A light source determination method, device, medium and product

Abstract

The application discloses a light source determination method, device, medium and product, and is applied to the field of photoetching technology. The method generates a plurality of target regions on a light source plane, and respectively performs imaging simulation on a target mask pattern under preset process conditions by using light sources of the target regions to obtain local target imaging performance indexes. Then, based on the local data, an overall imaging performance index is generated, and the final target light source is determined through the overall imaging performance index. The scheme determines the final target light source by acquiring the imaging performance index of the light source plane, so that the light source can be adjusted according to actual requirements in combination with the imaging performance index. The light source is determined by simulating the imaging performance index, more and more accurate information is obtained, the light source conforming to actual requirements can be accurately acquired, and therefore the production efficiency is improved. In addition, whether there is a conflict in mask pattern design can be judged through simulation, unnecessary debugging iteration is avoided, and the like.

Description

Technical Field

[0001] This application belongs to the field of photolithography technology, and in particular relates to a method, equipment, medium and product for determining a light source. Background Technology

[0002] Photolithography is the process of transferring a pattern from a photomask onto a wafer using a photolithography machine. Before actual photolithography, the initial light source needs to be determined. The initial light source has a certain impact on the light source optimization process; different initial light sources may lead to different optimization paths. Obtaining a better initial light source may improve the convergence efficiency of the optimization; in some cases, optimization may not be necessary, and a light source obtained solely through theoretical calculations can provide good imaging capabilities.

[0003] Traditional methods for determining the initial light source involve inputting data such as the light source wavelength, the numerical aperture of the lithography machine lens, and the repetition period of the mask pattern into an empirical formula. The energy center of the light source is then constructed, and the required light source is determined based on this energy center. However, this traditional method relies heavily on experience, while actual process conditions change constantly. Therefore, the light source obtained through this method may deviate from the actual required light source, leading to increased complexity in subsequent adjustments to the light source. Summary of the Invention

[0004] This application provides a method, device, medium, and product for determining a light source, which can accurately determine the required light source and improve production efficiency.

[0005] On one hand, embodiments of this application provide a method for determining a light source, including:

[0006] Acquire multiple target points on the light source plane;

[0007] Based on each of the target points, a corresponding target area is generated on the light source plane;

[0008] Using the light source of each target region, imaging simulation is performed on the target mask pattern under preset process conditions to obtain the corresponding target imaging performance index.

[0009] Based on the target imaging performance index and the corresponding position of the target region on the light source plane, an overall imaging performance index for the entire light source plane is generated to determine the target light source.

[0010] On the other hand, acquiring multiple target points on the light source plane includes:

[0011] The light source plane is divided into multiple cells;

[0012] Downsampling is performed in each of the cells to select multiple target cells;

[0013] The center point of each target cell is determined as the target point.

[0014] On the other hand, the downsampling in each of the cells, selecting multiple target cells, includes:

[0015] Each of the cells is sampled at equal intervals to obtain multiple cells to be determined.

[0016] Based on the undetermined cells, the target cell is determined.

[0017] On the other hand, the process of sampling each cell at equal intervals to obtain multiple cells to be determined includes:

[0018] Determine the sampling interval based on the constraints;

[0019] Based on the sampling interval, each of the cells is sampled at equal intervals to obtain a plurality of cells to be determined.

[0020] On the other hand, determining the target cell based on the undetermined cell includes:

[0021] Obtain the symmetry structure of the light source plane;

[0022] Based on the symmetrical structure, each of the cells to be determined is divided into multiple cell groups; each cell to be determined in the same cell group has the same imaging performance index.

[0023] Select one cell from each of the cell groups to be determined, and designate it as the target cell.

[0024] On the other hand, the process of using light sources in each of the target regions to perform imaging simulations on the target mask pattern under preset process conditions to obtain corresponding target imaging performance indicators includes:

[0025] Obtain the preset process conditions;

[0026] The preset process conditions, the target area, and the target mask pattern are input into the imaging simulation tool to obtain the target imaging performance indicators.

[0027] On the other hand, after generating the overall imaging performance index of the entire light source plane based on the target imaging performance index and the corresponding position of the target region on the light source plane, the method further includes:

[0028] Based on the values ​​of the overall imaging performance index, an imaging performance index image is drawn on the light source plane;

[0029] The image displays the imaging performance indicators.

