Source optimization for mitigating mask error effects

Abstract

Systems, methods, and computer software are disclosed for reducing wafer patterning errors caused by a mask device. A method (300) may include obtaining a first mask design (310) having a first portion (324) associated with an optimized pupil (322), where the optimized pupil is generated by a source-mask optimization process (320). An error on the mask device may be located and a second portion of the mask device having the error may be identified (330). The method may also include performing source optimization (340) by utilizing the first portion (324) and the second portion (330) in combination to produce a re-optimized pupil (350).

Description

[0001] Cross - reference to related applications

[0002] This application claims priority to U.S. Application No. 63 / 420,853, filed on October 31, 2022, and the entire contents of this U.S. application are incorporated herein by reference. Technical field

[0003] The description herein generally relates to mask manufacturing and patterning processes. More specifically, the present disclosure includes apparatuses, methods, and computer programs for optimizing sources to mitigate mask errors. Background art

[0004] A lithographic projection apparatus can be used, for example, in the manufacture of integrated circuits (ICs). In such a case, a "patterning device" or "mask device" (e.g., a mask) can comprise or provide a pattern (a "design layout") corresponding to a single layer of the IC, and such a pattern can be transferred, e.g., by means of irradiation of a target portion through the pattern on the mask device, onto a target portion (e.g., comprising one or more dies) on a substrate (e.g., a silicon wafer) that has been coated with a layer of radiation - sensitive material ("resist"). Typically, a single substrate comprises a plurality of adjacent target portions, and the pattern is transferred successively by the lithographic projection apparatus to the plurality of adjacent target portions, one target portion at a time. In this type of lithographic projection apparatus, the pattern on the entire mask device is transferred to one target portion at once; such an apparatus can also be referred to as a stepper. In an alternative apparatus, a step - and - scan apparatus can cause the projection beam to scan across the mask device in a given reference direction ("scan" direction), while the substrate is moved synchronously, parallel or anti - parallel to this reference direction. Different portions of the pattern on the mask device are transferred step - by - step to one target portion. Typically, since the lithographic projection apparatus will have a reduction ratio M (e.g., 4), the speed F of the moving substrate will be 1 / M times the speed at which the projection beam scans the mask device. More information about lithographic apparatuses can be found, for example, in U.S. 6,046,792, which is incorporated herein by reference.

[0005] Before transferring the pattern from the mask device to the substrate, the substrate may undergo various processes such as priming, resist coating, and soft baking. After exposure, the substrate may undergo other processes ("post-exposure processes") such as post-exposure bake (PEB), development, hard bake, and measurement / inspection of the transferred pattern. This array of processes serves as the basis for manufacturing a single layer of a device (e.g., an IC). The substrate may then undergo a variety of processes such as etching, ion implantation (doping), metallization, oxidation, chemical mechanical polishing, etc., all of which are aimed at finishing the single layer of the device. If several layers are required in the device, the entire process or a variant thereof is repeated for each layer. Eventually, there will be devices in each target portion on the substrate. These devices are then separated from each other by techniques such as dicing or sawing, whereby the individual devices can be mounted on a carrier, connected to pins, etc.

[0006] Thus, manufacturing a device such as a semiconductor device typically involves using multiple manufacturing processes to process a substrate (e.g., a semiconductor wafer) to form the various features and multiple layers of the device. Processes such as deposition, lithography, etching, chemical mechanical polishing, and ion implantation are commonly used to fabricate and process such layers and features. Multiple devices can be fabricated on multiple die on a substrate, and the devices are then separated into individual devices. Such a device manufacturing process can be regarded as a patterning process. The patterning process involves a patterning step for transferring a pattern on a mask device to a substrate, such as using optical and / or nanoimprint lithography of the mask device in a lithographic apparatus, and the patterning process typically but optionally involves one or more associated pattern processing steps such as resist development by a development device, baking the substrate using a baking tool, etching using a pattern with an etching device, etc.

[0007] As mentioned, lithography is a central step in manufacturing devices such as ICs, where the pattern formed on the substrate defines the functional elements of the device, such as microprocessors, memory chips, etc. Similar lithography techniques are also used to form flat panel displays, microelectromechanical systems (MEMS), and other devices.

[0008] As semiconductor manufacturing processes have continued to progress, over the decades, the size of functional elements has been continuously decreasing, while the amount of functional elements such as transistors per device has been steadily increasing, following a trend known as "Moore's Law". In the current state of the art, lithographic projection equipment is used to fabricate the layers of a device, which uses irradiation from a deep ultraviolet radiation source to project a design layout onto a substrate, thereby creating individual functional elements with dimensions far below 100 nm (i.e., less than half the wavelength of the radiation from the radiation source (e.g., a 193 nm radiation source)).

[0009] This process for printing features smaller than the classical resolution limit of a lithographic projection apparatus can be called low-k1 lithography according to the resolution formula CD = k1×λ / NA, where λ is the wavelength of the radiation used (e.g., 248 nm or 193 nm), NA is the numerical aperture of the projection optics in the lithographic projection apparatus, CD is the "critical dimension" (usually the smallest feature size printed), and k1 is an empirical resolution factor. Generally, the smaller k1 is, the more difficult it becomes to reproduce on the substrate a pattern similar in shape and size to that planned by the designer in order to achieve a specific electrical functionality and performance. To overcome these difficulties, complex fine-tuning steps are applied to the lithographic projection apparatus, the design layout, or the mask device. These steps include, for example but not limited to, optimization of the NA and optical coherence settings, customized illumination schemes, use of phase-shifting mask devices, optical proximity correction (OPC, sometimes also referred to as "optical and process correction") in the design layout, or other methods generally defined as "resolution enhancement techniques" (RET). The term "projection optics" as used herein should be interpreted broadly to cover various types of optical systems, including, for example, refractive optics, reflective optics, apertures, and catadioptric optics. The term "projection optics" can also include components operating according to any of these design types for jointly or individually guiding, shaping, or controlling a projection radiation beam. The term "projection optics" can include any optical component in a lithographic projection apparatus, regardless of where the optical component is positioned in the optical path of the lithographic projection apparatus. The projection optics can include optical components for shaping, adjusting, and / or projecting the radiation before it passes through the mask device from the source, and / or for shaping, adjusting, and / or projecting the radiation after it passes through the mask device. The projection optics generally do not include the source and the mask device. Summary of the Invention

[0010] Systems, methods, and computer software for reducing wafer patterning errors caused by a mask device are disclosed. In one aspect, a method can include obtaining a first mask design having a first portion associated with an optimized pupil, where the optimized pupil is generated by a source-mask optimization process. Errors can be located on the mask device and a second portion of the mask device having the errors can be identified. The method can further include performing source optimization by combinatorially utilizing the first portion and the second portion to generate a re-optimized pupil.

[0011] In some variations, the method can include locating the errors using an inspection tool. This can include performing a mask inspection of the mask device with the inspection tool or performing a wafer inspection of the wafer with the inspection tool.

[0012] In other variations, the method may include obtaining a prediction result of the error. The second part may be identified based on the prediction result. Additionally, the method may include determining that the prediction result of the error is higher than a local threshold.

[0013] In still other variations, the method may include performing lithography manufacturing inspection (LMC) using the mask device to obtain a prediction result of the second part having the error. This may include determining, using the LMC, that the error is a process window limiting term. The prediction result may be a depth of focus (DOF) or a mask error enhancement factor (MEEF) obtained by performing LMC using the mask device, and the error reduces the DOF. Additionally, the first part may not have the error or may have an error reduced compared to the error in the second part.

[0014] In some variations, the method may include identifying a portion of the mask device having an error of an error type, wherein source optimization may be performed using the portion where the error is maximum for the error type. The error type may be a bias (e.g., X bias, Y bias, X and Y biases, etc.), an edge shift (e.g., X edge shift, Y edge shift, X and Y edge shifts, etc.), or an edge defect (e.g., X edge defect, Y edge defect, or X and Y edge defects). The method may further include identifying a portion of the mask device having an error of a different type, wherein source optimization is performed using the portion having the maximum error for the error type.

[0015] In other variations, the method may include applying weights to the first part and the second part, the weights being selected to establish the relative contributions of the first part and the second part in generating the re-optimized pupil. The method may include: obtaining a plurality of prediction results of the mask device; localizing a plurality of first errors on the mask device based on the prediction results; and identifying a plurality of second parts of the mask device having the localized plurality of errors, wherein the weights are assigned to the plurality of second parts having the maximum error in an error type, wherein the plurality of second parts includes the second part. The weights may be iteratively adjusted during successive source optimizations to improve the process window. The mask device and the re-optimized pupil may produce an improved process window relative to the mask device and the optimized pupil.

