Methods, apparatus and storage media for electron beam exposure correction

Abstract

Embodiments of this disclosure provide a method, apparatus, and storage medium for electron beam exposure correction. The method includes: determining a first dose distribution for electron beam exposure by performing electron beam proximity effect correction on a target pattern based on a predetermined dose distribution, the first dose distribution indicating a set of dose adjustment values ​​for compensating for scattering effects during electron beam exposure on the target pattern; determining a second dose distribution for electron beam exposure by performing electron beam haze effect correction on the target pattern based on the first dose distribution, the second dose distribution indicating a set of dose adjustment values ​​for compensating for haze effects during electron beam exposure on the target pattern; and determining a target dose distribution for electron beam exposure by performing electron beam proximity effect correction on the target pattern based on the first and second dose distributions.

Description

Technical Field

[0001] The embodiments of this disclosure are primarily related to the field of semiconductor technology, and more specifically, to methods, apparatus, and storage media for electron beam exposure correction. Background Technology

[0002] As the critical dimension (CD) and half-pitch (HP) of integrated circuits continue to shrink, the complexity and cost of equipment and masks for deep ultraviolet (DUV) optical projection lithography at nanoscale nodes have increased dramatically to overcome subwavelength diffraction. Electron beam lithography (EBL), as a maskless, high-precision nanofabrication technology, directly writes patterns onto a substrate coated with electron resist using a focused electron beam. With its theoretically excellent resolution, it is considered a preferred next-generation technology for achieving high-resolution patterning in semiconductor processes, and its application value is extremely high. Summary of the Invention

[0003] In a first aspect of this disclosure, a method for electron beam exposure correction is provided. The method includes: determining a first dose distribution for electron beam exposure by performing electron beam proximity effect correction on a target pattern based on a predetermined dose distribution, the first dose distribution indicating a set of dose adjustment values ​​for compensating for scattering effects during electron beam exposure on the target pattern; determining a second dose distribution for electron beam exposure by performing electron beam haze effect correction on the target pattern based on the first dose distribution, the second dose distribution indicating a set of dose adjustment values ​​for compensating for haze effects during electron beam exposure on the target pattern; and determining a target dose distribution for electron beam exposure by performing electron beam proximity effect correction on the target pattern based on the first and second dose distributions.

[0004] In a second aspect of this disclosure, an electronic device is provided. The electronic device includes a processor and a memory coupled to the processor. The memory has instructions stored therein, which, when executed by the processor, cause the electronic device to perform a method according to a first aspect of this disclosure.

[0005] In a third aspect of this disclosure, a computer-readable storage medium is provided. A computer program is stored on the computer-readable storage medium. When executed by a processor, the computer program implements the method according to a first aspect of this disclosure.

[0006] As will be understood from the following description, according to embodiments of this disclosure, based on a predetermined dose distribution, an electron beam proximity effect correction is performed on the target layout to determine a first dose distribution for electron beam exposure, wherein the first dose distribution indicates a set of dose adjustment values ​​for compensating for scattering effects during electron beam exposure on the target layout. Further, based on the first dose distribution, an electron beam haze effect correction is performed on the target layout to determine a second dose distribution for electron beam exposure, wherein the second dose distribution indicates a set of dose adjustment values ​​for compensating for haze effects during electron beam exposure on the target layout. Then, based on the first and second dose distributions, an electron beam proximity effect correction is performed on the target layout to determine a target dose distribution for electron beam exposure. Thus, by combining electron beam proximity effect correction with electron beam haze effect correction, the overall correction effect can be effectively improved, the global critical dimension error (Global CD Error) caused by haze effects can be reduced, and the critical dimension uniformity (CDU) can be improved.

[0007] It should be understood that the content described in this summary section is not intended to limit the key or essential features of the embodiments of this disclosure, nor is it intended to restrict the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0008] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein: Figure 1 A schematic diagram of an example environment in which the various embodiments of this disclosure can be implemented is shown; Figure 2 A flowchart is shown for a process for electron beam exposure correction according to some embodiments of the present disclosure; Figure 3 A schematic diagram illustrating an example of a first dose distribution for electron beam exposure according to some embodiments of the present disclosure is shown; Figure 4 A schematic diagram of a process for determining edge placement error according to some embodiments of the present disclosure is shown; Figure 5 A flowchart is shown illustrating a process for electron beam proximity effect correction according to some embodiments of the present disclosure; Figure 6 A schematic diagram illustrating an example of a second dose distribution for electron beam exposure according to some embodiments of the present disclosure is shown; Figure 7A schematic diagram illustrating an example of a target dose distribution for electron beam exposure according to some embodiments of the present disclosure is shown; and Figure 8 A block diagram of an electronic device in which one or more embodiments of the present disclosure may be implemented is shown. Detailed Implementation

[0009] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0010] In the description of embodiments of this disclosure, the term "comprising" and similar terms should be understood as open-ended inclusion, i.e., "including but not limited to". The term "based on" should be understood as "at least partially based on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first", "second", etc., may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0011] The following will describe in detail various example implementations of this scheme with reference to the accompanying drawings.

