KR102009168B1 - Optical proximity correction modeling method and system - Google Patents

Optical proximity correction modeling method and system Download PDF

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KR102009168B1
KR102009168B1 KR1020120128939A KR20120128939A KR102009168B1 KR 102009168 B1 KR102009168 B1 KR 102009168B1 KR 1020120128939 A KR1020120128939 A KR 1020120128939A KR 20120128939 A KR20120128939 A KR 20120128939A KR 102009168 B1 KR102009168 B1 KR 102009168B1
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material pattern
region
edge function
generating
filter
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KR1020120128939A
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Korean (ko)
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KR20140030007A (en
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정문규
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삼성전자 주식회사
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    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
    • H01L21/00—Processes or apparatus adapted for the manufacture or treatment of semiconductor or solid state devices or of parts thereof
    • H01L21/02—Manufacture or treatment of semiconductor devices or of parts thereof
    • H01L21/027—Making masks on semiconductor bodies for further photolithographic processing not provided for in group H01L21/18 or H01L21/34
    • H01L21/0271—Making masks on semiconductor bodies for further photolithographic processing not provided for in group H01L21/18 or H01L21/34 comprising organic layers
    • H01L21/0273—Making masks on semiconductor bodies for further photolithographic processing not provided for in group H01L21/18 or H01L21/34 comprising organic layers characterised by the treatment of photoresist layers
    • H01L21/0274—Photolithographic processes
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
    • G03F1/00—Originals for photomechanical production of textured or patterned surfaces, e.g., masks, photo-masks, reticles; Mask blanks or pellicles therefor; Containers specially adapted therefor; Preparation thereof
    • G03F1/36—Masks having proximity correction features; Preparation thereof, e.g. optical proximity correction [OPC] design processes
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
    • G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
    • G03F7/20—Exposure; Apparatus therefor
    • G03F7/2002—Exposure; Apparatus therefor with visible light or UV light, through an original having an opaque pattern on a transparent support, e.g. film printing, projection printing; by reflection of visible or UV light from an original such as a printed image
    • G03F7/2014—Contact or film exposure of light sensitive plates such as lithographic plates or circuit boards, e.g. in a vacuum frame
    • G03F7/2016—Contact mask being integral part of the photosensitive element and subject to destructive removal during post-exposure processing

Abstract

Optical proximity correction modeling methods and systems are provided. The optical proximity compensation modeling method includes a topography effect by a pattern stack structure including a first material pattern, a second material pattern, and a boundary region between the first material pattern and the second material pattern. In the optical proximity correction modeling method that can predict), the first region filter corresponding to the first material pattern, the second region filter corresponding to the second material pattern, and the edge function corresponding to the boundary region edge function), a bulk image signal generated from a layout using the first region filter and the second region filter, and a feature kernel reflecting characteristics of the edge function and the edge region, the first region filter. And generating an edge image signal from the layout using the second area filter, and using the bulk image signal and the edge image signal. , It includes generating a final signal model.

Description

Optical proximity correction modeling method and system

The present invention relates to a method and system for optical proximity correction modeling.

In the design of integrated circuits, the layout of the circuit is fabricated to form the desired circuit on the semiconductor substrate, and the layout can be transferred to the wafer surface through a photomask. As semiconductor devices become highly integrated and complex integrated circuit designs are required, it is very important to accurately implement the pattern layout according to the originally intended design on the photomask required for the photolithography process.

While the wavelength of the light source used in the exposure equipment is close to the feature size of the semiconductor device, the distortion of the pattern may appear due to diffraction, interference, or the like of light. As a result, an optical proximity effect occurs in which an image having a shape different from the original shape is formed on the wafer, or distortion of the pattern shape due to the influence of the adjacent pattern. In order to prevent problems such as dimensional fluctuations due to the optical proximity effect, light for predicting dimensional fluctuations during pattern transfer in advance and deforming the design pattern in advance so that a pattern shape according to a desired layout can be obtained after pattern transfer. Proximity correction (hereinafter referred to as OPC) process is performed.

An object of the present invention is to provide an OPC modeling method capable of predicting a topography effect due to a pattern stack structure.

Another object of the present invention is to provide an optical proximity correction modeling system capable of predicting a topography effect by a pattern stack structure.

