Method for OPC model, electronic equipment and computer readable storage medium

Abstract

The embodiment of the invention relates to a method for an OPC model, electronic equipment and a computer readable storage medium. The method comprises the following steps: determining contour lines of different depth positions of a plurality of plane positions of photoresist; determining a measurement value of a corresponding critical dimension of each photoetching pattern based on each contour line; determining a value of a cost function based on the measured value of the critical dimension and the simulated value of the critical dimension; and determining a model corresponding to the value of the cost function as a target OPC model in response to the value of the cost function satisfying a predetermined condition. According to the scheme of the invention, the OPC model with improved precision can be constructed.

Description

Technical Field

[0001] Embodiments of the present disclosure generally relate to integrated circuits, and more particularly, to calibration methods, electronic devices, and computer-readable storage media for OPC models. Background Art

[0002] Optical proximity correction (OPC) is one of the important means of lithography resolution enhancement technology. OPC is widely used in semiconductor manufacturing to reduce the difference between wafer image and target pattern. OPC compensates imaging by modifying the mask layout so that the obtained wafer image is closer to the target pattern. The core of OPC is to use an accurate OPC model to predict the shape of different mask patterns corresponding to the photoresist pattern on the wafer. Therefore, an accurate lithography model is an important factor in determining the quality of wafer pattern correction (or correction).

[0003] In traditional solutions, for photoresist, usually only the line width of a specific position of a certain layer is considered, which cannot fully reflect the characteristics of the layer, resulting in low accuracy of the OPC model. Summary of the invention

[0004] According to an example embodiment of the present disclosure, a solution for an OPC model is provided to at least partially overcome the above or other potential drawbacks.

[0005] According to one aspect of the present disclosure, a method for optical proximity correction model is provided. The method includes: determining contour lines of different depth positions of multiple plane positions of photoresist; determining the measurement value of the corresponding critical dimension of the lithography pattern based on each contour line; determining the value of the cost function based on the measurement value of the critical dimension and the simulation value of the critical dimension; and in response to the value of the cost function satisfying a predetermined condition, determining the model corresponding to the value of the cost function as the target OPC model.

[0006] The embodiments of the present disclosure can effectively obtain the key dimensions of the graphics of planes at different depths in different layers by performing special image processing on the measured images, thereby providing key data for the establishment of the OPC model; and can simultaneously optimize the error between the simulation value and the measured value of the key dimensions of the planes at different depths, thereby effectively improving the accuracy of the lithography model.

[0007] In some embodiments, determining contour lines of different depth positions of multiple planar positions of the photoresist includes: determining multiple pixel curves based on grayscale information of pixels in different directions in the lithography image; comparing the pixel values ​​of each pixel on the multiple pixel curves with a predetermined threshold; and determining the contour lines based on the comparison results.

[0008] In some embodiments, comparing each pixel value on a plurality of pixel curves with a predetermined threshold value includes: determining pixels in the pixel curve whose grayscale values ​​are greater than a first threshold value as contour points on a top contour line; determining pixels in the pixel curve whose grayscale values ​​are less than a second threshold value as contour points on a bottom contour line, wherein the second threshold value is less than the first threshold value; and determining pixels in the pixel curve whose grayscale values ​​are between the first threshold value and the second threshold value as contour points on corresponding contour lines between the top contour line and the bottom contour line.

[0009] In some embodiments, determining the contour line based on the comparison result includes: determining corresponding contour points based on pixel curves corresponding to pixels in different directions at the same depth position of the lithography pattern in the layer; and connecting the respective contour points to form a contour line at the same depth position.

[0010] In some embodiments, determining the measurement value of the corresponding critical dimension of each lithography pattern based on each contour line includes: fitting each contour line to generate a respective fitting curve; and obtaining the measurement value of each critical dimension based on the fitting curve.

[0011] In some embodiments, fitting each contour line separately includes: fitting the contour line to generate a fitted ellipse; and obtaining the measurement value of each key dimension based on the fitting curve includes: measuring the values ​​obtained by measuring the major axis and the minor axis of the fitted ellipse respectively as the measurement value of the key dimension.

[0012] In some embodiments, determining the value of the cost function based on the measured value of the key dimension and the simulated value of the key dimension includes: respectively determining the difference between the measured value of the key dimension in each direction of the contour line at different depth positions in the lithography figure and the corresponding simulated value of the key dimension; and determining the mean square deviation of the key dimension of the contour line at different depth positions based on each difference; and determining the sum of each mean square deviation as the value of the cost function.

[0013] In some embodiments, determining the mean square error of the key size of the contour lines at different depth positions based on the differences respectively further includes: determining the mean square error of the key size of the corresponding contour lines based on the differences and the weights corresponding to the different depth positions.