[0016] In other alternative variations, the source optimization can be performed for a lithography system utilizing a numerical aperture (NA) greater than or equal to 0.4 (e.g., 0.55). The method can include stitching a mask device layout for use with a lithography system having the NA, where the mask device is projected at a magnification that maintains a mask reflectivity above 0.5. The mask design can correspond to one of a DRAM layer, a storage node (SP) layer, a storage node pad (SNP) layer, or an array pattern. The method can include performing a voting process using the re-optimized pupil to generate a second re-optimized pupil, or where generating the re-optimized pupil does not include performing a voting process.

[0017] In some variations, the source optimization can include generating a discrete pupil, generating a freeform pupil, or generating a discrete pupil and a freeform pupil. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate certain aspects of the subject matter disclosed herein and, together with the description, serve to explain some of the principles associated with the disclosed embodiments. In the drawings,

[0019] Figure 1 A block diagram illustrating a plurality of subsystems of a lithographic projection apparatus according to an embodiment of the present disclosure.

[0020] Figure 2 An exemplary flowchart illustrating lithography simulation in a lithographic projection apparatus according to an embodiment of the present disclosure.

[0021] Figure 3 Is a process flowchart illustrating a process of performing source optimization to generate a re-optimized pupil that reduces the impact of mask errors according to an embodiment of the present disclosure.

[0022] Figure 4 Is a process flowchart illustrating a process of performing source optimization using weighted mask portions and process window analysis according to an embodiment of the present disclosure.

[0023] Figure 5 Is a diagram of a mask device depicting errors and different error types according to an embodiment of the present disclosure.

[0024] Figure 6 Is a diagram illustrating high-NA operation using increased magnification according to an embodiment of the present disclosure.

[0025] Figure 7 Is a diagram of a stitching operation for use with some high-NA implementations according to an embodiment of the present disclosure.

[0026] Figure 8It is a block diagram of an example computer system according to an embodiment of the present disclosure.

[0027] Figure 9 It is a schematic diagram of a lithographic projection apparatus according to an embodiment of the present disclosure.

[0028] Figure 10 It is a schematic diagram of another lithographic projection apparatus according to an embodiment of the present disclosure.

[0029] Figure 11 It is a detailed view of a lithographic projection apparatus according to an embodiment of the present disclosure.

[0030] Figure 12 It is a detailed view of a source collector module of a lithographic projection apparatus according to an embodiment of the present disclosure. Detailed Description

[0031] Although specific reference may be made herein to the manufacture of ICs, it should be clearly understood that the description herein has many other possible applications. For example, the description herein can be used in the manufacture of integrated optical systems, guiding and detecting patterns for magnetic domain memories, liquid crystal display panels, thin film magnetic heads, etc. Those skilled in the art will appreciate that in the context of such alternative applications, any use herein of the terms "reticle", "wafer" or "die" should be considered as being interchangeable with the more general terms "mask", "substrate" and "target portion", respectively.

[0032] In this document, the terms "radiation" and "beam" are used to encompass all types of electromagnetic radiation, including ultraviolet radiation (e.g., having a wavelength of 365 nm, 248 nm, 193 nm, 157 nm or 126 nm) and EUV (extreme ultraviolet radiation, e.g., having a wavelength in the range of about 5 nm to 100 nm).

[0033] The mask device may include or may form one or more design layouts. A computer-aided design (CAD) process can be utilized to generate the design layout, which is often referred to as electronic design automation (EDA). Most CAD processes follow a set of predefined design rules in order to generate a functional design layout / mask device. These rules are set by processing and design constraints. For example, the design rules define the space tolerances between devices (such as gates, capacitors, etc.) or interconnect lines in order to ensure that the devices or lines do not interact with each other in an undesirable manner. One or more of the design rule limitations can be referred to as "critical dimension" (CD). The critical dimension of a device can be defined as the minimum width of a line or a hole or the minimum space between two lines or two holes. Thus, the CD determines the overall size and density of the designed device. Of course, one of the goals in device manufacturing is to faithfully reproduce the initial design intent on the substrate (via the mask device).

[0034] As used herein, the term "mask" or "mask device" can be broadly interpreted to mean a general mask device 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 created in a target portion of a substrate; the term "light valve" can also be used in this context. In addition to classical masks (transmission or reflection; binary, phase-shifting, hybrid, etc.), examples of other such mask devices include programmable mirror arrays and programmable LCD arrays.

[0035] An example of a programmable mirror array can be a matrix-addressable surface with a viscoelastic control layer and a reflective surface. The underlying principle implicit in such a device is (for example) that the addressed regions of the reflective surface reflect the incident radiation as diffracted radiation, while the non-addressed regions reflect the incident radiation as non-diffracted radiation. With the use of an appropriate filter, the non-diffracted radiation can be filtered out from the reflected beam, leaving only the diffracted radiation; in this way, the beam becomes patterned according to the addressing pattern of the matrix-addressable surface. The required matrix addressing can be performed using suitable electronic means.

[0036] An example of a programmable LCD array is given in U.S. Patent No. 5,229,872, which is incorporated herein by reference.

[0037] Figure 1 FIG. is a block diagram showing a plurality of subsystems of a lithographic projection apparatus 10A according to an embodiment of the present disclosure. The main components are: a radiation source 12A, which can be a deep ultraviolet excimer laser source or other types of sources including an extreme ultraviolet (EUV) source (as discussed above, the lithographic projection apparatus itself does not need to have a radiation source); illumination optics, which for example define partial coherence (expressed as a standard deviation) and can include optics 14A, 16Aa, and 16Ab for shaping the radiation from source 12A; a mask device 18A; and transmissive optics 16Ac, which project an image of the mask device pattern 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 incident on the substrate plane 22A, where the maximum possible angle defines the numerical aperture NA = n sin(Θ max ), where n is the refractive index of the medium between the substrate and the last element of the projection optics, and Θ max is the maximum angle of the beam emerging from the projection optics that can still be incident on the substrate plane 22A.

[0038] In a lithographic projection apparatus, a source provides illumination (i.e., radiation) to a mask device, and projection optics direct the illumination via the mask device onto a substrate and shape the illumination. The projection optics may include at least some of components 14A, 16Aa, 16Ab, and 16Ac. The aerial image (AI) is the radiation intensity distribution at the substrate level. A resist model can be used to calculate a resist image from the aerial image, examples of which can be found in US Patent Application Publication No. US 2009-0157360, the disclosure of which is incorporated herein by reference in its entirety. The resist model is only related to the properties of the resist layer (e.g., the effects of chemical processes occurring during exposure, post-exposure bake (PEB), and development). The optical properties of the lithographic projection apparatus (e.g., the properties of the illumination, mask device, and projection optics) dictate the aerial image and can be defined in an optical model. Since the mask device used in the lithographic projection apparatus can be changed, it is desirable to separate the optical properties of the mask device from the optical properties of the remainder of the lithographic projection apparatus, which includes at least the source and projection optics. Details of the techniques and models used to convert a design layout into various lithographic images (e.g., aerial image, resist image, etc.), details of the techniques and models used to apply OPC using those techniques and models, and details of the techniques and models used to evaluate performance (e.g., with respect to process window) are described in US Patent Application Publication Nos. US 2008-0301620, 2007-0050749, 2007-0031745, 2008-0309897, 2010-0162197, and 2010-0180251, the disclosure of each of which is incorporated herein by reference in its entirety.

[0039] One aspect of understanding the lithographic process is understanding the interaction of radiation with the mask device. The electromagnetic field of the radiation after it has passed through the mask device can be determined from the electromagnetic field of the radiation before it reaches the mask device and a function characterizing the interaction. Such a function can be referred to as a mask transmission function (which can be used to describe the interaction of transmissive mask devices and / or reflective mask devices).

[0040] The mask transmission function can have various different forms. One form is binary. The binary mask transmission function has either of two values (e.g., zero and a positive constant) at any given position on the mask device. The mask transmission function in binary form can be referred to as a binary mask. Another form is continuous. That is, the modulus of the transmittance (or reflectance) of the mask device is a continuous function of the position on the mask device. The phase of the transmittance (or reflectance) can also be a continuous function of the position on the mask device. The mask transmission function in continuous form can be referred to as a continuous tone mask or a continuous transmission mask (CTM). For example, a CTM can be represented as a pixelated image, where a value between 0 and 1 (e.g., 0.1, 0.2, 0.3, etc.) rather than a binary value of 0 or 1 can be assigned to each pixel. In an embodiment, the CTM can be a pixelated grayscale image, where each pixel has a certain number of values (e.g., normalized values in the range [-255, 255], in the range [0, 1] or [-1, 1] or other suitable ranges).

