Optical metrology system, optical metrology method, apparatus, medium, and product

Abstract

Embodiments of the present application provide an optical measurement system, an optical measurement method, an apparatus, a medium and a product. The system comprises a measurement device, a light source and a spectrometer. The spectrometer is configured to collect spectral information of light reflected by a wafer to be measured after the light is projected by the light source to the wafer to be measured. The measurement device is in communication connection with the spectrometer, configured to acquire the spectral information collected by the spectrometer, and input the spectral information into a pre-established optical model to obtain a corresponding measurement result. The optical model is established according to a plurality of characteristic data obtained by scanning the wafer to be measured by an atomic force microscope. The system can improve the accuracy of optical measurement.

Description

Technical Field

[0001] This application relates to the field of semiconductor measurement, and more particularly to an optical measurement system, optical measurement method, equipment, medium, and product. Background Technology

[0002] With the continuous advancement of semiconductor technology, device dimensions are gradually shrinking to the nanometer level. Traditional contact-based wafer measurement methods can no longer meet the requirements of high precision and non-destructive testing. Optical Critical Dimension (OCD) measurement technology has emerged to address this need. It uses optical methods to perform non-contact measurement of the critical dimensions of wafers, effectively avoiding physical damage to the wafer.

[0003] OCD (Optical Disc Reflection) measurement involves projecting light onto the patterned structure of a wafer under test and then measuring the spectrum of the reflected light to determine the size or contour of the tested pattern. This method utilizes optical principles and spectral analysis techniques to quickly and accurately obtain critical dimensional information about the wafer, including linewidth, depth, and sidewall angles, providing crucial information for process control in semiconductor manufacturing.

[0004] However, OCD measurement is based on optical models and spectral analysis. The complexity of actual materials and structures leads to discrepancies between model assumptions and reality, introducing errors. This results in deviations between OCD measurement results and actual dimensions in practical applications, making the results inaccurate and limiting its application in high-precision processes. Summary of the Invention

[0005] This application provides an optical measurement system, optical measurement method, device, medium, and product to improve the accuracy of optical measurements.

[0006] In a first aspect, embodiments of this application provide an optical measurement system, including: a measurement device, a light source, and a spectrometer; the spectrometer is used to collect spectral information of light from the light source directed onto the wafer under test after reflection by the wafer under test; the measurement device is communicatively connected to the spectrometer and is used to acquire the spectral information collected by the spectrometer and input the spectral information into a pre-established optical model to obtain corresponding measurement results; wherein, the optical model is established based on multiple sets of feature data obtained by scanning the wafer under test using an atomic force microscope.

[0007] In one possible implementation, before the measuring device inputs spectral information into a pre-established optical model, the measuring device is further configured to: scan the wafer under test using an atomic force microscope to obtain multiple sets of feature data corresponding to the wafer under test; wherein the feature data characterizes the size of the current trench morphology; and establish an optical model based on the multiple sets of feature data corresponding to the wafer under test.

[0008] In one possible implementation, when the measurement device is used to establish an optical model based on multiple sets of feature data corresponding to the wafer under test, it is specifically used to: set a hypothesis function and establish a corresponding linear regression model; input multiple sets of feature data into the linear regression model to obtain a first function corresponding to each dimension in the feature data; perform gradient descent processing on the first function corresponding to each dimension to obtain a target value for each dimension; and obtain an optical model based on the target value for each dimension.

[0009] In one possible implementation, when the measuring device is used to input multiple sets of feature data into a linear regression model to obtain the first function corresponding to each dimension in the feature data, it is specifically used to: for each dimension in the feature data, perform the following processing: obtain all data of the current dimension in multiple sets of feature data, and use the least squares method to perform linear fitting on all data of the current dimension to obtain the first function corresponding to the current dimension.

[0010] In one possible implementation, the dimensions in the feature data include: key dimensions at the top of the trench, key dimensions in the middle of the trench, key dimensions at the bottom of the trench, the inclination angle of the trench sidewalls, and the trench depth.

[0011] In one possible implementation, the inclination angle of the trench sidewall is the arctangent of the ratio of the trench depth to half the difference between the bottom critical dimension and the top critical dimension.

[0012] Secondly, embodiments of this application provide an optical measurement method based on an optical measurement system. The system includes a measurement device, a light source, and a spectrometer. The method includes: the spectrometer collecting spectral information of light incident on a wafer under test after reflection by the wafer; the measurement device acquiring the spectral information collected by the spectrometer and inputting the spectral information into a pre-established optical model to obtain corresponding measurement results; wherein the optical model is established based on multiple sets of feature data obtained by scanning the wafer under test using an atomic force microscope.

[0013] In one possible implementation, before the measuring device inputs spectral information into a pre-established optical model, the method further includes: scanning the wafer under test using an atomic force microscope to obtain multiple sets of feature data corresponding to the wafer under test; wherein the feature data characterizes the size of the current trench morphology; and establishing an optical model based on the multiple sets of feature data corresponding to the wafer under test.

[0014] In one possible implementation, when the measurement device establishes an optical model based on multiple sets of feature data corresponding to the wafer under test, the method includes: setting a hypothesis function and establishing a corresponding linear regression model; inputting multiple sets of feature data into the linear regression model to obtain a first function corresponding to each dimension in the feature data; performing gradient descent processing on the first function corresponding to each dimension to obtain a target value for each dimension; and obtaining an optical model based on the target value for each dimension.