[0014] In some embodiments, determining the value of the cost function based on the measured value of the critical dimension and the simulated value of the critical dimension includes calculating the value of the cost function using the following formula:

[0015]

[0016] Where i represents the i-th depth position in the lithography pattern, n represents the total number of depth positions, and RMS irepresents the mean square error of the critical dimension measured at the i-th depth position, j represents the j-th measurement position at a certain depth position, CD wafer，j represents the measured value of the critical dimension at the jth measurement position, CD model，j represents the simulation value of the key dimension at the jth measurement position, weight j represents the weight at the jth measurement position, m represents the total number of measurement positions, and Cost represents the cost function.

[0017] In some embodiments, the photolithography image is an image obtained by scanning the photoresist after photolithography using a scanning electron microscope.

[0018] In a second aspect of the present disclosure, an electronic device is provided. The electronic device includes a processor; and a memory coupled to the processor, the memory having instructions stored therein, and when the instructions are executed by the processor, the device performs an action, the action including: determining contour lines of different depth positions of multiple plane positions of a photoresist; determining a measured value of a corresponding critical dimension of a lithographic pattern based on each contour line; determining a value of a cost function based on the measured value of the critical dimension and a simulated value of the critical dimension; and in response to the value of the cost function satisfying a predetermined condition, determining a model corresponding to the value of the cost function as a target OPC model.

[0019] In a third aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the method according to the first aspect of the present disclosure is implemented.

[0020] It will be understood from the following description that the technical solution of the present disclosure can be effective.

[0021] This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the disclosure, nor is it intended to limit the scope of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A schematic diagram showing an example environment in which embodiments of the present disclosure can be implemented;

[0023] Figure 2 A flow chart showing a method for an optical proximity correction model according to some embodiments of the present disclosure is shown;

[0024] Figure 3 A schematic diagram showing a CD-SEM measurement image and a local magnified image according to some embodiments of the present disclosure;

[0025] Figure 4A schematic diagram showing pixel intensity of a photoresist in a certain direction according to some embodiments of the present disclosure;

[0026] Figure 5 shows a schematic cross-sectional view of a simulated photoresist according to some embodiments of the present disclosure;

[0027] Figure 6 Shows the Figure 3 A schematic diagram of a fitting curve obtained by fitting the contour lines in the image shown;

[0028] Figure 7 A block diagram of a computing device capable of implementing various embodiments of the present disclosure is shown.

[0029] In the various drawings, the same or corresponding reference numerals represent the same or corresponding parts. DETAILED DESCRIPTION

[0030] The principles of the present disclosure will be described below with reference to the various exemplary embodiments shown in the accompanying drawings. It should be understood that the description of these embodiments is only to enable those skilled in the art to better understand and further implement the present disclosure, and is not intended to limit the scope of the present disclosure in any way. It should be noted that similar or identical reference numerals may be used in the figures where feasible, and similar or identical reference numerals may represent similar or identical functions. Those skilled in the art will readily recognize from the following description that alternative embodiments of the structures and methods described herein may be adopted without departing from the principles of the present invention described herein.

[0031] As used herein, the term "including" and its variations mean open inclusion, i.e., "including but not limited to". Unless otherwise stated, the term "or" means "and / or". The term "based on" means "based at least in part on". The terms "an example embodiment" and "an embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". The terms "first", "second", etc. may refer to different or the same objects.

[0032] As mentioned above, the traditional scheme usually only considers the line width of a specific position of a certain layer of the photoresist, and thus cannot fully reflect the characteristics of the layer. Specifically, the traditional OPC model predicts the line width size of a plane of the photoresist, while in some layers, the OPC model is required to capture the line width size information of multiple plane positions of the photoresist. It can be seen that the traditional scheme cannot fully reflect the characteristics of the photoresist layer, resulting in insufficient accuracy of the OPC model. The numerical value of the accuracy of the model in the traditional scheme is based on the fitting error between the simulation value of the critical dimension (Critical Dimension, CD) of the graphic and the value measured by the measurement machine on the wafer, such as the root mean square error (Root Mean Squared Error, RMS). Among them, CD usually refers to the line width of a specific longitudinal position of the photoresist.

[0033] In addition, the OPC model is a non-completely physical model, so it is impossible to accurately predict the line width information of different planes of the photoresist by only changing the parameter settings. A non-completely physical model means that this model is fitted based on a large amount of data. The model contains many statistical components, which are the characteristics of a non-completely physical model, and the model does not have good extension. In addition, the traditional OPC model calibration cost function (also known as the cost function) only defines the RMS of the line width of a photoresist height, and cannot fit the RMS of the line width of multiple planes.