[0041] The thin mask approximation (also known as the Kirchhoff boundary condition) is widely used to simplify the determination of the interaction between radiation and the mask device. The thin mask approximation assumes that the thickness of the structures on the mask device is very small compared to the wavelength, and the width of the structures on the mask is very large compared to the wavelength. Thus, the thin mask approximation assumes that the electromagnetic field after the mask device is the product of the incident electromagnetic field and the mask transmission function. However, when the lithography process uses radiation with an increasingly short wavelength and the structures on the mask device become increasingly small, the assumptions of the thin mask approximation can break down. For example, due to the finite thickness of the structures (e.g., the edges between the top surface and the sidewalls), the interaction between the radiation and the structures ("mask 3D effect" or "M3D") can become significant. Incorporating such scattering in the mask transmission function can enable the mask transmission function to better capture the interaction between radiation and the mask device. The mask transmission function under the thin mask approximation can be referred to as the thin mask transmission function. The mask transmission function that incorporates the M3D effect can be referred to as the M3D mask transmission function.

[0042] According to embodiments of the present disclosure, one or more images can be generated. The images include various types of signals that can be characterized by pixel values or intensity values of each pixel. Those of ordinary skill in the art can understand that depending on the relative values of the pixels within the image, the signals can be referred to as, for example, weak signals or strong signals. The terms "strong" and "weak" are relative terms based on the intensity values of the pixels within the image, and specific values of the intensity may not limit the scope of the present disclosure. In an embodiment, strong signals and weak signals can be identified based on a selected threshold. In an embodiment, the threshold can be fixed (e.g., the midpoint between the highest intensity and the lowest intensity of the pixels within the image). In an embodiment, a strong signal can refer to a signal having a value greater than or equal to the average signal value across the image, and a weak signal can refer to a signal having a value less than the average signal value. In an embodiment, the relative intensity value can be based on a percentage. For example, a weak signal can be a signal having an intensity lower than 50% of the highest intensity of the pixels within the image (e.g., the pixels corresponding to the target pattern can be considered as the pixels having the highest intensity). Additionally, each pixel within the image can be considered as a variable. According to this embodiment, derivatives or partial derivatives can be determined with respect to each pixel within the image, and the value of each pixel can be determined or modified based on an evaluation of a cost function and / or a gradient-based calculation of the cost function. For example, a CTM image can include pixels, where each pixel is a variable that can take on any real value.

[0043] Figure 2 FIG. shows an exemplary flowchart for simulating lithography in a lithographic projection apparatus according to an embodiment of the present disclosure. The source model 31 represents the optical characteristics of the source (including the radiation intensity distribution and / or phase distribution). The projection optical device model 32 represents the optical characteristics of the projection optical device (including the change in the radiation intensity distribution and / or phase distribution caused by the projection optical device). The design layout model 35 represents the optical characteristics of the design layout (including the change in the radiation intensity distribution and / or phase distribution caused by the design layout 33), where the design layout is a representation of the feature arrangement on the mask device or a feature arrangement formed by the mask device. The aerial image 36 can be simulated based on the design layout model 35, the projection optical device model 32, and the design layout model 35. The resist image 38 can be simulated based on the aerial image 36 using the resist model 37. The simulation of lithography can, for example, predict the profiles and CDs in the resist image.

[0044] More specifically, it should be noted that the source model 31 can represent the optical characteristics of the source, which include but are not limited to numerical aperture settings, irradiation standard deviation (σ) settings, and any specific irradiation shape (e.g., off-axis radiation sources such as rings, quadrupoles, dipoles, etc.). The projection optical device model 32 can represent the optical characteristics of the projection optical device, which include aberrations, distortions, one or more refractive indices, one or more physical dimensions, one or more physical sizes, etc. The design layout model 35 can represent one or more physical properties of the physical mask device, as described, for example, in U.S. Patent No. 7,587,704, which is incorporated herein by reference in its entirety. The goal of the simulation is to accurately predict, for example, edge placement, spatial image intensity slope, and / or CD, which can then be compared with the expected design. The expected design is typically defined as a pre-OPC design layout that can be provided in a standardized digital file format such as GDSII or OASIS or other file formats.

[0045] Based on such a design layout, one or more portions referred to as "fragments" can be identified. In an embodiment, a set of fragments is extracted that represents complex patterns in the design layout (typically from about 50 to 1000 fragments, but any number of fragments can be used). These patterns or fragments represent small portions of the design (i.e., circuits, cells, or patterns), and more specifically, fragments typically represent small portions that require special attention and / or verification. In other words, a fragment can be a portion of the design layout or can be similar or have similar behavior to a portion of the design layout, where one or more critical features are identified through practice (including fragments provided by the customer), trial and error, or running full-chip simulations. Fragments can include one or more test patterns or gauge patterns.

[0046] An initial larger set of fragments can be provided a priori by the customer based on one or more known critical feature regions in the design layout that require specific image optimization. Alternatively, in another embodiment, an initial larger set of fragments can be extracted from the entire design layout by using some automated (such as machine vision) or manual algorithm that identifies one or more critical feature regions.

[0047] In a lithographic projection apparatus, as an example, the cost function can be expressed as

[0048] (Equation 1)

[0049] where (z 1 , z 2 ,…, z N ) are N design variables or their values. f p (z 1 , z2 , …, z N ) can be a design variable (z 1 , z 2 , …, z N ) and be a function of, for example, the difference between the actual value and the expected value of a characteristic of a set of values of the design variables (z 1 , z 2 , …, z N ). w p Let w be the weight constant associated with f p (z 1 , z 2 , …, z N ). For example, the characteristic can be the position of the edge of a pattern measured at a given point on the edge. Different f p (z 1 , z 2 , …, z N ) can have different weights w p . For example, if a particular edge has a narrow allowable position range, a higher value can be given to the weight w p of f 1 (z 2 , z N ) representing the difference between the actual and expected positions of the edge. f p (z p (z 1 , z 2 , …, z N ) can also be a function of an interlayer characteristic, which in turn is a function of the design variables (z 1 , z 2 , …, z N ). Of course, CF(z 1 , z 2 , …, z N ) is not limited to the form in Equation 1. CF(z 1 , z 2 , …, z N ) can take any other suitable form.

[0050] The cost function can represent any one or more suitable characteristics of a lithographic projection apparatus, a lithographic process, or a substrate, such as focus, CD, image shift, image distortion, image rotation, random variation, throughput, local CD variation, process window, interlayer characteristics, or a combination thereof. In one embodiment, the design variables (z 1 , z 2 , …, z N) includes one or more selected from dose, global deviation of the mask device, and / or irradiation shape. Since the resist image often defines the pattern on the substrate, the cost function may include a function representing one or more characteristics of the resist image. For example, f p (z 1 , z 2 ,…,z N ) can simply be the distance between the points in the resist image and the expected positions of the points (i.e., the edge placement error EPE p (z 1 , z 2 ,…, z N ). The design variables can include any adjustable parameters, such as dose, focus, mask device, projection optics, adjustable parameters of the source, etc.

[0051] The lithographic apparatus may include components collectively referred to as a "wavefront manipulator", which may be used to adjust the shape and / or phase shift of the wavefront and intensity distribution of the radiation beam. In an embodiment, the lithographic apparatus may adjust the wavefront and intensity distribution at any position along the optical path of the lithographic projection apparatus, such as in front of the mask device, near the pupil plane, near the image plane, and / or near the focal plane. The wavefront manipulator may be used to correct or compensate for certain deformations of the wavefront and intensity distribution and / or phase shift caused by, for example, temperature variations in the source, mask device, lithographic projection apparatus, thermal expansion of components of the lithographic projection apparatus, etc. Adjusting the wavefront and intensity distribution and / or phase shift may change the value of the characteristic represented by the cost function. These changes can be simulated according to a model or measured actually. The design variables can include the parameters of the wavefront manipulator.

[0052] The design variables may have constraints, which may be expressed as (z 1 , z 2 ,…, z N ) ∈ Z, where Z is the set of possible values of the design variables. A possible constraint on the design variables can be imposed by the desired throughput of the lithographic projection apparatus. In the absence of such a constraint imposed by the desired throughput, the optimization may result in an unrealistic set of values of the design variables. For example, if the dose is a design variable, in the absence of such a constraint, the optimization may result in a dose value that makes the throughput economically impossible. However, the usefulness of the constraint should not be construed as a necessity. For example, the throughput may be affected by the pupil fill ratio. For some irradiation designs, a low pupil fill ratio may discard radiation, resulting in a lower throughput. The throughput may also be affected by the resist chemical reaction. A slower resist (e.g., a resist that requires a properly higher amount of radiation exposure) results in a lower throughput.