[0015] In one possible implementation, when the measuring device inputs multiple sets of feature data into a linear regression model to obtain a first function corresponding to each dimension in the feature data, the method includes: for each dimension in the feature data, performing the following processing: obtaining all data of the current dimension in multiple sets of feature data, and using the least squares method to perform linear fitting on all data of the current dimension to obtain the first function corresponding to the current dimension.

[0016] Thirdly, embodiments of this application provide an electronic device, including: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory, causing the processor to perform the second aspect and / or various possible implementations of the second aspect as described above.

[0017] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the second aspect and / or various possible implementations of the second aspect as described above.

[0018] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the second aspect and / or various possible implementations of the second aspect as described above. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0020] Figure 1 The diagram below exemplarily illustrates the structure of the optical measurement system provided in Embodiment 1 of this application;

[0021] Figure 2 This is a schematic diagram of an example trench morphology;

[0022] Figure 3 The diagram above illustrates a flowchart of the optical measurement method based on an optical measurement system provided in Embodiment 2 of this application.

[0023] Figure 4A flowchart of an optical measurement method based on an optical measurement system provided in Embodiment 3 of this application;

[0024] Figure 5 A comparison of linear fitting data for an example of TCD;

[0025] Figure 6 This is a schematic diagram of the structure of the electronic device provided in Embodiment 4 of this application.

[0026] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0027] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0028] The terms "comprising" and "having" in this application are used to indicate an open-ended inclusion, meaning that additional elements / components / etc. may exist besides the listed elements / components / etc.; the terms "first" and "second," etc., are used only as markings or distinctions and are not intended to limit the order or quantity of the objects. Furthermore, the different elements and areas in the accompanying drawings are only schematic and are therefore not limited to the dimensions or distances shown in the drawings. The technical solutions will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0029] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with relevant laws, regulations and standards, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0030] With the development of the semiconductor industry, integrated circuits have been steadily improving the performance and density of transistors according to Moore's Law, primarily due to the miniaturization of device geometry. However, with the continuous miniaturization of device physical and geometric dimensions, the influence of 3D structure morphology on electrical properties is gradually increasing. To better observe and monitor the corresponding 3D structure and achieve effective control over device electrical properties, critical dimension monitoring has become an urgent problem to solve. Optical measurement has emerged as a solution, with OCD measurement being a prime example, characterized by its non-destructive, high-precision, and rapid nature, and has gradually become the main measurement method in optical measurement.

[0031] In practical applications, commonly used optical measurement techniques include critical dimension scanning electron microscopy (CD-SEM), conventional optical critical dimension (OCD) measurement, and transmission electron microscopy (TEM). CD-SEM scans the surface of the wafer under test with an electron beam, enabling high-precision measurement of its geometric features. However, it can damage the wafer, and its processing speed is slow due to the limited number of wafers processed per hour. Conventional OCD measurement, building upon CD-SEM, is non-destructive and can process a large number of wafers per hour, but it requires modeling, and the measurement results are significantly affected by the model, resulting in less accurate measurements. While TEM does not require modeling, it necessitates slicing the wafer to thin it for electron penetration. This results in only five sets of feature data after scanning, which is insufficient, leading to errors in the established optical model and consequently, inaccurate OCD measurement results.

[0032] The technical content provided in this application aims to solve the aforementioned technical problems in related technologies. In the embodiments of this application, the optical measurement system includes: a measurement device, a light source, and a spectrometer; the spectrometer is used to collect the spectral information of light incident on the wafer under test after reflection by the wafer; the measurement device is used to acquire the spectral information collected by the spectrometer and input the spectral information into a pre-established optical model to obtain the corresponding measurement results; wherein, the optical model is established based on multiple sets of feature data obtained by scanning the wafer under test using an atomic force microscope. The solution of this application, by establishing an optical model based on multiple sets of feature data obtained by atomic force microscopy, increases the amount of data used to establish the optical model, and combines it with the reflection spectral information collected by the spectrometer, enabling the system to more accurately reflect the physical morphology of the wafer, thereby improving the accuracy of optical measurement.

[0033] Some aspects of this application's examples involve the above considerations. The following examples illustrate the proposed solutions.

[0034] Example 1

[0035] Figure 1 The diagram above exemplarily illustrates the structure of the optical measurement system provided in Embodiment 1 of this application, such as... Figure 1As shown, the system includes: a measuring device 11, a light source 12, and a spectrometer 13;

[0036] Spectrometer 13 is used to collect the spectral information of light from light source 12 directed onto the wafer under test after reflection by the wafer under test;

[0037] The measuring device 11 is connected to the spectrometer 13 for acquiring the spectral information collected by the spectrometer 13 and inputting the spectral information into a pre-established optical model to obtain the corresponding measurement results. The optical model is established based on multiple sets of feature data obtained by scanning the wafer under test with an atomic force microscope.

[0038] In practical applications, the functions of this optical measurement system can be implemented in various ways. For example, it can be implemented through computer programs, such as application software; or it can be implemented as a medium storing relevant computer programs, such as a USB flash drive or cloud drive; or it can be implemented through a physical device that integrates or installs relevant computer programs, such as a chip.

