Operating method of electronic device for manufacture of semiconductor device

Abstract

A method of operating an electronic device for manufacturing a semiconductor device is disclosed. The method includes: receiving a layout image of the semiconductor device; generating an intermediate image by generating auxiliary features based on the main features of the layout image; evaluating process results by performing simulation based on the intermediate image; and correcting the intermediate image by correcting the shape of the main features and / or the shape of the auxiliary features based on the process results.

Description

Technical Field

[0001] Embodiments of the present disclosure described herein relate to a method of operating an electronic device, and more particularly, to a method of operating an electronic device for manufacturing a semiconductor device that can prevent defects without post-processing in optical proximity correction (OPC). Prior Art

[0002] Optical proximity correction (OPC) can correct in advance the situation where the shape of the generated mask pattern is different from the shape of the target mask pattern due to process characteristics or process errors during the lithography process. During optical proximity correction, the shape of the optical mask pattern to be used in the process can be corrected differently from the shape of the target mask pattern so that the shape of the generated mask pattern is consistent with the target mask pattern.

[0003] Various defects may occur during optical proximity correction. The defects that occur during optical proximity correction may render the optical mask obtained by optical proximity correction unusable. When the optical mask is unusable, the time and cost for optical proximity correction may not be recovered. Summary of the Invention

[0004] Embodiments of the present disclosure provide an apparatus and method capable of performing optical proximity correction that prevents the occurrence of defects.

[0005] According to an embodiment, a method of operating an electronic device for manufacturing a semiconductor device includes: receiving a layout image of the semiconductor device; generating an intermediate image by generating auxiliary features based on main features of the layout image; evaluating a process result by performing a simulation based on the intermediate image; and correcting the intermediate image by correcting the shape of the main features and / or the shape of the auxiliary features of the intermediate image based on the process result.

[0006] According to an embodiment, a method for operating an electronic device for manufacturing a semiconductor device: calculating a change in a target slope of a change in light intensity with respect to a photoresist image based on a simulation and evaluation result of a layout image including main features and auxiliary features, and a target slope of a change in light intensity at a boundary line of each of the main features; calculating a change in a target slope of a change in light intensity with respect to an optical image based on the change in the target slope of the change in light intensity with respect to the photoresist image; calculating a change in a target slope of a change in light intensity with respect to a mask image based on the change in the target slope of the change in light intensity with respect to the optical image; calculating a change in a target slope of a change in light intensity with respect to a curved shape image based on the change in the target slope of the change in light intensity with respect to the mask image; and calculating correction information for an intermediate image based on the change in the target slope of the change in light intensity with respect to the curved shape image.

[0007] According to an embodiment, a method for operating an electronic device for manufacturing a semiconductor device includes: receiving a layout image of the semiconductor device; generating an intermediate image by generating auxiliary features based on main features of the layout image; generating a curved shape image based on the intermediate image; generating a mask image by pixelating the curved shape image; generating an optical image by performing optical simulation on the mask image; generating a photoresist image by performing photoresist simulation on the optical image; calculating a slope of a change in light intensity at a boundary line of each of the main features; calculating a change in a target slope of a change in light intensity with respect to the photoresist image based on a target slope of a change in light intensity at a boundary line of each of the main features; calculating a change in a target slope of a change in light intensity with respect to the optical image based on the change in the target slope of the change in light intensity with respect to the photoresist image; calculating a change in a target slope of a change in light intensity with respect to the mask image based on the change in the target slope of the change in light intensity with respect to the optical image; calculating a change in a target slope of a change in light intensity with respect to the curved shape image based on the change in the target slope of the change in light intensity with respect to the mask image; and calculating correction information for the intermediate image based on the change in the target slope of the change in light intensity with respect to the curved shape image. Brief Description of the Drawings