[0053] As used herein, the term "patterning process" means a process of generating an etched substrate by applying a specified pattern of light as part of a lithography process.

[0054] As used herein, the term "target pattern" means an idealized pattern to be etched on a substrate.

[0055] As used herein, the term "printed pattern" means a physical pattern formed on a substrate based on a design layout. The printed pattern can include, for example, vias, contact holes, trenches, channels, recesses, edges, or other two-dimensional and three-dimensional features generated by a lithography process.

[0056] As used herein, the term "process model" means a model that includes one or more models simulating a patterning process. For example, a process model can include any combination of the following: an optical model (e.g., which models a lens system / projection system used to transfer light in a lithography process and can include modeling the final optical image of light onto a resist), a mask model, a resist model (e.g., which models the physical effects of a resist, such as chemical effects attributed to light), an OPC model (e.g., which can be used to fabricate a design layout and can include sub-resolution resist features (SRAF), etc.), an inspection tool model (e.g., which models what an inspection tool can image from a printed pattern).

[0057] As used herein, the term "inspection tool" means any number of devices and associated computer hardware and software or combinations thereof that can be configured to generate an image of a target, such as a printed pattern or a portion thereof. Non-limiting examples of inspection tools can include: a scanning electron microscope (SEM), an x-ray machine, etc.

[0058] A fabricated mask device (e.g., a mask) sometimes has errors, such as a positional shift or a dimensional change of some features in the mask (e.g., see some examples of errors in Figure 5 . Mitigation of the wafer error impact caused by such a mask device can be performed by "voting", which is a process in which incident light and / or the mask device are physically shifted to several (N) positions having the same design features as the erroneous position, and a reduced exposure (1 / N) is performed at each position. Although such a voting method can be performed according to certain embodiments of the present disclosure, the several exposures performed during voting reduce the manufacturing throughput, and thus the disclosed process can be utilized to avoid or reduce the number of exposures performed during voting.

[0059] According to embodiments of the present disclosure, by performing source optimization with identified error features on a defective mask device to generate a re-optimized pupil, the printing effect of mask device errors can be mitigated. This has the advantage of improving the manufacturing process without having to fabricate a new mask device. The re-optimized source (e.g., pupil) can advantageously eliminate or reduce the need for time-consuming voting. These improvements can be quantified, for example, by calculating a process window (or other metric), which can then enable iterative optimization of the source to obtain a pupil that provides the maximum process window improvement. Such a method can also be implemented by high-NA (e.g., NA > 0.4) operation, where the mask device is utilized with a stitching operation, which itself may result in reduced throughput and thus benefits from avoiding the voting process.

[0060] Figure 3 is a process flow diagram illustrating a process for performing source optimization to generate a re-optimized pupil that reduces the impact of mask errors, according to embodiments of the present disclosure. To provide an overview of some aspects of the present disclosure, a process 300 for reducing the impact of mask errors can include specifying design objectives 310 for a source-mask optimization process 320. Performing the source-mask optimization process 320 can generate an optimized pupil 322 and a first mask design having a first portion 324 with no (or reduced) errors. In some embodiments, the mask design can correspond to a DRAM layer, a storage node (SP) layer, a storage node pad (SNP) layer, or an array pattern. To reduce the impact of errors in a fabricated mask device, the first portion 324 (from the SMO process or alternatively measured mask data from a mask with no errors) and a second portion 330 (from the mask device) can be used in source optimization 340 to generate a re-optimized pupil 350. The second portion 330 can be representative mask data, e.g., the OPC mask pattern of the mask device. Since source optimization 340 attempts to account for the physical errors in the mask device and also for the "ideal" mask design that would in principle result in optimal production of the design objectives 310 at the wafer, the resulting re-optimized pupil, when used with the mask device, produces a wafer in which the impact of the errors present in the mask device is reduced.

[0061] Figure 4 is a process flow diagram illustrating a process for performing source optimization using weighted mask portions and process window analysis, according to embodiments of the present disclosure. Figure 4 The process 400 depicted in Figure 3 includes features from the process 300 in Figure 4As depicted, process 400 can reduce wafer patterning errors caused by a mask device. For example, as described in more detail below, this can include weighting the contributions of the first portion 324 and the second portion 330 such that the re-optimized pupil 350 can be based on contributions from both the first portion 324 and the second portion 330, thereby reducing the impact of the errors present in the second portion 330 while still taking into account the physical mask being utilized to some extent.

[0062] In one embodiment, process 400 can include obtaining a first mask design (including the first portion 324) associated with an optimized pupil 322, where the optimized pupil 322 and the first mask design can be generated by a source-mask optimization process 320. In some embodiments, after source-mask optimization 320, optical proximity effect correction can be performed to generate a mask design. The mask design can then be fabricated. Using the mask design or measurements from the fabricated mask, the first portion 324 can be obtained and used as described herein.

[0063] At 410, process 400 can include localizing errors on the mask device. Refer to Figure 5 Examples of errors are provided. Localizing errors on the mask device can include, for example, performing mask inspection of the mask device with an inspection tool, performing wafer inspection of the wafer with an inspection tool, etc. Generally, the mask device can include many errors and many types of errors. Thus, any number and type of such errors can be localized by performing mask inspection and / or wafer inspection.

[0064] At 420, a prediction result representing the impact of the error can be obtained for the mask device (or wafer). The prediction result can include, for example, depth of focus (DOF) (the error reduces the DOF), mask error enhancement factor (MEEF) obtained by performing lithography manufacturing inspection (LMC) using the mask device, etc. The prediction result can be calculated for any one of the errors found on the mask device during mask or wafer inspection. In some embodiments, this can include determining that the prediction result of the error is higher than a local threshold. An inspection tool can be used to localize the error. In some embodiments, this can include performing lithography manufacturing inspection (LMC) using the mask device to obtain a prediction result for a second portion with the error. Additionally, using LMC, it can be determined that the error is a process window limiting term. For example, this can be a case where the error, rather than other errors, limits the process window, and other errors may not directly affect the PW even if they exceed a threshold amount, such as a large X shift at a location where the X shift does not affect the PW. In other embodiments, the error can be a hot spot, a location with a large edge placement error (EPE), a critical dimension (CD) error, etc.

[0065] At 430, process 400 may include determining representative error locations (e.g., a particular subset of errors that may exist). The present disclosure is not limited to a particular number of representative error locations, a particular type of error, or a particular method of selecting representative error locations. For example, this may include identifying a portion of the mask device having an error (e.g., second portion 330), the identification being based on the prediction result (e.g., identifying the portion having an error that results in a high MEEF). For example, the portion may correspond to a mask fragment, such as a mask fragment that may be used for SMO. Representative defect locations may include those mask locations having different types of errors and / or errors above a certain threshold. For example, second portion 330 may be a portion having an X deviation. Other similar portions of the mask device may include portions having a Y deviation, an edge shift, etc. By representing different types of errors, process 400 may produce a re-optimized pupil that may reduce the impact of multiple types of errors.

[0066] In some embodiments, at 440, process 400 may include identifying portions of the mask device having an error (e.g., including second portion 330), each portion having one type of error (e.g., a deviation, an edge shift, etc.). Refer to Figure 5 Examples of error types are further described. In one embodiment, the mask device may have only portions having one type of error (e.g., an X deviation). In these embodiments, source optimization may be performed using the portion in which the error is the largest for the error type. For example, if the portion has different X deviations, this may include using the portion having the largest X deviation. Other embodiments may include identifying portions of the mask device having different types of errors (e.g., an X deviation, a Y deviation, etc.). In some embodiments, source optimization may be performed using the portion having the largest error for a particular error type. For example, this may include using the portion having the largest X deviation, the largest Y deviation, etc.

[0067] Since the first portion (from SMO) and the second portion (having one or more of the errors) may be used as inputs for source optimization, weights may be applied to first portion 324 and second portion 330. The weights may be selected to establish the relative contributions of first portion 324 and second portion 330 in generating the re-optimized pupil. For example, the first portion may have a first weight 442 such as 3, 4, 5, etc., and the second portion may have a second weight 444 such as 1, 2, etc.

