mixed loss function and an AdamW optimizer; and verifying the model through an average intersection-to-union ratio, a pore Dice coefficient and a pore error, and identifying the pores of the image to be processed after reaching the standard. The device correspondingly comprises an image acquisition annotation module, a data preprocessing module, a model construction module, a training module, a verification module and a pore recognition module. According to the method, full-automatic identification is realized, the multi-scale pore segmentation precision and the low-porosity sample adaptability are improved, and the efficient characterization requirement of the shale gas reservoir is met.

The invention discloses an integrated circuit equipment data optimization monitoring system and method based on big data, and relates to the technical field of integrated circuit manufacturing. The method is used for solving the problems of insufficient multi-physical field monitoring, difficulty in abnormal traceability and lack of closed-loop control in plasma etching. A plasma sheath thickness inversion model and an etching selection ratio model are constructed by collecting radio frequency reflection phase, mass spectrum ion strength and wafer temperature data, and process parameter-plasma state dynamic coupling is established. Interference image distortion features and electron microscope size data are fused, micro-groove geometric parameters are analyzed, morphology instability risk indexes are generated, and nanoscale early warning is achieved. And designing a dual-channel fusion network, embedding a physical constraint attention mechanism, and generating an etching rate optimization instruction. On the basis of incremental learning, model parameters are updated online, a'monitoring-decision-feedback 'closed-loop system is formed, anomaly detection sensitivity and decision reliability are improved, and technical support is provided for intelligence of integrated circuit equipment.

A protein structure prediction method based on a cryoelectron microscope and a diffusion model comprises the following steps: extracting feature points from an electron density map of the cryoelectron microscope, converting the feature points into point cloud structures, and predicting corresponding amino acid types through a DAQ model according to the point cloud structures; one-dimensional and two-dimensional tensor features are obtained for an input amino acid sequence through an AlphaFold2 neural network and are used for training and constructing an obtained denoising neural network based on conditional diffusion, so that the denoising neural network supports input of point cloud structure information of a cryoelectron microscope and fusion of electron microscope information and sequence information; and the trained denoising neural network is matched with a sampling process based on conditional diffusion to realize protein skeleton structure prediction. According to the method, a more accurate prediction structure is given according to the information of the cryoelectron microscope, meanwhile, a change conformation space is reflected through the diffusion model, the prediction structure precision can be improved on the basis of a low-quality prediction structure prediction sample, meanwhile, the overall structure prediction precision based on the electron density map of the cryoelectron microscope is improved, and the change of the prediction structure conformation is reflected.

To provide an oxide semiconductor layer that can be used for a semiconductor device with favorable electrical characteristics.SOLUTION: There is provided an oxide semiconductor layer which is formed over a substrate and includes indium. The oxide semiconductor layer is formed in parallel or substantially in parallel with a surface of the substrate. The oxide semiconductor layer includes a first region, a second region over the first region, and a third region over the second region. The first region is located in a range from a surface on which the oxide semiconductor layer is to be formed to greater than or equal to 0 nm to less than or equal to 3 nm in a direction substantially perpendicular to the surface. In cross-sectional observation of the oxide semiconductor layer using a transmission electron microscope, bright spots arranged in a layered manner in a direction parallel to the surface on which the oxide semiconductor layer is to be formed are observed in each of the first region, the second region, and the third region.SELECTED DRAWING: Figure 2

The invention relates to the technical field of electron microscope sample pretreatment, and discloses a critical point drying control method and device based on online near-infrared monitoring, and the method comprises the steps: obtaining infrared spectrum data, and unmixing the spectrum data to obtain a feature data set of a solvent; outputting a to-be-corrected signal according to the feature data set, correcting the to-be-corrected signal with preset data, and determining a signal feature of the solvent; carrying out dynamic correction on the signal characteristics and a preset characteristic matrix, outputting concentration time sequence data of the solvent, carrying out steady state judgment by combining a preset convergence threshold value, and determining a critical state of the solvent; acquiring control strategy data according to the critical state, analyzing the control strategy data into execution response characteristics, performing multi-channel mapping and correction processing, and outputting a process control signal; and performing control gain correction on the process control signal to finish closed-loop feedback control of the final drying process. The method is based on multi-solvent spectrum sensing and concentration dynamic analysis, and self-adaptive closed-loop control of the critical point drying process is achieved.

The invention relates to the technical field of metal material sample preparation, in particular to a preparation method for extracting carbon replica of steel for a high-carbon wire rod. The method specifically comprises the following steps: S1, preparing a sample; s2, immersing the sample into a nitric acid alcohol solution; s3, placing the sample in a sample chamber of a high-vacuum coating instrument, evaporating a carbon film with the thickness of 10-20 nm on the surface of the sample, and taking out the sample after vacuum is relieved; s4, performing electrolytic film removal by adopting an electrolytic polishing corrosion instrument; s5, after the carbon film falls off, the nitric acid alcohol on the carbon film is cleaned until the absolute ethyl alcohol in the weighing bottle is colorless; s6, the carbon film is transferred into deionized water, after the carbon film is fully unfolded, the carbon film is fished up through a transmission electron microscope and a copper net and placed on filter paper, and the carbon film is tightly attached to the copper net; and S7, baking the carbon film sample adhered to the copper mesh for 30-60 seconds, and placing the dried sample under an electron microscope for observation to complete the preparation of the steel extraction carbon replica sample for the high-carbon wire rod. The method has the advantages of high demolding speed, complete and firm carbon film form, simple configuration and low cost.