[0030] In another aspect, embodiments of this application provide a light source determining device, including: a processor and a memory storing computer program instructions;

[0031] When the processor executes the computer program instructions, it implements the light source determination method described above.

[0032] In another aspect, embodiments of this application provide a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the light source determination method described above.

[0033] In another aspect, embodiments of this application provide a computer program product, wherein the instructions in the computer program product, when executed by the processor of an electronic device, cause the electronic device to perform the light source determination method as described above.

[0034] This application provides a method for determining a light source. Based on multiple target points on a light source plane, corresponding target regions are generated. Using the light sources in each target region, imaging simulations are performed on the target mask pattern under preset process conditions to obtain corresponding target imaging performance indicators. Then, based on the acquired data, an overall imaging performance indicator for the entire light source plane is generated; the final target light source is determined using this overall imaging performance indicator. This solution determines the final target light source by obtaining the imaging performance indicators of the light source plane, thus allowing for adjustments to the light source based on actual needs and the imaging performance indicators. Compared to the traditional method of simply relying on empirical formulas to roughly derive the light source, this application determines the light source by simulating imaging performance indicators. Based on more and more accurate information, a light source that accurately matches actual needs can be obtained, thereby improving production efficiency. Furthermore, simulation can also determine whether there are conflicts in the mask pattern design, avoiding unnecessary debugging and iteration. Attached Figure Description

[0035] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 A flowchart illustrating a light source determination method according to an embodiment of this application is shown;

[0037] Figure 2 An energy distribution diagram of a light source provided in an embodiment of this application is shown;

[0038] Figure 3This illustration shows a schematic diagram of a cell division method for a light source plane according to an embodiment of this application;

[0039] Figure 4 This invention provides a schematic diagram illustrating the symmetry of a light source plane arrangement according to an embodiment of the present application.

[0040] Figure 5 This is an image illustrating one of the imaging performance indicators in one embodiment of this application;

[0041] Figure 6 A normalized logarithmic slope distribution of vertical bars with a period of 100 nm is provided for an embodiment of this application;

[0042] Figure 7 A normalized logarithmic slope distribution of vertical bars with a period of 140 nm is provided for an embodiment of this application;

[0043] Figure 8 A normalized logarithmic slope distribution of vertical bars with a period of 220 nm is provided for an embodiment of this application;

[0044] Figure 9 A normalized logarithmic slope distribution of vertical bars with a period of 300 nm is provided for an embodiment of this application;

[0045] Figure 10 A schematic diagram of the structure of the light source determining device provided in an embodiment of this application is shown;

[0046] Figure 11 A schematic diagram of the hardware structure of the light source determination device provided in an embodiment of this application is shown. Detailed Implementation

[0047] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0048] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0049] Photolithography is the process of transferring a pattern from a photomask onto a wafer using a photolithography machine. The light sources used in photolithography have evolved through various forms, including on-axis illumination, off-axis illumination, and free-form pixelated illumination. This application primarily focuses on free-form pixelated illumination. Free-form light source optimization is based on a light source grid, requiring a pixel-based illumination system. The light source plane is divided into a two-dimensional grid, with each grid point corresponding to a computer-controlled reflector. An array of multiple reflectors reflects light to a fixed area, creating an arbitrary distribution of light intensity.

[0050] Joint optimization of light source and mask is a primary method for obtaining free-form light sources under specific model conditions and an important resolution enhancement technique for advanced semiconductor process nodes. After using an optimized light source, the depth of focus, mask error enhancement factor, and normalized slope logarithm of the image can all be improved. To obtain a suitable light source for the lithography process or an initial light source for joint optimization of light source and mask, traditional methods typically rely on empirical references or simplified formulas to perform approximate calculations to obtain a usable light source. For example, for dense line patterns, there is an empirical formula:

[0051] sigma_center = λ / (2*NA*P) (1)

[0052] Where λ is the wavelength of the light source, NA is the numerical aperture of the lithography lens, and P is the repetition period of the mask pattern. The calculated light source center, sigma_center, can determine the empirically suitable off-axis illumination source center point for this type of pattern imaging. However, calculations based on empirical formulas cannot account for the influence of actual process factors on the results, and the obtained light source may deviate from actual requirements. This leads to increased complexity in subsequent light source correction and an increased number of optimization and debugging steps.

[0053] To address the problems of traditional solutions, embodiments of this application provide a method, apparatus, medium, and product for determining a light source. The method for determining a light source provided in this application embodiment will be described first below. Figure 1 A schematic flowchart of a light source determination method provided in one embodiment of this application is shown.