[0068] Similar to the identification of portions performed at 440, process 400 can weight multiple portions separately. For example, in some embodiments, process 400 can include obtaining a prediction result of a mask device and locating a first error on the mask device based on the prediction result. Process 400 can then include identifying a second portion of the mask device having the located error, where a weight can be assigned to the second portion having the largest error among an error type. For example, there can be second portions having an X deviation and a Y deviation, and the particular second portions used can be the two second portions having the largest X deviation and the largest Y deviation, where each second portion has a corresponding weight.

[0069] Process 400 can include performing source optimization 340 by utilizing a first portion 324 and a second portion 330 of a mask device to produce a re-optimized pupil 350. In some embodiments, the first portion 324 can have no error or can have an error reduced compared to the error in the second portion 330. Also, source optimization can thus be used to produce a re-optimized pupil, and since a more ideal first mask design is considered, the re-optimized pupil can produce an improved mask. Thus, various embodiments of the present disclosure can allow for the production of a re-optimized pupil 350 without including a voting process that can be time-consuming (e.g., by increasing the total exposure time to N times as described above and thus can greatly reduce the production volume). However, other embodiments can include performing a voting process using the re-optimized pupil 350 to produce a second re-optimized pupil. For example, such an operation can be performed to compare improvements in production volume, process window, etc.

[0070] In some embodiments, source optimization can include producing a free-form pupil (e.g., a pupil where the value at a given location has an intensity range). In other embodiments, source optimization can produce a discrete pupil (e.g., a pupil where the output is discrete at various locations). In still other embodiments, source optimization can include producing a discrete pupil and a free-form pupil, e.g., where the discrete pupil is produced by source optimization and then converted into a discrete pupil to be used for process window analysis.

[0071] The present disclosure is not limited to any particular algorithm, method, or process for source re-optimization. At 450, process window analysis can be performed to characterize the error reduction of the re-optimized pupil. In some embodiments, this can include iteratively adjusting weights during successive source optimizations to improve the process window. This is in Figure 4is represented by an iterative loop 452 in which the first weight 442 and the second weight 444 can be adjusted. In embodiments where the first portion 324 and / or the second portion 330 includes more than one portion (or segment) of its corresponding mask, each portion / segment can have its own separate weight. To determine whether the process window is improving, a PW analysis 450 can be performed based on the mask device and the re-optimized pupil obtained from source optimization 340, and the PW analysis 450 can be compared with a PW analysis 460 performed based on the optimized pupil 322 and the first mask design obtained from the source-mask optimization process 320. Thus, in some embodiments, the iterative loop 452 can continue until the mask device in combination with the re-optimized pupil produces an improved process window relative to the mask device and the optimized pupil. In other embodiments, the iteration can continue until the improvement reaches a maximum or until a certain number of iterations have been performed.

[0072] Figure 5 is a diagram showing a mask device with depictions of errors and different error types in accordance with an embodiment of the present disclosure. An example of a mask device 500 is shown as having a plurality of mask features 510 intended to produce a target pattern 512 on a wafer. In some embodiments, the mask features 510 can be slightly oversized but have a specific size to produce the target pattern. However, the mask device 500 is also depicted as having a plurality of errors 530 (the errors are shown in the mask device 500 as portions having diagonals therein), where in the example shown, a critical error 540 is near the middle of the mask device 500. As described herein, some embodiments can include identifying a first portion of the mask device 500 such that the first portion includes the critical error 540.

[0073] In Figure 5 also shows different types of errors. For example, the error type can be a deviation that is too large or too small in size (e.g., X and Y deviations, as shown for the critical error 540, X deviation 541, Y deviation 542, etc.). The critical error 540 with X and Y deviations is shown in an enlarged view and is an example of both X and Y deviations, in which both the X and Y dimensions are lower than a specific threshold by a certain amount. A dashed line representing how the mask feature 510 would look without the critical error 540 is also shown. Other error types can include edge shifts (e.g., X edge shift 543, Y edge shift 544, X and Y edge shift 545, etc.). But other error types can include edge defects (e.g., X edge defect, Y edge defect, X and Y edge defect 546).

[0074] Figure 6FIG. is a diagram illustrating high NA operation with increased magnification in accordance with an embodiment of the present disclosure. The present disclosure can be applied to general pupils for deep ultraviolet (DUV) systems, extreme ultraviolet (EUV) systems, any kind of mask, systems with any numerical aperture (NA), and applications utilizing stitching and / or non-stitching. However, some embodiments of the present disclosure can include source optimization performed on a lithography system with a numerical aperture greater than or equal to 0.4 (e.g., 0.5, 0.55, 0.6, etc.) (commonly referred to herein as “high NA”). Insert drawing 610 depicts an exemplary lithography system having a source 612, illumination optics 614, a mask device 616, and a wafer 618. Insert drawing 620 shows a simplified description of a “typical” NA configuration (0.33 NA) in a lithography apparatus. The cones represent the optical angles of the source light that can be transmitted during wafer fabrication (e.g., approximately 4.7 degrees × 11.3 degrees), especially in the case of using anamorphic lenses that stretch or compress the transmitted light differently along different axes (as shown). Insert drawing 630 depicts an example of a high NA configuration, showing a correspondingly larger optical angle (e.g., approximately 8 degrees and 18 degrees) and thus can provide a significant increase in resolution. However, this larger angle can also result in a significant reduction in mask reflectivity, substantially reducing the amount of light reaching the wafer. Some embodiments can mitigate this effect by operating at a higher magnification as shown in insert drawing 640, where one axis of the optical cone is shown to be even smaller than the 0.33 NA configuration. Thus, not only can the reflectivity be restored, but it can also be optimized to increase, for example, to increase to a maximum value or close to the maximum value. This is depicted in graph 650, which shows the change in reflectivity from 0.33 NA (11 degrees at 4X magnification) to 0.55 NA (18 degrees at 4X magnification), to 0.55 NA (9 degrees at 8X magnification).

[0075] Figure 7 FIG. is a diagram illustrating a stitching operation used with some high NA implementations in accordance with an embodiment of the present disclosure. In some embodiments, the disclosed method can include stitching a mask device layout for use with a lithography system having an NA, where the mask device is projected at a magnification that maintains a mask reflectivity above 0.5. Stitching can be utilized when reducing the magnification reduces the area available for light transmission. For example, area 720 can be generated as shown in inset 620 of Figure 6 which depicts a 4X magnification at 0.33 NA. It can be as shown by Figure 6Generate region 730 as shown in the inset drawing 630, which depicts a 4X magnification at 0.55 NA but has a smaller 4X region due to the higher NA. By further increasing the magnification (e.g., 8X), the reflectivity can be restored, but region 740 is currently 8X smaller. The inset drawing 750 depicts a stitching operation for stitching two high-NA regions 740a and 740b. Each of regions 740a and 740b covers the size of region 740 but also includes a stitching region 760 that overlaps when regions 740a and 740b are stitched together. Regions 740a and 740b can be printed together to form a region of the same size (e.g., region 730) for the desired high-NA operation. However, by generating a re-optimized pupil according to the method described herein, the stitching can be performed with only a double exposure in the stitching region 760 instead of the 4X exposure or more exposures required by some voting processes.

[0076] Figure 8 is a block diagram of an example computer system CS in accordance with an embodiment of the present disclosure.

[0077] The computer system CS includes a bus BS or other communication mechanism for communicating information and a processor PRO (or processors) coupled to the bus BS for processing information. The computer system CS also includes a main memory MM coupled to the bus BS for storing information and instructions to be executed by the processor PRO, such as random access memory (RAM) or other dynamic storage. The main memory MM can also be used to store transient variables or other intermediate information during the execution of instructions to be executed by the processor PRO. The computer system CS further includes a read-only memory (ROM) ROM or other static storage device coupled to the bus BS for storing static information and instructions for the processor PRO. A storage device SD, such as a magnetic disk or optical disk, is provided and coupled to the bus BS for storing information and instructions.

[0078] The computer system CS can be coupled by the bus BS to a display DS for displaying information to a computer user, such as a cathode ray tube (CRT), or a flat panel or touch panel display. An input device ID including alphanumeric and other keys is coupled to the bus BS for communicating information and command selections to the processor PRO. Another type of user input device is a cursor control CC for communicating direction information and command selections to the processor PRO and for controlling the movement of a cursor on the display DS, such as a mouse, trackball, or cursor direction keys. Such an input device typically has two degrees of freedom in two axes (a first axis (e.g., x) and a second axis (e.g., y)), thereby allowing the device to specify a position in a plane. A touch panel (screen) display can also be used as an input device.

