Method, system and apparatus for measuring residual silicon thickness, and storage medium

Abstract

Provided in the present application are a method, system and apparatus for measuring residual silicon thickness, and a storage medium. The method comprises: changing the distance between an objective lens and a sample to acquire a sampled image set; performing sharpness evaluation on the sampled image set, and, on the basis of a sharpness evaluation value data set, performing screening by using a preset condition to obtain corresponding clear images; and finally, performing computing according to the clear images, objective lens positions corresponding to the clear images, and a preset algorithm, thereby rapidly obtaining a high-precision residual silicon thickness measurement result. In addition, by means of a self-made rough-surface silicon wafer and objective lens positions corresponding to imaging thereof, an objective lens position corresponding to the surface of a smooth-surface wafer can be measured, thereby achieving real-time measurement of the residual silicon thickness of the smooth-surface wafer, and further improving the accuracy of residual silicon thickness measurement for wafers.

Description

A method, system, apparatus, and storage medium for measuring residual silicon thickness. Technical Field

[0001] This application relates to measurement technology, and more particularly to a method, system, apparatus, and storage medium for measuring residual silicon thickness. Background Technology

[0002] Through-Silicon Via (TSV) technology originated from the need for miniaturization and high integration of semiconductor devices. As Moore's Law advanced, traditional two-dimensional packaging technologies could no longer meet the ever-increasing demands for integration, thus TSV technology emerged. TSV technology achieves three-dimensional interconnection between chips by creating vertical vias inside the chip, thereby significantly improving the integration and packaging efficiency of electronic components.

[0003] In practical applications of TSV technology, wafer backside thinning is a crucial process step. Thinning the wafer backside reduces package mounting height, chip package size, and improves thermal diffusion efficiency and electrical performance. During wafer backside thinning, precise measurement of the residual silicon thickness (RST) is essential to ensure the thinned wafer meets design requirements and quality standards. However, common methods for measuring RST have drawbacks: for example, laser confocal microscopy is limited by the wafer structure, leading to a significant decrease in measurement accuracy; X-ray microscopy requires a demanding operating environment and is easily affected, resulting in low measurement efficiency; acoustic measurements also have high operating environment requirements and low efficiency. In summary, existing RST measurement techniques all suffer from low measurement accuracy and low efficiency. Summary of the Invention

[0004] In view of this, in order to solve one of the above problems, the purpose of the embodiments of this application is to provide a method, system, device and storage medium for measuring residual silicon thickness, which can effectively improve the measurement accuracy and measurement efficiency in the measurement technology of residual silicon thickness.

[0005] On the one hand, this application provides a method for measuring the remaining silicon thickness, the method comprising the following steps:

[0006] The distance between the objective lens and the sample is changed to obtain a set of sampled images; the set of sampled images is formed by light passing sequentially through the objective lens and a rough-surface silicon wafer and converging onto the sample, and then being reflected by the sample and passing sequentially through the rough-surface silicon wafer, the objective lens, and an imaging lens; the sample includes a smooth-surface wafer with several cylindrical holes;

[0007] Determine a number of clear images in the sampled image set that meet preset clarity conditions, and the objective lens positions corresponding to the number of clear images;

[0008] Based on the several clear images, the objective lens positions corresponding to the several clear images, and a preset algorithm, the remaining silicon thickness of the sample is calculated.

[0009] Further, determining a plurality of sharp images in the sampled image set that meet preset sharpness conditions and the objective lens positions corresponding to the plurality of sharp images includes:

[0010] Based on the sampled image set and the sharpness evaluation function, obtain a sharpness evaluation value dataset;

[0011] Based on the aforementioned sharpness evaluation value dataset and preset conditions, several sharp images that meet the preset conditions are obtained; the several sharp images that meet the preset conditions include a sharp image of the bottom of the cylindrical hole of the smooth surface wafer, a sharp image of the actual rough surface silicon wafer, and a sharp image of the virtual image reflected by the rough surface silicon wafer.

[0012] Based on several clear images, the corresponding objective lens position is obtained.

[0013] Further, the step of obtaining several clear images whose clarity meets the preset conditions based on the clarity evaluation value dataset and preset conditions includes:

[0014] Based on the aforementioned sharpness evaluation value dataset, several sharpness evaluation maxima are obtained;

[0015] Based on several sharpness evaluation maxima, several sharp images are obtained.