[0034] Generally speaking, the line width difference between the top and bottom of the photoresist morphology is relatively large. Usually, in relatively safe situations, processing is performed based on the premise that the line widths of the top and bottom are similar. However, the actual situation is not the case. For example, if there are some special or critical dimensions in some layers, the line width difference between the top and bottom is relatively large, and such problems will lead to some subsequent processes in the process. For example, a typical example in the etching process is top loss. Such an effect will bring about process problems, resulting in device performance degradation and even malfunction.

[0035] In view of this, the present disclosure provides an improved solution.

[0036] The embodiment of the present disclosure provides an improved method for OPC model. The method includes: determining contour lines of different depth positions of multiple plane positions of photoresist; determining the measured value of the corresponding critical dimension of the lithography pattern based on each contour line; determining the value of the cost function based on the measured value of the critical dimension and the simulated value of the critical dimension; and in response to the value of the cost function satisfying a predetermined condition, determining the model corresponding to the value of the cost function as the target OPC model.

[0037] The embodiments of the present disclosure can effectively obtain the key dimensions of graphics at different depths in different layers by performing special image processing on the measured images, thereby providing key data for the establishment of the OPC model; and can simultaneously optimize the errors between the simulation values ​​and the measured values ​​of the key dimensions at different depths, thereby effectively improving the accuracy of the lithography model.

[0038] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings.

[0039] Figure 1 1 is a schematic diagram of an example environment 100 in which embodiments according to the present disclosure can be implemented. Figure 1 As shown, the example environment 100 includes a computing device 110 and a client 120 .

[0040] In some embodiments, the computing device 110 may interact with the client 120. For example, the computing device 110 may receive an input message from the client 120 and output a feedback message to the client 120. In some embodiments, the input message from the client 120 may be photolithography image data. The computing device 110 may perform corresponding mathematical operations on the photolithography image data and output corresponding operation results to the client 120.

[0041] In some embodiments, computing device 110 may include, but is not limited to, a personal computer, a server computer, a handheld or laptop device, a mobile device (such as a mobile phone, a personal digital assistant (PDA), a media player, etc.), consumer electronics, a minicomputer, a mainframe computer, cloud computing resources, etc.

[0042] It should be understood that the structure and function of the example environment 100 are described for exemplary purposes only and are not intended to limit the scope of the subject matter described herein. The subject matter described herein can be implemented in different structures and / or functions. The environment is merely illustrative and is not intended to limit the application environment of the embodiments of the present disclosure.

[0043] In order to explain the principle of the present disclosure more clearly, the following will refer to Figure 2 Let's describe it in more detail.

[0044] Figure 2 A flow chart of a method 200 for an optical proximity correction model is shown, according to some embodiments of the present disclosure.

[0045] At block 202, contours of different depth locations of a plurality of planar locations of a photoresist are determined.

[0046] In some embodiments, a Critical Dimension Scanning Electron Microscope (CD-SEM) may be used to measure the photolithographic image of the layer on the wafer after photolithography. The pixel brightness information (i.e., grayscale information) of the measured image may then be extracted to draw a pixel curve.

[0047] A scanning electron microscope is a device between a transmission electron microscope and an optical microscope. It uses a focused, narrow high-energy electron beam to scan samples, and stimulates various physical information through the interaction between the beam and the substance. This information is collected, amplified, and re-imaged to achieve the purpose of characterizing the microscopic morphology of the substance. At present, the resolution of a scanning electron microscope can reach 1nm; the magnification can reach 300,000 times and above and is continuously adjustable; and it has a large depth of field, a large field of view, and a good three-dimensional imaging effect. In addition, the combination of a scanning electron microscope and other analytical instruments can perform micro-region composition analysis of the substance while observing the microscopic morphology. It should be understood that the embodiments of the present disclosure are not limited to this, and other devices can also be used to obtain corresponding images as needed.

[0048] Refer to the following Figure 3 Describe the measured image. Figure 3 Schematic diagrams of CD-SEM measurement images and local magnified images according to some embodiments of the present disclosure are shown. Figure 3 As shown, the left side is an image 302 measured by CD-SEM, that is, a CD-SEM image obtained by photographing a layer, such as a photoresist, from above after photolithography, which can be called a photolithography image. In some embodiments of the present disclosure, photoresist is used as an example for description, but it should be understood that the embodiments of the present disclosure are not limited thereto, and other layers that form various patterns after photolithography can also apply the solutions of the embodiments of the present disclosure according to actual needs.

[0049] Photoresist is three-dimensional. When measuring photoresist, the photoresist after lithography can be scanned by electron scanning microscope, i.e. SEM. SEM emits some electrons and hits the photoresist. As mentioned earlier, when electrons hit an object, it will scatter secondary electrons, which can then be received by a receiver for analysis.

