932 results about "Electron microscope" patented technology

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 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.

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 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 invention discloses a microscopic crack dynamic in-situ characterization method, and relates to the technical field of crack in-situ detection. According to the method, a plurality of hardened cement paste bodies are soaked in a sulfate solution, the porosity development trend of the hardened cement paste bodies is obtained through a nuclear magnetic resonance test and a mercury injection test in the soaking process, a test sample and a test sample are prepared after soaking is finished, and the crack propagation length of the test sample is measured through a scanning electron microscope. According to the distance gradient between the sampling angle of the test sample and the exposed surface, space coordinates of crack cracking are converted into a time process along the center axis of the test sample, a delay microscope is established on the microscale, and the test sample is scanned by using X-ray computed tomography equipment in a matched mode; a crack propagation animation image is formed based on a crack form between adjacent X-ray tomography slices, and a crack development process is obtained by continuously capturing high-resolution images, so that omission of time information is avoided, and in-situ detection of microscopic cracks in a hardened cement paste sample is realized.

The invention provides a method for measuring and calculating the article position of continuous silver ore with the particle size of 0.037 mm or above, and belongs to the technical field of mineral grade detection. The silver grade in the sample is measured and calculated through screening; leaching and measuring the content of silver monomers and continuous silver minerals, and reselecting to obtain a heavy sand product; carrying out fluorescent dyeing on the heavy sand product, and selecting monomer silver minerals; analyzing the color of the silver mineral through point scanning data of a scanning electron microscope, melting the monomer silver mineral to obtain the volume of the monomer silver mineral, and calculating the content of the monomer silver mineral; and carrying out conversion to obtain the continuous silver ore article position with the size of more than 0.037 mm. According to the method, the target mineral is rapidly and accurately obtained by adopting density medium reselection and fluorescent dye tracing; introducing a scanning electron microscope to measure and calculate the actual density of the silver mineral to replace the theoretical density, smelting the silver mineral in a mold, and carrying out volume measurement and calculation to obtain the actual metal amount closer to the actual silver mineral; measuring and calculating errors caused by impurities and irregular shapes of mineral particles are reduced; and the calculated grade of the silver mineral is more accurate.

The invention discloses chicken infectious anemia virus-like particles as well as a preparation method and application thereof. The invention discloses a virus-like particle vaccine for preventing chicken infectious anemia. The virus-like particle vaccine comprises VP1 and VP2 proteins of chicken infectious anemia viruses. Chicken infectious anemia VP1 and VP2 proteins are expressed by using a baculovirus expression system, immunoblotting shows that the two proteins are successfully expressed in sf9 cells, electron microscope observation finds that the expressed proteins can be autonomously assembled into complete chicken infectious anemia virus-like particles, and the chicken infectious anemia virus-like particles have a space structure similar to that of an original virus and can be used for preparing chicken infectious anemia virus-like particles. Meanwhile, the virus-like particles have the advantages of high titer, high safety, capability of stimulating humoral immunity and cellular immunity and the like. The preparation method disclosed by the invention is simple, can be used for preparing the antigen protein of the chicken infectious anemia virus on a large scale, is high in expression quantity and short in time consumption, greatly reduces the production cost, and is suitable for large-scale production.

The invention relates to the technical field of electron microscopic imaging, in particular to a correction method and device for geometric distortion in scanning electron microscope measurement, computer equipment, a storage medium and a computer program product. The method comprises the following steps: acquiring a scanning electron microscope image of a standard sample; calculating an orthogonal included angle parameter and a length-width ratio parameter of the scanning electron microscope image; iteratively adjusting the angle correction parameter and the gain correction parameter under a fixed scanning rotation angle until a preset local calibration constraint condition is met; verifying the orthogonal included angle parameter and the length-width ratio parameter under each scanning rotation angle; and when the orthogonality included angle parameter and the length-width ratio parameter do not meet a preset global stability constraint condition, adjusting a relative gain coefficient, and re-executing calibration verification under each scanning rotation angle until a full-angle correction requirement is met. By adopting the method, high precision and stability of imaging correction can be kept in a full-angle range.