[0054] like Figure 1 As shown, the method includes the following steps:

[0055] S101: Obtain multiple target points on the light source plane.

[0056] It should be noted that the specific number of target points selected here is not required. Selecting too many target points will increase the calculation time, while reducing the number of target points may reduce the calculation accuracy. Therefore, it can be determined according to the actual calculation time and the constraints of calculation accuracy.

[0057] Furthermore, the specific location of the target points on the light source plane is not limited. Generally, the selected target points are evenly distributed on the light source plane, so that the local target imaging performance indicators corresponding to the target points better reflect the overall imaging performance indicators of the entire light source plane. When specifically acquiring target points, the overall imaging performance indicators of the entire light source plane can be divided into multiple cells, then the target cell can be selected, and the center point of the target cell can be used as the target point. Alternatively, the center coordinates of the light source can be set to (0, 0), and a coordinate axis can be established. The length unit of the coordinate axis can be determined based on the width of the cell, facilitating the location of the center point of each cell.

[0058] S102: Based on each target point, generate the corresponding target area on the light source plane.

[0059] The above steps only take a coordinate point on the light source plane, but the light source needs a surface for illumination. Therefore, when generating the light source corresponding to the simulation, it is necessary to determine a surface for the selected target points in turn as the light source for illuminating the mask pattern.

[0060] The specific operation method is as follows: generate the poles (i.e., target areas) of the light source with the target point as the center; the shape of the poles can be specified in advance, usually circular, fan-shaped, elliptical, or leaf-shaped; these poles serve as the light source in the subsequent imaging simulation process, and the light intensity of the poles can be set to a uniform value, usually with the energy fill ratio meeting the production requirements as the minimum standard.

[0061] S103: Using the light sources of each target area, perform imaging simulation on the target mask pattern under preset process conditions to obtain the corresponding target imaging performance indicators.

[0062] In the above steps, multiple target areas have been identified. In this embodiment, during the imaging simulation process, it is necessary to generate a corresponding local light source for each target area, and the local light source corresponding to each target area needs to be simulated.

[0063] For one of the local light sources, imaging simulation of the target mask pattern needs to be performed under preset process conditions. This involves simulating the wafer pattern corresponding to the target mask pattern illuminated by this local light source, and then comparing the target mask pattern and the wafer pattern to obtain the target imaging performance indicators. Specific imaging performance indicators may include depth of focus, mask error enhancement factor, and normalized slope logarithm, etc.

[0064] As an optional implementation, preset process conditions may include focal length, exposure energy, mask offset, and measurement plane, etc.

[0065] In practical applications, the number of target mask patterns is not limited; one or more can be selected based on the actual situation. When multiple target mask patterns exist, an imaging simulation needs to be performed for each target mask pattern. Finally, the results corresponding to all target mask patterns are summarized and analyzed to obtain the target imaging performance indicators.

[0066] S104: Based on the target imaging performance index and the position of the corresponding target area on the light source plane, generate the overall imaging performance index of the entire light source plane to determine the target light source.

[0067] The above steps yield local target imaging performance indices for each target region. Based on the local information and corresponding locations, the overall imaging performance index of the entire light source plane can be derived. Finally, the final target light source needs to be determined based on the overall imaging performance index of the entire light source plane. As a feasible implementation method, the energy distribution area on the light source plane can be determined empirically based on the overall imaging performance index of the entire light source plane. Light sources (i.e., areas where light source energy exists) are placed in these suitable areas, while the energy intensity in other areas is zero, thus obtaining the final target light source.

[0068] As a feasible implementation, the light source plane can be divided into multiple cells, and the imaging performance index of the local cells can be obtained through the local target imaging performance index. Based on this, the imaging performance index of all cells can be derived, and then drawn onto the light source plane accordingly to generate the overall imaging performance index of the entire light source plane.

[0069] It can also display the drawn imaging performance index image, allowing users to intuitively understand the distribution of imaging performance index on the light source plane, and thus determine the final target light source based on the distribution.