[0039] In this example, the optical measurement system comprises three parts: a measurement device 11, a light source 12, and a spectrometer 13. The main function of the spectrometer 13 is to collect the spectral information of the light projected by the light source 12 onto the wafer under test after reflection from the wafer. The light source 12 can be any light-emitting device or apparatus used to project light onto the wafer under test. As an example, the light source 12 can be a xenon lamp, whose emission spectrum is distributed between 190nm and 1100nm, exhibiting strong emission intensity at wavelengths above 250nm. When the xenon lamp is incident on the wafer under test, the spectrometer 13 can collect the corresponding spectral information from the wafer on the other side. Alternatively, the light source 12 can also be a laser-driven white light source. Compared to traditional xenon lamps, laser-driven white light sources offer higher brightness, a wider spectral distribution, longer lifespan, and higher stability, and also make it easier to couple the spectral information corresponding to the wafer under test into the spectrometer 13.

[0040] When light emitted from light source 12 illuminates the surface of the wafer under test, the wafer reflects the light according to its own physical properties (such as surface structure and material composition). The reflected light contains rich information, and spectrometer 13 can decompose this reflected light according to different wavelengths to obtain spectral information. Spectrometer 13 is a scientific instrument that decomposes complex light into spectral lines. It consists of prisms or diffraction gratings. Using spectrometer 13, the light reflected from the surface of the wafer under test can be measured. By capturing the light information, spectrometer 13 can computerize and display and analyze the spectral information of the wafer under test. This spectral information contains key information about the wafer surface microstructure and material properties. For example, different materials have different reflectivities for specific wavelengths of light, and the microstructure of the wafer surface (such as trench morphology) can also cause light interference and diffraction phenomena, thus affecting the spectral shape of the reflected light. By accurately measuring the changes in the intensity of these reflected lights with wavelength, spectrometer 13 provides basic data for subsequent measurement and analysis.

[0041] Correspondingly, in the optical measurement system, the measurement device 11 is the key link connecting the spectrometer 13 and the final measurement results. The measurement device 11 communicates with the spectrometer 13, acquiring the spectral information collected by the spectrometer 13 and inputting this information into a pre-established optical model to obtain the corresponding measurement results. The measurement device 11 typically has the functions of data acquisition, processing, and interaction with the optical model. On the one hand, it can accurately receive spectral data from the spectrometer 13, ensuring the integrity and accuracy of the data; on the other hand, it processes and converts this spectral data according to the format required by the optical model. The optical model is constructed based on certain physical principles and mathematical algorithms to simulate the interaction process between the wafer under test and light. After the measurement device 11 inputs the spectral information into the optical model, the optical model analyzes and calculates the data according to its internal algorithms, ultimately outputting the measurement results. These measurement results can be structural parameters of the wafer surface (such as linewidth, depth, sidewall angles, etc.), material properties (such as refractive index, thickness, etc.), or defect information of the wafer surface.

[0042] In some embodiments, the optical model is established based on multiple sets of feature data obtained by scanning the wafer under test using an atomic force microscope (AFM). An AFM is a high-precision instrument for measuring microstructures, capable of scanning the wafer surface at nanometer-level resolution to acquire multiple sets of feature data, including the three-dimensional morphology and material properties of the wafer surface. This data provides the foundation and basis for establishing the optical model. The construction process of the optical model involves combining these feature data with optical principles, and through mathematical modeling and algorithm optimization, constructing a model that accurately describes the interaction process between the wafer under test and light. This model considers the influence of the wafer surface structure on physical phenomena such as light reflection, refraction, interference, and diffraction, as well as the effects of material properties on light absorption and scattering. Through the optical model, a clear correspondence can be established between complex spectral information and the actual physical properties of the wafer, thereby achieving non-contact, high-precision measurement of the wafer.

[0043] In the above example, an optical model is established by using multiple sets of feature data obtained from atomic force microscopy scanning, which increases the amount of data used to establish the optical model. Combined with the reflectance spectral information collected by the spectrometer, the system can more accurately reflect the physical morphology of the wafer, thereby improving the accuracy of optical measurement.

[0044] Based on the foregoing example, before the measuring device 11 inputs spectral information into the pre-established optical model, the measuring device 11 is also used for:

[0045] An atomic force microscope is used to scan the wafer under test to obtain multiple sets of feature data corresponding to the wafer under test; among them, the feature data characterizes the size of the current trench morphology.

[0046] An optical model is established based on multiple sets of feature data corresponding to the wafer under test.

[0047] In some embodiments, a portion of the wafer under test is selected as the test area, set to 50 μm × 50 μm. An atomic force microscope (AFM) is used to scan the test area to obtain multiple sets of feature data on its surface. These feature data are primarily used to characterize the size and shape of the trench morphology on the wafer. The AFM, with its high-resolution probe, can precisely depict the microstructure of the wafer surface. This structural information is crucial for understanding and controlling the wafer manufacturing process, as it directly affects the performance and reliability of semiconductor devices.

[0048] Accordingly, after scanning the area to be tested using an atomic force microscope, feature data of the area can be obtained. This feature data characterizes the dimensions of the current trench morphology. In one example, the dimensions in the feature data include: key dimensions at the top of the trench, key dimensions in the middle of the trench, key dimensions at the bottom of the trench, the inclination angle of the trench sidewalls, and the trench depth. Figure 2Here is a schematic diagram of an example trench morphology, such as Figure 2 As shown, the groove has protrusions on both sides, reflecting the actual shape of the groove.

[0049] Here, 'a' represents the Top Critical Dimension (TCD), which is the width at the trench opening, typically obtained directly through high-resolution atomic force microscopy. This dimension directly affects the electrical performance and reliability of the device.