[0079] According to one embodiment, portions of one or more of the methods described herein may be performed by a computer system CS in response to one or more sequences of one or more instructions included in a main memory MM being executed by a processor PRO. The instructions may be read into the main memory MM from another computer-readable medium, such as a storage device SD. Execution of the instruction sequences included in the main memory MM causes the processor PRO to perform the process steps described herein. One or more processors in a multiprocessing arrangement may also be used to execute the instruction sequences included in the main memory MM. In alternative embodiments, hardwired circuitry may be used in place of or in combination with software instructions. Accordingly, the description herein is not limited to any specific combination of hardware circuitry and software.

[0080] As used herein, the term “computer-readable medium” refers to any medium that participates in providing instructions to a processor PRO for execution. Such a medium may take many forms, including but not limited to non-volatile media, volatile media, and transmission media. Non-volatile media includes, for example, optical or magnetic disks, such as storage device SD. Volatile media includes volatile memory, such as main memory MM. Transmission media includes coaxial cables, copper wire, and fiber optics, including the wires that comprise a bus BS. Transmission media can also take the form of acoustic or light waves, such as those generated during radio frequency (RF) and infrared (IR) data communications. A computer-readable medium may be non-transitory; for example, a floppy disk, a flexible disk, a hard disk, a magnetic tape, any other magnetic medium, a CD-ROM, a DVD, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, RAM, PROM, and EPROM, FLASH-EPROM, any other memory chip or cartridge. The non-transitory computer-readable medium may have instructions recorded thereon. The instructions, when executed by a computer, may implement any of the features described herein. A transitory computer-readable medium may include a carrier wave or other propagating electromagnetic signal.

[0081] Various forms of computer-readable media may be involved in carrying one or more sequences of one or more instructions to a processor PRO for execution. For example, the instructions may initially be carried on a magnetic disk of a remote computer. The remote computer may load the instructions into its volatile memory and send the instructions using a modem via a telephone line. A modem local to the computer system CS may receive the data on the telephone line and convert the data to an infrared signal using an infrared transmitter. An infrared detector coupled to the bus BS may receive the data carried in the infrared signal and place the data on the bus BS. The bus BS carries the data to the main memory MM, from which the processor PRO retrieves and executes the instructions. The instructions received by the main memory MM may optionally be stored on the storage device SD before or after being executed by the processor PRO.

[0082] The computer system CS may also include a communication interface CI coupled to the bus BS. The communication interface CI provides two-way data communication coupled to a network link NDL, and the network link NDL is connected to a local area network LAN. For example, the communication interface CI 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, the communication interface CI may be a local area network (LAN) card to provide a data communication connection with a compatible LAN. A wireless link may also be implemented. In any such implementation, the communication interface CI transmits and receives electrical, electromagnetic, or optical signals that carry digital data streams representing various types of information.

[0083] The network link NDL generally provides data communication with other data devices via one or more networks. For example, the network link NDL may be provided by a local area network LAN to connect to a host computer HC. This may include providing data communication services via a global packet data communication network (now commonly referred to as the "Internet" INT). Both the local area network LAN (Internet) use electrical, electromagnetic, or optical signals that carry digital data streams. Signals via various networks and signals on the network data link NDL and via the communication interface CI are exemplary carrier forms for conveying information, and the signals carry digital data to and from the computer system CS.

[0084] The computer system CS may send messages and receive data (including program code) from the network, the network data link NDL, and the communication interface CI. In the Internet example, the host computer HC may transmit requested program code for an application program via the Internet INT, the network data link NDL, the local area network LAN, and the communication interface CI. For example, one such downloaded application program may provide all or part of the methods described herein. The received code may be executed by the processor PRO when it is received, and / or stored in the storage device SD or other non-volatile memory for later execution. In this way, the computer system CS may obtain application code in the form of a carrier wave.

[0085] Figure 9 is a schematic diagram of a lithographic projection apparatus according to an embodiment of the present disclosure.

[0086] The lithographic projection apparatus may include an illumination system IL, a first stage MT, a second stage WT, and a projection system PS.

[0087] The illumination system IL may condition a radiation beam B. In such a particular case, the illumination system also includes a radiation source SO.

[0088] The first stage (e.g., the mask stage) MT may be provided with a mask holder for holding a mask device MA (e.g., a reticle), and is connected to a first aligner for accurately positioning the mask device relative to the object PS.

[0089] The second stage (substrate stage) WT may have a substrate holder for holding a substrate W (e.g., a silicon wafer coated with resist), and is connected to a second aligner for accurately positioning the substrate relative to the object PS.

[0090] The projection system ("lens") PS (e.g., a refractive, reflective, or catadioptric optical system) may image the irradiated portion of the mask device MA onto a target portion C (e.g., including one or more dies) of the substrate W.

[0091] As depicted herein, the apparatus may be of the transmissive type (i.e., having a transmissive mask device). However, in general, it may also be of the reflective type, for example (having a reflective mask device). The apparatus may use a mask device different from classical mask types; examples include programmable mirror arrays or LCD matrices.

[0092] The source SO (e.g., a mercury lamp or an excimer laser, an LPP (laser-produced plasma) EUV source) generates a radiation beam. For example, such a beam is fed directly or after having traversed an adjusting device such as a beam expander Ex into the illumination system (illuminator) IL. The illuminator IL may include an adjusting device AD for setting the outer radial extent and / or the inner radial extent of the intensity distribution in the beam (commonly referred to as σ - outer and σ - inner, respectively). Additionally, it will typically include various other components, such as an integrator IN and a condenser CO. In this way, the beam B incident on the mask device MA has a desired uniformity and intensity distribution in its cross-section.

[0093] In some embodiments, the source SO may be located within the housing of the lithographic projection apparatus (often the case when the source SO is, for example, a mercury lamp), but it may also be remote from the lithographic projection apparatus, and the radiation beam generated by the source SO is guided into the apparatus (e.g., by means of a suitable directing mirror); this latter case may be when the source SO is an excimer laser (e.g., emitting laser based on KrF, ArF, or F2).

[0094] The bundle of beams PB can subsequently intersect the mask device MA held on the mask device stage MT. After having traversed the mask device MA, the beam B can pass through the lens PL which focuses the beam B onto the target portion C of the substrate W. By means of the second positioning device (and the interferometric device IF), the substrate stage WT can be accurately moved, for example, in order to position different target portions C in the path of the bundle of beams PB. Similarly, for example, after mechanically retrieving the mask device MA from the mask device library or during the scan, the first positioning device can be used to accurately position the mask device MA relative to the path of the beam B. Generally, the movement of the stages MT, WT can be achieved by means of a long-stroke module (coarse positioning) and a short-stroke module (fine positioning). However, in the case of a stepper (as opposed to a step-and-scan tool), the mask device stage MT can be connected only to a short-stroke actuator or can be fixed.

[0095] The tool depicted can be used in two different modes (step mode and scan mode). In step mode, the mask device stage MT is kept substantially stationary and the entire mask device image is projected onto the target portion C in one go (i.e., a single "flash"). The substrate stage WT can be displaced in the x and / or y directions such that different target portions C can be irradiated by the bundle of beams PB.

[0096] In scan mode, substantially the same situation applies, except that a given target portion C is not exposed in a single "flash". Instead, the mask device stage MT can be moved at a speed v in a given direction (the so-called "scan direction", e.g., the y direction) such that the projection beam B scans across the mask device image; simultaneously, the substrate stage WT moves synchronously in the same or opposite direction at a speed V = Mv, where M is the magnification of the lens PL (usually, M = 1 / 4 or 1 / 5). In this way, a relatively large target portion C can be exposed without compromising the resolution.

[0097] Figure 10 is a schematic view of another lithographic projection apparatus (LPA) according to an embodiment of the present disclosure.

[0098] The LPA can include a source collector module SO, an illumination system (illuminator) IL configured to condition a radiation beam B (e.g., EUV radiation), a support structure MT, a substrate stage WT, and a projection system PS.

[0099] The support structure (e.g., mask device stage) MT can be configured to support a mask device (e.g., a mask or a reticle) MA and is connected to a first positioner PM configured to accurately position the mask device.

[0100] A substrate table (e.g., a wafer table) WT can be configured to hold a substrate (e.g., a wafer coated with resist) W and is connected to a second positioner PW configured to accurately position the substrate.

[0101] A projection system (e.g., a reflective projection system) PS can be configured to project a pattern imparted to a radiation beam B by a mask device MA onto a target portion C (e.g., including one or more dies) of a substrate W.