[0070] In this embodiment, the light source plane is divided into multiple cells. When the target light source is finally determined, the specific energy intensity of each cell (with a value of 0 or 1) is determined, thereby obtaining the target light source. Figure 2 An energy distribution diagram of a light source provided in an embodiment of this application is shown; as follows: Figure 2 The image shows an example of a 201*201 cell light source distribution diagram. Inside the light source plane, black represents a cell with 0 energy, and white represents a cell with a normalized energy of 1. The center coordinates of the light source are (0, 0), and the coordinate axis scale is [-1, 1]. In this example, there are four local light source regions (regions where light source energy exists) in the light source plane, all of which are fan-shaped and symmetrical to each other.

[0071] To quickly and accurately obtain a suitable light source or an initial light source for joint optimization of light source and mask in photolithography, this application provides a method that, based on the partial coherence principle of photolithography light sources, analyzes the imaging performance (depth of focus, logarithm of normalized slope, and mask error enhancement factor, etc.) of a specific mask pattern based on the light source cell, thereby providing reference information for obtaining a suitable initial light source.

[0072] The proposed solution in this application can predict the gain effect (i.e., imaging performance index) of each point on the light source plane on the provided target mask pattern under specific process conditions, and can perform the following tasks accordingly: selection of illumination source under simple process, initial selection of light source for joint optimization of light source and mask, and determination of whether there is a situation where the provided mask samples cannot converge together; thereby improving the execution efficiency of process development and light source optimization.

[0073] Furthermore, in traditional approaches, when the joint optimization of the light source and mask is based on a large number of mask target patterns and there may be process conflicts, the current approach considers the possibility of such conflicts by evaluating the process simulation results after the optimization process. This means that it is impossible to scientifically and accurately assess the complexity of the light source and mask optimization caused by the number of mask samples before the light source optimization. This leads to the inability to determine whether the optimal solution has been converged after multiple rounds of optimization. This application, however, can determine whether there are conflicts in the mask design, avoiding unnecessary debugging and iterations.

[0074] This application provides a method for determining a light source. Based on multiple target points on a light source plane, corresponding target regions are generated. Using the light sources in each target region, imaging simulations are performed on the target mask pattern under preset process conditions to obtain corresponding target imaging performance indicators. Then, based on the acquired data, an overall imaging performance indicator for the entire light source plane is generated; the final target light source is determined using this overall imaging performance indicator. This solution determines the final target light source by obtaining the imaging performance indicators of the light source plane, thus allowing for adjustments to the light source based on actual needs and the imaging performance indicators. Compared to the traditional method of simply relying on empirical formulas to roughly derive the light source, this application determines the light source by simulating imaging performance indicators. Based on more and more accurate information, a light source that accurately matches actual needs can be obtained, thereby improving production efficiency. Furthermore, simulation can also determine whether there are conflicts in the mask pattern design, avoiding unnecessary debugging and iteration.

[0075] As mentioned in the above embodiments, multiple target points need to be acquired on the light source plane to generate a target region and obtain local target imaging performance indicators. Finally, based on the local target imaging performance indicators and the position of the target region, an overall imaging performance indicator is generated. Therefore, the local target imaging performance indicators need to be sufficiently representative, making the selection of target points particularly important. For example, multiple evenly distributed target points can be selected on the light source plane to obtain a more accurate overall imaging performance indicator.

[0076] This application provides a specific method for selecting target points. First, the light source plane is divided into multiple cells; then, downsampling is performed in each cell to select multiple target cells, and the center point of each target cell is determined as the target point.

[0077] It should be noted that the embodiments of this application do not limit the way the cells are divided. Typically, the light source plane is divided into grids of 32*32 (considering computational efficiency) or 201*201 (considering the physical structure of the light source). Figure 3 This illustration shows a schematic diagram of a cell division method for a light source plane provided in an embodiment of this application; as shown... Figure 3 As shown, the light source plane is a circular plane, divided into a series of equally spaced grid points (i.e., cells). Since the grid points are usually square, there are some incomplete grid points at the edges of the light source plane. These incomplete grid points can be ignored when selecting target points later. Each grid point in the light source plane can be set with a different energy intensity, usually normalized to the range of 0 to 1. The number of grid points is determined by the physical structure of the light source and computational efficiency.

[0078] After the light source plane is gridded, the cell coordinates can be represented using Cartesian coordinates or polar coordinates. The coordinates of the center point of the light source are generally set to (0, 0); the minimum X and Y coordinates of the light source cell are generally set to -1, and the maximum value is generally set to 1; based on the number of cells, the center coordinates of each cell are obtained. Taking 201*201 as an example, the X coordinate of each cell is as follows: -1, -0.99, -0.98, ..., -0.01, 0, 0.01, ..., 0.98, 0.99, 1, and the Y coordinate is the same; cells with a center distance of less than or equal to 1 are valid cells, while invalid cells do not exist physically, so invalid cells are not considered in subsequent steps.