[0050] 'b' represents the Middle Critical Dimension (MCD), which refers to the width at the center of the trench. Measuring this dimension helps assess the uniformity and consistency during the trench etching process. The MCD can be directly obtained using atomic force microscopy, allowing for optimization of the etching process and ensuring the uniformity of the trench structure.

[0051] 'c' represents the bottom critical dimension (BCD), which refers to the width of the trench bottom. This dimension is crucial for the electrical isolation and reliability of the device. The bottom critical dimension can be directly obtained using atomic force microscopy.

[0052] 'd' represents the trench depth, which is the vertical distance from the top to the bottom of the trench. This parameter is crucial for ensuring the electrical isolation and mechanical stability of devices. Trench depth can be precisely measured using atomic force microscopy.

[0053] e represents the sidewall angle (SWA), which is the angle between the sidewall and the horizontal direction. This angle can be calculated from the morphology data obtained by atomic force microscopy. In one example, the sidewall angle is the arctangent of the ratio of the trench depth to half the difference between the bottom critical dimension and the top critical dimension, as shown in equation (1).

[0054] SWA=Arctan Depth / (BCD-TCD) / 2 (1)

[0055] Where SWA represents the inclination angle of the trench sidewall; Depth represents the trench depth; BCD represents the critical dimension at the bottom of the trench; and TCD represents the critical dimension at the top of the trench.

[0056] After acquiring multiple sets of feature data of the wafer surface, the measurement device 11 uses this data to build an optical model. The optical model is constructed based on physical optics principles and mathematical algorithms to simulate the interaction process between the wafer surface and light. By inputting the feature data acquired by the atomic force microscope into the optical model, the optical model can be calibrated and optimized to more accurately reflect the actual optical properties of the wafer.

[0057] In the example above, this optical model based on atomic force microscopy data can not only improve the accuracy of measurements, but also be used to monitor changes in the manufacturing process in real time, promptly detect and correct potential process deviations, and ensure high quality and high efficiency in semiconductor manufacturing.

[0058] In one example, when the measuring device 11 is used to establish an optical model based on multiple sets of feature data corresponding to the wafer under test, it is specifically used for:

[0059] Set the hypothesis function and build the corresponding linear regression model;

[0060] By inputting multiple sets of feature data into a linear regression model, the first function corresponding to each dimension in the feature data is obtained;

[0061] Gradient descent is performed on the first function corresponding to each size to obtain the target value for each size;

[0062] An optical model is derived based on the target value for each dimension.

[0063] In one example, during the process of establishing an optical model in the measurement device 11, it is first necessary to set the hypothesis function and establish the corresponding linear regression model. The core of this step is to simplify the complex physical phenomenon into a mathematical model for calculation and analysis. The hypothesis function is the core part of the linear regression model, which defines the relationship between input feature data (such as the trench size and sidewall angle of the wafer surface) and output quantities (such as spectral reflectance intensity or other optical parameters).

[0064] The hypothesis function is typically a linear equation. In one example, the hypothesis function is expressed as:

[0065] y = w1X1 + w2X2 + w3X3… + b = w T X+b (2)

[0066] Among them, w1, w2, w3…, w T y represents the weight; b represents a constant; y represents the output quantity; X1, X2, X3, ..., X represent a certain feature data (such as TCD / BCD / MCD / SWA / Depth).

[0067] In one example, when the measurement device 11 is used to input multiple sets of feature data into a linear regression model to obtain the first function corresponding to each dimension in the feature data, it is specifically used for:

[0068] For each dimension in the feature data, the following processing is performed:

[0069] Obtain all data for the current size from multiple sets of feature data, and use the least squares method to perform linear fitting on all data for the current size to obtain the first function corresponding to the current size.

[0070] First, extract all data for the current size from multiple sets of feature data. Taking the Top Key Dimension (TCD) as an example, extract the values ​​of all TCDs from the feature data. Using the hypothesis function mentioned above and combining it with the least squares method, perform a linear fit on the TCD to obtain the first function corresponding to the TCD. The least squares method is a commonly used mathematical method that finds the best-fitting line by minimizing the sum of squared errors between the predicted and true values.

[0071] The formula for fitting the hypothesis function using the least squares method is as follows:

[0072] 2(Xw-y)·X=0 (3)

[0073] 2(Xw-y)·(XX T ) = 0X T (4)

[0074] 2(Xw-y)·(XX T (XX) T ) -1 =0X T (XX T ) -1 (5)

[0075] 2(Xw-y)=0 (6)

[0076] Xw=y (7)

[0077] X T Xw = X T y (8)

[0078] (X T X) -1 (X T X)·w=(X T X) -1 ·X T y (9)

[0079] w = (X T X) -1 ·X T y (10)

[0080] Where X represents a certain feature data (such as TCD / BCD / MCD / SWA / Depth); y represents the output quantity; and w represents a constant.

[0081] According to formulas (3)-(10) above, a linear fit is performed on each dimension to obtain the first function corresponding to each dimension. Then, gradient descent is applied to these first functions to optimize the model parameters. Gradient descent is an iterative optimization algorithm used to minimize the error function, so that the difference between the model prediction and the actual measurement is minimized. By continuously adjusting the model parameters, the gradient descent algorithm can find the target value for each dimension, which reflects the dimension characteristics under the best fit state. Finally, based on these target values, the measurement device can construct an accurate optical model.

