Optimization of lithography processes based on bandwidth and speckle

Abstract

A method for improving a lithography process in which a lithography apparatus is used to image a portion of a design layout onto a substrate, the method including calculating a multivariate cost function that is a function of (i) a plurality of design variables that affect a characteristic of the lithography process, and (ii) an emission bandwidth of a radiation source of the lithography apparatus, and reconfiguring one or more of the characteristics of the lithography process (e.g., EPE, image contrast, resist, etc.) by adjusting one or more of the design variables (e.g., radiation source, mask layout, bandwidth, etc.) until an end condition is met. The end condition also includes that a speckle characteristic (e.g., speckle contrast) is maintained within a speckle specification associated with the radiation source, and maintaining an image contrast associated with the lithography process within a desired range. The speckle characteristic is a function of the emission bandwidth.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Patent Application No. 63 / 129,957, filed December 23, 2020, which is incorporated herein by reference in its entirety.

[0002] The description herein relates to lithographic apparatus and processes, including methods or apparatus for optimizing an illumination source by allowing the bandwidth of the illumination source to be varied for a given patterning device. [Background technology]

[0003] Lithographic projection apparatuses may be used, for example, in the manufacture of integrated circuits (ICs). In such cases, a patterning device (e.g., a mask) may contain or be provided with a circuit pattern (a "design layout") corresponding to an individual layer of the IC, and this circuit pattern may be transferred onto a target portion (e.g., comprising one or more dies) on a substrate (e.g., a silicon wafer) that is coated with a layer of radiation-sensitive material ("resist"), by, for example, irradiating the target portion through the circuit pattern on the patterning device. Typically, a single substrate will contain several adjacent target portions (one target portion at a time), to which the circuit pattern is successively transferred by the lithographic projection apparatus. In one type of lithographic projection apparatus, the circuit pattern on the entire patterning device is transferred onto one target portion at a time; such an apparatus is commonly referred to as a stepper. In an alternative apparatus, commonly referred to as a step-and-scan apparatus, the projection beam is moved synchronously with scanning the patterning device in a given reference direction (the "scan" direction), and the substrate is moved parallel to or anti-parallel to this reference direction. Different portions of a circuit pattern on the patterning device are progressively transferred onto one target portion. Lithographic projection apparatus generally have a magnification factor M (generally <1), so that the speed F at which the substrate is moved is a factor M times the speed at which the projection beam scans the patterning device. More information on lithographic devices as described herein can be found, for example, in U.S. Pat. No. 6,046,792, incorporated herein by reference.

[0004] Before transferring the circuit pattern from the patterning device to the substrate, the substrate may undergo various procedures, such as priming, resist coating, and a soft bake. After exposure, the substrate may undergo other procedures, such as a post-exposure bake (PEB), development, a hard bake, and measurement / inspection of the transferred circuit pattern. This multitude of procedures is used as a basis for creating individual layers of a device, e.g., an IC. The substrate may then undergo various processes, such as etching, ion implantation (doping), metallization, oxidation, chemical-mechanical polishing, etc., all intended to finish off an individual layer of the device. If several layers are required for a device, the entire procedure, or a variant thereof, is repeated for each layer. Eventually, a device is present on each target portion of the substrate. These devices are then separated from each other by techniques such as dicing or sawing, so that the individual devices can be mounted on a carrier, connected to pins, etc.

[0005] As mentioned above, lithography is a central step in the fabrication of ICs, in which patterns formed on a substrate define the functional elements of the IC, such as microprocessors, memory chips, etc. Similar lithographic techniques are also used in the formation of flat panel displays, microelectromechanical systems (MEMS), and other devices.

[0006]

[0006] As semiconductor manufacturing processes continue to advance, the dimensions of functional elements have continually decreased, while the amount of functional elements, such as transistors, per device has steadily increased for decades, following a trend commonly referred to as "Moore's Law." In the current state of the art, device layers are fabricated using lithographic projection apparatus that use illumination from a deep ultraviolet illumination source to project a design layout onto a substrate, 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)).

[0007]

[0007] This process, in which features with dimensions below the classical resolution limit of the lithographic projection apparatus are printed, is commonly known as low k1 lithography, with the resolution formula CD=k1×λ / NA, where λ is the wavelength of the radiation used (currently most often 248 nm or 193 nm), NA is the numerical aperture of the projection optics in the lithographic projection apparatus, CD is the "critical dimension" (generally the smallest feature size to be printed), and k1 is an empirical resolution factor. In general, the smaller k1 is, the more difficult it is to reproduce a pattern on a substrate that closely resembles the shape and dimensions planned by the circuit designer to achieve a particular electrical functionality and performance. To overcome these difficulties, sophisticated fine-tuning steps are applied to the lithographic projection apparatus and / or the design layout. These include, for example, but are not limited to, optimization of NA and optical coherence settings, customized illumination schemes, use of phase-shifting patterning devices, optical proximity correction (OPC, sometimes also called "optical and process correction") in the design layout, or other methods commonly defined as "resolution enhancement techniques" (RET). As used herein, the term "projection optics" should be broadly interpreted to encompass various types of optical systems, including, for example, refractive optics, reflective optics, apertures, and catadioptric optics. The term "projection optics" may also include components that collectively or independently operate according to any of these design types to direct, shape, or control a projection beam of radiation. The term "projection optics" may include any optical component in a lithographic projection apparatus, regardless of where the optical component is located along the optical path of the lithographic projection apparatus. The projection optics may include optical components for shaping, conditioning, and / or projecting radiation from the source before it passes through the patterning device and / or optical components for shaping, conditioning, and / or projecting radiation after it has passed through the patterning device. The projection optics generally excludes the source and the patterning device. Summary of the Invention

[0008]

[0008] Disclosed herein is a method for improving a lithography process in which a lithography apparatus is used to image a portion of a design layout onto a substrate. The method includes calculating a multivariate cost function, the multivariate cost function being a function of (i) a plurality of design variables that affect characteristics of the lithography process and (ii) an emission bandwidth of a radiation source of the lithography apparatus, and reconstructing one or more of the characteristics of the lithography process by adjusting one or more of the design variables until an end condition is met, the end condition including a speckle characteristic being within a speckle specification associated with radiation generation by the radiation source while maintaining an image contrast associated with the lithography process within a desired range, the speckle characteristic being a function of the emission bandwidth. In one embodiment, the emission bandwidth is varied during the reconstruction.

[0009] In one embodiment, the speckle feature is a metric related to speckle caused by the mutual interference of a set of coherent wavefronts of a radiation source, the speckle being indicative of local dose variations. In one embodiment, the speckle feature is a speckle contrast associated with the radiation produced by the radiation source, the speckle contrast being reduced or minimized during reconstruction. In one embodiment, the speckle contrast associated with the radiation is characterized by contributions from both spatial and temporal coherence, and reducing the speckle contrast includes reducing the temporal coherence and / or spatial coherence. In one embodiment, the speckle contrast is

number

[0010] In an embodiment, the features related to the lithographic process include features related to one or more components of the lithographic apparatus, or features related to a process (e.g., a resist process, an etching process, etc.), for example, the features include one or more of an image contrast of an image generated during the lithographic process, a process window of the lithographic process, a radiation source feature, a performance index related to the lithographic process, or a speckle feature and a bandwidth range of the radiation source.

[0011]

[0011] According to one embodiment, a non-transitory computer-readable medium is provided for improving a lithography process in which a portion of a design layout is imaged onto a substrate using a lithography apparatus, the non-transitory computer-readable medium including instructions stored therein that, when executed by one or more processors, cause operations including steps of the methods herein. [Brief explanation of the drawings]

[0012] [Figure 1] FIG. 1 is a block diagram of various subsystems of a lithography system according to one embodiment of the present disclosure. [Figure 2]

[0013] FIG. 2 is a block diagram of a simulation model corresponding to the subsystems of FIG. 1 according to one embodiment of the present disclosure. [Figure 3A]

[0014] 1 illustrates two definitions of bandwidth, according to one embodiment of the present disclosure. [Figure 3B]

[0015] 1 is a curve showing Normalized Integrated Energy (vertical axis) as a function of wavelength (horizontal axis) according to one embodiment of the present disclosure. [Figure 4]

[0016] 10 illustrates an example of the effect of changing bandwidth, according to one embodiment of the present disclosure. [Figure 5]

[0017] 10 illustrates another example of the effect of changing bandwidth, according to one embodiment of the present disclosure. [Figure 6]

[0018] 1 is a flow diagram of a method for improving a lithography process, according to one embodiment of the present disclosure. [Figure 7]

[0019] 1 illustrates the behavior of speckle contrast and image contrast as a function of bandwidth, according to one embodiment of the present disclosure. [Figure 8A]

[0020] 1 illustrates a radiation source reconfigured for a bandwidth such as 300 fm, according to one embodiment of the present disclosure. [Figure 8B] 1 illustrates a radiation source reconfigured for a bandwidth such as 500 fm, according to one embodiment of the present disclosure. [Figure 8C] 1 illustrates a radiation source reconfigured for a bandwidth such as 1000 fm, according to one embodiment of the present disclosure. [Figure 9A]

[0021] 1 illustrates a radiation source and mask jointly optimized for a bandwidth such as 300 fm, according to one embodiment of the present disclosure. [Figure 9B] 1 illustrates a radiation source and mask jointly optimized for a bandwidth such as 600 fm, according to one embodiment of the present disclosure. [Figure 9C] 1 illustrates a radiation source and mask jointly optimized for a bandwidth such as 1000 fm, according to one embodiment of the present disclosure. [Figure 10]

[0022] 1 is a flow diagram illustrating aspects of an exemplary methodology for joint / co-optimization, according to one embodiment of the present disclosure. [Figure 11]

[0023] 10 illustrates an embodiment of a further optimization method, according to an embodiment of the present disclosure. [Figure 12A]

[0024] 1 illustrates an example flow diagram of various optimization processes according to one embodiment of the present disclosure. [Figure 12B]

[0024] An exemplary flow diagram of various optimization processes is shown, according to one embodiment of the present disclosure. [Figure 13]

[0024] An exemplary flow diagram of various optimization processes is shown, according to one embodiment of the present disclosure. [Figure 14]

[0025] FIG. 1 is a block diagram of an example computer system according to one embodiment of the present disclosure. [Figure 15]

[0026] 1 is a schematic diagram of a lithographic projection apparatus, according to one embodiment of the present disclosure; [Figure 16]

[0027] 1 is a schematic diagram of another lithographic projection apparatus, according to an embodiment of the present disclosure; [Figure 17]

[0028] FIG. 17 is a more detailed view of the device of FIG. 16, according to one embodiment of the present disclosure. [Figure 18]

[0029] FIG. 18 is a more detailed view of the source collector module SO of the apparatus of FIGS. 16 and 17, according to one embodiment of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0013]

[0030] While specific reference may be made herein to the manufacture of ICs, it should be expressly understood that the description herein has many other possible applications. For example, it may be used in the manufacture of integrated optical systems, guidance and detection patterns for magnetic domain memories, liquid crystal display panels, thin film magnetic heads, etc. Those skilled in the art will recognize that, in the context of such alternative applications, any use of the terms "reticle," "wafer," or "die" herein should be considered synonymous with the more general terms "mask," "substrate," and "target portion," respectively.

