Contact hole defect detection method, apparatus, device, medium, and program product

Abstract

The application relates to a contact hole defect detection method, device, equipment, medium and program product. The method comprises the following steps: acquiring a scanning electron image of a real wafer contact hole region, and constructing an initial three-dimensional structure model of the contact hole region based on the scanning electron image; performing electron trajectory simulation based on the initial three-dimensional structure model to obtain an initial electron beam imaging image; determining a sensitive region based on the initial electron beam imaging image; determining a target simulation rule based on the sensitive region, and performing electron trajectory simulation based on the target simulation rule and the initial three-dimensional structure model to obtain a target electron beam imaging image; generating a target three-dimensional structure model based on the target electron beam imaging image, and performing contact hole defect detection based on the target three-dimensional structure model. The method can improve the efficiency.

Description

Technical Field

[0001] This application relates to the field of semiconductor technology, and in particular to a method, apparatus, device, medium, and program product for detecting contact hole defects. Background Technology

[0002] In advanced semiconductor manufacturing processes, integrated circuits continue to evolve towards miniaturization and high integration. The reliability of the connection between front-end and back-end processes directly determines chip performance and yield. Contact holes, as the core vertical channels connecting the active regions of silicon-based transistors to the corresponding metal interconnect layers, need to be formed in the interlayer dielectric layer through high-precision photolithography and etching. The integrity of this etching is crucial for ensuring the electrical conductivity of the device. Due to micro-load effects, etching uniformity fluctuations, and process deviations, incomplete etching of insulating dielectrics such as silicon oxide is prone to occur at the bottom of the contact hole. Residual insulating layers can block the effective connection between the metal filler and the silicon substrate, leading to device open circuits.

[0003] In traditional technologies, the mainstream detection method for residual defects at the bottom of contact holes includes transmission electron microscopy (TEM) section inspection. TEM inspection achieves sub-nanometer cross-sectional imaging by preparing ultrathin sections, which can directly observe the thickness and location of residual defects and is the gold standard for defect verification.

[0004] However, TEM inspection requires complex sample preparation processes such as slicing and thinning, which takes several hours and consumes a lot of manpower. Furthermore, it is a destructive inspection method, requiring the scrapping of the entire wafer, resulting in significant material and cost waste. Therefore, there is an urgent need for a method that can detect defects in contact holes caused by incomplete bottom etching, leading to residual insulating materials such as silicon oxide. Summary of the Invention

[0005] Therefore, it is necessary to provide a contact hole defect detection method, apparatus, equipment, medium, and program product that can detect contact hole defects without damaging the wafer, in order to address the above-mentioned technical problems.

[0006] In a first aspect, this application provides a method for detecting contact hole defects, the method comprising:

[0007] A scanning electron image of the actual wafer contact hole region is obtained, and an initial three-dimensional structural model of the contact hole region is constructed based on the scanning electron image.

[0008] Based on the initial three-dimensional structural model, electron trajectory simulation is performed to obtain an initial electron beam imaging image;

[0009] Based on the initial electron beam imaging image, the sensitive region is determined;

[0010] Based on the sensitive region, target simulation rules are determined, and electron trajectory simulation is performed based on the target simulation rules and the initial three-dimensional structure model to obtain the target electron beam imaging image;

[0011] A three-dimensional structural model of the target is generated based on the target electron beam imaging image, and contact hole defects are detected based on the target three-dimensional structural model.

[0012] In one embodiment, constructing an initial three-dimensional structural model of the contact hole region based on the scanned electronic image includes:

[0013] Extract the grayscale curve and contour curve of the scanned electronic image;

[0014] Based on the grayscale curve and contour curve, an initial three-dimensional structural model of the contact hole region is constructed using a stereo matching algorithm or a three-dimensional reconstruction algorithm.

[0015] In one embodiment, the method further includes:

[0016] Based on the initial three-dimensional structural model, electron trajectory simulation was performed to obtain the initial diffraction pattern;

[0017] The process of determining the sensitive region based on the initial electron beam imaging image includes:

[0018] The initial electron beam imaging image is compared with the reference electron beam imaging image corresponding to the defect-free contact hole to obtain the first deviation value for each region, and the region with the first deviation value greater than the first deviation threshold is designated as the sensitive region; or

[0019] The initial electron beam imaging image is compared with the reference electron beam imaging image corresponding to the defect-free contact hole to obtain the first deviation value corresponding to each region; the initial diffraction pattern is compared with the reference diffraction pattern corresponding to the defect-free contact hole to obtain the peak position deviation value; based on the target position where the peak position deviation value is greater than the second deviation threshold and the region where the first deviation value is greater than the first deviation threshold, the sensitive region is determined.

[0020] In one embodiment, determining the target simulation rules based on the sensitive region includes:

[0021] Reduce the sampling interval and / or increase the number of samples corresponding to the sensitive region, and maintain or expand the sampling interval and / or reduce the number of samples corresponding to the non-sensitive region, wherein the non-sensitive region is the region in the initial three-dimensional structural model other than the sensitive region.

[0022] In one embodiment, the step of performing electron trajectory simulation based on the target simulation rules and the initial three-dimensional structure model to obtain a target electron beam imaging image includes:

[0023] A multi-field coupled physical model is established based on the electron transport equation, the heat conduction equation, and the elasticity equation. The electron transport equation is used to calculate the electron signal and motion trajectory corresponding to the electron beam imaging image. The heat conduction equation is used to determine the temperature distribution of the wafer based on the energy deposition of the electrons. The elasticity equation is used to determine the lattice distortion in the wafer based on the temperature distribution and to obtain the thermal stress field distribution based on the lattice distortion. The multi-field coupled physical model is used to determine the scattering cross section of the contact hole.

[0024] Based on the target simulation rules, the electron trajectory of the initial three-dimensional structure model is simulated to obtain the current electron beam signal;

[0025] The scattering cross section, temperature distribution, and thermal stress field distribution are iteratively corrected based on the multi-field coupled physical model, and the initial three-dimensional structural model is iteratively optimized based on the scattering cross section, temperature distribution, and thermal stress field distribution.