[0082] The solution presented in this example not only describes the current optical properties of the wafer but also predicts its optical behavior under different conditions, providing strong support for optimization and control in semiconductor manufacturing processes. Simultaneously, it supports a stable and accurate linear relationship between atomic force microscopy (AFM) scanning results and the optical model, allowing for model calibration based on AFM results and outputting stable and accurate measurement values. This univariate linear relationship is simple and efficient, eliminating multiple interference factors, and its simple and efficient evaluation mechanism improves the verification efficiency and convenience of optical measurements.

[0083] The optical measurement system provided in this embodiment includes a measurement device, a light source, and a spectrometer. The spectrometer collects the spectral information of light reflected from the wafer after being incident on it. The measurement device acquires the spectral information collected by the spectrometer and inputs it into a pre-established optical model to obtain the corresponding measurement results. The optical model is established based on multiple sets of feature data obtained by scanning the wafer using an atomic force microscope. This solution increases the amount of data used to establish the optical model by using multiple sets of feature data obtained from atomic force microscopy. Combined with the reflection spectral information collected by the spectrometer, the system can more accurately reflect the physical morphology of the wafer, thereby improving the accuracy of optical measurement.

[0084] Example 2

[0085] Figure 3 The diagram above illustrates a flowchart of an optical measurement method based on an optical measurement system provided in Embodiment 2 of this application. The executing entity in this embodiment can be an optical measurement system, which includes a measurement device, a light source, and a spectrometer, such as... Figure 3 As shown, the method includes:

[0086] Step 301: The spectrometer collects the spectral information of the light emitted from the light source onto the wafer under test after reflection from the wafer under test;

[0087] Step 302: The measuring device acquires the spectral information collected by the spectrometer and inputs the spectral information into the pre-established optical model to obtain the corresponding measurement results; wherein, the optical model is established based on multiple sets of feature data obtained by scanning the wafer under test using an atomic force microscope.

[0088] In practical applications, the subject of this method can be an optical measurement system. There are various ways to implement the function of an optical measurement system. For example, it can be implemented through a computer program, such as application software; or it can be implemented as a medium storing relevant computer programs, such as a USB flash drive or cloud drive; or it can be implemented through a physical device that integrates or installs relevant computer programs, such as a chip.

[0089] In this example, the main function of the spectrometer is to collect the spectral information of light reflected from the wafer under test after being incident on it. The light source can be any light-emitting device or apparatus used to project light onto the wafer. As an example, a xenon lamp can be used as the light source. Xenon lamps have an emission spectrum between 190nm and 1100nm, exhibiting strong emission intensity above 250nm. When the xenon lamp is incident on the wafer, the spectrometer can collect the corresponding spectral information from the other side. Alternatively, a laser-driven white light source can be used. Compared to traditional xenon lamps, laser-driven white light sources offer higher brightness, a wider spectral distribution, longer lifespan, and higher stability, and also make it easier to couple the spectral information of the wafer under test into the spectrometer.

[0090] When light emitted from a light source shines on the surface of a wafer under test, the wafer reflects the light according to its own physical properties (such as surface structure and material composition). The reflected light contains rich information, and a spectrometer can decompose this reflected light according to different wavelengths to obtain spectral information. A spectrometer is a scientific instrument that decomposes complex light into spectral lines. It consists of prisms or diffraction gratings, etc. Using a spectrometer, the light reflected from the surface of the wafer under test can be measured. By capturing the light information, the spectrometer can computerize and display and analyze the spectral information of the wafer under test. This spectral information contains key information about the wafer's surface microstructure and material properties. For example, different materials have different reflectivities for specific wavelengths of light, and the microstructure of the wafer surface (such as trench morphology) can also cause light interference and diffraction phenomena, thus affecting the spectral shape of the reflected light. By accurately measuring the changes in the intensity of these reflected lights with wavelength, the spectrometer provides fundamental data for subsequent measurement and analysis.

[0091] Correspondingly, the measurement device is a crucial link connecting the spectrometer and the final measurement results. The measurement device communicates with the spectrometer, acquiring the spectral information collected by the spectrometer and inputting this information into a pre-established optical model to obtain the corresponding measurement results. The measurement device typically possesses data acquisition, processing, and interaction functions with the optical model. On one hand, it accurately receives spectral data from the spectrometer, ensuring data integrity and accuracy; on the other hand, it processes and converts this spectral data according to the format required by the optical model. The optical model is constructed based on certain physical principles and mathematical algorithms to simulate the interaction process between the wafer under test and light. After the measurement device inputs the spectral information into the optical model, the optical model analyzes and calculates the data according to its internal algorithms, ultimately outputting the measurement results. These measurement results can be structural parameters of the wafer surface (such as linewidth, depth, sidewall angles, etc.), material properties (such as refractive index, thickness, etc.), or defect information on the wafer surface.

[0092] In some embodiments, the optical model is established based on multiple sets of feature data obtained by scanning the wafer under test using an atomic force microscope (AFM). An AFM is a high-precision instrument for measuring microstructures, capable of scanning the wafer surface at nanometer-level resolution to acquire multiple sets of feature data, including the three-dimensional morphology and material properties of the wafer surface. This data provides the foundation and basis for establishing the optical model. The construction process of the optical model involves combining these feature data with optical principles, and through mathematical modeling and algorithm optimization, constructing a model that accurately describes the interaction process between the wafer under test and light. This model considers the influence of the wafer surface structure on physical phenomena such as light reflection, refraction, interference, and diffraction, as well as the effects of material properties on light absorption and scattering. Through the optical model, a clear correspondence can be established between complex spectral information and the actual physical properties of the wafer, thereby achieving non-contact, high-precision measurement of the wafer.