[0008] The above and other objects and features of the present disclosure will become apparent by referring to the embodiments of the present disclosure described in detail with reference to the accompanying drawings. FIG. 1 is a block diagram showing an electronic device according to an embodiment of the present disclosure. FIG. 2 shows a method of operating an electronic device according to an embodiment of the present disclosure. FIG. 3 shows an example of an implementation of an optical proximity correction (OPC) module. FIG. 4 shows an example of a layout image. FIG. 5 shows an example of an intermediate image. FIG. 6 shows an example in which pixelation is performed. FIG. 7 shows an example in which pixelation is completed. FIG. 8 shows a change in a target slope of a change in light intensity with respect to a mask image in the shape of an image. FIG. 9 shows correction information for correcting an intermediate image in the shape of an image. FIG. 10A shows a first embodiment in which a curved shape image is defined. FIG. 10B shows an example in which an intermediate image is corrected based on the curved shape image defined as in FIG. 10A. FIG. 11A shows a second embodiment in which a curved shape image is defined. FIG. 11B shows an example in which an intermediate image is corrected based on the curved shape image defined as in FIG. 11A. FIG. 12 shows a third embodiment in which a curved shape image is defined. FIG. 13 shows a fourth embodiment in which a curved shape image is defined. Implementation

[0009] Hereinafter, embodiments of the present disclosure may be described in detail and clearly to the extent that those of ordinary skill in the art can easily implement the present disclosure. Hereinafter, the term "and / or" is interpreted to include any one of the items listed for the term or a combination of some of the listed items.

[0010] FIG. 1 is a block diagram showing an electronic device 100 according to an embodiment of the present disclosure. Referring to FIG. 1, the electronic device 100 may include a processor 110, a random access memory 120, a device driver 130, a storage device 140, a modem 150, and a user interface 160.

[0011] Processor 110 may include, for example, at least one general-purpose processor, such as a central processing unit (CPU) 111 or an application processor (AP) 112. Additionally, processor 110 may further include at least one dedicated processor, such as a neural processing unit (NPU) 113, a neuromorphic processor 114, or a graphics processing unit (GPU) 115. Processor 110 may include two or more processors of the same type.

[0012] At least one of the processors 110 may drive an optical proximity correction (OPC) module 200. For example, the OPC module 200 may be implemented in the form of instructions (or code) executed by at least one of the processors 110. In such a case, the at least one processor may load the instructions (or code) of the OPC module 200 onto the random access memory 120.

[0013] For another example, at least one (or at least another) of the processors 110 may be manufactured to implement the OPC module 200. For example, at least one processor may be a dedicated processor that implements the functions of the OPC module 200 in hardware.

[0014] The random access memory 120 may be used as the working memory of the processor 110 and may also be used as the main memory or system memory of the electronic device 100. The random access memory 120 may include: volatile memory, such as dynamic random access memory or static random access memory; or non-volatile memory, such as phase change random access memory, ferroelectric random access memory, magnetic random access memory, or resistive random access memory.

[0015] The device driver 130 may control the following peripheral devices according to the requests of the processor 110: a storage device 140, a modem 150, and a user interface 160. The storage device 140 may include: a fixed storage device, such as a hard disk drive or a solid state drive; or a removable storage device, such as an external hard disk drive, an external solid state drive, or a removable memory card.

[0016] The modem 150 can provide remote communication with an external device. The modem 150 can perform wired communication or wireless communication with the external device. The modem 150 can communicate with the external device based on at least one of various communication schemes such as Ethernet, wireless-fidelity (Wi-Fi), long term evolution (LTE), and the fifth generation (5G) mobile communication.

[0017] The user interface 160 can receive information from the user and can provide information to the user. The user interface 160 can include at least one user output interface (such as the display 161 or the speaker 162), and at least one user input interface (such as the mouse 163, the keyboard 164, or the touch input device 165).

[0018] The instructions (or codes) of the OPC module 200 can be received by the modem 150 and can be stored in the storage device 140. The instructions (or codes) of the OPC module 200 can be stored in a removable storage device, and the removable storage device can be connected to the electronic device 100. The instructions (or codes) of the OPC module 200 can be loaded from the storage device 140 and executed on the random access memory 120.