[0016] Further, the step of calculating the remaining silicon thickness of the sample based on the plurality of clear images, the objective lens positions corresponding to the plurality of clear images, and a preset algorithm includes:

[0017] Obtain the thickness value of the silicon wafer with the rough surface;

[0018] Based on the objective lens position corresponding to the clear image of the bottom of the cylindrical hole of the smooth surface wafer, the objective lens position corresponding to the clear image of the actual rough surface silicon wafer, the objective lens position corresponding to the clear image of the virtual image reflected by the rough surface silicon wafer, the thickness value, and the preset algorithm, the remaining silicon thickness of the sample is calculated.

[0019] Furthermore, the preset algorithm includes: Hrst = (h2 + h1 - d) / 2 - ht

[0020] Wherein, Hrst is the remaining silicon thickness of the sample, h1 is the objective lens position corresponding to the clear image of the actual rough surface silicon wafer, h2 is the objective lens position corresponding to the clear image of the virtual image reflected by the rough surface silicon wafer, d is the thickness value, and ht is the objective lens position corresponding to the clear image of the bottom of the cylindrical hole of the smooth surface wafer.

[0021] On the other hand, this application also provides a system for measuring the remaining silicon thickness, the system comprising a camera, a mirror cavity, a light source, a rough-surface silicon wafer, a leveling device, a platform, a column, a movable guide rail, and a processor; wherein,

[0022] The platform is used to fix the column and the leveling device;

[0023] The leveling device is used to load the sample;

[0024] The column is used to fix the movable guide rail;

[0025] The movable guide rail is used to fix the mirror cavity;

[0026] The mirror cavity includes: an aperture stop, a collimating lens unit, a beam splitter, an objective lens, and an imaging lens;

[0027] The processor is used to implement the measurement method as described above;

[0028] The light emitted by the light source passes sequentially through the aperture stop, the first collimating lens, the second collimating lens, and the beam splitter. After being deflected by the beam splitter, the light passes sequentially through the objective lens, the rough-surface silicon wafer, and the sample. After being reflected by the sample, the light passes sequentially through the rough-surface silicon wafer, the objective lens, the beam splitter, and the imaging lens before finally entering the camera.

[0029] Furthermore, the light source includes a wide bandwidth light source; the wide bandwidth light source includes components that are permeable to silicon and components that are not permeable to silicon.

[0030] Furthermore, the rough-surface silicon wafer includes a grid, the grid shape of which includes stripes, squares, and circles.

[0031] On the other hand, this application also provides a measuring device for residual silicon thickness, comprising:

[0032] At least one processor;

[0033] At least one memory for storing at least one program;

[0034] When the at least one program is executed by the at least one processor, the at least one processor implements the above-described testing method.

[0035] On the other hand, this application also provides a computer-readable storage medium storing a processor-executable program, characterized in that the processor-executable program, when executed by a processor, is used to perform the above-described measurement method.

[0036] In summary, the beneficial effects that the embodiments of this application can achieve include:

[0037] This application provides a method, system, apparatus, and storage medium for measuring residual silicon thickness. By changing the distance between the objective lens and the sample, a set of sampled images is acquired. The sharpness of the sampled images is evaluated, and based on the sharpness evaluation dataset, corresponding sharp images are obtained through filtering using preset conditions. Finally, based on the sharp images, the corresponding objective lens positions, and a preset algorithm, a high-precision measurement result of the residual silicon thickness can be quickly obtained. Simultaneously, by utilizing a self-made rough-surface silicon wafer and the objective lens position corresponding to its imaging, the objective lens position corresponding to the smooth-surface wafer surface can be measured, enabling the measurement of the residual silicon thickness of the smooth-surface wafer, further improving the accuracy of residual silicon thickness measurement. Therefore, the residual silicon thickness measurement system provided in this application can effectively improve the measurement accuracy and efficiency in residual silicon thickness measurement technology. Attached Figure Description

[0038] Figure 1 is a flowchart illustrating the steps of a method for measuring residual silicon thickness provided in an embodiment of this application;

[0039] Figure 2 is a structural block diagram of a residual silicon thickness measurement system provided in an embodiment of this application;

[0040] Figure 3 is a flowchart illustrating the steps of another method for measuring residual silicon thickness provided in an embodiment of this application;

[0041] Figure 4 is a schematic diagram of the position of a virtual image on a rough surface silicon wafer in the measurement method provided in the embodiment of this application;

[0042] Figure 5 is a schematic diagram of another case of virtual image position on a rough surface silicon wafer in the measurement method provided in the embodiments of this application;

[0043] Figure 6 is a schematic diagram of another case of virtual image position on a rough surface silicon wafer in the measurement method provided in the embodiments of this application;