[0050] like Figure 3 As shown, the image 302 includes multiple graphics, such as Figure 3 The hole in the photoresist shown in FIG. 3 has a pattern outline 304. The outline is the outline of the edge of the pattern (here, the hole) formed in the photoresist after photolithography. Figure 3 The right side of the figure shows an enlarged schematic diagram of one of the holes. Figure 3As can be seen in FIG. 3 , three contour lines are shown, namely the extracted bottom contour line 306 ( Figure 3 The innermost dark line in the right image), the extracted middle contour line 308 ( Figure 3 The white line in the middle of the right image in the figure), and the extracted top contour line 310. The above contour lines can be extracted based on the brightness information (or grayscale information) of the pixels in the image. The embodiments of the present disclosure are not limited thereto, and contour lines at more locations can be obtained as needed to obtain higher simulation accuracy. Figure 3 A gauge 305 is also shown in the figure for marking the position to be measured. This will be further described later.

[0051] In some embodiments, the contour lines of different depth positions of the photolithographic pattern in the photoresist layer after photolithography can be determined based on the grayscale information of the pixels in the image. The photolithographic pattern refers to the pattern formed in the resist, or the shape structure, such as a hole, a groove of other shapes, etc. The CD of the photolithographic pattern in the photoresist can be used to represent the CD of the pattern formed on the wafer.

[0052] In some embodiments, determining contour lines of different depth positions of multiple plane positions of the photoresist may include: determining multiple pixel curves based on grayscale information of pixels in different directions in the photolithography image; comparing the pixel values ​​of each pixel on the multiple pixel curves with a predetermined threshold; and determining the contour line based on the comparison result. The predetermined threshold may be set according to actual needs and experience.

[0053] In some embodiments, comparing each pixel value on each pixel curve with a predetermined threshold value may include: determining pixels in the pixel curve whose grayscale value is greater than a first threshold value (or called a top threshold value) as contour points on the top contour line; determining pixels in the pixel curve whose grayscale value is less than a second threshold value (or called a bottom threshold value) as contour points on the bottom contour line, wherein the second threshold value is less than the first threshold value; and determining pixels in the pixel curve whose grayscale value is between the first threshold value and the second threshold value as contour points on the corresponding contour line between the top contour line and the bottom contour line. Generally, two contour points can be determined based on the comparison of a pixel curve with a threshold value. The contour line can be obtained by obtaining multiple contour points and connecting them.

[0054] In some embodiments, determining a contour line based on the comparison result may include: determining corresponding contour points based on pixel curves corresponding to pixels in different directions at the same depth position of the photolithography pattern in the layer, in other words, determining corresponding contour points based on pixel curves corresponding to pixels in different directions in the same plane of the photolithography pattern (e.g., holes in the photoresist or other shapes, such as rectangular grooves, etc.); and connecting the contour points in the same plane to form a contour line at the same depth position.

[0055] Combine the following Figure 4 Further description. Figure 4 Schematic diagram showing the pixel intensity in a certain direction of the photoresist after photolithography according to some embodiments of the present disclosure. In other words, Figure 4 FIG. 4 shows a pixel curve 404 showing the relationship between the position of a pixel on a straight line along a predetermined direction and the grayscale value. Figure 4 As shown, the pixel curve 400 has two pulses 402, namely the pulses with the largest grayscale value, or peaks. The location of these pixel points can be determined by comparing the grayscale value of the points on the pixel curve with a predetermined threshold, such as the bottom, top, or between the bottom and top of the hole in the photoresist.

[0056] Wherein, the threshold value Tt represents the top contour threshold value, such as the contour threshold value of the top edge of the pattern (such as a hole) in the photolithography photoresist, which corresponds to the first threshold value. The threshold value Tt represents the bottom threshold value, such as the contour threshold value of the bottom edge of the pattern (such as a hole) in the photolithography photoresist, which corresponds to the second threshold value.

[0057] In some embodiments, corresponding to Figure 4 The vertices of the two pulses 402 in can determine two points located on a certain contour line. Figure 3 Two points on the contour line 308 in .

[0058] For example, Figure 4 The first straight line 404 in the graph may represent the value corresponding to Figure 3 Two points on the contour line 306 (ie, the bottom contour line) in . Figure 4 The second straight line 406 in the figure may represent the value corresponding to Figure 3 Two points on the contour line 310 (ie, the top contour line) in .

[0059] It should be pointed out that Figure 4 The parameters of the pixel curve shown in , such as shape, amplitude, pulse width, etc., are schematic, and the actual parameters may vary depending on various factors. In addition, the top threshold Tt and the bottom threshold Tb are also schematic, and the absolute value and the difference between the two also depend on the artificial setting and the actual process conditions.

[0060] Usually for the outline of a photolithographic pattern in a photoresist, such as a hole, the grayscale values ​​of the pixels on the outline at the same depth position are substantially the same. In addition, the grayscale value of the upper part of the pattern is usually greater than the grayscale value of the lower part. Based on this cognition, the outlines of different depth positions can be determined.

