Method and system for determining optimal anchor pattern size deviation for maximum depth of focus

Abstract

The embodiment of the present application provides a method and system for determining the optimal anchor pattern size deviation for maximum focal depth, which calculates the available common process window after initial mask correction, identifies the exposure dose corresponding to the maximum available focal depth under the preset exposure threshold margin, creates an optimization function between the anchor pattern size deviation and the exposure threshold, calculates the optimal anchor pattern size deviation according to the relationship between the exposure dose corresponding to the maximum available focal depth and the optimization function, updates the lithography model by using the optimal anchor pattern size deviation, modifies the loss function in the mask correction process, and re-executes the mask correction to obtain the maximum available focal depth and the corresponding mask correction result. The method can quickly obtain the optimal anchor pattern size deviation and the realized maximum available focal depth through an automatic calculation process, save the calculation time, improve the optimization efficiency, and reduce the error probability.

Description

Technical Field

[0001] This application relates to the field of light source mask joint optimization technology, and in particular to a method and system for determining the optimal anchoring pattern size deviation to obtain the maximum depth of focus. Background Technology

[0002] Source Mask Optimization (SMO) is a resolution enhancement technique in photolithography that improves lithographic imaging quality and process window by simultaneously optimizing the light source illumination mode and mask pattern. SMO uses the light source and mask pattern as variables for joint optimization, minimizing the deviation between the lithographic pattern and the target pattern through calculation and iterative optimization. Given a target pattern, SMO can find the optimal light source and mask that minimizes the squared Euler distance between the exposed pattern and the target pattern on the silicon wafer. During the optimization process, perturbations in exposure dose, focus, and mask pattern size can be introduced. The edge placement error (EPE) caused by these perturbations is calculated and used as the evaluation function.

[0003] When performing mask optimization, it is necessary to determine the exposure threshold in the lithography model, and then modify other mask patterns based on the exposure threshold. Therefore, the exposure threshold directly affects the modification result of the mask pattern, and thus affects the final common process window. A reasonable available common process window should be symmetrically distributed on both sides of the exposure threshold, at which point the available common depth of focus for all patterns is maximized. However, an unreasonable process window is mainly distributed on one side of the exposure threshold, resulting in a smaller available common depth of focus, making the exposure threshold unsuitable for most mask patterns, and requiring optimization of the exposure threshold.

[0004] Since the exposure threshold is determined by the size of the anchor pattern and the expected development result, adjusting the exposure threshold by modifying the pattern size and expected development result to obtain the maximum usable common depth of focus is an important approach to improving the process window in mask optimization techniques. When the common process window is not located at the center of the optimal exposure threshold, the exposure threshold can be changed by manually adjusting the anchor pattern size deviation. Then, by ensuring a mask correction process consistent with that before changing the exposure threshold, the relative translation of the common process window can be achieved. This process can maximize the usable depth of focus; however, manually adjusting and calculating the optimal anchor pattern size deviation is complex and inefficient. Summary of the Invention

[0005] In view of this, embodiments of this application provide a method and system for determining the optimal anchoring pattern size deviation to obtain the maximum depth of focus, so as to solve the problem of low optimization efficiency in the process of adjusting and calculating the optimal anchoring pattern size deviation.

[0006] According to one aspect of this application, a method for determining the optimal anchoring pattern size deviation for obtaining maximum depth of focus is provided, the method comprising:

[0007] The available common process window data after initial mask correction is obtained. The available common process window data includes the available common process window when the exposure dose is fixed at multiple dose values ​​after mask correction under the initial anchoring pattern size deviation.

[0008] Using the available common process window data, identify the exposure dose corresponding to the maximum available depth of focus under the preset exposure margin;

[0009] An optimization function is created to characterize the functional relationship between the anchoring pattern size deviation and the exposure threshold; the change in the exposure threshold and the change in the exposure dose are opposites of each other.

[0010] The optimal anchoring pattern size deviation is calculated based on the optimization function and the exposure dose;

[0011] The lithography model is updated using the optimal anchor pattern size deviation, and the mask correction is re-executed based on the updated lithography model.

[0012] In some embodiments, obtaining available common process window data after initial mask correction includes:

[0013] A photolithography model is established based on the initial anchoring pattern size deviation;

[0014] An initial mask correction is performed based on the photolithography model to generate initial mask correction result data, which includes the pattern result after initial mask correction.

[0015] A process window for drawing pattern results based on initial mask correction data, the process window including dose values ​​of defocus amount and exposure dose that are related;

[0016] Determine the available common process windows within the process window;

[0017] Establish the association between the available common process window and the dose value to generate the available common process window data.

[0018] In some embodiments, using the available common process window data, identifying the exposure dose corresponding to the maximum available depth of focus under a preset exposure margin includes:

[0019] Obtain the preset exposure margin;

[0020] Based on the available common process window data and the preset exposure margin, plot the linewidth variation curves under different dose values ​​and focal lengths;

[0021] From the linewidth variation curve, find the maximum depth of focus range within the acceptable linewidth variation range;

[0022] Based on the linewidth variation curve, determine the corresponding exposure dose within the maximum usable depth of focus range.

[0023] In some embodiments, determining the exposure dose corresponding to the maximum usable depth of focus range based on the linewidth variation curve includes:

[0024] Based on the linewidth variation curve, determine the corresponding dose value range within the maximum usable depth of focus;

[0025] Photolithography simulations are performed based on the maximum depth of focus range and the dose value range to simulate the imaging effects under different exposure doses and focal lengths.

[0026] The dose value range is corrected based on the imaging effect, and the exposure dose corresponding to the maximum usable depth of focus is extracted within the dose value range.