[0044] Figure 7 is a structural block diagram of a storage medium provided in an embodiment of this application;

[0045] Labels: 1-Wide bandwidth light source, 2-Aperture stop, 3-First collimating lens, 4-Second collimating lens, 5-Camera, 6-Imaging lens, 7-Beam splitter, 8-Objective lens, 9-Rough surface silicon wafer, 10-Sample, 11-Leveling device, 12-Platform, 13-Movable guide rail, 14-Column, 15-Mirror cavity, 21-Rough surface silicon wafer (actual), 22-Reflected virtual image of rough surface silicon wafer, d-Thickness of rough surface silicon wafer, h1-Objective position corresponding to the image of the self-made silicon wafer, h2-Objective position corresponding to the clear image of the reflected virtual image of the rough surface silicon wafer, h3-Objective position corresponding to the smooth surface of the sample wafer, htx-Objective position corresponding to the bottom of the cylindrical aperture (x=1, 2, 3……). Detailed Implementation

[0046] The present application will now be described in further detail with reference to the accompanying drawings and specific embodiments. The step numbers in the following embodiments are only for ease of explanation and do not limit the order of the steps. The execution order of each step in the embodiments can be adapted according to the understanding of those skilled in the art.

[0047] The relevant technologies involved in this application are described below:

[0048] Laser confocal microscopy measurement: Laser confocal microscopy measures the inner wall and remaining silicon thickness of a TSV by detecting reflected light signals, providing high-resolution depth information. It offers the advantage of non-contact measurement and is suitable for online monitoring during wafer fabrication. This method typically measures from the front to capture TSV surface features. However, as the aspect ratio of the TSV increases, the light reflection signal attenuates significantly, and scattering effects intensify when the TSV aperture is small, leading to a significant decrease in measurement accuracy.

[0049] X-ray microscopy measurement: X-ray microscopy obtains precise depth information in high aspect ratio TSVs by penetrating the TSV structure with X-rays. This method can measure from both the front and back sides, has high spatial resolution, and can image the inner and outer walls of the TSV. However, X-ray microscopy equipment is expensive and complex to operate, making it unsuitable for large-scale inspection on production lines, and it also requires highly skilled operators.

[0050] Acoustic Measurement: Acoustic measurement utilizes the propagation characteristics of ultrasonic waves in silicon materials to measure the TSV depth and remaining silicon thickness by analyzing reflected signals. Ultrasonic waves can penetrate materials and obtain information about their internal structure; however, in high aspect ratio TSVs, signal attenuation and multiple reflections affect the accuracy and reliability of the measurement. Acoustic measurement can be performed from both the front and back sides, but its complex equipment and environmental requirements limit its application in large-scale production.

[0051] Electrical Measurement: Electrical measurement methods deduce the remaining silicon thickness by applying an electrical signal to the TSV and measuring its resistance, capacitance, and other characteristics. This method is usually performed from the front. Although it has some practicality, its measurement accuracy depends on the material properties of the TSV and it is difficult to guarantee high accuracy in all scenarios, especially for TSV structures with large variations in material properties.

[0052] The following is an explanation of several terms used in this application:

[0053] Through-Silicon Via (TSV) technology is a revolutionary semiconductor packaging and interconnection solution. It enables high-speed, low-loss electrical connections between chips or between different layers within a chip by directly creating vertical conductive channels inside the chip, significantly improving data transmission rates and system performance. TSV technology is widely used in high-performance computing, 3D integrated circuits, and high-capacity memory stacking, and is an indispensable technology in the modern electronics industry.

[0054] Remaining Silicon Thickness (RST) refers to the thickness of the remaining silicon layer on a silicon wafer after a series of etching, grinding, or polishing steps in semiconductor manufacturing. This parameter is crucial to device performance and reliability, affecting circuit conductivity, thermal conductivity, and mechanical strength. Precisely controlling the remaining silicon thickness can optimize the electrical and thermal characteristics of devices, improve the integration density and operating frequency of integrated circuits, and is an indispensable part of semiconductor manufacturing.

[0055] Aspect ratio: This refers to the ratio between the depth of the etched or processed silicon structure and its lateral dimensions (such as diameter or width). This parameter is crucial for evaluating the processing accuracy, structural stability, and performance characteristics of silicon wafers. By measuring the aspect ratio, a more comprehensive understanding of the distribution of remaining silicon thickness can be obtained, providing important information for subsequent process control and optimization.

