Systems, products, and methods for generating a patterning device and thus a pattern

Abstract

Described herein is a method for improving a design of a patterning device. The method comprises: (i) obtaining mask points of a design of a mask feature, wherein the mask feature corresponds to a target feature in a target pattern to be printed on a substrate; and (ii) adjusting positions of the mask points to generate a modified design of the mask feature based on the adjusted mask points.

Description

[0001] Cross-reference to related applications

[0002] This application claims priority to U.S. Application No. 63 / 034,343, filed June 3, 2020; U.S. Application No. 63 / 037,513, filed June 10, 2020; and U.S. Application No. 63 / 122,760, filed December 8, 2020, the entire contents of which are incorporated herein by reference. Technical Field

[0003] The description herein generally relates to systems, products, and methods for generating pattern forming apparatus and thus generating patterns. Background Technology

[0004] Photolithography projection equipment can be used to manufacture, for example, integrated circuits (ICs). In this case, a patterning apparatus (e.g., a mask) can contain or provide a pattern corresponding to a separate layer of the IC (“design layout”), 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) that has already been coated with a layer of radiation-sensitive material (“resist”) by relying on the pattern on the patterning apparatus. Generally, a single substrate contains multiple adjacent target portions, and the pattern is continuously transferred by the photolithography projection equipment to the multiple adjacent target portions one at a time. In one type of photolithography projection equipment, the pattern on the entire patterning apparatus is transferred onto one target portion at a time; this equipment is often referred to as a stepper. In an alternative equipment, often referred to as a step-scanning equipment, a projection beam scans the entire patterning apparatus in a given reference direction (“scanning” direction) while the substrate is moved synchronously parallel to or antiparallel to the reference direction. Different portions of the pattern on the patterning apparatus are gradually transferred to a target portion. Generally, since the photolithography projection apparatus will have a reduction ratio M (e.g., 4), the speed at which the substrate is moved, F, will be 1 / M times the speed at which the projection beam scans the pattern forming apparatus. Further information regarding photolithography devices as described herein can be obtained, for example, from US 6,046,792, which is incorporated herein by reference.

[0005] Before the pattern is transferred from the patterning apparatus to the substrate, the substrate may undergo various processes, such as primer coating, resist coating, and soft baking. After exposure, the substrate may undergo other processes (“post-exposure processes”), such as post-exposure baking (PEB), development, hard baking, and measurement / inspection of the transferred pattern. This series of processes forms the basis for individual layers used in the fabrication of devices (e.g., ICs). The substrate may then undergo various processes, such as etching, ion implantation (doping), metallization, oxidation, chemical-mechanical polishing, etc., all intended to refine the individual layers of the device. If several layers are required in the device, the entire process or its variations are repeated for each layer. Ultimately, a device will be present in each target portion of the substrate. These devices are then separated from each other using techniques such as dicing or sawing, whereby individual devices can be mounted on carriers, connected to pins, etc.

[0006] Therefore, fabricating devices such as semiconductor devices typically involves processing a substrate (e.g., a semiconductor wafer) using multiple fabrication processes to form various features and multiple layers of the device. These layers and features are typically fabricated and processed using processes such as deposition, photolithography, etching, chemical mechanical polishing, and ion implantation. Multiple devices can be fabricated on multiple dies on a substrate, and then the multiple devices are separated into individual devices. This device fabrication process can be considered a patterning process. A patterning process involves patterning steps for transferring a pattern from a patterning apparatus to a substrate, such as optical and / or nanoimprint lithography using a patterning apparatus in a photolithography device, and the patterning process typically, but optionally, involves one or more associated patterning processing steps, such as resist development by a developing apparatus, baking the substrate using a baking tool, etching using an etching apparatus, and etching using the pattern.

[0007] As mentioned, photolithography is a central step in the fabrication of devices such as integrated circuits (ICs), in which patterns formed on a substrate define the functional elements of the device, such as microprocessors and memory chips. Similar photolithography techniques are also used to form flat panel displays, microelectromechanical systems (MEMS), and other devices.

[0008] As semiconductor manufacturing processes continue to advance, the size of functional components has been shrinking for decades, while the number of functional components, such as transistors, per device has been steadily increasing, following a trend commonly known as "Moore's Law." In the current state of technology, photolithography projection equipment is used to fabricate the layers of devices. This equipment projects a design layout onto a substrate using irradiation from a deep ultraviolet (DEU) source, resulting in individual functional components with dimensions significantly smaller than 100 nm—that is, dimensions less than half the wavelength of the radiation from that source (e.g., a 193 nm DEU source).

[0009] The process of printing features with dimensions smaller than the classical resolution limit of a photolithography projection apparatus is often referred to as low-k1 lithography according to the resolution formula CD = k1 × λ / NA, where λ is the wavelength of the radiation used (currently 248 nm or 193 nm in most cases), NA is the numerical aperture of the projection optics in the photolithography projection apparatus, CD is the “critical size”—typically the smallest feature size that can be printed—and k1 is an empirical resolution factor. Generally, the smaller k1 is, the more difficult it becomes to reproduce patterns on a substrate that resemble the shapes and sizes planned by the designer to achieve specific electrical functionalities and performance. To overcome these difficulties, complex fine-tuning steps are applied to the photolithography projection apparatus, design layout, or patterning apparatus. These steps include (e.g., but not limited to) optimization of NA and optical coherence settings, custom illumination schemes, the use of phase-shifting patterning apparatus, optical proximity correction (OPC, sometimes also called “optical and process correction”) in the design layout, or other methods generally defined as “resolution enhancement techniques” (RET). 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 that operate according to any of these design types for guiding, shaping, or controlling a projected radiation beam, either jointly or individually. The term "projection optics" can include any optical component in a lithographic projection apparatus, regardless of where the optical component is located in the optical path of the lithographic 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 source and a patterning apparatus. Summary of the Invention

[0010] According to an embodiment, a non-transitory computer-readable medium is provided, the computer-readable medium having instructions that, when executed by a computer, cause the computer to perform a method for improving the design of a pattern forming apparatus, the method comprising: (i) obtaining mask points of a design of mask features, wherein the mask features correspond to target features in a target pattern to be printed on a substrate; and (ii) adjusting the position of the mask points to generate a modified design of the mask features based on the adjusted mask points.

[0011] According to an embodiment, a non-transitory computer-readable medium is provided, the computer-readable medium having instructions that, when executed by a computer, cause the computer to perform a method for improving the design of a patterning apparatus, the method comprising: (i) obtaining mask points of a design of mask features, wherein the mask features correspond to target features in a target pattern to be printed on a substrate; and (ii) adjusting the position of the mask points to increase a process window, wherein the process window is associated with a patterning process for printing the target pattern on a substrate, wherein the adjustment includes: generating a modified design based on the adjusted position.

[0012] According to an embodiment, a method for improving the design of a pattern forming apparatus is provided, the method comprising: (i) obtaining mask points of a design of mask features, wherein the mask features correspond to target features in a target pattern to be printed on a substrate; and (ii) adjusting the position of the mask points to generate a modified design of the mask features based on the adjusted mask points. Attached Figure Description

[0013] Figure 1 A block diagram showing the various subsystems of the photolithography system is provided.

[0014] Figure 2 Examples of categories for processing variables are shown.

[0015] Figure 3 The flowchart for a patterned simulation method according to an embodiment is illustrated schematically.

[0016] Figure 4 The flowchart of a measurement simulation method according to an embodiment is illustrated schematically.

[0017] Figure 5A This is a flowchart of a method for generating or improving the design of mask features corresponding to a target pattern, consistent with various embodiments.

[0018] Figure 5B This is a flowchart of a method for generating an initial design of mask features, consistent with various embodiments.

[0019] Figure 5C This is a flowchart of the initial design process for optimizing mask features, consistent with various embodiments.

[0020] Figure 6A The target features with control points and initial mask points are described in accordance with the various embodiments.

[0021] Figure 6B This describes the design of mask features obtained from another process, consistent with various embodiments.

[0022] Figure 7 This describes the process of applying a smoothing process to mask points, consistent with various embodiments.

[0023] Figure 8 This describes a perturbed version of the initial design of mask features consistent with various embodiments.

[0024] Figure 9 This describes an optimized design of mask features consistent with various embodiments.

[0025] Figure 10A This illustrates an exemplary application of a point-based optimization process consistent with various embodiments, wherein an optimized design of mask features is generated for target features of a first shape.

[0026] Figure 10B This illustrates an exemplary application of a point-based optimization process consistent with various embodiments, wherein an optimized design of mask features is generated for target features of a second shape.

[0027] Figure 10C This section illustrates an exemplary application of a point-based optimization process consistent with various embodiments, wherein an optimized design of mask features is generated for target features and sub-resolution auxiliary features (SRAF).

[0028] Figure 10D This illustrates an exemplary application of a point-based optimization process consistent with various embodiments, wherein the optimized design of mask features is generated for target features rather than for SRAF.

[0029] Figure 11 This is a block diagram of an exemplary computer system according to an embodiment.

[0030] Figure 12 This is a schematic diagram of a photolithography projection apparatus according to an embodiment.

[0031] Figure 13 This is a schematic diagram of another photolithography projection device according to an embodiment.

[0032] Figure 14 According to the embodiments Figure 12 A more detailed view of the device.

[0033] Figure 15 According to the embodiments Figure 13 and Figure 14 A more detailed view of the device's source collector module SO.

[0034] Figure 16A This describes the curve design of the mask features consistent with various embodiments.

[0035] Figure 16B This describes a polygonal design for mask features consistent with various embodiments.

[0036] Figure 16C This describes the curve and polygon designs of the mask features consistent with various embodiments.

[0037] Figure 16D This describes the curve and polygon designs of the mask features consistent with various embodiments.

[0038] Figure 17 This describes a hybrid design of mask features consistent with various embodiments.

[0039] Figure 18 The description is consistent with various embodiments and can be implemented for execution. Figure 5A The flowchart of the "All Angles OPC" method described in [the document]. Detailed Implementation

[0040] In photolithography, a patterning apparatus (e.g., a mask) can provide a mask pattern (e.g., a mask design layout) corresponding to a target pattern (e.g., a target design layout), and this mask pattern can be transferred onto a substrate by transmitting light through the mask pattern. However, due to various limitations, the transferred pattern may exhibit many irregularities and, therefore, be dissimilar to the target pattern. Optical proximity correction (OPC) is an enhancement technique commonly used in mask pattern design to compensate for image errors caused by diffraction or other process effects in photolithography. Current OPC techniques enhance mask feature design by iteratively adjusting segments of the design (e.g., to minimize signals such as resist or etch image signals) and stitching the corrected segments to form a corrected design. Some techniques enhance the design to optimize the cost function, such as edge placement error, mask regularity checking, symmetry, etc. Some techniques correct all segments together to optimize the cost function. Some techniques employ image-based enhancement methods, such as freeform techniques, where a freeform mask design is generated from an initial image (e.g., a continuous transmission mask (CTM) image) and this freeform mask design is iteratively corrected to optimize variable pixels in the image. However, at least some of these current techniques are inefficient because they may suffer from convergence problems, may have finite process window sizes, may require users to tune many parameters to achieve the desired results, or may consume significant computational resources, such as runtime and memory, which prevents their use in production lines.

[0041] This disclosure discloses methods and systems for improving mask patterns using point-based OPC (or "full-angle OPC" herein). In point-based OPC, in some embodiments, initial mask points can be generated from a target pattern for a target feature, and these initial mask points can be associated with control points on the target feature, for example, one control point is associated with one or more mask points. The mask points are adjusted (e.g., their positions are changed) to generate a curved pattern. The mask points can be moved by an amount along a specified direction (e.g., a local normal to the curved pattern or other predetermined direction), for example, to optimize the cost function at the control points. The above process of adjusting the mask points can be iteratively implemented to update the curved pattern to achieve convergence.

[0042] In some embodiments, point-based OPC provides a final or intermediate design of a mask with a curved pattern that is more natural than an elongated design produced from known techniques. In some embodiments, multiple mask points can be consistently moved to optimize the cost function at one or more control points, allowing for finer and more accurate local control of the mask design and potentially improving overall lithography performance. In some embodiments, for example, if the mask design becomes significantly different from the target feature, the association between control points and mask points can be broken and re-established, enabling more efficient optimization at control points by intelligently selecting mask points to be corrected (in contrast, in the prior art, the association between segments and control points is fixed even when segments are quite far from the control points, such as near corners of the target feature). Full-angle OPC techniques can be used to generate curved or non-curved patterns (e.g., polygonal patterns where segments or lines of the pattern are at angles of 45*n degrees or 90*n degrees to the horizontal axis, where n is an integer) or hybrid designs (e.g., designs that are partly curved and partly polygonal) for mask features.