[0027] In some embodiments, an optimization function is created, including:

[0028] Construct anchoring patterns;

[0029] By modifying the anchor pattern size deviation, the exposure thresholds corresponding to multiple anchor pattern size deviations are calculated;

[0030] The optimized function is generated by fitting a functional relationship between the anchor pattern size deviation and the exposure threshold.

[0031] In some embodiments, the method further includes:

[0032] Obtain the initial exposure threshold and initial exposure dose;

[0033] Set the exposure dose change value according to the preset adjustment step size;

[0034] Calculate the adjusted exposure dose based on the initial exposure dose and the change in exposure dose;

[0035] Find the light intensity data at different locations corresponding to the adjusted exposure dose according to the light intensity distribution curve;

[0036] The exposure threshold change value is calculated based on the light intensity data to determine the correspondence between the exposure threshold change value and the exposure dose change value.

[0037] In some embodiments, calculating the optimal anchoring pattern size deviation based on the optimization function and the exposure dose includes:

[0038] Calculate the inverse function of the optimization function;

[0039] Obtain the exposure dose corresponding to the maximum usable depth of focus and the correspondence between the change value of the exposure threshold and the change value of the exposure dose;

[0040] The optimal anchoring pattern size deviation is calculated based on the inverse function of the optimization function, the exposure dose, and the corresponding relationship.

[0041] In some embodiments, calculating the optimal anchoring pattern size deviation based on the inverse function of the optimization function, the exposure dose, and the correspondence includes:

[0042] Obtain the initial exposure threshold and the change in exposure dose;

[0043] An intermediate variable is calculated based on the change in exposure dose, and the intermediate variable is the difference obtained by subtracting the change in exposure dose from 1.

[0044] Calculate the product of the intermediate variable and the initial exposure threshold;

[0045] The product is input into the inverse function of the optimization function to obtain the optimal anchoring pattern size deviation.

[0046] In some embodiments, updating the lithography model using the optimal anchoring pattern size deviation, and re-performing mask correction based on the updated lithography model, includes:

[0047] An updated model is established based on the optimal anchoring pattern size deviation;

[0048] Synchronously update the loss function settings during the mask correction process;

[0049] If the loss function includes the result information when the exposure dose changes, update the exposure dose change value according to the initial value of the exposure dose change and the exposure dose change value corresponding to the maximum available depth of focus;

[0050] Mask correction is performed based on the updated model and the loss function to output the final mask pattern and result process window.

[0051] According to another aspect of this application, an optimal anchoring pattern size deviation determination system for obtaining maximum depth of focus is provided, the method system being:

[0052] The acquisition module is used to acquire available common process window data after initial mask correction. The available common process window data includes available common process windows when the exposure dose is fixed at multiple dose values ​​after mask correction under the initial anchoring pattern size deviation.

[0053] The identification module is used to identify the exposure dose corresponding to the maximum available depth of focus under the preset exposure margin using the available common process window data.

[0054] The function module is used to create an optimization function that characterizes the functional relationship between the anchoring pattern size deviation and the exposure threshold; the change in the exposure threshold and the change in the exposure dose are opposites of each other.

[0055] The calculation module is used to calculate the optimal anchoring pattern size deviation based on the optimization function and the exposure dose;

[0056] The correction module is used to update the lithography model using the optimal anchoring pattern size deviation, and to re-perform mask correction based on the updated lithography model.

[0057] According to another aspect of this application, a computer device is provided, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor executes the program to implement the above-described method for determining the optimal anchoring pattern size deviation for obtaining the maximum depth of focus.

[0058] According to another aspect of this application, a storage medium is provided that stores a computer program thereon, which, when executed by a processor, implements the above-described method for determining the optimal anchoring pattern size deviation to obtain the maximum depth of focus.

[0059] By employing the above technical solution, embodiments of this application provide a method and system for determining the optimal anchor pattern size deviation to obtain the maximum depth of focus. After initial mask correction, the method calculates the available common process window and identifies the exposure dose corresponding to the maximum usable depth of focus under a preset exposure threshold margin. An optimization function is then created between the anchor pattern size deviation and the exposure threshold. The optimal anchor pattern size deviation is calculated based on the relationship between the exposure dose corresponding to the maximum usable depth of focus and the optimization function. The optimal anchor pattern size deviation is then used to update the lithography model, and the loss function in the mask correction process is modified. Mask correction is then re-executed to obtain the maximum usable depth of focus and the corresponding mask correction result. This method can quickly obtain the optimal anchor pattern size deviation and the achieved maximum usable depth of focus through an automated calculation process, saving computation time, improving optimization efficiency, and reducing the probability of errors.

[0060] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0061] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0062] Figure 1 A schematic flowchart of the method for determining the optimal anchoring pattern size deviation to obtain the maximum depth of focus, provided in an embodiment of this application.

[0063] Figure 2 This is a schematic diagram of the process window provided for an embodiment of this application;

[0064] Figure 3 This is a schematic diagram illustrating the correspondence between exposure thresholds and exposure dose changes provided in the embodiments of this application;

[0065] Figure 4 A schematic diagram of the common process window obtained by initial mask optimization provided in the embodiments of this application;

[0066] Figure 5 A schematic diagram of a common process window obtained by mask optimization based on the optimal anchoring pattern size deviation, provided for an embodiment of this application;

[0067] Figure 6 This is a schematic diagram of the optimal anchoring pattern size deviation determination system for obtaining maximum depth of focus provided in an embodiment of this application.

[0068] Figure 7 A schematic diagram illustrating the process of achieving the optimal anchoring pattern size deviation for obtaining the maximum depth of focus, provided in an embodiment of this application.