[0014]

[0031] As used herein, the terms "radiation" and "beam" are used to encompass all types of electromagnetic radiation, including ultraviolet (e.g., having wavelengths of 365, 248, 193, 157, or 126 nm) and EUV (extreme ultraviolet, e.g., having wavelengths in the range of about 5 to 100 nm).

[0015]

[0032] As used herein, the terms "optimizing" and "optimization" refer to or mean adjusting a lithographic projection apparatus, a lithographic process, etc., so that the lithographic results and / or process have more desirable characteristics, such as greater accuracy in projecting a design layout onto a substrate, a larger process window, etc. Accordingly, as used herein, the terms "optimizing" and "optimization" refer to or mean a process of identifying one or more values ​​of one or more parameters that provide an improvement, e.g., a local optimum, in at least one relevant metric, compared to an initial set of one or more values ​​for those one or more parameters. "Optimum" and other related terms should be interpreted accordingly. In one embodiment, the optimization step can be applied iteratively to provide further improvements in one or more metrics.

[0016]

[0033] Further, the lithographic projection apparatus may be of a type having two or more tables (e.g., two or more substrate tables, a substrate table and a measurement table, two or more patterning device tables, etc.). In such a "multi-stage" device, multiple tables may be used in parallel, or one or more tables may be used for exposure while preparatory steps are carried out on one or more of the other tables. A twin-stage lithographic projection apparatus is described, for example, in U.S. Patent No. 5,969,441, which is incorporated herein by reference.

[0017]

[0034] The patterning device mentioned above can include or form one or more design layouts. The design layout can be generated using a CAD (computer-aided design) program, a process often referred to as EDA (electronic design automation). Most CAD programs follow a predetermined set of design rules to generate a functional design layout / patterning device. These rules are set by process and design limitations. For example, design rules define the space tolerance between circuit devices (gates, capacitors, etc.) or interconnect lines to ensure that the circuit 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 dimensions" (CDs). A critical dimension of a circuit can be defined as the smallest width of a line or hole, or the smallest space between two lines or two holes. Thus, the CD determines the overall size and density of the designed circuit. Of course, one of the goals of integrated circuit manufacturing is to faithfully reproduce the original circuit design on a substrate (via a patterning device).

[0018]

[0035] The terms "mask" or "patterning device" as used herein may be broadly interpreted to refer to any general patterning device that can be used to impart an incoming radiation beam with a patterned cross section that corresponds to the pattern to be created in a target portion of a substrate, and the term "light valve" may also be used in this context. In addition to traditional masks (transmissive or reflective; binary, phase-shifting, hybrid, etc.), examples of other such patterning devices include: -programmable mirror arrays. An example of such a device is a matrix-addressable surface having a viscoelastic control layer and a reflective surface. The basic principle behind such an apparatus is that (for example) addressed areas of the reflective surface reflect incident radiation as diffracted radiation, while unaddressed areas reflect the incident radiation as undiffracted radiation. Using an appropriate filter, the undiffracted radiation can be filtered out of the reflected beam, leaving only the diffracted radiation behind; in this way, the beam is patterned according to the addressing pattern of the matrix-addressable surface. The required matrix addressing can be performed using appropriate electronic means. More information on such mirror arrays can be gleaned, for example, from U.S. Pat. Nos. 5,296,891 and 5,523,193, which are incorporated herein by reference. -Programmable LCD arrays. An example of such a construction is given in US Patent No. 5,229,872, which is incorporated herein by reference.

[0019]

[0036] As a brief introduction, Figure 1 shows an exemplary lithographic projection apparatus 10A. Its 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 explained above, the lithographic projection apparatus itself need not have a radiation source); illumination optics, which may include optics 14A, 16Aa, and 16Ab, that define the partial coherence (denoted by sigma) and shape the radiation from source 12A; a patterning device 14A; and transmission optics 16Ac, which projects an image of the patterning device pattern onto a substrate surface 22A. An adjustable filter or aperture 20A in a pupil plane of the projection optics can limit the range of beam angles impinging on substrate surface 22A, where the maximum possible angle is determined by the numerical aperture of the projection optics, NA = n sin(Θ max ), n is the refractive index of the medium between the last element of the projection optical system and the substrate, and Θ maxis the maximum angle of the beam exiting the projection optics that can still impinge on the substrate surface 22A. The radiation from the radiation source 12A does not necessarily have to be a single wavelength. Instead, the radiation may be a range of different wavelengths. The range of different wavelengths may be characterized by a quantity called the “imaging bandwidth,” “radiation source bandwidth,” or simply “bandwidth,” which are used interchangeably herein. A small bandwidth may reduce chromatic aberrations and associated focus errors in downstream components, including the radiation source, the patterning device, and the optics of the projection optics (e.g., optics 14A, 16Aa, and 16Ab). However, that does not necessarily lead to a rule that the bandwidth should not be increased.

[0020]

[0037] In a system optimization process, the system's figure of merit can be expressed as a cost function. The optimization process boils down to finding a set of system parameters (design variables) that optimizes (e.g., minimizes or maximizes) the cost function. The cost function may have any suitable form, depending on the optimization goal. For example, the cost function may be the weighted root mean square (RMS) of the deviations of certain system features (e.g., evaluation points) from their intended values ​​(e.g., ideal values). The cost function may be the maximum of these deviations (i.e., the worst deviation). The term "evaluation point" herein should be interpreted broadly to include any feature of the system. The design variables of the system may be limited to finite ranges and / or interdependent due to the feasibility of implementing the system. In the case of a lithographic projection apparatus, constraints are often related to physical properties and characteristics of the hardware, such as adjustment ranges, and / or patterning device manufacturability design rules, while evaluation points may include physical points on a resist image on a substrate, as well as non-physical features such as dose and focus.

[0021]

[0038] In a lithographic projection apparatus, a radiation source provides illumination (i.e., radiation) to a patterning device, and a projection optics system guides and shapes the illumination through the patterning device and onto a substrate. The term "projection optics" is broadly defined herein to include any optical component capable of modifying the wavefront of a radiation beam. For example, a projection optics system may include at least some of components 14A, 16Aa, 16Ab, and 16Ac. An aerial image (AI) is the radiation intensity distribution at substrate level. A resist layer on the substrate is exposed, and the aerial image is transferred to the resist layer as a latent "resist image" (RI) therein. The resist image (RI) can be defined as the spatial distribution of resist solubility in the resist layer. A resist model can be used to calculate the resist image from the aerial image, an example of which can be found in U.S. Patent Application Publication No. 2009-0157360, the disclosure of which is incorporated herein by reference in its entirety. The resist model is only concerned with the properties of the resist layer (e.g. the effects of chemical processes occurring during exposure, PEB and development). The optical properties of the lithographic projection apparatus (e.g. properties of the radiation source, patterning device and projection optics) determine the aerial image. Because the patterning devices used in a lithographic projection apparatus may vary, it is desirable to decouple the optical properties of the patterning device from the optical properties of the rest of the lithographic projection apparatus, which includes at least the source and projection optics.

[0022]

[0039] An exemplary flowchart for simulating lithography in a lithographic projection apparatus is shown in FIG. 2. Radiation source model 31 represents the optical characteristics of the radiation source (including radiation intensity distribution, bandwidth, and / or phase distribution). Projection optics model 32 represents the optical characteristics of the projection optics (including changes to the radiation intensity distribution and / or phase distribution caused by the projection optics). Design layout model 35 represents the optical characteristics of the design layout (which is a representation of the arrangement of features on or formed by a patterning device) (including changes to the radiation intensity distribution and / or phase distribution caused by a given design layout 33). An aerial image 36 can be simulated using design layout model 35, projection optics model 32, and design layout model 35. A resist image 38 can be simulated from aerial image 36 using resist model 37. For example, lithography simulation can predict the contour and CD of the resist image.

[0023]

[0040] More specifically, it should be noted that the radiation source model 31 may represent the optical characteristics of the radiation source, including, but not limited to, the numerical aperture setting, the illumination sigma (σ) setting, and any particular illumination geometry (e.g., an off-axis radiation source, such as an annular, quadrupole, or dipole). The projection optics model 32 may represent the optical characteristics of the projection optics, including aberrations, distortion, one or more refractive indices, one or more physical sizes, one or more physical dimensions, etc. The design layout model 35 may represent one or more physical characteristics of a physical patterning device, for example, as described in U.S. Pat. No. 7,587,704, which is incorporated by reference in its entirety. The goal of the simulation is to accurately predict, for example, edge placement, aerial image intensity gradient, and / or CD, which can then be compared to the intended design. The intended design is generally defined as a pre-OPC design layout, which may be provided in a standard digital file format, such as GDSII, OASIS, or other file format.

[0024]

[0041] From this design layout, one or more portions (these are called "clips") can be identified. In one embodiment, a set of clips representing complex patterns within the design layout is extracted (typically about 50-1000 clips, although any number of clips can be used). These patterns or clips represent small portions of the design (i.e., circuits, cells, or patterns); more specifically, clips typically represent small portions that require special attention and / or verification. That is, clips may be portions of the design layout that resemble, or have similar behavior to, portions of the design layout where one or more critical features are identified through experience (including customer-provided clips), trial and error, or by running full-chip simulations. Clips may include one or more test patterns or gauge patterns.

[0025]

[0042] The initial set of larger clips may be provided a priori by a customer based on one or more known critical feature areas in the design layout that require specific image optimization, or in another embodiment, the initial set of larger clips may be extracted from the entire design layout by using some type of automatic (such as machine vision) or manual algorithm that identifies one or more critical feature areas.