[0043] As a brief introduction, Figure 1An exemplary photolithography projection apparatus 10A is described. The main components are: a radiation source 12A, which can be a deep ultraviolet excimer laser source or other types of sources including extreme ultraviolet (EUV) sources (as discussed above, the photolithography projection apparatus itself does not need to have a radiation source); irradiation optics, which may define partial coherence (expressed as standard deviation) and may include optics 14A, 16Aa, and 16Ab that shape the radiation from source 12A; a pattern forming apparatus 18A; and a transmission optics 16Ac that projects an image of a pattern from the pattern forming apparatus onto a substrate plane 22A. An adjustable filter or aperture 20A at the pupil plane of the projection optics can define the range of beam angles irradiating the substrate plane 22A, wherein the largest possible angle defines the numerical aperture NA of the projection optics as n sin(Θ). max ), where n is the refractive index of the medium between the substrate and the final component of the projection optics, and Θ max It is the maximum angle at which the beam emitted from the self-projecting optics can still illuminate the substrate plane 22A.

[0044] In a photolithography projection apparatus, a source provides illumination (i.e., radiation) to a patterning apparatus, and projection optics guide the illumination onto a substrate and shape the illumination via the patterning apparatus. The projection optics may include at least some of components 14A, 16Aa, 16Ab, and 16Ac. An aerial image (AI) is the distribution of radiation intensity at a horizontal plane of the substrate. A resist model can be used to calculate a resist image from the aerial image, an example of which can be found in U.S. Patent Application Publication No. 2009-0157360, the entire disclosure of which is incorporated herein by reference. The resist model relates only to the characteristics of the resist layer (e.g., the effects of chemical processes occurring during exposure, post-exposure baking (PEB), and development). The optical characteristics of the photolithography projection apparatus (e.g., the characteristics of the illumination, the patterning apparatus, and the projection optics) define the aerial image and can be defined in the optical model. Because the patterning apparatus used in a photolithography projection apparatus can be modified, it is necessary to separate the optical characteristics of the patterning apparatus from the optical characteristics of the rest of the photolithography projection apparatus, which includes at least the source and the projection optics. U.S. Patent Application Publications Nos. 2008-0301620, 2007-0050749, 2007-0031745, 2008-0309897, 2010-0162197, and 2010-0180251 describe in detail the techniques and models for transforming design layouts into various lithographic images (e.g., aerial images, resist images, etc.), using those techniques and models to apply OPC and evaluate performance (e.g., based on process windows), the entire disclosure of each of which is incorporated herein by reference.

[0045] Patterning apparatuses can include or form one or more design layouts. Design layouts can be generated using CAD (Computer-Aided Design) programs, a process often referred to as EDA (Electronic Design Automation). Most CAD programs follow a predetermined set of design rules to generate functional design layouts / patterning apparatuses. These rules are set through processing and design constraints. For example, design rules define the space tolerances between devices (such as gates, capacitors, etc.) or interconnecting lines to ensure that devices or lines do not interact with each other in undesirable ways. One or more of these design rule constraints can be called “critical dimensions” (CDs). A critical dimension of a device can be defined as the minimum width of a line or via, or the minimum space between two lines or two vias. Therefore, CDs determine the overall size and density of the designed device. Of course, one of the goals in device fabrication is to faithfully reproduce the original design intent on the substrate (via the patterning apparatus).

[0046] As used herein, the terms "mask" 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; the term "optical valve" can also be used in this context. Examples of other such patterning apparatuses besides classic masks (transmissive or reflective; binary, phase-shifting, hybrid, etc.) include:

[0047] - A programmable array of reflectors. An example of such a device is a matrix-addressable surface with a viscoelastic control layer and a reflective surface. The underlying principle of this device is (for example): the addressable regions of the reflective surface reflect incident radiation as diffracted radiation, while the unaddressed regions reflect incident radiation as non-diffracted radiation. With the use of appropriate filters, the non-diffracted radiation can be filtered out from the reflected beam, leaving only the diffracted radiation; thus, the beam becomes patterned according to the addressing pattern of the matrix-addressable surface. Suitable electronic components can be used to perform the desired matrix addressing.

[0048] - Programmable LCD array. An example of this construction is given in U.S. Patent No. 5,229,872, which is incorporated herein by reference.

[0049] One aspect of understanding the photolithography process is understanding the interaction between radiation and the patterning apparatus. The electromagnetic field of the radiation after it has passed through the patterning apparatus can be determined based on the electromagnetic field of the radiation before it reaches the apparatus and a function characterizing this interaction. This function can be called the mask transmission function (which can be used to describe the interaction between the transmissive and / or reflective patterning apparatuses).

[0050] The variables in the patterning process are called "processing variables". The patterning process can include the upstream and downstream processes of the actual transfer of the pattern in the lithography equipment. Figure 2Exemplary categories of processing variables 370 are shown. The first category can be variables 310 of the lithography apparatus or any other apparatus used in the lithography process. Examples of this category include variables of the irradiation element, projection system, substrate platform, etc., of the lithography apparatus. The second category can be variables 320 of one or more steps performed during the patterning process. Examples of this category include focus control or focus measurement, dose control or dose measurement, bandwidth, exposure duration, development temperature, chemical composition used in development, etc. The third category can be variables 330 of the design layout and its implementation in or using the patterning apparatus. Examples of this category can include the shape and / or position of auxiliary features, adjustments applied by resolution enhancement techniques (RET), CD of mask features, etc. The fourth category can be variables 340 of the substrate. Examples include characteristics of the structure beneath the resist layer, the chemical composition and / or physical dimensions of the resist layer, etc. The fifth category can be characteristics 350 of the time-varying nature of one or more variables in the patterning process. Examples of this category include characteristics of high-frequency platform movement (e.g., frequency, amplitude, etc.), characteristics of high-frequency laser bandwidth changes (e.g., frequency, amplitude, etc.), and / or characteristics of high-frequency laser wavelength changes. These high-frequency changes or movements are high-frequency changes or movements that exceed the response time of the mechanism used to adjust the fundamental variables (e.g., platform position, laser intensity). A sixth category can be characteristics 360 of processes upstream or downstream of pattern transfer in a lithography apparatus, such as spin coating, post-exposure baking (PEB), development, etching, deposition, doping, and / or encapsulation.

[0051] As will be understood, many, if not all, of these variables will affect the parameters of the pattern-forming process and often the parameters of interest. Non-limiting examples of parameters of the pattern-forming process may include critical dimensions (CD), critical dimension uniformity (CDU), focal points, overlap, edge positions or placements, sidewall angles, pattern displacement, etc. Often, these parameters express errors relative to nominal values ​​(e.g., design values, averages, etc.). Parameter values ​​can be values ​​of individual pattern characteristics or statistics of characteristics of a group of patterns (e.g., mean, variance, etc.).

[0052] The values ​​of some or all of the processing variables, or related parameters, can be determined using appropriate methods. For example, values ​​can be determined based on data obtained using various measurement tools (e.g., substrate measurement tools). Values ​​can be obtained from various sensors or systems in the patterning process equipment (e.g., sensors in lithography equipment (such as leveling measurement sensors or alignment sensors), control systems of lithography equipment (e.g., substrate or patterning stage control systems), sensors in coating and developing system tools, etc.). These values ​​may also originate from the operator of the patterning process.

[0053] Figure 3An exemplary flowchart is provided to illustrate a portion of the pattern forming process used for modeling and / or simulating the pattern forming process. As will be understood, the model may represent different pattern forming processes and need not include all models described below. Source model 1200 represents the optical characteristics of the illumination of the pattern forming apparatus (including radiation intensity distribution, bandwidth, and / or phase distribution). Source model 1200 may represent the optical characteristics of the illumination, including but not limited to: numerical aperture setting, illumination standard deviation (σ) setting, and any specific illumination shape (e.g., off-axis radiation shape, such as toroidal, quadrupole, dipole, etc.), where σ (or standard deviation) is the external radial range of the illuminator.

[0054] The projection optics model 1210 represents the optical characteristics of the projection optics (including changes in the radiation intensity distribution and / or phase distribution caused by the projection optics). The projection optics model 1210 can represent the optical characteristics of the projection optics, including aberrations, distortion, one or more refractive indices, one or more physical dimensions, one or more physical dimensions, etc.

[0055] The patterning apparatus / design layout model module 1220 captures how design features are arranged within a pattern of the patterning apparatus and may include a representation of the detailed physical characteristics of the patterning apparatus, such as as described, for example, in U.S. Patent No. 7,587,704, which is incorporated herein by reference in its entirety. In an embodiment, the patterning apparatus / design layout model module 1220 represents the optical characteristics (including changes in radiation intensity distribution and / or phase distribution caused by a given design layout) of a design layout (e.g., a device design layout corresponding to features of an integrated circuit, memory, electronic device, etc.), which are representations of the arrangement of features on or formed by the patterning apparatus. Because the patterning apparatus used in a photolithography projection apparatus can be modified, it is necessary to separate the optical characteristics of the patterning apparatus from the optical characteristics of the rest of the photolithography projection apparatus, which includes at least the irradiation and projection optics. The goal of simulation is often to accurately predict, for example, edge placement and CD, which can then be compared with the device design. The device design is typically defined as a pre-OPC patterning apparatus layout and is provided in a standardized digital file format such as GDSII or OASIS.

[0056] An aerial image 1230 can be simulated based on the source model 1200, the projection optics model 1210, and the pattern forming apparatus / design layout model 1220. The aerial image (AI) is the radiation intensity distribution at the horizontal plane of the substrate. The optical characteristics of the photolithography projection equipment (e.g., the characteristics of the irradiator, the pattern forming apparatus, and the projection optics) define the aerial image.

[0057] A resist layer on a substrate is exposed by an aerial image, and this aerial image is transferred to the resist layer as a latent image therein, known as a "resist image" (RI). A resist image (RI) can be defined as the spatial distribution of the solubility of the resist in the resist layer. A resist image 1250 can be simulated using a resist model 1240 based on the aerial image 1230. An example of using a resist model to calculate a resist image based on an aerial image can be found in U.S. Patent Application Publication No. 2009-0157360, the entire disclosure of which is incorporated herein by reference. Resist models typically describe the effects of chemical processes occurring during resist exposure, post-exposure baking (PEB), and development in order to predict, for example, the profile of resist features formed on the substrate, and therefore are generally only related to such properties of the resist layer (e.g., the effects of chemical processes occurring during exposure, PEB, and development). In an embodiment, the optical properties of the resist layer, such as refractive index, film thickness, propagation, and polarization effects, can be captured as part of the projection optics model 1210.

[0058] Therefore, generally speaking, the connection between the optical model and the resist model is the simulated aerial image intensity within the resist layer. This simulated aerial image intensity arises from the projection of radiation onto the substrate, refraction at the resist interface, and multiple reflections within the resist film stack. The radiation intensity distribution (aerial image intensity) transforms into a latent image, the "resist image," through the absorption of incident energy; it is further modified by diffusion processes and various loading effects. A sufficiently fast and efficient simulation method for full-chip applications approximates the actual 3D intensity distribution within the resist stack using a 2D aerial (and resist) image.

[0059] In an embodiment, a resist image can be used as input to the post-pattern transfer process model module 1260. The post-pattern transfer process model 1260 defines the performance of one or more resist development processes (e.g., etching, development, etc.).

[0060] Simulation of the patterning process can, for example, predict the contours, CD (cutoff point), edge placement (e.g., edge placement error) in the resist and / or etched image. Therefore, the goal of this simulation is to accurately predict, for example, the edge placement of the printed pattern, and / or the intensity slope of the aerial image, and / or CD. These values ​​can be compared with the expected design to, for example, correct the patterning process, identify locations where defects are predicted, etc. The expected design is typically defined as a pre-OPC design layout, which can be provided in a standardized digital file format such as GDSII or OASIS, or other file formats.

[0061] Therefore, the model formulas describe most (if not all) of the known physical properties and chemical methods of the overall process, and each model parameter ideally corresponds to a different physical or chemical effect. Thus, the model formulas set an upper limit on the goodness of the model in simulating the overall manufacturing process.