The invention relates to an ultrafast electron microscopic imaging device and an imaging method thereof, in particular to a multi-mode multi-dimensional ultrafast electron microscopic imaging device and an imaging method thereof, and solves the problem that the existing electron microscopic imaging technical scheme is difficult to simultaneously meet the measurement requirements of high time-space-energy-momentum resolution and material diversification. The device comprises a sample cabin, an electron gun, a laser generation module, a secondary electron detector, an STEM detector, an in-cabin plug-in detection assembly, a plug-in camera and an energy filtering electron microscope assembly which are arranged below the sample cabin, and a vacuum system, a hollow sample table is arranged in the sample cabin, and at least two ultrafast pumping laser introduction windows are arranged on the cabin wall of the sample cabin; an ultrafast detection laser introduction window is arranged on the electronic gun shell; the secondary electron detector is arranged obliquely above the sample table; the STEM detector is arranged on the side cabin wall of the sample cabin and is positioned below the sample table; and the in-cabin plug-in detection assembly is arranged below the STEM detector.

A method for generating a training dataset for determining grain boundaries and minerals in a thin section of a rock sample, includes receiving the thin section of the rock sample, generating optical images of the thin section with an optical tool, generating mineral phase images of the thin section with an electron microscopy tool, computing first and second pseudo-images based on different features extracted from the optical images, generating the training dataset based on (1) the optical images, (2) the mineral phase images, and (3) the pseudo-images, and training a single deep neural network, DNN, based on the training dataset to simultaneously determine a mineral type and grain boundaries in the thin section of the rock sample.

The invention relates to a mechanical property simulation method for researching the service life of an aluminum alloy material for a reactor. The simulation method for the life period mechanical property of the aluminum alloy material comprises the following steps: S1, preparing initial, middle and last stage aluminum alloy samples according to a < 27 > Al-< 28 > Si transmutation path of the aluminum alloy material; s2, representing the sample by using a transmission electron microscope, obtaining precipitated particle parameters, calculating a volume fraction f, fitting f and operation time t, and constructing a precipitation evolution model f (t); s3, performing high-energy ion irradiation on the sample, and performing nanoindentation experiment and load-depth curve fitting to obtain nano hardness H; s4, based on the f (t), establishing a relation model of the nano hardness H and the irradiation damage D; and S5, calculating the change quantity of the nano hardness H, converting the change quantity into the change quantity of the yield strength, associating the irradiation damage D with the service time T, and establishing a life period yield strength prediction model. According to the method, the mechanical property of the aluminum alloy in the full service cycle of the research reactor can be accurately evaluated.

The invention discloses a bus duct insulation performance evaluation system, and the system comprises a microscopic collection module which is used for collecting a joint interface microscopic image through a scanning electron microscope, and obtaining material distribution and defect parameters; the finite element analysis module is used for performing finite element analysis by utilizing the material distribution and defect parameters and calculating an electric field intensity gradient value; the electric field distortion identification module is used for identifying an electric field distortion area according to the electric field intensity gradient value and determining a partial discharge position coordinate; the dielectric parameter measurement module is used for measuring a dielectric constant and a loss factor at the partial discharge position coordinates to generate a change curve; the aging index calculation module is used for extracting peak value and slope characteristics from the change curve and calculating a material aging index; the correlation model building module is used for building a correlation model of the material aging index and the insulation strength and generating a prediction coefficient; and the evaluation optimization module is used for correcting the insulation performance evaluation value by using the prediction coefficient and outputting an optimization evaluation report.

The invention relates to a comprehensive optimization method and system for thermal conductive plastic performance in the technical field of new materials, and the method comprises the following steps: obtaining initial dispersion state data of an inorganic filler in thermal conductive plastic, and analyzing spatial distribution of filler particles through a scanning electron microscope to obtain characteristic parameters of random distribution of the filler; according to the characteristic parameters of the random distribution of the filler, calculating the heat transfer efficiency among filler particles by adopting a finite element simulation method, and determining the distribution rule of the phonon scattering phenomenon; according to the improved interface bonding strength parameters, the Monte Carlo method is adopted to simulate orientation distribution of filler particles in a matrix, and a preliminary scheme of filler orientation control is obtained; for optimization parameters of complex mold forming, a particle swarm optimization algorithm is adopted to adjust the filler proportion and distribution, and the structure configuration of the efficient three-dimensional heat conduction network is generated; and according to the structure configuration of the efficient three-dimensional heat-conducting network, the improvement degree of the heat-conducting plastic performance is analyzed and verified through a heat-conducting finite element, and final heat transfer efficiency data is obtained.