[0026]

[0043] As explained above, the bandwidth of the source does not need to be kept as small as possible for the source hardware. Bandwidth can be used as an additional design variable, which may provide further flexibility or improvement to the lithography process. The optical characteristics represented by the source model 31 may include bandwidth. An example of the effect of widening the bandwidth is discussed in relation to FIG. 5.

[0027]

[0044] Figure 3A shows two schematic definitions of bandwidth. Other definitions are possible. The first is the full-width-at-half-maximum (FWHM) bandwidth 310. The FWHM bandwidth, as the name suggests, is the width of the emission peak at half the height of the source radiation (from the source). This FWHM bandwidth 310 provides a general representation of the source radiation spectrum and its variations at half intensity, but does not characterize the spectral shape. The second is the E95 bandwidth 320. The E95 bandwidth is the spectral width that contains 95% of the integrated energy of the source radiation. The E95 bandwidth provides more information about the spectral shape and is very sensitive to small changes in the spectral background intensity. Figure 3B shows a plot of normalized integrated energy (vertical axis) as a function of wavelength (horizontal axis). The E95 bandwidth is the spectral width from 2.5% to 97.5% of the integrated energy of the source radiation.

[0028]

[0045] Bandwidth can be adjusted as another design variable for various purposes. For example, bandwidth can be adjusted to improve image quality, such as contrast (characterized by one or more metrics such as image logarithmic slope (ILS) and / or normalized image logarithmic slope (NILS), where higher ILS or NILS indicate sharper images), to increase latitude for another design variable (e.g., depth of focus, exposure latitude), to increase the size of the process window, and / or to improve critical dimension uniformity (CDU) across the substrate or local CDU on the substrate. In one embodiment, ILS or NILS is a function of image intensity at a given location in the image. For example, the slope of the image intensity can be calculated as a function of position (dI / dx), which measures the image steepness at the transition from bright to dark, and then the slope can be divided by the intensity I to calculate the image logarithmic slope. In one embodiment, the image logarithmic slope can be multiplied by a geometric characteristic of the feature (e.g., nominal linewidth) to calculate the NILS of the image. The bandwidth can be extended to a value greater than the minimum allowed by the source hardware.

[0029]

[0046] In situations where there are constraints on design variables, allowing the bandwidth to be adjusted can increase flexibility and improve the lithography process despite the constraints. For example, after a patterning device is manufactured, its design layout likely cannot be adjusted. That is, there is a constraint on the design variables that no geometric features of the patterning device are allowed to change during optimization. As used herein, the term “geometric features of the patterning device” means shape and / or size features of the design layout of the patterning device. Even if the illumination is optimized (e.g., optimized alone or jointly optimized together with the patterning device and / or projection optics) before manufacturing the patterning device without allowing the bandwidth to be adjusted, re-optimizing the illumination, projection optics, non-geometric features of the patterning device, or a combination thereof, after manufacturing the patterning device in combination with allowing the bandwidth to be changed can improve the lithography process despite the patterning device being unable to be further adjusted.

[0030]

[0047] Figure 4 shows an example of the effect of varying bandwidth. In this example, the E95 bandwidth is varied from 200 fm to 400 fm in 50 nm increments, resulting in a reduction in NILS. In this example, the dose is kept constant. The horizontal axis in Figure 4 represents the focus.

[0031]

[0048] Figure 5 shows another example of the effect of changing bandwidth. In this example, the E95 bandwidth is varied from 100 fm to 400 fm in 100 fm increments, resulting in a decrease in exposure latitude (EL%) and an increase in depth of focus (DOF). This can be useful when improved exposure latitude is not required, but a greater depth of focus is required. Increasing the bandwidth allows for a greater depth of focus at the expense of exposure latitude. This flexibility may not be possible if the bandwidth is always fixed to the minimum value that the hardware can achieve.

[0032]

[0049] Additionally, polarization also has an effect: for example, for an array of features extending in the same direction, best results can be obtained using low bandwidth (e.g., 200 fm compared to 300 fm or more) and TE polarization compared to low bandwidth (e.g., 200 fm) and XY polarization.

[0033]

[0050] Furthermore, the bandwidth limit need not be symmetric about the nominal wavelength. For example, one end of the bandwidth boundary may be further from the nominal wavelength than the other end of the boundary. Thus, the symmetry of the bandwidth limit (e.g., whether one end of the bandwidth limit is further from the nominal wavelength than the other end of the bandwidth limit) can be evaluated, i.e., varied, in the optimization.

[0034]

[0051] Furthermore, the distribution of the bandwidth may be different from, for example, a Gaussian distribution, and therefore the distribution of the bandwidth around the nominal wavelength (e.g., a change to a non-Gaussian distribution) may be evaluated or varied in the optimization.

[0035]

[0052] The size, limitation, distribution, etc. of the bandwidth can be adjusted, for example, at the radiation source (e.g., laser) by a suitable adjustment device, for example, a line narrowing module (e.g., having a movable prism) and / or a dithering device can change the size, limitation, distribution, etc. of the bandwidth.

[0036]

[0053] As chip manufacturers continue to expand the use of laser sources in lithography to the 7nm node and below, variables that were previously not critical to wafer patterning success are now having a greater impact, and solutions are needed to minimize their adverse effects. For example, excimer laser sources used to illuminate mask patterns and project mask features onto photoresist-coated wafers are now exhibiting the potential effects of a self-interference phenomenon called speckle. Speckle causes non-uniformity in local illumination, which in turn can result in uneven exposure of the photoresist and reduced pattern fidelity.

[0037]

[0054] Speckle occurs when coherent light beams interfere with each other when projected onto a spot on a surface. Within the spot, the radiation intensity varies randomly, being darkest when the contributions of the scattering points within the spot interfere destructively and brightest when they interfere constructively. These intensity variations within the spot are called speckle. In one embodiment, speckle results in local dose variations during the lithography process. Many attempts have been made to solve the speckle problem, often based on angle diversification achieved by diffusers and / or moving optical elements, or by polarization diversification.

[0038]

[0055] In some applications, speckle may affect critical dimension uniformity (CDU), for example, primarily local CDU (LCDU) (e.g., corresponding to a portion of a design layout or the field of view of an inspection tool). According to one embodiment, speckle may be reduced by expanding the emission bandwidth or the emission pulse length. In one embodiment, to obtain high image quality with reduced local CDU (LCDU) due to speckle, the emission bandwidth may be expanded in conjunction with a source and / or mask reconfiguration (e.g., by an SO or SMO process) for a given pattern. In one embodiment, reduction of speckle-induced CDU and local CDU may be achieved while maintaining imaging contrast (e.g., image contrast at a standard 300 fm bandwidth) from expanding the laser bandwidth (which reduces speckle contrast).

[0039]

[0056] Speckle reduction according to the present disclosure has several advantages. For example, extending the pulse length reduces speckle, which in turn reduces the line width roughness (LWR) of the structure. Increasing the number of independent speckle patterns for speckle reduction can be achieved by pulse stretching and / or widening the source bandwidth to help further reduce local CD variations. Widening the laser bandwidth reduces speckle. Furthermore, imaging pupil and mask OPC (SMO-OPC) optimization and source-only (SO) optimization can be performed to further determine the optimal bandwidth settings to compensate for the loss of image contrast due to bandwidth widening (e.g., bandwidths beyond the standard 300 fm bandwidth).

[0040]

[0057] FIG. 6 is a flowchart of a method 600 for improving a lithography process for imaging a portion of a design layout onto a substrate using a lithography apparatus. In one embodiment, the improvement to the lithography process may be achieved by extending the bandwidth and / or pulse duration, reducing speckle, and maintaining image quality. For example, the bandwidth may be greater than a standard 300 fm bandwidth and / or extending the pulse length (e.g., up to 430 ns) substantially greater than a standard pulse duration (e.g., 150 ns). In one embodiment, the portion of the design layout includes one or more selected from the entire design layout, a clip, a section of the design layout known to have critical features, a section of the design layout in which hot spots or warm spots have been identified, or a section of the design layout in which critical features have been identified. In one embodiment, the method 600 includes processes P602 and P604, which are discussed in further detail below.

[0041]

[0058] Process P602 includes calculating a multivariate cost function, which includes (i) calculating a cost function for multiple design variables (e.g., z1, z2, ..., z) that affect characteristics of the lithography process. N), and (ii) a multivariate cost function CF that is a function of the radiation bandwidth (BW) of the radiation source of the lithography apparatus. In one embodiment, the cost function CF can be expressed as Equation 1 or other cost function equations discussed herein. Examples of cost function calculations are described throughout this disclosure. In one embodiment, the cost function is one or more selected from edge placement error (EPE), pattern placement error (PPE), critical dimension (CD), local CD uniformity as a function of speckle features, resist contour distance, worst defect size, best focus shift, or mask rule check. In one embodiment, the cost function is a function of EPE, CD, LCDU, speckle features, resist contour distance, worst defect size, best focus shift, mask rule check, or other features related to the lithography process.

[0042]

[0059] In one embodiment, the emission bandwidth can be expressed as a design variable. In one embodiment, the emission bandwidth is characterized by a range of emission bandwidth, a function of a variable that is a function of the bandwidth, or a function of a variable that affects the bandwidth, where the variable is a function of one or more of a plurality of design variables that represent one or more aspects of the lithography process. In one embodiment, the emission bandwidth is a full width at half maximum (FWHM) bandwidth, as discussed with respect to FIGS. 3A and 3B. In one embodiment, the emission bandwidth is an E95 bandwidth, as discussed with respect to FIGS. 4 and 5. In one embodiment, the bandwidth may be greater than the standard bandwidth of 300 fm. For example, the bandwidth may be in the range of 400 fm to 1000 fm. In one embodiment, the emission bandwidth is extended to a value greater than the minimum allowed by the source hardware.

[0043]

[0060] In one embodiment, the radiation source is a component that generates radiation used in a lithographic process. In one embodiment, the radiation source is a radiation source model configured to mimic radiation used in a lithographic process.

[0044]

[0061] In one embodiment, the design variables include one or more variables related to the illumination of the lithographic apparatus (e.g., intensity, pupil shape, etc.), the geometric properties of the design layout (e.g., shape, size, etc.), the projection optics of the lithographic apparatus, the resist of the substrate (e.g., resist thickness, resist type, etc.), or an aerial or resist image associated with the lithographic process. In one embodiment, the aerial or resist image is a simulated image. Further examples of design variables are described throughout this specification. For example, design variables that may be adjusted during different processes such as SO and SMO are discussed with respect to FIGS. 10-13.