[0019] FIG. 2 shows an operation method of the electronic device 100 according to an embodiment of the present disclosure. In the embodiment, an example in which the OPC module 200 performs OPC is shown in FIG. 2. Referring to FIGS. 1 and 2, in operation S110, the electronic device 100 or the OPC module 200 can receive a layout image. For example, the layout image can include a target pattern to be formed on a semiconductor wafer, such as a semiconductor pattern, a conductor pattern, or an insulator pattern. The target pattern on the layout image can be referred to as a "main feature".

[0020] In operation S120, the electronic device 100 or the OPC module 200 can generate auxiliary features according to the layout image. The auxiliary features can be used to assist in the generation of the main features. Patterns may not be formed at positions on the semiconductor wafer corresponding to the auxiliary features. The electronic device 100 or the OPC module 200 can generate an intermediate image by adding the auxiliary features to the layout image. The intermediate image can be a shape image including the shape of the main feature and the shape of the auxiliary feature. The intermediate image can be a candidate to be used as a photomask.

[0021] In an embodiment, the implementation of the layout image is shown in FIG. 4, and an example of the intermediate image is shown in FIG. 5. Referring to FIG. 4, the layout image LI can be divided into multiple regions, and each of the multiple regions may include a main feature MF. The electronic device 100 or the OPC module 200 can perform OPC on each of the multiple regions.

[0022] Referring to FIG. 5, the intermediate image "p" can be divided into multiple regions, and each of the multiple regions may include a main feature MF and an auxiliary feature AF. The main feature MF may correspond to the target pattern. The auxiliary feature AF can be added in a curved shape surrounding the main feature MF.

[0023] Referring again to FIGS. 1, 2, and 3, in operation S130, the electronic device 100 or the OPC module 200 can evaluate the process result. When using the intermediate image as a photomask to perform a semiconductor manufacturing process, the electronic device 100 or the OPC module 200 can calculate the process result by simulation.

[0024] In operation S140, the electronic device 100 or the OPC module 200 can determine whether the process result is acceptable. For example, when using the intermediate image as a photomask to perform a semiconductor manufacturing process, the electronic device 100 or the OPC module 200 can calculate the light intensity projected on the semiconductor wafer by simulation. The electronic device 100 or the OPC module 200 can determine whether the light intensity projected on the semiconductor wafer can produce a pattern similar to the target pattern.

[0025] When the process result is unacceptable, in operation S150, the electronic device 100 or the OPC module 200 can correct the main feature and / or the auxiliary feature of the intermediate image. For example, the electronic device 100 or the OPC module 200 can perform the evaluation process in reverse in operation S130 to calculate at least one adjustment information of the main feature and / or at least one adjustment information of the auxiliary feature. Then, the electronic device 100 or the OPC module 200 can perform operation S130 and operation S140 again.

[0026] When the process result is acceptable, in operation S160, the electronic device 100 or the OPC module 200 can confirm the OPC result image. For example, the electronic device 100 or the OPC module 200 can confirm the current intermediate image as the image of the photomask.

[0027] As described above, the electronic device 100 or the OPC module 200 according to the embodiments of the present disclosure can repeatedly perform simulation evaluation (e.g., the forward direction in operation S130) and correction of the intermediate image (e.g., the backward operation in operation S150), and can adjust the intermediate image as a photomask candidate.

[0028] The image correction of OPC can be performed in the pixelated state. Image pixelation can include reducing the resolution of the image to reduce computational complexity. When the pixelated image is fully corrected, post-processing for increasing the resolution may be required.

[0029] In the process of performing post-processing, the following consistency defects may occur: auxiliary features of different shapes are generated when the main features of the same shape are repeated. The following mask rule constraint (MRC) defects may occur in the process of performing post-processing: auxiliary features or main features that cannot be accepted in the semiconductor manufacturing process are generated.