[0061] In some embodiments, pixel points in the pixel curve whose grayscale values ​​are greater than the top threshold Tt may be determined as contour points on the top contour line.

[0062] In some embodiments, pixel points in the pixel curve whose grayscale values ​​are less than the bottom threshold Tb may be determined as contour points on the bottom contour line.

[0063] In some embodiments, a pixel point in the pixel curve whose grayscale value is between a bottom threshold value Tb and a top threshold value Tt may be determined as a contour point on the contour line at a position between the top and the bottom.

[0064] Specifically, in the actual measurement process, the position to be measured is usually pre-set, which can be achieved by, for example, setting the position of the ruler. For example, a first ruler is set in a first direction in the photolithography image, and the grayscale value of a corresponding row of pixels in the image can be measured along the orientation specifically indicated by the first ruler during measurement to obtain a first pixel curve. The ruler can be automatically set by a special tool (hardware or software), and its specific setting method is known in the industry. A second ruler can be set along different directions, up to the mth ruler, and the number of m can be very large, for example, it can be thousands or even tens of thousands. Correspondingly, the grayscale values ​​of the pixels corresponding to the orientation indicated by these rulers are measured to obtain the corresponding pixel curve. Usually, two points corresponding to two pulses can be obtained according to each pixel curve, that is, two points on the contour line. Connecting the points obtained by the pulses of each pixel curve at each position in the same plane obtains the contour line of the edge of the plane. In short, two points on the contour line can be determined based on the pulses on each pixel curve of pixels in different directions at the same depth corresponding to the pattern (such as a hole) in the photoresist. Multiple points can be determined by multiple contour lines. The contour line can be obtained by connecting the multiple points. In practical applications, CDs of different planes can be distinguished by contour lines of different colors (in the software).

[0065] In the above embodiment, the contour line of the lithography pattern is obtained by means of pulses in the pixel curve, but the embodiments of the present disclosure are not limited thereto, and various other methods known in the industry may also be used to obtain the contour line.

[0066] At block 204 , a critical dimension of the lithographic pattern is determined based on the various contour lines.

[0067] In conventional solutions, usually only the line width at a specific position of a certain layer of photoresist is considered as CD. In some embodiments of the present disclosure, the CD at the plane position of different depths of the photoresist is considered, thereby providing more data for constructing the OPC model of the photoresist, thereby improving the accuracy of the OPC model, and then obtaining a more accurate pattern on the wafer.

[0068] In some embodiments, determining the measurement value of the corresponding critical dimension of each lithographic pattern based on each contour line may include: fitting each contour line to generate a respective fitting curve; and obtaining the measurement value of each critical dimension based on the fitting curve. Usually, the measured contour line is not a smooth curve. By fitting the contour line, it is convenient to accurately measure it to obtain the value of its critical dimension.

[0069] In some embodiments, fitting each contour line may include: fitting the contour line to generate a fitted ellipse; and obtaining the measurement value of each key dimension based on the fitting curve may include: using the values ​​obtained by measuring the major axis and the minor axis of the fitted ellipse as the measurement value of the key dimension. Ellipse fitting is usually suitable for a hole layer, that is, a layer with holes formed therein. By performing ellipse fitting, the values ​​of the major axis, the minor axis, etc. of the ellipse can be obtained.

[0070] In some embodiments, the contour line may also be subjected to, for example, circle fitting, that is, generating a fitting circle, etc. It should be understood that the embodiments of the present disclosure are not limited thereto, and various graphics may be fitted according to actual needs.

[0071] At block 206 , a value of a cost function is determined based on the measured value of the critical dimension and the simulated value of the critical dimension.

[0072] The measured value of the critical dimension can be obtained by the aforementioned method. The simulated value of the critical dimension can be pre-stored in a memory, or can be measured on-site as needed.

[0073] The value of the cost function may be used to indicate the difference between the measured value of the critical dimension and the simulated value of the critical dimension. In some embodiments, determining the value of the cost function based on the measured value of the critical dimension and the simulated value of the critical dimension may include: respectively determining the difference between the measured value of the critical dimension in each direction of the contour line at different depth positions in the lithography pattern and the corresponding simulated value of the critical dimension; respectively determining the mean square deviation of the critical dimension of the contour line at different depth positions based on each difference; and determining the sum of each mean square deviation as the value of the cost function.

[0074] In some embodiments, determining the mean square error of the key dimensions of the contour lines at different depth positions based on the respective differences may include: determining the mean square error of the key dimensions of the corresponding contour lines based on the respective differences and the weights corresponding to the different depth positions. Different weights may be set for different planes (depth positions) as needed.

[0075] In some embodiments, determining the value of the cost function based on the measured value of the critical dimension and the simulated value of the critical dimension may include calculating the value of the cost function cost using the following formula.