[0012] First see Figure 1 It illustrates a schematic diagram of an example environment 100 in which the various embodiments of this disclosure can be implemented. For example... Figure 1 As shown, the example environment 100 may generally include electronic device 110.

[0013] In some embodiments, the electronic device 110 can receive input information and output feedback information. In some embodiments, the input information can be design layout data 120. For example, the design layout data 120 is a target layout that needs to be corrected by electron beam exposure. The electronic device 110 can perform corresponding processing on the design layout data 120 and output corresponding processing results 130. In some embodiments, the processing on the design layout data 120 can be based on electron beam proximity effect correction (PEC) and / or electron beam fogging effect correction (FEC), and correspondingly, the processing result 130 can be dose distribution data for the design layout data 120.

[0014] In example environment 100, electronic device 110 can be any type of computing-capable device, including terminal devices or server devices. Terminal devices can be any type of mobile terminal, fixed terminal, or portable terminal, including mobile phones, desktop computers, laptop computers, notebook computers, netbook computers, tablet computers, media computers, multimedia tablets, personal communication system (PCS) devices, personal navigation devices, personal digital assistants (PDAs), audio / video players, digital cameras / camcorders, positioning devices, television receivers, radio receivers, e-book devices, gaming devices, or any combination of the foregoing, including accessories and peripherals of these devices or any combination thereof. Server devices can include, for example, computing systems / servers, such as mainframes, edge computing nodes, computing devices in cloud environments, and so on.

[0015] It should be understood that the structure and function of environment 100 are described for illustrative purposes only and do not imply any limitation on the scope of this disclosure. Exemplary embodiments according to this disclosure will now be described in detail with reference to the accompanying drawings.

[0016] As briefly mentioned above, direct-write electron beam lithography, as a maskless high-precision nanofabrication technology, directly writes patterns onto a substrate coated with electron resist using a focused electron beam, theoretically offering excellent resolution. However, in electron beam lithography, when high-energy electrons bombard the photoresist, electron scattering occurs due to the Coulomb effect. Some electrons (e.g., backscattered electrons, secondary electrons, etc.) diffuse into non-exposed areas, resulting in overexposure in non-target areas within a range of tens to hundreds of micrometers, leading to pattern distortion and linewidth errors. This overexposure effect caused by electron scattering is known as the fogging effect. This fogging effect, along with the proximity effect (short-range interference), constitutes the main source of interference in dose distribution during electron beam exposure.

[0017] As an example, the fogging effect has the following characteristics: the influence range can reach hundreds of micrometers, which is significantly greater than the proximity effect; in high-density patterned areas, the superposition effect of scattered electrons is more prominent, which will further aggravate the local exposure dose deviation; it is closely related to the substrate material (e.g., silicon-based), the type and thickness of the resist, and the backscattering effect of high atomic number materials is more significant.

[0018] To address the characteristics of the aforementioned fogging effect, hardware methods (e.g., antireflecting plates) or software methods (e.g., dose correction software) can typically be used to reduce its impact. However, hardware methods can only reduce part of the fogging effect and cannot completely eliminate it. Furthermore, software methods are prone to producing significant errors in areas with drastic changes in image density.

[0019] Therefore, embodiments of this disclosure propose a scheme for electron beam exposure correction. According to embodiments of this disclosure, a first dose distribution for electron beam exposure is determined by performing electron beam proximity effect correction on a target pattern based on a predetermined dose distribution. Here, the first dose distribution indicates a set of dose adjustment values ​​for compensating for scattering effects during electron beam exposure on the target pattern. Further, based on the first dose distribution, a second dose distribution for electron beam exposure is determined by performing electron beam haze effect correction on the target pattern. Here, the second dose distribution indicates a set of dose adjustment values ​​for compensating for haze effects during electron beam exposure on the target pattern. Then, based on the first and second dose distributions, an electron beam proximity effect correction is performed on the target pattern to determine a target dose distribution for electron beam exposure.

[0020] According to embodiments of this disclosure, by combining electron beam proximity effect correction with electron beam fogging effect correction, the overall correction effect can be effectively improved, the global critical dimension error caused by fogging effect can be reduced, and the consistency of critical dimensions can be improved.

[0021] The following section provides a detailed description of various example implementations of this scheme, with reference to the accompanying drawings.

[0022] Figure 2 A flowchart of a process 200 for electron beam exposure correction according to some embodiments of the present disclosure is shown. In some embodiments, process 200 may be performed by, for example... Figure 1 The illustrated electronic device 110 performs this operation. It should be understood that process 200 may also include additional boxes not shown and / or some (or more) of the boxes shown may be omitted; the scope of this disclosure is not limited in this respect. The following is in conjunction with... Figure 1 The process 200 is described in detail.