[0102] As depicted herein, the LPA can be of the reflective type (e.g., employing a reflective mask device). It should be noted that since most materials are absorptive in the EUV wavelength range, the mask device can have a multilayer reflector including, for example, multiple stacks of molybdenum and silicon. In one example, the multilayer stack reflector has 40 layer pairs of molybdenum and silicon, where the thickness of each layer is a quarter wavelength. X-ray lithography can be used to generate even smaller wavelengths. Since most materials are absorptive at EUV and x-ray wavelengths, a thin sheet of patterned absorptive material on the mask device topography (e.g., a TaN absorber on top of the multilayer reflector) defines the locations where features will print (positive resist) or not print (negative resist).

[0103] An illuminator IL can receive an extreme ultraviolet radiation beam from a 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) with one or more emission spectral lines in the EUV range into a plasma state. In one such method (often referred to as laser-produced plasma (“LPP”)), a fuel (such as a droplet, stream, or cluster of a material having a spectral emission element) can be irradiated with a laser beam to generate a plasma. The source collector module SO can be part of an EUV radiation system including a laser for providing the laser beam that excites the fuel. The resulting plasma emits output radiation (e.g., EUV radiation), and the output radiation is collected using a radiation collector provided in the source collector module. For example, when using a CO 2 laser to provide the laser beam for fuel excitation, the laser and the source collector module can be separate entities.

[0104] In these cases, the laser may not be considered part of the lithographic apparatus, and the radiation beam can be transmitted from the laser to the source collector module by means of a beam delivery system including, for example, suitable steering mirrors and / or beam expanders. In other cases, for example, when the source is a discharge-produced plasma EUV generator (often referred to as a DPP source), the source can be an integral part of the source collector module.

[0105] The illuminator IL may include an adjuster for adjusting the angular intensity distribution of the radiation beam. Generally, at least the outer radial range and / or the inner radial range of the intensity distribution in the pupil plane of the illuminator may be adjusted (commonly referred to as σ - outer and σ - inner, respectively). Additionally, the illuminator IL may include various other components, such as a faceted field mirror device and a faceted pupil mirror device. The illuminator may be used to adjust the radiation beam to have a desired uniformity and intensity distribution in its cross - section.

[0106] The radiation beam B may be incident on a mask device (e.g., a mask) MA held on a support structure (e.g., a mask device table) MT and patterned by the mask device. After reflection from the mask device (e.g., a 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. By means of a second positioner PW and a position sensor PS2 (e.g., an interferometric device, a linear encoder, or a capacitive sensor), the substrate table WT can be accurately moved, for example, to position different target portions C in the path of the radiation beam B. Similarly, a first positioner PM and another position sensor PS1 may be used to accurately position the mask device (e.g., a mask) MA relative to the path of the radiation beam B. Mask device alignment marks M1, M2 and substrate alignment marks P1, P2 may be used to align the mask device (e.g., a mask) MA and the substrate W.

[0107] The depicted apparatus LPA may be used in at least one of the following modes: a step mode, a scan mode, and a stationary mode.

[0108] In the step mode, while the entire pattern imparted to the radiation beam is projected onto the target portion C at once (i.e., a single static exposure), the support structure (e.g., a mask device table) MT and the substrate table WT are kept substantially stationary. Then, the substrate table WT is displaced in the X and / or Y direction so that different target portions C can be exposed.

[0109] In the scan mode, while the pattern imparted to the radiation beam is projected onto the target portion C (i.e., a single dynamic exposure), the support structure (e.g., a mask device table) MT and the substrate table WT are scanned synchronously. The speed and direction of the substrate table WT relative to the support structure (e.g., a mask device table) MT can be determined by the (reduction ratio) magnification and the image inversion characteristics of the projection system PS.

[0110] In the stationary mode, when projecting the pattern imparted to the radiation beam onto the target portion C, the support structure (e.g., the mask device table) MT is kept substantially stationary to hold the programmable mask device, and the substrate table WT is moved or scanned. In such a mode, a pulsed radiation source is typically employed and the programmable mask device is updated as needed after each movement of the substrate table WT or between successive radiation pulses during the scan. This operating mode can be readily applied to maskless lithography using a programmable mask device such as a programmable mirror array.

[0111] Figure 11 is a detailed view of a lithographic projection apparatus according to an embodiment of the present disclosure.

[0112] The LPA shown may include a source collector module SO, an illumination system IL, and a projection system PS. The source collector module SO is constructed and arranged such that a vacuum environment can be maintained in the enclosure structure ES of the source collector module SO. EUV radiation emitting a hot plasma HP can be formed by generating a plasma source through a discharge. EUV radiation can be generated by a gas or vapor (e.g., Xe gas, Li vapor, or Sn vapor), where a hot plasma HP is generated to emit radiation in the EUV range of the electromagnetic spectrum. For example, the hot plasma HP is generated by a discharge that generates at least a partially ionized plasma. For efficient generation of radiation, a partial pressure of, for example, 10 Pa of Xe, Li, Sn vapor, or any other suitable gas or vapor may be required. In an embodiment, an excited tin (Sn) plasma is provided to generate EUV radiation.

[0113] The radiation emitted by the hot plasma HP is transferred from the source chamber SC to the collector chamber CC via an optional gas barrier or contaminant trap CT located in or behind an opening in the source chamber SC. The contaminant trap CT may include a channel structure. The contaminant trap CT may also include a gas barrier, or a combination of a gas barrier and a channel structure. It is known in the art that the contaminant trap or contaminant barrier CT further indicated herein includes at least a channel structure.

[0114] The collector chamber CC may include a radiation collector CO that may be a so-called grazing incidence collector. The radiation collector CO has an upstream radiation collector side US and a downstream radiation collector side DS. The radiation traversing the radiation collector CO can be reflected from the grating spectral filter SF and focused on the virtual source point IF along the optical axis indicated by the dotted line "O". The virtual source point IF may be referred to as an intermediate focus, and the source collector module is arranged such that the intermediate focus IF is located at or near the opening OP in the enclosure structure ES. The virtual source point IF is an image of the radiation-emitting plasma HP.

[0115] Subsequently, the radiation traverses the illumination system IL, which may include a faceted field mirror device FM and a faceted pupil mirror device PM, arranged to provide a desired angular distribution of the radiation beam B at the mask device MA and a desired uniformity of the radiation amplitude at the mask device MA. After reflection of the radiation beam B at the mask device MA held by the support structure MT, a patterned beam PB is formed, and the patterned beam PB is imaged via a reflective element RE through the projection system PS onto a substrate W held by a substrate table WT.

[0116] There may generally be more elements in the illumination optics unit IL and the projection system PS than those shown. Depending on the type of lithographic apparatus, a grating spectral filter SF may optionally be present. Additionally, there may be more mirrors than those shown in the figure, for example, there may be 1 to 6 additional reflective elements in the projection system PS.

[0117] The collector optics CO may be a nested collector with a grazing incidence reflector GR, shown only as an example of a collector (or collector mirror). The grazing incidence reflector GR is arranged axially symmetrically about the optical axis O, and this type of collector optics CO can be used in combination with a discharge-produced plasma source, commonly referred to as a DPP source.

[0118] Figure 12 is a detailed view of a source collector module SO of a lithographic projection apparatus LPA according to an embodiment of the present disclosure.

[0119] The source collector module SO may be part of the LPA radiation system. A laser LA may be arranged to deposit laser energy into a fuel such as xenon (Xe), tin (Sn), or lithium (Li), thereby generating a highly ionized plasma HP with an electron temperature of several 10 eV. The high-energy radiation generated during the de-excitation and recombination of these ions is emitted from the plasma, collected by the near-normal incidence collector optics CO, and focused onto an opening OP in an enclosure structure ES.

[0120] The concepts disclosed herein can simulate or mathematically model any general imaging system for imaging sub-wavelength features and can be particularly useful for emerging imaging technologies capable of generating increasingly shorter wavelengths. Emerging technologies already in use include extreme ultraviolet (EUV), DUV lithography capable of generating a 193 nm wavelength by using an ArF laser and even a 157 nm wavelength by using a fluorine laser. Additionally, EUV lithography can generate wavelengths in the range of 20 nm to 50 nm by using a synchrotron or by bombarding a material (solid or plasma) with high-energy electrons in order to generate photons in this range.

[0121] Embodiments of the present disclosure may be further described in the following aspects.

[0122] 1. A method for reducing wafer patterning errors caused by a mask device, the method comprising:

[0123] Obtaining a first mask design having a first portion associated with an optimized pupil, wherein the optimized pupil is generated by a source-mask optimization process;

[0124] Obtaining information about errors on the mask device, wherein the errors are located by using an inspection device, and wherein the mask device is fabricated with the first mask design; and

[0125] Performing source optimization by combinatorially using the first portion and a second portion to generate a re-optimized pupil.