[0076]

[0077] Where i represents the i-th plane or i-th depth position in the photolithography pattern, n represents the total number of planes (different photoresist heights), RMS i It represents the mean square error of the critical dimension measured at the i-th plane. j represents the j-th measurement position (XY plane measurement position) in a certain plane (or i-th depth position), which can also be called the marking position of the j-th ruler. CD wafer，j represents the measured value of the critical dimension at the jth measurement position, CD model，j represents the simulation value of the key dimension at the jth measurement position, weight j represents the weight at the jth measurement position, and m represents the total number of measurement positions. n is usually greater than or equal to 2, which means that at least two planes need to be measured, that is, the line width error calculation of the photoresist includes two planes.

[0078] In some embodiments, no weight may be set, that is, each plane may be considered to have the same weight.

[0079] At block 208 , in response to the value of the cost function satisfying a predetermined condition, a model corresponding to the value of the cost function is determined as a target OPC model.

[0080] In the process of constructing an OPC model or modifying an OPC model, for example, an OPC model for photoresist, an iteration process is involved. In other words, the process of calculating the cost function involves an iteration process. As the iteration proceeds, the value of the cost function becomes smaller and smaller, indicating that the corresponding model is closer to the ideal model (target OPC model).

[0081] In some embodiments of the present disclosure, the value of the cost function satisfies a predetermined condition, which may refer to satisfying at least one of the following: the value of the cost function is less than a predetermined threshold; the number of iterations or the iteration time reaches a predetermined threshold; or the ratio between the values ​​of two iterations is less than a predetermined threshold, etc. The embodiments of the present disclosure are not limited to this, and other conditions may be adopted as needed.

[0082] The determined target OPC model can be used for subsequent OPC model calibration (correction) or verification. As known in the industry, verification refers to the process of checking whether the generated lithography pattern meets the required pattern standard. Correction refers to improving the generated lithography pattern to obtain a more optimized pattern.

[0083] Traditional OPC models generally only predict the bottom CD of the photoresist. In some cases, the bottom CD may have reached the expected target, but the top CD is actually far from the expected target, for example, the top CD is very small. However, the traditional model cannot predict this situation, so it cannot predict the result. The size of the top will have a great impact on the subsequent process, especially in small-size nodes. Because for large sizes, the difference between the top CD and the bottom CD of large-size nodes is not too large. The smaller the node, the smaller the resolution, and there will be many effects, which leads to a large difference between the top and the bottom, resulting in a safe situation. This will cause trouble to the subsequent process, such as causing the formation of degraded devices, or the need to adjust the process.

[0084] In some embodiments of the present disclosure, by constructing an OPC model, the photoresist shape can be accurately predicted during photolithography. That is, the solution of the embodiments of the present disclosure can improve the accuracy of the OPC model, thereby improving the photolithography accuracy.

[0085] Figure 5 A schematic cross-sectional view of a simulated photoresist according to some embodiments of the present disclosure is shown. Figure 5 The horizontal axis represents the size in the horizontal direction, and the vertical axis represents the size in the vertical direction, and the units are respectively micrometers. A photoresist hole 502 is formed in the photoresist 500 by photolithography, and the cross-sectional shape of the photoresist hole 502 is as follows: Figure 5 As shown, the photoresist hole 502 has a contour 506. The three straight lines indicated by reference numeral 504 represent three horizontal plane positions. The contour lines at the three horizontal plane positions can be obtained by the method described in the above embodiments. Figure 5 The shape of the cross section of the photoresist shown in FIG. 1 is schematic, and the shape thereof may be variously changed in practice.

[0086] The dark part below the photoresist 500 is the anti-reflective coating and other layers below, which are not closely related to the content of the present disclosure, so the present disclosure will not describe them in detail.

[0087] In some embodiments, simulations can be performed using the model to obtain different depth positions (e.g. Figure 5 The simulated value of CD of the contour of the plane at the position of the plane indicated by the bottom 504 or the position of the plane indicated by other 504) is obtained. The obtained simulated value can be compared with the corresponding CD measured value obtained by the above-mentioned embodiment. That is, for the same plane position, the measured value of CD is compared with the simulated value to determine the error.

[0088] Figure 6 Shows the Figure 3 The diagram shows a schematic diagram of a fitting curve obtained by fitting the contour lines in the image. Figure 6 Zhongyu Figure 3 The same contents will not be described again.

[0089] Fitting the contour line to extract the CD value can be performed as follows: the contour lines of different heights can be fitted with ellipses. Of course, this method is applicable to the hole layer, that is, the photoresist layer etched with holes. The embodiments of the present disclosure are not limited to this, and other fittings can be performed as needed.