[0062] Figure 4 This section illustrates an exemplary flowchart for modeling and / or simulating measurement processes. As will be appreciated, the following models may represent different measurement processes and need not include all the models described below (e.g., some models may be combined). Source model 1300 represents the optical characteristics of the illumination of the measurement target (including radiation intensity distribution, radiation wavelength, polarization, etc.). Source model 1300 may represent the optical characteristics of the illumination, including but not limited to: wavelength, polarization, illumination standard deviation (σ) setting (where σ (or standard deviation) is the radial range of the illumination in the illuminator), any particular illumination shape (e.g., off-axis radiation shapes, such as toroidal, quadrupole, dipole, etc.), etc.

[0063] The measurement optics model 1310 represents the optical characteristics of the measurement optics (including changes in the radiation intensity distribution and / or phase distribution caused by the measurement optics). The measurement optics model 1310 can represent the optical characteristics of the illumination of the measurement target by the measurement optics, and the optical characteristics of the transfer of radiation redirected from the measurement target towards the detector of the measurement device. The measurement optics model can represent various characteristics related to the illumination of the target and the transfer of radiation redirected from the measurement target towards the detector, including aberrations, distortion, one or more refractive indices, one or more physical sizes, one or more physical dimensions, etc.

[0064] The measurement target model 1320 can represent the optical characteristics of illumination redirected by the measurement target (including changes in the intensity and / or phase distribution of the illumination radiation caused by the measurement target). Therefore, the measurement target model 1320 can model the transformation from illumination radiation to redirected radiation through the measurement target. Thus, the measurement target model can simulate the resulting illumination distribution of radiation redirected from the measurement target. The measurement target model can represent various characteristics related to the illumination of the target and the generation of radiation redirected from the measurement, including one or more refractive indices, one or more physical dimensions of the measurement, the physical layout of the measurement target, etc. Since the measurement target used can be varied, it is necessary to separate the optical characteristics of the measurement target from the optical characteristics of the rest of the measurement apparatus, which includes at least the illumination and projection optics and detectors. The simulation target is often to accurately predict, for example, intensity, phase, etc., which can then be used to derive parameters of interest in the patterning process, such as overlap, CD, focus, etc.

[0065] The pupil or aerial image 1330 can be simulated based on the source model 1300, the measurement optics model 1310, and the measurement target model 1320. The pupil or aerial image is the radiation intensity distribution at the detector's horizontal plane. The optical characteristics of the measurement optics and the measurement target (e.g., illumination, characteristics of the measurement target, and characteristics of the measurement optics) define the pupil or aerial image.

[0066] The detector of the measurement device is exposed to a pupil or aerial image and detects one or more optical characteristics (e.g., intensity, phase, etc.) of that pupil or aerial image. The detection model module 1320 represents how radiation from the measurement optics is detected by the detector of the measurement device. The detection model can describe how the detector detects the pupil or aerial image and can include signal sensitivity to noise, sensitivity to incident radiation on the detector, etc. Therefore, generally, the connection between the measurement optics model and the detector model is a simulated pupil or aerial image, which results from the illumination of the measurement target by the optics, the redirection of radiation by the target, and the transfer of the redirected radiation to the detector. The radiation distribution (pupil or aerial image) becomes the detection signal due to the absorption of incident energy on the detector.

[0067] Simulation of the measurement process can, for example, be based on the detector's detection of the pupil or aerial image to predict spatial intensity signals, spatial phase signals, etc., at the detector, or other calculated values ​​from the detection system, such as overlap and CD values. Therefore, the goal of the simulation is to accurately predict, for example, the detector signal corresponding to the measurement target or derived values ​​such as overlap and CD. These values ​​can be compared with expected design values ​​to, for example, correct the patterning process, identify the predicted location of defects, etc.

[0068] Therefore, the model formula describes most (if not all) of the known physical and chemical properties of the overall measurement process, and each model parameter in the model parameters ideally corresponds to a different physical and / or chemical effect in the measurement process.

[0069] Various patterns on or provided by a patterning apparatus can have different process windows, i.e., a space of processing variables upon which a pattern conforming to specifications is based. Examples of pattern specifications for potential systematic defects include checking for necking, line pullback, line thinning, CD, edge placement, overlap, resist top loss, resist undercut, and / or bridging. Typically, the process window is defined on two processing variables (i.e., dosage and focus) such that the CD obtained after patterning is within ±10% of the desired CD of the pattern's characteristics. The process windows for all patterns on the patterning apparatus or its area can be obtained by merging the process windows of each individual pattern (e.g., overlapping the process windows).

[0070] Figure 5A This is a flowchart of an exemplary method 500, consistent with various embodiments, for generating or improving the design of mask features corresponding to a target pattern to be printed onto a substrate via a patterning process involving photolithography. In embodiments, the target pattern may be a binary design layout, a continuous-tone design layout, or a design layout of another suitable form. The target pattern may include one or more target features to be printed onto the substrate, and the mask pattern includes mask features corresponding to one or more target features. In some embodiments, the design of the target feature may be polygonal, and the design of the corresponding mask feature may be a curved pattern. The mask feature may be a primary feature or a secondary resolution auxiliary feature (SRAF) corresponding to the target feature.

[0071] At process P501, mask points for the design of the mask feature are obtained. In some embodiments, mask points are a set of points located on the mask feature. Mask points can be adjusted (e.g., moved to different positions) to modify the design of the mask feature. Mask points are derived from an existing design of the mask feature or from a target feature, in which case the mask points are connected (smoothly) with lines to form an initial design. In some embodiments, the initial design has a curved pattern. Additional details for obtaining mask points or generating the initial design are referenced at least to... Figure 5B The process is described in 550.

[0072] At process P503, the initial design is optimized by adjusting the positions of the mask points. This adjustment of the mask point positions results in a modified design of the mask features (hence the term "point-based optimization process"). In some embodiments, the mask point positions are adjusted such that a cost function is optimized. The cost function may include one or more of the following: edge placement error (EPE), a simulated signal such as a resist image signal (or an etch image signal), mask rule checking (MRC) penalty, process window, etc. Process P503 may use one or more cost functions and may optimize different cost functions in different ways.

[0073] For example, process P503 can optimize a cost function such as EPE by reducing the EPE of one or more target features (e.g., until minimized). In some embodiments, EPE is the distance between a point on a contour (e.g., a contour corresponding to a mask feature) in the resist image and the expected location of said point (e.g., a control point on the target feature).

[0074] In another example, process P503 can optimize a cost function such as the simulation signal by reducing the simulation signal on one or more target features (e.g., until minimized). In some embodiments, the simulation signal can be obtained from a resist image (or etching image) that can be obtained based on a modified design of the mask features, for example, by simulating using a resist model (or etching model).

[0075] In another example, process P503 can optimize a cost function such as an MRC violation penalty by reducing the MRC violation penalty (e.g., until it is minimized). In some embodiments, MRC is an image regularization method used to reduce the complexity of the achievable mask pattern. MRC refers to constraints on the mask manufacturing process or equipment. The penalty can be a violation-dependent term of the cost function, such as the difference between a mask measurement and a given MRC or mask parameter (e.g., the mask pattern width versus the allowed (e.g., minimum or maximum) mask pattern width).

[0076] In another example, process P503 can optimize a cost function such as the process window by increasing the process window (e.g., up to maximizing it). In some embodiments, increasing the process window includes increasing the range of dose or focus values. In some embodiments, the process window of the patterning process includes a range of values ​​for source parameters (such as dose and focus) of a lithography apparatus used to print a target pattern onto a substrate using a mask pattern.

[0077] In some embodiments, the position adjustment process P503 is an iterative process, and the position adjustment iterations are performed until a specified condition is met. The specified condition may be performing a predefined number of iterations or optimizing a cost function. Additionally, the modified design is updated in each iteration (e.g., by adjusting the position of one or more mask points), and the output of the final iteration (e.g., the modified final design) can be used to fabricate a mask pattern. The mask pattern may have additional structural features, such as SRAFs corresponding to the modified design. The mask pattern can then be used to transfer the modified design onto a substrate using photolithography equipment.

[0078] Additional details regarding the initial design for optimizing mask features should at least refer to [reference needed]. Figure 5C The process is described in 575.

[0079] Figure 5B This is a flowchart of a method 550 for generating an initial design of mask features, consistent with various embodiments. In some embodiments, process 550 is performed as part of process P501 of process 500. At process P505, a target pattern 501 is obtained. The target pattern 501 may include one or more target features, such as Figure 6AThe target feature is 602. Figure 6A The target feature, consistent with various embodiments, has control points and an initial mask point. The target feature can have any shape, such as a circle, ellipse, polygon, etc. For example, target feature 602 is rectangular. Continuing on process P505, target feature 602 is associated with multiple control points, such as control point 656 and control point 662. In some embodiments, control points are associated with target feature 602 by segmenting target feature 602 into multiple segments and placing one or more control points on the edges of target feature 602 in each of the segments. Figure 6A In the example, control point 656 and another similar control point are placed at the midpoint of the shorter edge of target feature 602, and some control points (including control point 662) are placed on the longer edge of target feature 602. In some embodiments, control points on the target feature may be placed at user-defined locations on one or more edges of the target feature.

[0080] Multiple mask points 503 (such as mask points 604 and 606) are derived from target feature 602. Mask points 503 are a set of points that form a design of a mask feature corresponding to target feature 602. Mask points 503 can be connected using lines (e.g., curved or straight) to form a design of the mask feature. In some embodiments, mask points 503 are connected using curves to form a curved design. In some embodiments, the process of deriving mask points 503 from target feature 602 includes generating mask points 503 at user-defined locations (e.g., on or near target feature 602). Figure 6A As described, some mask points, such as mask point 604, are located on the edge of target feature 602, and some mask points, such as mask point 606, are located near the edge or corner of target feature 602. Mask point 503 can be adjusted, for example, by changing the position of the mask points to update the design (e.g., as at least referred to below). Figure 5C (As described).

[0081] Point-based OPC processes can begin with an initial design of mask features generated in various ways. For example, an initial design of mask features can be generated from target feature 602 by using mask points 503 derived from target feature 602 (as further described below). In another example, an input design 502 of mask features can be provided to process P505. Input design 502 can be obtained from another OPC process or generated using another OPC process. Examples of such OPC processes include machine learning freeform OPC, CTM freeform OPC, CTM+ freeform OPC, segment-based OPC, inverse lithography (ILT), machine learning (ML) based OPC, etc. Figure 6BThe design of the mask feature obtained from another process is described, consistent with various embodiments. An OPC process described above can be used to generate a mask feature design 654 (e.g., input design 502) from the target feature 602. Additionally, the shape of the design 654 can be curved. When the process receives the design 654 as input design 502, mask points 503 are derived from the design 654. For example, mask points 503 can be, for example, a set of points at user-defined locations on the design 654.

[0082] At process P507, mask points 503 are associated with control points to generate multiple control point-mask point associations 507. For example, a first association is generated between a set of mask points 658 and control points 656. This association can be generated based on user-defined input. For example, the user can select the set of mask points 658 to be associated with control point 656. In some embodiments, the associations are generated such that each control point is associated with the same number of mask points. For example, as... Figure 6B As illustrated, each control point is associated with three mask points (the association between mask points and control points is depicted using edges connecting the mask points to their corresponding control points). However, this is merely exemplary; any other suitable manner of associating one or more mask points with each control point may be used without departing from the scope of the invention. In some embodiments, the cost function at the control point is optimized by adjusting the position of one or more mask points associated with that control point, as at least with reference to the following... Figure 5C As described. Furthermore, the relationship between mask points and control points can change during the position adjustment process, as at least as described below. Figure 5C As described.

[0083] At process P509, a smoothing process is applied to mask points 503 to produce a design 509 of mask features. In some embodiments, the smoothing process may include applying curve fitting, which is the process of constructing a curve that best fits a set of data points (e.g., subject to constraints). Curve fitting may involve interpolation (where an exact fit to the data is required) or smoothing (where a “smooth” function that approximately fits the data is constructed). Figure 7 This describes the process of applying a smoothing process to mask points, consistent with various embodiments. Figure 7 In this process, a smoothing process is applied to mask points 503 (e.g., mask points 604 and 606) to produce a curved pattern 702 (e.g., design 509).

[0084] At process P511, a perturbation process is applied to design 509 to produce an enlarged (or reduced) design 511, which is an enlarged (or reduced) version of design 509. In some embodiments, the perturbation process enlarges (or reduces) design 509 by moving each of the mask points (e.g., by a specified distance) in a specified direction (e.g., a local normal). Figure 8 This describes a perturbed version of the initial design of a mask feature consistent with various embodiments. For example, by applying a perturbing process to curve pattern 702 (e.g., design 509 generated by a smoothing process), an enlarged version 802 of curve pattern 702 is generated. The enlarged version 802 can be input as the initial design 511 of the mask feature to... Figure 5C The design optimization process.