Problems to be solved by the present invention are not limited to the above-mentioned problems, and other problems not mentioned will be clearly understood by those skilled in the art from the following description.

An aspect of the optical proximity compensation modeling method of the present invention for solving the above problems is a pattern stack including a first material pattern, a second material pattern and a boundary region between the first material pattern and the second material pattern. An optical proximity correction modeling method capable of predicting a topography effect due to a pattern stack structure, the method comprising: a first region filter corresponding to the first material pattern and a second corresponding to the second material pattern Generating a two-region filter and an edge function corresponding to the boundary region, and generating a bulk image signal from a layout using the first region filter and the second region filter, and generating the bulk image signal from the layout. An edge image signal is generated from the layout by using a feature kernel, the first region filter, and the second region filter reflecting characteristics of a boundary region, and the bulk image is generated. Using the image signal and the image edge signal, it includes generating a final signal model.

The edge function may be formed by opening a boundary between the first material pattern and the second material pattern in a slit form.

The generating of the edge image signal may include generating a weighted edge function from a layout by using the edge function, reflecting a characteristic of the first material pattern side among the boundary regions, and a first region filter. The first partial edge function is generated from the weighted edge function and a second characteristic kernel reflecting the characteristics of the second material pattern side of the boundary region is obtained, and the weighted edge function is applied using a second region filter. Generating a second partial edge function from the edge function.

Generating the weighted edge function may generate a weighted edge function by multiplying the reflected image of the layout with the edge function.

The reflection image may be a layout image based on air.

Generating the first partial edge function includes first convolving the weighted edge function and the first characteristic kernel and multiplying the result of the first convolution by the first region filter, wherein the first Generating a two-part edge function may include second convolving the weighted edge function and the second characteristic kernel and multiplying the result of the second convolution by the second region filter.

Each of the feature kernels may be a linear combination of unit kernel sets with weights evenly distributed from the center to the outside.

The unit kernel set may be a Bessel set.

The generating of the bulk image signal may include multiplying a first aerial image of the layout by the first area filter to generate a first partial aerial image, and generating a second aerial image and the second area of the layout. The second partial aerial image may be generated by multiplying a filter, and the bulk image signal may be generated by adding the first partial aerial image and the second partial aerial image.

The first aerial image is a layout image based on a planar stack structure of the first material, and the second aerial image is a layout image based on a planar stack structure of the second material. Can be.

Generating the final model signal may include multiplying and adding each of the bulk image signal and the edge image signal.

Another aspect of the optical proximity compensation modeling method of the present invention for solving the above problems is a pattern stack structure including a first material pattern, a second material pattern and a boundary region between the first material pattern and the second material pattern In the optical proximity correction modeling method that can predict the topography effect (stack structure) by the stack structure, the first region filter corresponding to the first material pattern and the second region filter corresponding to the second material pattern And generating an edge function corresponding to the boundary region, generating an edge function weighted from a layout using the edge function, and reflecting characteristics of the first material pattern side of the boundary region. A first partial edge function is generated from the weighted edge function using a first characteristic kernel and a first region filter, and the characteristic of the second material pattern side of the boundary region is generated. And generating a second partial edge function from the weighted edge function by using the second characteristic kernel reflecting the second characteristic filter and the second region filter.

Generating the weighted edge function may generate a weighted edge function by multiplying the reflected image of the layout with the edge function.

The reflection image may be a layout image based on air.

Generating the first partial edge function includes first convolving the weighted edge function and the first characteristic kernel and multiplying the result of the first convolution by the first region filter, wherein the first Generating a two-part edge function may include second convolving the weighted edge function and the second characteristic kernel and multiplying the result of the second convolution by the second region filter.

Each of the feature kernels may be a linear combination of unit kernel sets with weights evenly distributed from the center to the outside.

The unit kernel set may be a Bessel set.