[0090] like Figure 6 The dashed line 312 in FIG. 3 is a fitting curve obtained by fitting the contour line 306. In this embodiment, a fitting ellipse is obtained. Then, the major axis and the minor axis of the fitting ellipse are obtained. Figure 6 The horizontal double arrow line in the figure represents the minor axis of the fitted ellipse, and the vertical double arrow line represents the major axis of the fitted ellipse. Figure 6 The measured CDs shown in can be fitted line widths X and Y, respectively.

[0091] In some embodiments of the present disclosure, the image data measured by CD-SEM is used to obtain the profile information of different photoresist height positions by analyzing the intensity of pixel brightness. After obtaining the profile information, a fitting method is used for the irregular profile to extract the key dimensions, which are then converted into data that can be directly used by the OPC model. In some embodiments of the present disclosure, a cost function design that calculates non-single, i.e., line width RMS in multiple planes can be used for model calibration.

[0092] In some embodiments of the present disclosure, the OPC model is established and calibrated by acquiring CDs at different positions and using a cost function optimization method.

[0093] In some embodiments of the present disclosure, special image processing is performed on the images measured by CD-SEM to obtain signals of different photoresist height positions, and the signals are used for OPC R3D model calibration.

[0094] The solutions of some embodiments of the present disclosure can effectively obtain the line width of the pattern of the photoresist at different height planes, and provide key data for the establishment of OPC R3D models, for example. In addition, the solutions of some embodiments of the present disclosure can simultaneously optimize the error between the key dimensions of different planes of the photoresist and the wafer measurement during the model calibration process, which can effectively improve the accuracy of the lithography model and provide a key guiding role for the model in subsequent correction stages.

[0095] Some embodiments of the present disclosure provide methods for optical proximity correction models. It should be noted that the examples given in the above embodiments are only for illustrating the schemes of the embodiments of the present disclosure, and are not used to limit the schemes of the present disclosure. For example, in the above embodiments, the method of model construction is illustrated by taking photoresist as an example. It should be understood that the embodiments of the present disclosure are not limited to this, but can be applied to a variety of similar devices or structures in semiconductor processes. As is known in the industry, photoresist can be used as a soft mask; and some other layers on the wafer can be used as hard masks. For these hard mask structures, the methods in the embodiments of the present disclosure can also be used to simulate, build models or correct models, and calibrate and / or verify them.

[0096] It should be understood that the embodiments shown in the drawings are only for schematically illustrating the solutions of some embodiments of the present disclosure and are not intended to limit the present disclosure. The embodiments of the present disclosure may also have various other forms.

[0097] An electronic device is also disclosed in an embodiment of the present disclosure. The electronic device includes: a processor; and a memory coupled to the processor, the memory having instructions stored therein, and when the instructions are executed by the processor, the device performs actions, including: determining contour lines of different depth positions of multiple plane positions of the photoresist; determining the measurement value of the corresponding critical dimension of the lithography pattern based on each contour line; determining the value of the cost function based on the measurement value of the critical dimension and the simulation value of the critical dimension; and in response to the value of the cost function satisfying a predetermined condition, determining a model corresponding to the value of the cost function as a target OPC model.

[0098] An embodiment of the present disclosure further discloses a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method for an optical proximity correction model according to an embodiment of the present disclosure is implemented.

[0099] Figure 7 A schematic block diagram of an electronic device according to some exemplary embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0100] like Figure 7As shown, the device 700 includes a CPU 701, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 702 or a computer program loaded from a storage unit 708 into a random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 can also be stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0101] Multiple components in the device 700 are connected to the I / O interface 705, including: an input unit 706, such as a keyboard, a mouse, etc.; an output unit 707, such as various types of displays, speakers, etc.; a storage unit 708, such as a disk, an optical disk, etc.; and a communication unit 709, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0102] The various processes and processing described above, such as method 200, may be executed by CPU 701. For example, in some embodiments, method 200 may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as storage unit 708. In some embodiments, part or all of the computer program may be loaded and / or installed on device 700 via ROM 702 and / or communication unit 709. When the computer program is loaded into RAM 703 and executed by CPU 701, one or more steps in method 200 described above may be performed.

[0103] The scheme according to the embodiment of the present disclosure may be a method, an apparatus, a system and / or a computer program product. The computer program product may include a computer-readable storage medium on which computer-readable program instructions for executing various aspects of the present disclosure are loaded. The computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. The computer-readable program instructions may be downloaded from the computer-readable storage medium to various computing / processing devices, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network and / or a wireless network.

[0104] Various embodiments of the present disclosure have been described above, and the above descriptions are exemplary and are only optional embodiments of the present disclosure, not exhaustive, and are not intended to limit the present disclosure. Although the claims in this application have been formulated for specific combinations of features, it should be understood that the scope of the present disclosure also includes any novel features or any novel combination of features disclosed herein, whether or not it relates to the same scheme in any claim currently claimed for protection. The applicant hereby informs that new claims may be formulated into these features and / or combinations of these features during the examination of this application or in any further application derived therefrom.