[0085] Figure 5C This is a flowchart of a process 575 for optimizing the design of mask features, consistent with various embodiments. In some embodiments, process 575 is performed as part of process P503 of process 500. At process P521, an initial design 511 is received as input. A process model, such as a resist and etching model, is applied to the initial design to obtain a simulation image (e.g., a resist image or an etching image), and the simulated image is used to calculate a cost function 521. In some embodiments, the cost function 521 is determined for each control point among the control points associated with the target feature 602. As described above, the cost function 521 can be one or more of EPE, simulation signal, process window, etc. For example, a cost function such as EPE can be determined using the simulated image by extracting the contour of the mask feature from the simulated image and comparing the contour with the target feature 602 to obtain the EPE at the control point.

[0086] At process P523, position adjustment data 523 for mask point 503 is determined for each control point, at least in part, based on cost function 521. In some embodiments, position adjustment data 523 may include slope and distance values ​​that one or more mask points associated with the control point must move to optimize cost function 521 (e.g., reduce or minimize EPE). For example, position adjustment data 523 for control point 656 may indicate the direction (e.g., direction of local normals or other directions) and distance that one or more mask points from that set of mask points 658 must move to minimize EPE at control point 656. The determination of position adjustment data 523 may also take into account the current position of the mask points associated with the control point and the geometric information (e.g., shape) of the target feature. For example, the determination of position adjustment data 523 for control point 656 may take into account the current position of that set of mask points 658 and the geometric information (e.g., shape) of the target feature 602.

[0087] At process P525, the positions of one or more mask points associated with each control point are adjusted based on position adjustment data 523 to optimize the cost function 521. After adjusting the positions of one or more mask points, a modified design 525 is generated, for example, as... Figure 9 As explained in the text.

[0088] Figure 9 This describes an optimized design of mask features consistent with various embodiments. After adjusting the positions of one or more mask points in the initial design 511, a modified design 902a (e.g., modified design 525) is produced. It should be noted that... Figure 9 The explanation is that by moving one or more mask points 658 relative to control point 656, the cost function 521, such as EPE, at control point 656 is reduced from an initial value to “3.5 nm”. In some embodiments, EPE is determined by obtaining a simulated image (e.g., a resist image or an etched image) from the modified design 902a, extracting a contour 912a from the simulated image, and measuring the distance between points on contour 912a and control point 656. In some embodiments, when adjusting mask points, the process may split the design into multiple segments (e.g., arcuate segments) and then apply adjustments to said segments of the design. For example, multiple mask points may be adjusted jointly (e.g., consistently) or individually (e.g., separately).

[0089] At process P527, a smoothing process is applied to the modified design 902a. As described above, the smoothing process can be a curve fitting process that constructs a curve that best fits a set of data points (e.g., adjusted mask points).

[0090] At process P529, the MRC process is applied to the modified design 902a to further update the modified design 902a to ensure that the modified design 902a complies with the constraints of the mask manufacturing process or equipment (e.g., the mask design width is within the allowed (e.g., minimum or maximum) mask design width).

[0091] At process P531, a determination is made as to whether the optimization conditions are met. If the optimization conditions are met (e.g., cost function 521 is optimized or a predefined number of iterations are performed), process 575 ends. If the optimization conditions are not met, the modified design 902a is input to process P521 and process 575 is repeated to further optimize cost function 521 by adjusting mask points and generating another modified design. In some embodiments, process 575 for optimizing the mask feature design (e.g., initial design 511 or modified design 902a) is an iterative process, and iterations are repeated (e.g., the above processes such as P521 to P529) until cost function 521 is optimized or a predefined number of iterations are performed, wherein each iteration generates a modified design by adjusting one or more mask points. After several iterations, a modified final mask design 525 is generated. In some embodiments, cost function 521 associated with the modified final design 525 is optimized. For example, in Figure 9 After several iterations, a modified final design 902b (e.g., a modified final design 525) is generated. It should be noted that the cost function 521 (such as EPE) in the modified final design 902b at control point 656 is “1.1nm”, which is less than the “3.5nm” EPE in the initial iteration. That is, the EPE decreases as the number of iterations increases (e.g., the cost function 521 is optimized). In some embodiments, further optimization to an EPE of “1.1nm” may not be necessary, and therefore, the modified design 902b can be considered to correspond to the final optimized design of the mask feature of the target feature 602. In some embodiments, the EPE is determined by obtaining a contour 912b (e.g., based on a simulated image as described above) and measuring the distance between points on the contour 912b and control point 656.

[0092] In some embodiments, when optimizing the modified design 525 over several iterations, the association between mask points and control points can be "fixed" or "dynamic." For example, in a fixed mode, if a first set of mask points is associated with a first control point in the first iteration, then the first set of mask points remains associated with the first control point in all iterations. In a dynamic mode, if the first set of mask points is associated with a first control point in the first iteration, then one or more mask points from the first set of mask points can be associated with a second control point in the second iteration to optimize the cost function 521. That is, existing associations between mask points and control points can be broken and new associations can be established. This dynamic adjustment will be helpful in various situations, such as when the modified design becomes significantly different from the shape of the target feature (which can be determined by comparing the modified design with the target feature). In this way, the cost function 521 at the control points can be optimized more effectively by intelligently selecting the mask points to be corrected.

[0093] In another association mode (referred to as the "soft" mode), a defined association may not exist between the mask point and the control point. The mask point can be adjusted based on a cost function 521 associated with each control point within a certain distance of the mask point. In some embodiments, the selected "soft" association mode may depend on the geometry of the target feature 602. For example, the amount of mask point adjustment may depend on the distance between the mask point and the control point and the angle between the local normal at the mask point and the line connecting the mask point and the control point.

[0094] While referring to the foregoing description of the cost function 521 for EPE, other cost functions such as simulation signals or process windows may also be used. If cost function 521 is a simulation signal, process 575 may adjust the position of the mask point to optimize the simulation signal by decreasing it (e.g., until minimizing it). In another example, if cost function 521 is a process window, process 575 may adjust the position of the mask point to optimize the process window by increasing it (e.g., until maximizing it). In yet another example, if cost function 521 is a combination of one or more metrics such as EPE and process window, process 575 may adjust the position of the mask point to optimize both EPE and process window by decreasing EPE (e.g., until minimizing it) and increasing the process window (e.g., until maximizing it). In some embodiments, cost functions such as simulation signals or EPE are local cost functions, such as cost functions local to control points, while cost functions such as process windows are global cost functions related to one or more target features globally. In some embodiments, conflicts may arise when optimizing both local and global cost functions. In such cases, optimization is achieved through trade-offs (e.g., other local or global cost functions can be optimized without optimizing one or more local cost functions, or vice versa). For example, if the simulated signal or EPE at one control point is affected by the simulated signal or EPE at another control point (e.g., an adjacent control point), both local cost functions may not be optimized simultaneously, and a trade-off optimization may be employed, such as one of them being optimized or both being optimized to a certain extent (e.g., EPE is reduced but not minimized), with one not affecting the other.

[0095] While the foregoing description describes the design of optimizing a single mask feature, a mask pattern can have multiple such mask features corresponding to multiple target features in a target pattern. A point-based optimization process (e.g., process 500) can be performed on all mask features in the mask pattern to produce an optimized design for the corresponding mask features. The mask pattern with the optimized design of the mask features (such as optimized design 902b) can then be used to fabricate a mask that can be used to transfer the mask pattern to a substrate.

[0096] Point-based optimization processes for generating or optimizing mask feature designs can be used in a variety of applications. Figures 10A to 10D This illustrates various exemplary applications of the design optimization process consistent with various embodiments. Figure 10A An exemplary application of a point-based optimization process is illustrated, wherein an optimized design (e.g., optimized design 1002) of mask features is generated for a target feature such as a square as illustrated (e.g., target feature 1001). Figure 1OB illustrates an exemplary application of a point-based optimization process, in which an optimized design of mask features (e.g., optimization design 1008) is generated for target features such as circles and ellipses (e.g., target feature 1007). Figure 10C This illustrates an exemplary application of a point-based optimization process, where optimized design of mask features is generated for target features such as tilted patterns. Figure 10C In this point-based optimization process, different types of mask features, such as principal features (e.g., target features) and SRAFs, are not separated; rather, optimization designs are generated for both principal features and SRAFs. For example, mask pattern 1003 includes mask features corresponding to principal features (e.g., target features) and SRAFs. The point-based optimization process generates an optimized design 1010 for mask features corresponding to target feature 1005. Figure 1 In OD, the point-based optimization process separates different types of mask features and produces optimized designs for mask features targeting the main feature rather than the SRAF. For example, mask pattern 1017 includes mask features corresponding to both the main feature (e.g., the target feature) and the SRAF. The point-based optimization process produces an optimized design 1025 for mask features corresponding to the target feature 1020.

[0097] While point-based optimization processes can generate an initial design of mask features from target features and optimize that initial design, they can also be used to improve the design of mask features generated through other OPC processes, such as free-form processes. Figure 10C and Figure 10D In the example, an initial design of mask features is generated using a free-form process, and then the initial design is fed into a point-based optimization process to optimize it into optimized designs 1010 and 1025.

[0098] In some embodiments, point-based optimization processes are more efficient than other OPC processes. For example, a point-based optimization process can optimize the cost function in fewer iterations than other processes, thereby minimizing the computational resources consumed in generating the optimized design, such as processor runtime and memory. In another example, a point-based optimization process achieves better optimization of the cost function compared to other OPC processes, while consuming fewer computational resources, such as processor runtime and memory.

[0099] In some embodiments, using a point-based optimization process in conjunction with other OPC processes is more efficient than using the other OPC processes without a point-based optimization process. That is, other OPC processes are used to generate an initial design, and then a point-based optimization process is used to optimize the initial design to achieve improved efficiency. For example, compared to the computational resources consumed by other processes in generating the optimized design without using a point-based optimization process, a point-based optimization process can generate an optimized design from the initial design by consuming fewer computational resources (e.g., processor runtime and memory). Furthermore, a point-based optimization process can achieve better optimization of the cost function compared to what would be achieved by other OPC processes without using a point-based optimization process.

[0100] In some embodiments, the point-based optimization process can be incorporated into the source mask optimization (SMO) flow by optimizing the mask point positions along with the source of the lithography apparatus to optimize the process window. For example, in each iteration of SMO, the direction and amount of movement of each mask point can depend on the source shape, which is also optimized in the same SMO iteration. The mask output from SMO is then composed of optimized mask points that are smoothly connected (e.g., using a smoothing process).

[0101] Figure 11 This is a block diagram illustrating a computer system 100 that can assist in implementing the methods, processes, or apparatus disclosed in this invention. The computer system 100 includes a bus 102 or other communication mechanism for transmitting information, and a processor 104 (or multiple processors 104 and 105) connected to the bus 102 for processing information. The computer system 100 also includes a main memory 106, such as random access memory (RAM) or other dynamic storage, connected to the bus 102 for storing information and instructions to be executed by the processor 104. The main memory 106 may also be used to store temporary variables or other intermediate information during the execution of instructions to be executed by the processor 104. The computer system 100 also includes a read-only memory (ROM) 108 or other static storage device connected to the bus 102 for storing static information and instructions for the processor 104. A storage device 110, such as a magnetic disk or optical disk, is provided and connected to the bus 102 for storing information and instructions.

[0102] Computer system 100 can be connected via bus 102 to a display 112 for displaying information to a computer user, such as a cathode ray tube (CRT), flat panel display, or touch panel display. Input device 114, including letter keys and other buttons, is connected to bus 102 to transmit information and command selections to processor 104. Another type of user input device is a cursor controller 116, such as a mouse, trackball, or cursor direction keys, for transmitting directional information and command selections to processor 104 and for controlling cursor movement on display 112. 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)), which allow the device to specify its position in a plane. Touch panel (screen) displays can also be used as input devices.

[0103] According to one embodiment, a portion of one or more methods described herein can be performed by computer system 100 in response to processor 104 executing one or more sequences of instructions included in main memory 106. Such instructions may be read into main memory 106 from another computer-readable medium, such as storage device 110. Execution of the instruction sequence included in main memory 106 causes processor 104 to perform the process steps described herein. One or more processors in a multiprocessor configuration may also be used to execute the instruction sequence included in main memory 106. In alternative embodiments, hard-wired circuitry may be used instead of or in combination with software instructions. Therefore, the description herein is not limited to any particular combination of hardware circuitry and software.