[0056] Scattering effect: In residual silicon thickness measurement, this refers to the scattering of light rays when a beam of light (such as a laser) strikes the surface of a silicon wafer. The direction and intensity distribution of these scattered rays are closely related to parameters such as the surface morphology, roughness, and residual silicon thickness of the silicon wafer. By analyzing the characteristics of the scattered rays, information about the residual silicon thickness can be indirectly deduced, providing important basis for silicon wafer processing and quality control.

[0057] Sharpness evaluation function: In the measurement of remaining silicon thickness, the sharpness of an image or video is determined by comprehensively evaluating factors such as edge sharpness, resolution, contrast, and noise. This indirectly reflects the thickness information of the silicon wafer and provides an important reference for high-precision silicon wafer thickness measurement. The following is a sharpness evaluation function that can be used in a method for measuring remaining silicon thickness provided in this application, where x and y represent the coordinates of pixels in the image:

[0058] Image sharpness evaluation function: This function determines the gradient magnitude of each pixel by calculating the sum of the squared grayscale differences between adjacent pixels along the x and y axes. The final image sharpness evaluation result is obtained by summing the gradient values ​​of all pixels.

[0059] Roberts operator: It calculates the grayscale difference between adjacent pixels on the diagonal. The sum of the squares of the interleaved subtractions of the grayscale values ​​of four neighboring pixels is used as the gradient value of each pixel. The gradient values ​​of all pixels are summed to form the value of the sharpness evaluation function.

[0060] The Tenengrad function uses the Sobel operator to obtain the gradient values ​​of a pixel in the horizontal and vertical directions. This function is defined as the sum of the squares of the pixel gradient values, and the sensitivity of the function can be adjusted by setting a threshold T.

[0061] Where G(x,y) is the gradient at pixel (x,y).

[0062] in and These are the gradient values ​​of the pixel in the horizontal and vertical directions.

[0063] in g is the convolution symbol. x g y These are the horizontal and vertical templates for the Sobel operator.

[0064] The gradient filter method, also known as the Brenner function, only requires difference operations on points two pixels apart on the x-axis, which is to calculate the second gradient, thereby reducing the amount of computation.

[0065] The variance function shows the dispersion of gray-level distribution in an image. When an image is out of focus, the range of gray-level values ​​is small, the dispersion is low, and therefore the variance is also small; while when an image is in focus, the range of gray-level values ​​is large, the dispersion is high, and therefore the variance is large.

[0066] Where μ is the average gray value of the image.

[0067] Information entropy sharpness evaluation method: In information theory, entropy is an indicator of information richness. Using the information entropy evaluation function, the diversity of grayscale distribution in a focused image can be analyzed. When the grayscale values ​​of pixels are widely distributed and significantly different from each other, the entropy value is correspondingly high; conversely, for out-of-focus images, the situation is exactly the opposite.

[0068] Where b is generally taken as 2, g represents the image gray value, G represents the maximum value of the image gray value, k represents the defocused image sequence, and P(g) represents the probability of gray value g appearing in the k-th image.

[0069] Where MN represents the total number of pixels, and n represents the number of pixels with a gray value of g in the k-th image.

[0070] As shown in Figure 1, this application embodiment provides a method for measuring the remaining silicon thickness, which includes the following steps:

[0071] S100: Change the distance between the objective lens and the sample to acquire a set of sampled images.

[0072] Optionally, the sampled image is formed by light passing sequentially through an objective lens and a rough-surface silicon wafer and converging onto the sample, then being reflected by the sample and sequentially passing through the rough-surface silicon wafer, the objective lens, and an imaging lens; the sample includes a smooth-surface wafer with several cylindrical holes.

[0073] For both smooth and rough wafers, the remaining silicon thickness (RST) is calculated by subtracting the height corresponding to the bottom of the through-silicon via (TSV) from the height corresponding to the wafer surface. Determining the surface height of a smooth wafer is relatively complex, while the surface height of a rough wafer is easier to ascertain. Therefore, this application primarily focuses on designing a measurement method for the RST of smooth-surfaced wafers. Through image sampling and analysis, the height of the smooth-surfaced wafer and the height corresponding to the bottom of the TSV are determined, and the RST of the smooth-surfaced wafer is calculated.

[0074] Optionally, the light is emitted by a wide bandwidth light source, comprising components that are permeable to silicon and components that are impermeable to silicon;

[0075] Because the imaging light includes components that penetrate silicon, the sampled image set can include sampled images of the wafer's interior, surface, and exterior. This application employs a back-side measurement method, effectively solving the problem of light not reaching the bottom in high aspect ratio TSV structures. Traditional optical measurement methods are often limited in deep-hole and high aspect ratio TSV structures, failing to accurately obtain depth information. By incident light from the back side, this application can better illuminate the bottom of the TSV, significantly improving measurement accuracy.