[0026] Based on the optimized initial three-dimensional structural model and the target simulation rules, the electron trajectory is re-simulated to obtain the current electron beam signal;

[0027] If the iterative convergence condition is met, the target electron beam imaging image is generated based on the current electron beam signal obtained in the final iteration.

[0028] In one embodiment, before generating the target three-dimensional structure model based on the target electron beam imaging image, the method further includes:

[0029] Based on the target simulation rules and the initial three-dimensional structural model, electron trajectory simulation is performed to obtain the target diffraction spectrum;

[0030] Based on the target electron beam imaging image and the reference electron beam imaging image corresponding to the defect-free contact hole, the image error value is obtained; and based on the target diffraction spectrum and the reference diffraction spectrum corresponding to the defect-free contact hole, the diffraction spectrum error value is obtained.

[0031] The image error value and the diffraction spectrum error value are input into the target model to obtain the correlation score;

[0032] If the correlation score is less than the score threshold, the multi-field coupling physical model is adjusted, and the electron trajectory simulation based on the target simulation rules and the initial three-dimensional structure model is performed to obtain the target electron beam imaging image. This process continues until the correlation score is greater than or equal to the score threshold, at which point the step of generating the target three-dimensional structure model based on the target electron beam imaging image is performed.

[0033] Secondly, this application also provides a contact hole defect detection device, the device comprising:

[0034] An initial three-dimensional structure model generation module is used to acquire a scanning electron image of the actual wafer contact hole region and, based on the scanning electron image, construct an initial three-dimensional structure model of the contact hole region.

[0035] The first imaging module is used to simulate the electron trajectory based on the initial three-dimensional structural model to obtain an initial electron beam imaging image.

[0036] A sensitive region determination module is used to determine the sensitive region based on the initial electron beam imaging image;

[0037] The second imaging module is used to determine the target simulation rules based on the sensitive area, and to perform electron trajectory simulation based on the target simulation rules and the initial three-dimensional structure model to obtain the target electron beam imaging image;

[0038] The defect detection module is used to generate a target three-dimensional structural model based on the target electron beam imaging image, and to perform contact hole defect detection based on the target three-dimensional structural model.

[0039] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method in any of the above embodiments.

[0040] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the methods in any of the above embodiments.

[0041] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the method in any of the above embodiments.

[0042] The aforementioned contact hole defect detection method, apparatus, equipment, medium, and program products acquire a scanning electron image of the actual wafer contact hole region and construct an initial three-dimensional structural model of the contact hole region based on the scanning electron image; perform electron trajectory simulation based on the initial three-dimensional structural model to obtain an initial electron beam imaging image; determine sensitive areas based on the initial electron beam imaging image; determine target simulation rules based on the sensitive areas, and perform electron trajectory simulation based on the target simulation rules and the initial three-dimensional structural model to obtain a target electron beam imaging image; generate a target three-dimensional structural model based on the target electron beam imaging image, and perform contact hole defect detection based on the target three-dimensional structural model. This method, by constructing an initial three-dimensional structural model based on a scanning electron image and determining sensitive areas based on the initial three-dimensional structural model, and then adjusting the corresponding simulation rules, generates a more accurate target electron beam imaging image. Consequently, the target three-dimensional structural model has higher accuracy, and contact hole defect detection can be performed based solely on the target three-dimensional structural model without wafer slicing. This avoids wafer damage, achieves contact hole defect detection, and is fully automated, thus improving detection efficiency. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is an application environment diagram of a contact hole defect detection method in one embodiment;

[0045] Figure 2 This is a flowchart illustrating a contact hole defect detection method in one embodiment;

[0046] Figure 3 This is a schematic diagram of the contour curve in one embodiment;

[0047] Figure 4 This is a schematic diagram of the grayscale curve in one embodiment;

[0048] Figure 5 This is a flowchart of the target electron beam imaging image generation step in one embodiment;

[0049] Figure 6 This is a structural block diagram of a contact hole defect detection device in one embodiment;

[0050] Figure 7 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0052] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0053] The contact hole defect detection method provided in this application embodiment can be applied to, for example... Figure 1 The application environment shown is as follows. A wafer is mounted on a machine, and a scanning electron microscope can be used to scan the wafer to obtain a scanned electronic image, which is then sent to a terminal.

[0054] The terminal can construct an initial three-dimensional structural model of the contact hole region based on the scanned electron image; perform electron trajectory simulation based on the initial three-dimensional structural model to obtain an initial electron beam imaging image; determine the sensitive area based on the initial electron beam imaging image; determine the target simulation rules based on the sensitive area, and perform electron trajectory simulation based on the target simulation rules and the initial three-dimensional structural model to obtain a target electron beam imaging image; generate a target three-dimensional structural model based on the target electron beam imaging image, and perform contact hole defect detection based on the target three-dimensional structural model. This eliminates the need to slice the wafer, thus avoiding wafer damage and enabling contact hole defect detection. The entire process is automated, improving detection efficiency.

[0055] In one exemplary embodiment, such as Figure 2 As shown, a method for detecting contact hole defects is provided, which can be applied to... Figure 1 Taking the terminal in the example, the explanation includes the following steps 202 to 210. Wherein:

[0056] S202: Obtain a scanning electron image of the actual wafer contact hole region, and construct an initial three-dimensional structural model of the contact hole region based on the scanning electron image.

[0057] The scanning electron image (SEE) is obtained by photographing the wafer on the equipment. Optionally, the wafer on the equipment is tilted by 15% and scanned using a scanning electron microscope to obtain the SEE image. The terminal can then construct a model of the contact hole area based on the SEE image to obtain an initial three-dimensional structural model. The SEE image can be a top view of the contact hole, which does not damage the wafer and allows the surface of the wafer to be seen.