[0104] As used herein, the term "computer-readable medium" refers to any medium that participates in providing instructions to processor 104 for execution. This medium can take many forms, including but not limited to non-volatile media, volatile media, and transmission media. Non-volatile media include, for example, optical discs or magnetic disks, such as storage device 110. Volatile media include volatile memory, such as main memory 106. Transmission media include coaxial cables, copper wires, and optical fibers, including wires including bus 102. Transmission media can also take the form of sound waves or light waves, such as sound waves or light waves generated during radio frequency (RF) and infrared (IR) data communications. Common forms of computer-readable media include, for example, floppy disks, flexible disks, hard disks, magnetic tapes, any other magnetic media, CD-ROMs, DVDs, any other optical media, punched cards, paper tapes, any other physical media with a perforated pattern, RAM, PROMs and EPROMs, FLASH-EPROMs, any other memory chips or cartridges, carrier waves as described below, or any other media that can be read by a computer.

[0105] The transmission of one or more instructions to processor 104 for execution can involve various forms of computer-readable media. For example, the instructions may initially be carried on a disk of a remote computer. The remote computer may load the instructions into its volatile memory and transmit them via a telephone line using a modem. A modem local to computer system 100 may receive data over the telephone line and use an infrared transmitter to convert the data into an infrared signal. An infrared detector coupled to bus 102 may receive the data carried in the infrared signal and place the data on bus 102. Bus 102 carries the data to main memory 106, from which processor 104 fetches and executes instructions. Instructions received by main memory 106 may optionally be stored on storage device 110 before or after execution by processor 104.

[0106] Computer system 100 may also include a communication interface 118 coupled to bus 102. Communication interface 118 provides a bidirectional data communication connection to network link 120, which is connected to local area network 122. For example, communication interface 118 may 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 118 may be a local area network (LAN) card to provide a data communication connection to a compatible LAN. A wireless link may also be implemented. In any such implementation, communication interface 118 transmits and receives electrical, electromagnetic, or optical signals carrying digital data streams representing various types of information.

[0107] Network link 120 typically provides data communication to other data devices via one or more networks. For example, network link 120 may provide connectivity to host computer 124 or to data devices operated by Internet Service Provider (ISP) 126 via local area network 122. ISP 126, in turn, provides data communication services via a global packet data communication network (now commonly referred to as the "Internet") 128. Both local area network 122 and Internet 128 use electrical, electromagnetic, or optical signals carrying digital data streams. Signals via various networks and signals on network link 120 and via communication interface 118 (which carry digital data to and from computer system 100) are exemplary forms of carriers for transmitting information.

[0108] Computer system 100 can send messages and receive data (including program code) via a network, network link 120, and communication interface 118. In an Internet example, server 130 may transmit requested program code for an application via the Internet 128, ISP 126, local area network 122, and communication interface 118. For example, such a downloaded application can provide all or part of the methods described herein. The received program code can be executed by processor 104 upon receipt and / or stored in storage device 110 or other non-volatile memory for later execution. In this way, computer system 100 can obtain application code in carrier form.

[0109] Figure 12 An exemplary photolithography projection apparatus that can be utilized in conjunction with the techniques described herein is schematically depicted. The apparatus includes:

[0110] - An irradiation system IL, which is used to modulate the radiation beam B. In this particular case, the irradiation system also includes a radiation source SO;

[0111] - A first stage (e.g., a pattern forming apparatus stage) MT, the first stage having a pattern forming apparatus holder for holding a pattern forming apparatus MA (e.g., a mask), and connected to a first locator for accurately positioning the pattern forming apparatus relative to an article PS;

[0112] - Second stage (substrate stage) WT, the second stage having a substrate holder for holding the substrate W (e.g., a silicon wafer coated with resist) and connected to a second positioner for accurately positioning the substrate relative to the article PS;

[0113] - A projection system (“lens”) PS (e.g., a refractive, reflective, or reflective-refractive optical system) for imaging an illuminated portion of the pattern forming apparatus MA onto a target portion C (e.g., comprising one or more dies) of the substrate W.

[0114] As described herein, the device is of the transmissive type (i.e., having a transmissive pattern forming apparatus). However, in general, it can also be of the reflective type, for example (having a reflective pattern forming apparatus). The device can use a different kind of pattern forming apparatus than a classic mask; examples include programmable mirror arrays or LCD matrices.

[0115] A source SO (e.g., a mercury lamp or excimer laser, LPP (laser-generated plasma) EUV source) generates a radiation beam. This beam may be fed directly into an irradiation system (irradiator) IL, or after passing through an adjustment member such as a beam expander Ex. The irradiator IL may include an adjustment member AD for setting the outer radial range and / or inner radial range (typically referred to as σ_outer and σ_inner, respectively) of the intensity distribution in the beam. Additionally, the irradiator IL will typically include various other components, such as a beam accumulator IN and a condenser CO. Thus, the beam B irradiated onto the pattern forming apparatus MA has the desired uniformity and intensity distribution in its cross-section.

[0116] about Figure 12 It should be noted that the source SO can be inside the housing of the photolithography projection device (this is often the case when the source SO is, for example, a mercury lamp), but the source SO can also be located away from the photolithography projection device, and the radiation beam generated by the source SO (e.g., by means of a suitable guiding mirror) is guided into the device; this latter scenario is often the case when the source SO is an excimer laser (e.g., based on KrF, ArF or F2 laser action).

[0117] The beam PB then intercepts the pattern forming apparatus MA held on the pattern forming apparatus stage MT. Having passed through the pattern forming apparatus MA, the beam B passes through the lens PL, which focuses the beam B onto the target portion C of the substrate W. The substrate stage WT can be accurately moved, for example, to position the different target portions C within the path of the beam PB, by means of a second positioning member (and an interferometry member IF). Similarly, the first positioning member can be used to accurately position the pattern forming apparatus MA relative to the path of the beam B, for example, after it has been mechanically retrieved from the pattern forming apparatus library or during scanning. Generally, this will be achieved by means of... Figure 12 The long-stroke module (coarse positioning) and short-stroke module (fine positioning) are clearly described in the diagram to realize the movement of the stages MT and WT. However, in the case of a stepper (relative to a stepping scanning tool), the pattern forming apparatus stage MT may be connected only to the short-stroke actuator, or it may be fixed.

[0118] The depicted tools can be used in two different modes:

[0119] - In step mode, the pattern forming apparatus stage MT is kept substantially stationary, and the entire pattern forming apparatus image is projected (i.e., a single "flash") onto the target portion C. Then, the substrate stage WT is shifted in the x and / or y directions so that different target portions C can be illuminated by the beam PB;

[0120] In scanning mode, the same principle applies, except that the given target portion C is not exposed in a single "flash". Instead, the pattern forming apparatus stage MT can move at a speed v in a given direction (the so-called "scanning direction", e.g., the y-direction), causing the projection beam B to scan the entire pattern forming apparatus image; simultaneously, the substrate stage WT moves simultaneously in the same or opposite direction at a speed V = Mv, where M is the magnification of the lens PL (typically M = 1 / 4 or = 1 / 5). In this way, a relatively large target portion C can be exposed without compromising resolution.

[0121] Figure 13 Another exemplary photolithography projection device 1000 that can be utilized in conjunction with the techniques described herein is schematically depicted.

[0122] The photolithography projection device 1000 includes:

[0123] -Source collector module SO;

[0124] - Irradiation system (irradiator) IL, the irradiation system being configured to modulate the radiation beam B (e.g., EUV radiation);

[0125] - A support structure (e.g., a pattern forming apparatus stage) MT, the support structure being configured to support a pattern forming apparatus (e.g., a mask or mask plate) MA, and connected to a first positioner PM configured to accurately position the pattern forming apparatus;

[0126] - A substrate stage (e.g., a wafer stage) WT, the substrate stage being configured to hold a substrate (e.g., a wafer coated with resist) W and connected to a second positioner PW configured to accurately position the substrate; and

[0127] - A projection system (e.g., a reflective projection system) PS, the projection system being configured to project a pattern, given by a patterning apparatus MA to a radiation beam B, onto a target portion C (e.g., comprising one or more dies) of a substrate W.

[0128] As described herein, device 1000 is of the reflective type (e.g., using a reflective patterning apparatus). It should be noted that because most materials are absorptive in the EUV wavelength range, the patterning apparatus can have a multilayer reflector comprising, for example, multiple stacks of molybdenum and silicon. In one example, the multilayer reflector has 40 pairs of molybdenum and silicon layers, each layer being a quarter wavelength thick. Even smaller wavelengths can be produced using X-ray lithography. Since most materials are absorptive at both EUV and X-ray wavelengths, the patterned absorbing material flakes on the patterning apparatus morphology (e.g., a TaN absorber on top of a multilayer reflector) define where features will be printed (positive resist) or not (negative resist).

[0129] Reference Figure 13 The irradiator IL receives an extreme ultraviolet (EUV) 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 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 13 The laser (not shown) is a component of an EUV radiation system used to provide a laser beam for exciting the fuel. The resulting plasma emits output radiation, such as EUV radiation, which is collected using a radiation collector located in the 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.

[0130] In such cases, the laser is not considered a component of the lithography apparatus, and the radiation beam is delivered from the laser to the source collector module by means of a beam delivery system including, for example, suitable guiding mirrors and / or beam expanders. In other cases, such as when the source is a discharge-generated plasma EUV generator (often referred to as a DPP source), the source can be an integral part of the source collector module.

[0131] 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.

[0132] A radiation beam B is 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 is patterned by the pattern forming apparatus. After being reflected 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, for example, to position different target portions C within the path of the radiation beam B, by means of a second locator PW and a position sensor PS2 (e.g., an interferometer, 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.

[0133] The depicted device 1000 can be used in at least one of the following modes:

[0134] 1. In step mode, the support structure (e.g., patterning apparatus stage) MT and substrate stage WT are kept substantially stationary (i.e., single static exposure) while the entire pattern to be applied to the target portion C is projected onto the target portion C in one step. Then, the substrate stage WT is shifted in the X and / or Y directions so that different target portions C can be exposed.

[0135] 2. In scanning mode, while the pattern to be irradiated is projected onto the target portion C, the support structure (e.g., patterning apparatus stage) MT and the substrate stage WT are scanned simultaneously (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.

[0136] 3. In another mode, while the pattern to be irradiated is projected onto the target portion C, the support structure (e.g., a patterning apparatus stage) MT is kept substantially stationary, thereby holding the programmable patterning apparatus in place, and the substrate stage WT is moved or scanned. 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 successive 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.

[0137] Figure 14The apparatus 1000 is shown in more detail, comprising a source collector module SO, an irradiation system IL, and a projection system PS. The source collector module SO is constructed and configured such that a vacuum environment can be maintained within the enclosure structure 220 of the source collector module SO. An EUV radiation emitting plasma 210 can be formed by a discharge-generated plasma source. EUV radiation can be generated by a gas or vapor (e.g., Xe gas, Li vapor, or Sn vapor), wherein an extremely hot plasma 210 is generated to emit radiation in the EUV range of the electromagnetic spectrum. For example, the extremely hot plasma 210 is generated by a discharge that causes at least partial ionization of the 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 an embodiment, an excited tin (Sn) plasma is provided to generate EUV radiation.

[0138] Radiation emitted by the thermal plasma 210 is transferred from the source chamber 211 to the collector chamber 212 via a selected gas barrier or contaminant trap 230 (in some cases also referred to as a contaminant barrier or foil trap) located in or behind an opening in the source chamber 211. The contaminant trap 230 may include a channel structure. The contaminant trap 230 may also include a gas barrier, or a combination of a gas barrier and a channel structure. As is known in the art, the contaminant trap or contaminant barrier 230 further indicated herein includes at least a channel structure.

[0139] Collector chamber 211 may include a radiation collector CO, which may be a so-called grazing incidence collector. The radiation collector CO has an upstream radiation collector side 251 and a downstream radiation collector side 252. Radiation passing through the collector CO may be reflected from a grating spectral filter 240 to be focused into a virtual source point IF along an optical axis indicated by the dashed line "O". The virtual source point IF is commonly referred to as the intermediate focus, and the source collector module is configured such that the intermediate focus IF is located at or near an opening 221 in the enclosure structure 220. The virtual source point IF is an image of the radiative emission plasma 210.

[0140] Subsequently, the radiation passes through 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 configured to provide a desired angular distribution of the radiation beam 21 at the patterning apparatus MA, and a desired uniformity of radiation intensity at the patterning apparatus MA. After the radiation beam 21 is reflected at the patterning apparatus MA held by the support structure MT, a patterned beam 26 is formed, and the patterned beam 26 is imaged by the projection system PS onto the substrate W held by the substrate stage WT via reflective elements 28 and 30.