The invention provides a CNN-based electron microscope rapid automatic focusing method and system, and relates to the technical field of electron microscope automatic focusing, and the method comprises the steps: collecting an electron microscope image, and carrying out the preprocessing of the image, and training a pre-constructed CNN model; inputting a real-time image into the trained CNN model, predicting an offset, and calculating a definition value; determining a focusing distance of next shooting based on the predicted offset and the definition value; focusing shooting is adjusted, and multiple sets of focusing distance and definition value data are collected until the preset number of times is reached; converting the data into coordinate points, fitting a Gaussian curve, and solving to obtain an optimal focusing distance; and adjusting the electron microscope according to the predicted optimal focusing distance to complete automatic focusing. According to the invention, shooting times are reduced, materials are protected, image definition is flexibly evaluated, high-precision automatic focusing is realized, and the model can be adaptively retrained and cope with changes and is flexible and practical.

Various implementations include a low temperature sample rod device for side entry electron microscopes. The device includes a conduction rod, a thermoelectric module, a coupler, and a thermal battery. The conduction rod has a first end configured to support a sample. The thermoelectric module has a first side thermally coupled to a second end of the conduction rod. The thermoelectric module is configured to transfer heat between the first side and a second side when supplied with electricity. The coupler has a first coupling surface thermally coupled to the second side of the thermoelectric module. The thermal battery has a battery coupling surface configured to be thermally coupled to a second coupling surface of the coupler. The thermal battery includes a material that can be melted from solid to liquid phase by heat transferred from the conduction rod, through the thermoelectric module, through the coupler, and into the thermal battery.

The invention discloses a preparation device of an electron microscope sheet sample, and belongs to the field of test and measurement. The cutting unit and the grinding unit are integrally arranged, and the feeding unit penetrates through the cutting unit and the grinding unit, so that feeding, cutting and grinding of samples can be sequentially completed by one set of device, the samples do not need to be transferred among different devices, and the sample processing quality is also improved while the sample processing efficiency is improved; in the whole set of preparation device, the working mode that the feeding unit and the grinding unit work simultaneously, the cutting unit and the receiving cavity discharge work simultaneously, and the feeding unit and the grinding unit as well as the cutting unit and the receiving cavity work alternately is achieved, and the adjacent units work alternately; according to the transmission electron microscope slice sample processing device, the preparation cohesion of feeding, cutting, grinding and discharging of a single sample is ensured, and synchronous operation of all unit components in the whole device is also ensured, so that continuous online production of transmission electron microscope slice samples can be realized, and the processing efficiency is favorably improved.

The invention discloses a machine vision-based automatic identification and calculation method for pore change of a rock section under an SEM (scanning electron microscope), and the method comprises the steps: obtaining original image data of the rock section through a scanning electron microscope, transmitting the original image data to a machine vision SEM pore intelligent quantification cloud platform, and dividing the original image data into a plurality of image sub-regions which are not overlapped with each other; calling a special threshold inversion model to analyze the gray information of each sub-region, and determining a dual-phase pore segmentation threshold; carrying out edge extraction on the sub-regions after threshold processing by adopting a pore edge gradient enhancement algorithm; performing topological structure analysis on the intermediate image data by using a biphase pore topological inversion model, constructing and optimizing a pore space topological network, and eliminating false pore structure data; and according to the optimized pore space topology network, integrating calculation results of all the sub-regions to obtain a pore change identification calculation result of the whole rock section. The method improves the pore identification precision and processing efficiency, and adapts to different types of rock samples.

The present invention relates to the field of adsorption materials. Disclosed are a lithium adsorption material, a preparation method therefor and a use thereof. The lithium adsorption material comprises a core and a shell covering the surface of the core; pores are formed in the shell of the lithium adsorption material, and the average diameter of the pores measured by a SEM electron microscope is 0.01-2.5 μm; the core of the lithium adsorption material comprises finger-like pores, and in the cross section of the lithium adsorption material, the maximum average length of the finger-like pores measured by the SEM electron microscope is 1-7 μm, and the minimum average length is 0.05-2.5 μm; and the thickness of the shell of the lithium adsorption material measured by the SEM electron microscope is 1-550 μm. The lithium adsorption material with the specific structure has a special structure having small pores in the outer shell and large pores in the inner core, the mass transfer rate of water and salt can be increased, and when the lithium adsorption material is used for extracting lithium in a liquid environment, the adsorption capacity for lithium can be significantly improved.