The invention relates to the technical field of semiconductors, and provides an amplification factor calibration method of a scanning electron microscope. The method comprises the following steps: in a TEM imaging mode, TEM measurement data of a key structure of a TEM sample is determined, and the TEM sample is a TEM sample with a known process structure size or clear lattice fringes; in an SEM imaging mode, determining an SEM measurement data set of the key structure of the TEM sample under different SEM amplification factors; each SEM magnification of the scanning electron microscope is calibrated based on the TEM measurement data and the SEM measurement data set. The method is easy and convenient to operate, does not need to depend on a standard sample, and is lower in calibration cost and higher in calibration accuracy.

Systems, methods, and media for calibrating a scanning electron microscope (SEM). The system includes a processor and a memory. The memory stores instructions that, when executed by the processor, configure the system to perform operations. An electron microscope image of a periodic structure is generated by the SEM. A Fourier transform of the electron microscope image is computed to generate a spectrum. Reciprocal lattice vectors are computed based on a known periodicity of the periodic structure. A pixel mask is generated based on the reciprocal lattice vectors and applied to filter the spectrum. A quality metric is generated based on an aggregate magnitude of the filtered spectrum and a magnitude of a zero-frequency component of the filtered spectrum. A pixel scaling parameter, focus parameter, and / or stigmation parameter of the SEM are determined based on the quality metric.

The invention relates to the technical field of material analysis, in particular to a light microscope-field emission electron microscope combined shale rock slice analysis and identification method, which comprises the following steps of: firstly, combining a brightness distribution condition represented by a bright field image of a shale rock slice and a birefringence deviation condition represented by a cross polarization image from an optical angle; determining a mineral discrimination index representing an atomic number agent; applying offsets of different sizes based on the distribution condition of mineral discrimination indexes and the surface fluctuation condition of shale rock slices, and determining a position offset vector by combining gray scale gradient distribution on the basis; and finally, determining the cross-scale positioning and more accurate electron microscope objective table coordinates corresponding to each pixel point in combination with a position offset vector in a pixel coordinate conversion process based on an image physical distance scale and rotation translation processing, so that the cross-scale positioning accuracy of the optical microscope and the field emission scanning electron microscope is higher. The reliability of analyzing and identifying the shale rock slice is obviously improved.

The invention discloses a method for preparing a section sample of a new energy automobile battery powder material, and relates to the technical field of battery material analysis, and the method comprises the following steps: uniformly mixing a battery powder material with a liquid conductive adhesive solution; pouring the mixture into a mold for curing, and demolding to obtain a conductive sample block with a regular shape; directly loading the conductive sample block in an ion beam cutting system for ion cutting to obtain a flat sample section; and surface metal spraying treatment is not needed, and electron microscope observation and analysis are directly carried out. According to the preparation method, the conductive adhesive solution is adopted for inlaying and is combined with mold forming, so that time-consuming mechanical grinding and polishing procedures in a traditional method are omitted, and the preparation period is greatly shortened; and meanwhile, an in-situ conductive network formed after the glue solution is cured is utilized to effectively inhibit the charge effect, so that direct observation without metal spraying is realized, sample preparation damage and plating interference are avoided, and the authenticity and accuracy of an analysis result are ensured. The method is simple and convenient to operate and good in repeatability.

The invention relates to the technical field of brain science image processing, and discloses a brain tissue neuronal morphology three-dimensional reconstruction and connection group analysis method and system, and the method comprises the steps: carrying out the feature point extraction and matching and optical flow registration of continuous ultrathin section electron microscope images, and obtaining three-dimensional image volume data; carrying out semantic segmentation on cell bodies, dendrites, axons and dendritic spines through a three-dimensional deep convolutional neural network, and driving secondary registration through confidence feedback; detecting synapses and classifying the synapses as excitatory or inhibitory types; executing topology perception skeletonized reconstruction and performing segmentation correction through topology anomaly feedback constraint; and constructing a synaptic connection matrix and executing graph theory analysis.

This invention provides a PAM staining method that enables staining suitable for magnified observation of various samples using a range of microscopes, from optical microscopes to electron microscopes. [Solution] A PAM staining method comprising the steps of: silvering a biological sample; coloring the biological sample; and fixing the color of the biological sample, wherein the biological sample is a biologically derived sample that has been oxidized; the silvering step involves immersing the biological sample in a methenamine silver aqueous solution at room temperature, raising the methenamine silver aqueous solution from room temperature to 62°C or higher and 68°C or lower, and carrying out the silvering reaction for 30 to 40 minutes from the start of the reaction at room temperature; the coloring step involves immersing the silvered biological sample in a 0.2% gold chloride aqueous solution at room temperature for 8 to 12 hours; and the fixing step involves immersing the sample in a hard film fixing solution containing 11% to 13% sodium thiosulfate and aluminum potassium sulfate dodecahydrate for 3 minutes or more at room temperature.

