Method of optical proximity correction

Abstract

The application provides a method for optical proximity correction, which comprises the following steps: obtaining a target pattern and a first menu parameter, wherein the first menu parameter is used for controlling the simulated profile of the target pattern after correction, and the area difference between the simulated profile and the target pattern is defined as a cost function; forming a line segment which is in contact with and continuous to the profile edge of the target pattern, and setting a mark point on the line segment; then generating a plurality of groups of mark points with different positions by using an algorithm, and obtaining the cost function corresponding to each group of mark points; selecting the mark point with the minimum value in the plurality of groups of cost functions and the parameter of the line segment, and obtaining a second menu parameter according to the mark point and the parameter; and performing optical proximity correction on the target pattern according to the second menu parameter. The application applies the "genetic algorithm" to optimize the menu parameter of optical proximity effect, so that the profile of the corrected pattern is smoother and more consistent with the target pattern.

Description

Technical Field

[0001] This invention relates to the field of semiconductor technology, and in particular to a method for optical proximity effect correction. Background Technology

[0002] The OPC (Optical Proximity Correction) menu parameters offer numerous options to control the simulated profile after optical proximity correction. Based on the OPC model and lithography process, convergence means that the profile of the layout after exposure is consistent under Eop / Fop conditions. However, traditional OPC menu processing methods rely on trial and error to fine-tune segmented analysis and target control to check the results, resulting in significant errors compared to the actual layout profile.

[0003] Therefore, a new method for optical proximity correction is needed to improve the accuracy of the simulated profile after optical proximity correction. Summary of the Invention

[0004] In view of the shortcomings of the prior art described above, the purpose of this invention is to provide a method for optical proximity effect correction, which solves the problem that the existing OPC menu processing method uses trial and error to fine-tune segmentation analysis and target control to check the results, resulting in a large error between the OPC menu processing method and the actual layout contour.

[0005] To achieve the above and other related objectives, the present invention provides a method for optical proximity effect correction, comprising:

[0006] Step 1: Obtain the target image to be corrected for optical proximity effect and the first menu parameters. The first menu parameters are used to control the simulated contour of the target image after correction. The area difference of the simulated contour outside the target image is defined as the cost function.

[0007] Step 2: Form a continuous line segment that fits the outline edge of the target graphic, set the marker point on the line segment, and then use the algorithm to generate multiple sets of marker points at different positions to obtain the cost function corresponding to each set of marker points;

[0008] Step 3: Select the marker point and the line segment with the smallest value among multiple cost functions, and obtain the second menu parameters based on them;

[0009] Step 4: Perform optical proximity effect correction on the target image according to the parameters in the second menu.

[0010] Preferably, the target graphic in step one is rectangular in shape.

[0011] Preferably, the line segment in step two coincides with the outline of the target graphic.

[0012] Preferably, the target graphic in step one has an irregular polygonal shape.

[0013] Preferably, the line segment in step two coincides with the outline of the target graphic.

[0014] Preferably, the algorithm in step two is a gene algorithm.

[0015] Preferably, in step two, the algorithm is used to form the first menu parameters of multiple generations and multiple families.

[0016] Preferably, the algorithm in step two forms 40 generations and 30 families of the first menu parameters.

[0017] As described above, the optical proximity effect correction method of the present invention has the following beneficial effects:

[0018] This invention uses a "genetic algorithm" to optimize the menu parameters of the optical proximity effect, making the corrected graphic contour smoother and more consistent with the target graphic. Attached Figure Description

[0019] Figure 1 The diagram shown is a schematic representation of the method of the present invention.

[0020] Figure 2 The diagram shown is a schematic representation of a rectangular graphic line segment according to the present invention.

[0021] Figure 3 This is a schematic diagram illustrating another example of a rectangular graphic line segment implementation of the present invention;

[0022] Figure 4 The diagram shown is a schematic diagram of the correction of an irregular shape according to the present invention;

[0023] Figure 5 The diagram shown is a correction schematic for another irregular shape according to the present invention. Detailed Implementation

[0024] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention.

[0025] Please see Figure 1 The present invention provides a method for optical proximity effect correction, comprising:

[0026] Step 1: Obtain the target pattern and the first menu parameters that need optical proximity correction. The target pattern is the provided layout. When the pattern is transferred to the substrate by photolithography, the pattern exposed by factors such as the light source will have an error with the target pattern. Therefore, it is necessary to correct the menu parameters by optical proximity correction to reduce the error between the corrected pattern and the target pattern. The first menu parameters are used to control the simulated contour of the target pattern after correction. The area difference of the simulated contour outside the target pattern is defined as the cost function. The larger the value of the cost function, the larger the error between the simulated contour and the target pattern. Conversely, the smaller the cost function, the smaller the error between the simulated contour and the target pattern.

