Method for inferring local uniformity metrics

Abstract

Disclosed is a method for inferring a value of at least one local uniformity metric associated with a product structure, the method comprising: obtaining intensity data including an intensity image associated with at least one diffraction order obtained based on a measurement result of a target; obtaining at least one intensity distribution based on the intensity image; determining an intensity index based on the at least one intensity distribution, the intensity index representing a change in intensity on the at least one diffraction order or a change in an intensity difference between two complementary diffraction orders on the intensity image; and inferring the value of the at least one local uniformity metric based on the intensity index.

Description

[0001] Cross-reference to related applications

[0002] This application claims priority to European Application No. 20160404.8, filed on Mar. 2, 2020, and European Application No. 20161969.9, filed on Mar. 10, 2020, the entire contents of which are incorporated herein by reference. Field of the invention

[0003] The present invention relates to metrology equipment and methods that can be used to perform metrology when manufacturing devices by lithography techniques. The present invention also relates to such methods for monitoring local uniformity metrics during the lithography process. Background art

[0004] A lithographic apparatus is a machine that applies a desired pattern onto a substrate, typically onto a target portion of the substrate. A lithographic apparatus can be used, for example, in the manufacture of integrated circuits (ICs). In that case, a patterning device (alternatively referred to as a mask or a reticle) can be used to generate a circuit pattern to be formed on an individual layer of the IC. This pattern can be transferred onto a target portion (e.g., a portion including dies, a single die, or several dies) of a substrate (e.g., a silicon wafer). The transfer of the pattern is typically via imaging onto a layer of radiation-sensitive material (resist) provided on the substrate. Usually, a single substrate will contain a network of adjacent target portions that are patterned in sequence.

[0005] During the lithography process, measurements of the structures produced need to be made frequently, for example for process control and verification. A variety of tools are known for making these measurements, including scanning electron microscopes, which are often used to measure critical dimensions (CDs), and dedicated tools for measuring overlay (the accuracy of alignment of two layers in a device). More recently, various forms of scatterometers have been developed for use in the lithography field. These devices direct a radiation beam onto a target and measure one or more properties of the scattered radiation—such as the intensity at a single reflection angle as a function of wavelength; the intensity at one or more wavelengths as a function of the reflection angle; or the polarization as a function of the reflection angle—to obtain a diffraction “spectrum” from which the property of interest of the target can be determined.

[0006] Examples of known scatterometers include angular resolved scatterometers of the type described in US2006033921A1 and US2010201963A1. The targets used by such scatterometers are relatively large (e.g., 40 microns by 40 microns) gratings, and the measurement beam produces a spot smaller than the grating (i.e., the grating is underfilled). Examples of dark field imaging metrology can be found in international patent applications US20100328655A1 and US2011069292A1, the entire contents of which are incorporated herein by reference. Further developments of the technology have been described in published patent publications US20110027704A, US20110043791A, US2011102753A1, US20120044470A, US20120123581A, US20130258310A, US20130271740A, and WO2013178422A1. These targets can be smaller than the illumination spot and can be surrounded by product structures on the wafer. Composite grating targets can be used to measure multiple gratings in one image. The contents of all these applications are also incorporated by reference into the present invention.

[0007] Current patterning performance is driven by edge placement error (EPE). The position of the edge of a feature is determined by the feature's lateral position (overlay) and the feature's dimension (CD). Part of it is very local and random in nature; for example, depending on local overlay (LOVL) and local CD uniformity (LCDU). In addition, line edge roughness (LER) and line width roughness (LWR) can cause very local CD variations. All of these can be important contributing factors to EPE performance.

[0008] Currently, CD-SEM inspection can be used to measure these local contributions to EPE. However, this is too slow for many applications.

[0009] There is a desire to provide a faster method for monitoring EPE and the parameters of the contributing factors to EPE. SUMMARY OF THE INVENTION

[0010] In a first aspect, the present invention provides a method for inferring the value of at least one local uniformity metric associated with a product structure, the method comprising: obtaining intensity data including an intensity image associated with at least one diffraction order obtained based on a measurement result of a target; obtaining at least one intensity distribution based on the intensity image; determining an intensity index based on the at least one intensity distribution, the intensity index representing a change in intensity on the at least one diffraction order or a change in the intensity difference between two complementary diffraction orders on the intensity image; and inferring the value of the at least one local uniformity metric based on the intensity index.

[0011] In a second aspect, the present invention provides a metrology apparatus, comprising: a support for the substrate, on which at least one of the target and the product structure is provided; an optical system for measuring each target; a processor; and a computer program carrier, the computer program carrier including a computer program operable to cause the processor to control the metrology apparatus to perform the method of the first aspect.

[0012] The present invention also provides a computer program product, the computer program product including machine-readable instructions for causing a processor to perform the method of the first aspect, as well as an associated metrology apparatus, a lithography system, and a method of manufacturing a device.

[0013] Additional features and advantages of the present invention, as well as the structure and operation of various embodiments of the present invention, are described in detail below with reference to the accompanying drawings. It should be noted that the present invention is not limited to the specific embodiments described herein. Such embodiments are presented herein for illustrative purposes only. Additional embodiments will be apparent to those skilled in the art based on the teachings contained herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Embodiments of the present invention will now be described, by way of example only, with reference to the accompanying schematic drawings, in which corresponding reference numerals indicate corresponding parts, and in which;

[0015] Figure 1 depicts a lithography apparatus;

[0016] Figure 2 depicts a lithography cell or cluster in which an inspection apparatus according to the present invention can be used;

[0017] Figure 3 schematically illustrates an inspection apparatus adapted to perform angular resolved scatterometry and dark field imaging inspection methods;

[0018] Figure 4 is a flowchart depicting a method according to an embodiment of the present invention; and

[0019] Figure 5 (a) to Figure 5 (c) illustrate exemplary targets that can be used in the Figure 4 method, the exemplary targets having different degrees of non-uniformity and corresponding asymmetry histograms. DETAILED DESCRIPTION

[0020] Before describing embodiments of the present invention in detail, it is instructive to present an example environment in which embodiments of the present invention can be implemented.