[0030] OPC can be sequentially performed on multiple regions defined by dividing a semiconductor die. The post-processing for increasing the resolution can also be sequentially performed on the multiple regions. A specific main feature may overlap at least two or more regions. Boundary defects where the boundary of a part of a specific feature belonging to one region does not match the boundary of a part of a specific feature belonging to another region may occur in the process of performing post-processing.

[0031] According to an embodiment of the present disclosure, the electronic device 100 or the OPC module 200 can perform correction on the non-pixelated intermediate image. Therefore, various defects including the above-mentioned defects are prevented from occurring.

[0032] FIG. 3 shows an example of an implementation of the OPC module 200. Referring to FIGS. 1, 2, and 3, the OPC module 200 may include a forward unit 210 that performs a forward operation and a backward unit 220 that performs a backward operation. In the embodiment, the component that generates the intermediate image according to the layout image is not shown in FIG. 3.

[0033] The forward unit 210 can receive the intermediate image "p". The forward unit 210 can perform simulation and evaluation on the intermediate image "p" to generate a slope "q". For example, when the intermediate image "p" is used as a photomask, the slope "q" can indicate the slope of the change in the light intensity reaching the semiconductor wafer. For example, the slope "q" can indicate the slope of the change in the light intensity at the boundary of each of the main features.

[0034] When the slope “q” of the change in light intensity at the boundary of each of the main features increases, the difference between the light intensity projected onto the portion where photoresist should be generated and the light intensity projected onto the portion where photoresist should not be generated can increase. That is, as the slope “q” becomes larger, the generated photoresist pattern can become clearer and more precise, and thus, the process margin can be improved.

[0035] The backward unit 220 can receive a target slope (e.g., “1”). The backward unit 220 can perform the forward operation of the forward unit 210 in reverse based on the target slope (e.g., “1”), for example, can perform a backward operation. The backward unit 220 can perform a backward operation to calculate correction information ▽pq for correcting the intermediate image.

[0036] By repeatedly performing the forward operation of the forward unit 210, the backward operation of the backward unit 220, and the correction of the intermediate image, the electronic device 100 or the OPC module 200 can optimize the shape of the photomask and can increase the process margin.

[0037] The forward unit 210 can include a curved shape generator 211, a mask image generator 212, an optical simulation block 213, a photoresist simulation block 214, and a target evaluation block 215. The curved shape generator 211, the mask image generator 212, the optical simulation block 213, the photoresist simulation block 214, and / or the target evaluation block 215 can be implemented using hardware, software, or a combination of hardware and software.

[0038] The curved shape generator 211 can calculate a curved shape image Ω based on the intermediate image “p”. For example, depending on the implementation method, the curved shape generator 211 can use various methods to generate the curved shape image Ω.

[0039] The mask image generator 212 can pixelate the curved shape image Ω to generate a mask image “M”. An example of the process of performing pixelation is shown in FIG. 6. Referring to FIG. 6, the curved shape image Ω can be divided into multiple regions, and pixelation can be performed on the main features and auxiliary features of each of the multiple regions.

[0040] Each of the multiple regions of the curved shape image Ω can be divided into pixels PX. The pixels PX can have the same size. The resolution of the pixels PX can be lower than the resolution of the data of the layout image LI or the resolution of the data of the curved shape image Ω.

[0041] Each of the pixels PX may have a value between 0 and 1 (e.g., a normalized value). The mask image generator 212 may calculate the value of the pixel PX of the mask image "M" based on the following Equation 1. [Equation 1] []

[0042] In Equation 1, x' and x may represent positions on the pixels of the intermediate image and may indicate values on a two-dimensional coordinate system based on the pixel PX, respectively. may be a filtering function. When the mask image "M" is a thin (e.g., two-dimensional) mask, the filtering function may be an anti-aliasing filter. When the mask image "M" is a thick (e.g., three-dimensional) mask, the filtering function may be an edge filter or a coupling filter.

[0043] An example in which pixelization is completed is shown in FIG. 7. Referring to FIG. 7, the resolution of the mask image "M" generated after pixelization is completed may be reduced.

