Indicators for determining the portion of the pattern on the substrate

Abstract

A system and method for determining one or more characteristic parameters of a portion of a pattern on a substrate are described. Pattern information for a pattern on the substrate is received. The pattern on the substrate has a first portion and a second portion. The first portion (404A, 406B) of the pattern is blocked (400, 402) based on the pattern information, for example using a geometric block mask (408, 410), such that the second portion of the pattern remains unblocked. One or more parameters of the unblocked second portion of the pattern are determined. In some embodiments, the first portion and the second portion of the pattern correspond to different exposures in a semiconductor lithography process. The semiconductor lithography process may be a multiple patterning technique, such as a double patterning process, a triple patterning process, or a spaced double patterning process.

Description

[0001] Cross Reference to Related Applications

[0002] This application claims priority to PCT Application No. PCT / CN2020 / 089387 filed May 9, 2020, the contents of which are incorporated herein by reference in their entirety. TECHNICAL FIELD

[0003] This specification relates to determining a characteristic indicator for a pattern on a substrate. BACKGROUND

[0004] Lithographic projection apparatuses can be used, for example, in the manufacture of integrated circuits (ICs). A patterning device (e.g., a mask) can contain or provide a pattern (a “design layout”) corresponding to a single layer of an IC, and this pattern can be transferred onto a target portion (e.g., comprising one or more dies) on a substrate (e.g., a silicon wafer) on which a layer of radiation- sensitive material (the “resist”) has been provided, by such means as by irradiating the target portion through the pattern on the patterning device. Typically, multiple target portions (e.g., including a plurality of dies) are provided on a single substrate, and the pattern is transferred to the target portions one at a time by the lithographic projection apparatus, in succession. In this type of lithographic projection apparatus, the pattern on the entire patterning device is transferred to one target portion in one operation. Such an apparatus is commonly referred to as a “stepper.” In an alternative apparatus, commonly referred to as a “scanner,” the projection beam scans over the entire patterning device while simultaneously moving the substrate parallel or antiparallel to a reference direction (the “scanning” direction) at a speed that is identical to or different from the speed of the scanning beam. Different parts of the pattern on the patterning device are transferred to one target portion in successive stages. Typically, the speed F at which the substrate is moved will be 1 / M times the speed at which the projection beam scans the patterning device, because the lithographic projection apparatus will have a reduction ratio M (e.g., 4), and the reduction ratio can be different in the x and y directions. More information on lithographic apparatuses as described herein can be gleaned, for example, from US 6,046,792, which is incorporated herein by reference.

[0005] Before the pattern is transferred from the patterning device to the substrate, the substrate can undergo various procedures, such as priming, resist coating, and soft baking. After the exposure(s), the substrate can be subjected to other processes such as post-exposure baking (PEB), development, hard baking, and measurement / inspection of the transferred pattern. This array of process operations is used as a basis to produce a completed device, such as an IC.

[0006] Thus, fabricating devices, such as semiconductor devices, typically involves using a number of fabrication processes to process a substrate (e.g., a semiconductor wafer) to form various features and multiple layers of the devices. These layers and features are typically created using, for example, deposition, lithography, etching, chemical-mechanical polishing, and ion implantation. Multiple devices can be fabricated on a plurality of dies of a substrate, and then separated into individual devices. This device fabrication process can be considered a patterning process. A patterning process involves performing a patterning step, such as optical and / or nanoimprint lithography, using a patterning device in an

[0007] Lithography is a central step in the manufacture of devices such as ICs, where patterns formed on substrates define functional elements of the devices such as microprocessors, memory chips, etc. Similar lithographic techniques are also used in the formation of flat panel displays, micro-mechanical systems (MEMS) and other devices.

[0008] As semiconductor manufacturing processes continue to advance, the dimensions of features have continually been reduced while the density of features on a given substrate has been steadily increasing. This trend is commonly referred to as Moore's Law. At the current state of technology, the dimensions of features are less than 100 nm, i.e. less than half the wavelength of radiation from a deep-ultraviolet (DUV) radiation source commonly used in semiconductor processing.

[0009] Such processes for printing features having dimensions smaller than the classical resolution limit of a lithographic projection apparatus can be referred to as “low-ki lithography” where ki < 1, since the resolution of the apparatus is better than the classical resolution limit. However, other processes, such as but not limited to, e-beam lithography, extreme ultraviolet (EUV) lithography, and extreme ultraviolet lithography with a reduction factor of less than 1, can also be used to print such fine features. These processes can be used in the manufacture of integrated circuits and other devices. SUMMARY

[0010] According to an embodiment, a method of determining one or more metrics of a portion of a pattern on a substrate is provided. The method includes receiving pattern information of the pattern on the substrate. The pattern on the substrate has a first portion and a second portion. The method includes blocking the first portion of the pattern based on the pattern information such that the second portion of the pattern remains unblocked, and determining one or more metrics of the unblocked second portion of the pattern.

[0011] In some embodiments, the one or more metrics include a critical dimension and / or an edge placement error.

[0012] In some embodiments, determining the one or more metrics of the unblocked second portion includes aligning and averaging images of the pattern on the substrate, performing profile extraction on the averaged images, and aligning the extracted profiles with the pattern information of the pattern on the substrate. The aligning is performed for both portions of the pattern, the portions including the blocked first portion and the unblocked second portion. In some embodiments, determining the one or more metrics of the unblocked second portion further includes creating one or more gauges in the profiles of the unblocked second portion of the pattern, and measuring the one or more gauges. The one or more gauges specify the one or more metrics of the unblocked second portion.

[0013] In some embodiments, the first portion and the second portion of the pattern are merged, and the images are scanning electron microscope (SEM) images including the merged first portion and second portion of the pattern on the substrate. In some embodiments, determining the one or more metrics of the unblocked second portion includes decomposing the first portion and the second portion of the pattern in the SEM images.

[0014] In some embodiments, the blocking includes generating a geometric patch mask for the first portion based on the pattern information.

[0015] In some embodiments, the pattern information specifies a geometry of the first portion of the pattern, and the generating the mask includes biasing the geometry of the first portion to be larger (i.e., to grow) or to be smaller (i.e., to shrink) relative to the geometry of the first portion specified in the pattern information.

[0016] In some embodiments, the pattern information specifies a geometry of the first portion of the pattern, and the generating the mask includes generating a first mask region by biasing the geometry of the first portion to grow relative to the geometry of the first portion specified in the pattern information, generating a second mask region by biasing the geometry of the first portion to shrink relative to the geometry of the first portion specified in the pattern information, and subtracting the second mask region from the first mask region to generate the mask.

[0017] In some embodiments, at least a portion of the mask is also formed by a cut layer of the pattern.

[0018] In some embodiments, the first portion and the second portion of the pattern are merged. The merged first and second portions of the pattern on the substrate correspond to different exposures in a semiconductor lithography process.

[0019] In some embodiments, the semiconductor lithography process is a multiple patterning technology process. In some embodiments, the multiple patterning technology process is a double patterning process, a triple patterning process, or a spacer double patterning process.

[0020] In some embodiments, the method further includes adjusting a semiconductor manufacturing process based on one or more indicators of the second portion that is not blocked.

[0021] In some embodiments, the adjusting includes changing a size, shape, and / or position of a feature in the second portion of the pattern, and / or changing a mask, dose, focus, and / or exposure associated with the second portion of the pattern.

[0022] In some embodiments, the method further includes unblocking the first portion based on the pattern information, blocking the second portion based on the pattern information such that the first portion remains unblocked, and determining one or more indicators of the first portion that is not blocked.

[0023] According to another embodiment, a non-transitory computer-readable medium having instructions thereon is provided. When executed by a computer, the instructions cause the computer to perform operations comprising: receiving pattern information for a pattern on a substrate, the pattern on the substrate having a first portion and a second portion; blocking the first portion based on the pattern information such that the second portion remains unblocked; and determining one or more metrics for the unblocked second portion.

[0024] In some embodiments, the one or more metrics include a critical dimension and / or an edge placement error.

[0025] In some embodiments, determining the one or more metrics for the unblocked second portion includes: aligning and averaging images of the pattern on the substrate; performing profile extraction on the averaged images; and aligning the extracted profiles with the pattern information for the pattern on the substrate. The aligning is performed on two portions of the pattern, the two portions including the blocked first portion and the unblocked second portion. In some embodiments, determining the one or more metrics for the unblocked second portion further includes: creating one or more gauges in the profile of the unblocked second portion of the pattern; and measuring the one or more gauges, the one or more gauges specifying the one or more metrics for the unblocked second portion.

[0026] In some embodiments, the first portion and the second portion of the pattern are merged, and the images are scanning electron microscope (SEM) images that include the merged first portion and second portion of the pattern on the substrate. In some embodiments, determining the one or more metrics for the unblocked second portion includes decomposing the first portion and the second portion of the pattern in the SFM images.

[0027] In some embodiments, the blocking includes creating a geometric tile mask for the first portion based on the pattern information.

[0028] In some embodiments, the pattern information specifies a geometry of the first portion of the pattern, and creating the mask includes biasing the geometry of the first portion to be larger or smaller relative to the geometry of the first portion specified in the pattern information.

[0029] In some embodiments, the pattern information specifies a geometry of the first portion of the pattern, and creating the mask includes: creating a first mask region by biasing the geometry of the first portion to be larger relative to the geometry of the first portion specified in the pattern information, creating a second mask region by biasing the geometry of the first portion to be smaller relative to the geometry of the first portion specified in the pattern information, and subtracting the second mask region from the first mask region to create the mask.

[0030] In some embodiments, at least a portion of the mask is further formed by a cut layer of the pattern.

[0031] In some embodiments, the first and second portions of the pattern on the substrate are merged and correspond to different exposures in a semiconductor lithography process. In some embodiments, the semiconductor lithography process is a multiple patterning technology process. In some embodiments, the multiple patterning technology process is a double patterning process, a triple patterning process, or a spacer double patterning process.

[0032] In some embodiments, the instructions are further configured to cause the computer to adjust the semiconductor manufacturing process based on the one or more metrics of the second portion that are not blocked.

[0033] In some embodiments, the adjusting includes: changing a size, shape, and / or position of features in the second portion of the pattern; and / or changing a mask, dose, focus, and / or exposure associated with the second portion of the pattern.

[0034] In some embodiments, the instructions are further configured to cause the computer to: unblock the first portion based on the pattern information; block the second portion based on the pattern information such that the first portion remains unblocked; and determine the one or more metrics of the first portion that are not blocked. BRIEF DESCRIPTION OF DRAWINGS

[0035] Figure 1 A block diagram showing various subsystems of a lithography system according to an embodiment.

[0036] Figure 2 A flowchart of a method for determining a pattern formation device pattern or target pattern to be printed on a substrate according to an embodiment.

[0037] Figure 3 An example of the present method for determining one or more metrics for a portion of a pattern on a substrate according to an embodiment is illustrated.

[0038] Figure 4 Blocking two different portions of a pattern by creating geometric tile masks for the different portions according to an embodiment is illustrated.

[0039] Figure 5 Creating various shaped masks by biasing the geometry of the first and second portions of a pattern in various ways according to an embodiment is illustrated.

[0040] Figure 6 Using a cut layer as a tile mask to block a portion of a pattern according to an embodiment is illustrated.

[0041] Figure 7 Using a cut layer in conjunction with biasing the geometry of a portion of a pattern in various ways to create various shaped masks according to an embodiment is illustrated. Figure 5 Creating various shaped masks by biasing the geometry of a portion of a pattern in various ways is illustrated in

[0042] Figure 8 An automated workflow for determining one or more indicators of unobstructed portions of a pattern is illustrated in accordance with an embodiment.

[0043] Figure 9 An example of an obstructed first portion of a pattern and an unobstructed second portion of the pattern is illustrated in accordance with an embodiment.

[0044] Figure 10 Another example of an obstructed first portion of a pattern and an unobstructed second portion of the pattern is illustrated in accordance with an embodiment.

[0045] Figure 11 A merged pattern feature including two different portions of a pattern is illustrated in accordance with an embodiment.

[0046] Figure 12 is a block diagram of an exemplary computer system in accordance with an embodiment.

[0047] Figure 13 is a schematic illustration of a lithographic projection apparatus in accordance with an embodiment.