[0076] S200: Determine several clear images in the sampled image set that meet preset clarity conditions, and the objective lens positions corresponding to several of the clear images.

[0077] Based on the sampled image set and the sharpness evaluation function, a sharpness evaluation value dataset is calculated; the sharpness evaluation function includes, but is not limited to, the energy gradient function, Roberts function, Tenengrad function, Brenner function, variance function, Laplace function, and sharpness evaluation function based on information entropy.

[0078] Based on the aforementioned sharpness evaluation value dataset and preset conditions, several sharp images whose sharpness meets the preset conditions are obtained; based on the several sharp images, the corresponding objective lens positions are obtained.

[0079] In some embodiments, the process of obtaining several clear images whose clarity meets the preset conditions based on the clarity evaluation value dataset and preset conditions in step S200 can be implemented by the following steps:

[0080] S210: Based on the aforementioned sharpness evaluation value dataset, obtain several sharpness evaluation maxima.

[0081] Analyzing the data trends in the sharpness evaluation value dataset reveals several sharpness evaluation maxima that conform to the trend of maximum values. When the sharpness evaluation value corresponding to an image is a maximum, it proves that the image is sharp.

[0082] S220: Based on several sharpness evaluation maxima, obtain several sharp images.

[0083] Based on the analysis of several sharpness evaluation maxima and their corresponding sampled images, clear images of the bottom of the cylindrical holes of the smooth surface wafer, clear images of the actual rough surface silicon wafer, and clear images of the virtual image reflected by the rough surface silicon wafer are selected.

[0084] S300: Based on several clear images, the objective lens positions corresponding to several clear images, and a preset algorithm, the remaining silicon thickness of the sample is calculated.

[0085] By obtaining clear images of several key locations and their objective lens positions, the objective lens position of the smooth surface wafer of the sample can be determined, and then the remaining silicon thickness of the sample can be calculated according to a preset algorithm.

[0086] In some embodiments, the process of calculating the remaining silicon thickness of the sample based on a plurality of clear images, the objective lens positions corresponding to the plurality of clear images, and a preset algorithm in step S300 can be implemented by the following steps:

[0087] S310: Obtain the thickness value of the rough surface silicon wafer.

[0088] S320: Based on the objective lens position corresponding to the clear image of the bottom of the cylindrical hole of the smooth surface wafer, the objective lens position corresponding to the clear image of the actual rough surface silicon wafer, the objective lens position corresponding to the clear image of the virtual image reflected by the rough surface silicon wafer, the thickness value, and the preset algorithm, the remaining silicon thickness of the sample is calculated.

[0089] By inserting a rough-surfaced silicon wafer and using a clear image of the actual rough-surfaced silicon wafer and a clear image of the reflected virtual image of the rough-surfaced silicon wafer, the position of the objective lens corresponding to the surface of the smooth-surfaced wafer can be determined. Furthermore, by combining the position of the objective lens corresponding to a clear image of the bottom of the cylindrical hole of the smooth-surfaced wafer, the remaining silicon thickness of the smooth-surfaced wafer sample can be calculated.

[0090] As shown in Figure 2, this application embodiment also provides a system for measuring the remaining silicon thickness. The system includes a light source 1, an aperture stop 2, a first collimating lens 3, a second collimating lens 4, a camera 5, an imaging lens 6, a beam splitter 7, an objective lens 8, a rough-surface silicon wafer 9, a sample 10, a leveling device 11, a platform 12, a movable guide rail 13, a column 14, and a processor.

[0091] The platform 12 is used to fix the column 14 and the leveling device 11;

[0092] The leveling device 11 is used to load the sample;

[0093] The column 14 is used to fix the movable guide rail 13;

[0094] The movable guide rail 13 is used to fix the mirror cavity 15; the mirror cavity 15 includes an aperture stop 2, a first collimating lens 3, a second collimating lens 4, a camera 5, an imaging lens 6, a beam splitter 7, and an objective lens 8.

[0095] Optionally, the movable guide rail can be configured with a speed variation pattern, which drives the mirror cavity to move, further moving the objective lens in the measurement system. Because the speed variation pattern of the movable guide rail can be set according to actual needs, and by recording the time of the movable guide rail movement, the position of the objective lens movement can be determined in real time (the distance the objective lens moves can be obtained in real time by setting the starting point of the objective lens as a reference point), which is used to measure the remaining silicon thickness.