Another aspect of the optical proximity compensation modeling method of the present invention for solving the above problems is a pattern stack structure including a first material pattern, a second material pattern and a boundary region between the first material pattern and the second material pattern ( In the optical proximity correction modeling method which can predict the topography effect by the pattern stack structure, the final model signal

Figure 112012093690600-pat00001
Is determined by the formula

Figure 112012093690600-pat00002

Figure 112012093690600-pat00003
Is the coefficient of each term,
Figure 112012093690600-pat00004
Is a first aerial image based on a planar stack structure of the first material,
Figure 112012093690600-pat00005
Is a first region filter corresponding to the first material pattern,
Figure 112012093690600-pat00006
Is a second aerial image based on the planar stack structure of the second material,
Figure 112012093690600-pat00007
Is a second region filter corresponding to the second material pattern,
Figure 112012093690600-pat00008
Is an edge function corresponding to the boundary region,
Figure 112012093690600-pat00009
Is an layout image based on air,
Figure 112012093690600-pat00010
Is a first characteristic kernel reflecting the characteristic of the first material pattern side of the boundary region,
Figure 112012093690600-pat00011
May be a second characteristic kernel reflecting characteristics of the second material pattern side of the boundary region.

One surface of the optical proximity compensation modeling system of the present invention for solving the other problem is a pattern stack structure including a first material pattern, a second material pattern and a boundary region of the first material pattern and the second material pattern ( A light proximity correction modeling system capable of predicting a topography effect due to a pattern stack structure, comprising: a first region filter corresponding to the first material pattern and a second region corresponding to the second material pattern A filter generator for generating a filter; An edge function generator for generating an edge function corresponding to the boundary area; A bulk image generation unit generating a bulk image signal from a layout by using the first region filter and the second region filter; An edge image generator configured to generate an edge image signal from the layout by using the edge function, a feature kernel reflecting characteristics of the boundary region, the first region filter, and the second region filter; And a final model generator configured to generate a final model signal by using the bulk image signal and the edge image signal.

Other specific details of the invention are included in the detailed description and drawings.

1 is a plan view for explaining a pattern stack structure and a mask.
2A and 2B are cross-sectional views taken along the line YY of FIG. 1.
3 is a flowchart illustrating an OPC modeling method according to some embodiments of the present invention.
4 is a flowchart for explaining S320 (bulk image signal generation step) of FIG. 3.
FIG. 5 is a flowchart for explaining S330 (edge image signal generation step) of FIG. 3.
6 to 8 are diagrams for explaining a first region filter, a second region filter, and an edge function, respectively.
9 is a conceptual diagram for explaining FIG. 4.
10 and 11 are diagrams for describing S321 (first aerial image generation step) and S325 (second aerial image generation step) of FIG. 4.
FIG. 12 is a diagram for explaining S331 (weighted edge function generation step) of FIG. 5.
FIG. 13 is a conceptual diagram for describing FIG. 5.
14 and 15 are conceptual diagrams for describing light affecting each material pattern.
16A to 16E are diagrams for describing a unit kernel set.
FIG. 17 is a conceptual diagram for explaining S340 (final model signal generation step) of FIG. 3.
18 is a block diagram illustrating an OPC modeling system according to some embodiments of the present invention.

Advantages and features of the present invention and methods for achieving them will be apparent with reference to the embodiments described below in detail with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but may be implemented in various forms. It is provided to fully convey the scope of the invention to those skilled in the art, and the present invention is defined only by the scope of the claims. Like reference numerals refer to like elements throughout.

When an element is referred to as being "connected to" or "coupled to" with another element, it may be directly connected to or coupled with another element or through another element in between. This includes all cases. On the other hand, when one device is referred to as "directly connected to" or "directly coupled to" with another device indicates that no other device is intervened. Like reference numerals refer to like elements throughout. “And / or” includes each and all combinations of one or more of the items mentioned.

Although the first, second, etc. are used to describe various elements, components and / or sections, these elements, components and / or sections are of course not limited by these terms. These terms are only used to distinguish one element, component or section from another element, component or section. Therefore, the first device, the first component, or the first section mentioned below may be a second device, a second component, or a second section within the technical spirit of the present invention.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. In this specification, the singular also includes the plural unless specifically stated otherwise in the phrase. As used herein, “comprises” and / or “comprising” refers to the presence of one or more other components, steps, operations and / or elements. Or does not exclude additions.

Unless otherwise defined, all terms (including technical and scientific terms) used in the present specification may be used in a sense that can be commonly understood by those skilled in the art. In addition, the terms defined in the commonly used dictionaries are not ideally or excessively interpreted unless they are specifically defined clearly.

1 is a plan view illustrating a pattern stack structure and a mask, and FIGS. 2A and 2B are cross-sectional views taken along the line Y-Y of FIG. 1.