[0048] Figure 14 is a schematic illustration of another lithographic projection apparatus in accordance with an embodiment.

[0049] Figure 15 is a detailed view of a lithographic projection apparatus in accordance with an embodiment.

[0050] Figure 16 is a detailed view of a source collector module of a lithographic projection apparatus in accordance with an embodiment. DETAILED DESCRIPTION

[0051] Multiple patterning techniques (MPT), including double, triple, spacer double patterning, cut layer, etc., are effective ways to reduce the pitch of pattern features and improve integration of features in semiconductor devices. MPTs are widely used in advanced semiconductor manufacturing processes. Due to the complexity of MPTs, accurate control of critical dimensions (CDs), edge placement (EP) (or edge placement error (EPE)), overlay, and / or other indicators are needed for metrology and / or simulation model calibration purposes. For example, MPTs require high-accuracy optical proximity correction (OPC) models for simulation that are configured to identify and correct weaknesses or defects in integrated MPT designs.

[0052] Embodiments of the present disclosure are described in detail with reference to SEM systems; however, the present disclosure is not limited to any particular type of metrology or inspection system used to scan a wafer and generate signals for measuring a pattern, as described below. In some embodiments, a scanning electron microscope image (SEM) of a substrate is used to generate metrology data in an MPT process. The SEM image of the substrate from the MPT process is an image of the merged portions of the MPT pattern in the substrate. However, individual metrology data is desired for each of the individual merged portions of the pattern (e.g., having separate pattern portions generated by different processes in the MPT process flow), for example, to characterize the individual portions of the pattern. The individual metrology data is desired to be generated for the individual portions of the pattern without interfering with other merged portions of the pattern. Conventionally, a commonly used solution for generating metrology data for individual portions of a pattern includes manually measuring the required metrics (e.g., CD, EP, overlay, EPE, etc.) one after another for each individual portion of the pattern. The individual performing the manual measurements determines which features belong to which individual portion of the pattern in the SEM image, and thus measures the required metrics.

[0053] There are many disadvantages to manually measuring the required metrics of individual portions of a pattern one after another. Manual measurements are not efficient, and the overall measurement turnaround time is very long. To get an accurate model, model calibration requires thousands of measurements. For example, there can be 5000 measurements required for each individual portion of a pattern in a double patterning process. It can take about ten seconds to perform one measurement. This measurement time will further increase with additional individual portions of the pattern. As another example, when several individual portions of a pattern are merged in an MPT process, it can be difficult to even manually identify which features in the substrate belong to which portions of the pattern. This can cause measurement errors and reduce model accuracy. As a third example, many desired measurements, including CD measurements in critical sites of one portion of the pattern, can be prevented by features of different portions of the pattern. This can result in model overfitting and reduced accuracy.

[0054] Advantageously, embodiments of the disclosed system and method are configured to accurately and automatically determine metrics for individual portions of a pattern on a substrate. The determined metrics can be used to establish and / or verify an OPC model, and / or for other purposes. Pattern information specifying the geometry of a pattern on a substrate is received and used to block a first portion of the pattern. The blocking can be performed, for example, with a geometric reticle mask, such that a second portion of the pattern remains unblocked and can be measured without interference from the first portion of the pattern. The masking and measurement can be repeated for any number of portions of the pattern. In contrast to the manual process described above, the present techniques save time and are more accurate because the blocking facilitates automatic measurement. For example, no manual decisions between features are needed because features that do not belong to the measured pattern are blocked. In addition, in contrast to conventional manual metrology, which measures only CD, embodiments of the present system and method are configured to output both CD and edge placement (EP) (or edge placement error (EPE)). This means that measurement information at locations that cannot be used to produce CD measurements can be supplemented with EP (or EPE), and accuracy of a corresponding OPC model is improved.

[0055] Although specific reference can be made in this text to the manufacture of ICs, it should be explicitly understood that the description herein has many other possible applications. For example, the description can be used in the manufacture of integrated optical systems, guidance and detection patterns for magnetic domain memories, liquid crystal display panels, thin-film magnetic heads, etc. One skilled in the art will appreciate that, in the context of such alternative applications, any use of the terms "reticle", "wafer" or "die" in this text should be considered as interchangeable with the more general terms "mask", "substrate" and "target portion", respectively.

[0056] As used herein, the terms “mask,” “mask plate,” or “patterning apparatus” can be broadly interpreted to refer to a general patterning apparatus that can be used to impart a patterned cross-section to an incident radiation beam, the patterned cross-section corresponding to a pattern to be generated in a target portion of a substrate. In such contexts, the term “light valve” may also be used. Examples of other such patterning apparatuses besides typical masks (transmissive or reflective; binary, phase-shifting, hybrid, etc.) include programmable mirror arrays. An example of such a device is a matrix-addressable surface with a viscoelastic control layer and a reflective surface. The underlying principle of such a device is (e.g.) that addressed regions of the reflective surface reflect incident radiation as diffracted radiation, while unaddressed regions reflect incident radiation as non-diffracted radiation. With the use of appropriate filters, non-diffracted radiation can be filtered out from the reflected beam, leaving only diffracted radiation; in this way, the beam becomes patterned according to the addressing pattern of the matrix-addressable surface. Suitable electronics can be used to perform the desired matrix addressing. Other examples of such patterning apparatuses also include programmable LCD arrays. An example is given in U.S. Patent No. 5,229,872, which is incorporated herein by reference.

[0057] In this invention document, the terms "radiation" and "beam" can be used to encompass different types of electromagnetic radiation, including ultraviolet radiation (e.g., having wavelengths of 365 nm, 248 nm, 193 nm, 157 nm, or 126 nm) and EUV (extreme ultraviolet radiation, e.g., having wavelengths in the range of about 5 nm to 100 nm). Typically, multiple patterning techniques use deep ultraviolet (DUV) radiation, but it may be feasible for those skilled in the art to apply the principles described herein to other types of radiation.

[0058] As used herein, the term "projection optics" should be broadly interpreted to encompass various types of optical systems, including, for example, refractive optics, reflective optics, aperture and reflective-refractive optics. The term "projection optics" may also include components operating according to any of these design types for jointly or individually guiding, shaping, or controlling a projected radiation beam. The term "projection optics" can include any optical component in a photolithography projection apparatus, regardless of where the optical component is positioned in the optical path of the photolithography projection apparatus. Projection optics can include optical components for shaping, adjusting, and / or projecting radiation from a source before it passes through a patterning apparatus, and / or for shaping, adjusting, and / or projecting radiation after it has passed through the patterning apparatus. Projection optics typically do not include a light source and a patterning apparatus.

[0059] As a brief introduction, Figure 1An exemplary lithographic projection apparatus 10A is illustrated. Major components are: a radiation source 12A, which can be a deep-ultraviolet (DUV) excimer laser source, or another type of source including an extreme ultra violet (EUV) source (as discussed above, the lithographic projection apparatus itself need not have the radiation source); illumination optics which, for example, define the partial coherence (indicated as the coherence factor) and which can include optics 14A that shape radiation from the radiation source 12A, optics 16Aa, and optics 16Ab; a patterning device (or mask) 18A; and transmission optics 16Ac, which project an image of the patterning device pattern onto a substrate plane 22A.

[0060] A pupil 20A can be included in the transmission optics 16Ac. In some embodiments, there can be one or more pupils before and / or after the mask 18A. As described in further detail herein, the pupil 20A can provide patterning of the light that ultimately reaches the substrate plane 22A. An adjustable filter or aperture at the pupil plane of the projection optics can define a range of beam angles that are illuminated onto the substrate plane 22A, with the largest possible angle defining the numerical aperture NA = n sin (Θ max ) of the projection optics, where n is the refractive index of the medium between the substrate and the last element of the projection optics, and Θ max is the maximum angle of the beam that is emitted from the projection optics that can still illuminate the substrate plane 22A.

[0061] In a lithographic projection apparatus, a source illuminates (i.e., provides radiation to) a patterning device, and a projection optics directs the illumination via the patterning device (e.g., a mask) onto a substrate and shapes the illumination. The projection optics can include at least some of the components 14A, 16Aa, 16Ab, and 16Ac. A aerial image (AI) is a distribution of radiation intensity at the substrate level. An resist model can be used to calculate a resist image from the aerial image, examples of which can be found in U.S. Patent Application Publication US 2009-0157630, the entire disclosure of which is hereby incorporated by reference. The resist model is related only to the properties of the resist layer (e.g., effects of chemical processes that occur during exposure, post-exposure bake (PEB), and development). The optical properties of the lithographic projection apparatus (e.g., properties of the illumination, the patterning device, and the projection optics) dictate the aerial image and can be defined in an optical model. Since the patterning device (e.g., mask) used in the lithographic projection apparatus can be changed, it is desirable to separate the optical properties of the patterning device from the optical properties of the rest of the lithographic projection apparatus, including the source and the projection optics. Details of techniques and models for transforming a design layout to various lithographic images (e.g., aerial images, resist images, etc.), applying optical proximity correction (OPC) using those techniques and models, and evaluating performance (e.g., in terms of process window) are described in U.S. Patent Application Publication Nos. US 2008-0301620, 2007-0050749, 2007-0031745, 2008-0309897, 2010-0162197, and 2010-0180251, the disclosures of each of which are hereby incorporated by reference in their entireties.

[0062] One aspect of understanding a lithographic process is to understand the interaction of the radiation with the patterning device (e.g., mask). The electromagnetic field of the radiation after the radiation has passed through the patterning device can be determined from the electromagnetic field of the radiation before it reaches the patterning device and a function that characterizes the interaction. This function can be referred to as a mask transmission function (which can be used to describe the interaction of transmissive patterning devices and / or reflective patterning devices).

[0063] A mask transmission function can have various different forms. One form is binary. A binary mask transmission function has either of two values (e.g., zero and a normal number) at any given site on the patterning device. A mask transmission function in binary form can be referred to as a binary mask. Another form is continuous. That is, the modulus of the transmissivity (or reflectivity) of the patterning device is a continuous function of position on the patterning device. The phase of the transmissivity (or reflectivity) can also be a continuous function of site on the patterning device. A mask transmission function in continuous form can be referred to as a continuous tone mask or a continuous transmission mask (CTM). For example, a CTM can be represented as a pixelated image, where instead of binary values of 0 or 1, each pixel can be assigned a value between 0 and 1 (e.g., 0.1, 0.2, 0.3, etc.). In embodiments, a CTM can be a pixelated grayscale image, where each pixel has a number of values (e.g., normalized values within a range [-255, 255], within a range [0, 1] or [-1, 1], or other suitable range).

[0064] A thin mask approximation (also referred to as Kirchoff boundary conditions) is widely used to simplify the determination of the interaction of radiation with a patterning device. The thin mask approximation assumes that the thickness of the structures on the patterning device is very small compared to the wavelength, and that the width of the structures on the mask is very large compared to the wavelength. Thus, the thin mask approximation assumes that the electromagnetic field after the patterning device is the product of the incident electromagnetic field and the mask transmission function. However, as lithographic processes use radiation with shorter and shorter wavelengths, and the structures on the patterning device become smaller and smaller, the assumption of the thin mask approximation can break down. For example, due to the finite thickness of the structures (e.g., edges between a top surface and a sidewall), the interaction of the radiation with the structures (“mask 3D effects” or “M3D”) can become important. Incorporating such scattering in the mask transmission function can enable the mask transmission function to preferably capture the interaction of the radiation with the patterning device. A mask transmission function under the thin mask approximation can be referred to as a thin mask transmission function. A mask transmission function that incorporates M3D can be referred to as a M3D mask transmission function.

[0065] Figure 2 is a flowchart of a method 200 for determining a patterning device pattern (or mask pattern hereinafter) from an image (e.g., a continuous transmission mask image, a binary mask image, a curve mask image, etc.) corresponding to a target pattern to be printed on a substrate by a patterning process involving a lithographic process. In embodiments, the design layout or target pattern can be a binary design layout, a continuous tone design layout, or another suitable form of design layout.