[0079] This application embodiment divides the data into cells and then selects the target cell from multiple cells through downsampling. Furthermore, it uses the center point of the target cell as the target point, thereby improving the rationality of the selected point and selecting a more representative target point, thus ensuring the accuracy of the calculation results.

[0080] In practical applications, the target cells can be selected according to the specific situation. Selecting too many target cells will increase the amount of calculation, while ensuring that the target area can represent the information of the entire light source plane. Therefore, it is best to distribute the target cells evenly on the light source plane.

[0081] Therefore, in the solution provided in this application embodiment, each divided cell is sampled at equal intervals to obtain multiple undetermined cells; then, the target cell is determined based on the undetermined cells. It should be noted that the specific size of the sampling interval is not limited here, and should be determined according to actual needs. Furthermore, the sampled undetermined cells can be directly used as the target cell, or they can be further simplified by selecting suitable cells from the undetermined cells as the target cell, thereby reducing the computational load.

[0082] This application's embodiments select cells using an equally spaced sampling method, ensuring that the selected cells are evenly distributed across the light source plane. This reduces the number of cells selected, thereby reducing computational load. Simultaneously, it ensures the representativeness of the sampling points, improving the accuracy of subsequent generation of imaging performance indicators for the entire light source plane.

[0083] As mentioned above, the specific size of the sampling interval is not limited in practical applications; a suitable sampling interval can ensure that both the calculation time and calculation accuracy meet the requirements. Therefore, in the solution proposed in this application embodiment, each cell is sampled at equal intervals to obtain multiple cells to be determined, including:

[0084] Based on the constraints, the sampling interval is determined; based on the sampling interval, each cell is sampled at equal intervals to obtain multiple cells to be determined. The constraints here can be preset maximum calculation time and minimum calculation precision, etc.

[0085] Specifically, the number of cells can be sampled at equal intervals according to the requirements of calculation time and accuracy. For example, for a 201*201 cell, one point can be selected every 5 points in the X and Y directions as an evaluation point to participate in the simulation. The cell coordinates in the evaluation group are -1, -0.95, -0.9, ..., 0.9, 0.95, 1.

[0086] The embodiments of this application determine the sampling interval by means of constraints such as calculation time and calculation accuracy, which can minimize the calculation time while ensuring the accuracy of calculation and meet the actual production needs.

[0087] As mentioned above, the identified cells to be determined can be further simplified to identify fewer target cells. This application proposes an implementation scheme:

[0088] First, the symmetry structure of the light source plane is obtained; then, based on the symmetry structure, each undetermined cell is divided into multiple cell groups. Within the same cell group, each undetermined cell has the same imaging performance index; therefore, one undetermined cell can be selected from each cell group and designated as the target cell. Thus, a single target cell can represent all undetermined cells within the same cell group.

[0089] The embodiments of this application further simplify the target cell based on the symmetry requirements of the light source plane setting. Figure 4 This invention provides a schematic diagram illustrating the symmetry of a light source plane arrangement according to an embodiment of the present application; as shown below. Figure 4As shown, there is a target cell 401 in the light source plane with coordinates (0.3, 0.7). This also includes cells that have the same function as the target cell (0.3, 0.7) when the light source plane has different symmetries. For example, symmetries typically include DX, DY, D45, R90, D135, and R180. For the target cell with coordinates (0.3, 0.7), when the light source plane has different symmetries on the coordinate axes, the coordinates of the cells that have the same function as the target cell (0.3, 0.7) are listed as follows: DX: (-0.3, 0.7); DY: (0.3, -0.7); D45: (0.7, 0.3); R90: (-0.7, 0.3) and (0.7, -0.3); D135: (-0.7, -0.3); R180: (-0.3, -0.7). Furthermore, the following symmetry descriptions are equivalent: D2 is equivalent to DX and DY; D4 is equivalent to DX, DY, D45, and D135.

[0090] This application embodiment determines cells with the same imaging performance indicators by using the symmetrical structure of the light source plane, thereby reducing the number of selected points and reducing the amount of computation.