[0093] In the above example, an optical model is established by using multiple sets of feature data obtained from atomic force microscopy scanning, which increases the amount of data used to establish the optical model. Combined with the reflectance spectral information collected by the spectrometer, the system can more accurately reflect the physical morphology of the wafer, thereby improving the accuracy of optical measurement.

[0094] Building upon the aforementioned example, before the measuring device inputs spectral information into the pre-established optical model, the method further includes:

[0095] An atomic force microscope is used to scan the wafer under test to obtain multiple sets of feature data corresponding to the wafer under test; among them, the feature data characterizes the size of the current trench morphology.

[0096] An optical model is established based on multiple sets of feature data corresponding to the wafer under test.

[0097] In some embodiments, a portion of the wafer under test is selected as the test area, set to 50 μm × 50 μm. An atomic force microscope (AFM) is used to scan the test area to obtain multiple sets of feature data on its surface. These feature data are primarily used to characterize the size and shape of the trench morphology on the wafer. The AFM, with its high-resolution probe, can precisely depict the microstructure of the wafer surface. This structural information is crucial for understanding and controlling the wafer manufacturing process, as it directly affects the performance and reliability of semiconductor devices.

[0098] Accordingly, after scanning the area to be measured using an atomic force microscope, feature data of the area can be obtained. This feature data characterizes the dimensions of the current trench morphology. In one example, the dimensions in the feature data include: key dimensions at the top of the trench, key dimensions in the middle of the trench, key dimensions at the bottom of the trench, the inclination angle of the trench sidewalls, and the trench depth. Figure 2 As shown, the groove has protrusions on both sides, reflecting the actual shape of the groove.

[0099] Here, 'a' represents the Top Critical Dimension (TCD), which is the width at the trench opening, typically obtained directly through high-resolution atomic force microscopy. This dimension directly affects the electrical performance and reliability of the device.

[0100] 'b' represents the Middle Critical Dimension (MCD), which refers to the width at the center of the trench. Measuring this dimension helps assess the uniformity and consistency during the trench etching process. The MCD can be directly obtained using atomic force microscopy, allowing for optimization of the etching process and ensuring the uniformity of the trench structure.

[0101] 'c' represents the bottom critical dimension (BCD), which refers to the width of the trench bottom. This dimension is crucial for the electrical isolation and reliability of the device. The bottom critical dimension can be directly obtained using atomic force microscopy.

[0102] 'd' represents the trench depth, which is the vertical distance from the top to the bottom of the trench. This parameter is crucial for ensuring the electrical isolation and mechanical stability of devices. Trench depth can be precisely measured using atomic force microscopy.

[0103] e represents the sidewall angle (SWA), which is the angle between the sidewall and the horizontal direction. This angle can be calculated from the morphology data obtained by atomic force microscopy. In one example, the sidewall angle is the arctangent of the ratio of the trench depth to half the difference between the bottom critical dimension and the top critical dimension, as shown in equation (1).

[0104] SWA=Arctan Depth / (BCD-TCD) / 2 (1)

[0105] Where SWA represents the inclination angle of the trench sidewall; Depth represents the trench depth; BCD represents the critical dimension at the bottom of the trench; and TCD represents the critical dimension at the top of the trench.

[0106] After acquiring multiple sets of characteristic data from the wafer surface, the measurement device uses this data to build an optical model. The optical model, constructed based on physical optics principles and mathematical algorithms, is used to simulate the interaction between the wafer surface and light. By inputting the characteristic data acquired by the atomic force microscope into the optical model, it can be calibrated and optimized to more accurately reflect the actual optical properties of the wafer.

[0107] In the example above, this optical model based on atomic force microscopy data can not only improve the accuracy of measurements, but also be used to monitor changes in the manufacturing process in real time, promptly detect and correct potential process deviations, and ensure high quality and high efficiency in semiconductor manufacturing.

[0108] In one example, when the measuring device establishes an optical model based on multiple sets of feature data corresponding to the wafer under test, the method includes:

[0109] Set the hypothesis function and build the corresponding linear regression model;

[0110] By inputting multiple sets of feature data into a linear regression model, the first function corresponding to each dimension in the feature data is obtained;

[0111] Gradient descent is performed on the first function corresponding to each size to obtain the target value for each size;

[0112] An optical model is derived based on the target value for each dimension.

[0113] In one example, the process of establishing an optical model for a measurement device first requires setting a hypothesis function and building a corresponding linear regression model. The core of this step is to simplify complex physical phenomena into a mathematical model for computation and analysis. The hypothesis function is the core part of the linear regression model; it defines the relationship between input feature data (such as trench dimensions and sidewall angles on the wafer surface) and output quantities (such as spectral reflectance intensity or other optical parameters).

[0114] The hypothesis function is typically a linear equation. In one example, the hypothesis function is expressed as:

[0115] y = w1X1 + w2X2 + w3X3… + b = w T X+b (2)

[0116] Among them, w1, w2, w3…, w T y represents the weight; b represents a constant; y represents the output quantity; X1, X2, X3, ..., X represent a certain feature data (such as TCD / BCD / MCD / SWA / Depth).