[0066] The method 200 is an iterative process in which an initial image (e.g., an enhanced image, a mask variable initialized from a CTM image, etc.) is progressively modified to produce different types of images according to different processes of the present disclosure to ultimately produce information including a mask pattern or image (e.g., a mask variable corresponding to a final curve mask) that is further used to make / fabricate a mask. The iterative modification of the initial image can be based on a cost function in which the initial image can be modified during the iterations such that the cost function is reduced, in embodiments, minimized. In embodiments, the method 200 can also be referred to as a binary CTM process in which the initial image is an optimized CTM image that is further processed according to the present disclosure to produce a curve mask pattern (e.g., a geometry or polygon representation shape of a curve mask or curve pattern). In embodiments, the initial image can be an enhanced image of a CTM image). The curve mask pattern can be in the form of a vector, a table, a mathematical equation, or other forms representing a geometry / polygon shape.

[0067] In embodiments, the process P201 can involve obtaining an initial image (e.g., a CTM image or an optimized CTM image, or a binary mask image). In embodiments, the initial image 201 can be a CTM image that is produced by a CTM production process based on a target pattern to be printed on a substrate. The CTM image can then be received by the process P201. In embodiments, the process P201 can be configured to produce a CTM image. For example, in a CTM production technique, an inverse lithography problem is formulated as an optimization problem. Variables are related to pixel values in a mask image, and a lithography metric such as EPE or sidelobe printing is used as a cost function. In iterations of the optimization, a mask image is constructed from the variables and then a process model is applied to obtain an optical or resist image and the cost function is computed. The cost computation then gives gradient values that are used in the optimization solution process to update the variables (e.g., pixel intensities). After several iterations during the optimization, a final mask image is produced, which is further used as a guide map for pattern extraction. Such an initial image (e.g., a CTM image) can include one or more features (e.g., features of a target pattern, SRAF, SRIF, etc.) corresponding to a target pattern to be printed on a substrate by a patterning process.

[0068] In embodiments, a CTM image (or an enhanced version of a CTM image) can be used to initialize a mask variable that can be used as the initial image 201 that is iteratively modified as discussed below.

[0069] Process P201 can involve generating an enhanced image 202 based on the initial image 201. The enhanced image 202 can be an image in which certain selected pixels within the initial image 201 are magnified. The selected pixels can be pixels within the initial image 201 that have relatively low values (or weak signals). In an embodiment, the selected pixels are pixels that have signal values that are below, for example, an average intensity of the pixels in the entire initial image, or a given threshold value. In other words, pixels within the initial image 201 that have weak signals are magnified, thus enhancing one or more features within the initial image 201. For example, a second order SRAF around a target feature can have a weak signal that can be magnified. Thus, the enhanced image 202 can highlight or identify additional features (or structures) that can be included within a mask image (generated later in the method). In a conventional method of determining a mask image (such as a CTM method), weak signals within the initial image can be ignored, and as such, the mask image can not include features that can be formed from the weak signals in the initial image 201.

[0070] The generation of the enhanced image 202 involves applying an image processing operation such as a filter (e.g., an edge detection filter) to magnify the weak signals within the initial image 201. Alternatively or additionally, the image processing operation can be deblurring, averaging, and / or feature extraction or other similar operations. Examples of edge detection filters include Prewitt operators, Laplacian operators, Gaussian Laplacian (LoG) filters, etc. The generation step can also involve combining the magnified signals of the initial image 201 with the original signals of the initial image 201 with or without modifying the original strong signals of the initial image 201. For example, in an embodiment, for one or more pixel values at one or more locations across the initial image 201 (e.g., at a contact hole), the original signals can be relatively strong (e.g., above a certain threshold value such as 150 or below -50), then the original signals at the one or more locations (e.g., at the contact hole) can not be modified or combined with the magnified signals at the locations.

[0071] In an embodiment, noise (e.g., random variations in brightness or color or pixel values) in the initial image 201 can also be magnified. Thus, alternatively or additionally, a smoothing process can be applied to reduce the noise (e.g., random variations in brightness or color or pixel values) in the combined image. Examples of image smoothing methods include Gaussian blur, running average, low pass filtering, etc.

[0072] In an embodiment, an edge detection filter can be used to generate the enhanced image 202. For example, an edge detection filter can be applied to an initial image 201 to generate a filtered image that highlights the edges of one or more features within the initial image 201. The resulting filtered image can also be combined with the original image (i.e., the initial image 201) to generate the enhanced image 202. In an embodiment, the combination of the initial image 201 and the image obtained after edge filtering can involve modifying only those portions of the initial image 201 with weak signals without modifying regions with strong signals, and the combination process can be weighted based on signal strength. In an embodiment, amplifying weak signals may also amplify noise within the filtered image. Therefore, according to an embodiment, a smoothing process can be performed on the combined image. Image smoothing can refer to an approximation function that attempts to capture important patterns (e.g., target patterns, SRAF) in the image while omitting noise or other fine-scale structures / fast phenomena. In smoothing, the data points of the signal can be modified such that individual points (largely due to noise) can be reduced, and points that may be lower than neighboring points can be increased, resulting in a smoother signal or a smoother image. Therefore, after the smoothing operation, according to embodiments of the present disclosure, a further smoothed version of the enhanced image 202 with reduced noise can be obtained.

[0073] In process P203, the method may involve generating a mask variable 203 based on the enhanced image 202. In a first iteration, the enhanced image 202 may be used to initialize the mask variable 203. In subsequent iterations, the mask variable 203 may be iteratively updated.

[0074] The contour of a real-valued function f with n real variables is extracted as a set of the following form:

[0075] L c (f) = {(x1, x2, ... x} n )|f(x1, x2, ... x n )=c}

[0076] In two-dimensional space, the set is defined on points on a surface where the function f is equal to a given value c. In two-dimensional space, the function f can extract the closed contours that will be presented to the mask image.

[0077] In the above process, x1, x2, ... x n This refers to a mask variable such as the intensity of an individual pixel, the intensity of which determines the location where the curve mask edge exists with a given constant value c (e.g., the threshold plane discussed in the following process on P205).

[0078] In an embodiment, at an iteration, the generation of the mask variable 203 can involve modifying one or more values of the variables (e.g., pixel values at one or more locations) within the enhanced image 202 based on, for example, an initialization condition or a gradient map (which can be subsequently generated in the method). For example, one or more pixel values can be increased or decreased. In other words, the amplitude of one or more signals within the enhanced image 202 can be increased or decreased. The modified amplitude of the signals can enable different curve patterns to be generated depending on the amount of change in the amplitude of the signals. Thus, the curve pattern gradually evolves until the cost function is reduced, in one embodiment, minimized. In an embodiment, further smoothing can be performed on the horizontal mask variable 203.

[0079] Further, the process P205 involves generating a curve mask pattern 205 (e.g., having a polygon shape represented in vector form) based on the mask variable 203. The generation of the curve mask pattern 205 can involve thresholding of the mask variable 203, which is used to trace or generate a curve (or curved) pattern from the mask variable 203. For example, the thresholding can be performed using a threshold plane (e.g., x-y plane) intersecting the signal of the mask variable 203 with a fixed value. The intersection of the threshold plane with the signal of the mask variable 203 generates a trace or contour (i.e., a curved polygon shape), which forms the polygon shape of the curve pattern used as the curve mask pattern 205. For example, the mask variable 203 can intersect a zero plane parallel to the (x, y) plane. Thus, the curve mask pattern 205 can be any curve pattern generated as above. In an embodiment, the curve pattern traced or generated from the mask variable 203 depends on the signal of the enhanced image 202. In this way, the image enhancement process P203 facilitates improving the pattern generated for the final curve mask pattern. The final curve mask pattern can be further used by a mask manufacturer to fabricate a mask for use in a lithography process.

[0080] The process P207 can involve rendering the curve mask pattern 205 to generate a mask image 207. Rendering is an operation performed on the curve mask pattern that is a similar process to converting a rectangular mask polygon to a discrete gray scale image representation. This process can be generally understood as sampling a box function of continuous coordinates (polygon) to a value at each point of an image pixel.

[0081] The method also involves forward simulation or forward modeling of the patterning process using a process model that generates or predicts a pattern that can be printed on a substrate based on the mask image 207. For example, the process P209 can involve executing and / or simulating a process model using the mask image 207 as an input, and generating a process image 209 (e.g., aerial image, resist image, etch image, etc.) on the substrate. In embodiments, the process model can include a mask transmission model coupled to an optical model that is further coupled to a resist model and / or an etch model. The output of the process model can be a process image 209 represented with different process variation factors during the simulation process. The process image can be further used to determine parameters of the patterning process (e.g., edge placement error, critical dimension, overlay, sidelobe, etc.) by, for example, tracking the contours of the patterns within the process image. The parameters can also be used to define a cost function that is further used to optimize the mask image 207 such that the cost function is reduced, or in embodiments, minimized.

[0082] In the process P211, the cost function can be evaluated based on the process image 209 (also referred to as a simulated substrate image or substrate image or wafer image). Thus, the cost function can be considered process-aware in the case of variations in the patterning process, enabling the generation of a curvilinear mask pattern that takes into account variations in the patterning process. For example, the cost function can be an edge placement error (EPE), a sidelobe, a mean square error (MSE), a pattern placement error (PPE), a normalized image log, or other suitable variable defined based on the pattern contours in the process image. As one example, the EPE can be an edge placement error associated with one or more patterns and / or a sum of all edge placement errors related to all patterns of the process model image 209 and corresponding target patterns. In embodiments, the cost function can include more than one condition that can be simultaneously reduced or minimized. For example, in addition to the MRC violation probability, the number of defects, EPE, overlay, CD, or other parameters can also be included, and all conditions can be simultaneously reduced (or minimized).

[0083] Further, one or more gradient maps can be generated based on the cost function (e.g., EPE), and the mask variables can be modified based on such gradient maps. The mask variable (MV) refers to the intensity of Thus, the gradient calculation can be represented as and the gradient values are updated by capturing the inverse mathematical relationship from the mask image (MI) to the curvilinear mask polygon to the mask variable. Thus, a chain of derivative of the cost function can be calculated with respect to the mask image, from the mask image to the curvilinear mask polygon and from the curvilinear mask polygon to the mask variable, which allows the value of the mask variable at the mask variable to be modified.

[0084] In embodiments, image regularization can be added to reduce the complexity of the mask pattern that can be produced. Such image regularization can be mask rule checking (MRC). MRC refers to the limitations of the mask manufacturing process or equipment. Thus, the cost function can include different components, e.g., based on EPE and MRC violation penalties. The penalty can be a cost function term that depends on the amount of violation, e.g., the difference between a mask measurement and a given MRC or mask parameter (e.g., mask pattern width and the allowed (e.g., minimum or maximum) mask pattern width). Thus, according to embodiments of the present disclosure, a mask pattern can be designed and a corresponding mask can be made based not only on a forward simulation of the patterning process but also additionally on manufacturing limitations of the mask manufacturing equipment / process. Thus, a manufacturable curve mask can be obtained that yields high yield (i.e., minimal defects) and high accuracy with respect to, e.g., EPE, CD, or overlay on printed patterns.

[0085] The pattern corresponding to the process image should be exactly the same as the target pattern, however, such exact target pattern can not be feasible (e.g., typically sharp corners) and some discrepancies are introduced due to variations in the patterning process itself and / or approximations in the model of the patterning process. In the first iteration of the method, the mask image 207 can not produce a pattern (in the resist image) that resembles the target pattern. The determination of the accuracy or acceptability of the printed pattern in the resist image (or etch image) can be based on a cost function such as EPE. For example, if the EPE of the resist pattern is high, the EPE of the resist pattern indicates that the printed pattern using the mask image 207 is not acceptable and the pattern in the mask variables 203 must be modified.

[0086] To determine whether the mask image 207 is acceptable, the process P213 can involve determining whether the cost function is reduced or minimized, or whether a given number of iterations is reached. For example, the EPE value of the previous iteration can be compared to the EPE value of the current iteration to determine whether the EPE has been reduced, minimized, or converged (i.e., no substantial improvement in the printed pattern is observed). When the cost function is minimized, the method can stop and the curve mask pattern information that is produced is considered the optimization result.

[0087] However, if the cost function is not reduced or minimized, the mask related variables or enhanced image related variables (e.g., pixel values) can be updated. In embodiments, the update can be according to a gradient based method. For example, if the cost function is not reduced, the method 200 proceeds to produce the next iteration of the mask image after performing processes P215 and P217 that indicate how to further modify the mask variables 203.