[0023] In block 210, electronic device 110 determines a first dose distribution for electron beam exposure by performing electron beam proximity effect correction on a target pattern based on a predetermined dose distribution. This first dose distribution indicates a set of dose adjustment values ​​for compensating for scattering effects during electron beam exposure on the target pattern. In some embodiments, scattering effects may include forward scattering and backscattering effects. In other words, the first dose distribution may indicate a set of dose adjustment values ​​for compensating for both forward scattering and backscattering effects during electron beam exposure on the target pattern. This allows for a more accurate dose input for subsequent electron beam fogging effect correction.

[0024] Typically, the target pattern is on the order of centimeters. In electron beam proximity correction, the forward scattering convolution kernel is on the order of nanometers, and the backscattering convolution kernel is on the order of micrometers. Because the target pattern, the forward scattering convolution kernel, and the backscattering convolution kernel differ significantly in size, the target pattern needs to be segmented. Then, electron beam proximity correction is performed on multiple regions obtained from the segmentation of the target pattern to determine the initial dose distribution for the target pattern.

[0025] In some embodiments, the electronic device 110 can divide a target layout into multiple regions. The segmentation of the target layout can be implemented in any suitable manner. For example, such implementations may include, but are not limited to: segmentation based on the geometric dimensions or area of ​​the target layout, segmentation based on the graphic density distribution characteristics of the target layout, segmentation based on the effective range of the convolution kernel related to electron beam proximity correction, segmentation based on predetermined process requirements or main field boundaries, segmentation based on the functional modules or pattern types of the target layout, and so on. It should be understood that the above-described segmentation methods for the target layout are merely exemplary and are not intended to be limiting. Other suitable segmentation methods can also be used in practice, and the embodiments of this disclosure are not limited in this respect. After segmenting the target layout, the electronic device 110 can determine the dose distribution associated with each of the multiple regions by performing electron beam proximity correction on the multiple regions obtained through segmentation of the target layout based on a predetermined dose distribution, and determine a first dose distribution based on the dose distribution associated with each of the multiple regions.

[0026] In some embodiments, after the target layout is segmented, the electronic device 110 can perform electron beam proximity effect correction for multiple regions respectively. As an example, the electronic device 110 can adjust a predetermined dose distribution based on a scattering model during electron beam exposure to determine local dose distributions corresponding to the multiple regions respectively. The predetermined dose distribution may include an initial exposure dose distribution set for the target layout.

[0027] In some examples, the scattering model may include a forward scattering model and a backscattering model. The electronic device 110 can determine the exposure energy distribution of the target pattern at each region due to electron scattering based on the forward scattering model and the backscattering model. Further, the electronic device 110 can generate a predicted image based on the determined exposure energy distribution, and adjust the predetermined dose distribution based on the error between the predicted image and the target pattern to determine the dose distribution corresponding to each region. Further still, the electronic device 110 can stitch together the dose distributions corresponding to each region to obtain a first dose distribution.

[0028] Taking the segmentation of the target field area based on the main field boundary as an example, the electronic device 110 can segment the target field area based on the main field boundary corresponding to the target field area to obtain multiple main field areas. Further, the electronic device 110 can perform electron beam proximity effect correction for each main field area based on a predetermined dose distribution to obtain the dose distribution corresponding to each main field area. It should be understood that the predetermined dose distribution can be set for the entire target field area or for each of the multiple main field areas. The embodiments of this disclosure are not limited in this respect.

[0029] Next, the electronic device 110 can stitch together the dose distributions corresponding to each main field region to obtain the first dose distribution described above. The stitching process for the dose distributions corresponding to each main field region can be implemented in any suitable manner. For example, such implementations may include, but are not limited to: directly stitching the dose distributions based on the position coordinates of each main field region; performing dose-weighted fusion processing in the overlapping area of ​​adjacent main field regions; performing dose smoothing transition processing based on the boundary matching relationship of adjacent main field regions; and correcting the dose distribution at the stitching boundary based on the process parameters of electron beam exposure, etc. It should be understood that the above-described stitching methods for the dose distributions corresponding to each main field region are merely exemplary and are not intended to be limiting. In practice, any other suitable stitching method can be used, and the embodiments of this disclosure are not limited in this respect.

[0030] As an example, see Figure 3 This illustrates an example 300 of a first dose distribution for electron beam exposure according to some embodiments of the present disclosure. Figure 3 As shown, Figure 3 The left side shows the target layout 310, and the right side shows enlarged views 322 and 332 of region 321 and region 331 in the target layout 310. Both enlarged views 322 and 332 include multiple grid cells, and each grid cell is labeled with a corresponding dose factor.

[0031] As another example, the first dose distribution can also be represented in tabular form. For example, the first dose distribution for electron beam exposure can be shown in Table 1 below.