[0069] Figure 8 This is a schematic diagram of the computer device structure provided in an embodiment of this application. Detailed Implementation

[0070] The present application will be described in detail below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in the embodiments of the present application can be combined with each other.

[0071] In this application embodiment, photolithography (Photo) is a process used to manufacture semiconductors. Photolithography is a key step in the process of using exposure and development to etch geometric patterns onto a photoresist layer, and then transferring the patterns from the photomask onto the substrate through etching.

[0072] In some embodiments, the photolithography process may include the following steps: cleaning and surface preparation, photoresist coating, soft baking, alignment and exposure, development, hard baking, etching, photoresist removal, inspection and testing, repetition and iteration, etc. In the repetition and iteration steps, process parameters can be adjusted and the photolithography process optimized based on the inspection results. By analyzing the quality of the photolithographic product and adjusting parameters such as exposure dose, focal length, and photoresist coating thickness, and repeating the photolithography process until satisfactory pattern quality is achieved, this process may involve source mask optimization (SMO).

[0073] Joint optimization of the light source and mask is a resolution enhancement technique in photolithography. It improves the lithographic imaging quality and process window by simultaneously optimizing the light source illumination mode and mask pattern. Joint optimization treats the light source and mask pattern as variables for joint optimization, minimizing the deviation between the lithographically rendered pattern and the target pattern through calculation and iterative optimization.

[0074] In some embodiments, when performing joint optimization of the light source and mask, the optimization objective can be determined first, clarifying the graphic features that need to be optimized, such as minimum period and critical dimensions. An optical model is then established, including the light source shape, intensity distribution, and phase, as well as the graphic features, structural layer composition, and transmittance of the mask. Since optimizing all graphics is time-consuming, key graphics can be selected to eliminate duplicate or redundant graphics.

[0075] For the key images obtained through screening, preliminary optimization can be performed. During this preliminary optimization, light source optimization and synchronization optimization can be performed. Light source optimization uses a separate light source optimization algorithm to quickly reduce imaging errors. Synchronization optimization utilizes a synchronous SMO algorithm to jointly optimize the light source and mask. Then, through result fitting, the optimized light source distribution is fitted to a diffractive optical element (DOE) light source or a free-form light source.

[0076] After initial optimization, mask optimization can be performed. During mask optimization, auxiliary graphics can be inserted. Starting from the distribution of the continuous transmission mask (CTM), sub-resolution assist features (SRAFs) can be inserted, and the main mask graphic and SRAFs can be modified according to mask manufacturing rules. Further optimization of the mask graphic can then be performed, adjusting parameters such as line width, spacing, or adding auxiliary lines.

[0077] After obtaining the mask optimization results, it is necessary to further optimize and verify these results. For example, a photomask can be fabricated based on the optimization results, exposure and development experiments can be conducted, and photoresist data on actual wafers can be collected. A photoresist model can then be established based on the photoresist data, and the light source and mask can be jointly optimized again using the photoresist model to obtain a more accurate light source shape and key dimensions of the photomask.

[0078] Before applying the optimization results to actual production, they need to be evaluated, specifically the imaging quality and the process window. To evaluate imaging quality, the optimized image can be compared to the ideal image, and evaluation metrics such as Edge Placement Error (EPE) can be calculated. When checking the process window, it's crucial to ensure that the optimized light source and mask meet the requirements within the process window.

[0079] After the optimization results are evaluated, the optimized light source and mask are applied to actual production to improve the precision and yield of chip manufacturing. It is evident that SMO can find the optimal light source and mask for a given target pattern, minimizing the squared Euler distance between the exposed pattern and the target pattern on the silicon wafer. During the optimization process, perturbations in exposure dose, focus, and pattern size on the mask can be introduced. The edge placement error (EPE) caused by these perturbations is calculated, and the edge placement error is used as the evaluation function.

[0080] When optimizing a mask, it's necessary to determine the exposure threshold in the lithography model and then modify other mask patterns based on this threshold. Therefore, the exposure threshold directly affects the modification result of the mask pattern, and consequently, the final common process window. A reasonable common process window should be symmetrically distributed on both sides of the exposure threshold, maximizing the available common depth of focus for all patterns. Conversely, an unreasonable process window, primarily distributed on one side of the exposure threshold, results in a smaller available common depth of focus, making the exposure threshold unsuitable for most mask patterns, thus requiring optimization of the exposure threshold.

[0081] Since the exposure threshold is determined by the size of the anchor pattern and the expected development result, adjusting the exposure threshold by modifying the pattern size and expected development result to obtain the maximum usable common depth of focus is a technique for improving the process window in mask optimization. When the common process window is not located at the center of the optimal exposure threshold, in some embodiments, the exposure threshold can be changed by manually adjusting the anchor pattern size deviation, and then the common process window can be relatively shifted by ensuring a mask correction process consistent with that before changing the exposure threshold. This process can maximize the usable depth of focus; however, manually adjusting and calculating the optimal anchor pattern size deviation is complex and inefficient.

[0082] In some embodiments, a common process window closer to the center of the exposure threshold can be achieved by fixing the anchor pattern size deviation, i.e., keeping the exposure threshold constant, and then modifying the loss function or correction method in the mask correction process. However, this process requires a significant amount of time and effort to explore the optimal script settings and will result in a loss of the final process window.

