Simulation assistance method and software to guide selection of patterns or gauges for lithographic processes

Abstract

A method, computer program and system are disclosed, wherein one method includes characterizing a depth change of a predicted result within a feature of a pattern from a lithographic simulation. The method evaluates the depth change characterization and selects a pattern or gauge based on the depth change evaluation. In some embodiments, the evaluation may be based on spatial image (AI) depth sensitivity with the depth variation.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. application No. 63 / 419,420, filed on October 26, 2022, and the entire contents of that U.S. application are incorporated herein by reference. Technical Field

[0003] The description herein generally relates to analysis of simulated or printed patterns. More specifically, the present disclosure includes apparatus, methods, and computer programs for determining a pattern or gauge suitable for use with imaging and / or modeling. Background Art

[0004] Lithographic projection apparatus may be used, for example, in the manufacture of integrated circuits (ICs). In such cases, a patterning device (e.g., a mask) may include or provide a pattern (a "design layout") corresponding to a single layer of the IC, and such pattern may be transferred to a target portion (e.g., comprising one or more dies) on a substrate (e.g., a silicon wafer) coated with a layer of radiation-sensitive material ("resist") by methods such as irradiating the target portion through the pattern on the patterning device. Typically, a single substrate comprises a plurality of adjacent target portions, to which the pattern is transferred successively, one target portion at a time, by the lithographic projection apparatus. In one type of lithographic projection apparatus, the pattern on the entire patterning device is transferred to one target portion in one operation; such an apparatus may also be referred to as a stepper. In an alternative apparatus, a step-and-scan apparatus may cause the projection beam to be scanned across the patterning device in a given reference direction (the "scanning" direction) while synchronously moving the substrate parallel or antiparallel to such reference direction. Different portions of the pattern on the patterning device are gradually transferred to one target portion. Typically, since the lithographic projection apparatus will have a reduction ratio M (eg 4), the speed F of the substrate movement will be 1 / M times the speed at which the projection beam scans the patterning device.More information on lithographic apparatus can be found in, for example, US 6,046,792, incorporated herein by reference.

[0005] Before the pattern is transferred from the pattern forming 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 baking (PEB), development, hard baking and measurement / detection of the transferred pattern. An array of such processes is used as the basis for making a single layer of a device (e.g., IC). The substrate may then undergo various processes, such as etching, ion implantation (doping), metallization, oxidation, chemical mechanical polishing, etc., all of which are intended to refine a single layer of the device. If several layers are required in the device, the entire process or a variation thereof is repeated for each layer. Ultimately, there will be a device in each target portion on the substrate. These devices are then separated from each other by techniques such as cutting or sawing, so that individual devices can be mounted on a carrier, connected to pins, etc.

[0006] Therefore, manufacturing devices (such as semiconductor devices) generally involves using multiple manufacturing processes to process substrates (e.g., semiconductor wafers) to form various features and multiple layers of the device. These layers and features are generally manufactured and processed using, for example, deposition, photolithography, etching, chemical mechanical polishing, and ion implantation. Multiple devices can be manufactured on multiple dies on a substrate, and the devices are subsequently separated into separate devices. Such a device manufacturing process can be considered a patterning process. The patterning process involves a patterning step, such as optical and / or nanoimprint lithography that uses a pattern forming device in a lithographic device to transfer a pattern on a pattern forming device to a substrate, and the patterning process generally but optionally involves one or more related pattern processing steps, such as resist development by a developing device, baking the substrate using a baking tool, etching using a pattern using an etching device, etc.

[0007] As mentioned, photolithography is a central step in the fabrication of devices such as ICs, where patterns formed on a substrate define the functional elements of the device, such as microprocessors, memory chips, etc. 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 elements has been continuously reduced for decades, while the number 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, the layers of a device are fabricated using a lithographic projection apparatus that projects a design layout onto a substrate using illumination from a deep ultraviolet illumination source, thereby producing individual functional elements with dimensions well below 100 nm (i.e., less than half the wavelength of the radiation from the illumination source (e.g., a 193 nm illumination source)).

[0009] This process of printing features with dimensions smaller than the classical resolution limit of the lithographic projection apparatus may be referred to as 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. In general, the smaller k1 is, the more difficult it becomes to reproduce a pattern on a substrate that resembles the shape and dimensions planned by the designer in order to achieve 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 patterning device. These steps include, for example, but are not limited to, optimization of NA and optical coherence settings, customized illumination schemes, use of phase-shifted patterning devices, 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). The term "projection optics" as used herein should be broadly interpreted to cover various types of optical systems, including, for example, refractive optics, reflective optics, apertures, and reflective-refractive optics. The term "projection optics" may also include components that operate according to any of these design types for collectively or individually directing, shaping, or controlling a projection radiation beam. The term "projection optics" may include any optical component in a lithographic projection apparatus, regardless of where the optical component is positioned on the optical path of the lithographic projection apparatus. Projection optics may include optical components for shaping, adjusting, and / or projecting radiation from a source before the radiation passes through a patterning device, and / or optical components for shaping, adjusting, and / or projecting the radiation after the radiation passes through a patterning device. Projection optics typically do not include a source and a patterning device.

[0010] During the manufacturing process of integrated circuits (ICs), unfinished or completed circuit components are inspected to ensure that the circuit components are manufactured according to the design and are defect-free. Inspection systems using optical microscopes or charged particle (e.g., electron) beam microscopes (such as scanning electron microscopes (SEMs)) can be used. As the physical size of IC components continues to shrink and the structure of IC components continues to become more complex, the accuracy and throughput of defect detection and detection become more important. The overall image quality depends in particular on the combination of high secondary electron and backscattered electron signal detection efficiency. Backscattered electrons have higher emission energy to escape from deeper layers of the sample, and therefore, the detection of backscattered electrons may be desirable for imaging complex structures such as buried layers, nodes, high aspect ratio trenches or holes of 3D NAND devices. For applications such as overlay measurement, it may be desirable to simultaneously obtain high-quality imaging from secondary electrons and efficient collection of surface information, as well as buried layer information from backscattered electrons, thereby highlighting the need for using multiple electron detectors in the SEM. The ability to monitor and detect IC non-idealities may be limited by the image quality of the inspection system, including limitations on the alignment or calibration of the SEM system. Summary of the invention

[0011] Systems, methods, and computer software for determining a pattern or gauge suitable for use with imaging and / or modeling are disclosed. In one aspect, the method includes: characterizing a depth variation of a predicted result within a feature of a pattern from a lithography simulation; evaluating the depth variation characterization; and selecting a pattern or gauge based on the depth variation evaluation.

[0012] In some variations, the prediction result may represent a resist profile or a resist CD, and the depth variation characterization may be a resist profile depth variation or a resist CD depth variation.

[0013] In some variations, the prediction result may represent an aerial image contour or an aerial image CD, and the depth change representation may be a depth change of the aerial image contour or a depth change of the aerial image CD.

[0014] In some variations, the prediction result may represent an etch profile or an etch CD, and the depth variation characterization may be an etch profile depth variation or an etch CD depth variation.

[0015] In some variations, the assessment may be based on an aerial image (AI) depth sensitivity with the depth variation, the AI ​​depth sensitivity being based on a first derivative of CD as a function of depth, and the AI ​​depth sensitivity being based on a comparison of a total CD change to a total depth change.

[0016] In some variations, the selecting may be based on the aerial image depth sensitivity being less than a threshold. The method may also include performing optical proximity correction (OPC) modeling using a pattern or a gauge.

[0017] In some variations, the selection may be performed based on the spatial image depth sensitivity being greater than a threshold.

[0018] In some variations, the method may include performing local OPC on the features in the pattern where the spatial image depth sensitivity is greater than the threshold to reduce depth variation of the pattern. The local OPC may include detecting hot spot locations in the pattern and performing the local OPC at the hot spot locations. The local OPC may reduce a difference between a first profile of the feature at a first depth and a second profile of the feature at a second depth. The difference may be between a first location on the first profile and a second location on the second profile, the difference determining a sidewall angle of the feature.