[0088] Process P215 can involve generating a gradient map 215 based on the cost function. The gradient map can be a derivative and / or partial derivative of the cost function. In embodiments, the partial derivative of the cost function can be determined with respect to the pixels of the mask image, and the derivative can be further chained to determine the partial derivative with respect to the mask variables 203. Such gradient computation can involve determining the inverse relationship between the mask image 207 and the mask variables 203. Furthermore, the inverse of any smoothing operation (or function) performed in processes P205 and P203 must be considered.

[0089] The gradient map 215 can provide a suggestion as to how to increase or decrease the value of the mask variables in a manner that reduces (in embodiments, minimizes) the value of the cost function. In embodiments, an optimization algorithm can be applied to the gradient map 215 to determine the mask variable values. In embodiments, an optimization solving process can be used to perform gradient-based computation (in process P217).

[0090] In embodiments, for an iteration, the mask variables can change while the threshold plane can remain fixed or unchanged in order to gradually reduce or minimize the cost function. Thus, the resulting curve pattern can gradually evolve during the iterations such that the cost function is reduced, or in embodiments, minimized. In another embodiment, both the mask variables as well as the threshold plane can change to achieve faster convergence of the optimization process. A final set of binarized CTM results (i.e., modified versions of the enhanced image, mask image, or curve mask) can be produced after several iterations and / or minimization of the cost function.

[0091] In embodiments of the present disclosure, the transition from CTM optimization by grayscale image to binarized CTM optimization by curve mask can be simplified by replacing the threshold setting process (i.e., P203 and P205) with a different process at which an S-shaped transformation is applied to the enhanced image 202 and a corresponding change of gradient computation is performed. The S-shaped transformation of the enhanced image 202 produces a transformed image that gradually evolves into a curve pattern during the optimization process (e.g., minimizing the cost function). During the iteration or optimization steps, the variables related to the S-shaped function (e.g., steepness and / or threshold) can be modified based on the gradient computation. As the S-shaped transformation becomes steeper (e.g., the steepness of the slope of the S-shaped transformation increases) during successive iterations, a gradual transition from the CTM image to the final binarized CTM image can be achieved, allowing for improved results of the final binarized CTM optimization by curve mask pattern.

[0092] In embodiments of the present disclosure, additional steps / processes can be inserted into the loop of the optimization iteration to enhance the results to have selected or desired properties. For example, smoothness can be ensured by adding a smoothing step, or other filters can be used to enhance the image to favor horizontal / vertical structures.

[0093] As lithography nodes continue to shrink, more and more complex masks are needed. The present methods can be utilized in critical layers using DUV scanners and / or other scanners. The methods according to the present disclosure can be included in different aspects of a mask optimization process including source mask optimization (SMO), mask optimization, and / or OPC.

[0094] For example, a prior art source mask optimization process is described in U.S. Patent No. 9,588,438, entitled "Optimization Flows of Source, Mask and Projection Optics," which is incorporated by reference in its entirety. This prior art source mask optimization process is performed for a slit center on a typical layout fragment. The resulting optimization of source and mask variables is considered to represent all locations on the slit (and / or other locations).

[0095] Optical proximity correction (OPC) enhances integrated circuit patterning processes by compensating for distortions that occur during processing. Distortions occur during processing because features printed on a wafer are smaller than the wavelength of light used in the patterning and printing processes. OPC verification identifies OPC errors or weaknesses in a post-OPC wafer design that can potentially lead to patterning defects on the wafer.

[0096] OPC deals with the fact that the final size and placement of an image of a design layout projected on a substrate will not be identical to or simply depend on the size and placement of the design layout on a patterning device. In the context of resolution enhancement techniques (RET) such as OPC, it is not necessary to use a physical patterning device, but the design layout can be used to represent a physical patterning device. For smaller feature sizes and higher feature densities present on some design layouts, the position of a particular edge of a given feature will be influenced to some extent by the presence or absence of other neighboring features. These proximity effects result from small amounts of radiation coupling from one feature to another or non-geometrical optical effects such as diffraction and interference. Similarly, proximity effects can result from diffusion and other chemical effects during typically following photo-lithography's post-exposure bake (PEB), resist development, and etching.

[0097] To increase the chances that a projected image of a design layout will meet the requirements of a given target circuit design, complex numerical models of the design layout, corrections or pre-distortions can be used to predict and compensate for proximity effects. The paper "Full-Chip Lithography Simulation and Design Analysis - How OPC Is Changing IC Design" (C. Spence, Proc. SPIE, Vol. 5751, pp. 1-14 (2005)) provides an overview of current "model-based" optical proximity correction processes. In a typical high-end design, almost every feature of the design layout has some modification in order to achieve high fidelity of the projected image to the target design. These modifications can include shifts or biases of edge positions or line widths, as well as the application of "assist" features intended to aid the projection of other features.

[0098] In some embodiments, OPC can be based on measured metrics from, for example, actual or simulated images (such as SEM images), and / or other information. For example, CD, EP and / or EPE, overlay, and / or other metrics can be measured and provided as input to an OPC model for training, making predictions, and / or other reasons.

[0099] As described above, multiple patterning technology (MPT) processes (including double, triple, spacer double patterning, cut layer, etc.) are effective in reducing pattern feature spacing and improving integration of features in semiconductor devices. For example, MPT requires a high accuracy OPC model for simulation that is configured to identify and correct weaknesses or defects in integrated MPT designs. To establish an accurate OPC model, highly reliable metrology data is needed. SEM images from a substrate of a MPT process are images of MPT patterns in the substrate. For example, the images are captured after a MPT pattern is fabricated after multiple steps of a sequence (e.g., including lithography, etch lithography, etch, and etch processes). That is, the images can include all or some of the portions of the MPT pattern. However, separate metrology data is needed for each of the separate portions of the pattern (e.g., having separate pattern portions corresponding to different process steps in the MPT process flow) to characterize the separate portions of the pattern and the associated process steps. Separate metrology data needs to be generated for the separate portions of the pattern without interfering with other portions of the pattern.

[0100] In embodiments of the present systems and methods, pattern information specifying a geometry of a pattern on a substrate is received and used to block a first portion of the pattern. The blocking can be performed, for example, with a geometric reticle such that a second portion of the pattern remains unblocked and can be measured without interference from the first portion of the pattern. The geometric reticle can be generated based on the pattern design (e.g., a graphic data system (GDS) design or other) and / or a die-to-database (D2DB) alignment process. The masking can be repeated for any number of portions of the pattern.

[0101] Figure 3 An example of an exemplary method 300 for determining one or more metrics for a portion of a pattern on a substrate in accordance with embodiments of the present disclosure is illustrated. Figure 3 The method 300 illustrated in FIG. 3 includes receiving 302 pattern information for a pattern on a substrate, blocking 304 a first portion of the pattern based on the pattern information such that a second portion of the pattern remains unblocked, and determining 306 one or more metrics for the unblocked second portion of the pattern. In some embodiments, optionally adjusting 308 a semiconductor manufacturing process and / or other operations based on the one or more metrics for the unblocked second portion can be included in the method 300.

[0102] The operations of the method 300 are intended to be illustrative. In some embodiments, the method 300 can be implemented with one or more additional operations not described, and / or without one or more of the operations discussed. For example, in some embodiments, the method 300 need not include the adjusting operation 308. Additionally, in some embodiments, the method 300 can include one or more operations in addition to those illustrated in FIG. 3. Figure 3 The order in which the operations of the method 300 are illustrated and described in FIG. 3 is not intended to be limiting. In some embodiments, one or more portions of the method 300 can be implemented (e.g., by simulation, modeling, etc.) in one or more processing devices. The one or more processing devices can include one or more devices that perform some or all of the operations of the method 300 in response to instructions stored electronically on an electronic storage medium. The one or more processing devices can include one or more devices configured via hardware, firmware, and / or software that are specifically designed for performing one or more of the operations of, for example, the method 300.

[0103] It should be noted that while the examples described below generally refer to a first portion of a pattern being blocked and a second portion of the pattern being unblocked, the method 300 can also include unblocking a first portion based on pattern information, blocking a second portion based on the pattern information such that the first portion remains unblocked, and determining one or more metrics for the unblocked first portion. These operations can occur sequentially or substantially in parallel. These principles of blocking and unblocking can also be extended to any number of portions of a pattern.

[0104] Receiving 302 includes receiving pattern information for a pattern on a substrate. The pattern information can be communicated electronically (e.g., from the computing system to another computing system, from one portion of a computing system to another portion of the computing system, etc.) and / or by other methods. The pattern on the substrate can already have a plurality of different portions. The portions can correspond to different process steps in a manufacturing process flow (e.g., in an MPT process). For example, the pattern on the substrate can have a first, second, third, fourth, fifth, etc. portion, and each portion corresponds to a process layer. The portions can be unique and / or can be repeated one or more times throughout the pattern and / or throughout the substrate. For simplicity, the description herein focuses on only two different portions (e.g., a first portion and a second portion), but the principles described herein can be extended to any number of portions of a pattern.

[0105] The different portions can be or include different pattern designs within the overall pattern, and / or other portions. The pattern information specifies the geometry of the different pattern designs for the different portions of the pattern. The geometry can include feature shapes, feature sizes, feature locations in the pattern, spacing between features, relative locations of features, etc. and / or other characteristics of the different pattern designs. The pattern information can be and / or include a GDS file that specifies the geometry of the individual portions of the pattern, and / or other types of information. By way of non-limiting example, the pattern information can specify the geometry of a first portion of the pattern, the geometry of a second portion of the pattern, the geometry of the first portion and the second portion relative to each other, and / or other information.

[0106] In some embodiments, the different portions are merged in the pattern on the substrate. The merged portions can include different portions positioned in proximity to each other, mixed or doped features of different portions (e.g., features of one portion of the pattern located between, inside, and / or positioned around one or more features of another portion of the pattern), features of different portions that are in contact or superimposed (and / or appear to be in contact or superimposed), and / or other mergers. Continuing the above example, the first portion and the second portion of the pattern can be merged. As described above, in some embodiments, the merged portions of the pattern on the substrate can correspond to different process layers. For example, the merged first and second portions of the pattern on the substrate can correspond to a first exposure and a second exposure in a semiconductor lithography process (e.g., an MPT process, such as a double patterning process, a triple patterning process, a spacer double patterning process, and / or other processes).

[0107] In some embodiments, a metrology apparatus (or inspection equipment) is used to generate detected signals (e.g., capture images) of the MDT pattern, including some or all of the portions of the MDT pattern. The apparatus can be an e-beam metrology apparatus or an optical metrology apparatus configured to generate detected signals for measuring CD, EP, EPE, overlay, and other metrics. According to the present disclosure, the metrology apparatus can acquire raw signals or raw data. The raw signals or raw data are then measured and processed by an automated process installed on the apparatus or a separate computing device. The blocking mask can be applied in the measurement and data processing substantially in parallel with the raw data acquisition process or in offline data post-processing.

[0108] The blocking 304 includes a portion of the blocking pattern such that another portion of the pattern remains unblocked. For example, a first portion of the pattern can be blocked such that a second portion of the pattern remains unblocked. As another example, a portion of the pattern can include various specifically designed metrology targets. In some embodiments, the blocking 304 can include blocking one portion of a given metrology target while leaving another portion of the metrology target unblocked.

[0109] The blocking is based on the pattern information and / or other information. Since the pattern information specifies the geometry of the different portions, the pattern information can be used to determine which portions of the overall pattern are separate (e.g., the first portion and the second portion, different portions of a metrology target, etc.). Blocking one portion or another portion of the overall pattern can advantageously prevent the portion of the pattern from interfering with the measurement of the unblocked portion of the pattern (e.g., the blocked features of one portion will not inadvertently be used to measure metrics for a different unblocked portion of the pattern). Blocking one portion or another portion of the overall pattern facilitates the automatic identification of measurement locations in the unblocked portion of the pattern by an automated inspection process. For example, the automated inspection equipment can be programmed to search only in the unblocked portion of the pattern design of the features to be used to make measurements. Further, for example, the automated inspection apparatus will not inadvertently capture blocked features in the same location or proximate to the target features used for measurement.

[0110] In some embodiments, the blocking 304 can include model simulations and complex GDS operations configured to generate the blocking mask. The model simulations can generate, for example, model contours, and / or for other purposes. The complex GDS operations can include, for example, polygon Boolean operations, and / or other complex GDS operations.