The invention relates to the technical field of scanning electron microscope image processing, and discloses a scanning electron microscope image restoration method based on a wavelet frequency domain adjustment diffusion model, and the method comprises the steps: constructing a two-stage degradation pipeline comprising random light path disturbance and fixed circuit collection limitation, and generating a specific domain training data set; extracting multi-scale high-frequency energy characteristic modulation noise distribution by using a frequency domain prior encoder, and training a wavelet frequency domain adjustment diffusion model; and inputting a target low-quality degraded image into the pre-training model, initializing a potential noisy state, then executing reverse denoising iteration, calculating wavelet domain consistency gradient correction noise prediction, and updating the potential noisy state until a restored image is generated. According to the method, data distribution mismatch is relieved through physical degradation modeling, high-frequency detail perception is enhanced by means of a frequency domain adjustment mechanism, the structural fidelity is improved through wavelet domain gradient guidance, and balance between scanning electron microscope image noise suppression and detail recovery is achieved.

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 relates to the technical field of wafer defect detection, and discloses a wafer defect detection method, a storage medium and electronic equipment.The wafer defect detection method comprises the steps that an electron microscope is controlled to conduct positioning scanning on a target lattice in a wafer according to optical coordinates of the target lattice, and an electron microscope image of the target lattice is obtained; and performing defect detection on the electron microscope image of the target lattice by using a pre-trained ViT model to generate a defect type of the target lattice. According to the wafer defect detection method, the electron microscope image of the target lattice in the wafer can be obtained by controlling the electron microscope to scan according to the optical coordinate of the target lattice, convenient control and acquisition of the high-resolution electron microscope image of the target lattice are realized, defect detection is performed on the electron microscope image of the target lattice by using the pre-trained ViT model, and the defect detection accuracy is improved. And fine defect classification of a target lattice can be realized.

The invention belongs to the crossing field of computer vision and material micro-analysis, and relates to a cross-scale invariant information-based intelligent identification method for a fiber master batch agglomeration structure, which comprises the following steps of: constructing and training an end-to-end detection frame for extracting cross-scale invariant information, and inputting a to-be-identified fiber color master batch electron microscope image into the end-to-end detection frame; outputting an identification result of the agglomeration structure; the detection framework comprises a convolutional network with selectively enhanced edge information, a self-attention encoder, a self-attention decoder, a scale classifier and a full-connection network. According to the method, an artificial intelligence supervised learning mode is utilized, accurate and robust effective recognition is carried out on cross-scale fiber master batch aggregation by learning invariant information of aggregation in a cross-scale ultrastructure, and the method has important significance on actual industrial fiber color master batch preparation.

To provide an aluminum alloy sheet excellent in rollability.SOLUTION: 0.05% by mass or more and 0.35% by mass or less of Si, 0.05% by mass or more and 0.50% by mass or less of Fe, 0.01% by mass or more and 0.35% by mass or less of Cu, 0.10% by mass or more and 0.80% by mass or less of Mn, 2.0% by mass or more and 6.0% by mass or less of Mg, 0.01% by mass or more and 0.15% by mass or less of Cr, and a balance of Al and inevitable impurities, in a cross section in a sheet thickness direction, a ratio of an area occupied by central grains is 1.15% or less, and in a sheet thickness Mg2Si region, a number-density ratio obtained by dividing a number-density of precipitates observed with a transmission-type electron microscope by a number-density in a reference aluminum alloy sheet, a Si-amount ratio obtained by dividing a Si content by a reference Si content, and a Mg-amount ratio obtained by dividing a Mg content by a reference Mg content satisfy the following formulas: Number density ratio ≥ 10.929 * Si amount ratio - 15.814 + 2.043 * (Mg amount ratio - 1) SELECTED DRAWING: Figure 5

The invention discloses a method for measuring the number of layers of a two-dimensional material by utilizing Goos-Haenchen displacement, which comprises the following steps: establishing a Goos-Haenchen displacement theoretical database when a horizontal polarized light beam is reflected on the surfaces of the two-dimensional materials with different layers at different incident angles according to a theoretical relation model of the two-dimensional materials with different layers and the Goos-Haenchen displacement; enabling the horizontal polarization incident light beam to be incident to the surface of the measured two-dimensional material at a certain incident angle; measuring Goos-Hanchen shift generated by the reflected light beam under the condition; sequentially changing the incident angles to obtain a group of Goos-Hanchen shift measurement data under different incident angles; and comparing and analyzing the measured data with theoretical data in a Goos-Hanchen shift theory database to obtain the number of layers of the measured two-dimensional material. Compared with a traditional two-dimensional material layer number measuring method, such as a Raman spectrum method, an atomic force microscopy method and a transmission electron microscope method, the method is easy to operate and high in measuring efficiency, does not damage a sample and has a good application prospect.