[0019] In some variations, the method may include: generating a SEM image of the pattern while excluding portions of the SEM image where the aerial image depth sensitivity is above the threshold; and performing OPC model building using the SEM image.

[0020] In some variations, the method may include: generating a SEM image of the pattern wherein the aerial image depth sensitivity is above the threshold; and performing stochastic modeling using the SEM image.

[0021] In some variations, the method may include obtaining a SEM image of the selected pattern or gauge.

[0022] In some variations, the method may include obtaining, wherein obtaining includes discarding a portion of the SEM image where the aerial image depth sensitivity is above the threshold. The method may also include performing OPC model construction using the SEM image.

[0023] In some variations, the method may include performing stochastic modeling of the pattern based on a portion of the SEM image where the aerial image depth sensitivity is above the threshold.

[0024] In some variations, the method may include calibrating a stochastic failure model based on a portion of the SEM image. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] 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, help explain some principles associated with the disclosed embodiments.

[0026] Figure 1 A block diagram illustrating various subsystems of a lithographic projection apparatus according to an embodiment of the present disclosure.

[0027] Figure 2A An exemplary flow chart for simulating lithography in a lithographic projection apparatus according to an embodiment of the present disclosure is illustrated.

[0028] Figure 2B is a schematic diagram of an exemplary electron beam tool according to an embodiment of the present disclosure.

[0029] Figure 3 An exemplary prediction result of a portion of a pattern having a depth variation according to an embodiment of the present disclosure is illustrated.

[0030] Figure 4 An exemplary process of selecting a pattern or gauge based on depth variation evaluation according to an embodiment of the present disclosure is illustrated.

[0031] Figure 5 An exemplary process illustrating various operations that may be performed based on processing stages and evaluation of AI depth sensitivity according to an embodiment of the present disclosure.

[0032] Figure 6 An exemplary process for reducing depth variation of a pattern according to an embodiment of the present disclosure is illustrated.

[0033] Figure 7 is a block diagram of an exemplary computer system according to an embodiment of the present disclosure.

[0034] Figure 8 is a schematic diagram of a lithography projection apparatus according to an embodiment of the present disclosure.

[0035] Fig. 9 is a schematic diagram of another lithography projection apparatus according to an embodiment of the present disclosure.

[0036] Fig.10 is a detailed view of a lithographic projection apparatus according to an embodiment of the present disclosure.

[0037] Fig.11 is a detailed view of a source collector module of a lithographic projection apparatus according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0038] Although specific reference may be made herein to IC manufacturing, it should be clearly understood that the description herein has many other possible applications. For example, the description herein may be used to manufacture integrated optical systems, guidance and detection 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 of the terms "reticle", "wafer" or "die" herein should be considered interchangeable with the more general terms "mask", "substrate" and "target portion", respectively.

[0039] In this document, the terms "radiation" and "beam" are used to cover 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).

[0040] The pattern forming device may include or may form one or more design layouts. The design layout may be generated using a CAD (computer-aided design) program, a process often referred to as EDA (electronic design automation). Most CAD programs follow a set of predetermined design rules in order to generate a functional design layout / pattern forming device. These rules are set by process and design constraints. For example, the design rules define the spatial tolerance between devices (such as gates, capacitors, etc.) or interconnects to ensure that the devices or lines do not interact with each other in an undesirable manner. One or more of the design rule constraints may be referred to as a "critical dimension" (CD). The critical dimension of a device may be defined as the minimum width of a line or hole or the minimum space between two lines or two holes. Therefore, 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 pattern forming device).

[0041] The terms "mask" or "patterning device" as used herein may be broadly interpreted as referring to a general patterning device that can be used to impart a patterned cross-section to an incident radiation beam that corresponds to the pattern to be produced in a target portion of the substrate; the term "light valve" may also be used in this context. In addition to classical masks (transmissive or reflective; binary, phase-shifting, hybrid, etc.), other examples of such patterning devices include programmable mirror arrays and programmable LCD arrays.

[0042] An example of a programmable mirror array may be a matrix-addressable surface having a viscoelastic control layer and a reflective surface. The basic principle underlying such a device is, for example, that addressed areas of the reflective surface reflect incident radiation as diffracted radiation, while unaddressed areas reflect incident radiation as undiffracted radiation. With the use of appropriate filters, the undiffracted radiation can be filtered out of the reflected beam, leaving only the diffracted radiation; in this way, the beam is patterned according to the addressing pattern of the matrix-addressable surface. Suitable electronic methods can be used to perform the desired matrix addressing.

[0043] An example of a programmable LCD array is given in US Pat. No. 5,229,872, which is incorporated herein by reference.

[0044] Figure 1 A block diagram of various subsystems of a lithographic projection apparatus 10A according to an embodiment of the present disclosure is illustrated. The main components are: a radiation source 12A, which may be a deep ultraviolet excimer laser source or other type of source including an extreme ultraviolet (EUV) source (as discussed above, the lithographic projection apparatus itself need not have a radiation source); an illumination optical device, which, for example, defines partial coherence (represented as sigma) and may include optical devices 14A, 16Aa and 16Ab that shape the radiation from source 12A; a patterning device 18A; and a transmissive optical device 16Ac that projects an image of the patterning device pattern onto a substrate plane 22A. An adjustable filter or aperture 20A at a pupil plane of the projection optics may limit the range of beam angles impinging on the substrate plane 22A, wherein the largest possible angle defines the numerical aperture NA of the projection optics = 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 impinge on the substrate plane 22A.

[0045] In a lithographic projection apparatus, a source provides illumination (i.e., radiation) to a patterning device, and projection optics direct the illumination onto a substrate via the patterning device and shape the illumination. The projection optics may include at least some of components 14A, 16Aa, 16Ab, and 16Ac. An aerial image (AI) is the radiation intensity distribution at the substrate level. A resist model may be used to calculate a resist image from an aerial image, an example of which may be found in U.S. Patent Application Publication No. US 2009-0157630, the entire disclosure of which is hereby incorporated by reference. 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 baking (PEB), and development). The optical properties of the lithographic projection apparatus (e.g., the properties of the illumination, patterning device, and projection optics) indicate the aerial image and may be defined in the optical model. Since the patterning device used in the lithographic projection apparatus may be changed, it is desirable to separate the optical properties of the patterning device from the optical properties of the rest of the lithographic projection apparatus, including at least the source and projection optics. Details of techniques and models for transforming a design layout into various lithography images (e.g., aerial images, resist images, etc.), applying OPC using those techniques and models, and evaluating performance (e.g., in terms of process windows) are described in U.S. Patent Application Publication Nos. US 2008-0301620, 2007-0050749, 2007-0031745, 2008-0309897, 2010-0162197, and 2010-0180251, the disclosures of each of the foregoing publications are hereby incorporated by reference in their entirety.

[0046] One aspect of understanding the lithography process is understanding the interaction of radiation with the patterning device. The electromagnetic field of the radiation after it passes through the patterning device can be determined based on the electromagnetic field of the radiation before it reaches the patterning device and a function that characterizes the interaction. This function can be called a mask transmission function (a mask transmission function can be used to describe the interaction performed by a transmissive patterning device and / or a reflective patterning device).

[0047] The mask transmission function can have a variety of different forms. One form is binary. A binary mask transmission function has either of two values ​​(e.g., zero and a positive constant) at any given location on the pattern forming device. A mask transmission function in binary form can be referred to as a binary mask. Another form is continuous. That is, the modulus of the transmittance (or reflectance) of the pattern forming device is a continuous function of the location on the pattern forming device. The phase of the transmittance (or reflectance) can also be a continuous function of the location on the pattern forming device. A mask transmission function in continuous form can be referred to as a continuous tone mask or a continuous transmission type mask (CTM). For example, a CTM can be represented as a pixelated image, where each pixel can be assigned a value between 0 and 1 (e.g., 0.1, 0.2, 0.3, etc.) instead of a binary value of 0 or 1. In an embodiment, the CTM may be a pixelated grayscale image, where each pixel has multiple values ​​(eg, in the range [-255, 255], normalized values ​​in the range [0, 1] or [-1, 1] or other suitable range).