[0058] In some optional embodiments, an initial three-dimensional structural model of the contact hole region is constructed based on the scanned electronic image, including: extracting the grayscale curve and contour curve of the scanned electronic image; and constructing the initial three-dimensional structural model of the contact hole region based on the grayscale curve and contour curve using a stereo matching algorithm or a three-dimensional reconstruction algorithm.

[0059] Among them, combined Figure 3 As shown, Figure 3 This is a schematic diagram of the contour curve in one embodiment. In this embodiment, the contour curve is a curve that represents the height, depth, and slope of the structure. For example, the contact hole can be drawn as a shape line when viewed in cross-section. The horizontal axis represents the position (from one side of the contact hole to the other), and the vertical axis represents the depth or height. The contour curve of a normal contact hole is: the middle is obviously concave (hole depth), the bottom is flat, clean, and the sidewalls are almost vertical. The contour curve of a contact hole with residue or incomplete etching is: the middle is not deep enough, and the bottom is convex and uneven. Therefore, the surface information of the contact hole can be obtained through the contour curve.

[0060] Among them, combined Figure 4 As shown, Figure 4 This is a schematic diagram of a grayscale curve in one embodiment. The grayscale curve plots the brightness of a scanned electronic image along a line. A straight line is drawn through the contact hole on the scanned electronic image, and the machine plots the brightness of each point along this line as a curve. In the chip, a clean, conductive hole bottom results in more reflected electrons, leading to higher brightness and a higher grayscale value; conversely, residual silicon oxide blocking the hole results in less reflection, leading to lower brightness, a darker appearance, and a lower grayscale value. Therefore, information about the interior of the contact hole can be obtained through this grayscale curve.

[0061] In this application, a stereo matching algorithm or a three-dimensional reconstruction algorithm can be used to simulate TEM, i.e., transmission electron microscope 3D imaging. For ease of description, this application refers to it as the initial three-dimensional structural model.

[0062] In some optional embodiments, the three-dimensional structure of the contact hole can be reconstructed in a computer using multiple scanned electronic images and stereo matching or three-dimensional reconstruction algorithms. This allows for the simulation of a three-dimensional internal morphology similar to that of a TEM without cutting the wafer or performing a real TEM, enabling non-destructive and rapid detection of hole bottom residue and cross-sectional shape. However, since the initial three-dimensional structure model is based on scanned electronic images, its accuracy depends entirely on the scanned electronic images. To improve accuracy, the initial three-dimensional structure model is modified, as detailed in steps S204 to S208.

[0063] S204: Electron trajectory simulation is performed based on the initial three-dimensional structural model to obtain the initial electron beam imaging image.

[0064] The initial electron beam imaging image is obtained based on electron trajectory simulation using an initial 3D structural model. This initial electron beam imaging image can be generated based on SE / BSE signals, where SE signal is the secondary electron signal and BSE signal is the backscattered electron signal. Both are electrons ejected after the electron beam hits the wafer. The generation process of SE (secondary electron) includes: the electron gun firing a high-energy electron beam ( When a high-energy electron beam hits the surface of silicon, silicon oxide, or a metal, it knocks out the weakly bound outer electrons from the atoms in the sample. These knocked-out low-energy electrons are called secondary electrons (SE). Similarly, when a high-energy electron beam hits the sample, the electrons are not absorbed or knocked out of their inner shells. Instead, they bounce off the atomic nucleus elastically and return along the same path with high energy. These returning electrons are called BSE backscattered electrons.

[0065] This application does not actually perform the above-mentioned process of hitting the wafer with an electron beam. Instead, it simulates the initial electron beam imaging image obtained by hitting the initial three-dimensional structure model in a computer based on the initial three-dimensional structure model, thus achieving higher efficiency.

[0066] Specifically, the initial electron beam imaging image is obtained through low-precision electron trajectory simulation based on an initial three-dimensional structural model. This initial electron beam imaging image is generated based on secondary electron signals and backscattered electron signals. The secondary electron signals are low-energy escape electron signals generated by the interaction between the high-energy electron beam and the weakly bound electrons in the outer shell of the sample atoms, while the backscattered electron signals are high-energy electron signals emitted in the opposite direction after elastic scattering of the high-energy electron beam with the atomic nuclei. The above simulation process does not involve performing electron beam bombardment on a real wafer, but rather performing numerical calculations of electron-material interactions in a computer based on the initial three-dimensional structural model, thus resulting in higher detection efficiency.

[0067] S206: Determine the sensitive region based on the initial electron beam imaging image.

[0068] The sensitive area is determined based on the reference electron beam imaging image corresponding to the defect-free contact hole. That is, the area where the initial electron beam imaging image differs from the reference electron beam imaging image is taken as the sensitive area, which means that contact hole defects may exist in these areas.

[0069] S208: Determine the target simulation rules based on the sensitive area, and perform electron trajectory simulation based on the target simulation rules and the initial three-dimensional structural model to obtain the target electron beam imaging image.

[0070] Target simulation rules are designed to improve the accuracy of sensitive area determination. For example, by increasing sampling in sensitive areas, the accuracy of the data in those areas can be improved. In other words, target simulation rules are adaptive non-uniform sampling rules, used to reduce computational load while maintaining accuracy. By re-simulating the electron trajectory based on these target simulation rules and the initial 3D structural model, a more accurate target electron beam imaging image can be obtained.

[0071] S210: Generate a three-dimensional structural model of the target based on the target electron beam imaging image, and perform contact hole defect detection based on the target three-dimensional structural model.

[0072] Based on the converged target electron beam imaging image, grayscale curve, and contour curve, a three-dimensional structural model of the target is generated through stereo matching or three-dimensional reconstruction algorithms. The target three-dimensional structural model is a high-precision virtual transmission electron microscope three-dimensional morphology. Based on the target three-dimensional structural model, it is possible to identify whether there is silicon oxide residue at the bottom of the contact hole, thereby completing the contact hole defect detection.