[0111] Blocking 304 includes generating a geometric tile mask for a given portion (e.g., a first portion) of the pattern based on the pattern information and / or other information. The blocking position and geometry can be determined based on, for example, the position and geometry of the individual pattern portion derived from the pattern design and D2DB alignment. For example, in some embodiments, generating the mask further includes biasing the geometry of the portion to be blocked (e.g., the first portion in this example) larger or smaller relative to the geometry of the portion as specified in the pattern information. Figure 4 Figures illustrate blocking 400, 402 of two different portions 404(A), 406(B) of a pattern positioned in proximity to each other by generating geometric tile masks 408, 410 of the different portions 404, 406. In some embodiments, the GDS file and D2DB alignment indicate the position of the two portions. Figure 4 Measurement positions (as indicated by arrows) that can be used to determine the index of the portion of the pattern are shown. For example, these can be seed gauges 401, 403. The seed gauges can be initial positions designated for measurement. In some embodiments, other equivalent positions can be found in the vicinity of the seed gauges to perform more measurements. For example, the seed gauges 401 and 403 can be positioned in proximity to each other in the pattern. As Figure 4 As shown in the middle, the geometry of the portion 404 is biased 405 larger to form the mask 408, such that the mask 408 can be used to block the portion 404 and its associated seed gauge 401 (including the measurement positions shown by arrows) to facilitate index measurements for the portion 406 and / or seed gauge 403. Similarly, the geometry of the portion 406 can be biased 407 larger to form the mask 410, such that the mask 410 can be used to block the portion 406 / seed gauge 403 (including the measurement positions shown by arrows) to facilitate index measurements for the portion 404 and / or seed gauge 401.

[0112] As another example, generating the mask can include generating a first mask region by biasing the geometry of a portion (e.g., a first portion) of the pattern larger relative to the geometry of the portion as specified in the pattern information, generating a second mask region by biasing the geometry of the portion smaller relative to the geometry of the portion as specified in the pattern information, and subtracting the second mask region from the first mask region to generate the mask. These biasing larger / smaller techniques, biasing in combination with each other and / or subtracting can be used in combination to create various shaped masks.

[0113] For example, Figure 5 Figures illustrate the creation of various shaped exemplary masks in embodiments of the present disclosure by biasing the geometry of a first portion 404 and a second portion 406 of a pattern. In particular, Figure 5 Figures illustrate the creation of exemplary masks for a spaced double patterning process.Figure 5 Two seed gauges 500 (corresponding to portion 404), 502 (corresponding to portion 406) are illustrated positioned proximate to each other, each including an inner measurement location and an outer measurement location (again indicated by arrows). In this example, separate inner and outer gauges are used when their measurement portions are different process layers. In this example, portion 404 is biased large by two different amounts 504, 506, and also biased small 508. Portion 406 is biased large by two different amounts 510, 512, and also biased small 514. As Figure 5 shown in FIG. 5B, bias amount 506 can be subtracted from bias amount 504 to create a mask 520. Bias amount 506 can be used as a mask and / or define the mask. Bias amount 508 can be subtracted from bias amount 504 to create a mask 522. Bias amount 512 can be subtracted from bias amount 510 to create a mask 524. Bias amount 512 can be used as a mask and / or define the mask. Bias amount 514 can be subtracted from bias amount 510 to create a mask 526. These masks can be combined in different ways (e.g., as shown with arrows and "+" and "-" symbols) to block one portion or another portion of a given pattern. In this example, the masks can be combined in different ways as shown to facilitate measurement 530 of outer gauge 500 of portion 404 (by blocking other portions of the combined gauge 500, 502 pattern), measurement 532 of inner gauge 500 of portion 404, measurement 534 of outer gauge 502 of portion 406, or measurement 536 of inner gauge 502 of portion 406.

[0114] In some embodiments, at least a portion of a mask is formed for a cut layer of a pattern. For example, in advanced semiconductor nodes, this can create a simple long line that is later cut into smaller lines to construct a complex structure. A cut layer is needed for such a cutting process. By way of non-limiting example, Figure 6 is shown using 601 cut layer 600 as a block mask to block a portion 404 of a pattern. In this example, the portion of the pattern is seed gauge 401 from portion 404. As Figure 6 shown in FIG. 5B, cut layer 600 is used to block the ends of seed gauge 401 so that only the middle portion of seed gauge 401 (e.g., as indicated by the remaining arrows that are not covered by cut layer 600) is used for index measurements.

[0115] As another example, Figure 7 is shown using cut layer 600 in combination with biasing the geometry of first portion 404 and second portion 406 of a pattern in various ways to create various shaped masks. In Figure 5 shown in FIG. 5B, cut layer 600 is used to block the ends of seed gauge 401 so that only the middle portion of seed gauge 401 (e.g., as indicated by the remaining arrows that are not covered by cut layer 600) is used for index measurements. Figure 7In the example shown in FIG. 6, the mask can be combined in different ways as shown to facilitate measurement 700 of the cut portion of the outer gauge 500 of portion 404 (by blocking other portions of the combined gauge 500, 502 pattern), measurement 702 of the inner gauge 500 of portion 404, measurement 704 of the outer gauge 502 of portion 406, or measurement 706 of the inner gauge 502 of portion 406. As shown in FIG. 6, the cut layer 600 is used to block the end portions of the seed gauges 500 and 502 so that the index measurements are made only from the middle portions of the seed gauges 500 or 502 (e.g., as indicated by the remaining arrows that are not covered by the cut layer 600). Figure 7 In the example shown in FIG. 6, the mask can be combined in different ways as shown to facilitate measurement 700 of the cut portion of the outer gauge 500 of portion 404 (by blocking other portions of the combined gauge 500, 502 pattern), measurement 702 of the inner gauge 500 of portion 404, measurement 704 of the outer gauge 502 of portion 406, or measurement 706 of the inner gauge 502 of portion 406. As shown in FIG. 6, the cut layer 600 is used to block the end portions of the seed gauges 500 and 502 so that the index measurements are made only from the middle portions of the seed gauges 500 or 502 (e.g., as indicated by the remaining arrows that are not covered by the cut layer 600).

[0116] Returning to Figure 3 , the determining 306 includes determining one or more indices for the unblocked (e.g., second) portion of the pattern. The one or more indices include critical dimensions, edge placement and / or edge placement errors, overlay, line edge roughness, and / or other indices. In some embodiments, determining one or more indices for the unblocked portion includes aligning and averaging images of the pattern on the substrate, performing profile extraction on the averaged images, and aligning the extracted profiles with pattern information for the pattern on the substrate. Determining one or more indices for the unblocked (e.g., second) portion also includes generating one or more gauges in the profiles of the unblocked portion of the pattern, and measuring the one or more gauges. In some embodiments, the one or more indices for the unblocked portion are determined based on the measured one or more gauges. Figure 8 These operations are illustrated in FIG. 6 and further described below.

[0117] Figure 8 An automated workflow 800 for determining one or more indices for an unblocked portion of a pattern (e.g., in an MPT process) is illustrated. The determining operation 306 Figure 3 ) can include some or all of the steps of the workflow 800. However, the workflow 800 can also include other steps that are included in the other operations described herein. The workflow 800 begins with a layer map or layer set generation step 802. The layer map generation step 802 can include at least a portion of the receiving 302 and blocking 304 operations described above. For example, the layer map generation step 802 can include generating a geometric bin mask for a given portion (e.g., first portion, second portion, etc.) of the pattern based on the pattern information and / or other information. This can include biasing and / or adding / subtracting pattern geometry as described herein to facilitate mask generation and blocking.

[0118] Workflow 800 continues with raw image processing 804. The images are scanning electron microscope (SEM) images, optical images, and / or other signals or data that can be generated by a metrology or inspection system. For example, the SEM images can be actual or simulated SEM images. The SEM images include multiple images of a given merged (e.g., first and second) repeat portion of a pattern on a substrate. As workflow 800 continues, determining one or more indicators of the second portion that is not blocked includes decomposing the merged (e.g., first and second) portion of the pattern in the SEM images. Raw image processing 804 can include filtering, noise reduction, cropping, flipping, rotation, and / or other raw image processing operations.

[0119] Workflow 800 includes an image alignment step 806. Alignment step 806 can include identifying common features in the entire SEM images and aligning the images based on the common features. For example, corresponding edges, lines, corners, metrology targets, and / or other features in the images can be identified. The images can be oriented and / or otherwise positioned relative to each other based on the identified features such that the common features are oriented and / or positioned in the different images in the same way.

[0120] The aligned images can be averaged at step 808. Averaging the aligned images can result in a single representative image of the pattern in the SEM images. Averaging the aligned images can also reduce image noise and facilitate profile extraction from the averaged image, and / or have other purposes.

[0121] Profile extraction 810 can include identifying a profile of a feature of the pattern in the averaged image. The profile can be a trace of an edge of the feature of the pattern, for example, and / or other profiles. Other portions of the image can be discarded, for example, such that a clear representation of the pattern in the image is obtained.

[0122] At step 812, the extracted contours are aligned with the pattern information. In some embodiments, alignment is performed for substantially all of the portions of the pattern, including the blocked portions and the unblocked portions (e.g., the first portions and the second portions). As described above, the pattern information specifies the geometry of the different pattern designs for different portions of the pattern. The geometry can include feature shapes, feature sizes, feature locations in the pattern, spacing between features, relative locations of features, etc., and / or other characteristics of the different pattern designs. For example, the pattern information can be and / or include a GDS file that specifies the geometry of the individual portions of the pattern, and / or other types of information. The contour shapes, contour sizes, spacing between contour features, relative locations of contour features, etc., and / or other characteristics of the extracted contours can be aligned with the feature shapes, feature sizes, feature locations in the pattern, spacing between features, relative locations of features, etc., and / or other characteristics of the different pattern designs described in the pattern information. In some embodiments, for example, step 812 can include converting a coordinate system from an image pixel-based coordinate system to a GDS coordinate, and / or other operations.

[0123] At step 814, the extracted contours can be adjusted. Contour adjustment can include sharpening and / or otherwise enhancing portions of the contours. For example, portions of the extracted contours that have gaps, appear blurry, appear not to intersect, etc., can be adjusted (e.g., such that the gaps are filled, the lines are smoothed, etc.) such that the contours form a sharpened, clear, substantially continuous representation of the pattern.

[0124] Finally, workflow 800 includes generating 816 a gauge and then measuring 818 the gauge. The gauge can specify one or more metrics. Generating the gauge can include specifying measurement locations in the extracted contours for measurement. For example, a given metric can be a spacing between two different features. Generating a corresponding gauge can include identifying edges of the two different features and determining that the distance between the two edges should be measured. As another example, a given metric can be a location or placement of an edge of a feature (e.g., an absolute location, a location of the edge relative to other features, etc.). Generating a corresponding gauge can include identifying an edge of the feature and determining that the location of the edge should be measured. In some embodiments, measuring 818 the gauge includes causing a metrology device to determine the distance, location, etc., specified by the gauge. In some embodiments, measuring 818 the gauge includes determining the distance, location, etc., based on properties of the extracted contours (e.g., performing the measurement directly in the contour image or based on the contour image electronically), and / or other determinations. In some embodiments, the measurement 818 can be performed using a model generated based on the extracted contours and / or otherwise.

[0125] As Figure 8As shown in FIG. 8, the layer map generation 802 (e.g., the generated block mask) can be used in steps 812 and 816 to generate gauges for the unobstructed portion of the pattern. In this way, the one or more gauges can specify one or more indicators for the unobstructed portion. For example, step 816 can include excluding the obstructed portion of the pattern and generating gauges only for the unobstructed portion of the pattern. In step 812, a transformation of the coordinate system from image pixel-based coordinates to GDS coordinates is performed. Which gauges are within the block mask region can be determined based on the transformed coordinates.