[0083] To address the problem of low optimization efficiency in adjusting and calculating the optimal anchoring pattern size deviation, some embodiments of this application provide a method for determining the optimal anchoring pattern size deviation to obtain the maximum depth of focus. This method can be applied to electronic devices with data processing capabilities, such as computers, servers, mobile terminals, and industrial control computers. In some embodiments of this application, electronic devices are used as the execution subject of each step of the method to illustrate the method. It should be understood that other execution subjects conceived by those skilled in the art based on the corresponding embodiments also fall within the protection scope of this application. Figure 1 As shown, the method includes:

[0084] S101. Obtain the available common process window data after the initial mask correction.

[0085] When performing joint optimization of the light source mask in electronic devices, initial mask correction can be performed first to obtain available common process window data after the initial mask correction. Mask correction involves adjusting the mask pattern to compensate for pattern distortion caused by factors such as optical effects, proximity effects, and etching deviations during photolithography, thereby ensuring that the final pattern formed on the silicon wafer is consistent with the design pattern. Initial mask correction is performed using the initial anchor pattern size deviation.

[0086] Exposure dose refers to the light energy emitted onto a unit area of ​​photoresist, and can be expressed as energy / area (e.g., mJ / cm²). 2 The available common process window is the overlapping portion of the process windows for multiple key patterns. The available common process window reflects that, within a certain range, all key patterns can achieve qualified pattern transfer under the same exposure dose and defocus amount conditions. Therefore, the available common process window data includes the available common process window when the exposure dose is fixed at multiple dose values ​​after mask correction under the initial anchor pattern size deviation.

[0087] In some embodiments, to obtain available common process window data after initial mask correction, the electronic device, when performing initial mask correction, may first establish a photolithography model based on the initial anchoring pattern size deviation, and then perform initial mask correction based on the photolithography model to generate initial mask correction result data, which includes the pattern result after initial mask correction. Next, a process window for the pattern result is drawn based on the initial mask correction result data, and available common process windows are determined within the process window. The process window includes dose values ​​for defocusing amount and exposure dose that are correlated. The available common process window data is then generated by establishing the correlation between the available common process windows and the dose values.

[0088] For example, an electronic device can establish a photolithography model based on the initial anchor pattern size deviation, perform mask correction based on this model, and plot the process window for each pattern result. A schematic diagram of the process window is shown below. Figure 2 As shown, the horizontal axis represents the defocus amount, and the vertical axis represents the exposure dose.

[0089] Figure 2 The ellipse drawn in the diagram represents the common process window for all patterns, where the major axis of the ellipse represents the common depth of focus, and the minor axis represents the common exposure margin. By calculating the common depth of focus corresponding to different exposure dose values, i.e., determining the major axis of the ellipse at different heights of its center, usable common process window data can be obtained.

[0090] S102. Using the available common process window data, identify the exposure dose corresponding to the maximum available depth of focus under the preset exposure margin.

[0091] After acquiring the available common process window data, the electronic device can use this data to identify the exposure dose corresponding to the maximum usable depth of focus under a preset exposure margin. Here, exposure margin refers to the maximum allowable deviation of exposure energy within the allowable range of linewidth variation. Exposure margin is an indicator of the lithography process's tolerance to exposure dose fluctuations. Preset exposure margin refers to an acceptable preset exposure margin input in advance based on the actual lithography process requirements.

[0092] Maximum usable depth of focus (MDF) refers to the maximum range of movement of the focal plane along the optical axis while maintaining acceptable image quality. MDF is a parameter used to measure the ability of a lithography system to maintain sharp imaging even when out of focus. For example, it is the amount of exposure dose change Δ corresponding to the MDF under an acceptable preset exposure margin. dose , which is the ordinate of the center of the ellipse when the minor axis is minimized.

[0093] In some embodiments, to identify the exposure dose corresponding to the maximum usable depth of focus under a preset exposure margin, the electronic device may first obtain the preset exposure margin and plot linewidth variation curves under different dose values ​​and focal lengths based on the available common process window data and the preset exposure margin. Then, from the linewidth variation curves, the maximum depth of focus range within the acceptable linewidth variation range is found, and the exposure dose corresponding to the maximum usable depth of focus range is determined based on the linewidth variation curves.

[0094] To determine the exposure dose within the maximum usable depth of focus (MDF), when determining the exposure dose within the MDF based on the linewidth variation curve, the dose value range within the MDF can be determined using the linewidth variation curve. Then, lithographic simulation is performed based on the MDF range and the dose value range to simulate the imaging effects under different exposure doses and focal lengths. Finally, the dose value range is corrected based on the imaging effects, and the exposure dose corresponding to the MDF is extracted within the dose value range.

[0095] For example, to identify the exposure dose corresponding to the maximum usable depth of focus within an acceptable exposure margin, the electronic device can first determine the process window and key parameters. These key parameters may include the acceptable linewidth variation range of the lithography process, such as ±10%, and the corresponding exposure margin (EL) and depth of focus (DOF). For the determined key process parameters, the electronic device then performs a focus-energy matrix (FEM) experiment. Through the FEM experiment, linewidth variation curves (Bossung plots) are plotted under different exposure doses and focal lengths. Specifically, these curves are plotted at 16, 18, 20, 22, and 24 mJ / cm². 2 The recording linewidth varies with focal length under different exposure doses.

[0096] By analyzing the linewidth variation curves, the maximum depth of focus (DF) within the acceptable linewidth variation range can be identified. For example, in a 90nm process, when the linewidth variation range is ±10%, the maximum usable DF is approximately 0.30 μm. Then, based on the linewidth variation curves, the corresponding exposure dose range within the maximum usable DF range can be determined. For instance, by analyzing the linewidth variation curves under different exposure doses, it can be determined that the exposure dose range at the maximum usable DF is 19–21 mJ / cm². 2 Then, using lithography simulation tools such as PROLITH and SOLID-C, the imaging effects under different exposure doses and focal lengths are simulated to further optimize the exposure dose range. For example, simulations can determine that under specific process conditions, the exposure dose range for FOCAL technology is 25–55 mJ / cm². 2In the actual photolithography process, it was verified whether the determined exposure dose range could achieve the maximum usable depth of focus. Based on the actual results, the exposure dose and focal length parameters were further adjusted to ensure the stability and reliability of the process window.