[0073] The grayscale curve and contour curve can be determined first based on the target electron beam imaging image, and then a three-dimensional structural model of the target can be generated through stereo matching or three-dimensional reconstruction algorithms. The generation of the target three-dimensional structural model can refer to the generation of the initial three-dimensional structural model mentioned above, and no specific limitations are made here.

[0074] The aforementioned contact hole defect detection method acquires a scanning electron microscope (SEM) image of the actual wafer contact hole region and constructs an initial three-dimensional structural model of the contact hole region based on the SEM image. Electron trajectory simulation is performed based on the initial three-dimensional structural model to obtain an initial electron beam imaging image. Sensitive regions are determined based on the initial electron beam imaging image. Target simulation rules are determined based on the sensitive regions, and electron trajectory simulation is performed based on the target simulation rules and the initial three-dimensional structural model to obtain a target electron beam imaging image. A target three-dimensional structural model is generated based on the target electron beam imaging image, and contact hole defect detection is performed based on the target three-dimensional structural model. This method constructs an initial three-dimensional structural model based on the SEM image, determines sensitive regions based on the initial three-dimensional structural model, and adjusts the corresponding simulation rules to generate a more accurate target electron beam imaging image. Consequently, the target three-dimensional structural model has higher accuracy, and contact hole defect detection can be performed based solely on the target three-dimensional structural model without wafer slicing. This avoids wafer damage, achieves contact hole defect detection, and the entire process is automated, improving detection efficiency.

[0075] In some optional embodiments, the method further includes: performing electron trajectory simulation based on an initial three-dimensional structural model to obtain an initial diffraction pattern; determining sensitive regions based on the initial electron beam imaging image, including: comparing the initial electron beam imaging image with a reference electron beam imaging image corresponding to a defect-free contact hole to obtain a first deviation value for each region, and designating regions with first deviation values ​​greater than a first deviation threshold as sensitive regions; or comparing the initial electron beam imaging image with a reference electron beam imaging image corresponding to a defect-free contact hole to obtain a first deviation value for each region; comparing the initial diffraction pattern with a reference diffraction pattern corresponding to a defect-free contact hole to obtain a peak position deviation value; and determining sensitive regions based on target positions with peak position deviation values ​​greater than a second deviation threshold and regions with first deviation values ​​greater than the first deviation threshold.

[0076] In this embodiment, the determination of the sensitive area can include two methods: the first is to locate the sensitive area based on the electron beam imaging image, and the second is to fuse the electron beam imaging image and the diffraction spectrum to jointly determine the sensitive area.

[0077] For the first method, the initial electron beam imaging image is compared region by region with the pre-constructed reference electron beam imaging image corresponding to the defect-free contact hole. The signal difference corresponding to each spatial location is calculated to obtain the first deviation value for each region. This first deviation value can be represented by mean square error, relative brightness difference, or contrast deviation. Regions with a first deviation value greater than a first deviation threshold are marked as sensitive regions. These regions typically exhibit abnormally high or low brightness.

[0078] In this embodiment, the first deviation threshold can be 5%, but in other embodiments, it can be other values.

[0079] It should be noted that before the region-by-region comparison, the initial electron beam imaging image and the reference electron beam imaging image can be divided into multiple regions according to a preset method. The sizes of the initial and reference electron beam imaging images are first normalized to the same size before region division to ensure comparability. This allows for the extraction of key features (grain boundaries, defects) from the initial image using image segmentation algorithms, facilitating subsequent focused sampling.

[0080] The second approach involves first comparing the initial electron beam imaging image with the reference electron beam imaging image corresponding to the defect-free contact hole to obtain the first deviation value for each region. Simultaneously, the initial diffraction pattern is matched with the reference diffraction pattern corresponding to the defect-free contact hole to calculate the peak position shift of each diffraction peak, yielding the peak position deviation value. The spatial locations corresponding to diffraction peaks with peak position deviation values ​​greater than a second deviation threshold are designated as diffraction-sensitive locations, and the regions with first deviation values ​​greater than the first deviation threshold are designated as imaging-sensitive regions. These two types of locations are spatially superimposed and fused, and their intersection or union is used to form the final sensitive region. Through dual-modal joint determination, the influence of non-structural factors such as scanning electron image noise, signal interference, and charge effects can be eliminated. Furthermore, by combining crystal integrity and surface morphology information, the sensitive region positioning becomes more accurate, providing a reliable constraint basis for subsequent adaptive sampling optimization and high-precision simulation.

[0081] In some optional embodiments, the second deviation threshold corresponding to the above peak deviation value can be 0.1°, and in other embodiments it can be other values, without specific limitations.

[0082] The second method described above aims to further improve the accuracy and reliability of sensitive area location and avoid misjudgments and missed detections caused by a single signal mode. During electron trajectory simulation, not only is an initial electron beam imaging image generated, but the corresponding initial diffraction spectrum is also output simultaneously, achieving joint analysis of dual-mode signals and precise marking of sensitive areas. Specifically, electron diffraction simulation is performed based on the initial three-dimensional structural model. Utilizing the Bragg diffraction effect of electrons in the crystal structure, an initial diffraction spectrum containing information on diffraction peak positions, intensities, and angles is obtained. Since the material composition at the bottom of the contact hole, crystal integrity, residual dielectric layer, and lattice distortion directly alter the position and intensity of the diffraction peaks, the initial diffraction spectrum can reflect crystal defects and residual dielectric information within the three-dimensional structural model, serving as an important supplementary basis for sensitive area determination.

[0083] In some optional embodiments, the target simulation rules are determined based on the sensitive regions, including: reducing the sampling interval and / or increasing the number of samples corresponding to the sensitive regions, and maintaining or expanding the sampling interval and / or reducing the number of samples corresponding to the non-sensitive regions, wherein the non-sensitive regions are the regions in the initial three-dimensional structural model other than the sensitive regions.

[0084] In this application, to improve computational efficiency while ensuring simulation accuracy and achieve a balance between high precision and high efficiency, the target simulation rules need to be adaptively determined based on the distribution characteristics of sensitive areas. The target simulation rules are a spatial sampling strategy for electronic trajectory simulation. The core idea is to use differentiated simulation accuracies for areas with different structural sensitivities, so that computational resources are concentrated on key areas where defects are prone to occur, signals change drastically, and the impact on imaging results is significant.