[0048] The thin mask approximation (also known as the Kirchhoff boundary case) is widely used to simplify the determination of the interaction of radiation with the patterning device. The thin mask approximation assumes that the thickness of the structures on the patterning device is very small compared to the wavelength, and the width of the structures on the mask is very large compared to the wavelength. Therefore, the thin mask approximation assumes that the electromagnetic field after the patterning device is the product of the incident electromagnetic field and the mask transmission function. However, as the lithography process uses radiation with shorter and shorter wavelengths, and the structures on the patterning device become smaller and smaller, the assumption of the thin mask approximation can break down. For example, due to the finite thickness of the structure (e.g., the edge between the top surface and the sidewall), the interaction of radiation with the structure ("mask 3D effect" or "M3D") may become important. Including this scattering in the mask transmission function can enable the mask transmission function to better capture the interaction of radiation with the patterning device. The mask transmission function under the thin mask approximation can be referred to as a thin mask transmission function. The mask transmission function that includes M3D can be referred to as an M3D mask transmission function.

[0049] According to an embodiment of the present disclosure, one or more images may be generated. An image includes various types of signals that may be characterized by a pixel value or an intensity value of each pixel. Depending on the relative value of the pixels within the image, the signal may be referred to as, for example, a weak signal or a strong signal, as may be understood by a person of ordinary skill in the art. The terms "strong" and "weak" are relative terms based on the intensity values ​​of the pixels within the image, and the specific value of the intensity may not limit the scope of the present disclosure. In an embodiment, a strong signal and a weak signal may be identified based on a selected threshold. In an embodiment, the threshold may 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 may refer to a signal having a value greater than or equal to an average signal value across the image, and a weak signal may refer to a signal having a value lower than the average signal value. In an embodiment, a relative intensity value may be based on a percentage. For example, a weak signal may be a signal having an intensity lower than 50% of the highest intensity of a pixel within the image (e.g., a pixel corresponding to a target pattern may be considered as a pixel having the highest intensity). In addition, each pixel within the image may be considered a variable. According to the present embodiment, a derivative or partial derivative may be determined with respect to each pixel within the image, and the value of each pixel may be determined or modified based on an evaluation based on a cost function and / or a gradient-based calculation of a cost function. For example, a CTM image may include pixels, where each pixel is a variable that may take any real value.

[0050] Figure 2A An exemplary flow chart for simulating lithography in a lithographic projection apparatus according to an embodiment of the present disclosure is illustrated. A source model 31 represents the optical properties of a source (including radiation intensity distribution and / or phase distribution). A projection optics model 32 represents the optical properties of the projection optics (including changes in radiation intensity distribution and / or phase distribution caused by the projection optics). A design layout model 35 represents the optical properties of a design layout (including changes in radiation intensity distribution and / or phase distribution caused by a design layout 33), which is a representation of the arrangement of features on or formed by a pattern forming device. An aerial image 36 can be simulated based on the design layout model 35, the projection optics model 32, and the design layout model 35. A resist image 38 can be simulated based on the aerial image 36 using a resist model 37. For simulation of lithography, for example, the profile and CD in the resist image can be predicted.

[0051] More particularly, it should be noted that the source model 31 can represent the optical characteristics of the source, including but not limited to numerical aperture settings, illumination sigma (σ) settings, and any specific illumination shape (e.g., off-axis radiation sources such as toroidal, quadrupole, dipole, etc.). The projection optics model 32 can represent the optical characteristics of the projection optics, including aberrations, deformations, one or more refractive indices, one or more physical dimensions, one or more physical dimensions, etc. The design layout model 35 can represent one or more physical properties of a physical pattern forming device, such as described 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, aerial image intensity slope, and / or CD, which can then be compared to the intended design. The intended 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.

[0052] From this design layout, one or more portions referred to as "snippets" may be identified. In an embodiment, a collection of snippets is extracted, the collection of snippets representing complex patterns in the design layout (typically about 50 snippets to 1000 snippets, but any number of snippets may be used). These patterns or snippets represent small portions of the design (i.e., circuits, cells, or patterns), and more particularly, the snippets typically represent smaller portions that require special attention and / or verification. In other words, a snippet may be a portion of a design layout, or may be similar or have similar behavior to a portion of a design layout, wherein one or more key features are identified through experience (including snippets provided by a customer), through trial and error, or by running a full chip simulation. A snippet may include one or more test patterns or gauge patterns.

[0053] An initial larger set of segments may be provided a priori by the customer based on one or more known key feature areas in the design layout that require specific image optimization. Alternatively, in another embodiment, an initial larger set of segments may be extracted from the entire design layout using some automatic (such as machine vision) or manual algorithm that identifies one or more key feature areas.

[0054] In a lithographic projection apparatus, as an example, the cost function can be expressed as

[0055] (Equation 1)

[0056] where ( z 1 , z 2 , ..., z N ) are N design variables or the values ​​of N design variables. p( z 1 , z 2 , ..., z N ) can be a design variable ( z 1 , z 2 , ..., z N ), such as for ( z 1 , z 2 ,……, z N ) is the difference between the actual and expected values ​​of a characteristic for a set of values ​​of the design variables. p For and f p ( z 1 , z 2 , ..., z N ) is associated with a weight constant. For example, a characteristic may be the position of the edge of a pattern measured at a given point on the edge of the pattern. Different f p ( z 1 , z 2 , ..., z N ) can have different weights w p For example, if a particular edge has a narrow range of allowed positions, then f, which represents the difference between the actual position of the edge and the expected position, p ( z 1 , z 2 , ..., z N )’s weight w p Can be given higher values. f p ( z 1 , z 2 ,……, z N ) can also be a function of the interlayer characteristics, which are in turn 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 ) may be in any other suitable form.

[0057] The cost function may represent any one or more suitable characteristics of the lithographic projection apparatus, the lithographic process, or the substrate, such as focus, CD, image shift, image deformation, image rotation, random variation, throughput, local CD variation, process window, inter-layer characteristics, or a combination of focus, CD, image shift, image deformation, image rotation, random variation, throughput, local CD variation, process window, and inter-layer characteristics. In one embodiment, the design variables ( z 1 , z 2 , ..., z N ) includes one or more selected from dose, global bias of the patterning device, and / or shape of the irradiation. Since the resist image often dictates 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 ) may simply be the distance between a point in the resist image and the expected position of that point (i.e., the edge placement error EPE p ( z 1 , z 2 , ..., z N )). Design variables may include any adjustable parameters, such as, adjustable parameters of the source, pattern forming device, projection optics, dose, focus, etc.

[0058] The lithographic apparatus may include components collectively referred to as "wavefront manipulators" that can be used to adjust the shape of the wavefront and intensity distribution and / or the phase shift of the radiation beam. In an embodiment, the lithographic apparatus can adjust the wavefront and intensity distribution at any location along the optical path of the lithographic projection apparatus, such as before the pattern forming device, near the pupil plane, near the image plane and / or near the focal plane. The wavefront manipulator can be used to correct or compensate for certain deformations of the wavefront and intensity distribution and / or phase shift caused by, for example, temperature changes in the source, pattern forming device, lithographic projection apparatus, thermal expansion of components of the lithographic projection apparatus, etc. Adjusting the wavefront and intensity distribution and / or phase shift can change the value of the characteristic represented by the cost function. Such changes can be simulated according to a model or actually measured. The design variables may include parameters of the wavefront manipulator.

[0059] Design variables may have constraints, which may be expressed as (z 1 , z 2, ……, z N)∈ Z, where Z is a set of possible values ​​of the design variables. One possible constraint on the design variables may 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 a set of values ​​of the design variables that are unrealistic. For example, if the dose is a design variable, then 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 a constraint should not be interpreted as a necessity. For example, the throughput may be affected by the pupil fill ratio. For some illumination designs, a lower pupil fill ratio may discard radiation, resulting in a lower throughput. The throughput may also be affected by the chemical reaction of the resist. Slower resists (e.g., resists that require a higher amount of radiation to be properly exposed) result in lower throughput.