[0097] S103. Create an optimization function.

[0098] After identifying the exposure dose corresponding to the maximum usable depth of focus under a preset exposure margin, the electronic device can also create an optimization function. This optimization function characterizes the functional relationship between the anchor pattern size deviation and the exposure threshold. The anchor pattern size deviation refers to the difference between the actual pattern size and the design target size caused by factors such as optical effects, mask manufacturing errors, and photoresist characteristics during the photolithography process. The exposure threshold is the minimum light intensity required for the photoresist to undergo a photochemical reaction; it determines whether the photoresist can form the expected pattern after exposure. A specific functional relationship can exist between the anchor pattern size deviation and the exposure threshold, which can be established using photolithography models and experimental data. This functional relationship can be non-linear and can be influenced by various factors, including photoresist characteristics, mask patterns, light source characteristics, and photolithography process parameters.

[0099] In some embodiments, in order to create an optimization function, the electronic device can construct an anchor pattern and calculate exposure thresholds corresponding to multiple anchor pattern size deviations by modifying the anchor pattern size deviations, thereby fitting a functional relationship between the anchor pattern size deviations and the exposure thresholds to generate the optimization function.

[0100] For example, in a photolithography model, the final imaging result can be determined by calculating the light intensity distribution of the pattern and then using the exposure threshold. That is, the portion of the light intensity above (or below) the exposure threshold represents the final pattern result. Since the exposure threshold is determined based on the anchor pattern size deviation, the exposure threshold corresponding to each anchor pattern size deviation is calculated by modifying the anchor pattern size deviation, and a functional relationship between the two is fitted. This functional relationship can be expressed by the following formula:

[0101] T = f(Ab);

[0102] Where T represents the exposure threshold; Ab represents the anchor pattern size deviation; and f() represents the functional relationship between the anchor pattern size deviation and the exposure threshold.

[0103] In some embodiments, while calculating the functional relationship between the anchor pattern size deviation and the exposure threshold, the electronic device can also calculate the correspondence between the change in exposure dose and the change in exposure threshold.

[0104] For example, the correspondence between exposure threshold and exposure dose change is as follows: Figure 3 As shown in the figure, the solid line represents the light intensity distribution curve under different exposure doses, and the dashed line represents different exposure thresholds. Increasing the exposure dose increases the light intensity at all locations. When the exposure dose increases by 10%, the light intensity at all points increases by 10%. Conversely, when the exposure dose decreases by 10%, the light intensity at all points decreases by 10%. The pattern obtained after increasing the exposure dose by 10% and correspondingly increasing the exposure threshold by 10% is the same as the result when both the exposure dose and exposure threshold are at their initial values. That is:

[0105]

[0106] Where, Δ dose =Δ T T0 is the initial exposure threshold, dose0 is the initial exposure dose, and Δ dose Δ represents the change in exposure dose. T This represents the change in the exposure threshold.

[0107] Therefore, the change in the exposure threshold and the change in the exposure dose are opposites of each other. That is, to ensure the same pattern result, the change in exposure dose and the change in exposure threshold should remain opposites.

[0108]

[0109] Where, Δ dose =-Δ T Similarly, T0 is the initial exposure threshold, dose0 is the initial exposure dose, and Δ dose Δ represents the change in exposure dose. T This represents the change in the exposure threshold.

[0110] In some embodiments, to calculate the correspondence between changes in exposure dose and changes in exposure threshold, the electronic device can acquire an initial exposure threshold and an initial exposure dose, and set the exposure dose change value according to a preset adjustment step size. Then, based on the initial exposure dose and the exposure dose change value, an adjusted exposure dose is calculated, and light intensity data at different locations corresponding to the adjusted exposure dose is found according to a light intensity distribution curve. Based on the light intensity data, an exposure threshold change value is calculated to determine the correspondence between the exposure threshold change value and the exposure dose change value.

[0111] For example, when determining the relationship between changes in exposure dose and changes in exposure threshold, electronic devices can first establish an exposure model for the photoresist. The exposure process of the photoresist can be described using the Dill model, which considers the absorption and photochemical reactions of the photosensitive component (PAC) in the photoresist. The basic equations of the Dill model are as follows:

[0112]

[0113] Where [PAC] is the concentration of the photosensitive component; α is the absorption coefficient; I is the incident light intensity; the relationship between the exposure dose D and the exposure time t is: D = I·t.

[0114] After establishing the exposure model of the photoresist, the exposure threshold can be determined, which is the minimum exposure dose required for the photoresist to undergo a photochemical reaction. The exposure threshold can be obtained through experimental measurement or theoretical calculation. For example, for positive photoresist, the exposure threshold is the minimum dose required for complete removal of the photoresist. For negative photoresist, the exposure threshold is the minimum dose required for the photoresist to begin crosslinking.

[0115] Next, the relationship between the change in exposure dose and the change in exposure threshold is calculated. That is, through experiments or simulations, the relationship curve between the photoresist's exposure dose and exposure threshold can be obtained. Specifically, for positive photoresists, as the exposure dose increases, the remaining film thickness of the photoresist gradually decreases until it is completely removed. For negative photoresists, as the exposure dose increases, the degree of cross-linking of the photoresist increases, and the remaining film thickness gradually increases.