[0044] Referring again to FIGS. 1, 2, and 3, the optical simulation module 213 may perform an optical simulation based on the mask image "M" and may calculate the optical image "I" to be projected onto the semiconductor wafer. The photoresist simulation block 214 may perform a photoresist simulation based on the optical image "I" and may calculate the photoresist image "R" to be formed on the semiconductor wafer. The target evaluation module 215 may perform an evaluation based on the photoresist image "R" and may calculate the slope "q".

[0045] The backward unit 220 may include a first block 221, a second block 222, a third block 223, a fourth block 224, and a fifth block 225.

[0046] The first module 221 may calculate the Frechet derivative Q'* based on the target slope (e.g., "1") and the calculation of the target evaluation module 215 and may output the change in the target slope of the change in the light intensity with respect to the change in the photoresist image as the adjoint variable .

[0047] The second module 222 can calculate the Fréchet derivative R'* based on the change in the target slope of the change in the photoresist image due to the change in light intensity, and can output the change in the target slope of the change in light intensity with respect to the change in the optical image as the adjoint variable. and the calculation of the photoresist simulation module 214, and can output the change in the target slope of the change in light intensity with respect to the change in the optical image as the adjoint variable. .

[0048] The third block 223 can calculate the Fréchet derivative I'* based on the change in the target slope of the change in light intensity with respect to the change in the optical image, and can output the change in the target slope of the change in light intensity with respect to the change in the mask image as the adjoint variable. and the calculation of the optical simulation block 213, and can output the change in the target slope of the change in light intensity with respect to the change in the mask image as the adjoint variable. .

[0049] In an embodiment, the change in the mask image (e.g., the shape derivative of the mask image "M" ) can be derived from Equation 1 to Equation 2. [Equation 2]

[0050] In Equation 2, can represent the boundary line of the curved shape image Ω. can be the normal vector of each point (or pixel) belonging to the boundary line of the curved shape image Ω. can indicate the position movement of each point (or pixel) belonging to the boundary line of the curved shape image Ω. It can be understood from Equation 2 that the shape derivative of the mask image "M" can be calculated at the boundary line (or the pixels PX of the boundary line) of the curved shape image Ω.

[0051] The change in the target slope of light intensity (i.e., the target derivative ) can be defined by Equation 3 based on the chain rule. [Equation 3]

[0052] Equation 3 can be transformed into Equation 4 by changing the order of integration of Equation 3. [Equation 4]

[0053] Change in the target slope of the change in light intensity due to the change in the mask image It can be expressed using a shape similar to the image in FIG. 8. In FIG. 8, as the boundary line of the main feature or auxiliary feature gets closer to the bright part, the slope "q" of the change in light intensity can increase; as the boundary line of the main feature or auxiliary feature gets closer to the dark part, the slope "q" of the change in light intensity can decrease.

[0054] Referring again to FIGS. 1, 2, and 3, the fourth block 224 can calculate the Fréchet derivative (M'*) based on the change in the target slope of the change in light intensity due to the change in the mask image and the calculation of the mask image generator 212 and can output the change in the target slope of the change in light intensity due to the change in the curve-shaped image (e.g., can output the shape gradient) as the adjoint variable. The change in the target slope of the change in light intensity due to the change in the curve-shaped image ( . The change in the target slope of the change in light intensity due to the change in the curve-shaped image ( ) can be calculated by Equation 5. [Equation 5]

[0055] The fifth block 225 can calculate the Fréchet derivative x'* based on the change in the target slope of the change in light intensity due to the change in the curve-shaped image and the calculation of the curve-shaped image generator 211 and can output the correction information ▽ pq for correcting the intermediate image as the adjoint variable. The correction information ▽ pq for correcting the intermediate image can be calculated by Equation 6. [Equation 6]

[0056] The correction information ▽ pq for intermediate image correction can be expressed using a shape similar to the image in FIG. 9. In FIG. 9, the circular shape can indicate the points that define the curve-shaped image Ω. The lines extending from the circular shape indicate the correction positions of the points that define the curve-shaped image Ω.