[0060] Figure 2B A schematic diagram of an exemplary imaging system 200 according to an embodiment of the present disclosure is illustrated. The electron beam tool 140 of FIG. 2 may be configured for use in an EBI system. The electron beam tool 140 may be a single beam device or a multi-beam device. As shown in FIG. 2 , the electron beam tool 140 includes a motorized sample stage 201, and a wafer holder 202 supported by the motorized stage 201 to hold a wafer 203 to be inspected. The electron beam tool 140 also includes an objective lens assembly 204, an electron detector 206 (the electron detector 206 includes electron sensor surfaces 206a and 206b), an objective lens aperture 208, a condenser lens 210, a beam limiting aperture 212, a gun aperture 214, an anode 216, and a cathode 218. In some embodiments, the objective lens assembly 204 may include a modified swinging objective deceleration immersion lens (SORIL), which includes a pole piece 204a, a control electrode 204b, a deflector 204c, and an excitation coil 204d. The electron beam tool 140 may additionally include an energy dispersive X-ray spectrometer (EDS) detector (not shown) to characterize the materials on the wafer 203 .

[0061] A primary electron beam 220 is emitted from the cathode 218 by applying a voltage between the anode 216 and the cathode 218. The primary electron beam 220 passes through the gun aperture 214 and the beam limiting aperture 212, which can determine the size of the electron beam entering the condenser lens 210 residing below the beam limiting aperture 212. The condenser lens 210 focuses the primary electron beam 220 before the beam enters the objective lens aperture 208 to set the size of the electron beam before entering the objective lens assembly 204. The deflector 204c deflects the primary electron beam 220 to facilitate scanning of the beam on the wafer. For example, during scanning, the deflector 204c can be controlled to continuously deflect the primary electron beam 220 to different locations on the top surface of the wafer 203 at different points in time to provide data for image reconstruction of different portions of the wafer 203. In addition, the deflector 204c can also be controlled to deflect the primary electron beam 220 to different sides of the wafer 203 at a specific location at different time points to provide data for stereoscopic image reconstruction of the wafer structure at the location. In addition, in some embodiments, the anode 216 and the cathode 218 can be configured to generate multiple primary electron beams 220, and the electron beam tool 140 can include multiple deflectors 204c to simultaneously project multiple primary electron beams 220 to different parts / sides of the wafer to provide data for image reconstruction of different parts of the wafer 203.

[0062] The excitation coil 204d and the pole piece 204a generate a magnetic field that starts at one end of the pole piece 204a and ends at the other end of the pole piece 204a. A portion of the wafer 203 scanned by the primary electron beam 220 may be immersed in the magnetic field and may be charged, which in turn generates an electric field. The electric field reduces the energy of the primary electron beam 220 that strikes the vicinity of the surface of the wafer 203 before the primary electron beam 220 collides with the wafer 203. The control electrode 204b, which is electrically isolated from the pole piece 204a, controls the electric field on the wafer 203 to prevent micro-arching of the wafer 203 and ensure proper beam focusing.

[0063] After receiving the primary electron beam 220, a secondary electron beam 222 may be emitted from a portion of the wafer 203. The secondary electron beam 222 may form a beam spot on the sensor surfaces 206a and 206b of the electron detector 206. The electron detector 206 may generate a signal (e.g., voltage, current, etc.) representing the intensity of the beam spot and provide the signal to the image processing system 250. The intensity of the secondary electron beam 222 and the resulting beam spot may vary according to the external or internal structure of the wafer 203. In addition, as discussed above, the primary electron beam 220 may be projected onto different portions of the top surface of the wafer or onto different sides of the wafer at a specific portion to generate secondary electron beams 222 (and resulting beam spots) of different intensities. Therefore, by mapping the intensity of the beam spot using the portion of the wafer 203, the processing system may reconstruct an image reflecting the internal or surface structure of the wafer 203.

[0064] As discussed above, the imaging system 200 can be used to detect the wafer 203 on the sample stage 201 and includes the electron beam tool 140. The imaging system 200 can also include an image processing system 250, which includes an image acquisition device 260, a storage device 270, and a controller 150. The image acquisition device 260 can include one or more processors. For example, the image acquisition device 260 can include a computer, a server, a mainframe computer, a terminal, a personal computer, any kind of mobile computing device, etc., or a combination thereof. The image acquisition device 260 can be connected to the detector 206 of the electron beam tool 140 via a medium (such as an electrical conductor, a fiber optic cable, a portable storage medium, IR, Bluetooth, the Internet, a wireless network, a radio, or a combination thereof). The image acquisition device 260 can receive a signal from the detector 206 and can construct an image. The image acquisition device 260 can therefore acquire an image of the wafer 203. The image acquisition device 260 can also perform various post-processing functions, such as generating a profile, superimposing an indicator on the acquired image, and the like. The image acquirer 260 may be configured to perform adjustments to the brightness and contrast of the acquired image, etc. The storage 270 may be a storage medium such as a hard disk, a cloud storage, a random access memory (RAM), other types of computer-readable memory, etc. The storage 270 may be coupled to the image acquirer 260 and may be used to save the scanned raw image data as an initial image and a post-processed image. The image acquirer 260 and the storage 270 may be connected to the controller 150. In some embodiments, the image acquirer 260, the storage 270, and the controller 150 may be integrated into one control unit.

[0065] In some embodiments, the image acquirer 260 can acquire one or more images of the sample based on the imaging signal received from the detector 206. The imaging signal can correspond to a scanning operation for performing charged particle imaging. The acquired image can be a single image including multiple imaging regions. The single image can be stored in the storage 270. The single image can be an original image that can be divided into multiple regions. Each of the regions can include an imaging region containing a feature of the wafer 203.

[0066] As used herein, the term "patterning process" means a process that produces an etched substrate by the application of a designated pattern of light as part of a photolithography process.

[0067] As used herein, the term "target pattern" means an idealized pattern to be etched on a substrate.

[0068] As used herein, the term "printed pattern" means a physical pattern on a substrate formed based on a design layout. The printed pattern may include, for example, vias, contact holes, grooves, channels, recesses, edges, or other two-dimensional and three-dimensional features produced by a lithography process.

[0069] As used herein, the term "process model" means a model that includes one or more models that simulate a patterning process. For example, a process model may include any combination of the following: an optical model (e.g., an optical model models the lens system / projection system used to deliver light during the lithography process and may include modeling the final optical image of the light traveling onto the resist), a mask model, a resist model (e.g., a resist model models the physical effects on the resist, such as the chemical effects caused by light), an OPC model (e.g., an OPC model may be used to manufacture a design layout and may include sub-resolution resist features (SRAFs), etc.), an imaging device model (e.g., an imaging device model models what the imaging device may image from the printed pattern).

[0070] As used herein, the term "imaging device" means any number of devices or combinations of devices, associated computer hardware and software that can be configured to produce an image of a target, such as a printed pattern or portion thereof. Non-limiting examples of imaging devices may include: scanning electron microscopes (SEMs), x-ray machines, etc.

[0071] As used herein, the term "calibrate" means to modify (eg, improve or tune) and / or validate, for example, a process model.

[0072] The choice of pattern or gauge constructed or used to characterize a stochastic manufacturing process using a model can depend on the degree of variation of such pattern features. When performing 3D resist modeling, as part of a simulated lithography process, the simulated shape and depth profile of the resist features can be determined. However, optimization of some aspects of the process (e.g., OPC) may result in changes in other parts of the process, such as the resist features determined according to the 3D resist model. For example, in an ideal case, the resist features may initially have almost vertical sides, but during optimization, the sides may form angles so that the size or shape of the resist features changes with depth. In some parts of the pattern, such depth variations (and the resulting changes in CD) may be tolerated. In the case where the pattern includes more sensitive features, such a pattern may result in a simulated CD that varies too much and impermissibly reduces the robustness of the simulation that predicts the simulated CD. Such changes may interfere with the generation of a robust OPC model for pattern optimization.

[0073] The present disclosure particularly addresses the depth variation of features characterizing (e.g., in a simulated resist layer) and the selection of simulated patterns with features that are not impermissibly sensitive based on the simulated depth. If performed before mask tape-out, further OPC can be performed to reduce pattern sensitivity, thereby making the pattern more useful for OPC model building. If after tape-out, SEM images of features with sufficiently low sensitivity can be used to specifically perform OPC model building. Similarly, features with higher sensitivity can be selected for SEM imaging as part of a stochastic modeling process, in which such variations may be useful.