The invention discloses a scanning electron microscope three-dimensional shape measurement method and a measurement system thereof, which are characterized in that the method adopts a directional focusing method to perform separated focusing and measurement on the top and the bottom of a target structure, and three-dimensional shape parameters of the target structure are obtained through a definition evaluation function; the system comprises a displacement sample stage system, an electron beam imaging system and an image processing algorithm, the electron beam imaging system is composed of an electron source, an electromagnetic lens, an electron detector and an imaging module, and the electron beam imaging system generates a focused electron beam and obtains a secondary electronic signal image; the image processing algorithm is integrated in an electron beam imaging module in the CD-SEM, and accurate positioning, feature recognition and precise measurement of a target structure are achieved. Compared with the prior art, the method has the advantages that directional focusing of the top or the bottom is achieved by analyzing the gradient distribution characteristics of the image profile curve, and the measurement problem of separating and quantifying key three-dimensional parameters such as the side wall angle, the bottom key size and the structure depth is effectively solved.

The invention provides an infrared detector readout circuit repairing method, and relates to the technical field of silicon readout circuit repairing, and the method comprises the steps: screening chips with abnormal electrical properties from processed circuit chips, and determining the relative coordinates of a problem line and a nearest bonding pad according to the fault type; under an FIB-SEM double-beam scanning electron microscope, the sample table is moved to reach the relative coordinates, and a reference pattern with the depth shallower than the thickness of the metal layer is formed through etching with the relative coordinates as the center; measuring a problem line operation point coordinate by taking the reference graphic feature point as a zero point; performing etching exposure on the coordinate area of the operation point by using an FIB-SEM double-beam scanning electron microscope; and carrying out line repairing operation. The problems that the reference point distance is long and the positioning deviation is large are effectively solved, and accurate positioning of a small-feature-size circuit needing to be operated in the infrared detector reading circuit repairing process is achieved.

The invention relates to a processing method of a transmission electron microscope test piece and the transmission electron microscope test piece, the transmission electron microscope test piece comprises a plurality of holes arranged at intervals, the inner wall of each hole is provided with a diffusion barrier layer comprising a multi-layer structure, and the processing method comprises the following steps: arranging a first protection layer on the surface of the diffusion barrier layer; a reserved area is divided in the hole, a first edge line and a second edge line which are oppositely arranged are divided in the reserved area, the reserved area comprises two arc-shaped sections located on the edge of the hole, and the first edge line and the second edge line are connected between the two arc-shaped sections; cutting the transmission electron microscope test piece from the outer side of the reserved area to the first edge line; cutting the transmission electron microscope test piece from the outer side of the reserved area to a second edge line; a remaining portion of the first protective layer is removed. Thus, the cross section of the hole can be exposed, layering of the diffusion barrier layer on the surface of the inner wall of the hole can be observed, the boundary between multiple layers is more obvious, the coating condition of the diffusion barrier layer can be checked more easily, and whether the coating missing phenomenon exists or not can be judged.

The application provides a method for regulating halogen perovskite microstructure at a frozen temperature by using a laser and an electric field, and relates to a device, which is a customized TEM in-situ sample rod equipped with a laser optical fiber and a liquid nitrogen Dewar bottle, and a Nd:YAG pulse laser system with a wavelength of 532 nm, adjustable pulse frequency and a pulse duration of 7 ns coupled into a transmission electron microscope through the optical fiber; first, at a frozen temperature, perovskite nanocrystals are etched by controlling the energy, frequency and action time of the pulse laser, then at the frozen temperature, the small crystal nucleus rotation of the perovskite nanocrystals is controlled by using a low-energy pulse laser and applying an electric field, and the perovskite nanocrystals are recrystallized along specific crystal faces, so that perovskite nanocrystals with specific exposed surfaces, reduced microstructure defects and increased radiation resistance are obtained, and the method has great value for large-scale industrial production.