[0141] Components exceeding those shown can typically be present in the illumination optics unit IL and the projection system PS. Depending on the type of photolithography equipment, a grating spectral filter 240 may optionally be present. Furthermore, more mirrors than shown in the figures may be present; for example, more mirrors than are shown in the projection system PS. Figure 12 The shown reflective elements have 1 to 6 additional reflective elements.

[0142] like Figure 12 The collector optics CO described herein are depicted as a nested collector with grazing incidence reflectors 253, 254, and 255, as an example only of a collector (or collector mirror). The grazing incidence reflectors 253, 254, and 255 are configured to be axially symmetrical about the optical axis O, and this type of collector optics CO can be used in combination with a discharge-generated plasma source, often referred to as a DPP source.

[0143] Alternatively, the source collector module SO can be as follows: Figure 15 The components of the LPP radiation system shown are illustrated. A laser LA is configured to deposit laser energy onto a fuel such as xenon (Xe), tin (Sn), or lithium (Li), thereby generating a highly ionized plasma 210 with an electron temperature of tens of electron volts. High-energy radiation generated during the de-excitation and recombination of these ions is emitted from the plasma, collected by a near-normal incident collector optics CO, and focused onto an opening 221 in the enclosure structure 220.

[0144] As mentioned above, at least refer to Figures 5A to 1 The “full-angle OPC” technique described by OD generates a curved pattern for a mask feature corresponding to a target feature in a target pattern. This curved pattern is generated by adjusting mask points derived from the input mask feature or the corresponding target feature until the cost function is optimized. In some embodiments, the “full-angle OPC” technique can generate non-curved designs (e.g., polygonal patterns where segments or lines of the pattern are at angles of 45*n degrees or 90*n degrees to the horizontal axis, where n is an integer) or hybrid designs (e.g., designs that are partly curved and partly polygonal). Additionally, such designs can be generated for mask features that can be (a) a master feature corresponding to the target feature or (b) a SRAF. It should be noted that the terms “polygonal design” or “polygonal pattern” used herein refer to a pattern where segments or lines of the pattern are at angles of 45*n degrees or 90*n degrees to the horizontal axis, where n is an integer. In some embodiments, at least referenced… Figures 5A to 5CThe described method generates a polygonal pattern by adjusting the mask points so that the angle between two straight lines in the final design (e.g., the modified final design 525 or 902b) is 45*n degrees or 90*n degrees. For example, at least referring to Figure 5B The described smoothing process or at least referencing Figure 5C The described cost function 521 (cost function 521 is used to determine the position adjustment data of the mask points) can be adapted to produce polygonal or hybrid designs for mask features rather than curve designs.

[0145] The type of design to be generated (e.g., curved, polygonal, or hybrid) can be determined based on one or more parameters. In some embodiments, mask features can be generated as polygonal or hybrid designs based on user preference. For example, a user can choose to generate mask features as polygonal or hybrid designs instead of curved designs to minimize the complexity of manufacturing a pattern forming apparatus with curved designs. In some embodiments, mask features can be generated as polygonal or hybrid designs to better optimize the cost function (e.g., EPE, MRC violation penalties) compared to what can be achieved using curved designs. For example, when generating mask features using curved designs, the cost function (such as EPE) can be reduced to a first value, but when generating mask features using polygonal or hybrid designs, the cost function can be reduced even further to a second value (second value < first value). In some embodiments, mask features can be generated as polygonal or hybrid designs when the target pattern has a dense configuration of target features and generating a curved design may violate one or more MRC constraints, such as mask feature size, width, distance between two mask features, or other MRC constraints. For example, when mask features are generated as a curved design, the distance between two mask features may be less than a minimum distance threshold, but when mask features are generated as polygonal or hybrid designs, the distance between two mask features may be equal to or greater than the minimum distance threshold. In some embodiments, mask features may be generated as a curved design of a specified portion of the target feature and as a polygonal design of other portions of the target feature. For example, a mask feature may be generated as a curved design of a portion of the target feature close to one or more vertices or line ends of the target feature, and as a polygonal design of the remaining portion of the target feature (e.g., as shown in the image). Figure 17 (As described in the document). In some embodiments, mask features may be generated as polygonal or hybrid designs rather than curved designs to minimize the computational resources consumed when generating curved designs.

[0146] Figure 16A The curved design of the mask feature is illustrated, consistent with various embodiments. The mask feature 1604 corresponding to target feature 1602 is generated as a curved design. In some embodiments, mask feature 1604 is similar to... Figure 9The modified design 902b, and target feature 1602 is similar to target feature 602.

[0147] Figure 16B This describes a polygonal design of mask features consistent with various embodiments. Mask feature 1606 corresponding to target feature 1602 is generated as a polygonal design (e.g., a design constructed using straight lines). In some embodiments, this is done in conjunction with at least reference... Figures 5A to 10D The described method generates mask feature 1606 in a similar manner, except that mask feature 1606 is generated as a polygon and not as a curved pattern.

[0148] Figure 16C The curved and polygonal designs of the mask features, consistent with various embodiments, are described. Mask feature 1604, corresponding to target feature 1602, is generated as a curved design. Mask feature 1614, corresponding to SRAF, is generated as a polygonal design.

[0149] Figure 16D The curved and polygonal designs of the mask features consistent with various embodiments are described. Mask feature 1606 corresponding to target feature 1602 is generated as a polygonal design, while mask feature 1616 corresponding to SRAF is generated as a curved design.

[0150] Figure 17 This describes a hybrid design of mask features consistent with various embodiments. Mask feature 1704, corresponding to target feature 1702, is generated as a hybrid design, wherein a first portion 1706 is generated as a polygonal design and a second portion 1708 (e.g., near a vertex of target feature 1702) is generated as a curved design. In some embodiments, mask feature 1704 is similar to... Figure 9 The modified design 902b (except that mask feature 1704 is generated as a polygon and curve pattern) and target feature 1702 is similar to target feature 602.

[0151] Although Figure 16C and Figure 16D This illustrates specific combinations of designs for mask features, such as Figure 16C The curve design for master mask feature 1604 and the polygon design for SRAF mask feature 1614, and Figure 16D The design of the polygon for the master mask feature 1606 and the curve design for the SRAF mask feature 1616 are given, but various other combinations are also possible. For example, the master mask feature and the SRAF mask feature can have the same design. In another example, the design of the master mask feature can be different from the design of the SRAF mask feature. In yet another example, no SRAF mask feature may be generated.

[0152] Figure 18 The description is consistent with the various embodiments for execution. Figure 5A The flowchart of the "All-Angle OPC" method described in the document.

[0153] At process P1801, multiple segments 1801, which are target images corresponding to the target pattern, are input into the CTM engine to perform OPC on the segments 1801, thereby generating a CTM or CTM+ mask image 1802. In some embodiments, the CTM engine may perform multiple stages of CTM and CTM+ on the segments 1801 to obtain a mask image 1802 as the result of optimized OPC. The mask image 1802 may include both principal features and SRAF. The mask image 1802 can be used as a ground truth for training a machine learning (ML) model 1805 to generate a mask pattern (e.g., post-OPC) for any given target pattern.

[0154] At process P1802, fragment 1801 and mask image 1802 are provided as training datasets to ML model 1805 to train ML model 1805. In some embodiments, training ML model 1805 can be an iterative process, and each iteration may include: determining a cost function indicating the difference between the predicted mask pattern (e.g., the mask pattern generated by ML model 1805) and the mask image input to ML model 1805; and adjusting the parameters of ML model 1805 to minimize the cost function. ML model 1805 is considered trained when the cost function is minimized (e.g., the difference between the predicted mask pattern and the input mask image is less than a threshold). After ML model 1805 is well trained, ML model 1805 can be used to generate mask patterns for any given target pattern.

[0155] The target image 1803 of the target pattern is input into the trained ML model 1805 to obtain a mask pattern 1804 for the target pattern. In some embodiments, the mask pattern 1804 generated by the ML model 1805 may not be optimized (e.g., the EPE may not be optimized).

[0156] At process P1803, mask pattern 1804 is input into the full-angle OPC module, which executes the full-angle OPC method (e.g., as at least referring to...). Figures 5A to 5C (As described) to improve mask pattern 1804 and produce improved mask pattern 1807. In some embodiments, the improved mask pattern 1807 and... Figure 5C The modified final mask design 525 is similar. In some embodiments, the improved mask pattern 1807 may be optimized (e.g., the EPE may be optimized). Additionally, the mask pattern 1807 may have a curved design, a polygonal design, or a hybrid design.

[0157] In some embodiments, the difference between full-angle OPC and free-form OPC lies in that full-angle OPC generates a mask pattern by adjusting mask points associated with the mask pattern, while free-form OPC generates a mask pattern by adjusting pixel values ​​in an image corresponding to the design layout. Additionally, in previous segment-based OPC methods, while segment angles are preserved (e.g., segments are limited to angles of 45*n degrees, where n is an integer), the number of mask points used to adjust the mask pattern may not be preserved. In contrast, in full-angle OPC, neither the number of mask points nor the angles between segments of the mask pattern are preserved during the adjustment process, because mask points can be added or removed during the adjustment process and the angles between segments can be any angle (e.g., any degree, such as "0" to "360" degrees for curve design, and 45*n or 90*n degrees for polygon design). Furthermore, in the full-angle OPC technology, compared to the segment-based OPC method where the edge segments of the mask pattern are adjusted along the segment normal direction, the mask points can be moved in any direction.

[0158] In some embodiments, the full-angle OPC technique can be combined with other OPC techniques to generate mask patterns. Each technique can be used to generate different mask features or different portions of a mask feature, and each technique can be used to generate polygonal or curved designs. For example, for Figure 16D The target feature 1602 described herein can be generated by segment-based OPC technology or image-based OPC technology, and full-angle OPC technology can be generated by OPC technology, which is described as 1616.

[0159] While references to IC manufacturing may be specifically made herein, it should be clearly understood that the descriptions herein have many other possible applications. For example, the descriptions herein can be used to manufacture integrated optical systems, guide and detection patterns for magnetic domain memory, liquid crystal display panels, thin-film magnetic heads, etc. Those skilled in the art will understand that, in the context of such alternative applications, any use of the terms “mask,” “wafer,” or “die” herein should be considered interchangeable with the more general terms “mask,” “substrate,” and “target portion,” respectively.

[0160] In this document, the terms “radiation” and “beam” are used to cover all 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).

[0161] The concepts disclosed herein can be used to simulate or mathematically model any general imaging system for imaging subwavelength features, and can be particularly applied to emerging imaging techniques capable of producing wavelengths with increasingly smaller dimensions. Emerging techniques already in use include EUV (Extreme Ultraviolet) lithography, which can produce wavelengths of 193 nm using ArF lasers and even 157 nm using fluorine lasers. Furthermore, EUV lithography can produce wavelengths in the range of 5 nm to 20 nm by using synchrotrons or by bombarding materials (solid or plasma) with high-energy electrons, thereby generating photons within this range.

[0162] While the concepts disclosed herein 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 lithography imaging system, for example, a lithography imaging system for imaging on substrates other than silicon wafers.

[0163] As used herein, the terms "optimizing" and "optimization" refer to or mean adjusting patterning equipment (e.g., photolithography equipment), patterning processes, etc., to give the result and / or process more desirable characteristics, such as higher projection accuracy of the pattern onto the substrate, a larger process window, etc. Therefore, as used herein, the terms "optimizing" and "optimization" refer to or mean the process of identifying one or more values ​​for one or more parameters that provide an improvement in at least one relevant metric compared to an initial set of one or more values ​​for those parameters, e.g., local optimization. The terms "optimization" and other related terms should be interpreted accordingly. In embodiments, optimization steps may be applied iteratively to provide a further improvement in one or more metrics.

[0164] The aspects of the invention can be implemented in any convenient form. For example, embodiments can be implemented by one or more suitable computer programs that can be carried on a suitable carrier medium, which may be a tangible carrier medium (e.g., a disk) or an intangible carrier medium (e.g., a communication signal). Embodiments of this disclosure can be implemented using suitable devices that can specifically take the form of a programmable computer executing a computer program configured to implement the methods described herein. Therefore, embodiments of this disclosure can be implemented in hardware, firmware, software, or any combination thereof. Embodiments of this disclosure can also be implemented as instructions stored on a machine-readable medium that can be read and executed by one or more processors. A machine-readable medium can include any means for storing or transmitting information in a form that can be read by a machine (e.g., a computing device). For example, a machine-readable medium can include: read-only memory (ROM); random access memory (RAM); disk storage media; optical storage media; flash memory devices; electrical, optical, acoustic, or other forms of propagation signals (e.g., carrier waves, infrared signals, digital signals, etc.). Additionally, firmware, software, routines, and instructions can be described herein as performing certain actions. However, it should be understood that such descriptions are for convenience only, and such actions are in fact caused by computing devices, processors, controllers, or other devices that execute firmware, software, routines, instructions, etc.