[0057] The electronic device 100 or the OPC module 200 can correct the points defining the curve-shaped image Ω based on the correction information ▽ pq for correcting the intermediate image. The correction of the intermediate image can be calculated by Equation 7 based on gradient descent. [Equation 7]

[0058] In Equation 7, i can be a positive integer and can indicate the number of times of the forward operation including the forward unit 210, the backward operation of the backward unit 220, and the loop of correcting the intermediate image. can be a constant and can be determined randomly or based on process characteristics.

[0059] FIG. 10A shows a first embodiment in which the curve-shaped image Ω is defined. Referring to FIGS. 3 and 10A, the electronic device 100 or the OPC module 200 can set a first point P1 at the boundary line of the main feature of the intermediate image "p". The electronic device 100 or the OPC module 200 can parameterize the intermediate image "p" with the first point P1. The curve shape generator 211 can generate a curve inscribed in the boundary line connecting the first point P1 as the curve-shaped image Ω.

[0060] FIG. 10B shows an example in which the intermediate image "p" is corrected based on the curve-shaped image Ω defined as in FIG. 10A. Referring to FIGS. 3, 10A, and 10B, the electronic device 100 or the OPC module 200 can correct the positions of the first point P1 to the second point P2. The curve shape generator 211 can generate a curve inscribed in the boundary line connecting the second point P2 as the curve-shaped image Ω.

[0061] FIG. 11A shows a second embodiment in which the curve-shaped image Ω is defined. Referring to FIGS. 3 and 11A, the electronic device 100 or the OPC module 200 can set a third point P3 at the boundary line of the main feature of the intermediate image "p". The electronic device 100 or the OPC module 200 can parameterize the intermediate image "p" with the third point P3. The curve shape generator 211 can generate a curve connecting the third point P3 as the curve-shaped image Ω.

[0062] FIG. 11B shows an example in which the intermediate image "p" is corrected based on the curved shape image Ω defined as in FIG. 11A. Referring to FIGS. 3, 11A, and 11B, the electronic device 100 or the OPC module 200 can correct the positions of the third point P3 to the fourth point P4. The curved shape generator 211 can generate a curve connecting the fourth point P4 as the curved shape image Ω.

[0063] FIG. 12 shows a third embodiment in which the curved shape image Ω is defined. Referring to FIGS. 3 and 12, the electronic device 100 or the OPC module 200 can set a fifth point P5 from the boundary line of the main features of the intermediate image "p". The electronic device 100 or the OPC module 200 can parameterize the intermediate image "p" with respect to the fifth point P5. The curved shape generator 211 can generate the curved shape image Ω based on the fifth point P5 and the spline curve function.

[0064] As described with reference to FIGS. 10A, 10B, 11A, and 11B, the electronic device 100 or the OPC module 200 can correct the position of the fifth point P5. The curved shape generator 211 can generate the curved shape image Ω based on the fifth point P5 and the spline curve function.

[0065] FIG. 13 shows a fourth embodiment in which the curved shape image Ω is defined. Referring to FIGS. 3 and 13, the electronic device 100 or the OPC module 200 can set a sixth point (including P6_i and P6_j) at the center inside the boundary defined by the auxiliary features of the intermediate image "p". The electronic device 100 or the OPC module 200 can parameterize the intermediate image "p" with respect to the sixth point (including P6_i and P6_j).

[0066] The electronic device 100 and the OPC module 200 can mark width information (e.g., W_i relative to P6_i or W_j relative to P6_j) and at least one point identifier information (e.g., C_i1 and C_i2 relative to P6_i) on each of the sixth points. The at least one point identifier information can indicate at least one point that is closest to it and is connected to form a continuous auxiliary feature. The width information can include width information in the normal direction from each point to the boundary of the auxiliary feature. The curved shape generator 211 can generate the curved shape image Ω based on the width information and the point identifier information of the sixth point.