1, 2A, and 2B, pattern stack structures 10 and 20 are formed on a substrate. Here, the pattern stack structures 10 and 20 mean that the structure formed under the mask 30 includes two or more materials. On the other hand, a planar stack structure means that the structure formed under the mask 30 includes only one material. As shown in FIG. 1, the pattern stack structures 10 and 20 may include, for example, a first material pattern 10 and a second material pattern 20. The first material pattern 10 may be formed long in one direction (eg, in a horizontal direction), and the second material pattern 20 may be formed to surround the first material pattern 10. Cutting along the Y-Y of FIG. 1, the cross-sectional view may be, for example, the same as FIG. 2A or 2B. As illustrated in FIG. 2A, an upper surface of the first material pattern 10 and an upper surface of the second material pattern 20 may be connected to each other flatly. Alternatively, as shown in FIG. 2B, the second material pattern 20 may be formed on the first material pattern 10.

In FIG. 1, the pattern stack structures 10 and 20 are illustrated to include only two material patterns, but are not limited thereto. For example, it may include three or more material patterns.

On the other hand, the structure formed under the mask 30 may have an effect when forming the mask. This effect is referred to herein as a "topography effect." The shape of the mask 30 may vary depending on what stack structure is formed under the mask 30.

Hereinafter, an OPC modeling method capable of predicting the topography effect of the pattern stack structures 10 and 20 will be described. The OPC modeling method according to some embodiments of the present invention is divided into a boundary region and a bulk region and modeled independently. Here, the boundary region refers to a boundary between the first material pattern 10 and the second material pattern 20 and an adjacent region, and the bulk region refers to the first material pattern 10 and the second material pattern (distant from the boundary region). 20).

3 is a flowchart illustrating an OPC modeling method according to some embodiments of the present invention. 4 is a flowchart for explaining S320 (bulk image signal generation step) of FIG. 3. FIG. 5 is a flowchart for explaining S330 (edge image signal generation step) of FIG. 3. 6 to 8 are diagrams for explaining a first region filter, a second region filter, and an edge function, respectively. 9 is a conceptual diagram for explaining FIG. 4. 10 and 11 are diagrams for describing S321 (first aerial image generation step) and S325 (second aerial image generation step) of FIG. 4. FIG. 12 is a diagram for explaining S331 (weighted edge function generation step) of FIG. 5. FIG. 13 is a conceptual diagram for describing FIG. 5. 14 and 15 are conceptual diagrams for describing light affecting each material pattern. 16A to 16E are diagrams for describing a unit kernel set. FIG. 17 is a conceptual diagram for explaining S340 (final model signal generation step) of FIG. 3.

First, referring to FIG. 3, from the pattern stack structures 10 and 20, the first region filter corresponding to the first material pattern 10 (see 40 in FIG. 6) and the second material pattern 20 may correspond to the first material filter 10. A second region filter (see 50 of FIG. 7) and an edge function (see 60 of FIG. 8) corresponding to the boundary region 19 are generated (S310).

For example, the first region filter 40 may open a portion corresponding to the first material pattern 10 and may cover a portion corresponding to the second material pattern 20 (see reference numeral 41). ). For example, the second region filter 50 may open a portion corresponding to the second material pattern 20 and may cover a portion corresponding to the first material pattern 10 (see reference numeral 51). The edge function 60 may be formed by opening the boundary between the first material pattern 10 and the second material pattern 20 in the form of a slit 61.

Meanwhile, referring back to FIG. 3, a bulk image signal is generated (S320). Generating the bulk image signal will be described in detail with reference to FIG. 4.

First, a first aerial image (see 112 of FIG. 9) of the layout is generated (S321). Here, as shown in FIG. 10, the first aerial image 112 may be a layout image based on a planar stack structure of the first material 10. That is, the first aerial image 112 may be a layout image when the structure formed under the mask 30 includes only the first material 10. The reason for doing this is that the region distant from the boundary region may be assumed to be a planar stack structure.

By multiplying the first aerial image 112 and the first region filter 40, a first partial aerial image (see 45 of FIG. 9) is generated (S322).

A second aerial image (see 114 in FIG. 9) of the layout is generated (S325). Here, the second aerial image 114 may be a layout image based on the planar stack structure of the second material 20, as shown in FIG. 11. That is, the second aerial image 114 may be a layout image when the structure formed under the mask 30 includes only the second material 20. The reason for doing this is that the region distant from the boundary region may be assumed to be a planar stack structure.