[0091] In practice, there is no limitation on how to perform imaging simulation. You can first obtain the preset process conditions; then input the preset process conditions, target area and target mask pattern into the imaging simulation tool. The imaging simulation tool will simulate the light source plane at the target area. By illuminating the target mask pattern through the simulated light source plane at the target area, the simulation pattern is obtained. Then, by comparing the simulation pattern with the target mask pattern, the target imaging performance index corresponding to the target area is obtained.

[0092] In practical applications, the specific imaging simulation tool used can be selected based on requirements. For example, a light source-based Abbe imaging simulation tool can be used. Abbe imaging simulation tools can quickly obtain imaging performance indicators for a specified mask pattern under preset process conditions using a given light source. Different tools can have different implementation methods.

[0093] By iterating through the target regions generated above, corresponding local light sources are generated. Imaging simulation is then performed on the specified target mask pattern under preset process conditions to obtain imaging performance indicators. The key settings are as follows:

[0094] Preset process conditions include, but are not limited to, focal length, exposure energy, mask offset, and measurement plane.

[0095] The specified target mask graphic can be a two-dimensional planar graphic that conforms to or closely approximates the design rules; it can be a collection of multiple mask graphics; and the location to be measured is usually specified in the mask graphic.

[0096] Specified imaging performance indicators: These are usually depth of focus, mask error enhancement factor, and normalized slope logarithm, or they can be some custom imaging performance indicators.

[0097] If necessary, the mask needs to be optimized during simulation to achieve imaging of the target size.

[0098] Furthermore, based on the symmetry of the light source plane mentioned above, points with equivalent effects will synchronously generate poles (i.e., target areas) and be added to the light source composition. When calculating the fill rate, the poles of the equivalent points also need to be considered.

[0099] The embodiments of this application can obtain accurate imaging performance indicators by inputting information such as photolithography process conditions, target area, and mask pattern into a simulation tool.

[0100] Furthermore, to determine the required target light source, the overall imaging performance indicators can be analyzed directly through the processor to obtain the target light source. Alternatively, the overall imaging performance indicators can be displayed to the user, who can then determine the appropriate target light source based on their actual needs. Therefore, after generating the overall imaging performance indicators for the entire light source plane, an imaging performance indicator image can be plotted on the light source plane based on the values ​​of the overall imaging performance indicators; and the imaging performance indicator image can be displayed. This visualizes the correspondence between the imaging performance indicators of the target mask graphic and each cell of the light source plane.

[0101] First, calculate the imaging performance index of the target mask pattern generated by the light source in each cell at the measurement position, and then plot the values ​​onto the light source plane according to the cell coordinates. Based on the symmetry set above, equivalent cells can be equivalently extended, meaning that the imaging index values ​​of equivalent cells are considered to be the same as those of the current cell.

[0102] Figure 5 This is an image illustrating one type of imaging performance index according to an embodiment of this application; such as Figure 5 As shown, the light source plane has D4 symmetry, the period of the target mask pattern is 120nm, and the specific imaging index is the normalized slope logarithm. The figure includes a first region 501, a second region 502, and a light source plane 503. The first region 501 has a higher normalized slope logarithm, while the second region 502 has a lower normalized slope logarithm.

[0103] Users can intuitively understand the overall imaging performance of the light source plane on the target mask pattern through the imaging performance index image, thereby designing the target light source required in practice.

[0104] The following is a specific embodiment. The minimum X and Y coordinates of the cells are set to -1, the maximum to 1, the number of cells is 32*32, the grid spacing is 0.0625, the symmetry is D2, the pole shape is square, and the size is one cell. The process conditions are as follows: 193nm immersion lithography, NA = 1.35; polarization is transverse electric field (TE); focal length (positive from the top layer of the film) is 50nm, measurement plane is 65nm; the anchor pattern is a numerical line with a width of 50nm and a period of 100nm, and its mask anchor bias is 1nm (i.e., the exposure imaging of a 52nm mask pattern is 50nm). A set of film parameters (refractive index, extinction coefficient, and thickness) needs to be provided.

[0105] Target mask pattern: Vertical lines with a feature width of 50nm and periods of 100, 140, 220, and 300nm. Measurement location is line width. Evaluation metric is the normalized logarithm of the slope of each pattern.