[0021] Figure 1 Schematically depicts a lithographic apparatus LA. The lithographic apparatus includes: an illumination system (illuminator) IL configured to condition a radiation beam B (e.g., UV radiation or DUV radiation); a patterning device support or support structure (e.g., a mask table) MT configured to support a patterning device (e.g., a mask) MA and connected to a first positioner PM configured to accurately position the patterning device according to certain parameters; two substrate tables (e.g., wafer tables) WTa and WTb, each substrate table configured to hold a substrate (e.g., a wafer coated with resist) W and each substrate table connected to a second positioner PW configured to accurately position the substrate according to certain parameters; and a projection system (e.g., a refractive projection lens system) PS configured to project the pattern imparted to the radiation beam B by the patterning device MA onto a target portion C (e.g., including one or more dies) of the substrate W. A reference frame RF connects the various components and serves as a reference or reference object for setting and measuring the positions of the patterning device and the substrate, and the positions of features on the patterning device and the substrate.

[0022] The illumination system may include various types of optical components for guiding, shaping, or controlling the radiation, such as refractive, reflective, magnetic, electromagnetic, electrostatic, or other types of optical components, or any combination thereof.

[0023] The patterning device MT holds the patterning device in a manner that depends on the orientation of the patterning device, the design of the lithographic apparatus, and other conditions such as whether the patterning device is held in a vacuum environment. The patterning device support can take many forms; the patterning device support can ensure that the patterning device, for example, is located in a desired position relative to the projection system.

[0024] The term “patterning device” as used herein should be broadly interpreted to mean any device that can be used to impart a pattern to a cross-section of a radiation beam so as to create a pattern in a target portion of the substrate. It should be noted that, for example, if the pattern includes phase-shifting features or so-called assist features, the pattern imparted to the radiation beam may not exactly correspond to the desired pattern in the target portion of the substrate. Generally, the pattern imparted to the radiation beam will correspond to a particular functional layer in a device (such as an integrated circuit) created in the target portion.

[0025] As depicted herein, the apparatus is of the transmissive type (e.g., employing a transmissive patterning device). Alternatively, the apparatus may be of the reflective type (e.g., using a programmable mirror array of the type mentioned above, or using a reflective mask). Examples of patterning devices include masks, programmable mirror arrays, and programmable LCD (liquid crystal display) panels. Any term "reticle" or "mask" used herein may be considered synonymous with the more general term "patterning device". The term "patterning device" may also be construed to mean a device that stores pattern information in digital form for controlling such a programmable patterning device.

[0026] The term "projection system" used herein should be broadly construed to include any type of projection system, including refractive, reflective, catadioptric, magnetic, electromagnetic, and electrostatic optical systems or any combination thereof, as appropriate for the exposure radiation used or for other factors such as the use of immersion liquid or the use of a vacuum. Any term "projection lens" used herein may be considered synonymous with the more general term "projection system".

[0027] The lithographic apparatus may also be of the type in which at least a portion of the substrate is also covered by a liquid having a relatively high refractive index (e.g., water) to fill the space between the projection system and the substrate. The immersion liquid may also be applied to other spaces in the lithographic apparatus, such as the space between the mask and the projection system. As is well known in the art, immersion techniques are used to increase the numerical aperture of the projection system.

[0028] In operation, the illuminator IL receives a radiation beam from the radiation source SO. For example, when the source is an excimer laser, the source and the lithographic apparatus may be separate entities. In such a case, the source is not considered to be part of the lithographic apparatus, and the radiation beam is transmitted from the source SO to the illuminator IL by means of a beam delivery system BD including, for example, suitable directing mirrors and / or beam expanders. In other cases, for example, when the source is a mercury lamp, the source may be an integral part of the lithographic apparatus. The source SO, the illuminator IL, and the beam delivery system BD, if provided, may together be referred to as the radiation system.

[0029] The illuminator IL may include, for example, an adjuster AD for adjusting the angular intensity distribution of the radiation beam, an integrator IN, and a condenser CO. The illuminator may be used to adjust the radiation beam so as to have a desired uniformity and intensity distribution in its cross-section.

[0030] The radiation beam B is incident on the patterning device MA held on the patterning device support MT, and is patterned by the patterning device. After having traversed the patterning device (e.g., mask) MA, the radiation beam B passes through the projection system PS, which focuses the beam onto a target portion C of the substrate W. By means of the second positioner PW and the position sensor IF (e.g., an interferometric device, a linear encoder, a 2D encoder or a capacitive sensor), the substrate table WTa or WTb can be moved precisely, e.g. in order to position different target portions C in the path of the radiation beam B. Similarly, for example after the mechanical retrieval from the mask library or during a scan, the first positioner PM and another position sensor ( Figure 1 the other position sensor is not explicitly shown in) can be used to position the patterning device (e.g., reticle / mask) MA accurately relative to the path of the radiation beam B.