[0045]

[0062] Process P604 includes reconfiguring one or more characteristics of the lithography process by adjusting one or more of the design variables until an exit condition is met. In one embodiment, the exit condition includes the speckle characteristics being within a speckle specification associated with radiation generation by the radiation source while maintaining image quality associated with the lithography process within a desired range. The speckle characteristics are a function of radiation bandwidth. In one embodiment, the radiation bandwidth can be changed during the reconstruction. In one embodiment, the image quality can be characterized by the image contrast or normalized image logarithm slope (NILS) metric (normalized to feature size) of an image generated during the lithography process. In one embodiment, the exit condition can further include maintaining an edge placement error (EPE) associated with the pattern on the substrate within a desired EPE range. FIG. 7 illustrates an example of reducing speckle contrast while maintaining NILS within a desired range of best NILS (e.g., less than 3% of best NILS).

[0046]

[0063] In one embodiment, the termination condition includes one or more selected from, but not limited to, minimizing a cost function, maximizing a cost function, reaching a certain number of iterations, a value of the cost function reaching or exceeding a certain threshold, reaching a certain computation time, a value of the cost function reaching within an acceptable error limit, or minimizing exposure time in a lithography process.

[0047]

[0064] In one embodiment, the cost function may be minimized or maximized by a method selected from the group consisting of a Gauss-Newton algorithm, a Levenberg-Marquardt algorithm, a Broyden-Fletcher-Goldfarb-Shanno algorithm, a gradient descent algorithm, a simulated annealing algorithm, an interior point algorithm, and a genetic algorithm.

[0048]

[0065] In one embodiment, the termination includes speckle features, which may be a metric related to speckle caused by the mutual interference of a set of coherent wavefronts of a radiation source, hi one embodiment, the speckle is indicative of local dose variations.

[0049]

[0066] In one embodiment, the speckle feature may be a speckle contrast associated with radiation produced by a radiation source, and the speckle contrast is reduced or minimized during reconstruction. In one embodiment, the speckle contrast associated with the radiation is characterized by contributions from both spatial and temporal coherence, and reducing the speckle contrast comprises reducing the temporal coherence, the spatial coherence, or both.

[0050]

[0067] In one embodiment, the speckle contrast is calculated by:

number

[0051]

[0068] In the above formula, λ is the radiation source wavelength, and A beam is the source size and Ω divergence is the source emittance, TIS is the time integral squared (TIS) pulse length of the source, c is the light source, and BW is the emission bandwidth. In one embodiment, the emission bandwidth is expanded to a value greater than the minimum allowed by the source hardware.

[0052]

[0069] The reduction in speckle contrast is due to the beam size A beam and the source emittance Ω divergence This can be achieved by increasing the etendue, which is the product of the radiative and photon intensities. However, increasing the etendue requires significant redesign of the main components of the radiation source, which is a rather complex endeavor. On the other hand, it is possible to increase the spectral laser bandwidth (BW), but this has a negative impact on the image contrast. According to the present disclosure, the time integral squared (TIS) pulse length may be increased to achieve a reduction in speckle contrast.

[0053]

[0070] Based on the above formula, assuming a spatial speckle contrast of 4%, and calculating the speckle contrast using a standard bandwidth of 300 fm and an E95 of 130 ns pulse duration, the speckle contrast is about 5.75. On the other hand, using an expanded bandwidth of 600 fm and an E95 given by an extended pulse length of 430 ns, the speckle contrast is 3.6, which is a reduction in speckle contrast of about 30% compared to the standard bandwidth.

[0054]

[0071] In another example, assuming a spatial speckle contrast of 3%, and calculating the speckle contrast using a standard bandwidth of 300 fm and an E95 of 130 ns pulse duration, the speckle contrast is approximately 5.25, whereas using an E95 given a BW of 600 fm and a pulse length extension of 430 ns, the speckle contrast is 3.6, which is a reduction in speckle contrast of approximately 35%.

[0055]

[0072] Based on experimental results, comparing a baseline pulse stretcher (e.g., limited to 130 ns) with a pulse stretcher configured to extend the pulse duration up to approximately 450 ns, the results show that a pulse stretcher providing a pulse length of approximately 450 ns achieves a reduction in LWR(LCDU) of over 30%.

[0056]

[0073] In an embodiment, the characteristics of the lithography process include, but are not limited to, one or more of: an image contrast of an image produced during the lithography process; a process window of the lithography process; a performance index associated with the lithography process; and / or radiation source characteristics such as speckle characteristics and a bandwidth range of the radiation source.

[0057]

[0074] In one embodiment, reconstructing one or more features of the lithography process includes performing source optimization or source-mask optimization. For example, the reconstruction includes performing source optimization using a multivariate cost function with one or more process models associated with the lithography process to reduce speckle contrast (e.g., compared to using a standard bandwidth) while maintaining image contrast within a desired range. In another example, the reconstruction includes performing source-mask joint optimization using a multivariate cost function with one or more process models associated with the lithography process to reduce speckle contrast (e.g., compared to using a standard bandwidth) while maintaining image contrast within a desired range. Figures 10-13 provide exemplary flowcharts of SO and SMO that can be modified using the cost functions (e.g., including bandwidth) and termination conditions (e.g., speckle contrast and image contrast) discussed herein.

[0058]

[0075] In one embodiment, the reconfiguration of one or more features of the lithography process maintains image contrast associated with the design layout or portion of the design layout within a desired range (e.g., 3%, 5%, or 10%) of the best image contrast. For example, FIG. 7 shows a significant reduction in speckle contrast (e.g., greater than 30%) while maintaining image contrast loss within 3% of the best image contrast. In one embodiment, the reconfiguration of one or more features of the lithography process increases the latitude of at least one of the design variables. In one embodiment, the latitude is depth of focus or exposure latitude. In one embodiment, the reconfiguration of one or more features of the lithography process increases the size of a process window. In one embodiment, the reconfiguration of one or more features of the lithography process optimizes the radiation bandwidth of a radiation source until an exit condition is met.

[0059]

[0076] In one embodiment, the reconfiguration of one or more features of the lithography process is an iterative process, with each iteration including (i) simulating one or more process models associated with the lithography process by perturbing one or more design variables, (ii) calculating a multivariate cost function using the values ​​of the design variables and the simulation results, (iii) determining whether a termination condition is satisfied based on the multivariate cost function, and (iv) in response to the termination condition not being satisfied, performing steps (i)-(iv) by further perturbing the one or more design variables.

[0060]

[0077] In one embodiment, an optimal radiation bandwidth can be determined to improve a lithography process. For example, a method for determining the optimal radiation bandwidth may include calculating a multivariate cost function, where the multivariate cost function is a function of (i) a plurality of design variables that affect characteristics of the lithography process and (ii) the radiation bandwidth of a radiation source of the lithography apparatus. For example, calculating the multivariate cost function may be the same as process P602 discussed with respect to FIG. 6 . Furthermore, the method includes determining the optimal radiation bandwidth by adjusting one or more design variables until an end condition is met. The end condition includes speckle characteristics being within a speckle specification associated with radiation generation by the radiation source while maintaining image contrast associated with the lithography process within a desired range. The speckle characteristics are a function of the radiation bandwidth, as described above.

[0061]

[0078] As discussed herein, speckle feature is a metric related to speckle caused by the mutual interference of a set of coherent wavefronts of a radiation source, where the speckle is indicative of local dose variations. Speckle feature is the speckle contrast associated with the radiation produced by the radiation source, where the speckle contrast is reduced or minimized when determining the optimal bandwidth. Speckle contrast is calculated using the speckle contrast formula described above.

[0062]

[0079] Also, as discussed herein, the cost function may be one or more selected from edge placement error, pattern placement error, critical dimension (CD), local CD uniformity as a function of speckle features, resist contour distance, worst defect size, best focus shift, or mask rule check. In an embodiment, the termination condition may include one or more selected from minimizing a cost function, maximizing a cost function, reaching a certain number of iterations, a cost function value reaching or exceeding a certain threshold, reaching a certain computation time, a cost function value reaching within an acceptable error limit, or minimizing exposure time in the lithography process. As discussed herein, design variables include one or more variables related to illumination in the lithography apparatus, geometric properties of the design layout, projection optics in the lithography apparatus, resist on the substrate, or an aerial or resist image generated during the lithography process.

[0063]

[0080] Figure 7 shows an example relationship between speckle contrast and NILS as a function of bandwidth for feature sizes of 40 nm and 80 nm pitch. The data is generated by SMO-OPC simulated reconstructions of 40 nm line-space feature combinations for each bandwidth change. The left graph on the Y1 axis is speckle contrast versus bandwidth (X axis), and the right graph on the Y2 axis is NILS versus bandwidth (X axis). These results demonstrate that while speckle contrast is significantly reduced, NILS is maintained or lost at less than 3% of the best NILS. Furthermore, further lithography-related optimizations (e.g., illumination, resist, etc.) can be performed to improve the loss of NILS values.

[0064]

[0081] 8A, 8B, and 8C show the results of optimizing the source only for different bandwidths, according to one embodiment. In one embodiment, the source is reconfigured to expand the bandwidth while keeping the mask and NILS fixed. For example, source pupil S1 corresponds to a bandwidth of 300 fm, source pupil S2 corresponds to a bandwidth of 500 fm, and source pupil S3 corresponds to a bandwidth of 1000 fm. A comparison of source pupils S1, S2, and S3 reveals different pupil characteristics, such as shapes characterized by different intensities (e.g., represented by real numbers from 0 (darkest / black) to 1 (brightest / white)) in different parts of the pupil. For example, the bright portion of pupil S1 is different from the bright portions of pupils S2 and S3, respectively. Such pupil changes, with respect to their respective bandwidths, allow the characteristics of the lithography process to fall within a desired range. In one embodiment, this option of optimizing only the source without changing the mask layout may be desirable because changing the mask layout (e.g., during lithography manufacturing) may not be an expensive or complicated task.