[0106] Figure 6 This application provides a normalized logarithmic slope distribution of vertical lines with a period of 100 nm as an embodiment of the present application; wherein the target mask pattern used for simulation imaging is a vertical line with a period of 100 nm. Figure 7 This application provides a normalized logarithmic slope distribution of vertical lines with a period of 140 nm as an embodiment of the present application; wherein the target mask pattern used for simulation imaging is a vertical line with a period of 140 nm. Figure 8 This application provides a normalized logarithmic slope distribution of vertical lines with a period of 220 nm as an embodiment of the present application; wherein the target mask pattern used for simulation imaging is a vertical line with a period of 220 nm. Figure 9 A normalized logarithmic slope distribution of vertical bars with a period of 300 nm is provided for an embodiment of this application; as shown... Figure 9 As shown, the target mask pattern used for simulation imaging is a vertical line with a period of 300 nm. Figures 6 to 9 In the diagram, a normalized logarithmic slope distribution is plotted based on the light source plane. The color depth represents the magnitude of the normalized logarithmic slope. The normalized logarithmic slope distribution is symmetrical in each diagram.

[0107] Figures 6 to 9 The two contour lines in the middle serve as the defined boundaries for the normalized logarithm of the slope, with normalized logarithm values ​​of NILS = 1.2 and NILS = 2, respectively. It can be seen that a light source that meets the normalized logarithm requirement for a pattern with a period of 100nm can also basically achieve the normalized logarithm requirement for imaging other patterns.

[0108] To address the aforementioned technical problems, embodiments of this application also provide a light source determining device. Figure 10 A schematic diagram of the structure of the light source determining device provided in an embodiment of this application is shown. Figure 10 As shown, the device includes the following modules:

[0109] The acquisition module 1001 is used to acquire multiple target points on the light source plane;

[0110] The first generation module 1002 is used to generate corresponding target areas on the light source plane based on each target point.

[0111] Simulation module 1003 is used to perform imaging simulation on the target mask pattern under preset process conditions using the light source of each target area to obtain the corresponding target imaging performance index.

[0112] The second generation module 1004 is used to generate an overall imaging performance index of the entire light source plane based on the target imaging performance index and the position of the corresponding target area on the light source plane, so as to determine the target light source.

[0113] In some embodiments, the acquisition module 1001 is specifically used for:

[0114] Divide the light source plane into multiple cells;

[0115] Downsampling is performed in each cell to select multiple target cells;

[0116] The center point of each target cell is determined as the target point.

[0117] In some embodiments, the acquisition module 1001 is specifically used for:

[0118] Sample each cell at equal intervals to obtain multiple cells to be determined;

[0119] Based on the cells to be determined, determine the target cell.

[0120] In some embodiments, the acquisition module 1001 is specifically used for:

[0121] Determine the sampling interval based on the constraints;

[0122] Based on the sampling interval, each cell is sampled at equal intervals to obtain multiple cells to be determined.

[0123] In some embodiments, the acquisition module 1001 is specifically used for:

[0124] Obtain the symmetrical structure of the light source plane;

[0125] Based on a symmetrical structure, each cell to be determined is divided into multiple cell groups; each cell to be determined in the same cell group has the same imaging performance index.

[0126] Select one cell from each cell group and designate it as the target cell.

[0127] In some embodiments, the simulation module 1003 is specifically used for:

[0128] Obtain the preset process conditions;

[0129] Input the preset process conditions, target area, and target mask pattern into the imaging simulation tool to obtain the target imaging performance indicators.

[0130] In some embodiments, the light source determining device further includes:

[0131] The drawing module is used to generate the overall imaging performance index of the entire light source plane based on the target imaging performance index and the position of the corresponding target area on the light source plane, and then draw the imaging performance index image on the light source plane based on the value of the overall imaging performance index.

[0132] The display module is used to display images of imaging performance indicators.

[0133] The apparatus provided in this application is the same as the method in the above embodiments, and therefore both have the same embodiments and beneficial effects, which will not be repeated here.

[0134] Figure 11 A schematic diagram of the hardware structure of the light source determination device provided in an embodiment of this application is shown. Figure 11 As shown, the light source determining device may include a processor 1101 and a memory 1102 storing computer program instructions.

[0135] Specifically, the processor 1101 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0136] Memory 1102 may include mass storage for data or instructions. For example, and not limitingly, memory 1102 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 1102 may include removable or non-removable (or fixed) media. Where appropriate, memory 1102 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 1102 is non-volatile solid-state memory.

[0137] Memory 1102 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this disclosure.

[0138] The processor 1101 reads and executes computer program instructions stored in the memory 1102 to implement any of the light source determination methods in the above embodiments.