[0031] The patterning device (e.g., reticle / mask) MA and the substrate W can be aligned by using mask alignment marks M1, M2 and substrate alignment marks P1, P2. Although the illustrated substrate alignment marks occupy dedicated target portions, they can be located in the space between multiple target portions (which multiple target portions are referred to as scribe alignment marks). Similarly, in the case where more than one die is provided on the patterning device (e.g., mask) MA, the mask alignment marks can be located between the dies. Smaller alignment marks can also be included within the die, between device features, in which case it is desirable for the identification to be as small as possible and not to require any imaging or process conditions different from adjacent features. An alignment system for detecting the alignment marks is described further below.

[0032] The depicted apparatus can be used in various modes. In the scanning mode, while the pattern to be imparted to the radiation beam is projected onto the target portion C, the patterning device support (e.g., mask table) MT and the substrate table WT are scanned synchronously (i.e., single dynamic exposure). The speed and direction of the substrate table WT relative to the patterning device support (e.g., mask table) MT can be determined by the magnification (reduction ratio) and the image inversion characteristics of the projection system PS. In the scanning mode, the maximum size of the exposure field limits the width of the target portion (along the non-scanning direction) in a single dynamic exposure, while the length of the scanning movement determines the height of the target portion (along the scanning direction). As is known in the art, other types of lithographic apparatus and operating modes are possible. For example, the step mode is known. In so-called “maskless” lithography, a programmable patterning device is kept stationary, but has a changing pattern, and the substrate table WT is moved or scanned.

[0033] Combinations and / or variants of the usage patterns described above may also be employed, or completely different usage patterns.

[0034] The lithographic apparatus LA belongs to the so-called dual-platform type, which has two substrate tables WTa, WTb, and two stations - an exposure station EXP and a measurement station MEA - between which the substrate tables can be exchanged. When a substrate on one substrate table is being exposed at the exposure station, another substrate can be loaded onto the other substrate table at the measurement station, and various preparatory steps can be carried out. This enables a significant increase in the throughput of the apparatus. The preparatory steps may include mapping or profiling the surface height of the substrate using a level sensor LS and measuring the position of alignment marks on the substrate using an alignment sensor AS. If the position sensor IF is unable to measure the position of the substrate table while the substrate table is at the measurement station and at the exposure station, a second position sensor may be provided to enable tracking of the position of the substrate table relative to a reference frame RF at both stations. Instead of the dual-platform arrangement shown, other arrangements are known and available. For example, other lithographic apparatuses in which a substrate table and a measurement table are provided are known. These substrate tables and measurement tables are docked together when performing preparatory measurements and then separated when the substrate table undergoes exposure.

[0035] As Figure 2 shown, the lithographic apparatus LA forms part of a lithographic cell LC (sometimes also referred to as a lithocell or cluster), which also includes equipment for performing pre-exposure and post-exposure processes on a substrate. Conventionally, this equipment includes a spin coater SC for depositing a resist layer, a developer DE for developing the exposed resist, a chill plate CH, and a bake plate BK. A substrate handling device or robot RO picks up substrates from input / output ports I / O1, I / O2, moves the substrates between different process equipment, and then transfers the substrates to the feed table LB of the lithographic apparatus. These devices, often collectively referred to as a track or a coat and develop system, are under the control of a track control unit TCU, which itself is controlled by a management control system SCS that also controls the lithographic apparatus via a lithography control unit LACU. Thus, the different equipment can be operated to maximize throughput and processing efficiency.

[0036] To correctly and consistently expose the substrates exposed by the lithographic apparatus, it is necessary to inspect the exposed substrates to measure properties such as overlay errors between subsequent layers, line thickness, critical dimension (CD), etc. Therefore, a manufacturing facility equipped with a lithography cell LC also includes a metrology system MET that receives some or all of the substrates W that have been processed in the lithography cell. The metrology results are provided directly or indirectly to the supervisory control system SCS. In particular, if the inspection can be completed quickly enough such that other substrates of the same batch are still awaiting exposure, if an error is detected, the exposure of subsequent substrates can be adjusted. Additionally, substrates that have been exposed can be stripped and reworked to improve yield, or discarded, thereby avoiding further processing of substrates known to be defective. In cases where only some target portions of the substrate are defective, further exposure can be performed only on those target portions that are good.

[0037] Within the metrology system MET, inspection equipment is used to determine the properties of the substrate, and specifically, how the properties of different substrates or different layers of the same substrate vary between different layers. The inspection equipment can be integrated into the lithography apparatus LA or the lithography cell LC, or can be a separate device. To enable the fastest measurements, it is necessary for the inspection equipment to measure the properties in the exposed resist layer immediately after exposure. However, the latent image in the resist has a very low contrast - there is only a very small refractive index difference between the exposed and unexposed portions of the resist - and not all inspection equipment has sufficient sensitivity to make useful measurements of the latent image. Therefore, the measurement can be performed after the post-exposure bake step (PEB), which is typically the first step performed on the exposed substrate and increases the contrast between the exposed and unexposed portions of the resist. At this stage, the image in the resist can be referred to as a semi-latent image. It is also possible to measure the developed resist image - at this time, the exposed or unexposed portions of the resist have been removed - or to measure the developed resist image after a pattern transfer step such as etching. The latter possibility limits the possibility of reworking defective substrates but can still provide useful information.