[0085] Specifically, this embodiment employs a high-density, fine-grained sampling method for sensitive areas, reducing the sampling interval for these areas. This results in a smaller grid size for the electron trajectory simulation, denser electron incident points, and more trajectory calculations. Furthermore, the number of sampling operations can be increased to enhance the trajectory calculations, or a combination of both methods can be used to improve the simulation accuracy of sensitive areas. Here, the grid size for electron trajectory simulation can be considered as the electron density; a smaller size indicates a higher electron density.

[0086] For non-sensitive areas, a low-density sparse sampling method is adopted to maintain or appropriately expand the sampling interval and / or reduce the number of samplings corresponding to non-sensitive areas. Non-sensitive areas are the areas in the initial three-dimensional structural model other than sensitive areas. These areas are usually flat in shape, have stable signals, and have a low defect incidence. Using sparse sampling can significantly reduce the amount of computation and shorten the simulation time.

[0087] In practical applications, an "atomic-level grid" (grid size = atomic spacing) is used for sensitive areas, increasing the number of samplings to 5000; while a coarse grid is maintained for non-sensitive areas, reducing the number of samplings to 500.

[0088] In this embodiment, by introducing target simulation rules, it is possible to achieve atomic-level precision electron trajectory simulation in sensitive areas and simplify the calculation process in non-sensitive areas, so that the overall simulation process achieves the optimal match between accuracy and efficiency, providing a stable and reliable sampling basis for subsequent multi-field coupling iterative calculations and high-precision electron beam imaging image reconstruction.

[0089] In some alternative embodiments, combined with Figure 5 As shown, Figure 5 This is a flowchart of the target electron beam imaging image generation steps in one embodiment. In this embodiment, electron trajectory simulation is performed based on target simulation rules and an initial three-dimensional structure model to obtain the target electron beam imaging image, including:

[0090] S502: A multi-field coupled physical model is established based on the electron transport equation, the heat conduction equation, and the elasticity equation. The electron transport equation is used to calculate the electron signal and motion trajectory corresponding to the electron beam imaging image. The heat conduction equation is used to determine the temperature distribution of the wafer based on the energy deposition of electrons. The elasticity equation is used to determine the lattice distortion in the wafer based on the temperature distribution, and to obtain the thermal stress field distribution based on the lattice distortion. The multi-field coupled physical model is used to determine the scattering cross section of the contact hole.

[0091] In order to improve the quality of the target electron beam imaging image, this application introduces a multi-field coupling physical model, which includes the electron transport equation, the heat conduction equation, and the elasticity equation.

[0092] When the electron beam acts on the contact hole region of the wafer, a large amount of energy is deposited. Based on the electron transport equation, the motion path, scattering behavior, and excitation law of secondary electrons and backscattered electrons of high-energy incident electrons can be fully simulated, and the output intensity and distribution characteristics of electron signals at different structural positions can be accurately quantified.

[0093] The energy generated by the interaction between electrons and materials diffuses in the form of heat. By using the heat conduction equation and combining the thermal physical properties of the wafer material itself, such as thermal conductivity and specific heat capacity, the instantaneous temperature distribution and heat diffusion range of the local area of ​​the contact hole can be calculated in real time.

[0094] Drastic local temperature changes trigger thermal expansion and contraction in materials. Using elasticity equations and mechanical parameters such as the material's elastic modulus and coefficient of thermal expansion, the torsional, tensile, and compressive deformation states of the crystal lattice are deduced from the temperature gradient. Then, based on the quantitative data of lattice distortion, the distribution of the thermal stress field generated inside the wafer is calculated in reverse. Furthermore, by integrating the combined effects of the temperature field, stress field, and lattice distortion, the electron scattering cross-section parameters of different materials and deformation regions are dynamically corrected. This provides dynamic and differentiated boundary conditions for subsequent electron trajectory simulations, ensuring that the simulation process closely reflects the actual interaction mechanism between the electron beam and the sample.

[0095] The components of the multi-field coupled physical model may include, firstly, determining initial input parameters, including conventional sample parameters (composition, crystal structure) and electron beam parameters, as well as the thermophysical properties (thermal conductivity, specific heat capacity) and mechanical properties (elastic modulus, coefficient of thermal expansion) of the input sample, providing basic data for multi-field coupling. Then, a coupled equation set of electron transport equation, heat conduction equation, and elasticity equation is established. The electron transport equation calculates the generation and trajectory of electron beams (SE / BSE), the heat conduction equation calculates the sample temperature distribution based on electron energy deposition, and the elasticity equation calculates lattice distortion based on the temperature distribution. These three equations interact in real time through a link of electron energy deposition rate, temperature change, lattice parameter correction, and scattering cross section adjustment. The temperature and stress field are updated iteratively every preset number of steps (e.g., 100, but other values ​​may apply in other embodiments).

[0096] In practical applications, the following formula can be used as a multi-field coupled physical model:

[0097]

[0098] Where ρ is the material density of the wafer, and c p Here, T represents the specific heat capacity at constant pressure, and t represents the temperature. The rate of change of temperature over time. Here, k(T,C) is the gradient operator, and k(T,C) is the thermal conductivity of the wafer material. This represents the temperature gradient, which is the rate of change of temperature in space. This is a thermal conductivity term used to describe the diffusion process of heat within a material; This is a heat source term, referring to the heat generated by the electron beam energy deposited within the wafer, and is the direct source of temperature increase. It is a position vector, that is, the spatial position of a point within the wafer, used to describe the distribution of heat sources at different locations of contact holes.

[0099] S504: Based on the target simulation rules, the electron trajectory is simulated on the initial three-dimensional structural model to obtain the current electron beam signal.