[0065]

[0082] 9A, 9B, and 9C show results of source-mask joint optimization for different bandwidths, according to one embodiment. In one embodiment, the source is reconfigured to increase the bandwidth while modifying the mask layout (e.g., the distance between key features) to maintain the NILS within a desired range. In FIG. 9A, source pupil S10 and mask layout M10 with features having distance d1 correspond to a bandwidth of 300 fm. In FIG. 9B, source pupil S20 and mask layout M20 with features having distance d2 correspond to a bandwidth of 600 fm. In FIG. 9C, source pupil S30 and mask layout M30 correspond to a bandwidth of 1000 fm. In one embodiment, the distances between features in mask layouts M10, M20, and M30 may be different. For example, distances d1>d2>d3. Comparing source pupils S10, S20, and S30, the sources differ in their brighter areas, and this pupil variation, in combination with the corresponding mask layouts M10, M20, and M30, respectively, causes the lithographic process characteristics to fall within desired ranges.

[0066]

[0083] According to the present disclosure, combinations and sub-combinations of the disclosed elements constitute separate embodiments. For example, a first combination includes improving a lithography process for imaging a portion of a design layout onto a substrate using a lithography apparatus by modifying design variables to produce speckle features within speckle specifications while maintaining image contrast associated with the lithography process within a desired range. In a sub-combination, improving the lithography process may also satisfy EPE associated with the lithography process. A second combination includes reconfiguring the radiation source, the mask, or both the radiation source and the mask to satisfy one or more characteristics (e.g., EPE) of the lithography process. A third combination includes determining an optimized bandwidth by minimizing speckle and maintaining image contrast within a desired range (e.g., 3%, 5%, or 10%) of best image contrast.

[0067]

[0084] In a lithographic projection apparatus, as an example, the cost function can be expressed as:

number

[0068]

[0085] 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 distortion, image rotation, stochastic variation, throughput, local CD variation, process window, or a combination thereof. In one embodiment, the design variables (z1, z2, ..., z N ) comprises one or more selected from dose, global bias of the patterning device, and / or illumination geometry. In one embodiment, the design variables (z1, z2, ..., z N ) includes the bandwidth of the radiation source. Since it is often the resist image that determines the pattern on the substrate, the cost function may include a function that represents one or more characteristics of the resist image. For example, the f p (z1, z2, …, z N ) is simply the distance between a point in the resist image and its intended location (i.e., the edge placement error EPE p (z1, z2, …, z N)) The design variables may include any adjustable parameters such as adjustable parameters of the radiation source (e.g., bandwidth), patterning device, projection optics, dose, focus, etc.

[0069]

[0086] Lithographic apparatus may include components collectively referred to as "wavefront manipulators" that can be used to adjust the shape of the wavefront and the intensity distribution and / or phase shift of a radiation beam. In one embodiment, the lithographic apparatus may adjust the wavefront and intensity distribution anywhere along the optical path of the lithographic projection apparatus, such as in front of the patterning 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 distortions of the wavefront and intensity distribution and / or phase shift caused by, for example, temperature fluctuations of the radiation source, the patterning device, the 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 values ​​of the evaluation points and the cost function. Such changes may be simulated from a model or measured in practice.

[0070]

[0087] There may be constraints on the design variables, which means that (z1, z2, ..., z N)∈Z, where Z is the set of possible values ​​for the design variable. In one embodiment, the design variable may be bandwidth and the constraint may be a speckle feature. One possible constraint on the design variable may be imposed by a desired throughput of the lithographic projection apparatus. Without such a constraint imposed by the desired throughput, optimization may produce an unrealistic set of design variable values. For example, if dose is a design variable, without such a constraint, optimization may produce dose values ​​that make the throughput economically unfeasible. However, the usefulness of a constraint should not be interpreted as necessary. For example, throughput may be affected by pupil fill factor. Depending on the illumination design, a low pupil fill factor may waste radiation, leading to reduced throughput. Throughput may also be affected by the chemistry of the resist. A longer-lasting resist (e.g., a resist that requires a higher radiation dose to be properly exposed) will result in reduced throughput. In one embodiment, the constraint on the design variable is such that the design variable cannot have a value that changes a geometric feature of the patterning device; that is, the pattern on the patterning device remains unchanged during optimization.

[0071]

[0088] Therefore, the optimization process is performed by applying the constraints (z1, z2, ..., z N )∈Z, to find a set of values ​​of one or more design variables that optimizes the cost function, e.g.,

number

[0072]

[0089] Different subsets of design variables (e.g., one subset containing illumination features, one subset containing patterning device features, and one subset containing projection optics features) can be selectively optimized (referred to as alternative optimization) or simultaneously optimized (referred to as simultaneous optimization). Thus, when two subsets of design variables are optimized "simultaneously" or "together," it means that the design variables of the two subsets can be varied simultaneously. When two subsets of design variables are "selectively" optimized, as used herein, it means that in a first optimization, the design variables of the first subset but not the second subset can be varied, and then, in a second optimization, the design variables of the second subset but not the first subset can be varied.

[0073]

[0090] In FIG. 10 , optimization of all design variables is performed simultaneously. Such a flow is sometimes called a simultaneous flow or a joint optimization flow. Alternatively, optimization of all design variables can be performed selectively, as shown in FIG. 11 . In this flow, in each step, some design variables are fixed while others are optimized to optimize a cost function, and then in the next step, a different set of variables is fixed while others are optimized to minimize or maximize the cost function. These steps are performed selectively until convergence or a specific termination condition is met. As shown in the non-limiting flowchart example of FIG. 11 , first, a design layout (step S402) is obtained, and then a lighting optimization step is performed in step S404, in which one or more design variables of lighting (e.g., bandwidth) are optimized to minimize or maximize the cost function while other design variables are fixed (SO). Then, in the next step S406, projection optics optimization (LO) is performed, in which design variables of the projection optics are optimized to minimize or maximize a cost function while other design variables are fixed. These two steps are selectively performed until a specific termination condition is met in step S408. One or more various termination conditions can be used, such as the cost function value being equal to a threshold, exceeding a threshold, reaching a preset error limit, or reaching a preset number of iterations. Note that SO-LO-selective optimization is used as an example of a selective flow. As another example, a first illumination-patterning device joint optimization (SMO) or illumination-patterning device-projection optics joint optimization (SMLO) can be performed without allowing for bandwidth changes, followed by a second SO or illumination-projection optics joint optimization (SLO) that allows for bandwidth changes. Finally, an optimization result output is obtained in step S410, and the process stops.

[0074]

[0091] As mentioned above, the pattern selection algorithm may be integrated with joint optimization or selective optimization. For example, if selective optimization is employed, full-chip SO may be performed first to identify one or more "hot spots" and / or "warm spots," and then LO may be performed. Given the present disclosure, numerous permutations and combinations of sub-optimizations are possible to achieve the desired optimization results.

[0075]

[0092] FIG. 12A illustrates one exemplary method of optimization, in which a cost function is minimized or maximized. In step S502, initial values ​​for one or more design variables are obtained, including one or more associated adjustment ranges, if any. In step S504, a multivariable cost function is established. In step S506, the cost function is expanded within a sufficiently small neighborhood around the starting point values ​​of one or more design variables for the first iteration step (i=0). In step S508, standard multivariable optimization techniques are applied to the cost function. Note that the optimization problem may impose constraints, such as one or more adjustment ranges, during the optimization process in S508 or at a later stage in the optimization process. Step S520 shows that each iteration is performed for one or more given test patterns (also known as "gauges") of identified evaluation points selected to optimize the lithography process. In step S510, the lithography response is predicted. In step S512, the results of step S510 are compared to the desired or ideal lithographic response values ​​obtained in step S522. If a termination condition is met in step S514, i.e., if the optimization produces lithographic response values ​​that are sufficiently close to the desired values, the final values ​​of the design variables are output in step S518. The output step may also include outputting one or more other functions using the final values ​​of the design variables, such as a wavefront aberration-adjusted map at the pupil plane (or other plane), an optimized illumination map, and / or an optimized design layout. If the termination condition is not met, in step S516, the values ​​of one or more design variables are updated using the results of the ith iteration, and the process returns to step S506. The process of FIG. 12A is described in more detail below.

[0076]

[0093] In the exemplary optimization process, f p (z1, z2, …, z N ) is sufficiently smooth (e.g., the first derivative

number

number

[0077]

[0094] Here, we use the Gauss-Newton algorithm as an example. The Gauss-Newton algorithm is an iterative method that can be applied to general nonlinear multivariable optimization problems. N ) is (z 1i , z 2i , …, z Ni At the iteration where the Gauss-Newton algorithm takes a value of (z 1i , z 2i , …, z Ni ) in the neighborhood of f p (z1, z2, …, z N ) is linearized, and then CF(z1, z2, ..., z N ) gives the minimum value of (z 1i , z 2i , …, z Ni ) in the neighborhood of 1(i+1) , z 2(i+1) , …, z N(i+1) ) is calculated by the design variables (z1, z2, ..., z N ) is the (i+1)th iteration, (z 1(i+1) , z 2(i+1) , …, z N(i+1) ) values. This iteration converges (i.e., CF(z1, z2, ..., z NThis continues until either ) does not decrease any further) or a preset number of iterations is reached.

[0078]

[0095] Specifically, at the ith iteration, (z 1i , z 2i , …, z Ni ) in the vicinity of

number

[0079]

[0096] Under the approximation of Equation 3, the cost function becomes:

number

[0080]

[0097] Design variables (z1, z2, ..., z N ) is not under any constraint, then (z 1(i+1) , z 2(i+1) , …, z N(i+1) ) can be derived by solving the following N linear equations:

number

[0081]

[0098] Design variables (z1, z2, ..., z N ) is a set of J inequalities (e.g., (z1, z2, …, z N ) adjustment range)

number

number

[0082]

[0099] f p (z1, z2, …, z N Instead of minimizing the RMS of , the optimization process can minimize the magnitude of the maximum deviation (worst defect) among the evaluation points from the intended value. In this approach, the cost function can alternatively be expressed as:

number

[0083]

[0100] The cost function in Equation 5 can be approximated as follows:

number

[0084]

[0101] Minimizing the size of the worst defect is f p (z1, z2, …, z N ) can be combined with the linearization of f p (z1, z2, …, z N ) is approximated as in Equation 3. Then, the constraint on the size of the worst defect is given by the inequality E Lp ≦f p (z1, z2, …, z N )≦E Up where E Lp and E Up is f p (z1, z2, …, z N ) are two constants that define the minimum and maximum allowable deviations of the σ. Substituting Equation 3, these constraints translate to the following for p=1,...,P:

number

number

[0085]

[0102] Equation 3 is generally expressed as (z1, z2, ..., z N), so that the desired constraint E Lp ≦f p (z1, z2, …, z N )≦E Up If it is not possible to achieve this (which may be determined by some contradiction between the inequalities), then the constant E Lp and E Up can be relaxed until the constraints are achievable. This optimization process is N ), minimize the size of the worst defect in the neighborhood of i. Each step reduces the size of the worst defect incrementally, and each step is performed repeatedly until a specific termination condition is met, resulting in an optimal reduction in the size of the worst defect.