[0038] Figure 3 (a) shows a metrology device suitable for an embodiment of the present invention. It should be noted that this is only one example of a suitable metrology device. Alternative suitable metrology devices can use EUV radiation, such as, for example, the EUV radiation disclosed in WO2017 / 186483A1. Figure 3(b) shows more details of the target structure T and the diffracted rays of the measurement radiation used to irradiate the target structure. The measurement device shown belongs to the type known as a dark-field measurement device. The measurement device can be an independent device, can be included in a lithographic apparatus LA (e.g., at a measurement station), or can be included in a lithographic cell LC. The optical axis with several branches passing through the device is indicated by the dashed line O. In such a device, light emitted by a source 11 (e.g., a xenon lamp) is guided via a beam splitter 15 to a substrate W through an optical system including lenses 12, 14, and an objective 16. These lenses are arranged in a double order of a 4F arrangement. Different lens arrangements can be used as long as they still provide an image of the substrate onto the detector while allowing access to the intermediate pupil plane for spatial frequency filtering. Thus, the angular range of the radiation incident on the substrate can be selected by defining a spatial intensity distribution in the plane presenting the spatial spectrum of the substrate plane, which is here called the (conjugate) pupil plane. Specifically, this can be done by inserting an appropriately shaped aperture plate 13 between lenses 12 and 14 in the plane of the back-projected image of the objective pupil plane. In the example shown, the aperture plate 13 has different forms labeled 13N and 13S to allow selection of different illumination modes. The illumination system in this example forms an off-axis illumination mode. In the first illumination mode, for the sake of description only, the aperture plate 13N provides off-axis (illumination) from the direction designated as "north". In the second illumination mode, the aperture plate 13S is used to provide a similar illumination, but from the opposite direction labeled "south". Other illumination modes are possible by using different apertures. The rest of the desired pupil plane is desired to be dark because any unnecessary light outside the desired illumination mode will interfere with the desired measurement signal.

[0039] As Figure 3(As shown in (b), the target structure T is placed such that the substrate W is perpendicular to the optical axis O of the objective lens 16. The substrate W can be supported by a support (not shown). Rays I of the measurement radiation incident on the target structure T at an angle deviating from the axis O generate a zero-order ray (solid line 0) and two first-order rays (the dotted line represents the +1 order and the double-dotted line represents the -1 order), hereinafter referred to as a pair of complementary diffraction orders. It should be noted that this pair of complementary diffraction orders can be any higher-order pair, for example, the +2, -2 pair, etc. and is not limited to the first-order complementary pair. It should be noted that for smaller underfilled target structures, these rays are just one of many parallel rays covering the area of the substrate including the measurement target structure T and other features. Since the holes in the plate 13 have a finite width (necessary for allowing a useful amount of light), the incident ray I will actually occupy an angular range, and the diffracted rays 0 and +1 / -1 will be slightly spread out. According to the point spread function of the smaller target, each of the orders +1 and -1 will be further spread out over an angular range rather than a single ideal ray as shown. Note that the grating pitch and the illumination angle of the target structure can be designed or adjusted such that the first-order rays entering the objective lens are nearly aligned with the central optical axis.) Figure 3 (The rays shown in FIGS. 3(a) and 3(b) are shown slightly off-axis, which is purely to enable Figure 3 (the rays shown in FIGS. 3(a) and 3(b) to be more easily distinguishable in the figure.)

[0040] (At least the 0 and +1 orders diffracted by the target structure T on the substrate W are collected by the objective lens 16 and guided back through the beam splitter 15. Returning to Figure 3 (FIG. 3(a), both the first illumination mode and the second illumination mode are illustrated by specifying diametrically opposite holes labeled North (N) and South (S). When the incident ray I of the measurement radiation comes from the north side of the optical axis, that is, when the first illumination mode is applied using the aperture plate 13N, the +1 order diffracted ray labeled +1(N) enters the objective lens 16. In contrast, when the second illumination mode is applied using the aperture plate 13S, the -1 order diffracted ray (labeled -1(S)) is the ray entering the lens 16.)

[0041] (The second beam splitter 17 divides the diffracted beam into two measurement branches. In the first measurement branch, the optical system 18 forms a diffracted spectrum (pupil plane image) of the target structure on the first sensor 19 (such as a CCD or CMOS sensor) using the zero-order and first-order diffracted beams. Each diffracted order hits a different point on the sensor so that image processing can compare and contrast multiple orders. The pupil plane image captured by the sensor 19 can be used for focusing the metrology device and / or normalizing the intensity measurements of the first-order beam. The pupil plane image can also be used for many measurement purposes such as reconstruction.)

[0042] In a second measurement branch, optical systems 20, 22 form an image of a target structure T on a sensor 23 (e.g., a CCD or CMOS sensor). In the second measurement branch, an aperture stop 21 is disposed in a plane conjugate to the pupil plane. The aperture stop 21 serves to block the zero-order diffraction beam such that the image of the target formed on the sensor 23 is formed only by the -1 or +1 first-order beams. The images captured by sensors 19 and 23 are output to a processor PU that processes the images, and the functionality of this processor PU will depend on the specific type of measurement being performed. It should be noted that the term "image" is used here in a broader sense. If only one of the -1 order and +1 order exists, the image of the grating lines will not be formed in this way.

[0043] Local random metrics or local variation metrics, such as local critical dimension uniformity (CDU), local overlay (LOVL) uniformity, and line width roughness (LWR) and / or line edge roughness (LER), are all contributing factors to the edge placement error (EPE) budget. These effects manifest as dimensional variations that are too small to be measured using relatively fast metrology tools such as scatterometers, and are thus monitored using a scanning electron microscope (SEM) or similar tools. However, SEM measurements are slow and cannot be used for wafer-by-wafer metrology in an actual high-volume manufacturing setting. Thus, there is currently no method fast enough to allow monitoring of the EPE budget variations wafer by wafer.