[0126] Figure 9 and Figure 10 FIG. 8 illustrates an example of an obstructed first portion of a pattern and an unobstructed second portion of the pattern, in accordance with an embodiment of the disclosure. Figure 9 FIG. 8 illustrates an obstructed first portion 800 and an unobstructed second portion 802. Portions 800 and 802 include merged portions of an overall pattern 804. For example, portions 800 and 802 are positioned proximate to one another. As shown in FIG. 8, a number of measurement locations (e.g., gauges) have been identified for the unobstructed portion 802 as indicated by the arrow heads across portion 802. In contrast, no measurement locations have been identified for portion 800. This is because portion 800 has been obscured by mask 806. In this example, mask 806 includes a geometry that has been offset to enlarge portion 800 such that portion 800 and any corresponding measurement locations for portion 800 are obstructed by mask 806. This facilitates accurate measurement of portion 802 (e.g., features of portion 800 will not be accidentally measured because the features of portion 800 are obstructed by mask 806). Figure 9

[0127] Figure 10 FIG. 10 illustrates an obstructed first portion 1050 and an unobstructed second portion 1052. Portions 1050 and 1052 include merged portions of an overall pattern 1054. For example, portions 1050 and 1052 are positioned proximate to one another. As shown in FIG. 10, a number of measurement locations (e.g., gauges) have been identified for the unobstructed portion 1052 as indicated by the arrow heads across portion 1052. In contrast, no measurement locations have been identified for portion 1050. This is because portion 1050 has been obscured by mask 1056. In this example, mask 1056 includes a geometry that has been offset to enlarge portion 1050 such that portion 1050 and any corresponding measurement locations for portion 1050 are obstructed by mask 1056. This facilitates accurate measurement of portion 1052 (e.g., features of portion 1050 will not be accidentally measured because the features of portion 1050 are obstructed by mask 1056). Figure 10 ​As shown in FIG. 10, several measurement locations (e.g., gauges) have been identified for the unobstructed portion 1052 as indicated by the arrow heads across the portion 1052. In contrast, no measurement locations have been identified for the portion 1050. This is because the portion 1052 has been obscured by the mask 1056. In this example, the mask 1056 includes a geometry that has been biased large such that the portion 1050, such that the portion 1050 and any corresponding measurement locations for the portion 1050 are obstructed by the mask 1056. This facilitates accurate measurement of the portion 1052 (e.g., because the features of the portion 1050 are obstructed by the mask 1056, the features of the portion 1050 will not be inadvertently measured).

[0128] Figure 11 FIG. 11 illustrates a merged pattern feature 1100 that includes two different portions 1102, 1104 of a pattern. As described above, the inventive method is configured to facilitate determination of both CD and EP as compared to typical measurement methods. During the MPT process, it can be difficult to measure CD at some locations. For example, at location 1110 shown in FIG. 11, CD / EP cannot be measured because the portions 1102 and 1104 overlap to form the feature 1100. There is an overlap between the polygons from the two different portions 1102, 1104 of the pattern. In such a case, the CD / EP does not pertain to a single portion of the mask pattern. The inventive method will not include measurements in the region 1110. For example, using the inventive method, pattern information for the pattern is received, a first portion of the pattern (e.g., portion 1102) is obstructed based on the pattern information such that a second portion of the pattern (e.g., portion 1104) remains unobstructed, and the EP of the unobstructed second portion of the pattern is determined, and vice versa. Figure 11

[0129] Returning to Figure 3 Adjusting 308 includes adjusting the semiconductor manufacturing process, process simulation model, or OPC model based on the one or more metrics for the individual portions of the pattern obtained by using the obstruction mask as described above. In some embodiments, adjusting 308 includes, for example, changing the size, shape, and / or position of features in the pattern in the mask design based on the measured metrics for the unobstructed portions; or changing the mask, dose, focus, and / or exposure associated with the unobstructed portions of the pattern, and / or other adjustments. In some embodiments, adjusting 308 includes performing OPC based on the one or more metrics for the unobstructed portions of the pattern.

[0130] ​In some embodiments, the adjusting 308 includes first determining an actual adjustment. This can be an amount or value of a size change, a shape change, a position change, a dose change, an exposure change, etc. Alternatively and / or additionally, the determined adjustment can be communicated to a different system and / or user, and / or used in other operations, without performing any actual adjustment. This can be in the form of a recommendation and / or suggestion, for example, and / or other forms. Such a recommendation and / or suggestion can be communicated to a user by a user interface, for example, communicated to a different system electronically, and / or communicated in other ways.

[0131] In some embodiments, the operation 308 includes determining one or more adjustments of a device pattern, a mask pattern, a projection optic, an illumination source, and / or other components. For example, the one or more patterns, projection optics, illumination source, and / or other components can be adjusted until a termination condition is satisfied. In some embodiments, the termination condition includes a determination that features patterned onto a substrate (e.g., physically and / or in an electronic model) substantially match a target design. In some embodiments, the adjustments can be iterative adjustments of, for example, a device pattern, a mask pattern, parameters of an illumination source, parameters of a projection optic, and / or other iterative adjustments. The iterative adjustments can continue until a termination condition is satisfied (e.g., until one or more features patterned on a substrate substantially match a target design). In some embodiments, the adjustments of the pattern include adjustments of design variables (e.g., feature sizes, positions, etc.; addition and / or subtraction of auxiliary features; etc.). The adjustments of parameters of an illumination source include adjustments of a dose, a wavelength, an intensity, and / or other parameters of the illumination. The adjustments of parameters of a projection optic can include pupil adjustments, adjusting slits and / or other parameters of the projection optic.

[0132] In some embodiments, the iterative adjustments of a pattern, parameters of an illumination source, parameters of a projection optic, and / or other iterative adjustments until a termination condition is satisfied are performed without constraints of a range of possible values of adjustable variables. In some embodiments, the iterative adjustments of a pattern, parameters of an illumination source, parameters of a projection optic, and / or other iterative adjustments until a termination condition is satisfied are performed with at least one constraint that limits a range of possible values of at least one adjustable variable (e.g., a critical dimension, a minimum line width, a minimum separation between curved shapes, etc.). In some embodiments, the at least one constraint is associated with one or more of a dependence of a design variable (e.g., a curvature of a segment of a first feature) on one or more other design variables (e.g., a curvature of a related segment of a second feature), a physical characteristic of a mask and / or a physical characteristic of a mask manufacturing, or a physical characteristic of a lithographic projection apparatus.

[0133] Figure 12is a diagram of one or more exemplary computer systems CS that can be used in one or more of the operations described herein. Computer system CS includes a bus BS or other communication mechanism for communicating information, and a processor PRO (or multiple processors) coupled with bus BS for processing information. Computer system CS also includes a main memory, such as a random access memory (RAM) or other dynamic storage device, coupled to bus BS for storing information and instructions to be executed by processor PRO. Main memory also can be used for storing temporary variables or other intermediate information during execution of instructions by processor PRO. Computer system CS further includes a read only memory (ROM) or other static storage device coupled to bus BS for storing static information and instructions for processor PRO. A storage device, such as a magnetic disk or optical disk, is provided and coupled to bus BS for storing information and instructions.

[0134] Computer system CS can be coupled via bus BS to a display DS, such as a cathode ray tube (CRT), for displaying information to a computer user. An input device ID, including alphanumeric and other keys, is coupled to bus BS for communicating information and command selections to processor PRO. Another type of user input device is cursor control 33, such as a mouse, trackball, or cursor direction keys, for communicating direction information and command selections to processor PRO and for controlling cursor movement on display DS. This input device typically has two degrees of freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allows the device to specify positions in a plane. A touch panel (screen) display can also be used as an input device.

[0135] In some embodiments, portions of the methods described herein, or variations thereof, can be performed by computer system CS in response to processor PRO executing one or more sequences of one or more instructions contained in main memory MM. Such instructions can be read into main memory MM from another computer-readable medium, such as storage device SD. Execution of the sequences of instructions included in main memory MM causes processor PRO to perform the process steps (operations) described herein. One or more processors in a multi-processing arrangement can also be employed to execute sequences of instructions contained in main memory MM. In some embodiments, hard-wired circuitry can be used in place of or in combination with software instructions. Thus, the description herein is not limited to any specific combination of hardware circuitry and software.

[0136] The term "computer readable media" as used herein refers to any media that participates in providing instructions to processor PRO for execution. Such media can take many forms, including but not limited to, nonvolatile media, volatile media, and transmission media. Nonvolatile media includes, for example, optical or magnetic disks, such as storage device SD. Volatile media includes, for example, memory such as main memory MM. Transmission media includes coaxial cables, copper wire, and fiber optics, including the wires that comprise bus BS. Transmission media can also take the form of acoustic or light waves, such as those generated during radio frequency (RF) and infrared (IR) data communications. Computer readable media can be non-transitory, such as a floppy disk, a flexible disk, a hard disk, a magnetic tape, any other magnetic medium, a CD-ROM, a DVD, any other optical medium, a punch card, a paper tape, any other physical medium with patterns of holes, a RAM, a PROM, and EPROM, a FLASH-EPROM, any other memory chip or cartridge, or any other medium from which a computer can read. The instructions can be embodied in any of various forms, including but not limited to, a compiled or interpreted form.

[0137] Various forms of computer readable media can be involved in carrying one or more sequences of one or more instructions to processor PRO for execution. For example, the instructions can initially be carried on a magnetic disk of a remote computer. The remote computer can load the instructions into its dynamic memory and send the instructions over a telephone line using a modem. A modem local to computer system CS can receive the data on the telephone line and use an infra-red transmitter to convert the data to an infra-red signal. An infra-red detector coupled to bus BS can receive the data carried in the infra-red signal and place the data on bus BS. Bus BS carries the data to main memory MM, from which processor PRO retrieves and executes the instructions. The instructions received by main memory MM can optionally be stored on storage device SD either before or after execution by processor PRO.

[0138] Computer system CS can also include a communication interface CI coupled to bus BS. Communication interface CI provides a two-way data communication coupling to a network link NDL that is connected to a local network LAN. For example, communication interface CI can be an integrated services digital network (ISDN) card or a modem to provide a data communication connection to a corresponding type of telephone line. As another example, communication interface CI can be a local area network (LAN) card to provide a data communication connection to a compatible LAN. Wireless links can also be implemented. In any such implementation, communication interface CI sends and receives electrical, electromagnetic or optical signals that carry digital data streams representing various types of information.

[0139] The network link ND L provides data communication through one or more networks to other data devices. For example, a network link ND L can provide a connection through a local network LAN to a host computer HC. This can include a connection through a global packet data communication network (now often termed an "Internet" INT). The local network LAN (Internet) can use electrical, electromagnetic or optical signals that carry digital data streams. The signals through the various networks and the signals on network link ND L and through communication interface CI provide examples of the communication media that can carry the digital data to and from computer system CS and can also carry digital data to, from, and / or for computer system CS based on computer system CS's role in one implementation of the communication mechanism.

[0140] Computer system CS can send messages and receive data, including program code, through the network(s), network link(s) ND L, and communication interface(s) CI. In the Internet example, a server host HC might transmit a requested code for an application program through the Internet, network link ND L, local network LAN, and communication interface CI to computer system CS. One such downloaded application can provide a part or all of the functionality described herein for the methods. The received code can be executed by processor PRO as it is received, and / or stored in storage device SD, or other non-volatile storage for later execution. In this manner, computer system CS can obtain application code in the form of a carrier wave.

[0141] Figure 13 is a schematic diagram of a lithographic projection apparatus according to an embodiment. The lithographic projection apparatus can be associated with one or more of the operations described herein. For example, a verified mask design can be used for a mask that is removably coupled to the lithographic projection apparatus. The lithographic projection apparatus can include an illumination system IL, a first object table MT, a second object table WT, and a projection system PS. The illumination system IL can condition a radiation beam B. In this example, the illumination system also includes a radiation source SO. The first object table (e.g., a patterning device table) MT can be provided with a patterning device holder for holding a patterning device MA (e.g., a mask or reticle), and connected to a first positioner for accurately positioning the patterning device in relation to the object PS. The second object table (e.g., a substrate table) WT can be provided with a substrate holder for holding a substrate W (e.g., a silicon wafer coated with a resist), and connected to a second positioner for accurately positioning the substrate in relation to the object PS. The projection system (e.g., a projection system including lenses) PS (e.g., a refractive, catoptric, or catadioptric optical system) can image an irradiated portion of the patterning device MA onto a target portion C (e.g., including one or more dies) of the substrate W. The patterning device MA and the substrate W can be aligned using, for example, patterning device alignment marks M1, M2 and substrate alignment marks P1, P2.