[0032] Table 1

[0033] In Table 1, Dose_level represents the dose level, and Dose_factor represents the dose factor. The dose level can be used to represent the actual exposure dose used in the current area (e.g., dose value, dose level, etc.), and is a dose parameter that can be directly used for electron beam exposure. The dose factor is usually a dimensionless correction coefficient used to scale, compensate, or correct the reference exposure dose.

[0034] In some embodiments, for one of a plurality of regions obtained by dividing a target layout (also referred to as a "first region" or "target region"), the electronic device 110 may determine a dose distribution (also referred to as a "third dose distribution" or "initial dose distribution") for the target region based on a point spread function, a predetermined dose distribution, and a pattern associated with the target region. The point spread function may be used to describe the energy diffusion distribution of the electron beam on the substrate, and the pattern associated with the target region may be a polygonal pattern unit for electron beam exposure, and such polygonal pattern units may indicate the areas and / or locations within the target region that need to be exposed.

[0035] In some embodiments, the electronic device 110 can select a suitable point spread function from various types of point spread functions based on electron beam energy, beam spot size, substrate material, accuracy requirements, etc. In some embodiments, the pattern associated with the target region can be a polygonal graphic unit extracted by the electronic device 110 from the target region. In some embodiments, the predetermined dose distribution can include parameters such as dose level and dose factor.

[0036] In some embodiments, the electronic device 110 can determine a predicted image for a target region based on the point spread function and the third dose distribution described above. This predicted image can indicate the expected graphic result obtained after electron beam exposure of the target region using the third dose distribution. For example, the electronic device 110 can perform a convolution operation on the point spread function and the third dose distribution to obtain the predicted image for the target region.

[0037] Furthermore, the electronic device 110 can determine the edge placement error of the predicted image for the target region. For example, see... Figure 4 This illustrates a schematic diagram of a process 400 for determining edge placement error according to some embodiments of the present disclosure. In some embodiments, process 400 may be performed by, for example... Figure 1 The electronic device 110 shown is performing this operation. The following is in conjunction with... Figure 1 The process 400 is described in detail.

[0038] like Figure 4As shown, the electronic device 110 can select the location on the graphic associated with the target region where the edge placement error needs to be measured, and determine the position (px, py) of the measurement point in the graphic associated with the target region based on a predetermined correction box. Then, the electronic device 110 uses linear interpolation to obtain the energy intensity (intensity (px, py) at the measurement location on the graphic associated with the target region. Next, the electronic device 110 determines the gradient (px, py) at the measurement location, and determines the energy intensity (px', py') at the new measurement location along the gradient (px, py) direction with a predetermined step size, until the intensity (px', py') reaches an energy threshold. Finally, the electronic device 110 determines the distance between the new measurement location (px', py') and the original measurement location (px, py) based on the pixel size of the graphic associated with the target region, and determines this distance as the edge placement error of the predicted image for the target region.

[0039] If the edge placement error meets a first predetermined condition, the electronic device 110 can determine that the third dose distribution is a dose distribution associated with the target region. If the edge placement error does not meet the first predetermined condition, the electronic device 110 can adjust the third dose distribution until the edge placement error meets the first predetermined condition, and determine that the adjusted third dose distribution that meets the first predetermined condition is a dose distribution associated with the target region. In some embodiments, the first predetermined condition may include an error threshold or a maximum number of iterations. Specifically, if the edge placement error meets the error threshold (e.g., the edge placement error is less than the error threshold), or the number of iterations is greater than the maximum number of iterations, the first predetermined condition is considered to be met; otherwise, the first predetermined condition is considered not met. It should be noted that the process of determining the edge placement error by predicting the image can be considered as one iteration.

[0040] For example, see Figure 5 The document illustrates a flowchart of a process 500 for electron beam proximity effect correction according to some embodiments of the present disclosure. In some embodiments, process 500 may be performed by, for example... Figure 1 The electronic device 110 shown is performing this operation. The following is in conjunction with... Figure 1 The process 500 is described in detail.

[0041] like Figure 5As shown, in box 511, electronic device 110 loads a point spread function and a graphics unit associated with the target region. In box 512, electronic device 110 loads a predetermined dose distribution. In box 513, electronic device 110 performs an initialization process based on the loaded point spread function, the graphics unit associated with the target region, and the predetermined dose distribution to determine an initial dose distribution for the target region. In box 514, electronic device 110 obtains a predicted image for the target region by performing a convolution operation on the point spread function and the initial dose distribution.

[0042] In some embodiments, the electronic device 110 may further determine the edge placement error of the predicted image relative to a first region and statistical indices of the dose values ​​corresponding to the plurality of electron beams associated with the first region. The edge placement error can be used to characterize the degree of deviation between the predicted image and the target pattern. The statistical indices can be used to characterize the distribution of the dose values ​​corresponding to the plurality of electron beams. For example, the statistical indices may include at least one of dose variance, dose dynamic range, dose value dispersion, etc.