[0027] In one alternative implementation, please refer to Figure 2 and Figure 3 In step one, the target graphic is a rectangle.

[0028] In one alternative implementation, please refer to Figure 4 and Figure 5 In step one, the target graphic is an irregular polygon.

[0029] It should be understood that the target graphic may also be more complex, including combinations of rectangles and irregular polygons.

[0030] Step two: Form continuous line segments that fit the outline edge of the target graphic. The length and tilt angle of the line segments are set by menu parameters. Multiple continuous line segments are used to simulate the outline of the graphic. Then, mark points are set on the line segments. The mark points are used to calculate the convergence at the mark point. The convergence is determined by the closest distance between the mark point and the edge of the graphic outline. That is, the closer the mark point is to the edge of the graphic outline, the smaller the convergence, and vice versa. Then, the algorithm is used to generate multiple sets of mark points at different positions to obtain the cost function corresponding to each set of mark points.

[0031] In one optional implementation, the target graphic in step one is rectangular, and the line segments in step two coincide with the outline of the target graphic.

[0032] In one optional implementation, the target graphic in step one is an irregular polygon, and in step two, the line segments coincide with the outline of the target graphic.

[0033] The length of the line segment is preset in the menu, and the length of the line segment can be adjusted according to the parameters in the menu.

[0034] In an alternative implementation, the algorithm in step two is a genetic algorithm (GA), a heuristic optimization method that operates through undetermined random search. The set of possible solutions to the optimization problem is considered as a population of individuals. An individual's fitness to its environment is represented by its fitness. An individual's reference point in the search space is represented by a chromosome (actually a set of strings). A gene is a segment of a chromosome, encoding a single parameter to be optimized. A typical encoding for a gene can be binary or integer. By simulating the recombination, mutation, and selection processes of evolution, a new generation of search points is found whose average fitness is better than that of their ancestors.

[0035] In an alternative implementation, the algorithm in step two can also be optimized for menu parameters through deep learning or other methods.

[0036] In one alternative implementation, step two utilizes an algorithm to form the first menu parameters for multiple generations and multiple families.

[0037] In one alternative implementation, due to factors such as computational complexity, the algorithm in step two generates 40 generations and 30 families of first menu parameters.

[0038] Step 3: Select the marker point and line segment with the smallest value from multiple cost functions, and obtain the second menu parameters based on them. The second menu parameters are the optimal solution among the multiple sets of data obtained.

[0039] Step four: Perform optical proximity effect correction on the target graphic according to the second menu parameters. The second menu parameters include the optimized parameters of the marker points, which can make the corrected graphic contour smoother.

[0040] In one alternative implementation, please refer to Figure 4 and Figure 5 The larger contour in the outer circle is the simulated contour of the existing technology, while the smaller contour in the inner circle is the simulated contour obtained by using the second menu parameters, which is more closely aligned with the target graphic.

[0041] It should be noted that the illustrations provided in this embodiment are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0042] In summary, this invention applies a "genetic algorithm" to optimize the menu parameters of the optical proximity effect, resulting in a smoother, more closely matching, corrected graphic contour. Therefore, this invention effectively overcomes the various shortcomings of existing technologies and possesses high industrial applicability.

[0043] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A method of optical proximity correction, characterized in that, At least comprising: Step one, obtaining a target pattern requiring optical proximity correction and a first menu parameter, the first menu parameter is used to control the simulated profile of the target pattern after correction, the area difference between the simulated profile and the target pattern is defined as a cost function; Step two, forming a line segment that fits and is continuous with the contour edge of the target pattern, setting the marker points on the line segment, then using genetic algorithm to generate different groups of marker points and / or line segment parameter combinations by changing the position of the marker points and / or the parameters of the line segment, and obtaining the cost function corresponding to each group of combinations; Step three, selecting the group of marker points and the parameters of the line segment corresponding to the minimum value of the cost function from the multiple groups, and obtaining a second menu parameter based on the selected marker points and the parameters of the line segment; Step four, performing optical proximity correction on the target pattern according to the second menu parameter.

2. The method of optical proximity correction according to claim 1, wherein: The shape of the target pattern in step one is a rectangle.

3. The method of optical proximity correction according to claim 2, wherein: The line segment in step two coincides with the contour of the target pattern.

4. The method of optical proximity correction according to claim 1, wherein: The shape of the target pattern in step one is an irregular polygon.

5. The method of optical proximity correction according to claim 4, wherein: The line segment in step two partially coincides with the contour of the target pattern.

6. The method of optical proximity correction according to claim 5, wherein: In step two, the algorithm is used to form multiple generations and multiple families of the first menu parameter.

7. The method of optical proximity correction according to claim 6, wherein: In step two, the algorithm forms 40 generations and 30 families of the first menu parameter.

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