[0067] As described with reference to FIGS. 10A, 10B, 11A, and 11B, the electronic device 100 or the OPC module 200 can correct the position of the sixth point P6. In addition, the electronic device 100 or the OPC module 200 can correct the width information marked on the sixth point P6. The curve shape generator 211 can generate a curve shape image Ω based on the width information of the sixth point and the point identifier information.

[0068] In an embodiment, to optimize the intermediate image "p", the movement of the position of the sixth point P6 can be restricted to the normal direction.

[0069] According to an embodiment of the present disclosure, the photomask pattern is expressed in a curve shape, and the photomask pattern is corrected by directly correcting the curve shape. Therefore, since the correction of the curve shape is not performed in a pixelated state, various defects such as coherence defects, mask rule constraint (MRC) defects, and boundary defects can be prevented.

[0070] 1: Target slope 100: Electronic device 110: Processor 111: Central processing unit (CPU) 112: Application processor (AP) 113: Neural processing unit (NPU) 114: Neuromorphic processor 115: Graphics processing unit (GPU) 120: Random access memory 130: Device driver 140: Storage device 150: Modem 160: User interface 161: Display 162: Speaker 163: Mouse 164: Keyboard 165: Touch input device 200: Optical proximity correction (OPC) module 210: Forward unit 211: Curve shape generator 212: Mask image generator 213: Optical simulation block / optical simulation module 214: Photoresist simulation block / photoresist simulation module 215: Target Evaluation Block / Target Evaluation Module 220: Backward Unit 221: First Block 222: Second Block 223: Third Block 224: Fourth Block 225: Fifth Block C_i1, C_i2: Dot Identification Information I: Optical Image I'*, M'*, Q'*, R'*, x'*: Fréchet Derivative LI: Layout Image M: Mask Image MF: Main Feature p: Intermediate Image P1: First Point P2: Second Point P3: Third Point P4: Fourth Point P5: Fifth Point P6_i, P6_j: Sixth Point PX: Pixel q: Slope R: Photoresist Image S110, S120, S130, S140, S150, S160: Operations W_i, W_j: Width Information , , , : Change Ω: Curved Shape Image ▽ pq: Calibration Information

Claims

1. A method of operating an electronic device for manufacturing a semiconductor device, the method comprising: The process includes: receiving a layout image of the semiconductor device; generating an intermediate image by generating auxiliary features based on the main features of the layout image; evaluating a process result by performing a simulation based on the intermediate image; and correcting the intermediate image by correcting the shape of the main features and / or the shape of the auxiliary features based on the process result, wherein the correction of the intermediate image is performed inversely to the evaluation of the process result to generate correction information for the intermediate image, and wherein the intermediate image is corrected based on a target slope of the change in light intensity at the boundary of each of the main features obtained by evaluating the process result and the slope of the change in light intensity.

2. The method of operation as described in claim 1, wherein the evaluation and the correction are repeated until the corrected result of the intermediate image matches the layout image.

3. The operating method as described in claim 1, wherein the evaluation includes: A curved image is generated based on the intermediate image; a mask image is generated by pixelating the curved image; an optical image is generated by performing optical simulation on the mask image; a photoresist image is generated by performing photoresist simulation on the optical image; and the process result is evaluated based on the photoresist image.

4. The method of operation as described in claim 3, wherein generating the curved shape image includes: A curve is generated that is internally tangent to an outer line connecting a point to each of the main features, and serves as an element of the curve shape image corresponding to each of the main features.

5. The operation method as described in claim 4, wherein correcting the intermediate image includes: The position of at least one of the points is adjusted.

6. The operating method as described in claim 3 further includes: A curve is generated that connects the points of each of the main features as an element of the curve shape image corresponding to each of the main features.

7. The operation method as described in claim 6, wherein correcting the intermediate image includes: The position of at least one of the points is adjusted.