[0043] Furthermore, the electronic device 110 can adjust the third dose distribution based on at least one of edge placement error and statistical indicators to determine the dose distribution associated with the first region. This not only reduces the deviation between the predicted exposure result and the target pattern but also improves the stability of the dose distribution during electron beam exposure, thereby enhancing the manufacturability and exposure accuracy of the electron beam exposure results.

[0044] For example, continue to refer to Figure 5 In box 515, electronic device 110 determines the edge placement error of the predicted image for the target region. In box 516, electronic device 110 determines whether the current iteration number is greater than the maximum iteration number, or whether the edge placement error is less than an error threshold. If the current iteration number is less than or equal to the maximum iteration number, or the edge placement error is greater than or equal to the error threshold, process 500 proceeds to box 517. In box 517, electronic device 110 adjusts the initial dose distribution and increments the iteration number by 1. If the current iteration number is greater than the maximum iteration number, or the edge placement error is less than the error threshold, electronic device 110 can determine the initial dose distribution as the dose distribution associated with the target region.

[0045] In some embodiments, if the edge placement error does not meet the first predetermined condition, the electronic device 110 may further adjust the predetermined dose distribution to adjust the initial dose distribution based on the adjusted predetermined dose distribution until the edge placement error meets the first predetermined condition, and determine the adjusted third dose distribution that meets the first predetermined condition as the dose distribution associated with the target region.

[0046] It should be understood that, based on the above process, the dose distributions associated with each region in the multiple regions obtained by segmenting the target map can be determined, and the dose distributions corresponding to each region can be spliced ​​together to obtain the first dose distribution mentioned above.

[0047] In some embodiments, after determining the dose distribution associated with the target region, the electronic device 110 can further verify whether the dose distribution meets process requirements. For example, the electronic device 110 can again determine whether the edge placement error is less than an error threshold. If the edge placement error is greater than or equal to the error threshold, it indicates that the dose distribution associated with the target region was determined under the condition that the number of iterations exceeds the maximum number of iterations. In this case, the electronic device 110 can provide an error message to indicate that the pattern error still does not meet the process requirements.

[0048] In some embodiments, the electronic device 110 may adjust the beam spot size of a plurality of electron beams associated with a first region in response to a statistical indicator not meeting a second predetermined condition. The second predetermined condition may indicate that the statistical indicator meets a predetermined dose distribution requirement. For example, the predetermined dose distribution requirement may include: dose value fluctuation less than a predetermined range, dose standard deviation less than a standard deviation threshold, etc.

[0049] As an example, if the edge placement error is less than an error threshold, it indicates that the pattern error meets the process requirements. At this time, the electronic device 110 can determine statistical indices of the dose values ​​corresponding to the multiple electron beams associated with the target region based on the third dose distribution. If the statistical indices do not meet the second predetermined condition, the electronic device 110 can adjust the beam spot size of the multiple electron beams associated with the target region until the statistical indices meet the second predetermined condition. Then, the electronic device 110 can adjust the third dose distribution based on the dose values ​​corresponding to the adjusted beam spot size of the multiple electron beams associated with the target region. If the statistical indices meet the second predetermined condition, the electronic device 110 can provide the dose values ​​corresponding to the multiple electron beams associated with the target region.

[0050] For example, see [link to example]. Figure 5In box 521, electronic device 110 determines whether the edge placement error is less than an error threshold. If the edge placement error is greater than or equal to the error threshold, process 500 proceeds to box 522. In box 522, electronic device 110 provides an error message. If the edge placement error is less than the error threshold, in box 523, electronic device 110 determines the dose value and dose standard deviation of the electron beams associated with the target region. In box 524, electronic device 110 determines whether the dose standard deviation is less than a standard deviation threshold. If the dose standard deviation is less than the standard deviation threshold, process 500 proceeds to box 525. In box 525, electronic device 110 provides the dose value corresponding to each electron beam associated with the target region. If the dose standard deviation is greater than or equal to the standard deviation threshold, process 500 proceeds to box 526. In box 526, electronic device 110 invokes graphical control software to divide the target region into smaller regions, and executes boxes 523 and 524 again until the dose standard deviation is less than the standard deviation threshold, and finally provides the dose value corresponding to each electron beam.

[0051] Return to reference Figure 2 In box 220, the electronic device 110 determines a second dose distribution for electron beam exposure by performing electron beam fogging effect correction on the target layout using a first dose distribution as an initial dose distribution. This second dose distribution indicates a set of dose adjustment values ​​used to compensate for fogging effects during electron beam exposure on the target layout.

[0052] In some embodiments, since the convolution kernel associated with electron beam atomization effect correction is typically on the centimeter scale, when determining the second dose distribution, it is necessary to downsample the first dose distribution and determine the second dose distribution by performing electron beam atomization effect correction on the target layout based on the downsampled first dose distribution.