[0044] Multiple methods will be described that will allow measurement of one or more of these random or variation metrics faster than currently possible and fast enough to enable monitoring of the local EPE uniformity (LEPE) between wafers. In particular, methods will be described that enable these measurements to be performed using a scatterometer- or interferometer-based tool (or any other radiometric tool capable of performing radiometric measurements). Such a tool can be Figure 2 the scatterometry-based metrology device MET shown, or Figure 3 a specific metrology device or a similar device shown. Alternatively or additionally, such a tool can be, for example, Figure 1 the alignment sensor labeled AS in

[0045] The method can include performing intensity measurements on a suitable periodic target associated with the intensity of at least one (non-zero) diffraction order. Generally, the intensity is represented by an intensity image of at least one diffraction order, the image consisting of intensity values corresponding to their associated coordinates, such as pupil coordinates associated with a scatterometer. Alternatively, the coordinates are associated with angles within the angular spectrum of the radiation within the at least one diffraction order. The target can be a periodic target having a large enough pitch to be measured using a metrology tool but divided into sub-segments to simulate product feature behavior. The measurement can include overfill measurement. An intensity distribution can be determined based on the intensity measurement, the intensity distribution describing the variation of intensity on the intensity image.

[0046] In a preferred embodiment, instead of the raw intensity data, asymmetry data (e.g., intensity asymmetry data) can be used. For the raw intensity data, the intensity signal can be associated with other symmetric variations in the target (e.g., local layer thickness variations). By using the asymmetry data, these symmetric effects not associated with the uniformity parameter of interest will be substantially filtered out. The remainder of the description will describe embodiments using asymmetry data; however, they are also applicable to embodiments using raw intensity data.

[0047] Thus, an asymmetry distribution can be determined based on the asymmetry measurement, the asymmetry distribution describing the variation of asymmetry on the asymmetry image. The asymmetry image can include, for example, an image difference between a first image or first radiation measurement from a first diffraction order of a pair of complementary diffraction orders diffracted from the target and a second image or second radiation measurement image from a second diffraction order of the pair of complementary diffraction orders. For example, the asymmetry image can be the difference between a first image or +1 image from the +1 diffraction order and a second image or -1 image from the -1 diffraction order. Thus, the asymmetry distribution can be described by the intensity difference distribution on the asymmetry image.

[0048] Figure 4 is a high-level flowchart describing a method encompassing the above concepts. At step 400, a calibration step is performed to establish the correlation between one or more local change metrics within a dedicated metrology structure and a parameter of interest on the product (such as LEPE). The calibration can include performing a first calibration measurement on a calibration wafer (the calibration wafer can be an actual product wafer or a deliberately exposed calibration wafer) using a metrology tool that will be used for actual product monitoring in the next step, and performing a second calibration measurement using a verification tool (e.g., SEM or electron beam tool) capable of directly measuring the local change metric.

[0049] For example, the first calibration measurement may include an asymmetry distribution, such as a measurement of the distribution within an asymmetry image. Such an asymmetry distribution may include asymmetry as a function of target position (or detector position / pixel), or as a function of scan time (e.g., for some alignment sensors or the like that measure a signal as a function of time (rather than an image)). This description may be characterized by a single asymmetry metric, such as the width of an asymmetry histogram (or other suitable dimension) (e.g., describing the asymmetry within a single asymmetry image). Any suitable position for making the width measurement may be used (e.g., full width at half maximum FWHM, full width at one-tenth of the maximum peak FWTM, or any other position). The inventors have inferred that the width of the asymmetry histogram (or any other suitable asymmetry measure or asymmetry metric) is a suitable metric for deriving a local uniformity metric and may be associated therewith.

[0050] As already described, alignment sensors can be used to obtain asymmetry data. In the context of using alignment sensors, the determined asymmetry data can describe local alignment position differences (e.g., color to color) while scanning over a target.

[0051] For correlation, the calibration wafer may include both a target and a product structure (or a similar product structure that sufficiently mimics the product structure), the first calibration measurement is performed on the target, and the second calibration measurement is performed on the product structure / the structure of the similar product. The target may be similar to or the same as the target that will be used during actual product monitoring in the next step. This will be described in more detail below in connection with Figure 5 a more detailed description of the form of the target. Generally, the target may be a periodic target that has sufficient pitch to be measured by a scatterometer / interferometer-based tool and is divided into sub-segments by a similar product structure such that its exposure behavior mimics the exposure behavior of the product structure. In an embodiment, the sub-segments of the similar product may be made more sensitive to errors compared to the product, rather than directly mimicking the product behavior.

[0052] Any suitable calibration or correlation technique may be used to establish the relationship between the first calibration measurement and the second calibration measurement. This may include a direct correlation of the asymmetry metric with an SEM measurement (e.g., an SEM measurement of LEPE or other local uniformity parameters that contribute to LEPE), for example, by determining a suitable regression model or a similar model. Alternatively, a machine learning model may be trained based on multiple sets of measurements such that the machine learning model can infer LEPE (or other local uniformity parameters) based on future asymmetry metric measurements.

[0053] In an embodiment, the first calibration measurement can be performed using radiation having multiple measurement conditions, enabling different local uniformity metrics to be separated. For example, radiation including two or more wavelengths can enable each of two or more different uniformity metrics to be separated. This can include, for example, measuring an asymmetry histogram as a function of wavelength (or a different combination of wavelength or measurement conditions), and separately correlating each corresponding asymmetry index (or other asymmetry metric) with different SEM measurement values for different metrics (e.g., correlating a first wavelength asymmetry index with LCDU, a second wavelength asymmetry index with LOVL, etc.). In this way, two or more local uniformity metrics, such as (e.g.) LCDU, LER, LWR, LOVL, and LEPE, can be monitored separately between wafers.