[0126] 2. The method according to aspect 1, further comprising locating the errors by using an inspection tool.

[0127] 3. The method according to aspect 2, further comprising performing a mask inspection of the mask device by using an inspection tool.

[0128] 4. The method according to aspect 2, further comprising performing a wafer inspection of the wafer by using an inspection tool.

[0129] 5. The method according to aspect 1, further comprising obtaining a prediction result of the errors.

[0130] 6. The method according to aspect 5, wherein the second portion is identified based on the prediction result.

[0131] 7. The method according to aspect 5, further comprising determining that the prediction result of the errors is higher than a local threshold.

[0132] 8. The method according to aspect 7, further comprising: performing a lithography manufacturing inspection (LMC) using the mask device to obtain a prediction result of the second portion having the errors.

[0133] 9. The method according to aspect 8, further comprising determining, by using the LMC, that the errors are process window limiting terms.

[0134] 10. The method according to aspect 1, wherein the prediction result is a mask error enhancement factor (MEEF) obtained by performing an LMC using the mask device.

[0135] 11. The method according to aspect 1, wherein the prediction result is a depth of focus (DOF), and the errors reduce the DOF.

[0136] 12. The method according to aspect 1, wherein the first part does not have the error or has an error reduced compared to the error in the second part.

[0137] 13. The method according to aspect 7, further comprising identifying a part of the mask device having an error of a type of error, wherein the source optimization is performed using the part where the error is the largest for the type of error.

[0138] 14. The method according to aspect 13, wherein the type of error is a deviation.

[0139] 15. The method according to aspect 14, wherein the type of error is an X deviation.

[0140] 16. The method according to aspect 14, wherein the type of error is a Y deviation.

[0141] 17. The method according to aspect 14, wherein the type of error is an X and Y deviation.

[0142] 18. The method according to aspect 13, wherein the type of error is an edge shift.

[0143] 19. The method according to aspect 18, wherein the type of error is an X edge shift.

[0144] 20. The method according to aspect 18, wherein the type of error is a Y edge shift.

[0145] 21. The method according to aspect 18, wherein the type of error is an X and Y edge shift.

[0146] 22. The method according to aspect 13, wherein the type of error is an edge defect.

[0147] 23. The method according to aspect 19, wherein the type of error is an X edge defect.

[0148] 24. The method according to aspect 19, wherein the type of error is a Y edge defect.

[0149] 25. The method according to aspect 19, wherein the type of error is an X and Y edge defect.

[0150] 26. The method according to aspect 7, further comprising identifying parts of the mask device having different types of errors, wherein the source optimization is performed using the parts having the largest error for the type of error.

[0151] 27. The method according to aspect 1 further comprises applying weights to the first part and the second part, the weights being selected to establish the relative contributions of the first part and the second part in generating the re-optimized pupil.

[0152] 28. The method according to aspect 27 further comprises:

[0153] Obtaining a plurality of prediction results of the mask device;

[0154] Locating a plurality of first errors on the mask device based on the plurality of prediction results; and

[0155] Identifying a plurality of second parts of the mask device having the located plurality of errors, wherein weights are assigned to the plurality of second parts having the maximum errors in an error type, and wherein the plurality of second parts includes the second part.

[0156] 29. The method according to aspect 27 further comprises iteratively adjusting the weights during successive source optimizations to improve the process window.

[0157] 30. The method according to aspect 29, wherein the mask device and the re-optimized pupil result in an improved process window relative to the mask device and the optimized pupil.

[0158] 31. The method according to aspect 1, wherein the source optimization is performed for a lithography system having a numerical aperture (NA) greater than or equal to 0.4.

[0159] 32. The method according to aspect 31, wherein the NA is 0.55.

[0160] 33. The method according to aspect 31 further comprises stitching a mask device layout for use with a lithography system having the NA, wherein the mask device is projected with a magnification that maintains a mask reflectivity higher than 0.5.

[0161] 34. The method according to aspect 1, wherein the mask design corresponds to one of a DRAM layer, a storage node (SP) layer, a storage node pad (SNP) layer, or an array pattern.

[0162] 35. The method according to aspect 1 further comprises performing a voting process using the re-optimized pupil to generate a second re-optimized pupil.

[0163] 36. The method according to aspect 1, wherein generating the re-optimized pupil does not include performing a voting process.

[0164] 37. The method according to aspect 1, wherein the source optimization includes generating a discrete pupil.

[0165] 38. The method according to aspect 1, wherein source optimization includes generating a freeform pupil.

[0166] 39. The method according to aspect 1, wherein source optimization includes generating a discrete pupil and a freeform pupil.

[0167] 40. A non-transitory computer-readable medium having recorded thereon instructions for reducing wafer patterning errors caused by a mask device, the instructions, when executed by a computer having at least one programmable processor, cause the operations as described in any one of aspects 1 to 39.

[0168] 41. A system for reducing wafer patterning errors caused by a mask device, the system comprising:

[0169] at least one programmable processor; and

[0170] a non-transitory computer-readable medium having recorded thereon instructions, the instructions, when executed by a computer having at least one programmable processor, cause the operations as described in any one of aspects 1 to 39.

[0171] Although the concepts disclosed herein can be used for imaging on a substrate such as a silicon wafer, it should be understood that the disclosed concepts can be used with any type of lithographic imaging system, e.g., those lithographic imaging systems for imaging on substrates other than silicon wafers.

[0172] The combinations and sub-combinations of elements disclosed herein constitute separate embodiments and are provided only by way of example. Additionally, the above description is intended to be illustrative and not restrictive. Accordingly, those skilled in the art will appreciate that modifications can be made as described without departing from the scope of the claims set forth below.

Claims

1. A non - transitory computer - readable medium having instructions recorded thereon, which, when executed by a computer having at least one programmable processor, cause the processor to execute a method for reducing wafer patterning errors caused by a mask device for lithography, the method comprises: obtaining a first mask design having a first portion associated with an optimized pupil, wherein the optimized pupil is generated by a source - mask optimization process; acquiring an error on the mask device, wherein the error is located by using an inspection device, and wherein the mask device is fabricated with the first mask design; identifying a second portion of the mask device having the error; and performing source optimization by combinatorially utilizing the first portion and the second portion to generate a re - optimized pupil.

2. The medium according to claim 1, wherein, the error is located by using a mask inspection device or a wafer inspection device.

3. The medium according to claim 1, wherein, the method further comprises obtaining a prediction result of the error, and wherein the second portion is identified based on the prediction result.

4. The medium according to claim 3, wherein, the method further comprises: performing lithography manufacturing inspection (LMC) to obtain a prediction result of the second portion having the error.

5. The medium according to claim 4, wherein, the method further comprises: determining, by using the LMC, that the error is a process window limiting term.

6. The medium according to claim 1, wherein, the prediction result includes one or more of depth of focus (DOF) and mask error enhancement factor (MEEF), the mask error enhancement factor is obtained by performing LMC using the mask device, and the error reduces the DOF.

7. The medium according to claim 1, wherein, the first portion does not have the error or has a reduced error compared to the error in the second portion.

8. The medium according to claim 3, wherein, the method further comprises identifying a portion of the mask device having an error of an error type, and wherein the source optimization is performed using the portion where the error is the largest for the error type.

9. The medium according to claim 8, wherein, the error type is X - deviation or Y - deviation or edge shift.

10. The medium according to claim 1, wherein, the method further comprises applying weights to the first portion and the second portion, the weights being selected to establish the relative contributions of the first portion and the second portion in generating the re - optimized pupil.

11. The medium according to claim 1, wherein, the method further comprises: obtaining a plurality of prediction results of the mask device; locating a plurality of first errors on the mask device based on the plurality of prediction results; and Identify a plurality of second portions of the mask device having a plurality of located errors, wherein the weights are assigned to the plurality of second portions having the largest error in an error type, and wherein the plurality of second portions includes the second portion.

12. The medium according to claim 10, wherein, the method further comprises: iteratively adjusting the weights during successive source optimizations to improve the process window.

13. The medium according to claim 1, wherein, the method further comprises: performing a voting process using the re-optimized pupil to generate a second re-optimized pupil.

14. The medium according to claim 1, wherein, generating the re-optimized pupil does not include performing a voting process.

15. The medium according to claim 1, wherein the source optimization includes generating a discrete pupil or a freeform pupil.

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