[0116] The established relationship curve is then calibrated using experimental data. This involves experimentally measuring the change in photoresist film thickness under different exposure doses to establish a quantitative relationship between exposure dose and exposure threshold. For example, scanning electron microscopy (SEM) images combined with threshold segmentation algorithms can be used to quantitatively assess the residual photoresist level, thereby calculating and predicting the correspondence between changes in exposure dose and changes in exposure threshold.

[0117] S104. Calculate the optimal anchoring pattern size deviation based on the optimization function and the exposure dose.

[0118] After constructing the optimization function and determining the correspondence between the exposure threshold change value and the exposure dose change value, the electronic device can calculate the optimal anchoring pattern size deviation based on the optimization function and the exposure dose. The optimal anchoring pattern size deviation refers to minimizing the deviation between the actual pattern size and the design target size by optimizing process parameters such as exposure dose and focal length and mask design under specific photolithography conditions.

[0119] To determine the optimal anchor pattern size deviation, in some embodiments, the electronic device can collect parameter information required to build an Optical Proximity Correction (OPC) model, including mask parameters, lithography wavelength and numerical aperture parameters, photoresist film thickness and refractive index, etc. An initial virtual model is then built, i.e., the shape of the initial illumination source is determined, generating an optical model simulating the propagation of incident light waves on the wafer and a mask database with three-dimensional effects. These are combined into the initial OPC virtual model. Then, the anchor pattern size is pre-selected, i.e., a series of pre-selected lithography anchor point pattern sizes are determined based on the design rules of the current technology node and the lithography anchor point pattern size of the previous technology node.

[0120] For each pre-selected lithographic anchor point pattern size, a lithographic deviation range is chosen, and the energy and focus of the OPC virtual model are adjusted. Lithographic inversion technology (ILT) is used to simulate and calculate the pre-selected lithographic anchor point patterns and key patterns. The optimal lithographic deviation is selected by comparing evaluation parameters such as strongest light intensity, weakest light intensity, contrast, slope, image log slope, normalized image log slope, and mask error enhancement factor. By repeating the above steps for all pre-selected lithographic anchor point pattern sizes, the optimal lithographic anchor point pattern size and its corresponding lithographic deviation are finally determined.

[0121] In some embodiments, to calculate the optimal anchoring pattern size deviation, the electronic device may first calculate the inverse function of the optimization function and obtain the exposure dose corresponding to the maximum available depth of focus and the correspondence between the change in the exposure threshold and the change in the exposure dose; then, the optimal anchoring pattern size deviation is calculated based on the inverse function of the optimization function, the exposure dose, and the correspondence. Specifically, when calculating the optimal anchoring pattern size deviation, the electronic device may first obtain the initial exposure threshold and the change in exposure dose; then, an intermediate variable is calculated based on the change in exposure dose, where the intermediate variable is the difference obtained by subtracting the change in exposure dose from 1. The product of the intermediate variable and the initial exposure threshold is then calculated, and the product is input into the inverse function of the optimization function to obtain the optimal anchoring pattern size deviation.

[0122] For example, when calculating the optimal anchoring pattern size deviation, we can first take the inverse function of the optimization function, i.e., f -1 (), and combined with the identification results of step S102, that is, the correspondence between the exposure dose corresponding to the maximum available depth of focus and the change of exposure dose and the change of exposure threshold, the optimal anchoring pattern size deviation can be calculated as:

[0123] Ab best =f -1 (T0·(1-Δ dose ));

[0124] Among them, Ab best For optimal anchor pattern size deviation, T0 is the initial exposure threshold, Δ dose This represents the change in exposure dose.

[0125] S105. Update the lithography model using the optimal anchoring pattern size deviation, and re-perform mask correction based on the updated lithography model.

[0126] After calculating the optimal anchoring pattern size deviation, the electronic device can update the lithography model using the optimal anchoring pattern size deviation, and re-perform mask correction based on the updated lithography model. That is, the electronic device can perform mask correction based on the model and loss function, and output the final mask pattern and the resulting process window.

[0127] In mask correction, the loss function is a key metric used to measure the correction effect. It assesses the difference between the corrected mask pattern and the target pattern. For example, the loss function in mask correction can be one or more combinations of Mean Squared Error (MSE), pattern error loss, reverse lithography loss, mask weighting loss, loss functions from self-supervised learning, and dynamic masking loss functions. Different loss functions are suitable for different optimization objectives and application scenarios during mask correction. For instance, MSE loss is suitable for simple pixel-level difference calculations, while reverse lithography loss is more suitable for complex lithography process optimization. Selecting or designing an appropriate loss function based on specific needs can significantly improve the effectiveness and efficiency of mask correction.

[0128] In some embodiments, to enable the mask correction electronics to re-execute, an updated model can first be established based on the optimal anchoring pattern size deviation, and then the loss function settings during the mask correction process can be updated synchronously. If the loss function includes result information for exposure dose changes, the exposure dose change value is updated based on the initial value of the exposure dose change and the exposure dose change value corresponding to the maximum available depth of focus. Then, mask correction is performed based on the updated model and the loss function to output the final mask pattern and result process window.

[0129] For example, a photolithography model is established based on the optimal anchoring pattern size deviation, and the loss function settings during the mask optimization process are updated simultaneously. When the loss function includes information about the results of exposure dose changes, the exposure dose change value is updated according to the following formula:

[0130]

[0131] in, The settings have been updated for the change in exposure dose. This sets the initial parameters for exposure dose variation. Δ dose This is the change in exposure dose corresponding to the maximum usable depth of focus determined in step S102.