[0142] As depicted, the apparatus can be of the transmissive type (i.e. with transmissive patterning means). However, generally, the apparatus can also be of the reflective type, e.g. (with reflective patterning means). The apparatus can employ a different kind of patterning means than the classical mask; examples include programmable mirror arrays or LCD matrices.

[0143] A source SO (e.g. a mercury lamp or excimer laser, LPP (laser produced plasma) EUV source) produces a beam of radiation. This beam is fed into the illumination system (illuminator) IL, either directly or after having traversed adjustment means such as a beam expander or beam delivery system BD (including, for example, directional mirrors, beam expanders, etc.) that are included in the lithography apparatus LA, as depicted. The illuminator IL can include an adjustment mechanism AD to set the outer and / or inner radial extent (commonly referred to as σ-outer and σ-inner, respectively) of the intensity distribution in the beam. In addition, the illuminator IL generally includes various other components, such as an integrator IN and a condenser CO. In this manner, the beam B impinging on the patterning means MA has a desired uniformity and intensity distribution in its cross section.

[0144] In some embodiments, the source SO can be within the housing of the lithography projection apparatus (this is often the case when the source SO is a mercury lamp), but the source SO can also be remote from the lithography projection apparatus. For example, the source SO can generate a beam of radiation that is directed into the apparatus (e.g. with the aid of a suitable directing mirror). This latter scenario can be the case, for example, when the source SO is a laser, such as an excimer laser (e.g. based on KrF, ArF or F2laser action).

[0145] The beam B can then be intercepted by the patterning means MA held in the patterning means table MT. After having traversed the patterning means MA, the beam B can pass through the lens PL, which focuses the beam B onto a target portion C of the substrate W. By means of the second positioning means (and interferometer measurement device IF), the substrate table WT can be accurately moved, for example, so as to position a different target portion C in the path of the beam B. Similarly, the first positioning means can be used for accurately positioning the patterning means MA, for example, in the beam path of the beam B after mechanical fetching of the patterning means MA from the patterning means library or during a scan. Generally, the movement of the tables MT, WT can be realized with the aid of long-stroke modules (coarse positioning) and short-stroke modules (fine positioning). However, in the case of a stepper (as opposed to a step-and-scan tool), the patterning means table MT can be connected to short-stroke actuators, or can be fixed.

[0146] The depicted tools can be used in two different modes - a step mode and a scan mode. In the step mode, the patterning device table MT is held substantially still and an entire patterning device image is projected (i.e. in a single "flash") onto the target portion C. The substrate table WT can be shifted along the x and / or y directions so that different target portions C can be irradiated by the beam B. In the scan mode, substantially the same can apply, except that a given target portion C is not exposed in a single "flash". Instead, the patterning device table MT and possibly the substrate table WT are scanned synchronously so that the beam B and thus the patterned beam B is caused to scan over the target portion C. During scanning, the substrate table WT can be moved relatively slowly so that the beam B scans over the same point on the substrate W many times. In this way, the beam B is scanned in a raster pattern over the target portion C. The substrate table WT can be moved at a speed such that each point under the beam B is scanned at a frequency of at least 50 Hz, at least 1 kHz, at least 10 kHz, at least 50 kHz, at least 100 kHz or at least 1 MHz.

[0147] Figure 14 is a schematic diagram of another exemplary lithographic projection apparatus (LPA) that can be used in and / or in connection with one or more of the operations described herein. The LPA can include a source collector module SO, an illumination system (illuminator) IL configured to condition (e.g., to shape or otherwise direct) a radiation beam B (e.g., EUV radiation), a support structure (e.g., patterning device table) MT constructed to support a patterning device (e.g., a mask or reticle) MA and connected to a first positioner PM configured to accurately position the patterning device, a substrate table (e.g., wafer table) WT constructed to hold a substrate (e.g., a resist-coated wafer) W and connected to a second positioner PW configured to accurately position the substrate, and a projection system (e.g., a reflective projection system) PS configured to project a pattern imparted to the radiation beam B by patterning device MA onto a target portion C (e.g., including one or more dies) of the substrate W.

[0148] As shown in this example, the LPA can be of a reflective type (e.g., employing a reflective patterning device). It is noted that because most materials are absorptive at EUV wavelengths, the patterning device can have a multilayer reflector including, for example, 40 alternating layers of molybdenum and silicon, with each layer's thickness being a quarter wavelength. Even smaller wavelengths can be produced with x-ray lithography. Because most materials are absorptive at EUV and x-ray wavelengths, patterned absorber material segments (e.g., TaN absorbers on top of the multilayer reflector) on the patterning device topography define where features will or will not be printed (positive or negative tone resist, respectively).

[0149] The irradiator IL can receive an extreme ultraviolet radiation beam from the source collector module SO. Methods for generating EUV radiation include, but are not limited to, converting a material having at least one element (e.g., xenon, lithium, or tin) into a plasma state using one or more emission spectral lines in the EUV range. In one such method (often referred to as laser-generated plasma (“LPP”)), plasma can be generated by irradiating a fuel (such as droplets, streams, or clusters of material having spectral emission elements) with a laser beam. The source collector module SO may include a laser ( Figure 14 The laser (not shown) is part of an EUV radiation system used to provide a laser beam for exciting the fuel. The resulting plasma emits output radiation (e.g., EUV radiation), which is collected using a radiation collector disposed in a source collector module. For example, when a CO2 laser is used to provide a laser beam for fuel excitation, the laser and the source collector module can be separate entities. In this example, the laser may not be considered part of the lithography apparatus, and the radiation beam can be delivered from the laser to the source collector module by means of a beam delivery system including, for example, suitable directional mirrors and / or beam expanders. In other examples, for example, when the source is a discharge-generated plasma EUV generator (often referred to as a DPP source), the source can be part of the source collector module.

[0150] An irradiator IL may include adjusters for adjusting the angular intensity distribution of the radiation beam. Typically, at least the outer radial range and / or inner radial range (often referred to as σ-outer and σ-inner, respectively) of the intensity distribution in the pupil plane of the irradiator can be adjusted. Additionally, the irradiator IL may include various other components, such as faceted field mirror assemblies and faceted pupil mirror assemblies. The irradiator can be used to adjust the radiation beam to have a desired uniformity and intensity distribution in its cross-section.

[0151] A radiation beam B can be incident on a pattern forming apparatus (e.g., a mask) MA held on a support structure (e.g., a pattern forming apparatus stage) MT, and patterned by the pattern forming apparatus. After reflection from the pattern forming apparatus (e.g., the mask) MA, the radiation beam B passes through a projection system PS, which focuses the beam onto a target portion C of the substrate W. The substrate stage WT can be accurately moved (e.g., to position different target portions C in the path of the radiation beam B) by means of a second locator PW and a position sensor PS2 (e.g., an interferometric device, a linear encoder, or a capacitive sensor). Similarly, a first locator PM and another position sensor PS1 can be used to accurately position the pattern forming apparatus (e.g., the mask) MA relative to the path of the radiation beam B. The pattern forming apparatus (e.g., the mask) MA and the substrate W can be aligned using pattern forming apparatus alignment marks M1, M2 and substrate alignment marks P1, P2.

[0152] The described apparatus LPA can be used in at least one of the following modes: step mode, scan mode, and static mode. In step mode, the support structure (e.g., patterning apparatus stage) MT and substrate stage WT are kept substantially stationary (e.g., single static exposure) while the entire pattern to be applied to the radiation beam is projected onto the target portion C in one pass. Then, the substrate stage WT is shifted along the X and / or Y directions to expose different target portions C. In scan mode, the support structure (e.g., patterning apparatus stage) MT and substrate stage WT are scanned synchronously while the pattern to be applied to the radiation beam is projected onto the target portion C (i.e., single dynamic exposure). The speed and direction of the substrate stage WT relative to the support structure (e.g., patterning apparatus stage) MT can be determined by the magnification (reduction) and image inversion characteristics of the projection system PS. In static mode, the support structure (e.g., patterning apparatus stage) MT, which holds the programmable patterning apparatus, is kept substantially stationary while the substrate stage WT is moved or scanned while the pattern to be applied to the radiation beam is projected onto the target portion C. In this mode, a pulsed radiation source is typically used, and the programmable patterning apparatus is updated as needed after each movement of the substrate stage WT or between consecutive radiation pulses during scanning. This mode of operation can be readily applied to maskless lithography utilizing programmable patterning apparatuses, such as programmable mirror arrays of the type mentioned above.

[0153] Figure 15 yes Figure 14 A more detailed view of the photolithography projection device is shown in the image. Figure 15 As shown, the LPA may include a source collector module SO, an irradiation system IL, and a projection system PS. The source collector module SO is configured such that a vacuum environment can be maintained within the enclosure structure 220 of the source collector module SO. EUV radiation emitting plasma 210 can be formed by generating a plasma radiation source through discharge. EUV radiation can be generated by a gas or vapor (e.g., Xe gas, Li vapor, or Sn vapor), wherein a thermal plasma 210 is generated to emit radiation in the EUV range of the electromagnetic spectrum. The thermal plasma 210 is generated, for example, by a discharge that generates at least partially ionized plasma. For efficient radiation generation, Xe, Li, Sn vapor, or any other suitable gas or vapor with a partial pressure of, for example, 10 Pa may be required. In some embodiments, an excited tin (Sn) plasma is provided to generate EUV radiation.

[0154] Radiation emitted by thermal plasma 210 is transmitted from source chamber 211 to collector chamber 212 via an optional gas barrier or contaminant trap 230 (also referred to in some cases as a contaminant barrier or fin trap) positioned in or behind an opening in source chamber 211. Contaminant trap 230 may include a channel structure. Contaminant trap 230 may also include a gas barrier, or a combination of a gas barrier and a channel structure. Contaminant trap or contaminant barrier 230 (described below) also includes a channel structure. Collector chamber 212 may include a radiation collector CO, which may be a grazing incidence collector. Radiation collector CO has an upstream radiation collector side 251 and a downstream radiation collector side 252. Radiation traversing collector CO may be reflected from grating spectral filter 240 to be focused into a virtual source point IF along the optical axis indicated by line “O”. The virtual source point IF is often referred to as the intermediate focus, and the source collector module is arranged such that the intermediate focus IF is located at or near an opening 221 in the enclosed structure 220. The virtual source point IF is an image of the radiative emission plasma 210.

[0155] Subsequently, radiation traverses the illumination system IL, which may include a faceted field mirror assembly 22 and a faceted pupil mirror assembly 24. The faceted field mirror assembly 22 and the faceted pupil mirror assembly 24 are arranged to provide a desired angular distribution of the radiation beam 21 at the patterning apparatus MA, and a desired uniformity of the radiation intensity at the patterning apparatus MA. After reflecting the radiation beam 21 at the patterning apparatus MA held by the support structure MT, a patterned beam 26 is formed, and the patterned beam 26 is imaged via the projection system PS onto the substrate W held by the substrate stage WT through reflective elements 28 and 30. More elements than those shown may typically be present in the illumination optics unit IL and the projection system PS. Depending on, for example, the type of lithography equipment, a grating spectral filter 240 may optionally be present. Furthermore, more mirrors than those shown in the figures may be present, for example, with… Figure 15 Compared to the diagram, a projection system PS can have 1 to 6 additional reflective elements.

[0156] like Figure 15 The collector optics CO illustrated is depicted as a nested collector with grazing incidence reflectors 253, 254, and 255, and is only an example of a collector (or collector mirror). The grazing incidence reflectors 253, 254, and 255 are arranged to be axially symmetrical about the optical axis O, and this type of collector optics CO can be used in conjunction with a discharge-generated plasma source, often referred to as a DPP source.

[0157] Figure 16Detailed view of a source collector module SO for a lithographic projection apparatus LPA (shown in previous figures). The source collector module SO can be part of the LPA radiation system. A laser LA can be arranged to deposit laser energy into a fuel, such as xenon (Xe), tin (Sn) or lithium (Li), creating a highly ionized plasma 210 with electron temperatures of several 10's of electron volts. High energy radiation is produced during de-excitation and recombination of these ions, emitted from the plasma, collected by a near-normal incidence collector optic CO, and focused into the opening 221 in an enclosing structure 220.

[0158] Embodiments of the present disclosure can be further described by the following aspects.