[0054] At step 410, local EPE and / or one or more other local uniformity metrics can be monitored via radiation measurement using, for example, a scatterometer- or interferometer-based tool. The measurement technique can be the same as that already described for the first calibration measurement; for example, measuring one or more suitable targets divided into sub-sections to obtain an asymmetry image for each target, determining an asymmetry index for each target, and inferring EPE or other uniformity metrics based on the asymmetry index according to the calibration of the previous step. The measurement can be a multi-wavelength measurement (or, more generally, multi-measurement condition) that, if calibrated as such in the previous step, enables disentangling, i.e., decoupling, of different local uniformity measurements. As previously described, this can include determining a histogram and an asymmetry index according to the measurement conditions, and using the correlations determined in the previous step to infer the corresponding metrics.

[0055] At step 420, an action can be performed based on the inferred LEPE and / or other uniformity metrics measured in the previous step. This can include flagging the wafer for further inspection (e.g., using SEM) or even directly for rework. The error can be fed back to the scanner to determine a correction to potentially minimize the advancing error on a wafer-to-wafer basis, i.e., on an inter-wafer basis (e.g., in a feedback process control loop).

[0056] Other monitoring actions can include reticle qualification or resist qualification. For example, the reticle-exposed monitoring wafer can be used, and then the techniques described can be used to measure the reticle to infer LEPE or other parameters. This can indicate how the reticle prints and thus indicate any reticle or optical proximity correction (OPC) errors.

[0057] Figure 5Illustrated are example targets available in the methods described herein, and corresponding exemplary asymmetry histograms / metrics for different error levels. Figure 5 (a) Illustrates an exemplary perfect target without any local edge placement non-uniformity (e.g., all elements of the target are formed to have uniform dimensions, shapes, and positions). The target is a periodic target with a pitch P1, where the pitch P1 should be large enough to be readable by a metrology device for monitoring (e.g., at step 410). For example, P1 can be greater than 100 nm, greater than 300 nm, or greater than 500 nm. The example shown is a line-space target that is subdivided or divided into sub-sections, but any periodic target arrangement that is divided into sub-sections can be used (e.g., the space regions do not need to be empty, but can be filled with different (significantly different, i.e., highly contrasting) single or multiple periodic structures). The target shown has a periodic array in one direction, but targets can be set in two directions of the substrate plane (e.g., setting for different errors may better correlate with asymmetries in the other direction).

[0058] Subdivided or divided into sub-sections refers to dividing or splitting each line (or if the target includes alternating first and second sets of contrast regions of periodic features, then subdivided or divided into sub-sections refers to each region of a set of periodic features). The sub-sections can have a second periodic pitch P2, and the second periodic pitch P2 matches or is similar to the product pitch (e.g., in the case where the product is assumed to be periodic, the pitch of the product). Each sub-section feature SF can also be similar or identical to the corresponding product feature. For example, the target illustrated here may be suitable for monitoring a product including an array of contact holes, where each sub-section feature SF includes a circle with a size similar (or smaller) to each contact hole of the array. In this way, each of these sub-section features SF should behave in a manner similar to the product structure. Thus, if the product includes a periodic line-space structure, the sub-sections can include line-space sub-sections of similar size; and so on.

[0059] In an embodiment, instead of having sub-section features SF with substantially the same or similar dimensions and shapes to closely mimic product behavior, the sub-section features can be made more sensitive than the product on purpose, for example, by shifting them away from the center of their corresponding process window. This can be achieved, for example, by forming the sub-section features SF to be smaller than the equivalent product structure in the associated dimension. For the example here, this can be achieved by forming sub-section features SF with a smaller diameter compared to the contact holes of the product. Note that the dashed lines are not part of the target design, but are references to the centers of the sub-section features SF in the direction of periodicity.

[0060] Figure 5(a) The right side of the target in (a) is an asymmetry histogram (the relationship between the asymmetry on the x-axis and the count on the y-axis), which describes the change in asymmetry on the target (or its asymmetry image, e.g., the asymmetry image per pixel). For this perfect target, there is no local EPE non-uniformity, and thus the histogram is a single spike, indicating that all asymmetry values on the asymmetry image are substantially the same. Therefore, the asymmetry metric value (if using the width of the histogram) will be zero or very small. For this target, the spike is at zero asymmetry, which indicates a completely symmetric target, but a perfect target (in the context of the present disclosure) may be asymmetric and have no local EPE non-uniformity (e.g., the histogram may still include a zero-width spike but at a non-zero asymmetry value).

[0061] Figure 5 (b) shows the same target in a more realistic real-world example, where there is some local EPE non-uniformity, but this is to an extent within an acceptable process margin or process window. For example, it can be seen that five sub-segment features SF (those including the white dots) are formed off-center (as highlighted by the reference dashed lines). This will result in increased local EPE non-uniformity, which is manifested as an increased width of the asymmetry histogram on the right side of the figure.

[0062] Figure 5 (c) shows the same target with EPE controlled to a very poor extent (e.g., at a level of a die that would be unacceptable in a manufacturing environment and is unlikely to yield a good rate). Many sub-segment features SF (again, those including the white dots) are formed with non-uniformity in terms of size and position, with a pair of contacting sub-segment features. The histogram of this example is wider than that of Figure 5 (b). Thus, it can be understood that the width of such a histogram can indicate local non-uniformity and is used as an indicator thereof. Note that in this example, two (or more) wavelengths can be used to separate / de-couple and separately monitor different contributing factors for the EPE budget (e.g., the relationship between position and diameter), where the histogram is determined for each wavelength. This assumes that separate calibration for each wavelength has been completed.