[0086]

[0103] Another way to minimize the worst defects is to use the weight w p For example, if after the iteration, the rth evaluation point has the worst defect, then w is adjusted so that higher priority is given to reducing the defect size of that evaluation point. r can be increased at the (i+1)th iteration.

[0087]

[0104] Furthermore, by introducing the Lagrange multiplier method, the cost functions of Equations 4 and 5 can be modified to achieve a compromise between optimizing the RMS defect size and optimizing the size of the worst defect, i.e.,

number

[0088]

[0105] By optimizing the lithographic projection apparatus, the process window can be widened: the larger the process window, the more flexibility there is in process and chip design. The process window can be defined, for example, as the set of focus, dose, aberration, laser bandwidth (e.g., E or (λ min - λ max), and fare specific to intensity values ​​where the resist image is within certain limits of the resist image design target. It should be noted that all methods discussed herein can also be extended to generalized process window definitions that can be established with different or additional fundamental parameters for exposure dose and defocus. These may include, but are not limited to, optical settings such as NA, sigma, aberration, polarization, or optical constants of the resist layer. For example, as mentioned above, if the process window (PW) also includes different patterning device pattern biases (mask biases), optimization includes minimizing the mask error enhancement factor (MEEF), where MEEF is defined as the ratio between the substrate edge placement error (EPE) and the induced patterning device pattern edge bias. The process window defined for focus and dose values ​​serves merely as an example in this disclosure.

[0089]

[0106] A method for maximizing the process window using, for example, dose and focus as parameters, according to one embodiment, is described below: In the first step, starting from a known condition (f, ε) in the process window, where f is the nominal focus and ε is the nominal dose, one minimizes one of the following cost functions in the neighborhood (f ± Δf, ε ± ε):

number

number

number

[0090]

[0107] If the nominal focus f0 and the nominal dose ε0 are allowed to shift, they are N ) can be optimized together. In the next step, we optimize (z1, z2, ..., z) such that the cost function is within a predetermined limit. N , f, ε) can be found, then (f0±Δf, ε0±ε) is accepted as part of the process window.

[0091]

[0108] If the focus and dose cannot be shifted, the design variables (z1, z2, ..., z N ) is optimized by fixing the focus and dose at a nominal focus f0 and a nominal dose ε0. In an alternative embodiment, the cost function is optimized by optimizing (z1, z2, ..., z) such that the cost function is within preset limits. N ) is found, then (f0±Δf, ε0±ε) is accepted as part of the process window.

[0092]

[0109] The cost function of Equation 7, Equation 7', or Equation 7'', respectively, can be minimized using the methods described above in this disclosure. If the design variables represent one or more characteristics of the projection optics, such as the Zernike coefficients, minimizing the cost function of Equation 7, Equation 7', or Equation 7'' maximizes the process window based on projection optics optimization, i.e., LO. If the design variables represent one or more characteristics of the illumination and patterning device in addition to the characteristics of the projection optics, minimizing the cost function of Equation 7, Equation 7', or Equation 7'' maximizes the process window based on SMLO, as shown in FIG. 10. If the design variables represent one or more characteristics of the radiation source and patterning device, minimizing the cost function of Equation 7, Equation 7', or Equation 7'' maximizes the process window based on SMO. The cost function of Equation 7, Equation 7', or Equation 7'' is a function of at least one f, such as those described herein, which is a function of bandwidth. p (z1, z2, …, z N ) may also be included.

[0093]

[0110] FIG. 13 illustrates one specific example of how the simultaneous SMLO process can use gradient-based optimization (e.g., a quasi-Newton or Gauss-Newton algorithm). In step S702, starting values ​​for one or more design variables are identified. An adjustment range for each variable may also be identified. In step S704, a cost function is defined using one or more design variables. In step S706, the cost function is expanded around the starting values ​​of all evaluation points in the design layout. In step S708, an appropriate optimization technique is applied to minimize or maximize the cost function. In optional step S710, a full-chip simulation is performed to cover all critical patterns in the full-chip design layout. Desired lithography response metrics (such as CD, EPE, or EPE and PPE) are obtained in step S714 and compared to predicted values ​​of these quantities in step S712. In step S716, a process window is determined. Steps S718, S720, and S722 are similar to corresponding steps S514, S516, and S518 as described with respect to Figure 12A. As previously mentioned, the final output may be, for example, a wavefront aberration map at the pupil plane that has been optimized to produce the desired imaging performance. The final output may be, for example, an optimized illumination map and / or an optimized design layout.

[0094]

[0111] Figure 12B shows the relationship between the design variables (z1, z2, ..., z N ) includes design variables that can assume only discrete values.

[0095]

[0112] The method begins by defining pixel groups for the illumination and patterning device tiles for the patterning device (step S802). Generally, pixel groups or patterning device tiles are sometimes referred to as divisions of lithography process components. In one exemplary scheme, the illumination is divided into 117 pixel groups and 94 patterning device tiles are defined for the patterning device, substantially as described above, resulting in a total of 211 divisions.

[0096]

[0113] In step S804, a lithography model is selected as the basis for a lithography simulation. The lithography simulation generates results that are used in calculating one or more lithography metrics or responses. A particular lithography metric is defined as the performance metric to be optimized (step S806). In step S808, initial (pre-optimization) conditions for the illumination and patterning device are set. The initial conditions include the initial states of the pixel groups of the illumination and the patterning device tiles of the patterning device, so as to refer to the initial illumination shape and initial patterning device pattern. The initial conditions may also include the patterning device pattern bias (sometimes referred to as mask bias), NA, and / or focus lamp range. It will be understood that although steps S802, S804, S806, and S808 are shown as sequential steps, in other embodiments, these steps may be performed in other orders.

[0097]

[0114] In step S810, the pixel groups and patterning device tiles are ranked. The pixel groups and patterning device tiles may be interleaved in the ranking. Various ranking methods may be used, including sequentially (e.g., from pixel group 1 to pixel group 117 and from patterning device tile 1 to patterning device tile 94), randomly, according to the physical location of the pixel groups and patterning device tiles (e.g., ranking pixel groups closer to the center of illumination higher), and / or according to how changing the pixel group or patterning device tile affects the performance metrics.

[0098]

[0115] Once the pixel groups and patterning device tiles have been ranked, the illumination and patterning device are adjusted to improve the performance metric (step S812). In step S812, each pixel group and patterning device tile is analyzed in rank order to determine whether a change to the pixel group or patterning device tile leads to an improvement in the performance metric. If it is determined that the performance metric is improved, the pixel group or patterning device tile is correspondingly changed, and the resulting improved performance metric and modified illumination shape or modified patterning device pattern form a baseline for comparison for subsequent analysis of lower-ranked pixel groups and patterning device tiles. In other words, the change that improves the performance metric is retained. As changes to the state of the pixel groups and patterning device tiles are made and retained, the initial illumination shape and initial patterning device pattern are correspondingly changed, resulting in modified illumination shape and modified patterning device pattern resulting from the optimization process of step S812.

[0099]

[0116] In other approaches, adjustments to patterning device polygon shapes and pairwise polling of pixel groups and / or patterning device tiles are also performed within the optimization process of S812.

[0100]

[0117] In one embodiment, the interleaved joint optimization procedure may involve changing pixel groups of illumination, and if an improvement in the performance metric is seen, the dose or intensity is increased and / or decreased in search of further improvement. In a further embodiment, the increase and / or decrease in dose or intensity may be replaced by a bias change in the patterning device pattern in order to search for further improvement in the joint optimization procedure.

[0101]

[0118] In step S814, a determination is made as to whether the performance metric has converged. The performance metric may be deemed to have converged, for example, if there is little or no improvement to the performance metric in the last few iterations of steps S810 and S812. If the performance metric has not converged, steps S810 and S812 are repeated for the next iteration, where the modified illumination shape and modified patterning device from the current iteration are used as the initial illumination shape and initial patterning device for the next iteration (step S816).

[0102]

[0119] The above optimization method can be used to increase the throughput of a lithographic projection apparatus. For example, the cost function can be a function of exposure time, f p (z1, z2, …, z N ) In one embodiment, the optimization of such a cost function is constrained or influenced by a bandwidth measure or other metric.

[0103]

[0120] 14 is a block diagram illustrating a computer system 100 that can assist in implementing the optimization methods and flows disclosed herein. The computer system 100 includes a bus 102 or other communication mechanism for communicating information and a processor 104 (or multiple processors 104 and 105) coupled with the bus 102 for processing information. The computer system 100 also includes a main memory 106, such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 102 for storing information and instructions executed by the processor 104. The main memory 106 may also be used to store temporary variables or other intermediate information during execution of instructions executed by the processor 104. The computer system 100 further includes a read-only memory (ROM) 108 or other static storage device coupled to the bus 102 for storing static information and instructions for the processor 104. A storage device 110, such as a magnetic or optical disk, is provided and coupled to the bus 102 for storing information and instructions.

[0104]

[0121] Computer system 100 may be coupled via bus 102 to a display 112, such as a cathode ray tube (CRT), flat panel, or touch panel display, for displaying information to a computer user. An input device 114, including alphanumeric and other keys, is coupled to bus 102 for communicating information and command selections to processor 104. Another type of user input device is a cursor control 116, such as a mouse, trackball, or cursor direction keys, for communicating directional information and command selections to processor 104 and for controlling cursor movement on display 112. This input device typically has two degrees of freedom, allowing the device to be positioned in two axes—a first axis (e.g., x) and a second axis (e.g., y)—within a plane. A touch panel (screen) display may also be used as an input device.

[0105]

[0122] According to some embodiments, portions of the optimization process may be performed by computer system 100 in response to processor 104 executing one or more sequences of one or more instructions contained in main memory 106. Such instructions may be read into main memory 106 from another computer-readable medium, such as storage device 110. Execution of the sequences of instructions contained in main memory 106 causes processor 104 to perform the process steps described herein. One or more processors in a multi-processing arrangement may be used to execute the sequences of instructions contained in main memory 106. In some alternative embodiments, hard-wired circuitry may be used in place of or in combination with software instructions. Thus, the description herein is not limited to any specific combination of hardware circuitry and software.