[0139] In one example, the light source determination device may also include a communication interface 1103 and a bus 1104. The processor 1101, memory 1102, and communication interface 1103 are connected via bus 1104 and communicate with each other.

[0140] The communication interface 1103 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0141] Bus 1104 includes hardware, software, or both, that couples components of a light source determining device together. For example, and not limitingly, the bus may include an Accelerated Graphical Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 1104 may include one or more buses. Although specific buses are described and illustrated in the embodiments of this application, this application considers any suitable bus or interconnection.

[0142] Furthermore, in conjunction with the light source determination methods in the above embodiments, this application embodiment can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the light source determination methods in the above embodiments.

[0143] This application also provides a computer program product, including a computer program, which, when executed, implements any of the light source determination methods described in the above embodiments.

[0144] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0145] The functional blocks shown in the structural diagram above can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, ASICs, appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on machine-readable media or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable media" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, compact disc read-only memory (CD-ROM), optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0146] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0147] The foregoing flowcharts and / or block diagrams describing a light source determination method, apparatus, medium, and product according to embodiments of the present disclosure have described various aspects of the present disclosure. It should be understood that each block in the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to create a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowcharts and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by dedicated hardware performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0148] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for determining a light source, characterized in that, include: Acquire multiple target points on the light source plane; Based on each of the target points, a corresponding target area is generated on the light source plane; Using the light source of each target region, imaging simulation is performed on the target mask pattern under preset process conditions to obtain the corresponding target imaging performance index. Based on the target imaging performance index and the corresponding position of the target region on the light source plane, an overall imaging performance index of the entire light source plane is generated to determine the target light source. Specifically, by utilizing the light sources of each target region, imaging simulations are performed on the target mask pattern under preset process conditions to obtain corresponding target imaging performance indicators, including: For each target region, an imaging simulation is performed on the target mask pattern under preset process conditions using a local light source to obtain the wafer pattern corresponding to the target mask pattern illuminated by the local light source. The target mask pattern and the wafer pattern are compared to obtain the target imaging performance index, which includes depth of focus, mask error enhancement factor, and normalized slope logarithm.

2. The light source determination method according to claim 1, characterized in that, The acquisition of multiple target points on the light source plane includes: The light source plane is divided into multiple cells; Downsampling is performed in each of the cells to select multiple target cells; The center point of each target cell is determined as the target point.

3. The light source determination method according to claim 2, characterized in that, The downsampling in each of the cells, selecting multiple target cells, includes: Each of the cells is sampled at equal intervals to obtain multiple cells to be determined. Based on the undetermined cells, the target cell is determined.

4. The light source determination method according to claim 3, characterized in that, The step of sampling each cell at equal intervals to obtain multiple cells to be determined includes: Determine the sampling interval based on the constraints; Based on the sampling interval, each of the cells is sampled at equal intervals to obtain a plurality of cells to be determined.

5. The light source determination method according to claim 3, characterized in that, Determining the target cell based on the undetermined cell includes: Obtain the symmetry structure of the light source plane; Based on the symmetrical structure, each of the cells to be determined is divided into multiple cell groups; each cell to be determined in the same cell group has the same imaging performance index. Select one cell from each of the cell groups to be determined, and designate it as the target cell.

6. The light source determination method according to claim 1, characterized in that, The step of using light sources in each of the target regions to perform imaging simulations on the target mask pattern under preset process conditions to obtain corresponding target imaging performance indicators includes: Obtain the preset process conditions; The preset process conditions, the target area, and the target mask pattern are input into the imaging simulation tool to obtain the target imaging performance indicators.

7. The light source determination method according to any one of claims 1 to 6, characterized in that, After generating the overall imaging performance index of the entire light source plane based on the target imaging performance index and the corresponding position of the target region on the light source plane, the method further includes: Based on the values ​​of the overall imaging performance index, an imaging performance index image is drawn on the light source plane; The image displays the imaging performance indicators.

8. A light source determining device, characterized in that, include: Processor and memory storing computer program instructions; When the processor executes the computer program instructions, it implements the light source determination method as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions that, when executed by a processor, implement the light source determination method as described in any one of claims 1 to 7.

10. A computer program product, characterized in that, When the instructions in the computer program product are executed by the processor of the electronic device, the electronic device performs the light source determination method as described in any one of claims 1 to 7.

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