8. The method of operation as described in claim 3, wherein generating the curved shape image comprises: A curve is generated based on a spline curve function, using points of each of the principal features as the element of the curve shape image corresponding to each of the principal features.

9. The operation method as described in claim 8, wherein correcting the intermediate image includes: The position of at least one of the points is adjusted.

10. The method of operation as described in claim 3, wherein generating the curved shape image comprises: At each of the auxiliary features, points are connected based on at least one point identifier information marked at each point, and boundary lines based on the width information of each of the interconnected points are generated as elements of the curved shape image.

11. The method of operation as described in claim 10, wherein correcting the intermediate image includes: Adjust at least one of the position and width information of at least one of the points.

12. The method of operation as described in claim 1, wherein evaluating the process result includes: Calculate the slope of the change in light intensity at the boundary line of each of the main features.

13. The operation method as described in claim 1, wherein correcting the intermediate image includes: Based on the target slope of the change in light intensity at the boundary line of each of the main features, calculate the change in the target slope of the change in light intensity for the change in photoresistive image; based on the change in the target slope of the change in light intensity for the change in photoresistive image, calculate the change in the target slope of the change in light intensity for the change in optical image; based on the change in the target slope of the change in light intensity for the change in optical image, calculate the change in the target slope of the change in light intensity for the change in mask image; based on the change in the target slope of the change in light intensity for the change in mask image, calculate the change in the target slope of the change in light intensity for the change in curved shape image; and based on the change in the target slope of the change in light intensity for the change in curved shape image, calculate the correction information of the intermediate image.

14. The method of operation as described in claim 13, wherein the change in the target slope for the change of the photoresist image, the change in the target slope for the change of the optical image, the change in the target slope for the change of the mask image, the change in the target slope for the change of the curve shape image, and the correction information of the intermediate image are calculated based on the Fraser derivative.

15. A method of operating an electronic device for manufacturing a semiconductor device, the method comprising: Based on the simulation and evaluation results of the layout image including main features and auxiliary features, the change in the target slope of the change in light intensity due to the change in photoresistive image is calculated according to the target slope of the change in light intensity at the boundary line of each of the main features; the change in the target slope of the change in light intensity due to the change in photoresistive image is calculated according to the change in the target slope of the change in light intensity due to ...

16. The method of operation as claimed in claim 15, wherein the primary features each include a photomask pattern for manufacturing the semiconductor device, wherein the auxiliary features are used to assist in generating the primary features, and wherein each of the auxiliary features is represented by a point, a distance from each point to its nearest boundary line in the normal direction, and at least one point adjacent to each point.

17. The method of operation as described in claim 16, wherein the correction information includes a distance by which at least one of the points of at least one of the auxiliary features is moved in the normal direction.

18. The method of operation as described in claim 16, wherein the correction information includes a correction value for the distance from at least one point of at least one of the auxiliary features to the nearest boundary line in the normal direction.

19. A method of operating an electronic device for manufacturing a semiconductor device, the method comprising: The method includes: receiving a layout image of the semiconductor device; generating an intermediate image by generating auxiliary features based on the main features of the layout image; generating a curved shape image based on the intermediate image; generating a mask image by pixelating the curved shape image; generating an optical image by performing optical simulation on the mask image; generating a photoresist image by performing photoresist simulation on the optical image; calculating the slope of the change in light intensity at the boundary line of each of the main features; calculating the change in the target slope of the change in light intensity due to the change in the photoresist image based on the target slope of the change in light intensity at the boundary line of each of the main features; calculating the change in the target slope of the change in light intensity due to the change in the optical image based on the change in the target slope of the change in light intensity due to the change in the optical image; and calculating the change in the target slope of the change in light intensity due to the change in the mask image based on the change in the target slope of the change in light intensity due to the change in the optical image. The change in the target slope caused by the change in light intensity with respect to the curved image is calculated based on the change in the target slope caused by the change in light intensity with respect to the mask image; and the correction information for the intermediate image is calculated based on the change in the target slope caused by the change in light intensity with respect to the curved image.

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