The second partial image 114 is multiplied by the second region filter 50 to generate a second partial aerial image (see 55 of FIG. 9) (S326).

Subsequently, the first partial aerial image 45 and the second partial aerial image 55 are combined to complete the bulk image signal 130 (S328).

Meanwhile, referring back to FIG. 3, an edge image signal is generated (S330). Generating the edge image signal will be described in detail with reference to FIG. 5.

First, a weighted edge function is generated (S331). As illustrated in FIG. 12, the weighted edge function 120 may be generated by multiplying the edge function 60 and the reflection image 110 of the layout by each other.

Here, the reflection image 110 of the layout is what shows if the light portion (that is, the portion not covered by the mask 30) and the dark portion (ie, the portion hidden by the mask 30) of the layout is shown. Anything is possible.

For example, the reflection image 110 of the layout may be a layout image based on air. That is, the reflection image 110 of the layout may be a layout image when there is air under the mask 30, but is not limited thereto.

In another example, the reflection image 110 of the layout includes the first aerial image (see 112 in FIG. 9) (the layout image based on the planar stack structure of the first material) and the second aerial image (FIG. 9). 114) (the layout image based on the planar or stack structure of the second material). In this case, the first aerial image 112 may be used in the first partial edge function generation step S333, and the second aerial image 114 may be used in the second partial edge function generation step S336.

Meanwhile, in the OPC modeling method according to some embodiments of the present invention, the first partial edge function and the second partial edge function are separately calculated.

Next, a first characteristic kernel is generated (S332).

The first characteristic kernel (see 152 of FIG. 13) may reflect the characteristic of the first material pattern 10 side in the boundary region. That is, the first characteristic kernel 152 is a function obtained by reflecting only an element affecting the first material pattern 10 side in the boundary region. As shown in FIG. 14, light affecting the first material pattern 10 is, for example, light L1 reflected at the boundary between the first material pattern 10 and the second material pattern 20. And the light L2 refracted from the second material pattern 20 into the first material pattern 10 and incident. The first characteristic kernel 152 may reflect physical phenomena caused by various lights as described above.

For example, the first feature kernel 152 may be a linear combination of unit kernel sets with weights evenly distributed from the center to the outside. The linear combination may be as in Equation 1 below. The first characteristic kernel 152 expresses the physical behavior that may occur in the boundary region by approximating a linear system.

[Equation 1]

Figure 112012093690600-pat00012

Figure 112012093690600-pat00013
Means the first characteristic kernel,
Figure 112012093690600-pat00014
Denotes a unit kernel, and C i denotes a weight. Here, the unit kernel set may be a Bessel set, but is not limited thereto. E.g,
Figure 112012093690600-pat00015
(I = 1 to 5) may be in various forms, as shown in FIGS. 16A to 16E. C i can be determined together when optimizing other parameters of the OPC model based on the wafer measurement results.

Subsequently, a first partial edge function (see 162 of FIG. 13) is generated (S333).

In detail, the first partial edge function 162 may be generated from the weighted edge function 120 using the first characteristic kernel 152 and the first region filter 40. For example, a first convolution of the weighted edge function 120 and the first characteristic kernel 152 is performed, and the result of the first convolution is multiplied by the first region filter 40 to generate the first partial edge. Function 162 may be generated.

Next, a second characteristic kernel is generated (S335).

The second characteristic kernel (see 154 of FIG. 13) may reflect the characteristic of the second material pattern 20 in the boundary region. That is, the second characteristic kernel 154 is a function obtained by reflecting only an element affecting the second material pattern 20 side in the boundary region. As shown in FIG. 15, light affecting the second material pattern 20 is, for example, light L3 reflected at the boundary between the first material pattern 10 and the second material pattern 20. And the light L4 refracted from the first material pattern 10 into the second material pattern 20 and incident. The second characteristic kernel 154 may reflect physical phenomena caused by various lights as described above.

Similar to the first feature kernel 152, the second feature kernel 154 may be a linear combination of unit kernel sets with weights evenly distributed from the center to the outside.

Next, a second partial edge function (see 164 of FIG. 13) is generated (S336).