[0165] Embodiments of this disclosure can be further described in the following ways.

[0166] 1. A non-transitory computer-readable medium having instructions that, when executed by a computer, cause the computer to perform a method for improving the design of a pattern forming apparatus, the method comprising:

[0167] Obtain mask points for a design of mask features, wherein the mask features are associated with target features in a target pattern to be printed on a substrate; and

[0168] The positions of the mask points are adjusted to generate a modified design of the mask features based on the adjusted mask points.

[0169] 2. The computer-readable medium as described in aspect 1, wherein adjusting the position of the mask point is an iterative process, wherein each iteration includes:

[0170] Determine the cost function associated with the optical proximity effect correction process or the source mask optimization process.

[0171] For each control point on the target feature, the position data of the mask point is determined based on the cost function; and

[0172] The position of one or more mask points is adjusted based on the location data to optimize the cost function, wherein the adjustment includes updating the modified design.

[0173] 3. The computer-readable medium as described in aspect 2, wherein the cost function includes edge placement error or a simulation signal, and wherein optimizing the cost function includes reducing the cost function.

[0174] 4. The computer-readable medium as described in aspect 3, wherein determining the cost function comprises:

[0175] A simulation is performed using the modified design to obtain a simulation image, wherein the simulated image includes a resist image or an etched image.

[0176] Extracting contours from the simulated image, and

[0177] The edge placement error, which is the cost function, is determined based on the contour and the target features for each control point.

[0178] 5. The computer-readable medium as described in aspect 4, wherein adjusting the position of the mask point includes performing multiple iterations until the edge placement error is minimized.

[0179] 6. The computer-readable medium as described in aspect 3, wherein determining the cost function comprises:

[0180] Simulation is performed using the modified design to obtain resist image signals or etching image signals as simulation signals, and

[0181] Determine the simulation signal for each control point.

[0182] 7. The computer-readable medium as described in aspect 6, wherein adjusting the position of the mask point includes performing multiple iterations until the simulation signal is minimized.

[0183] 8. The computer-readable medium of aspect 2, wherein the cost function includes a process window for a patterning process of printing the modified design onto a substrate, and wherein optimizing the cost function includes increasing the process window.

[0184] 9. The computer-readable medium as described in aspect 8, wherein determining the cost function comprises:

[0185] Simulations are performed using the modified design to obtain simulation images, wherein the simulation images include resist images or etching images, and

[0186] The process window is obtained using the simulated image, wherein the process window includes the target pattern printed on the substrate using the modified design to meet predetermined specifications for the focal range and dose range.

[0187] 10. The computer-readable medium of aspect 9, wherein adjusting the position of the mask point includes performing multiple iterations until the process window is maximized.

[0188] 11. The computer-readable medium as described in aspect 2, wherein the cost function includes at least one of edge placement error, simulation signal, process window or mask rule check violation penalty.

[0189] 12. The computer-readable medium as described in aspect 1, wherein obtaining the mask points comprises:

[0190] The mask points are derived from the target features.

[0191] 13. The computer-readable medium as described in aspect 2, wherein adjusting the position of the mask point comprises:

[0192] The mask points are associated with control points on the target feature to generate a first association between a first set of mask points and a first control point, and a second association between a second set of mask points and a second control point.

[0193] 14. The computer-readable medium of aspect 13, wherein adjusting the position of the mask point comprises:

[0194] Based on the comparison between the modified design and the target features, the association between the mask points and the control points is modified.

[0195] 15. The computer-readable medium of aspect 13, wherein each control point on the target feature is associated with the same set of mask points in each iteration.

[0196] 16. The computer-readable medium of aspect 13, wherein one or more control points on the target feature are associated with different sets of mask points in at least two iterations.

[0197] 17. The computer-readable medium as described in aspect 1, wherein obtaining the mask points comprises:

[0198] A smoothing process is applied to the mask points, wherein the smoothing process performs curve fitting to connect the mask points with curves to produce the design as a first curve pattern.

[0199] 18. The computer-readable medium as described in aspect 17 further includes:

[0200] An image perturbation is performed on the design to produce an enlarged version of the design.

[0201] 19. The computer-readable medium as described in aspect 2, wherein adjusting the position of one or more of the mask points comprises adjusting a group of the mask points together.

[0202] 20. The computer-readable medium as described in aspect 2, wherein adjusting the position of one or more mask points includes adjusting the mask points individually.

[0203] 21. The computer-readable medium of aspect 2, wherein the position data of each mask point includes a slope value and a distance value, and the position adjustment of the corresponding mask point is performed with respect to a control point associated with the corresponding mask point by means of the slope value and the distance value.

[0204] 22. The computer-readable medium as described in aspect 2 further includes:

[0205] A smoothing process is applied to the modified design.

[0206] 23. The computer-readable medium as described in aspect 22 further includes:

[0207] The modified design is then subjected to a mask rule check process to satisfy the mask rule check constraints.

[0208] 24. The computer-readable medium as described in aspect 2, wherein adjusting the position of the mask points to produce the modified design includes performing a predetermined number of iterations.

[0209] 25. The computer-readable medium as described in aspect 1, wherein obtaining the design comprises:

[0210] The design is obtained from the target features through a process that generates the design, wherein the process includes one or more of the following: Optimal Proximity Correction (OPC) based on machine learning (ML), Continuous Transmission Mask (CTM) freeform OPC, CTM+freeform OPC, segment-based OPC, or reverse lithography.

[0211] 26. The computer-readable medium as described in aspect 1, wherein the mask feature is a sub-resolution auxiliary feature.

[0212] 27. The computer-readable medium according to any one of aspects 1 to 26 further includes:

[0213] The modified design is used to perform a patterning step to print a pattern onto the substrate via a patterning process.

[0214] 28. The computer-readable medium according to any one of aspects 1 to 27 further includes:

[0215] Manufacturing the pattern forming apparatus including structural features corresponding to the modified design.

[0216] 29. The computer-readable medium as described in aspect 28 further includes:

[0217] The modified design of the pattern forming apparatus is transferred to the substrate via a photolithography device.

[0218] 30. A non-transitory computer-readable medium having instructions that, when executed by a computer, cause the computer to perform a method for improving the design of a pattern forming apparatus, the method comprising:

[0219] The mask points for obtaining the mask features of the design, wherein the mask features correspond to target features in the target pattern to be printed on the substrate; and

[0220] The position of the mask point is adjusted to increase the process window, wherein the process window is associated with a patterning process for printing the target pattern onto a substrate, wherein the adjustment includes generating a modified design based on the adjusted position.

[0221] 31. The computer-readable medium of aspect 30, wherein adjusting the position is an iterative process, wherein each iteration includes:

[0222] The process window is obtained based on the modified design, wherein the process window includes a range of values ​​for at least one parameter of the patterning process for printing the target pattern onto the substrate using the modified design, and

[0223] Adjusting the position of one or more of the mask points to increase the range of the values ​​of the one or more parameters, wherein the adjustment includes updating the modified design.

[0224] 32. The computer-readable medium of aspect 31, wherein the at least one parameter includes at least one of dose or focus associated with a photolithography apparatus for printing the target pattern on the substrate.

[0225] 33. A non-transitory computer-readable medium having instructions that, when executed by a computer, cause the computer to perform a method for improving the design of a pattern forming apparatus, the method comprising:

[0226] The design of the target pattern to be printed on the substrate and the mask features corresponding to the target features in the target pattern is obtained;

[0227] Derive the mask points of the design; and

[0228] The design is iteratively updated by adjusting the position of one or more mask points based on a cost function, wherein the update produces a modified design of the mask features.

[0229] 34. The computer-readable medium as described in aspect 33, wherein obtaining the design comprises:

[0230] The design is obtained from the target pattern through a process that includes one or more of the following: Optimal Proximity Correction (OPC) based on Machine Learning (ML), Continuous Transmission Mask (CTM) Freeform OPC, CTM+Freeform OPC, Segment-based OPC, or Reverse Lithography.

[0231] 35. The computer-readable medium as described in aspect 33, wherein deriving the mask points comprises:

[0232] Associating the mask points with control points on the target feature, wherein the association includes associating a first set of mask points with a first control point and associating a second set of mask points with a second control point.

[0233] 36. The computer-readable medium as described in aspect 35, wherein iteratively updating the design includes performing the following operations in each iteration:

[0234] Determine the cost function, wherein the cost function includes edge placement error.

[0235] For each control point, the location data of the mask point is determined based on the cost function, and

[0236] Based on the location data, the position of one or more mask points is adjusted to reduce the cost function.

[0237] 37. The computer-readable medium of aspect 36, wherein iteratively updating the design includes performing several iterations until the cost function is minimized.

[0238] 38. The computer-readable medium as described in aspect 35, wherein iteratively updating the design includes performing the following operations in each iteration:

[0239] Determine the cost function, wherein the cost function includes a process window for the patterning process of printing the modified design onto a substrate.

[0240] For each control point, the location data of the mask point is determined based on the cost function, and

[0241] Based on the location data, the position of one or more mask points is adjusted to increase the cost function.

[0242] 39. The computer-readable medium of aspect 38, wherein iteratively updating the design includes performing several iterations until the cost function is maximized.

[0243] 40. A method for improving the design of a pattern forming apparatus, the method comprising:

[0244] The mask points for obtaining the mask features of the design, wherein the mask features correspond to target features in the target pattern to be printed on the substrate; and

[0245] The positions of the mask points are adjusted to generate a modified design based on the adjusted mask points.

[0246] 41. A method for improving the design of a pattern forming apparatus, the method comprising:

[0247] The mask points for obtaining the mask features of the design, wherein the mask features correspond to target features in the target pattern to be printed on the substrate; and

[0248] The position of the mask point is adjusted to increase the process window, wherein the process window is associated with a patterning process for printing the target pattern onto a substrate, wherein the adjustment includes generating a modified design based on the adjusted position.

[0249] 42. A method for improving the design of a pattern forming apparatus, the method comprising:

[0250] The design of the target pattern to be printed on the substrate and the mask features corresponding to the target features in the target pattern is obtained;

[0251] Derive the mask points of the design; and

[0252] The design is iteratively updated by adjusting the position of one or more mask points based on a cost function, wherein the update produces a modified design of the mask features.

[0253] 43. A computer program product comprising a non-transitory computer-readable medium having instructions recorded thereon, the instructions, when executed by a computer, performing the method as described in any of the preceding aspects.

[0254] 44. A non-transitory tangible computer-readable medium (CRM) storing instructions, which, when executed by a processor, cause the processor to perform optical proximity correction (OPC) using a method thereof:

[0255] Obtain the mask points of the design of the mask features; and modify the design of the mask features by performing OPC to adjust the position of the mask points.

[0256] 45. The medium as described in aspect 44, wherein the method further includes obtaining control points located on a target polygon of the mask feature, and wherein each control point is associated with one or more mask points.

[0257] 46. ​​The medium as described in aspect 45, wherein the modification includes performing curve fitting on the mask points to obtain the modified design of the mask features, and wherein the edges of the mask features in the modified design comprise curves fitted between the mask points.

[0258] 47. The medium as described in aspect 44, wherein performing OPC includes adjusting the position of the mask point to optimize the simulation signal or EPE at the control point.

[0259] 48. The medium as described in aspect 47, wherein the simulated signal is a resist image signal.

[0260] 49. The medium as described in aspect 47, wherein the adjustment includes consistently adjusting a plurality of mask points to optimize the simulation signal at an increasing number of control points.

[0261] 50. The medium as described in aspect 47, wherein the adjustment includes individually adjusting the mask points to optimize the simulation signal at one or more control points.

[0262] 51. The medium as described in aspect 44, wherein the mask points are initially obtained based on a target polygon design of the feature.

[0263] 52. The medium as described in aspect 44, wherein the isomask points are initially obtained based on a design generated by a segment-based OPC process.

[0264] 53. The medium as described in aspect 52, wherein the segment-based OPC process is a CTM free-form OPC process, a machine learning OPC process, or an ILT process.

[0265] 54. The medium as described in aspect 44, the method further comprising:

[0266] Establish the association between control points and mask points;

[0267] Break the association between the control point and the mask point; and

[0268] Establish the association between the control point and another mask point.