[0106]

[0123] The term "computer-readable medium," as used herein, refers to any medium that participates in providing instructions to processor 104 for execution. Such media may take many forms, including, but not limited to, non-volatile media, volatile media, and transmission media. Non-volatile media include, for example, optical or magnetic disks, such as storage device 110. Volatile media include dynamic memory, such as main memory 106. Transmission media include coaxial cables, copper wire, and fiber optics (including the wires that comprise bus 102). Transmission media may also take the form of acoustic or light waves, such as those generated during radio frequency (RF) and infrared (IR) data communications. Common forms of computer-readable media include, for example, floppy disks, flexible disks, hard disks, magnetic tape, other magnetic media, CD-ROMs, DVDs, other optical media, punch cards, paper tape, other physical media with patterns of holes, RAM, PROMs, and EPROMs, FLASH-EPROMs, other memory chips or cartridges, carrier waves, as described below, or other computer-readable media.

[0107]

[0124] Various forms of computer-readable media may be involved in carrying one or more sequences of one or more instructions to processor 104 for execution. For example, the instructions may initially reside on a magnetic disk of a remote computer. The remote computer may load the instructions into its dynamic memory and send the instructions over a telephone line using a modem. A modem local to computer system 100 may receive the data on the telephone line and use an infrared transmitter to convert the data to an infrared signal. An infrared detector coupled to bus 102 may receive the data carried in the infrared signal and place the data on bus 102. Bus 102 carries the data to main memory 106, from which processor 104 retrieves and executes the instructions. The instructions received by main memory 106 may optionally be stored on storage device 110 either before or after execution by processor 104.

[0108]

[0125] Computer system 100 may also include a communication interface 118 coupled to bus 102. The communication interface 118 provides a two-way data communication coupling to a network link 120 that is connected to a local network 122. For example, communication interface 118 may be an Integrated Services Digital Network (ISDN) card or a modem to provide a data communication connection to a corresponding type of telephone line. As another example, communication interface 118 may be a local area network (LAN) card to provide a data communication connection to a compatible LAN. A wireless link may also be implemented. In such an implementation, communication interface 118 sends and receives electrical, electromagnetic, or optical signals that carry digital data streams representing various types of information.

[0109]

[0126] Network link 120 typically provides data communication through one or more networks to other data devices. For example, network link 120 may provide a connection through local network 122 to a host computer 124 or to data equipment operated by an Internet Service Provider (ISP) 126. ISP 126 in turn provides data communication services through the world wide packet data communication network (now commonly referred to as the "Internet" 128). Local network 122 and Internet 128 both use electrical, electromagnetic, or optical signals that carry digital data streams. The signals through the various networks and on network link 120 and through communication interface 118, which carry the digital data to and from computer system 100, are exemplary forms of carrier waves transporting the information.

[0110]

[0127] Computer system 100 can send messages and receive data, including program code, through one or more networks, network link 120, and communication interface 118. In the Internet example, server 130 might send requested code for an application program through Internet 128, ISP 126, local network 122, and communication interface 118. One such downloaded application may provide, for example, lighting optimization for the embodiment. The received code may be executed by processor 104 as received and / or stored in storage device 110 or other non-volatile storage for later execution. In this manner, computer system 100 can obtain application code in the form of a carrier wave.

[0111]

[0128] 15 shows a schematic diagram of an exemplary lithographic projection apparatus, the illumination of which may be optimized using the methods described herein. The apparatus includes: an illumination system IL for conditioning a beam of radiation B. In this particular case, the illumination system also includes a radiation source SO. - a first object table (e.g., patterning device table) MT, provided with a patterning device holder for holding a patterning device MA (e.g., a reticle) and connected to a first positioner for accurately positioning the patterning device relative to the item PS. a second object table (substrate table) WT, comprising a substrate holder for holding a substrate W (e.g., a resist-coated silicon wafer) and connected to a second positioner for accurately positioning the substrate relative to the item PS; a projection system ("lens") PS (e.g., a refractive, reflective, or catadioptric system) for imaging an illuminated portion of the patterning device MA onto a target portion C (e.g., comprising one or more dies) of the substrate W.

[0112]

[0129] As here depicted, the apparatus is of a transmissive type (i.e. has a transmissive patterning device). However, in general, the apparatus may be of a reflective type (with a reflective patterning device), for example. The apparatus may employ different types of patterning device, typically a mask. Examples include a programmable mirror array or an LCD matrix.

[0113]

[0130] A source SO (e.g. a mercury lamp or excimer laser, LPP (Laser Produced Plasma) EUV source) produces a beam of radiation. This beam is fed to an illumination system (illuminator) IL, either directly or after having traversed conditioning means, such as a beam expander Ex. The illuminator IL may comprise conditioning means AD for setting the outer and / or inner radial extent (commonly referred to as σ-outer and σ-inner, respectively) of the intensity distribution of the beam. In addition, it will generally comprise 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.

[0114]

[0131] It should be noted, with regard to Figure 15, that the source SO may be located within the housing of the lithographic projection apparatus (as is 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 that it produces may be directed into the apparatus (for example by the use of appropriate directing mirrors). This latter scenario is often the case when the source SO is an excimer laser (for example based on KrF, ArF or F2 lasing).

[0115]

[0132] Subsequently, beam PB intersects the patterning device MA, which is held on a patterning device table MT. After traversing the patterning device MA, beam B passes through a lens PL, which focuses beam B onto a target portion C of the substrate W. Using the second positioning means (and interferometric measurement means IF), the substrate table WT can be precisely moved, e.g., to position a different target portion C in the path of beam PB. Similarly, the first positioning means can be used to precisely position the patterning device MA with respect to the path of beam B, e.g., after mechanical retrieval of the patterning device MA from a patterning device library, or during a scan. In general, movement of the object table MT, WT, is realized using a long-stroke module (coarse positioning) and a short-stroke module (fine positioning), which are not explicitly depicted in Figure 15. However, in the case of a stepper (as opposed to a step-and-scan tool), the patterning device table MT may be connected to a short-stroke actuator only, or may be fixed.

[0116]

[0133] The depicted tool can be used in two different modes: in step mode, the patterning device table MT remains essentially stationary and the entire patterning device image is projected onto the target portion C in one go (i.e. in a single "flash"), and the substrate table WT is then shifted in the x and / or y directions so that a different target portion C can be irradiated by the beam PB; In scan mode, essentially the same scenario applies, except that a given target portion C is not exposed in a single "flash". Instead, the patterning device table MT is movable in a given direction (the so-called "scan direction", e.g. the y direction) with a speed v, such that the projection beam B is caused to scan over the patterning device image. In parallel, the substrate table WT is simultaneously moved in the same or opposite direction with a speed V = Mv, in which M is the magnification factor 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 on resolution.

[0117]

[0134] FIG. 16 schematically depicts another exemplary lithographic projection apparatus 1000 whose illumination can be optimized using the methods described herein.

[0118]

[0135] Lithographic projection apparatus 1000 includes: - Source collector module SO an illumination system (illuminator) IL configured to condition a radiation beam B (e.g., EUV radiation); a support structure (e.g., patterning device table) MT constructed to support a patterning device (e.g., a mask or reticle) MA and connected to a first positioner PM configured to accurately position the patterning device; a substrate table (e.g., wafer table) WT constructed to hold a substrate (e.g., a resist-coated wafer) W and connected to a second positioner PW configured to accurately position the substrate; and a projection system (e.g., a reflective projection system) PS configured to project a pattern imparted to the radiation beam B by the patterning device MA onto a target portion C (e.g., comprising one or more dies) of the substrate W.

[0119]

[0136] As depicted here, the apparatus 1000 is reflective (e.g., uses a reflective patterning device). Note that because most materials are absorptive in the EUV wavelength range, the patterning device can have a multi-layer reflector including, for example, a multi-stack of molybdenum and silicon. In one example, a multi-stack reflector has 40 layer pairs of molybdenum and silicon, with each layer being a quarter wavelength thick. Even smaller wavelengths can be produced using x-ray lithography. Because most materials are absorptive at EUV and x-ray wavelengths, a thin strip of patterned absorbing material (e.g., TaN absorber on a multi-layer reflector) on the patterning device topography defines where features will or will not print (positive resist) or print (negative resist).

[0120]

[0137] Referring to FIG. 16 , the illuminator IL receives a beam of extreme ultraviolet radiation from a source collector module SO. Methods for generating EUV radiation include, but are not limited to, converting a material into a plasma state having at least one element (e.g., xenon, lithium, or tin) with one or more emission lines in the EUV range. In one such method, often referred to as laser-produced plasma (“LPP”), the plasma can be generated by irradiating a fuel, such as droplets, streams, or clusters of material having a line-emitting element, with a laser beam. The source collector module SO may be part of an EUV radiation system that includes a laser (not shown in FIG. 16 ) that provides a laser beam that excites the fuel. The resulting plasma emits output radiation (e.g., EUV radiation), which is collected using a radiation collector disposed in the source collector module. The laser and source collector module may be separate entities, for example, when a CO laser is used to provide the laser beam for fuel excitation.

[0121]

[0138] In such cases, the laser is not considered to form part of the lithographic apparatus, and the radiation beam is passed from the laser to the source collector module using a beam delivery system, for example including appropriate directing mirrors and / or beam expanders. In other cases, the source may be an integral part of the source collector module, for example when the source is a discharge produced plasma EUV generator, often referred to as a DPP source.

[0122]

[0139] The illuminator IL may include an adjuster for adjusting the angular intensity distribution of the radiation beam. Generally, at least the outer and / or 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 faceted field and pupil mirror devices. The illuminator may be used to condition the radiation beam to have a desired uniformity and intensity distribution in its cross-section.

[0123]

[0140] The radiation beam B is incident on a patterning device (e.g., mask) MA, which is held on a support structure (e.g., patterning device table) MT, and is patterned by the patterning device. After reflecting from the patterning device (e.g., 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. The substrate table WT can be accurately moved using a second positioner PW and a position sensor PS2 (e.g., an interferometric device, a linear encoder, or a capacitive sensor), for example, to position a different target portion C in the path of the radiation beam B. Similarly, the first positioner PM and another position sensor PS1 can be used to accurately position the patterning device (e.g., mask) MA with respect to the path of the radiation beam B. The patterning device (e.g., mask) MA and substrate W may be aligned using patterning device alignment marks M1, M2 and substrate alignment marks P1, P2.