[0096] The processor is used to implement the above-described measurement method;

[0097] The light emitted by the light source 1 passes sequentially through the aperture stop 2, the first collimating lens 3, the second collimating lens 4, and the beam splitter 7. After being deflected by the beam splitter 7, the light passes sequentially through the objective lens 8, the rough surface silicon wafer 9, and the sample 10. After being reflected by the sample 10, the light passes sequentially through the rough surface silicon wafer 9, the objective lens 8, the beam splitter 7, and the imaging lens 6, and finally enters the camera.

[0098] Optionally, the light source includes a wide bandwidth light source, comprising a silicon-permeable portion and a silicon-impermeable portion.

[0099] Furthermore, the measurement system provided in this application can combine visible and infrared light for measurement, enabling both high-resolution imaging of the wafer surface and effective measurement of the wafer's internal structure. This innovative method can comprehensively acquire depth information and adapt to the measurement needs of various materials and structures.

[0100] The measurement system provided in this application acquires a set of sampled images by changing the distance between the objective lens and the sample. The sharpness of these images is evaluated, and based on the sharpness evaluation dataset, corresponding sharp images are selected using preset conditions. Finally, based on the sharp images, the corresponding objective lens position, and a preset algorithm, a high-precision measurement result of the remaining silicon thickness can be quickly obtained. Unlike traditional contact measurement methods, this application uses imaging for measurement, maintaining the advantages of non-contact detection and avoiding potential damage to devices caused by physical contact. This detection method is more suitable for rapid inspection on production lines, ensuring the safety and integrity of the equipment.

[0101] It is evident that the content of the above method embodiments is applicable to this system embodiment. The specific functions implemented in this system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0102] As shown in Figure 3, Figure 3 is a flowchart illustrating another method for measuring residual silicon thickness provided in an embodiment of this application; this application also provides another method for measuring residual silicon thickness, applied to a residual silicon thickness measurement system as shown in Figure 2, including the following steps:

[0103] S500: Optical path setup: Complete the optical path setup as shown in Figure 2.

[0104] Specifically, the light emitted by the light source passes sequentially through the aperture stop, the first collimating lens, the second collimating lens, and the beam splitter; after being deflected by the beam splitter, the light passes sequentially through the objective lens, the rough-surface silicon wafer, and the sample; after being reflected by the sample, it passes sequentially through the rough-surface silicon wafer, the objective lens, the beam splitter, and the imaging lens, and finally enters the camera.

[0105] S510: Perform a scan on the sample to determine if it is smooth.

[0106] Specifically, the objective lens is moved to perform an image sampling of the entire sample. Computer analysis is then used to determine whether the surface of the sample wafer is smooth. If the sample wafer surface is rough, a corresponding image of the rough surface can be directly obtained; otherwise, the sample wafer has a smooth surface.

[0107] Specifically, when the scanning direction is not perpendicular to the wafer surface, the leveling device 11 can be controlled by the image sampling information to compensate for the tilt angle.

[0108] S520: Change the distance between the objective lens and the sample to acquire a set of sampled images.

[0109] By sampling the images in step S510, the position of the objective lens corresponding to the bottom of the cylindrical hole on the sample wafer can be confirmed (if there are multiple cylindrical holes, the one closest to the sample wafer surface that can be clearly imaged is selected). During actual measurement, the objective lens is first moved downwards until it is below the objective lens position corresponding to the bottom of the cylindrical hole on the sample wafer. Then, the objective lens is moved upwards at a constant speed, and images are acquired at a constant speed to form a sampled image set.

[0110] Optionally, if the sample wafer surface is rough, the rough-surfaced silicon wafer is removed from the system before step S520 is performed.

[0111] Furthermore, the movable guide rail is designed to move at a constant speed, which drives the mirror cavity to move, thereby making the objective lens in the measurement system move at a constant speed. Since the movable guide rail is designed to move at a constant speed, the position of the objective lens can be determined in real time by recording the time of the movable guide rail (the distance the objective lens moves can be obtained in real time by setting the starting point of the objective lens as a reference point), which is used to measure the remaining silicon thickness.

[0112] S530: Based on the sampled image set, determine the clear image of the key location and confirm the corresponding objective lens position.