[0063] Additional embodiments are disclosed in the list of numbered aspects below:

[0064] 1. A method for inferring a value of at least one local uniformity metric associated with a product structure, the method comprising:

[0065] Obtaining intensity data associated with a measurement of a target and describing at least one intensity distribution for each target position of the target;

[0066] Determine at least one intensity metric based on the at least one intensity distribution; and

[0067] Infer the value of the at least one local uniformity metric based on the at least one intensity metric.

[0068] 2. The method according to aspect 1, wherein the target includes a main pitch large enough to be measured by a scatterometer or interferometer-based metrology tool.

[0069] 3. The method according to aspect 2, wherein the main pitch is greater than 300 nm.

[0070] 4. The method according to any of the foregoing aspects, wherein the target is divided into sub-segments, and each sub-segment has the same, similar, and / or smaller size compared to the product structure or an element of the product structure.

[0071] 5. The method according to aspect 4, wherein the pitch of the sub-segments is similar to the pitch of the product structure or an element of the product structure.

[0072] 6. The method according to aspect 4 or 5, wherein each sub-segment has a shape similar to or the same as the product structure or an element of the product structure.

[0073] 7. The method according to any one of aspects 4 to 6, wherein each sub-segment has at least one dimension smaller than the product structure or an element of the product structure to increase sensitivity to process variations compared to the product structure.

[0074] 8. The method according to any of the foregoing aspects, wherein the method includes measuring the target to obtain the intensity data.

[0075] 9. The method according to aspect 8, wherein the measurement is performed using an alignment sensor or a post-exposure metrology tool.

[0076] 10. The method according to any of the foregoing aspects, wherein the intensity metric includes a measurement of intensity variation or asymmetry variation within the intensity data.

[0077] 11. The method according to aspect 10, wherein the intensity metric includes the width of a histogram of the intensity data.

[0078] 12. The method according to any of the foregoing aspects, wherein the intensity data includes asymmetry data, each of the at least one intensity distribution includes an asymmetry distribution, and the intensity metric includes an asymmetry metric.

[0079] 13. The method according to aspect 12, wherein the asymmetry data includes a per-target position difference of intensities of a pair of complementary higher diffraction orders from diffraction of the measurement radiation after measurement of the target.

[0080] 14. The method according to aspect 12, wherein the asymmetry data includes a local alignment position difference between different measurement settings while scanning the target.

[0081] 15. The method according to any of the preceding aspects, wherein the intensity data relates to a plurality of different measurement conditions, and the method includes: determining an intensity index for each measurement condition according to the intensity distribution of each measurement condition; and determining values of different local uniformity metrics respectively according to each of the intensity indices.

[0082] 16. The method according to aspect 15, wherein each measurement condition relates to a different wavelength or combination of wavelengths.

[0083] 17. The method according to any of the preceding aspects, wherein the method includes an initial calibration step for calibrating each intensity index among the at least one intensity index to a corresponding one of the at least one local uniformity metric.

[0084] 18. The method according to aspect 17, wherein the calibration step includes: calibrating first calibration data measured from a target using a metrology tool of a type similar to or the same as the metrology tool used to obtain the intensity data to second calibration data including a direct measurement result of the at least one local uniformity metric.

[0085] 19. The method according to any of the preceding aspects, wherein the at least one local uniformity metric includes one or more of local overlap uniformity, local edge placement error uniformity, line width roughness, line edge roughness, and local critical dimension uniformity.

[0086] 20. The method according to any of the preceding aspects, including making a decision on further inspection or rework based on the inferred value.

[0087] 21. The method according to any of the preceding aspects, including performing steps for inferring values of the at least one local uniformity metric during a manufacturing process of manufacturing an integrated circuit.

[0088] 22. The method according to aspect 21, wherein the method is performed on at least one substrate per batch.

[0089] 23. The method according to aspect 21 or 22, wherein the method is performed on a plurality of substrates per batch.

[0090] 24. A computer program comprising processor-readable instructions which, when run on a suitably processor-controlled device, cause the processor-controlled device to perform the method according to any one of the preceding aspects.

[0091] 25. A computer program carrier comprising the computer program according to aspect 24.

[0092] 26. A metrology device comprising:

[0093] a support for the substrate having at least one of the target and the product structure thereon;

[0094] an optical system for measuring each target;

[0095] a processor; and

[0096] the computer program carrier according to aspect 25, enabling the processor to control the metrology device to perform the method according to any one of aspects 1 to 23.

[0097] 27. A method of inferring a value of at least one local uniformity metric associated with a product structure, the method comprising: obtaining intensity data including an intensity image associated with at least one diffraction order obtained from a measurement result regarding a target; obtaining at least one intensity distribution from the intensity image; determining an intensity metric from the at least one intensity distribution, the intensity metric representing a change in intensity on the at least one diffraction order, or a change in the intensity difference between two complementary diffraction orders on the intensity image; and inferring the value of the at least one local uniformity metric from the intensity metric.

[0098] 28. The method according to aspect 27, wherein the target includes a main pitch large enough to be measured by a scatterometer- or interferometer-based metrology tool.

[0099] 29. The method according to aspect 27 or 28, wherein the target is divided into sub-segments, and each sub-segment has a size that is the same, similar, and / or smaller compared to the product structure or an element of the product structure.

[0100] 30. The method according to aspect 29, wherein each sub-segment has a shape similar or identical to the product structure or an element of the product structure.

[0101] 31. The method according to aspect 29 or 30, wherein each sub-segment has at least one dimension smaller compared to the product structure or an element of the product structure to increase sensitivity to process variations compared to the product structure.

[0102] 32. The method according to any one of aspects 27 to 31, wherein the method includes measuring the target to obtain the intensity data.