[0159] 1. A non-transitory computer readable medium having instructions thereon that, when executed by a computer, cause the computer to perform a method comprising:

[0160] receiving pattern information of a pattern on a substrate, the pattern on the substrate having a first portion and a second portion;

[0161] blocking the first portion based on the pattern information such that the second portion remains unblocked; and

[0162] determining one or more metrics for the unblocked second portion.

[0163] 2. The non-transitory computer readable medium of aspect 1, wherein the one or more metrics comprise a critical dimension and / or an edge placement error.

[0164] 3. The non-transitory computer readable medium of any of aspects 1 or 2, wherein determining the one or more metrics for the unblocked second portion comprises:

[0165] aligning and averaging images of the pattern on the substrate;

[0166] performing profile extraction on the averaged images; and

[0167] aligning the extracted profiles with pattern information of the pattern on the substrate, the aligning being performed on two portions of the pattern, the two portions comprising the blocked first portion and the unblocked second portion.

[0168] 4. The non-transitory computer readable medium of aspect 3, wherein determining the one or more metrics for the unblocked second portion further comprises:

[0169] creating one or more gauges in the profile of the unblocked second portion of the pattern; and

[0170] measuring the one or more gauges that specify the one or more indicators of the unobstructed second portion.

[0171] 5. The non-transitory computer readable medium of aspect 3 or 4, further comprising obtaining data representing the image, wherein the first portion and the second portion of the pattern are merged, wherein the image is a scanning electron microscope (SEM) image comprising the merged first portion and second portion of the pattern on the substrate, and wherein determining the one or more indicators of the unobstructed second portion comprises decomposing the first portion and the second portion of the pattern in the SEM image.

[0172] 6. The non-transitory computer readable medium of any of aspects 1-5, wherein obstructing comprises generating a geometric bin mask for the first portion based on the pattern information.

[0173] 7. The non-transitory computer readable medium of aspect 6, wherein the pattern information specifies a geometry of the first portion of the pattern, and wherein generating the mask comprises biasing the geometry of the first portion to be larger or smaller relative to the geometry of the first portion specified in the pattern information.

[0174] 8. The non-transitory computer readable medium of aspect 6, wherein the pattern information specifies a geometry of the first portion of the pattern, and wherein generating the mask comprises generating a first mask region by biasing the geometry of the first portion to be larger relative to the geometry of the first portion specified in the pattern information, generating a second mask region by biasing the geometry of the first portion to be smaller relative to the geometry of the first portion specified in the pattern information, and subtracting the second mask region from the first mask region to generate the mask.

[0175] 9. The non-transitory computer readable medium of any of aspects 6-8, wherein at least a portion of the mask is further formed by a cut layer of the pattern.

[0176] 10. The non-transitory computer readable medium of any of aspects 1-9, wherein the first portion and the second portion of the pattern on the substrate are merged and correspond to different exposures in a semiconductor lithography process.

[0177] 11. The non-transitory computer readable medium of aspect 10, wherein the semiconductor lithography process is a multiple patterning technology process.

[0178] 12. The non-transitory computer-readable medium of aspect 11, wherein the multiple patterning technology process is a double patterning process, a triple patterning process, or a split double patterning process.

[0179] 13. The non-transitory computer-readable medium of any of aspects 1 to 12, wherein the instructions are further configured to cause the computer to adjust a semiconductor manufacturing process based on the one or more metrics of the unobstructed second portion.

[0180] 14. The non-transitory computer-readable medium of aspect 13, wherein the adjusting comprises: changing a size, shape, and / or position of features in the second portion of the pattern; and / or changing a mask, dose, focus, and / or exposure associated with the second portion of the pattern.

[0181] 15. The non-transitory computer-readable medium of any of aspects 1 to 14, wherein the instructions are further configured to cause the computer to:

[0182] unblock the first portion based on the pattern information;

[0183] block the second portion based on the pattern information such that the first portion remains unblocked; and

[0184] determine the one or more metrics of the unobstructed first portion.

[0185] 16. A method for determining one or more metrics of a portion of a pattern on a substrate, the method comprising:

[0186] receiving pattern information of a pattern on the substrate, the pattern on the substrate having a first portion and a second portion;

[0187] blocking the first portion of the pattern based on the pattern information such that the second portion of the pattern remains unblocked; and

[0188] determining the one or more metrics for the unobstructed second portion of the pattern.

[0189] 17. The method of aspect 16, wherein the one or more metrics comprise a critical dimension and / or an edge placement error.

[0190] 18. The method of any of aspects 16 or 17, wherein determining the one or more metrics of the unobstructed second portion comprises:

[0191] aligning and averaging images of the pattern on the substrate;

[0192] performing profile extraction on the averaged image; and

[0193] aligning the extracted profile with pattern information of a pattern on the substrate, the aligning being performed on two portions of the pattern, the two portions including the blocked first portion and an unblocked second portion.

[0194] 19. The method of aspect 18, wherein determining the one or more indicators of the unblocked second portion further comprises:

[0195] creating one or more gauges in the profile of the unblocked second portion of the pattern; and

[0196] measuring the one or more gauges, the one or more gauges specifying the one or more indicators of the unblocked second portion.

[0197] 20. The method of any of aspects 18 or 19, wherein the first portion and the second portion of the pattern are merged, wherein the image is a scanning electron microscope (SEM) image including the merged first portion and second portion of the pattern on the substrate, and wherein determining the one or more indicators of the unblocked second portion comprises decomposing the first portion and the second portion of the pattern in the SEM image.

[0198] 21. The method of any of aspects 16 to 20, wherein blocking comprises creating a geometric patch mask for the first portion based on the pattern information.

[0199] 22. The method of aspect 21, wherein the pattern information specifies a geometry of the first portion of the pattern, and wherein creating the mask comprises biasing the geometry of the first portion to be larger or smaller relative to the geometry of the first portion specified in the pattern information.

[0200] 23. The method of aspect 21, wherein the pattern information specifies a geometry of the first portion of the pattern, and wherein creating the mask comprises creating a first mask region by biasing the geometry of the first portion to be larger relative to the geometry of the first portion specified in the pattern information, creating a second mask region by biasing the geometry of the first portion to be smaller relative to the geometry of the first portion specified in the pattern information, and subtracting the second mask region from the first mask region to create the mask.

[0201] 24. The method of any one of aspects 21-23, wherein at least a portion of the mask is further formed by a cut layer of the pattern.

[0202] 25. The method of any one of aspects 16-24, wherein the first portion and the second portion of the pattern are merged, and wherein the merged first and second portions of the pattern on the substrate correspond to different exposures in a semiconductor lithography process.

[0203] 26. The method of aspect 25, wherein the semiconductor lithography process is a multiple patterning technology process.

[0204] 27. The method of aspect 26, wherein the multiple patterning technology process is a double patterning process, a triple patterning process, or a spacer double patterning process.

[0205] 28. The method of any one of aspects 16-27, further comprising adjusting a semiconductor manufacturing process based on the one or more indicators of the unblocked second portion.

[0206] 29. The method of aspect 28, wherein the adjusting comprises: changing a size, shape, and / or position of a feature in the second portion of the pattern; and / or changing a mask, dose, focus, and / or exposure associated with the second portion of the pattern.

[0207] 30. The method of any one of aspects 16-29, further comprising:

[0208] unblocking the first portion based on the pattern information;

[0209] blocking the second portion based on the pattern information such that the first portion remains unblocked; and

[0210] determining the one or more indicators of the unblocked first portion.

[0211] 31. The non-transitory computer-readable medium of aspects 1-15, wherein the blocking comprises generating a geometric tile mask based on D2DB alignment.

[0212] 32. The method of aspects 21-30, wherein the blocking comprises generating a geometric tile mask based on D2DB alignment.

[0213] The concepts disclosed herein can be modeled mathematically or simulated for any general imaging system for imaging sub-wavelength features and can be used especially for emerging imaging technologies capable of producing shorter and shorter wavelengths. Emerging technologies already in use include EUV (extreme ultraviolet), DUV lithography capable of producing 193 nm wavelengths by using ArF lasers and even 157 nm wavelengths by using fluorine lasers. In addition, EUV lithography is capable of producing wavelengths in the range between 5 nm and 20 nm by using synchrotrons or by impacting a material (solid or plasma) with high energy electrons in order to produce photons in this range.

[0214] While the disclosed concepts can be used for imaging on substrates such as silicon wafers, it should be understood that the disclosed concepts can be used with any type of lithographic imaging system, for example, a lithographic imaging system for imaging on substrates other than silicon wafers. In addition, combinations and sub-combinations of the disclosed elements can include separate embodiments. For example, a single portion of a blocking pattern can form its own embodiment, or a single portion of a blocking pattern can be included with one or more other embodiments that also include other portions of a blocking pattern, as described in the present disclosure.

[0215] The above description is intended to be illustrative, and not restrictive. Those skilled in the art will appreciate modifications can be made without departing from the scope of the claims as set forth below.

Claims

1. A non-transitory computer-readable medium having instructions thereon that, when executed by a computer, cause the computer to: receive pattern information for a pattern on a substrate, the pattern on the substrate having a first portion and a second portion; block the first portion based on the pattern information, such that the second portion remains unblocked; and determining one or more indicators of the second portion that is not blocked, wherein, the one or more metrics include a critical dimension and / or an edge placement error.

2. The non-transitory computer-readable medium of claim 1, wherein, determining the one or more metrics for the unblocked second portion includes: aligning and averaging images of the pattern on the substrate; performing profile extraction on the averaged images; and aligning the extracted profiles to pattern information for the pattern on the substrate, the aligning being performed for two portions of the pattern, the two portions including a blocked first portion and an unblocked second portion.

3. The non-transitory computer-readable medium of claim 2, wherein, determining the one or more metrics for the unblocked second portion further includes: creating one or more gauges in a profile of the unblocked second portion of the pattern; and measuring the one or more gauges, the one or more gauges specifying the one or more metrics for the unblocked second portion.

4. The non-transitory computer-readable medium of claim 2, wherein, the first portion and the second portion of the pattern are merged, wherein the images are scanning electron microscope (SEM) images that include the merged first portion and second portion of the pattern on the substrate, and wherein determining the one or more metrics for the unblocked second portion includes decomposing the first portion and the second portion of the pattern in the SEM images.

5. The non-transitory computer-readable medium of claim 1, wherein, the blocking includes creating a geometric tile mask for the first portion based on the pattern information.

6. The non-transitory computer-readable medium of claim 5, wherein, the pattern information specifies a geometry of the first portion of the pattern, and wherein creating the geometric tile mask includes biasing the geometry of the first portion to be larger or smaller relative to the geometry of the first portion specified in the pattern information.

7. The non-transitory computer-readable medium of claim 5, wherein, the pattern information specifies a geometry of the first portion of the pattern, and wherein creating the geometric tile mask includes creating a first mask region by biasing the geometry of the first portion to be larger relative to the geometry of the first portion specified in the pattern information, creating a second mask region by biasing the geometry of the first portion to be smaller relative to the geometry of the first portion specified in the pattern information, and subtracting the second mask region from the first mask region to create the geometric tile mask.

8. The non-transitory computer-readable medium of claim 5, wherein, at least a portion of the geometric tile mask is further formed by a cut layer of the pattern.

9. The non-transitory computer-readable medium of claim 1, wherein, the first portion and the second portion of the pattern on the substrate are merged and correspond to different exposures in a semiconductor lithography process.

10. The non-transitory computer-readable medium of claim 9, wherein, the semiconductor lithography process is a multiple patterning technology process.

11. The non-transitory computer-readable medium of claim 5, wherein, the blocking includes creating a geometric tile mask for the first portion further based on a D2DB alignment.

12. The non-transitory computer-readable medium of claim 1, wherein, the instructions are further configured to cause the computer to adjust a semiconductor manufacturing process based on the one or more metrics for the unblocked second portion.

13. The non-transitory computer-readable medium of claim 12, wherein, The adjusting includes: changing a size, shape, and / or position of a feature in the second portion of the pattern; and / or changing a mask, dose, focus, and / or exposure associated with the second portion of the pattern.

14. The non-transitory computer-readable medium of claim 1, wherein, The instructions are further configured to cause the computer to: unblock the first portion based on the pattern information; block the second portion based on the pattern information such that the first portion remains unblocked; and determine one or more indicators of the first portion that is unblocked.

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