[0132] By applying the technical solutions of the above embodiments, the method for determining the optimal anchoring pattern size deviation to obtain the maximum depth of focus provided in the above embodiments can, after completing mask correction under the initial anchoring pattern size deviation, calculate the available common process window when the exposure dose is fixed at multiple dose values, and identify the exposure dose corresponding to the maximum usable depth of focus under acceptable exposure threshold margin. Then, the functional relationship between the anchoring pattern size deviation and the exposure threshold is calculated. Based on the exposure dose corresponding to the maximum usable depth of focus, the correspondence between the exposure dose change value and the exposure threshold change value, and the functional relationship between the anchoring pattern size deviation and the exposure threshold, the optimal anchoring pattern size deviation is calculated. By modifying the anchoring pattern size deviation to obtain a new lithography model, and correspondingly modifying the loss function in the mask correction process, the maximum usable depth of focus and the corresponding mask correction results are finally obtained.

[0133] For example, using the optimal anchoring pattern size deviation determination method for obtaining the maximum depth of focus described in the above embodiments, experiments can be conducted on representative patterns of key metal layers etched using deep ultraviolet light to obtain the optimal anchoring pattern size deviation and the corresponding mask optimization results. Specifically, when obtaining the usable common process window data after initial mask correction, the initial anchoring pattern size deviation is set to -4nm. Mask optimization is then performed based on this setting, and the resulting process window is as follows: Figure 4 As shown.

[0134] For the step of identifying the exposure dose corresponding to the maximum usable depth of focus under a preset exposure margin using the available common process window data, when the acceptable exposure margin is 7%, the change in exposure dose corresponding to the maximum usable depth of focus is -1%. Furthermore, by creating an optimization function and calculating the optimal anchoring pattern size deviation based on the optimization function and the exposure dose, the optimal anchoring pattern size deviation is calculated to be -3nm. Therefore, the lithography model and the corresponding loss function in the mask correction process are updated based on the calculated optimal anchoring pattern size deviation, and mask optimization is performed. The final process window is as follows: Figure 5 As shown, determining the optimal anchor pattern size deviation can increase the common depth of focus by approximately 8%. Furthermore, the above calculation process is automated, allowing for the rapid acquisition of the optimal anchor pattern size deviation and the maximum usable depth of focus. This saves time and effort compared to manual calculations and minimizes the probability of errors.

[0135] Furthermore, the method described in the above embodiments can also provide guidance for mask correction methods in subsequent optical proximity effect correction processes, ultimately maximizing the available process window, improving product yield, and reducing the probability of rework.

[0136] In some embodiments, as a specific implementation of the method for determining the optimal anchoring pattern size deviation for obtaining the maximum depth of focus described in the above embodiments, some embodiments of this application also provide a system for determining the optimal anchoring pattern size deviation for obtaining the maximum depth of focus, such as... Figure 6 , Figure 7 As shown, the system includes:

[0137] The acquisition module is used to acquire available common process window data after initial mask correction. The available common process window data includes available common process windows when the exposure dose is fixed at multiple dose values ​​after mask correction under the initial anchoring pattern size deviation.

[0138] The identification module is used to identify the exposure dose corresponding to the maximum available depth of focus under the preset exposure margin using the available common process window data.

[0139] The function module is used to create an optimization function that characterizes the functional relationship between the anchoring pattern size deviation and the exposure threshold; the change in the exposure threshold and the change in the exposure dose are opposites of each other.

[0140] The calculation module is used to calculate the optimal anchoring pattern size deviation based on the optimization function and the exposure dose;

[0141] The correction module is used to update the lithography model using the optimal anchoring pattern size deviation, and to re-perform mask correction based on the updated lithography model.

[0142] It should be noted that other corresponding descriptions of the functional units involved in the optimal anchoring pattern size deviation determination system for obtaining maximum depth of focus provided in the embodiments of this application can be found in the corresponding descriptions in the optimal anchoring pattern size deviation determination method for obtaining maximum depth of focus provided in the above embodiments, and will not be repeated here.

[0143] By applying the technical solutions of the above embodiments, the optimal anchor pattern size deviation determination system for obtaining the maximum depth of focus provided by the above embodiments can, after initial mask correction, acquire the available common process window through the acquisition module, and the identification module identifies the exposure dose corresponding to the maximum usable depth of focus under a preset exposure threshold margin. The function module then creates an optimization function between the anchor pattern size deviation and the exposure threshold. The calculation module calculates the optimal anchor pattern size deviation based on the relationship between the exposure dose corresponding to the maximum usable depth of focus and the optimization function. The correction module then updates the lithography model using the optimal anchor pattern size deviation, modifies the loss function in the mask correction process, and re-executes the mask correction to obtain the maximum usable depth of focus and the corresponding mask correction result. The system can quickly obtain the optimal anchor pattern size deviation and the achieved maximum usable depth of focus through an automated calculation process, saving calculation time, improving optimization efficiency, and reducing the probability of errors.

[0144] like Figure 8 As shown in the illustration, this application also provides a computer device, specifically a personal computer, server, network device, etc. This computer device includes a bus, processor, memory, and communication interface, and may also include input / output interfaces and a display device. The processor of this computer device provides computing and control capabilities. The memory of this computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of this computer device stores location information. The network interface of this computer device is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the steps in the various method embodiments.

[0145] Those skilled in the art will understand that the structure of the computer device described above is only a partial structure related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. A specific computer device may include more or fewer components, or combine certain components, or have different component arrangements.

[0146] In one embodiment, a computer-readable storage medium is also provided, which may be non-volatile or volatile, and a computer program is stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0147] In one embodiment, a computer program product is also provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0148] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0149] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods.