In detail, the second partial edge function 164 may be generated from the weighted edge function 120 using the second characteristic kernel 154 and the second region filter 50. For example, the second partial convolution of the weighted edge function 120 and the second characteristic kernel 154 and multiplying the result of the second convolution by the second area filter 50 results in the second partial edge function 164. ) Can be created.

Referring to FIG. 4 again, the final model signal 190 is generated using the bulk image signal 130 and the edge image signals 162 and 164 (S328).

Specifically, as shown in FIG. 17, the bulk image signal 130, the first edge image signal 162, and the second edge image signal 164 are each multiplied by the weights d0, d1, and d2 to add the final values. The model signal 190 may be generated.

Here, the OPC modeling method according to some embodiments of the present invention described with reference to FIGS. 1 to 17 are summarized as follows. That is, the final model signal

Figure 112012093690600-pat00016
May be determined by Equation 2 below.

[Equation 2]

Figure 112012093690600-pat00017

Figure 112012093690600-pat00018
May be a coefficient of each term. In FIG. 17, this may correspond to the weight d0, d1, and d2.

The two terms in front of Equation 2 mean generating a bulk image signal, and the two terms after Equation 2 mean generating an edge image signal.

In other words,

Figure 112012093690600-pat00019
Is a first aerial image based on a planar stack structure of the first material,
Figure 112012093690600-pat00020
Is a first region filter corresponding to the first material pattern,
Figure 112012093690600-pat00021
Is a second aerial image based on the planar stack structure of the second material,
Figure 112012093690600-pat00022
Is a second area filter corresponding to the second material pattern.

Also,

Figure 112012093690600-pat00023
Is an edge function corresponding to the boundary region,
Figure 112012093690600-pat00024
Is an layout image based on air,
Figure 112012093690600-pat00025
Is a first characteristic kernel reflecting the characteristic of the first material pattern side of the boundary region,
Figure 112012093690600-pat00026
May be a second characteristic kernel reflecting characteristics of the second material pattern side of the boundary region.

18 is a block diagram illustrating an OPC modeling system according to some embodiments of the present invention. The OPC modeling system of FIG. 18 is a system for implementing the OPC modeling method described with reference to FIGS. 1 to 17. For convenience of explanation, the parts described with reference to FIGS. 1 to 17 will be omitted.

Referring to FIG. 18, an OPC modeling system 1 according to some embodiments of the present disclosure may include a pattern stack structure including a first material pattern, a second material pattern, and a boundary region between the first material pattern and the second material pattern. A topography effect due to a pattern stack structure can be predicted. The OPC modeling system 1 may include a filter generator 410, an edge function generator 420, a bulk image generator 430, an edge image generator 440, a final model generator 450, and the like. Can be.

The filter generator 410 may generate a first region filter 40 corresponding to the first material pattern 10 and a second region filter 50 corresponding to the second material pattern 20.

The edge function generator 420 may generate the edge function 60 corresponding to the boundary area.

The bulk image generator 430 may generate a bulk image signal from the layout by using the first region filter 40 and the second region filter 50.

The edge image generator 440 may generate an edge image signal from the layout by using the edge function 60, the feature kernel reflecting the characteristics of the boundary region, the first region filter 40, and the second region filter 50. Can be.

The final model generator 450 may generate the final model signal by using the bulk image signal and the edge image signal.

Although embodiments of the present invention have been described above with reference to the accompanying drawings, those skilled in the art to which the present invention pertains may implement the present invention in other specific forms without changing the technical spirit or essential features thereof. I can understand that. Therefore, it should be understood that the embodiments described above are exemplary in all respects and not restrictive.

S310: Step of generating area filter and edge function
S320: Bulk Image Creation Steps
S321: first aerial image generation step
S322: generating a first partial aerial image
S325: second aerial image generation step
S326: second partial aerial image generation step
S328: bulk image signal completion step
S330: Edge Image Generation Step
S331: Weighted Edge Function Generation Step
S332: generating the first characteristic kernel
S333: generating a first partial edge function
S335: generating the second characteristic kernel
S336: generating a second partial edge function
S340: generating the final model signal

Claims (10)