[0269] 55. The medium as described in aspect 54, wherein the breaking and / or the re-establishment is based on a comparison of the modified design with the target polygon of the feature.

[0270] 56. The medium as described in aspect 44, wherein the mask feature is a main feature or SRAF.

[0271] 57. The medium as described in aspect 44, further comprising determining the process window based on the adjusted design of the mask features.

[0272] 58. A non-transitory tangible computer-readable medium (CRM) storing instructions, which, when executed by a processor, cause the processor to perform source mask optimization (SMO) using a method thereof:

[0273] Obtain the mask points of the design of the mask features; and modify the design of the mask features by adjusting the position of the mask points according to the SMO process optimization window.

[0274] 59. The computer-readable medium as described in aspect 1, wherein adjusting the position of the mask points to produce the modified design includes producing the modified design as a polygonal pattern.

[0275] 60. The computer-readable medium of aspect 59, wherein the polygonal pattern comprises a pattern, wherein the angle between the straight line of the pattern and the horizontal axis is 45*n degrees, where n is an integer.

[0276] 61. The computer-readable medium of aspect 59, wherein the polygonal pattern comprises a pattern, wherein the angle between the straight line of the pattern and the horizontal axis is 90*n degrees, where n is an integer.

[0277] 62. The computer-readable medium as described in aspect 1, wherein adjusting the position of the mask points to produce the modified design includes producing the modified design as a curve pattern.

[0278] 63. The computer-readable medium of aspect 62, wherein adjusting the position of the mask point comprises adjusting the position of the mask point by moving the mask point in any direction relative to a control point on the target feature.

[0279] 64. The computer-readable medium of any one of aspects 59 to 63, wherein the modified design is generated as the polygonal pattern or the curved pattern based on a cost function associated with an optical proximity effect correction process or a source mask optimization process.

[0280] 65. The computer-readable medium of aspect 64, wherein the modified design is generated as the polygonal pattern based on a determination of the cost function that is optimized more than when the modified design is generated as the curved pattern.

[0281] 66. The computer-readable medium of aspect 64, wherein the modified design is generated as the polygonal pattern based on the determination that the mask rule check constraint is not satisfied when the modified design is generated as the curved pattern.

[0282] 67. The computer-readable medium as described in aspect 1, wherein adjusting the position of the mask points to produce the modified design includes producing the modified design as a combination of polygonal patterns and curved patterns.

[0283] 68. The computer-readable medium of aspect 67, wherein the modified design is generated as a curve pattern approximating a portion of one or more vertices of the target feature.

[0284] 69. The computer-readable medium of aspect 67, wherein the modified design is generated as a polygonal pattern of a portion of the target feature except for a portion of one or more vertices of the target feature.

[0285] 70. The computer-readable medium of aspect 67, wherein the modified design is generated as the curve pattern of a first portion of the target feature and the polygon pattern of a second portion of the target feature.

[0286] 71. The computer-readable medium of aspect 70, wherein the first portion of the target feature includes a portion adjacent to one or more vertices of the target feature.

[0287] 72. The computer-readable medium of aspect 70, wherein the second portion of the target feature includes a portion other than a portion adjacent to one or more vertices of the target feature.

[0288] In the block diagrams, the illustrated components are depicted as individual functional blocks, but the embodiments are not limited to systems organized as illustrated herein in terms of functionality. The functionality provided by each of the components may be provided by software or hardware modules organized in a manner different from that depicted herein; for example, this software or hardware may be mixed, combined, replicated, dissolved, distributed (e.g., within a data center or by region), or otherwise organized differently. The functionality described herein may be provided by one or more processors of one or more computers executing program code stored on a tangible, non-transitory machine-readable medium. In some cases, a third-party content delivery network may have control over some or all of the information transmitted via the network, in which case, in cases where information (e.g., content) is allegedly supplied or otherwise provided, the information may be provided by sending instructions to retrieve it from the content delivery network.

[0289] Unless otherwise specifically stated, it will be understood from the discussion that throughout this specification, the use of terms such as “processing,” “calculation,” “operation,” “determine,” or the like refers to the actions or processes of a particular device such as a dedicated computer or similar dedicated electronic processing / computing apparatus.

[0290] The reader will understand that this application describes several inventions. These inventions have been grouped into a single document rather than separated into multiple individual patent applications because their related subject matter contributes to economic development in practice. However, the different advantages and aspects of such inventions should not be combined. In some cases, embodiments resolve all the deficiencies mentioned in this invention; however, it should be understood that the inventions are independently useful, and some embodiments solve only a subset of such problems or provide other unmentioned benefits that will be apparent to those skilled in the art upon review of this invention. Due to cost constraints, some inventions disclosed herein may not be claimed at present, and may be claimed in later applications (such as continuation applications or by amendments to this technical solution). Similarly, due to space limitations, the "Summary" and "Conclusion" sections of this document should not be considered as a comprehensive list including all such inventions or all aspects of such inventions.

[0291] It should be understood that this specification and drawings are not intended to limit the invention to the specific forms disclosed, but rather, on the contrary, are intended to cover all modifications, equivalents and alternatives that fall within the spirit and scope of the invention as defined by the appended claims.

[0292] Modifications and alternative embodiments of various aspects of the invention will be apparent to those skilled in the art in light of this specification. Therefore, this specification and the accompanying drawings should be interpreted as illustrative only and for the purpose of teaching those skilled in the art the general manner of practicing the invention. It should be understood that the forms of the invention shown and described herein should be considered as examples of embodiments. Components and materials may be substituted for those described herein, parts and processes may be reversed or omitted, certain features may be utilized independently, and embodiments or features of embodiments may be combined, all of which will be apparent to those skilled in the art upon obtaining the benefits of this specification. Changes may be made to the elements described herein without departing from the spirit and scope of the invention as set forth in the following claims. Titles used herein are for organizational purposes only and are not intended to limit the scope of this specification.

[0293] As used herein, the word “may” is used in a permissive sense (i.e., meaning possible) rather than a mandatory sense (i.e., meaning must). The words “comprising,” “including,” and “included,” and similar terms mean, but are not limited to, those included. As used herein, the singular forms “a,” “an,” and “the” include multiple indicators unless expressly indicated otherwise. Thus, for example, although other terms and phrases such as “a or more” may be used for one or more elements, reference to “a” or “an” element includes combinations of two or more elements. Unless otherwise indicated, the term “or” is non-exclusive, i.e., encompasses both “and” and “or.” As used herein, unless otherwise specifically stated, the term “or” covers all possible combinations unless such combinations are impractical. For example, if an element is stated to include A or B, then unless otherwise specifically stated or impractical, the element may include A, or B, or A and B. As a second example, if a statement element can include A, B, or C, then unless otherwise specifically stated or impractical, the element can include A or B, or C, or A and B, or A and C, or B and C, or A and B and C. Terms describing conditional relationships, such as “in response to X, Y,” “after X, Y,” “if X, then Y,” “when X, Y,” and similar terms encompass causal relationships, where the premise is a necessary causal condition, the premise is a sufficient causal condition, or the premise is a contributing causal condition to the outcome. For example, “after condition Y is obtained, state X occurs” is common to “only after Y occurs” and “after Y and Z, X occurs.” Such conditional relationships are not limited to results obtained immediately by following the premise, as some results may be delayed, and in a conditional statement, the premise is connected to its outcome; for example, the premise relates to the probability of the outcome occurring. Unless otherwise indicated, a statement that multiple traits or functions are mapped to multiple objects (e.g., one or more processors performing steps A, B, C, and D) covers both cases where all such traits or functions are mapped to all such objects and cases where a subset of traits or functions is mapped to a subset of traits or functions (e.g., all processors each perform steps A through D, and processor 1 performs step A, processor 2 performs a portion of steps B and C, and processor 3 performs a portion of step C and step D). Additionally, unless otherwise indicated, a statement that a value or action is "based on" another condition or value covers both cases where the condition or value is a single factor and cases where the condition or value is one of multiple factors. Unless otherwise indicated, a statement that "each" item of a set has a certain property should not be interpreted as excluding cases where some other similar or identical members of a larger set do not have that property (i.e., "each" does not necessarily mean "every"). Statements of selection from a range include the endpoints of that range.

[0294] In the above description, any process, description, or block in the flowchart should be understood as representing a module, segment, or portion of program code, which includes one or more executable instructions for implementing a specific logical function or step in the process, and alternative implementations are included within the scope of exemplary embodiments of the present invention, wherein functionality may depend on the functionality involved and may not be performed in the order shown or discussed, including substantially simultaneously or in reverse order, as should be understood by those skilled in the art.

[0295] Where certain U.S. patents, U.S. patent applications, or other materials (such as papers) have been incorporated herein by reference, the text of such U.S. patents, U.S. patent applications, and other materials is incorporated by reference only if there is no conflict between the material and the statements and figures set forth herein. Where such conflicts exist, any such conflicting text from U.S. patents, U.S. patent applications, and other materials incorporated herein by reference is not specifically incorporated herein by reference.

[0296] While certain embodiments have been described, these embodiments are presented by way of example only and are not intended to limit the scope of the invention. In fact, the novel methods, apparatuses, and systems described herein can be embodied in many other forms; furthermore, various omissions, substitutions, and changes can be made to the forms of the methods, apparatuses, and systems described herein without departing from the spirit of the invention. The appended claims and their equivalents are intended to cover such forms or modifications that fall within the scope and spirit of the invention.

Claims

1. A non-transitory computer-readable medium having instructions that, when executed by a computer, cause the computer to perform a method for improving the design of a pattern forming apparatus, the method comprising: Obtain mask points for a design of mask features, wherein the mask features are associated with target features in a target pattern to be printed on a substrate; and The positions of the mask points are adjusted to generate a modified design of the mask features based on the adjusted mask points; Adjusting the position of the mask points is an iterative process, where each iteration includes: Determine the cost function associated with the optical proximity effect correction process or the source mask optimization process. For each control point on the target feature, the position data of the mask point is determined based on the cost function; and The position of one or more mask points is adjusted based on the location data to optimize the cost function, wherein the adjustment includes updating the modified design.

2. The computer-readable medium as claimed in claim 1, wherein, Determining the cost function includes: Simulations are performed using the modified design to obtain resist image signals or etching image signals as simulation signals, and A simulation signal is determined for each control point on the target feature, wherein the adjustment is based on the simulation signal at the control point and the association between the mask point and the control point.

3. The computer-readable medium as claimed in claim 1, wherein, Determining the cost function includes: The modified design is used to perform a simulation to obtain a simulation image; A process window is obtained using the simulation image, wherein the process window includes a range of focal and dose values ​​that satisfy predetermined specifications for the target pattern printed on the substrate using the modified design.

4. The computer-readable medium as claimed in claim 1, wherein, The cost function includes at least one of edge placement error, simulation signal, process window or mask rule check violation penalty.

5. The computer-readable medium as claimed in claim 1, wherein, Obtaining the mask points includes: The mask points are derived from the target features, wherein the deriving includes associating the mask points with control points on the target features to generate a first association between a first set of mask points and a first control point, and a second association between a second set of mask points and a second control point.

6. The computer-readable medium of claim 5, wherein, Adjusting the position of the mask point includes: For the next iteration of mask point adjustment, modify the association between the mask point and the control point.

7. The computer-readable medium of claim 5, wherein, One or more control points on the target feature are associated with different sets of mask points in at least two iterations.

8. The computer-readable medium of claim 1, further comprising: A smoothing process is applied to the mask points, wherein the smoothing process performs curve fitting to connect the mask points with curves to produce the design of the pattern forming apparatus as a first curve pattern.

9. The computer-readable medium of claim 7, further comprising: The design of the pattern forming apparatus is subjected to image perturbation to produce an enlarged version of the design.

10. The computer-readable medium of claim 1, wherein, Adjusting the position of one or more of the mask points includes: uniformly adjusting a group of the mask points.

11. The computer-readable medium of claim 1, wherein, Adjusting the position of one or more of the mask points includes: adjusting each of the mask points in a set of mask points individually.

12. The computer-readable medium of claim 1, wherein, The position data for each mask point includes a slope value and a distance value. Using the slope value and the distance value, the position adjustment of the corresponding mask point is performed with respect to the control points associated with the corresponding mask point.

13. The computer-readable medium of claim 1, wherein, The design is derived from one or more of the following: Optimal Proximity Correction (OPC) based on machine learning (ML), Continuous Transmission Mask (CTM) freeform OPC, CTM+freeform OPC, segment-based OPC, and reverse lithography.

14. The computer-readable medium of claim 1, wherein, The mask features are either sub-resolution auxiliary features or main features.

Images