[0150] Any references to memory, database, or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc.

[0151] Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can take many forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0152] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchain. The processors involved in the embodiments provided in this application may be, but are not limited to, general-purpose processors, graphics processors, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc.

[0153] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0154] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for determining the optimal anchoring pattern size deviation to obtain the maximum depth of focus, characterized in that, The method includes: The available common process window data after initial mask correction is obtained. The available common process window data includes the available common process window when the exposure dose is fixed at multiple dose values ​​after mask correction under the initial anchoring pattern size deviation. Using the available common process window data, identify the exposure dose corresponding to the maximum available depth of focus under the preset exposure margin; An optimization function is created to characterize the functional relationship between the anchoring pattern size deviation and the exposure threshold; the change in the exposure threshold and the change in the exposure dose are opposites of each other. The optimal anchoring pattern size deviation is calculated based on the optimization function and the exposure dose; The lithography model is updated using the optimal anchor pattern size deviation, and the mask correction is re-executed based on the updated lithography model.

2. The method according to claim 1, characterized in that, Obtain the available common process window data after initial mask correction, including: A photolithography model is established based on the initial anchoring pattern size deviation; An initial mask correction is performed based on the photolithography model to generate initial mask correction result data, which includes the pattern result after initial mask correction. A process window for drawing pattern results based on initial mask correction data, the process window including dose values ​​of defocus amount and exposure dose that are related; Determine the available common process windows within the process window; Establish the association between the available common process window and the dose value to generate the available common process window data.

3. The method according to claim 1, characterized in that, Using the available common process window data, identify the exposure dose corresponding to the maximum available depth of focus under the preset exposure margin, including: Obtain the preset exposure margin; Based on the available common process window data and the preset exposure margin, plot the linewidth variation curves under different dose values ​​and focal lengths; From the linewidth variation curve, find the maximum depth of focus range within the acceptable linewidth variation range; Based on the linewidth variation curve, determine the corresponding exposure dose within the maximum usable depth of focus range.

4. The method according to claim 3, characterized in that, Based on the linewidth variation curve, determine the corresponding exposure dose within the maximum usable depth of focus range, including: Based on the linewidth variation curve, determine the corresponding dose value range within the maximum usable depth of focus; Photolithography simulations are performed based on the maximum depth of focus range and the dose value range to simulate the imaging effects under different exposure doses and focal lengths. The dose value range is corrected based on the imaging effect, and the exposure dose corresponding to the maximum usable depth of focus is extracted within the dose value range.

5. The method according to claim 1, characterized in that, Create optimization functions, including: Construct anchoring patterns; By modifying the anchor pattern size deviation, the exposure thresholds corresponding to multiple anchor pattern size deviations are calculated; The optimized function is generated by fitting a functional relationship between the anchor pattern size deviation and the exposure threshold.

6. The method according to claim 1, characterized in that, The method further includes: Obtain the initial exposure threshold and initial exposure dose; Set the exposure dose change value according to the preset adjustment step size; Calculate the adjusted exposure dose based on the initial exposure dose and the change in exposure dose; Find the light intensity data at different locations corresponding to the adjusted exposure dose according to the light intensity distribution curve; The exposure threshold change value is calculated based on the light intensity data to determine the correspondence between the exposure threshold change value and the exposure dose change value.

7. The method according to claim 1, characterized in that, The optimal anchoring pattern size deviation is calculated based on the optimization function and the exposure dose, including: Calculate the inverse function of the optimization function; Obtain the exposure dose corresponding to the maximum usable depth of focus and the correspondence between the change value of the exposure threshold and the change value of the exposure dose; The optimal anchoring pattern size deviation is calculated based on the inverse function of the optimization function, the exposure dose, and the corresponding relationship.

8. The method according to claim 7, characterized in that, The optimal anchoring pattern size deviation is calculated based on the inverse function of the optimization function, the exposure dose, and the corresponding relationship, including: Obtain the initial exposure threshold and the change in exposure dose; An intermediate variable is calculated based on the change in exposure dose, and the intermediate variable is the difference obtained by subtracting the change in exposure dose from 1. Calculate the product of the intermediate variable and the initial exposure threshold; The product is input into the inverse function of the optimization function to obtain the optimal anchoring pattern size deviation.

9. The method according to claim 1, characterized in that, The lithography model is updated using the optimal anchor pattern size deviation, and mask correction is re-performed based on the updated lithography model, including: An updated model is established based on the optimal anchoring pattern size deviation; Synchronously update the loss function settings during the mask correction process; If the loss function includes the result information when the exposure dose changes, update the exposure dose change value according to the initial value of the exposure dose change and the exposure dose change value corresponding to the maximum available depth of focus; Mask correction is performed based on the updated model and the loss function to output the final mask pattern and result process window.

10. A system for determining the optimal anchoring pattern size deviation to obtain maximum depth of focus, characterized in that, The method system: The acquisition module is used to acquire available common process window data after initial mask correction. The available common process window data includes available common process windows when the exposure dose is fixed at multiple dose values ​​after mask correction under the initial anchoring pattern size deviation. The identification module is used to identify the exposure dose corresponding to the maximum available depth of focus under the preset exposure margin using the available common process window data. The function module is used to create an optimization function that characterizes the functional relationship between the anchoring pattern size deviation and the exposure threshold; the change in the exposure threshold and the change in the exposure dose are opposites of each other. The calculation module is used to calculate the optimal anchoring pattern size deviation based on the optimization function and the exposure dose; The correction module is used to update the lithography model using the optimal anchoring pattern size deviation, and to re-perform mask correction based on the updated lithography model.

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