Optical proximity capable of predicting a topography effect due to a pattern stack structure including a first material pattern, a second material pattern, and a boundary region between the first material pattern and the second material pattern In the correction modeling method,
Generating a first region filter corresponding to the first material pattern, a second region filter corresponding to the second material pattern, and an edge function corresponding to the boundary region,
Generating a bulk image signal from a layout using the first region filter and the second region filter,
Generating an edge image signal from the layout by using the edge function, a characteristic kernel reflecting characteristics of the boundary region, the first region filter, and the second region filter,
And generating a final model signal using the bulk image signal and the edge image signal. The method of claim 1,
The edge function is an optical proximity correction modeling method of opening a boundary between the first material pattern and the second material pattern in a slit form. The method of claim 1, wherein generating the edge image signal,
Using the edge function, generate a weighted edge function from the layout,
Generating a first partial edge function from the weighted edge function using a first characteristic kernel reflecting the characteristic of the first material pattern side of the boundary region and a first region filter,
And generating a second partial edge function from the weighted edge function using a second characteristic kernel reflecting the characteristic of the second material pattern side of the boundary region and a second region filter. . The method of claim 3, wherein generating the weighted edge function,
And a reflection image of the layout and the edge function to generate a weighted edge function. The method of claim 3, wherein
Generating the first partial edge function comprises first convolving the weighted edge function and the first characteristic kernel, and multiplying the result of the first convolution by the first region filter,
Generating the second partial edge function includes convolution of the weighted edge function with the second characteristic kernel and multiplying the result of the second convolution by the second region filter. Modeling method. The method of claim 3, wherein
Wherein each characteristic kernel is a linear combination of unit kernel sets. The method of claim 1, wherein generating the bulk image signal comprises:
Multiplying the first aerial image of the layout by the first region filter to generate a first partial aerial image,
Multiplying the second aerial image of the layout by the second area filter to generate a second partial aerial image;
And the first partial aerial image and the second partial aerial image to generate the bulk image signal. Optical proximity capable of predicting a topography effect due to a pattern stack structure including a first material pattern, a second material pattern, and a boundary region between the first material pattern and the second material pattern In the correction modeling method,
Generating a first region filter corresponding to the first material pattern, a second region filter corresponding to the second material pattern, and an edge function corresponding to the boundary region,
Using the edge function, generate a weighted edge function from the layout,
Generating a first partial edge function from the weighted edge function using a first characteristic kernel reflecting the characteristic of the first material pattern side of the boundary region and a first region filter,
And generating a second partial edge function from the weighted edge function using a second characteristic kernel reflecting the characteristic of the second material pattern side of the boundary region and a second region filter. . Optical proximity capable of predicting a topography effect due to a pattern stack structure including a first material pattern, a second material pattern, and a boundary region between the first material pattern and the second material pattern In the correction modeling method,
Final Model Signal
Figure 112012093690600-pat00027
Is determined by the formula
Figure 112012093690600-pat00028

Figure 112012093690600-pat00029
Is the coefficient of each term,
Figure 112012093690600-pat00030
Is a first aerial image based on a planar stack structure of the first material,
Figure 112012093690600-pat00031
Is a first region filter corresponding to the first material pattern,
Figure 112012093690600-pat00032
Is a second aerial image based on the planar stack structure of the second material,
Figure 112012093690600-pat00033
Is a second region filter corresponding to the second material pattern,
Figure 112012093690600-pat00034
Is an edge function corresponding to the boundary region,
Figure 112012093690600-pat00035
Is an layout image based on air,
Figure 112012093690600-pat00036
Is a first characteristic kernel reflecting the characteristic of the first material pattern side of the boundary region,
Figure 112012093690600-pat00037
Is a second characteristic kernel reflecting the characteristics of the second material pattern side of the boundary region. Optical proximity capable of predicting a topography effect due to a pattern stack structure including a first material pattern, a second material pattern, and a boundary region between the first material pattern and the second material pattern In a calibration modeling system,
A filter generator configured to generate a first region filter corresponding to the first material pattern and a second region filter corresponding to the second material pattern;
An edge function generator for generating an edge function corresponding to the boundary area;
A bulk image generation unit generating a bulk image signal from a layout by using the first region filter and the second region filter;
An edge image generator configured to generate an edge image signal from the layout by using the edge function, a feature kernel reflecting characteristics of the boundary region, the first region filter, and the second region filter; And
And a final model generator configured to generate a final model signal by using the bulk image signal and the edge image signal.
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