[0124]

[0141] The depicted apparatus 1000 can be used in at least one of the following modes: 1. In step mode, the support structure (e.g. patterning device table) MT and the substrate table WT remain essentially stationary while an entire pattern imparted to the radiation beam is projected onto a target portion C in one go (i.e. a single static exposure), where the substrate table WT is then shifted in the X and / or Y directions so that a different target portion C can be exposed. 2. In scan mode, the support structure (e.g. patterning device table) MT and the substrate table WT are scanned synchronously (i.e. single dynamic exposure) while 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. 3. In another mode, the support structure (e.g. patterning device table) MT holds a programmable patterning device and remains essentially stationary, while the substrate table WT is moved or scanned, while a pattern imparted to the radiation beam is projected onto a target portion C. In this mode, a pulsed radiation source is generally used, and the programmable patterning device is updated as required after each movement of the substrate table WT, or between successive radiation pulses during a scan. This mode of operation is readily adaptable to maskless lithography, employing a programmable patterning device such as a programmable mirror array of the type referred to above.

[0125]

[0142] FIG. 17 shows apparatus 1000 in more detail, including 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 within an enclosure 220 of the source collector module SO. The EUV radiation-emitting plasma 210 can be formed by a discharge-produced plasma source. The EUV radiation can be generated by a gas or vapor (e.g., Xe gas, Li vapor, or Sn vapor, from which a very hot plasma 210 is created to emit radiation in the EUV range of the electromagnetic spectrum). The very hot plasma 210 is created, for example, by a discharge that produces an at least partially ionized plasma. A partial pressure of, for example, 10 Pa of Xe, Li, Sn vapor, or any other suitable gas or vapor may be required for efficient generation of radiation. In an embodiment, a plasma of excited tin (Sn) is provided to generate EUV radiation.

[0126]

[0143] Radiation emitted by the high-temperature plasma 210 passes from the source chamber 211 into the collector chamber 212 through an optional gas barrier or contaminant trap 230 (sometimes also referred to as a contaminant barrier or foil trap) located in or behind the opening of the source chamber 211. The contaminant trap 230 may include a channel structure. The contaminant trap 230 may also include a gas barrier or a combination of a gas barrier and a channel structure. The contaminant trap or contaminant barrier 230 further described herein includes at least a channel structure, as known in the art.

[0127]

[0144] The collector chamber 211 may include a radiation collector CO, which may be a so-called grazing incidence collector. The radiation collector CO has an upstream radiation collector side 251 and a downstream radiation collector side 252. Radiation traversing the collector CO may be reflected off a grating spectral filter 240 to be focused to a virtual source point IF along the optical axis indicated by the dash-dotted line "O". The virtual source point IF is commonly called the intermediate focus, and the source collector module is positioned such that the intermediate focus IF is located at or near the opening 221 of the enclosure structure 220. The virtual source point IF is an image of the radiation-emitting plasma 210.

[0128]

[0145] The radiation subsequently traverses an illumination system IL, which may include a faceted field mirror device 22 and a facetted pupil mirror device 24 arranged to provide a desired angular distribution of the radiation beam 21 at the patterning device MA, and a desired uniformity of the radiation intensity at the patterning device MA. Upon reflection of the radiation beam 21 off the patterning device MA, which is held by a support structure MT, a patterned beam 26 is formed, and the patterned beam 26 is imaged by the projection system PS via reflective elements 28, 30 onto a substrate W held by a substrate table WT.

[0129]

[0146] Generally, more elements than shown may be present in illumination optics unit IL and projection system PS. A grating spectral filter 240 may optionally be present, depending on the type of lithographic apparatus. Furthermore, more mirrors than shown in the figures may be present, for example, 1 to 6 additional reflective elements may be present in projection system PS than shown in Figure 17.

[0130]

[0147] 17 is depicted as a nested collector with grazing incidence reflectors 253, 254, and 255, just as an example of a collector (or collector mirror). The grazing incidence reflectors 253, 254, and 255 are arranged axisymmetrically about the optical axis O, and this type of collector system CO may be used in combination with a discharge produced plasma source, often referred to as a DPP source.

[0131]

[0148] Alternatively, the source collector module SO may be part of an LPP radiation system, as shown in Figure 18. A laser LA is arranged to deposit laser energy into a fuel such as xenon (Xe), tin (Sn), or lithium (Li) to create a highly ionized plasma 210 with an electron temperature of tens of eV. Energetic radiation produced during de-excitation and recombination of these ions is emitted from the plasma and collected by a near-normal incidence collector system CO and focused onto an opening 221 in an enclosure 220.

[0132]

[0149] U.S. Patent Application Publication No. 2013-0179847 is incorporated herein by reference in its entirety.

[0133]

[0150] The embodiments can be further described using the following clauses. 1. A non-transitory computer-readable medium for improving a lithography process for imaging a portion of a design layout onto a substrate using a lithography apparatus, the medium, when executed by one or more processors, calculating a multivariate cost function, the multivariate cost function being a function of (i) a plurality of design variables that affect characteristics of the lithography process, and (ii) a radiation bandwidth of a radiation source of the lithography apparatus; reconstructing one or more characteristics of the lithography process by adjusting one or more of the design variables until an exit condition is met, the exit condition including the speckle characteristics being within a speckle specification associated with radiation generation by the radiation source while maintaining an image contrast associated with the lithography process within a desired range, the speckle characteristics being a function of radiation bandwidth; A non-transitory computer-readable medium having instructions stored therein that cause operations including 2. A medium as described in clause 1, wherein the emission bandwidth changes upon reconfiguration. 3. A medium according to any one of the preceding clauses, wherein the speckle feature is a metric related to speckle caused by the mutual interference of a set of coherent wavefronts of a radiation source, the speckle being indicative of local dose variations. 4. A medium according to any one of the preceding clauses, wherein the speckle feature is a speckle contrast associated with radiation produced by a radiation source, and the speckle contrast is reduced or minimized upon reconstruction. 5. The medium of clause 4, wherein the speckle contrast associated with the radiation is characterized by contributions from both spatial coherence and temporal coherence, and reducing the speckle contrast includes reducing the temporal coherence and / or the spatial coherence. 6.Speckle contrast is

number

number

number

number

[0134]

[0151] The concepts disclosed herein can be used to simulate or mathematically model general imaging systems for imaging subwavelength features and can be particularly useful for new imaging technologies capable of producing increasingly shorter wavelengths. New technologies already in use include EUV (extreme ultraviolet), DUV lithography, which can produce wavelengths of 193 nm using ArF lasers, and even 157 nm using fluorine lasers. EUV lithography can also produce wavelengths within this range by using synchrotrons or by bombarding materials (solids or plasmas) with high-energy electrons to generate photons within the 20-5 nm range.

[0135]

[0152] Although the concepts disclosed herein may be used for imaging on substrates such as silicon wafers, it is understood that the disclosed concepts may be used in any type of lithographic imaging system (e.g., one used for imaging on substrates other than silicon wafers).

[0136]

[0153] The word "or" should not be construed as excluding any combination of the listed items, unless the context requires.

[0137]

[0154] The above description is intended to be illustrative and not limiting. Thus, it will be apparent to one skilled in the art that modifications can be made as described without departing from the scope of the claims set forth below.

Claims

1. 1. A method for improving a lithography process for imaging a portion of a design layout onto a substrate using a lithography apparatus, the method comprising: calculating, by a hardware computer system, a multivariate cost function, the multivariate cost function being a function of (i) a plurality of design variables that affect characteristics of the lithography process, and (ii) an emission bandwidth of a radiation source of the lithography apparatus; reconstructing, by the hardware computer system, one or more of the characteristics of the lithography process by adjusting one or more of the design variables until an exit condition is met, the exit condition including speckle characteristics being within a speckle specification associated with radiation generation by the radiation source while maintaining an image contrast associated with the lithography process within a desired range, the speckle characteristics being a function of the radiation bandwidth; A method comprising:

2. The method of claim 1 , wherein the emission bandwidth changes during the reconfiguration.

3. The method of claim 1 , wherein the speckle feature is a metric related to speckle caused by mutual interference of a set of coherent wavefronts of the radiation source, the speckle being indicative of local dose variations.

4. The method of claim 1 , wherein the speckle feature is a speckle contrast associated with the radiation produced by the radiation source, and the speckle contrast is reduced or minimized during reconstruction.

5. 5. The method of claim 4, wherein the speckle contrast associated with the radiation is characterized by contributions from both spatial and temporal coherence, and wherein reducing the speckle contrast comprises reducing temporal coherence and / or spatial coherence.

6. The feature is the image contrast of an image produced during the lithography process; a process window of said lithography process; Radiation source characteristics, a performance index associated with said lithography process; or Bandwidth range of the speckle features and the radiation source The method of claim 1 , comprising one or more of:

7. reconstructing the one or more of the features of the lithography process; performing a radiation source optimization using the multivariate cost function using one or more process models associated with the lithography process; or performing a source-mask co-optimization using the multivariate cost function with one or more process models associated with the lithography process; The method of claim 1 , comprising:

8. The method of claim 1 , wherein the emission bandwidth is a full width at half maximum (FWHM) bandwidth.

9. The method of claim 1 , wherein the emission bandwidth is an E95 bandwidth.

10. The method of claim 1 , wherein the emission bandwidth is expanded to a value greater than the minimum allowed by the source hardware.

11. 2. The method of claim 1, wherein reconfiguring the one or more of the features of the lithography process maintains the image contrast associated with the portion of the design layout within a desired range of best image contrast.

12. reconfiguring the one or more of the features of the lithography process increases the latitude of at least one of the design variables; and / or The method of claim 1 , wherein the latitude is depth of focus or exposure latitude.

13. The method of claim 1 , wherein reconfiguring the one or more of the features of the lithographic process optimizes the radiation bandwidth of the radiation source until the termination condition is met.

14. Reconstructing the one or more of the features of the lithography process is an iterative process, each iteration comprising: (i) simulating one or more process models associated with the lithography process by perturbing the one or more design variables; (ii) calculating the multivariable cost function using the design variable values ​​and simulation results; (iii) determining whether the termination condition is satisfied based on the multivariate cost function; (iv) in response to the termination condition not being satisfied, further perturbing the one or more design variables to perform steps (i)-(iv); The method of claim 1 , comprising:

15. 2. The method of claim 1, wherein the multivariate cost function is one or more selected from edge placement error, pattern placement error, critical dimension (CD), local CD uniformity as a function of the speckle features, resist contour distance, worst defect size, best focus shift, or mask rule check.

Images