[0074] Figure 3 An exemplary prediction result of a portion of a pattern with depth variation according to an embodiment of the present disclosure is illustrated. Figure 3An exemplary ideal resist pattern 310 (e.g., a portion of a resist layer for printing a bar, line, etc.) is depicted. Inset 302 shows target 310 in side view 304 and top view 306. Feature 320 is a simulated pattern, but as can be seen in side view 304, feature 320 can have depth variations. Four depths 310a to 310d are shown at which a lithography simulation (e.g., a resist model) can produce predicted shapes 320a to 320d (e.g., resist profiles) of feature 320 on the resist layer. These depths can vary from the top surface (e.g., 0 nm) to the bottom surface (e.g., 37 nm), and can include any number of intermediate depths (e.g., steps of 3 nm, 5 nm, 7 nm), and any combination of such possible depths. Examples of corresponding predicted shapes 320a to 320d of feature 320 are shown in top view 306 along with a top view of target feature 310 for comparison.

[0075] In some embodiments, a metric such as CD in a particular direction at a given gauge may be determined to quantify changes in the predicted shape. As shown in the exemplary curve 340, for a change in depth 342, there may be a corresponding change in CD 344. In this example, the dimensions (length and width, and corresponding CD) are simulated to be smaller at depth 310a than at 310d. This can also be seen by the increase in the dimensions of the shapes 320a to 320d with the corresponding depths 310a to 310d. However, the change in CD relative to depth may be complex and need not be linear. This is reflected in the curve 340, which shows that as depth increases, the corresponding change in CD decreases. In other words, the simulated features may have a sensitivity (simulated change) that varies with depth. Specifically, different features / patterns may have different sensitivities and may thus be useful or useless for applications related to OPC model building or stochastic modeling. Therefore, in some embodiments, a pattern gauge or the like may be selected based on a simulated image (e.g., an aerial image) at a depth where the sensitivity of the predicted result is generally lower than the sensitivity at some other depths. By quantifying the AI ​​depth sensitivity of a feature, various features / patterns can be selected that produce a more robust model (e.g., an OPC model). As used herein, the term "AI depth sensitivity" means a measure of a feature as a function of depth within a simulated pattern (e.g., based on an aerial image). While many of the examples herein utilize AI depth variation and variation sensitivity as indicators, the present disclosure contemplates that any method of quantifying the variation of a feature as a function of depth can be used for substantially similar analysis and used with any of the disclosed embodiments, such as etch depth variation, resist depth variation, etc.

[0076] Figure 4 An exemplary process for selecting a pattern or gauge based on a depth variation assessment according to an embodiment of the present disclosure is illustrated. At 410, the method may include characterizing a depth variation of a prediction result (e.g., one or more predicted shapes 320a to 320d) within a feature (e.g., feature 320) of a pattern from a lithography simulation. In some embodiments, the prediction result may represent a resist profile or a resist CD. Thus, the depth variation characterization may be a resist profile depth variation or a resist CD depth variation. In other embodiments, the prediction result may represent an aerial image profile or an aerial image CD. Thus, the depth variation characterization may be an aerial image profile depth variation or an aerial image CD depth variation. In some other embodiments, the prediction result may represent an etch profile or an etch CD. Thus, the depth variation characterization may be an etch profile depth variation or an etch CD depth variation.

[0077] At 420, the method may include evaluating a depth variation characterization. In some embodiments, the evaluation may be based on a spatial image depth sensitivity with depth variation.

[0078] At 430, the method may include selecting a pattern or gauge based on the depth variation assessment. As previously mentioned, the selection may be based on the stage in the lithography manufacturing process, and may also be based on the desired application of the selected pattern and gauge (e.g., for performing OPC or stochastic modeling, as further described herein).

[0079] Figure 5 An exemplary process of various operations that may be performed based on processing stages and evaluation of AI depth sensitivity according to an embodiment of the present disclosure is illustrated. Figure 4 The general process described in Figure 5 , but with the addition of optional processes, which may be present in any combination according to various embodiments. A right branch delineates processes (e.g., processes 532, 542, and 552), wherein selection is made based on spatial image depth sensitivity being less than a threshold. A left branch delineates processes (e.g., processes 534, 544, 554), wherein selection is made based on spatial image depth sensitivity being greater than a threshold. In some embodiments, the AI ​​depth sensitivity may be based on a first-order derivative of CD as a function of depth (e.g., the derivative of curve 340), for example, wherein the threshold is the derivative of a specific value at a local location along curve 340. In other embodiments, the AI ​​depth sensitivity may be based on a comparison of total CD change to total depth change. For example, if curve 340 has a local flattening, such a range may be considered sensitive if the depth range includes a portion of a sharp CD change. Conversely, such a range may not be considered sensitive if the sensitivity has only a small transient change.

[0080] These processes are further illustrated as being performed at different stages (530, 540, 550) in a lithography process. Although the processes described below refer to specific stages that provide various technical benefits, the processes are provided only as examples and may be performed at any suitable stage in a lithography process.

[0081] In some embodiments, when the AI ​​site sensitivity is less than a threshold, an embodiment may include performing OPC modeling using a pattern or gauge. Because the selected pattern or gauge may be relatively insensitive to depth, such features may be robust and provide a consistent and accurate basis for the OPC model. In this way, the OPC model can provide corrections that can produce the expected results over the entire depth of the corrected feature. Conversely, when the pattern or gauge has an AI sensitivity greater than a threshold, the present disclosure provides other processes based on the lithography stage for reducing AI depth sensitivity, selecting a pattern or gauge, and the like. Such a reduction in AI depth sensitivity can make such features suitable for OPC modeling.

[0082] Before utilizing the mask in an actual lithography process, it may be advantageous to optimize the mask design as much as possible. Figure 5 ) At the pre-tapeout stage 530, which may be before the mask design is completed, process 532 may be performed and includes selecting a gauge or pattern having an AI depth sensitivity less than a threshold for SEM imaging.

[0083] Figure 6 An exemplary process for reducing depth variation of a pattern according to an embodiment of the present disclosure is illustrated. Return to Reference Figure 5 In some embodiments, the pre-tapeout stage 530 may include performing a process 534 for reducing depth variation. Figure 6 As shown in , process 534 may include: performing local OPC on features in the pattern at one or more locations where the AI ​​depth sensitivity is greater than a threshold to reduce the depth variation of the pattern. Such local OPC may include detecting hot spot locations in the pattern and performing local OPC at the hot spot locations. Examples of hot spots may include pinching, bridging, etc.

[0084] Figure 6Reproduced feature 320 and predicted shapes 320a-320d, where, in this example, the sensitivity depicted by curve 340 is above a threshold. Performing local OPC 605 can reduce the difference between a first profile 620a of feature 620 at a first depth 610b and a second profile 620b of feature 620 at a second depth 610c (depicted here as substantially covering first profile 620a). The present disclosure contemplates that OPC can be used to perform pattern improvement in a variety of ways. Comparing CD change 344 before OPC with CD change 644 after OPC, it can be seen that feature 620 is less sensitive. Figure 6 The example provided in also illustrates that the reduced sensitivity can be reflected in the change in the sidewall angle of the feature. Because the profile can define the calculated sidewall angle, a (reduced) difference can be between a first location 650a on the first profile 620a and a second location 650b on the second profile 620b, which determines the sidewall angle of the feature 620. Again, the depicted example illustrates a highly corrected feature having a sidewall angle of approximately 90 degrees, but other correction ranges are possible based on OPC optimization.

[0085] Back to Figure 5 , the post-tapeout stage 540 may include a process 544 that may be post-tapeout but before at least some SEM images are acquired. In some embodiments, process 544 may include: generating a SEM image of the pattern while excluding portions of the SEM image where the AI ​​depth sensitivity is above a threshold. The method may also include performing OPC model building using the SEM image. Configuring the lithography process to exclude patterns or gauges with higher sensitivity can improve the lithography process by not requiring SEM image acquisition time and processing of SEM images that may cause instability in the OPC model. In other embodiments, process 544 may also include: generating a SEM image of the pattern where the AI ​​depth sensitivity is above a threshold. Here, the method may also include performing stochastic modeling using the SEM image.