[0117] In one example, when the measuring device inputs multiple sets of feature data into a linear regression model to obtain the first function corresponding to each dimension in the feature data, the method includes:

[0118] For each dimension in the feature data, the following processing is performed:

[0119] Obtain all data for the current size from multiple sets of feature data, and use the least squares method to perform linear fitting on all data for the current size to obtain the first function corresponding to the current size.

[0120] First, extract all data for the current size from multiple sets of feature data. Taking the Top Key Dimension (TCD) as an example, extract the values ​​of all TCDs from the feature data. Using the hypothesis function mentioned above and combining it with the least squares method, perform a linear fit on the TCD to obtain the first function corresponding to the TCD. The least squares method is a commonly used mathematical method that finds the best-fitting line by minimizing the sum of squared errors between the predicted and true values.

[0121] The formula for fitting the hypothesis function using the least squares method is as follows:

[0122] 2(Xw-y)·X=0 (3)

[0123] 2(Xw-y)·(XX T ) = 0X T (4)

[0124] 2(Xw-y)·(XX T (XX) T )-1 =0X T (XX T ) -1 (5)

[0125] 2(Xw-y)=0 (6)

[0126] Xw=y (7)

[0127] X T Xw = X T y (8)

[0128] (X T X) -1 (X T X)·w=(X T X) -1 ·X T y (9)

[0129] w = (X T X) -1 ·X T y (10)

[0130] Where X represents a certain feature data (such as TCD / BCD / MCD / SWA / Depth); y represents the output quantity; and w represents a constant.

[0131] According to formulas (3)-(10) above, a linear fit is performed on each dimension to obtain the first function corresponding to each dimension. Then, gradient descent is applied to these first functions to optimize the model parameters. Gradient descent is an iterative optimization algorithm used to minimize the error function, so that the difference between the model prediction and the actual measurement is minimized. By continuously adjusting the model parameters, the gradient descent algorithm can find the target value for each dimension, which reflects the dimension characteristics under the best fit state. Finally, based on these target values, the measurement device can construct an accurate optical model.

[0132] The solution presented in this example not only describes the current optical properties of the wafer but also predicts its optical behavior under different conditions, providing strong support for optimization and control in semiconductor manufacturing processes. Simultaneously, it supports a stable and accurate linear relationship between atomic force microscopy (AFM) scanning results and the optical model, allowing for model calibration based on AFM results and outputting stable and accurate measurement values. This univariate linear relationship is simple and efficient, eliminating multiple interference factors, and its simple and efficient evaluation mechanism improves the verification efficiency and convenience of optical measurements.

[0133] The optical measurement method based on an optical measurement system provided in this embodiment includes a measurement device, a light source, and a spectrometer. The spectrometer is used to collect the spectral information of light reflected from the wafer after being incident on it. The measurement device is used to acquire the spectral information collected by the spectrometer and input the spectral information into a pre-established optical model to obtain the corresponding measurement results. The optical model is established based on multiple sets of feature data obtained by scanning the wafer using an atomic force microscope. This application's solution increases the amount of data used to establish the optical model by using multiple sets of feature data obtained from atomic force microscopy, and by combining this with the reflection spectral information collected by the spectrometer, the system can more accurately reflect the physical morphology of the wafer, thereby improving the accuracy of optical measurement.

[0134] Example 3

[0135] The following example illustrates the optical measurement method based on the optical measurement system described above.

[0136] Figure 4 A flowchart of an optical measurement method based on an optical measurement system provided in Embodiment 3 of this application is shown below. Figure 4 As shown, the steps are as follows:

[0137] Step 401: Scan the wafer under test using an atomic force microscope to obtain multiple sets of feature data corresponding to the wafer under test; wherein, the feature data characterizes the size of the current trench morphology;

[0138] Step 402: Set the hypothesis function and establish the corresponding linear regression model;

[0139] Step 403: For each dimension in the feature data, perform the following processing: obtain all data of the current dimension in multiple sets of feature data, and use the least squares method to perform linear fitting on all data of the current dimension to obtain the first function corresponding to the current dimension;

[0140] Step 404: Perform gradient descent processing on the first function corresponding to each size to obtain the target value for each size;

[0141] Step 405: Obtain the optical model based on the target value for each dimension;

[0142] Step 406: The spectrometer collects the spectral information of the light emitted from the light source onto the wafer under test after reflection from the wafer under test;

[0143] Step 407: The measuring device acquires the spectral information collected by the spectrometer and inputs the spectral information into the pre-established optical model to obtain the corresponding measurement results.

[0144] Perform linear fitting based on the aforementioned steps. Figure 5 This is a comparison chart of linear fitting data for an example of TCD. Wherein, Figure 5 (a) shows a schematic diagram of linear fitting of multiple sets of TCD data obtained by scanning the wafer under test using a transmission electron microscope. Figure 5 (b) shows a schematic diagram of linear fitting of multiple sets of TCD data obtained by scanning the wafer under test using an atomic force microscope. (Comparison) Figure 5 (a) and Figure 5 (b) It can be seen that the multiple sets of TCD data obtained by scanning the wafer under test using atomic force microscopy are more numerous than the multiple sets of TCD data obtained by scanning the wafer under test using transmission electron microscopy, and the linear fitting results are more reliable.