[0053] In some examples, the electronic device 110 can perform a convolution operation on the downsampled first dose distribution based on a convolution kernel corresponding to the electron beam haze effect to determine the exposure dose distribution caused by long-range electron beam scattering. Further, the electronic device 110 can compensate and adjust the dose values ​​in the downsampled first dose distribution based on the determined exposure dose distribution to determine a second dose distribution. Since the first dose distribution already characterizes the local exposure dose after electron beam proximity effect correction, performing haze effect correction based on the first dose distribution can more accurately reflect the global exposure energy distribution in the target plot.

[0054] As an example, see Figure 6This illustrates an example 600 of a second dose distribution for electron beam exposure according to some embodiments of the present disclosure. As another example, the second dose distribution can also be represented in tabular form. For example, the second dose distribution for electron beam exposure can be shown in Table 2 below.

[0055] Table 2

[0056] In Table 2, Dose_level represents the dose level, and Dose_factor represents the dose factor.

[0057] In box 230, electronic device 110 determines a target dose distribution for electron beam exposure by performing electron beam proximity effect correction on the target pattern based on a first dose distribution and a second dose distribution. Here, the target dose distribution indicates a set of dose adjustment values ​​used to compensate for scattering and fogging effects during electron beam exposure on the target pattern.

[0058] In some embodiments, since the electronic device 110 downsamples the first dose distribution when determining the second dose distribution, the electronic device 110 needs to upsample the second dose distribution to determine the processed second dose distribution when determining the target dose distribution, and then determine the target dose distribution by performing electron beam proximity correction on the target pattern based on the first dose distribution and the processed second dose distribution.

[0059] In some embodiments, the electronic device 110 can determine an input dose distribution for subsequent electron beam proximity effect correction based on a first dose distribution and a processed second dose distribution. For example, the electronic device 110 can superimpose the first dose distribution and the processed second dose distribution as the input dose distribution for electron beam proximity effect correction. The first dose distribution can characterize the compensation result for electron beam scattering effects, and the processed second dose distribution can characterize the compensation result for electron beam fogging effects. By incorporating both types of compensation results into the subsequent correction process, the subsequent correction can simultaneously consider the effects of local scattering effects and global fogging effects on the exposure dose.

[0060] In some examples, the superposition of the first dose distribution and the processed second dose distribution may include an addition operation. For example, electronic device 110 may add the dose values ​​corresponding to each position in the first dose distribution to the dose values ​​at the corresponding positions in the processed second dose distribution to generate an input dose distribution.

[0061] In other examples, the overlay may also include a weighted fusion operation. For instance, electronic device 110 may weight and combine a first dose distribution and a processed second dose distribution according to predetermined weights to generate an input dose distribution. The predetermined weights may be determined based on target process parameters, pattern density distribution in the target layout, electron beam exposure system parameters, and predetermined exposure accuracy requirements.

[0062] The input dose distribution obtained in the above manner can be used as the initial dose distribution map for subsequent joint correction processes. Unlike the traditional electron beam proximity effect correction, which directly uses the target layout rasterized image as the initial input, the initial dose distribution map in this embodiment already includes proximity effect compensation results and fogging effect compensation results, thereby providing a more accurate initial state for subsequent joint correction.

[0063] In some embodiments, the electronic device 110 can utilize an electron beam exposure correction model to perform iterative calculations based on the input dose distribution to determine the target dose distribution. The electron beam exposure correction model includes a proximity effect compensation term and a haze effect compensation term. The proximity effect compensation term characterizes the local dose deviation caused by forward scattering and backscattering effects during electron beam exposure and is used to compensate for this local dose deviation. The haze effect compensation term characterizes the dose accumulation effect caused by long-distance electron scattering and is used to compensate for this type of dose deviation. Compared to electron beam proximity effect correction that only considers proximity effects, by introducing a haze effect compensation term into the electron beam exposure correction model, the electronic device 110 can optimize local exposure accuracy while also considering global dose uniformity, thereby improving the overall correction accuracy of the target pattern.

[0064] As an example, the electron beam exposure correction model can be expressed by the following formula:

[0065] in, The input dose distribution is obtained by superimposing the first dose distribution and the processed second dose distribution, and can also be called the initial dose distribution map. and These represent the dose scaling factors for the nth and (n+1)th iterations, respectively. The influencing factor of forward scattering effect, The influencing factor of backscattering effect, These are the factors influencing the fogging effect (e.g., the corresponding Gaussian convolution kernel or other spatial influence functions, respectively). and These are the weighting coefficients corresponding to the proximity effect and the fogging effect. This indicates a convolution operation.