[0113] While acquiring images at a constant speed, the sharpness evaluation value of each acquired image is calculated in real time according to the sharpness evaluation function until several sharpness evaluation maxima are found. From these, three sharpness evaluation maxima are selected, and the corresponding images are a sharp image of the bottom of the cylindrical hole of a smooth surface wafer, a sharp image of the actual silicon wafer with a rough surface, and a sharp image of the virtual image reflected by the silicon wafer with a rough surface. If the sample wafer surface is rough, the sample wafer surface can be imaged directly. In the measurement, only two sharpness evaluation maxima and their corresponding images need to be selected, specifically a sharp image of the sample wafer surface and a sharp image of the bottom of the cylindrical hole of the sample wafer.

[0114] Furthermore, the rough-surface silicon wafer is manufactured in-house and can be reused repeatedly. Since the surface pattern of the rough-surface silicon wafer is known, the sharp images corresponding to several maximum sharpness evaluation values ​​can be selected by analyzing image information to determine the sharp images of the actual rough-surface silicon wafer and its reflected virtual image.

[0115] S540: Calculate the remaining silicon thickness of the sample based on the image position corresponding to the key position.

[0116] When the sample wafer surface is smooth, the positional relationship between the virtual image reflected by the rough surface silicon wafer and the bottom of the cylindrical holes includes three cases as shown in Figures 4 to 6: the virtual image of the rough surface silicon wafer is located above the bottom of all the cylindrical holes, the virtual image of the rough surface silicon wafer is located between the bottoms of the cylindrical holes, and the virtual image of the rough surface silicon wafer is located below the bottom of all the cylindrical holes.

[0117] In either case, the real and virtual images of the rough-surfaced silicon wafer satisfy the plane mirror imaging rules, and the rough-surfaced silicon wafer is imaged through reflection from the smooth surface of the sample wafer. Therefore, the objective position corresponding to the smooth surface of the sample wafer can be obtained by using the objective positions corresponding to the real and virtual images of the rough-surfaced silicon wafer.

[0118] Specifically, the objective lens position corresponding to the smooth surface of the sample wafer is calculated using the following formula: h3=(h2-h1-d) / 2

[0119] In this context, d represents the thickness of the rough-surfaced silicon wafer, h1 represents the objective lens position corresponding to a clear image of the actual rough-surfaced silicon wafer, h2 represents the objective lens position corresponding to the actual self-made silicon wafer, and h3 represents the objective lens position corresponding to the smooth surface of the sample wafer.

[0120] Furthermore, the remaining silicon thickness of the sample can be calculated using the following formula:

[0121] Remaining silicon thickness Hrst = (h2 - h1 - d) / 2 - htx

[0122] In this context, d represents the thickness of the rough-surfaced silicon wafer, h1 represents the objective lens position corresponding to the image of the self-made silicon wafer, h2 represents the objective lens position corresponding to the clear image of the virtual image reflected by the rough-surfaced silicon wafer, h3 represents the objective lens position corresponding to the smooth surface of the sample wafer, and htx represents the objective lens position corresponding to the bottom of the cylindrical hole (x = 1, 2, 3...).

[0123] Furthermore, in the measurement, the measurement system provided in this application can image the bottom of multiple cylindrical holes and can automatically calculate the number of cylindrical holes in the image (there may be multiple cylindrical holes with their bottoms located at the same objective lens position).

[0124] On the other hand, when the sample wafer surface is rough, there is no need to use a self-made rough-surface silicon wafer; the remaining silicon thickness of the sample can be calculated using the following formula:

[0125] Remaining silicon thickness Hrst = H - htx

[0126] In this context, H represents the objective lens position corresponding to a clear image of the rough wafer surface, and htx represents the objective lens position corresponding to the bottom of the cylindrical aperture (x = 1, 2, 3...).

[0127] As shown in Figure 7, this application embodiment also provides a measuring device for residual silicon thickness, including:

[0128] At least one processor;

[0129] At least one memory for storing at least one program;

[0130] When the at least one program is executed by the at least one processor, the at least one processor performs the method steps described in the above method embodiments.

[0131] The memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. The memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory may optionally include remote memory located remotely relative to the processor, which can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0132] It is evident that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented in this device embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0133] Furthermore, embodiments of this application also disclose a computer program product or computer program stored in a computer-readable storage medium. A processor of a computer device can read the computer program from the computer-readable storage medium, and the processor executes the computer program, causing the computer device to perform the methods described above.

[0134] This application also provides a computer-readable storage medium storing a processor-executable program that, when executed by a processor, implements the above-described method. Similarly, the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0135] It is understood that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0136] The above is a detailed description of the preferred embodiments of this application. However, the invention of this application is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of this application. All such equivalent modifications or substitutions are included within the scope defined by the claims of this application.