[0086] The post-SEM stage 550 includes embodiments that include obtaining a SEM image of the selected pattern or gauge. Here, various embodiments are disclosed that allow data cleaning, efficient stochastic modeling, etc., where the SEM image has been obtained. At process 552, some embodiments may include performing OPC modeling using the SEM image that has been obtained with features having an AI site sensitivity below a threshold.

[0087] When acquiring SEM images of a wafer, it is possible that such SEM images may include both SEM images having features with an AI depth sensitivity below a threshold and SEM images having features with an AI depth sensitivity above a threshold. In some embodiments of process 554, obtaining may include discarding portions of the SEM image where the spatial image depth sensitivity is above the threshold. Because the remaining SEM images (with lower sensitivity patterns or gauges) may be advantageous for performing OPC modeling, some embodiments may include performing OPC model building using SEM images without the discarded portions.

[0088] In addition, other embodiments of process 554 may include performing stochastic modeling of the pattern based on a portion of the SEM image where the aerial image depth sensitivity is above a threshold. In some embodiments, this may include calibrating a stochastic failure model based on the portion of the SEM image in a manner similar to that previously described with respect to process 544.

[0089] Figure 7 is a block diagram of an exemplary computer system CS according to an embodiment of the present disclosure.

[0090] The computer system CS comprises a bus BS or other communication mechanism for transmitting information, and a processor PRO (or multiple processors) coupled to the bus BS for processing information. The computer system CS also comprises a main memory MM, such as a random access memory (RAM) or other dynamic storage device, coupled to the bus BS for storing information and instructions to be executed by the processor PRO. The main memory MM can also be used to store temporary variables or other intermediate information during the execution of instructions to be executed by the processor PRO. The computer system CS also comprises 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.

[0091] The computer system CS can be coupled to a display DS for displaying information to a computer user via a bus BS, 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, such as a mouse, trackball or cursor direction keys, for communicating direction information and command selections to the processor PRO and for controlling cursor movement on the display DS. This input device typically has two degrees of freedom on two axes, a first axis (e.g., x) and a second axis (e.g., y), which allow the device to specify a position in a plane. A touch panel (screen) display can also be used as an input device.

[0092] According to one embodiment, a part of one or more methods described herein can be performed by a computer system CS in response to one or more sequences of one or more instructions included in the processor PRO executing the main memory MM. These instructions can be read into the main memory MM from another computer-readable medium (such as a storage device SD). The execution of the instruction sequence included in the main memory MM causes the processor PRO to execute the process steps described herein. One or more processors in a multi-processing arrangement can also be used to execute the instruction sequence included in the main memory MM. In an alternative embodiment, a hard-wired circuit can be used instead of or in combination with a software instruction. Therefore, the description herein is not limited to any specific combination of hardware circuits and software.

[0093] The term "computer-readable medium" as used herein refers to any medium that participates in providing instructions to the processor PRO for execution. Such a medium can be in many forms, including but not limited to non-volatile media, volatile media and transmission media. Non-volatile media include, for example, optical disks or disks, such as storage devices SD. Volatile media include dynamic memory, such as main memory MM. Transmission media include coaxial cables, copper wires and optical fibers, including wires containing bus BS. Transmission media can also be in the form of sound waves or light waves, such as sound waves or light waves generated during radio frequency (RF) and infrared (IR) data communication. Computer-readable media can be non-temporary, such as floppy disks, flexible disks, hard disks, magnetic tapes, any other magnetic media, CD-ROMs, DVDs, any other optical media, punch cards, paper tapes, any other physical media with hole patterns, RAMs, PROMs and EPROMs, FLASH-EPROMs, any other memory chips or cassettes. Non-temporary computer-readable media can have instructions recorded thereon. When executed by a computer, instructions can implement any of the features described herein. Transitory computer readable media may include carrier waves or other propagated electromagnetic signals.

[0094] Various forms of computer-readable media can be involved when one or more sequences of one or more instructions are carried to the processor PRO for execution. For example, the instructions can be initially carried on the disk of the remote computer. The remote computer can load the instructions into its volatile memory and send the instructions via the telephone line using a modem. The modem local to the computer system CS can receive the data on the telephone line and use an infrared transmitter to convert the data into an infrared signal. The infrared detector coupled to the bus BS can 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, and the processor PRO obtains the instructions from the main memory MM and executes the instructions. The instructions received by the main memory MM can be optionally stored on the storage device SD before or after being executed by the processor PRO.

[0095] The computer system CS may also include a communication interface CI coupled to the bus BS. The communication interface CI provides a bidirectional data communication coupling with a network link NDL, which 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 with 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 sends and receives electrical, electromagnetic or optical signals carrying digital data streams representing various types of information.

[0096] The network link NDL typically provides data communications to other data devices via one or more networks. For example, the network link NDL can provide a connection to the host computer HC via a local area network LAN. This can include data communication services provided via the global packet data communication network (now generally referred to as the "Internet" INT). Local area networks LAN (Internet) all use electrical signals, electromagnetic signals 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 carrier waves that convey information in an exemplary form, and the signals carry digital data to and from the computer system CS.

[0097] The computer system CS can send messages and receive data (including program code) via (multiple) networks, network data links NDL and communication interfaces CI. In the example of the Internet, the host computer HC can transmit the requested program code for the application program via the Internet INT, the network data link NDL, the local area network LAN and the communication interface CI. For example, such a downloaded application program can provide all or part of the method described herein. The received program code can be executed by the processor PRO when it is received, and / or stored in the storage device SD or other non-volatile storage for later execution. In this way, the computer system CS can obtain the application code in the form of a carrier wave.

[0098] Figure 8 is a schematic diagram of a lithography projection apparatus according to an embodiment of the present disclosure.

[0099] The lithographic projection apparatus may include an illumination system IL, a first stage MT, a second stage WT and a projection system PS.

[0100] The illumination system IL may condition the radiation beam B. In such a particular case, the illumination system also comprises a radiation source SO.

[0101] A first stage (eg, patterning device table) MT may be provided with a patterning device holder for holding a patterning device MA (eg, a reticle) and connected to a first positioner for accurately positioning the patterning device relative to the article PS.

[0102] A second stage (substrate stage) WT may be provided with a substrate holder for holding a substrate W (eg, a silicon wafer coated with resist), and connected to a second positioner for accurately positioning the substrate relative to the item PS.

[0103] A projection system ("lens") PS (eg, a refractive, reflective or catadioptric optical system) may image the irradiated portion of the patterning device MA onto a target portion C of the substrate W (eg, comprising one or more dies).

[0104] As depicted herein, the device may be of the transmissive type (i.e., have a transmissive patterning device). However, in general, the device may also be of, for example, the reflective type (have a reflective patterning device). The device may employ a different kind of patterning device than a classical mask; examples include a programmable mirror array or an LCD matrix.

[0105] A source SO (e.g. a mercury lamp or an excimer laser, an LPP (laser produced plasma) EUV source) generates a radiation beam. This beam is fed into an illumination system (illuminator) IL, for example directly or after having traversed a conditioning device such as a beam expander Ex. The illuminator IL may include an adjustment device AD ​​for setting the outer radial extent and / or the inner radial extent (commonly referred to as σ-outer and σ-inner, respectively) of the intensity distribution in the beam. In addition, the illuminator IL will typically include various other components, such as an integrator IN and a condenser CO. In this way, the beam B impinging on the patterning device MA has a desired uniformity and intensity distribution in its cross section.

[0106] In some embodiments, the source SO may be within the housing of the lithographic projection device (this is often the case when the source SO is, for example, a mercury lamp), but the source SO may also be remote from the lithographic projection device, the radiation beam generated by the source SO being directed into the device (for example, with the aid of a suitable directional reflector); this latter case may be the case when the source SO is an excimer laser (for example, based on a KrF, ArF or F2 laser).