[0066] In some embodiments, the proximity effect compensation term may include compensation terms corresponding to the forward scattering effect and the backscattering effect, for example... and The atomization effect compensation term can include a compensation term corresponding to the atomization effect, for example... Specifically, the influence factor and weighting coefficients corresponding to the fogging effect compensation term are not components of the traditional electron beam proximity effect correction model, but rather compensation terms introduced to characterize the cumulative dose effect caused by fogging. This is achieved by introducing influence factors into the electron beam exposure correction model. and the corresponding weight parameters This allows for the comprehensive consideration of the effects of proximity effect compensation and fogging effect during the proximity effect correction process, thereby improving the overall accuracy of electron beam exposure correction results.

[0067] In some examples, during the iteration process, the electronic device 110 can use the input dose distribution map P as the initial input for the iterative calculation, and based on a preset initial dose scaling factor. Determine the initial iteration state. For example, the initial dose scaling factor. This can be a preset default value, an empirical value, or a value determined based on the input dose distribution map. Electronic device 110 can also use the dose scaling factor corresponding to the current iteration. The dose contributions corresponding to the proximity effect compensation term and the nebulization effect compensation term are calculated separately, and the dose scaling factor corresponding to the next iteration is determined using the above iterative formula. .

[0068] In determining Then, the electronic device 110 can determine whether a predetermined convergence condition is met. For example, the predetermined convergence condition may include the number of iterations reaching a threshold or the change in the dose scaling factor being less than a threshold. If the predetermined convergence condition is not met, the electronic device 110 can... The new dose scaling factor is used to continue the next iteration. If a predetermined convergence condition is met, the electronic device 110 can determine the target dose distribution based on the dose scaling factor corresponding to the current iteration. For example, the electronic device 110 can determine the target dose distribution based on the pixel-by-pixel product of the final converged dose scaling factor and the input dose distribution.

[0069] As an example, see Figure 7 This illustrates an example 700 of a target dose distribution for electron beam exposure according to some embodiments of the present disclosure. As another example, the target dose distribution can also be represented in tabular form. For example, the target dose distribution for electron beam exposure can be shown in Table 3 below.

[0070] Table 3

[0071] In Table 3, Dose_level represents the dose level, and Dose_factor represents the dose factor.

[0072] In summary, by combining electron beam proximity effect correction with electron beam atomization effect correction, the generated target dose distribution can effectively improve the correction effect (e.g., accuracy) of electron beam proximity effect correction, while reducing global critical dimension errors caused by atomization effect and improving the consistency of critical dimensions.

[0073] Figure 8 A block diagram is shown of an electronic device 800 in which one or more embodiments of the present disclosure may be implemented. The electronic device 800 may, for example, be used to implement... Figure 1 The electronic device 110 shown. It should be understood that, Figure 8 The electronic device 800 shown is merely exemplary and should not be construed as limiting the functionality and scope of the embodiments described herein.

[0074] like Figure 8 As shown, electronic device 800 is in the form of a general-purpose electronic device. Components of electronic device 800 may include, but are not limited to, one or more processors 810 or processing units, memory 820, storage device 830, one or more communication units 840, one or more input devices 850, and one or more output devices 860. The processing unit may be a physical or virtual processor and is capable of performing various processes according to programs stored in memory 820. In a multiprocessor system, multiple processing units execute computer-executable instructions in parallel to improve the parallel processing capability of electronic device 800.

[0075] Electronic device 800 typically includes multiple computer storage media. Such media can be any available media accessible to electronic device 800, including but not limited to volatile and non-volatile media, removable and non-removable media. Memory 820 can be volatile memory (e.g., registers, cache, random access memory (RAM)), non-volatile memory (e.g., read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory), or some combination thereof. Storage device 830 can be a removable or non-removable medium and can include machine-readable media, such as flash drives, disks, or any other media that can be used to store information and / or data (e.g., training data for training) and can be accessed within electronic device 800.

[0076] Electronic device 800 may further include additional removable / non-removable, volatile / non-volatile storage media. Although not explicitly stated... Figure 8As shown, disk drives for reading from or writing to removable, non-volatile disks (e.g., "floppy disks") and optical disk drives for reading from or writing to removable, non-volatile optical disks can be provided. In these cases, each drive can be connected to a bus (not shown) via one or more data media interfaces. Memory 820 may include computer program product 825 having one or more program modules configured to perform various methods or actions of various embodiments of this disclosure.

[0077] The communication unit 840 enables communication with other electronic devices via a communication medium. Additionally, the functionality of the components of the electronic device 800 can be implemented using a single computing cluster or multiple computing machines capable of communicating via communication connections. Therefore, the electronic device 800 can operate in a networked environment using logical connections to one or more other servers, networked personal computers (PCs), or another network node.

[0078] Input device 850 can be one or more input devices, such as a mouse, keyboard, trackball, etc. Output device 860 can be one or more output devices, such as a monitor, speaker, printer, etc. Electronic device 800 can also communicate with one or more external devices (not shown) via communication unit 840 as needed. These external devices include storage devices, display devices, etc., and can communicate with one or more devices that enable user interaction with electronic device 800, or with any device that enables electronic device 800 to communicate with one or more other electronic devices (e.g., network card, modem, etc.). Such communication can be performed via input / output (I / O) interface (not shown).