[0100] After completing the construction of the multi-field coupled physical model, the first round of electron trajectory simulation calculations was carried out under the constraints of the target simulation rules mentioned above. The target simulation rules implemented differentiated sampling configurations based on sensitive and non-sensitive regions. Sensitive regions used small sampling intervals, high-density grids, and high sampling times, while non-sensitive regions used large sampling intervals, sparse grids, and conventional sampling times. Using the initial three-dimensional structural model as the simulation carrier, and following the aforementioned target simulation rules, the collision, reflection, penetration, and energy loss processes of massive incident electrons were simulated in batches. The number of electrons produced and the signal intensity at different spatial locations were statistically analyzed, and the complete current electron beam signal was generated. This first round of simulation is a basic coarse-precision calculation, capable of quickly outputting raw signal data, providing basic comparative data and optimization benchmarks for subsequent multi-field parameter iterative corrections. Each round of simulation typically involves 1000 electron trajectory simulations. In other embodiments, the number of electron trajectory simulations per round can also be other values, which are not specifically limited here.

[0101] S506: Based on the multi-field coupled physical model, the scattering cross section, temperature distribution and thermal stress field distribution are iteratively corrected, and the initial three-dimensional structural model is iteratively optimized based on the scattering cross section, temperature distribution and thermal stress field distribution.

[0102] In this application, the dynamic changes of multiple physics fields caused by the continuous action of electrons are introduced into the subsequent rounds of electron trajectory simulation through a multi-field coupled physical model. Specifically, based on the results of the first round of electron energy deposition, the dynamic changes of the local temperature field are recalculated, and the degree of lattice distortion and the value of thermal stress field caused by temperature changes are updated simultaneously. According to the regional differences in lattice deformation, stress concentration, and temperature differences, the electron scattering cross-section parameters of each region are specifically corrected to eliminate the calculation errors caused by fixed scattering parameters. At the same time, combined with the updated scattering characteristics, thermal and mechanical distribution parameters, the initial three-dimensional structural model is corrected at the microscale, optimizing the microscopic features such as hole wall morphology, hole bottom structure, and material interface state. This corrects the morphological deviations caused by the initial three-dimensional structural model relying solely on scanning electron image reconstruction, making the structural model more consistent with the microscopic physical state of contact holes under actual processes.

[0103] S508: Based on the optimized initial three-dimensional structural model and target simulation rules, the electron trajectory is re-simulated to obtain the current electron beam signal.

[0104] After completing the micro-optimization of the three-dimensional structural model and the correction of multiple physical parameters, the target simulation rules remain unchanged, and the differentiated spatial sampling strategy is used to carry out electronic trajectory simulation calculations again on the optimized initial three-dimensional structural model.

[0105] Subsequent simulations employ updated dynamic parameters such as the scattering cross-section, temperature field, and stress field, combined with corrected microstructural morphology, to realistically recreate the propagation and excitation patterns of the electron beam on the distorted lattice, stress region, and residual dielectric layer surface. Through secondary simulation calculations, the current electron beam signal is updated and compared with the initial signal data, accurately reflecting the impact of structural deformation, thermal stress, and changes in scattering characteristics on the electron signal. This continuously reduces the deviation between the simulated signal and the actual scanned electron signal, improving the realism of the imaging simulation.

[0106] S510: If the iterative convergence condition is met, generate a target electron beam imaging image based on the current electron beam signal obtained from the final iteration.

[0107] The convergence condition can be that the number of iterations has reached a preset number, or it can be determined by combining image deviation, diffraction spectrum deviation, and stability of multi-field parameters. When all indicators tend to stabilize and the error is controlled within a reasonable threshold range, the iteration process is terminated.

[0108] The final iterative calculation outputs the target electron beam imaging image, providing accurate imaging data support for subsequent 3D structure reconstruction and contact hole defect detection.

[0109] In the above embodiments, a multi-field coupled physical model is introduced to ensure accuracy.

[0110] In some optional embodiments, before generating the target three-dimensional structure model based on the target electron beam imaging image, the method further includes: performing electron trajectory simulation based on the target simulation rules and the initial three-dimensional structure model to obtain the target diffraction spectrum; obtaining an image error value based on the target electron beam imaging image and the reference electron beam imaging image corresponding to the defect-free contact hole; obtaining a diffraction spectrum error value based on the target diffraction spectrum and the reference diffraction spectrum corresponding to the defect-free contact hole; inputting the image error value and the diffraction spectrum error value into the target model to obtain a correlation score; if the correlation score is less than the score threshold, adjusting the multi-field coupling physical model and continuing to perform the step of performing electron trajectory simulation based on the target simulation rules and the initial three-dimensional structure model to obtain the target electron beam imaging image, until the correlation score is greater than or equal to the score threshold, and then continuing to perform the step of generating the target three-dimensional structure model based on the target electron beam imaging image.

[0111] In this application, to ensure the accuracy of both the surface morphology and internal crystal state of the final reconstructed target 3D structural model, the reliability of the target electron beam imaging image is determined before generating the target 3D structural model based on the target electron beam imaging image. This determination is made jointly using the target electron beam imaging image and the target diffraction spectrum.

[0112] Simultaneously with the aforementioned electron beam imaging of the target, the corresponding target diffraction spectrum is also output. The target diffraction spectrum contains key information such as diffraction peak position, peak intensity, and peak width, which can reflect the crystal integrity, lattice distortion, and material composition state inside the contact hole, and is an important basis for judging internal defects.

[0113] In this embodiment, the target electron beam imaging image is compared pixel by pixel with the reference electron beam imaging image corresponding to the defect-free contact hole. The image error value is obtained by means of mean square error, peak signal-to-noise ratio or structural similarity, which is used to characterize the deviation between the simulated morphology and the real morphology. At the same time, the target diffraction spectrum is matched with the reference diffraction spectrum corresponding to the defect-free contact hole, and the diffraction peak position deviation, intensity deviation and peak width deviation are calculated to obtain the diffraction spectrum error value, which is used to characterize the difference between the simulated crystal state and the ideal state.