[0107] The beam PB may then intercept the patterning device MA held on the patterning device table MT. Having traversed the patterning device MA, the beam B may pass through a lens PL which focuses the beam B onto a target portion C of the substrate W. With the aid of the second positioning device (and the interferometric measurement device IF), the substrate table WT may be accurately moved, for example in order to position a different target portion C in the path of the beam PB. Similarly, the first positioning device may be used to accurately position the patterning device MA relative to the path of the beam B, for example after mechanical acquisition of the patterning device MA from a patterning device library or during scanning. Typically, movement of the stage MT, WT may be achieved with the aid 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 patterning device table MT may be connected only to the short-stroke actuator, or may be fixed.

[0108] The depicted tool can be used in two different modes: a step mode and a scan mode. In the step mode, the patterning device table MT is held substantially stationary and the entire patterning device image is projected at once (i.e. a single "flash") onto a target portion C. The substrate table WT can be shifted in the x and / or y direction so that a different target portion C can be irradiated by the beam PB.

[0109] In scan mode, essentially the same situation applies, except that a given target portion C is not exposed in a single "flash". Instead, the patterning device table MT can be moved at a speed v in a given direction (the so-called "scanning direction", e.g. the y-direction) so that the projection beam B is scanned over the patterning device image; while the substrate table WT is simultaneously moved 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 having to compromise resolution.

[0110] Fig. 9 is a schematic diagram of another lithographic projection apparatus (LPA) according to an embodiment of the present disclosure.

[0111] The LPA may comprise a source collector module SO, an illumination system (illuminator) IL configured to condition a radiation beam B (eg EUV radiation), a support structure MT, a substrate table WT and a projection system PS.

[0112] The support structure (eg, patterning device table) MT may be configured to support a patterning device (eg, mask or reticle) MA and be connected to a first positioner PM configured to accurately position the patterning device.

[0113] A substrate table (eg, wafer stage) WT may be configured to hold a substrate (eg, a resist-coated wafer) W and connected to a second positioner PW configured to accurately position the substrate.

[0114] The projection system (eg, a reflective projection system) PS may be configured to project the pattern imparted to the radiation beam B by the patterning device MA onto a target portion C of the substrate W (eg, comprising one or more dies).

[0115] As depicted here, the LPA can be of a reflective type (e.g., using a reflective patterning device). It should be noted that since most materials are absorptive in the EUV wavelength range, the patterning device can have a multilayer reflector comprising, for example, multiple overlapping layers of molybdenum and silicon. In one example, the multiple overlapping layer reflectometry instrument has forty layer pairs of molybdenum and silicon, where each layer is a quarter wavelength thick. Even smaller wavelengths can be produced using x-ray lithography. Since most materials are absorptive at EUV and x-ray wavelengths, a thin segment of patterned absorbing material on the patterning device topography (e.g., a TaN absorber on top of a multilayer reflector) defines where features will be printed (positive resist) or not (negative resist).

[0116] The illuminator IL may receive an extreme ultraviolet radiation beam from a source collector module SO. Methods for generating EUV radiation include, but are not necessarily 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 produced plasma ("LPP"), a plasma may be generated by irradiating a fuel (such as a droplet, stream, or cluster of a material having a line emitting element) with a laser beam. The source collector module SO may be a portion of an EUV radiation system that includes a laser that is used to provide a laser beam that excites the fuel. The resulting plasma emits output radiation (e.g., EUV radiation) that is collected using a radiation collector disposed 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 may be separate entities.

[0117] In these cases, the laser may not be considered to form part of the lithographic apparatus, and the radiation beam may be delivered from the laser to the source collector module by means of a beam delivery system comprising, for example, suitable directing mirrors and / or a beam expander. In other cases, for example, when the source is a discharge produced plasma EUV generator (often referred to as a DPP source), the source may be an integral part of the source collector module.

[0118] The illuminator IL may include an adjuster for adjusting the angular intensity distribution of the radiation beam. Typically, at least the outer radial extent and / or the inner radial extent (commonly referred to as σ-outer and σ-inner, respectively) of the intensity distribution in a pupil plane of the illuminator may be adjusted. In addition, the illuminator IL may include various other components, such as a faceted field mirror arrangement and a faceted pupil mirror arrangement. The illuminator may be used to adjust the radiation beam to have a desired uniformity and intensity distribution in its cross-section.

[0119] The radiation beam B may be incident on a patterning device (e.g. a mask) MA held on a support structure (e.g. a patterning device table) MT and patterned by the patterning device. After reflection from the patterning 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 a substrate W. With the aid 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 may be accurately moved, for example in order to position a different target portion C in the path of the radiation beam B. Similarly, a first positioner PM and a further position sensor PS1 may be used to accurately position the patterning device (e.g. a mask) MA relative to the path of the radiation beam B. The patterning device (e.g. a mask) MA and the substrate W may be aligned using patterning device alignment marks M1, M2 and substrate alignment marks P1, P2.

[0120] The depicted device LPA can be used in at least one of the following modes: a stepping mode, a scanning mode and a stationary mode.

[0121] In step mode, the support structure (e.g. patterning device table) MT and substrate table WT are held substantially stationary while the entire pattern imparted to the radiation beam is projected at one time (i.e. a single static exposure) onto a target portion C. Subsequently, the substrate table WT is shifted in the X and / or Y direction so that a different target portion C can be exposed.

[0122] In scan mode, the support structure (e.g. patterning device table) MT and substrate table WT are scanned synchronously (i.e. single dynamic exposure) as a pattern imparted to the radiation beam is projected onto a target portion C. The velocity and direction of the substrate table WT relative to the support structure (e.g. patterning device table) MT may be determined by the (de-)magnification and image reversal characteristics of the projection system PS.

[0123] In stationary mode, the support structure (e.g., patterning device table) MT is held substantially stationary, thereby holding the programmable patterning device, and the substrate table WT is moved or scanned, while a pattern imparted to the radiation beam is projected onto a target portion C. In such a mode, a pulsed radiation source is typically employed, and the programmable patterning device is updated as required after each movement of the substrate table WT or between consecutive radiation pulses during a scan. This mode of operation can be readily applied to maskless lithography using a programmable patterning device, such as a programmable mirror array.

[0124] Fig.10 is a detailed view of a lithographic projection apparatus according to an embodiment of the present disclosure.

[0125] As shown, the LPA 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 so that a vacuum environment can be maintained in the enclosure structure ES of the source collector module SO. A plasma source may be formed by a discharge to emit EUV radiation from a thermal plasma HP. EUV radiation may be generated by a gas or vapor (e.g., Xe gas, Li vapor, or Sn vapor), wherein the thermal plasma HP is generated to emit radiation in the EUV range of the electromagnetic spectrum. For example, the thermal plasma HP is generated by a discharge that generates at least 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.

[0126] 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 (also referred to as a contaminant barrier or fin trap in some cases) positioned 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. As known in the art, the contaminant trap or contaminant barrier CT further indicated herein includes at least a channel structure.

[0127] The collector chamber CC 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 US and a downstream radiation collector side DS. Radiation traversing the radiation collector CO may be reflected from the grating spectral filter SF to be focused in a 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 may be arranged such that the intermediate focus IF is located at or near an opening OP in the enclosing structure ES. The virtual source point IF is an image of the radiation of the emitting plasma HP.

[0128] The radiation then traverses an illumination system IL which may include a faceted field mirror arrangement FM and a faceted pupil mirror arrangement PM arranged to provide a desired angular distribution of the radiation beam B at the patterning device MA and a desired uniformity of the amplitude of the radiation at the patterning device MA. After reflection of the radiation beam B at the patterning device MA held by the support structure MT, a patterned beam PB is formed and is imaged by the projection system PS via a reflective element RE onto a substrate W held by a substrate table WT.

[0129] In general, there may be more elements than shown in the illumination optics unit IL and the projection system PS. Depending on the type of lithographic apparatus, a grating spectral filter SF may optionally be present. Furthermore, there may be more mirrors than shown in the figures, for example, there may be 1 to 6 additional reflective elements present in the projection system PS.