[0145] The specific methods of optical measurement can be found in the foregoing embodiments. In summary, the optical measurement method based on the optical measurement system provided in this example establishes an optical model by using multiple sets of feature data obtained from atomic force microscopy scanning, which increases the amount of data used to establish the optical model. Combined with the reflectance spectral information collected by the spectrometer, the system can more accurately reflect the physical morphology of the wafer, thereby improving the accuracy of optical measurement.

[0146] Example 4

[0147] Figure 6 This is a schematic diagram of the structure of the electronic device provided in Embodiment 4 of this application, as shown below. Figure 6 As shown, the electronic device includes a processor 291 and a memory 292; it may also include a communication interface 293 and a bus 294. The processor 291, memory 292, and communication interface 293 can communicate with each other via the bus 294. The communication interface 293 can be used for information transmission. The processor 291 can invoke logical instructions stored in the memory 292 to execute the method described in the example above.

[0148] Furthermore, the logic instructions in the aforementioned memory 292 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium.

[0149] The memory 292, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of this application. The processor 291 executes functional applications and data processing by running the software programs, instructions, and modules stored in the memory 292, that is, it implements the methods in the above method examples.

[0150] The memory 292 may include a program storage area and a data storage area. The program storage area may store the operating system and application programs required for at least one function; the data storage area may store data created based on the use of the terminal device. Furthermore, the memory 292 may include high-speed random access memory and may also include non-volatile memory.

[0151] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method in any of the embodiments.

[0152] This application also provides a computer program product, which, when executed by a processor, implements the method in any of the embodiments.

[0153] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the claims.

[0154] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. An optical metrology system, comprising: include: Measuring devices, light sources, and spectrometers; The spectrometer is used to collect the spectral information of the light emitted by the light source onto the wafer under test after reflection by the wafer under test; The measuring device is communicatively connected to the spectrometer and is used to acquire the spectral information collected by the spectrometer and input the spectral information into a pre-established optical model to obtain the corresponding measurement results; wherein, the optical model is established based on multiple sets of feature data obtained by scanning the wafer under test using an atomic force microscope.

2. The system of claim 1, wherein, The measuring device is used to input the spectral information into the pre-established optical model before the measuring device is used to: The atomic force microscope is used to scan the wafer under test to obtain multiple sets of feature data corresponding to the wafer under test; wherein, the feature data characterizes the size of the current trench morphology; The optical model is established based on multiple sets of feature data corresponding to the wafer under test.

3. The system of claim 2, wherein, When the measuring device is used to establish the optical model based on multiple sets of feature data corresponding to the wafer under test, it is specifically used for: Set the hypothesis function and build the corresponding linear regression model; The multiple sets of feature data are input into the linear regression model to obtain the first function corresponding to each dimension in the feature data; Gradient descent is performed on the first function corresponding to each size to obtain the target value of each size; The optical model is obtained based on the target value of each dimension.

4. The system of claim 3, wherein, The measurement device is used to input the multiple sets of feature data into the linear regression model to obtain the first function corresponding to each dimension in the feature data, specifically for: For each dimension in the feature data, the following processing is performed: Obtain all data for the current size from the multiple sets of feature data, and use the least squares method to perform linear fitting on all data for the current size to obtain the first function corresponding to the current size.

5. The system of any one of claims 1-4, wherein, The dimensions in the feature data include: key dimensions at the top of the trench, key dimensions in the middle of the trench, key dimensions at the bottom of the trench, the inclination angle of the trench sidewalls, and the trench depth.

6. The system of claim 5, wherein, The inclination angle of the trench sidewall is the arctangent of the ratio of the trench depth to half the difference between the bottom critical dimension and the top critical dimension.

7. An optical measurement method based on an optical measurement system, characterized by, The system includes: a measuring device, a light source, and a spectrometer; the method includes: The spectrometer collects the spectral information of the light emitted by the light source and reflected by the wafer under test; The measuring device acquires the spectral information collected by the spectrometer and inputs the spectral information into a pre-established optical model to obtain the corresponding measurement results; wherein, the optical model is established based on multiple sets of feature data obtained by scanning the wafer under test using an atomic force microscope.

8. The method of claim 7, wherein, Before the measuring device inputs the spectral information into the pre-established optical model, the method further includes: The atomic force microscope is used to scan the wafer under test to obtain multiple sets of feature data corresponding to the wafer under test; wherein, the feature data characterizes the size of the current trench morphology; The optical model is established based on multiple sets of feature data corresponding to the wafer under test.

9. The method of claim 8, wherein, When the measuring device establishes the optical model based on multiple sets of feature data corresponding to the wafer under test, the method includes: Set the hypothesis function and build the corresponding linear regression model; The multiple sets of feature data are input into the linear regression model to obtain the first function corresponding to each dimension in the feature data; Gradient descent is performed on the first function corresponding to each size to obtain the target value of each size; The optical model is obtained based on the target value of each dimension.

10. The method of claim 9, wherein, When the measuring device inputs the multiple sets of feature data into the linear regression model to obtain the first function corresponding to each dimension in the feature data, the method includes: For each dimension in the feature data, the following processing is performed: Obtain all data for the current size from the multiple sets of feature data, and use the least squares method to perform linear fitting on all data for the current size to obtain the first function corresponding to the current size.

11. An electronic device, comprising: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method as described in claims 7-10.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in claims 7-10.

13. A computer program product comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in claims 7-10.

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