[0114] The image error value and the diffraction spectrum error value are input into the trained target association model. Based on preset weights and judgment logic, the model outputs an association score that comprehensively reflects the consistency between the morphology and the crystal state. If the association score is less than the preset scoring threshold, it indicates that the current simulation result deviates significantly from the actual state. It is necessary to backtrack and adjust the key parameters in the multi-field coupled physical model, such as the thermal expansion coefficient, scattering cross-section correction factor, or temperature-stress-field coupling coefficient. The electron trajectory simulation, error calculation, and scoring judgment process should be repeated until the association score is greater than or equal to the scoring threshold, at which point the simulation result is considered converged. At this point, both the target electron beam imaging image and the target diffraction spectrum meet the preset accuracy requirements, and the subsequent steps of generating the target three-dimensional structure model based on the target electron beam imaging image can continue.

[0115] The target association model can be a trained random forest model. The input image error value and diffraction spectrum error are used to predict the association score between the two (0-100 points). When the score is > 90 points and the single-mode error meets the threshold, convergence is determined. Otherwise, the process is backtracked to the multi-field coupling equation solution step, i.e., step S502 above, and the thermal expansion coefficient or scattering cross section correction factor is adjusted until the convergence condition is met.

[0116] In the above embodiments, the collaborative constraint of dual-mode error effectively avoids misjudgment caused by a single signal mode, improves the reliability of simulation results, and provides a solid data foundation for subsequent high-precision three-dimensional structure reconstruction.

[0117] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0118] Based on the same inventive concept, this application also provides a contact hole defect detection device for implementing the contact hole defect detection method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more contact hole defect detection device embodiments provided below can be found in the limitations of the contact hole defect detection method described above, and will not be repeated here.

[0119] In one exemplary embodiment, such as Figure 6 As shown, a contact hole defect detection device is provided, comprising: an initial three-dimensional structural model generation module 601, a first imaging module 602, a sensitive area determination module 603, a second imaging module 604, and a defect detection module 605, wherein:

[0120] The initial three-dimensional structure model generation module 601 is used to acquire a scanning electron image of the actual wafer contact hole region and construct an initial three-dimensional structure model of the contact hole region based on the scanning electron image.

[0121] The first imaging module 602 is used to simulate the electron trajectory based on the initial three-dimensional structural model to obtain an initial electron beam imaging image.

[0122] Sensitive region determination module 603 is used to determine the sensitive region based on the initial electron beam imaging image;

[0123] The second imaging module 604 is used to determine the target simulation rules based on the sensitive area, and to perform electron trajectory simulation based on the target simulation rules and the initial three-dimensional structure model to obtain the target electron beam imaging image;

[0124] The defect detection module 605 is used to generate a target three-dimensional structural model based on the target electron beam imaging image, and to perform contact hole defect detection based on the target three-dimensional structural model.

[0125] In one optional embodiment, the aforementioned initial three-dimensional structural model generation module 601 is specifically used to extract the grayscale curve and contour curve of the scanned electronic image; based on the grayscale curve and contour curve, an initial three-dimensional structural model of the contact hole region is constructed using a stereo matching algorithm or a three-dimensional reconstruction algorithm.

[0126] In one optional embodiment, the first imaging module 602 is further configured to perform electron trajectory simulation based on the initial three-dimensional structural model to obtain an initial diffraction spectrum;

[0127] The aforementioned sensitive region determination module 603 is specifically used for: comparing the initial electron beam imaging image with the reference electron beam imaging image corresponding to the defect-free contact hole to obtain a first deviation value for each region, and taking the region with the first deviation value greater than the first deviation threshold as a sensitive region; or comparing the initial electron beam imaging image with the reference electron beam imaging image corresponding to the defect-free contact hole to obtain a first deviation value for each region; comparing the initial diffraction pattern with the reference diffraction pattern corresponding to the defect-free contact hole to obtain a peak position deviation value; and determining the sensitive region based on the target position with the peak position deviation value greater than the second deviation threshold and the region with the first deviation value greater than the first deviation threshold.

[0128] In one optional embodiment, the second imaging module 604 is specifically used to reduce the sampling interval and / or increase the number of samplings corresponding to the sensitive region, and to maintain or expand the sampling interval and / or reduce the number of samplings corresponding to the non-sensitive region, wherein the non-sensitive region is the region other than the sensitive region in the initial three-dimensional structural model.

[0129] In one optional embodiment, the second imaging module 604 is specifically used to establish a multi-field coupled physical model based on the electron transport equation, the heat conduction equation, and the elasticity equation. The electron transport equation is used to calculate the electron signal and motion trajectory corresponding to the electron beam imaging image. The heat conduction equation is used to determine the temperature distribution of the wafer based on the energy deposition of electrons. The elasticity equation is used to determine the lattice distortion in the wafer based on the temperature distribution and to obtain the thermal stress field distribution based on the lattice distortion. The multi-field coupled physical model is used to determine the scattering cross section of the contact hole. Based on the target simulation rules, the electron trajectory is simulated on the initial three-dimensional structure model to obtain the current electron beam signal. The scattering cross section, temperature distribution, and thermal stress field distribution are iteratively corrected based on the multi-field coupled physical model. The initial three-dimensional structure model is iteratively optimized based on the scattering cross section, temperature distribution, and thermal stress field distribution. The electron trajectory is re-simulated based on the optimized initial three-dimensional structure model and the target simulation rules to obtain the current electron beam signal. If the iterative convergence condition is met, the target electron beam imaging image is generated based on the current electron beam signal obtained by the final iteration.

[0130] In one optional embodiment, the above apparatus further includes: a verification module, configured to perform electron trajectory simulation based on target simulation rules and an initial three-dimensional structural model to obtain a target diffraction spectrum; obtain an image error value based on a target electron beam imaging image and a reference electron beam imaging image corresponding to a defect-free contact hole; obtain a diffraction spectrum error value based on the target diffraction spectrum and the reference diffraction spectrum corresponding to a defect-free contact hole; input the image error value and the diffraction spectrum error value into the target model to obtain a correlation score; if the correlation score is less than a score threshold, adjust the multi-field coupling physical model and continue to perform the step of performing electron trajectory simulation based on target simulation rules and an initial three-dimensional structural model to obtain a target electron beam imaging image, until the correlation score is greater than or equal to the score threshold, and then continue to perform the step of generating a target three-dimensional structural model based on the target electron beam imaging image.