[0079] According to an exemplary implementation of this disclosure, a computer-readable storage medium is provided that stores one or more computer instructions, wherein one or more computer instructions are executed by a processor to implement the methods described above.

[0080] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products implemented according to this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0081] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processing unit of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner. Thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0082] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions that execute on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0083] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction, which contains one or more executable instructions for implementing the specified logical function. In some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0084] Various implementations of this disclosure have been described above. The foregoing description is exemplary and not exhaustive, nor is it limited to the disclosed implementations. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described implementations. The terminology used herein is chosen to best explain the principles, practical applications, or improvements to technology in the market, or to enable others skilled in the art to understand the implementations disclosed herein.

Claims

1. A method for correction of electron beam exposure, characterized in that, include: Based on a predetermined dose distribution, a first dose distribution for electron beam exposure is determined by performing electron beam proximity effect correction on the target pattern. The first dose distribution indicates a set of dose adjustment values ​​for compensating for scattering effects during electron beam exposure on the target pattern. Based on the first dose distribution, a second dose distribution for electron beam exposure is determined by performing electron beam fogging effect correction on the target pattern. The second dose distribution indicates a set of dose adjustment values ​​for compensating for fogging effects during electron beam exposure on the target pattern. as well as Based on the first dose distribution and the second dose distribution, a target dose distribution for electron beam exposure is determined by performing electron beam proximity effect correction on the target pattern.

2. The method according to claim 1, characterized in that, Determining the second dose distribution includes: The processed first dose distribution is determined by downsampling the first dose distribution; and The second dose distribution for electron beam exposure is determined by performing electron beam atomization effect correction on the target pattern using the processed first dose distribution as the initial dose distribution.

3. The method according to claim 1, characterized in that, Determining the target dose distribution includes: The processed second dose distribution is determined by upsampling the second dose distribution; and The target dose distribution is determined by superimposing the first dose distribution and the processed second dose distribution as the input dose distribution and performing electron beam proximity effect correction on the target pattern.

4. The method according to claim 3, characterized in that, The process of performing electron beam proximity effect correction and determining the target dose distribution includes: The target dose distribution is determined by performing iterative calculations based on the input dose distribution using an electron beam exposure correction model, wherein the electron beam exposure correction model includes a proximity effect compensation term and a fogging effect compensation term.

5. The method according to claim 1, characterized in that, Determining the first dose distribution includes: The target map is divided into multiple regions; Based on the predetermined dose distribution, by performing electron beam proximity effect correction on the plurality of regions, a dose distribution associated with each of the plurality of regions is determined; and The first dose distribution is determined based on the dose distributions associated with the plurality of regions, respectively.

6. The method according to claim 5, characterized in that, The determination of the dose distribution associated with each of the plurality of regions includes: For the first region among the multiple regions divided in the target map, Determine the third dose distribution and predicted image for the first region; Determine statistical indices for the edge placement error of the predicted image for the first region and the dose values ​​corresponding to the multiple electron beams associated with the first region; and The third dose distribution is adjusted based on at least one of the edge placement error and the statistical indicators to determine the dose distribution associated with the first region.

7. The method according to claim 6, characterized in that, The determination of the third dose distribution and predicted image for the first region includes: Based on the point spread function, the predetermined dose distribution, and the graph associated with the first region, a third dose distribution is determined for the first region; and Based on the point spread function and the third dose distribution, a predicted image for the first region is determined.

8. The method according to claim 6, characterized in that, Adjusting the third dose distribution includes: In response to the edge placement error not meeting a first predetermined condition, the third dose distribution is adjusted until the edge placement error meets the first predetermined condition, wherein the first predetermined condition indicates that the edge placement error is less than an error threshold.

9. The method according to claim 6, characterized in that, The adjustment of the third dose distribution includes: In response to the statistical indicator failing to meet a second predetermined condition, the beam spot size of multiple electron beams associated with the first region is adjusted until the statistical indicator meets the second predetermined condition, the second predetermined condition indicating that the statistical indicator meets a predetermined dose distribution requirement; and The third dose distribution is adjusted based on the dose values ​​corresponding to the size of the beam spots of the multiple electron beams associated with the first region.

10. The method according to claim 9, characterized in that, Also includes: In response to the statistical index meeting a second predetermined condition, dose values ​​corresponding to multiple electron beams associated with the first region are provided.

11. An electronic device, characterized in that, include: At least one processing unit; as well as At least one memory, coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit, the instructions causing the electronic device to perform the method according to any one of claims 1 to 10 when executed by the at least one processing unit.

12. A computer-readable storage medium, characterized in that, It stores a computer program thereon, characterized in that the computer program can be executed by a processor to implement the method according to any one of claims 1 to 10.

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