Claims

1. A method for measuring residual silicon thickness, characterized in that, include: By changing the distance between the objective lens and the sample, a set of sampled images can be obtained; The sampled image set is formed by light rays passing sequentially through an objective lens and a rough-surface silicon wafer and converging onto the sample. After being reflected by the sample, the light rays pass sequentially through the rough-surface silicon wafer, the objective lens, and the imaging lens. The sample includes a smooth-surface wafer with several cylindrical holes. Determine several clear images in the sampled image set that meet preset clarity conditions, and the objective lens positions corresponding to several of the clear images; Based on several clear images, the objective lens positions corresponding to the clear images, and a preset algorithm, the remaining silicon thickness of the sample is calculated.

2. The measurement method as described in claim 1, characterized in that, The step of determining a plurality of sharp images in the sampled image set that meet preset sharpness conditions, and the objective lens positions corresponding to the plurality of sharp images, includes: Based on the sampled image set and the sharpness evaluation function, a sharpness evaluation value dataset is calculated; Based on the resolution evaluation value dataset and preset conditions, several clear images whose resolution meets the preset conditions are determined; the several clear images whose resolution meets the preset conditions include a clear image of the bottom of the cylindrical hole of the smooth surface wafer, a clear image of the actual rough surface silicon wafer, and a clear image of the virtual image reflected by the rough surface silicon wafer. Based on several clear images, the corresponding objective lens position is obtained.

3. The measurement method as described in claim 2, characterized in that, Based on the sharpness evaluation value dataset and preset conditions, several sharp images whose sharpness meets the preset conditions are obtained; including: Based on the aforementioned sharpness evaluation value dataset, several sharpness evaluation maxima are obtained; Based on several sharpness evaluation maxima, several sharp images are obtained.

4. The measurement method as described in claim 2, characterized in that, The calculation of the remaining silicon thickness of the sample based on several clear images, the objective lens positions corresponding to the clear images, and a preset algorithm includes: Obtain the thickness value of the silicon wafer with the rough surface; The remaining silicon thickness of the sample is calculated based on the objective lens position corresponding to the clear image of the bottom of the cylindrical hole of the smooth surface wafer, the objective lens position corresponding to the clear image of the actual rough surface silicon wafer, the objective lens position corresponding to the clear image of the virtual image reflected by the rough surface silicon wafer, the thickness value, and a preset algorithm.

5. The measurement method as described in claim 4, characterized in that, The preset algorithm includes: Hrst = (h2 + h1 - d) / 2 - ht Wherein, Hrst is the remaining silicon thickness of the sample, h1 is the objective lens position corresponding to the clear image of the actual rough surface silicon wafer, h2 is the objective lens position corresponding to the clear image of the virtual image reflected by the rough surface silicon wafer, d is the thickness value, and ht is the objective lens position corresponding to the clear image of the bottom of the cylindrical hole of the smooth surface wafer.

6. A system for measuring residual silicon thickness, characterized in that, The measurement system includes a camera, a mirror cavity, a light source, a rough-surface silicon wafer, a leveling device, a platform, a column, a movable guide rail, and a processor; wherein, The platform is used to fix the column and the leveling device; The leveling device is used to load the sample; The column is used to fix the movable guide rail; The movable guide rail is used to fix the mirror cavity; The processor is used to implement the measurement method as described in any one of claims 1 to 5; The mirror cavity includes: an aperture stop, a collimating lens unit, a beam splitter, an objective lens, and an imaging lens; The light emitted by the light source passes sequentially through the aperture stop, the first collimating lens, the second collimating lens, and the beam splitter; after being deflected by the beam splitter, the light passes sequentially through the objective lens, the rough-surface silicon wafer, and the sample; after being reflected by the sample, it passes sequentially through the rough-surface silicon wafer, the objective lens, the beam splitter, and the imaging lens, and finally enters the camera.

7. A measurement system as described in claim 6, characterized in that, The light source includes a wide bandwidth light source; the wide bandwidth light source includes components that are permeable to silicon and components that are not permeable to silicon.

8. A measurement system as described in claim 6, characterized in that, The rough-surface silicon wafer includes a grid, the grid shape of which includes strips, squares, and circles.

9. A device for measuring residual silicon thickness, characterized in that, include: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor performs the method as described in any one of claims 1 to 5.

10. A computer-readable storage medium storing a processor-executable program, characterized in that, The processor-executable program, when executed by the processor, is used to perform the method as described in any one of claims 1 to 5.

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