[0105] The terms used in this article are selected to best explain the principles of each embodiment, practical application or technical improvement in the market, or to enable other ordinary technicians in the field to understand the embodiments disclosed herein. For those skilled in the art, the present disclosure may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure shall be included in the scope of protection of the present disclosure.

Claims

1. A method for an optical proximity correction model, comprising: Determining contour lines of different depth positions of a plurality of planar positions of the photoresist; Determining a measurement value of a corresponding critical dimension of the lithographic pattern based on each of the contour lines; determining a value of a cost function based on the measured value of the critical dimension and a simulated value of the critical dimension; as well as In response to the value of the cost function satisfying a predetermined condition, a model corresponding to the value of the cost function is determined as a target OPC model.

2. The method according to claim 1, wherein determining the contours of different depth positions of a plurality of planar positions of the photoresist comprises: Determine a plurality of pixel curves based on the grayscale information of pixels in different directions in the lithography image respectively; Comparing the pixel value of each pixel on the plurality of pixel curves with a predetermined threshold value respectively; as well as The contour line is determined based on a result of the comparison.

3. The method according to claim 2, wherein comparing each pixel value on the plurality of pixel curves with a predetermined threshold value comprises: Determine pixels in the pixel curve whose grayscale values ​​are greater than a first threshold as contour points on the top contour line; Determine pixels in the pixel curve whose grayscale values ​​are less than a second threshold as contour points on the bottom contour line, wherein the second threshold is less than the first threshold; as well as Pixels in the pixel curve whose grayscale values ​​are between the first threshold and the second threshold are determined as contour points on corresponding contour lines between the top contour line and the bottom contour line.

4. The method according to claim 2, wherein determining the contour line based on the result of the comparison comprises: Determining corresponding contour points based on pixel curves corresponding to pixels in different directions at the same depth position of the photolithographic pattern in the layer; as well as The contour points are connected to form the contour line at the same depth position.

5. The method according to claim 1, wherein determining the measurement value of the corresponding critical dimension of each lithography pattern based on each of the contour lines comprises: Fitting each of the contour lines respectively to generate respective fitting curves; as well as The measured values ​​of the key dimensions are obtained based on the fitting curve.

6. The method according to claim 5, wherein: Fitting each of the contour lines separately includes: performing ellipse fitting on the contour line to generate a fitting ellipse; and Obtaining the measurement values ​​of each of the key dimensions based on the fitting curve includes: taking the values ​​obtained by respectively measuring the major axis and the minor axis of the fitting ellipse as the measurement values ​​of the key dimensions.

7. The method of claim 1 , wherein determining a value of a cost function based on the measured value of the critical dimension and the simulated value of the critical dimension comprises: respectively determining the difference between the measured value of the critical dimension in each direction of the contour line at different depth positions in the lithography pattern and the corresponding simulated value of the critical dimension; Determining the mean square deviation of the key dimensions of the contour lines at the different depth positions based on the differences respectively; as well as The sum of the mean square errors is determined as the value of the cost function.

8. The method according to claim 7, wherein determining the mean square deviation of the critical dimensions of the contour lines at the different depth positions based on the differences respectively further comprises: The mean square error of the key dimension of the corresponding contour line is determined based on the differences and the weights corresponding to the different depth positions.

9. The method of claim 8, wherein determining a value of a cost function based on the measured value of the critical dimension and the simulated value of the critical dimension comprises calculating the value of the cost function using the following formula: in, i represents the i-th depth position in the lithographic pattern, n represents the total number of depth positions, RMS t represents the mean square error of the critical dimension measured at the i-th depth position, j represents the j-th measurement position at a certain depth position, CD wafer，j represents the measured value of the critical dimension at the jth measurement position, CD model，j represents the simulation value of the key dimension at the jth measurement position, weight j represents the weight at the jth measurement position, m represents the total number of measurement positions, and Cost represents the cost function.

10. The method according to any one of claims 1 to 9, wherein: The photolithography image is an image obtained by scanning the photoresist after photolithography using a scanning electron microscope.

11. An electronic device, comprising: processor; as well as A memory coupled to the processor, the memory having instructions stored therein, the instructions causing the device to perform actions when executed by the processor, the actions comprising: Determining contour lines of different depth positions of a plurality of planar positions of the photoresist; Determining a measurement value of a corresponding critical dimension of the lithographic pattern based on each of the contour lines; determining a value of a cost function based on the measured value of the critical dimension and a simulated value of the critical dimension; and In response to the value of the cost function satisfying a predetermined condition, a model corresponding to the value of the cost function is determined as a target OPC model.

12. A computer-readable storage medium having machine-executable instructions stored thereon, which, when executed by a processor, enables the processor to implement the method according to any one of claims 1 to 10.

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