[0130] The collector optics CO may be a nested collector with a grazing incidence reflector GR, which is only an example of a collector (or collector reflector). The grazing incidence reflector GR is arranged axially symmetrical around the optical axis O, and this type of collector optics CO may be used in combination with a discharge produced plasma source, generally referred to as a DPP source.

[0131] Fig.11is a detailed view of a source collector module SO of a lithographic projection apparatus LPA according to an embodiment of the present disclosure.

[0132] The source collector module SO may be part of an LPA radiation system. The laser LA may be arranged to deposit laser energy into a fuel such as xenon (Xe), tin (Sn) or lithium (Li), thereby producing a highly ionized plasma HP with an electron temperature of several 10 eV. The high energy radiation produced during the deexcitation and recombination of these ions is emitted from the plasma, collected by a near normal incidence collector optical device CO, and focused onto an opening OP in the enclosure structure ES.

[0133] The concepts disclosed herein can simulate or mathematically model any general imaging system for imaging sub-wavelength features, and can be used in particular with emerging imaging technologies that can produce shorter and shorter wavelengths. Emerging technologies already in use include EUV (extreme ultraviolet), DUV lithography that can produce wavelengths of 193 nm by using ArF lasers and even 157 nm by using fluorine lasers. In addition, EUV lithography can produce wavelengths in the range of 20 nm to 50 nm by using a synchrotron or by using high energy electrons to shoot at a material (solid or plasma) in order to produce photons in this range.

[0134] The embodiments of the present disclosure may be further described through the following aspects.

[0135] 1. A method comprising:

[0136] characterizing depth variations of predicted results within features of a pattern from a lithographic simulation;

[0137] evaluating the depth variation representation; and

[0138] A pattern or gauge is selected based on the depth variation assessment.

[0139] 2. The method according to aspect 1, wherein the prediction result represents a resist profile or a resist CD; and the depth variation is characterized as a resist profile depth variation or a resist CD depth variation.

[0140] 3. The method according to aspect 1, wherein the prediction result represents an aerial image contour or an aerial image CD; and the depth change is characterized as an aerial image contour depth change or an aerial image CD depth change.

[0141] 4. The method according to aspect 1, wherein the prediction result represents an etch profile or an etch CD; and the depth variation is characterized as an etch profile depth variation or an etch CD depth variation.

[0142] 5. The method according to clause 1, wherein the evaluating is performed based on an aerial image (AI) depth sensitivity with the depth variation.

[0143] 6. A method according to clause 5, wherein the AI ​​depth sensitivity is based on the first derivative of CD as a function of depth.

[0144] 7. The method of clause 5, wherein the AI ​​depth sensitivity is based on a comparison of total CD change to total depth change.

[0145] 8. The method according to clause 5, wherein the selecting is performed based on the spatial image depth sensitivity being less than a threshold.

[0146] 9. The method of clause 8, further comprising: performing optical proximity correction (OPC) modeling using the pattern or gauge.

[0147] 10. The method according to clause 5, wherein the selecting is performed based on the spatial image depth sensitivity being less than a threshold.

[0148] 11. The method according to clause 10, further comprising: performing local OPC on the features in the pattern where the spatial image depth sensitivity is greater than the threshold to reduce depth variation of the pattern, the local OPC comprising:

[0149] detecting hot spot locations in the pattern; and

[0150] The local OPC is performed at the hot spot location.

[0151] 12. The method of clause 11, wherein the local OPC reduces a difference between a first profile of the feature at a first depth and a second profile of the feature at a second depth.

[0152] 13. The method of clause 12, wherein the difference is between a first location on the first contour and a second location on the second contour, the difference determining a sidewall angle of the feature.

[0153] 14. The method according to aspect 10, further comprising:

[0154] generating a SEM image of the pattern while excluding portions of the SEM image where the aerial image depth sensitivity is above the threshold; and

[0155] OPC model building was performed using the SEM images.

[0156] 15. The method according to aspect 10, further comprising:

[0157] generating a SEM image of the pattern wherein the aerial image depth sensitivity is above the threshold; and

[0158] Stochastic modeling was performed using the SEM images.

[0159] 16. The method of clause 10, further comprising: obtaining a SEM image of the selected pattern or gauge.

[0160] 17. The method of clause 16, wherein obtaining comprises discarding a portion of the SEM image in which the aerial image depth sensitivity is above the threshold.

[0161] 18. The method of clause 17, further comprising: performing OPC model building using the SEM image.

[0162] 19. The method of clause 16, further comprising performing stochastic modeling of the pattern based on a portion of the SEM image where the aerial image depth sensitivity is above the threshold.

[0163] 20. The method of clause 16, the evaluating further comprising calibrating a random failure model based on a portion of the SEM image.

[0164] 21. A non-transitory computer-readable medium having recorded thereon instructions that, when executed by a computer having at least one programmable processor, cause the operations of any one of aspects 1 to 20.

[0165] 22. A system comprising:

[0166] at least one programmable processor; and

[0167] A non-transitory computer-readable medium having recorded thereon instructions which, when executed by a computer having at least one programmable processor, cause the operations of any one of aspects 1 to 20.

[0168] Although the concepts disclosed herein may be used for imaging on substrates such as silicon wafers, it should be understood that the disclosed concepts may be used with any type of lithography imaging system, such as a lithography imaging system for imaging on substrates other than silicon wafers.

[0169] The combination and sub-combination of the elements disclosed herein constitute separate embodiments and are provided as examples only. In addition, the above description is intended to be illustrative, not restrictive. Therefore, it will be appreciated by those skilled in the art that modifications may 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, the instructions, when executed by a computer having at least one programmable processor, causing the processor to perform a method, the method include: characterizing depth variations of predicted results within features of a pattern from a lithographic simulation; evaluating the depth change representation; as well as A pattern or gauge is selected based on the depth variation assessment.

2. The medium according to claim 1, in, The prediction result represents a resist profile or a resist CD; and the depth variation is characterized as a resist profile depth variation or a resist CD depth variation.

3. The medium according to claim 1, in, The prediction result represents an aerial image contour or an aerial image CD; and the depth change is characterized as a depth change of the aerial image contour or a depth change of the aerial image CD.

4. The medium according to claim 1, in, The prediction result represents an etch profile or an etch CD; and the depth variation is characterized as an etch profile depth variation or an etch CD depth variation.

5. The medium according to claim 1, in, The evaluation is performed based on an aerial image (AI) depth sensitivity with the depth variation.

6. The medium according to claim 5, in, The AI ​​depth sensitivity is based on the first derivative of CD as a function of depth.

7. The medium according to claim 5, in, The AI ​​depth sensitivity is based on a comparison of the total CD change to the total depth change.

8. The medium according to claim 5, in, The selection is performed based on that the depth sensitivity of the spatial image is less than a threshold.

9. The medium according to claim 8, further comprising: include: Optical proximity correction (OPC) modeling is performed using the pattern or gauge.

10. The medium according to claim 5, further comprising: include: Performing local OPC on the features in the pattern where the spatial image depth sensitivity is greater than the threshold to reduce depth variation of the pattern, the local OPC comprising: detecting hot spot locations in the pattern; and The local OPC is performed at the hot spot location.

11. The medium according to claim 10, in, The local OPC reduces a difference between a first profile of the feature at a first depth and a second profile of the feature at a second depth.

12. The medium according to claim 5, further comprising: include: generating a SEM image of the pattern while excluding a portion of the SEM image where the aerial image depth sensitivity is above the threshold; as well as OPC model building was performed using the SEM images.

13. The medium according to claim 5, further comprising: include: generating a SEM image of the pattern wherein the aerial image depth sensitivity is above the threshold; as well as Stochastic modeling was performed using the SEM images.

14. The medium according to claim 5, further comprising: include: Obtaining an SEM image of the selected pattern or gauge; and discarding a portion of the SEM image in which the aerial image depth sensitivity is above the threshold.

15. The medium according to claim 5, further comprising: include: Obtaining an SEM image of the selected pattern or gauge; performing stochastic modeling of the pattern based on a portion of the SEM image where the aerial image depth sensitivity is above the threshold; Or the evaluating further includes: calibrating a random failure model based on a portion of the SEM image.

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