[0131] Each module in the aforementioned contact hole defect detection device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0132] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 7As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a method for detecting contact hole defects. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0133] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0134] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0135] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0136] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0137] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0138] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0139] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for detecting contact hole defects, characterized in that, The method includes: A scanning electron image of the actual wafer contact hole region is obtained, and an initial three-dimensional structural model of the contact hole region is constructed based on the scanning electron image. Based on the initial three-dimensional structural model, electron trajectory simulation is performed to obtain an initial electron beam imaging image; Based on the initial electron beam imaging image, the sensitive region is determined; Based on the sensitive region, target simulation rules are determined, and electron trajectory simulation is performed based on the target simulation rules and the initial three-dimensional structure model to obtain the target electron beam imaging image; A three-dimensional structural model of the target is generated based on the target electron beam imaging image, and contact hole defects are detected based on the target three-dimensional structural model.

2. The method according to claim 1, characterized in that, The process of constructing an initial three-dimensional structural model of the contact hole region based on the scanned electronic image includes: Extract the grayscale curve and contour curve of the scanned electronic image; Based on the grayscale curve and contour curve, an initial three-dimensional structural model of the contact hole region is constructed using a stereo matching algorithm or a three-dimensional reconstruction algorithm.

3. The method according to claim 1, characterized in that, The method further includes: Based on the initial three-dimensional structural model, electron trajectory simulation was performed to obtain the initial diffraction pattern; The process of determining the sensitive region based on the initial electron beam imaging image includes: The initial electron beam imaging image is compared with the reference electron beam imaging image corresponding to the defect-free contact hole to obtain the first deviation value for each region, and the region with the first deviation value greater than the first deviation threshold is designated as the sensitive region; or The initial electron beam imaging image is compared with the reference electron beam imaging image corresponding to the defect-free contact hole to obtain the first deviation value corresponding to each region; the initial diffraction pattern is compared with the reference diffraction pattern corresponding to the defect-free contact hole to obtain the peak position deviation value; based on the target position where the peak position deviation value is greater than the second deviation threshold and the region where the first deviation value is greater than the first deviation threshold, the sensitive region is determined.

4. The method according to claim 1, characterized in that, The determination of target simulation rules based on the sensitive region includes: Reduce the sampling interval and / or increase the number of samples corresponding to the sensitive region, and maintain or expand the sampling interval and / or reduce the number of samples corresponding to the non-sensitive region, wherein the non-sensitive region is the region in the initial three-dimensional structural model other than the sensitive region.

5. The method according to any one of claims 1 to 4, characterized in that, The process of simulating the electron trajectory based on the target simulation rules and the initial three-dimensional structural model to obtain a target electron beam imaging image includes: A multi-field coupled physical model is established based on the electron transport equation, the heat conduction equation, and the elasticity equation. The electron transport equation is used to calculate the electron signal and motion trajectory corresponding to the electron beam imaging image. The heat conduction equation is used to determine the temperature distribution of the wafer based on the energy deposition of the electrons. The elasticity equation is used to determine the lattice distortion in the wafer based on the temperature distribution and to obtain the thermal stress field distribution based on the lattice distortion. The multi-field coupled physical model is used to determine the scattering cross section of the contact hole. Based on the target simulation rules, the electron trajectory of the initial three-dimensional structure model is simulated to obtain the current electron beam signal; The scattering cross section, temperature distribution, and thermal stress field distribution are iteratively corrected based on the multi-field coupled physical model, and the initial three-dimensional structural model is iteratively optimized based on the scattering cross section, temperature distribution, and thermal stress field distribution. Based on the optimized initial three-dimensional structural model and the target simulation rules, the electron trajectory is re-simulated to obtain the current electron beam signal; If the iterative convergence condition is met, the target electron beam imaging image is generated based on the current electron beam signal obtained in the final iteration.

6. The method according to claim 5, characterized in that, Before generating the target three-dimensional structure model based on the target electron beam imaging image, the method further includes: Based on the target simulation rules and the initial three-dimensional structural model, electron trajectory simulation is performed to obtain the target diffraction spectrum; Based on the target electron beam imaging image and the reference electron beam imaging image corresponding to the defect-free contact hole, the image error value is obtained; and based on the target diffraction spectrum and the reference diffraction spectrum corresponding to the defect-free contact hole, the diffraction spectrum error value is obtained. The image error value and the diffraction spectrum error value are input into the target model to obtain the correlation score; If the correlation score is less than the score threshold, the multi-field coupling physical model is adjusted, and the electron trajectory simulation based on the target simulation rules and the initial three-dimensional structure model is performed to obtain the target electron beam imaging image. This process continues until the correlation score is greater than or equal to the score threshold, at which point the step of generating the target three-dimensional structure model based on the target electron beam imaging image is performed.

7. A contact hole defect detection device, characterized in that, The device includes: An initial three-dimensional structure model generation module is used to acquire a scanning electron image of the actual wafer contact hole region and, based on the scanning electron image, construct an initial three-dimensional structure model of the contact hole region. The first imaging module is used to simulate the electron trajectory based on the initial three-dimensional structural model to obtain an initial electron beam imaging image. A sensitive region determination module is used to determine the sensitive region based on the initial electron beam imaging image; The second imaging module is used to determine the target simulation rules based on the sensitive area, and to perform electron trajectory simulation based on the target simulation rules and the initial three-dimensional structure model to obtain the target electron beam imaging image; The defect detection module is used to generate a target three-dimensional structural model based on the target electron beam imaging image, and to perform contact hole defect detection based on the target three-dimensional structural model.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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