[0103] 33. The method according to any one of aspects 27 to 32, wherein the intensity data includes at least two diffraction orders, and the intensity metric includes a measurement of a change in intensity or a change in asymmetry within the intensity data.

[0104] 34. The method according to any one of aspects 27 to 33, wherein the intensity metric includes the width of a histogram of the intensity data.

[0105] 35. The method according to any one of aspects 27 to 34, wherein the intensity data includes asymmetry data, each of the at least one intensity distribution includes an asymmetry distribution, and the intensity metric includes an asymmetry metric.

[0106] 36. The method according to aspect 35, wherein the asymmetry data includes a per-target-position difference in intensity of a pair of complementary higher diffraction orders of diffraction of the measurement radiation after measurement of the target.

[0107] 37. The method according to any one of aspects 27 to 36, wherein the intensity data relates to a plurality of different measurement conditions, and the method includes: determining an intensity metric for each measurement condition based on the intensity distribution for each measurement condition; and determining a value of a different local uniformity metric based on each of the intensity metrics, respectively.

[0108] 38. The method according to aspect 37, wherein each measurement condition relates to a different wavelength or combination of wavelengths.

[0109] 39. The method according to any one of aspects 27 to 36, wherein the method includes an initial calibration step for calibrating each intensity metric of the at least one intensity metric to a corresponding one of the at least one local uniformity metric.

[0110] 40. The method according to aspect 39, wherein the calibration step includes: calibrating first calibration data measured from a target using a metrology tool of a similar or same type as the metrology tool used to obtain the intensity data to second calibration data including a direct measurement result of the at least one local uniformity metric.

[0111] 41. A computer program product comprising machine-readable instructions configured to infer a value of at least one local uniformity metric associated with a product structure, the instructions being configured to: obtain intensity data including an intensity image associated with at least one diffraction order obtained based on measurements of a target; obtain at least one intensity distribution based on the intensity image; determine an intensity index based on the at least one intensity distribution, the intensity index representing a variation of intensity on the at least one diffraction order or a variation of an intensity difference between two complementary diffraction orders on the intensity image; and infer the value of the at least one local uniformity metric based on the intensity index.

[0112] As used herein, the terms “radiation” and “beam” encompass all types of electromagnetic radiation, including ultraviolet (UV) radiation (e.g., having a wavelength of or about 365 nm, 355 nm, 248 nm, 193 nm, 157 nm, or 126 nm) and extreme ultraviolet (EUV) radiation (e.g., having a wavelength in the range of 5 nm to 20 nm), as well as particle beams, such as ion beams or electron beams.

[0113] The term “lens” may refer to any one or combination of various types of optical components, including refractive, reflective, magnetic, electromagnetic, and electrostatic optical components, when the context permits.

[0114] The term “target” should not be construed to refer only to a dedicated target formed for a specific purpose of measurement. The term “target” should be construed to cover other structures, including product structures having characteristics suitable for measurement applications.

[0115] The foregoing description of the specific embodiments will so fully disclose the general nature of the invention that others can, by applying knowledge within the scope of the art, readily modify and / or adapt such specific embodiments for various applications without undue experimentation, without departing from the general concept of the invention. Therefore, based on the teachings and guidance given herein, these changes and modifications are intended to fall within the meaning and scope of the equivalents of the disclosed embodiments. It should be understood, for example, that the words or terms herein are for the purpose of description and not of limitation, such that the terminology or wording of this specification should be interpreted by those skilled in the relevant art in light of the teachings and guidance herein.

[0116] The breadth and scope of the present invention should not be limited by any of the above exemplary embodiments, but should be defined only in accordance with the appended claims and their equivalents in terms of aspects.

Claims

1. A method for inferring the value of at least one local uniformity metric associated with a product structure, the method comprising: obtaining intensity data including an intensity image associated with at least one diffraction order obtained from a measurement of a target; obtaining at least one intensity distribution from the intensity image; determining an intensity metric from the at least one intensity distribution, the intensity metric representing a) a variation in intensity over the at least one diffraction order or b) a variation in the intensity difference between two complementary diffraction orders on the intensity image; and inferring the value of the at least one local uniformity metric from the intensity metric.

2. The method according to claim 1, wherein the target includes a pitch large enough to be measured by a scatterometer or interferometer-based metrology tool.

3. The method according to claim 1 or 2, wherein the target is divided into sub-segments, each sub-segment having a size that is the same, similar, and / or smaller compared to the product structure or an element of the product structure.

4. The method according to claim 3, wherein each sub-segment has a shape that is similar or identical to the product structure or an element of the product structure.

5. The method according to claim 3, wherein each sub-segment has at least one dimension that is smaller compared to the product structure or an element of the product structure to increase sensitivity to process variations compared to the product structure.

6. The method according to claim 1, wherein the method includes measuring the target to obtain the intensity data.

7. The method according to claim 1, wherein the intensity data includes at least two diffraction orders, and the intensity metric includes a measure of intensity variation or asymmetry variation within the intensity data.

8. The method according to claim 1, wherein the intensity metric includes the width of a histogram of the intensity distribution.

9. The method according to claim 1, wherein the intensity data includes asymmetry data, each of the at least one intensity distribution includes an asymmetry distribution, and the intensity metric includes an asymmetry metric.

10. The method according to claim 9, wherein the asymmetry data includes the per-target-position difference in intensity of a pair of complementary higher diffraction orders of diffracted measurement radiation after measurement of the target.

11. The method according to claim 1, wherein the intensity data relates to multiple different measurement conditions, and the method includes: determining an intensity metric for each measurement condition from the intensity distribution for each measurement condition; and determining the value of a different local uniformity metric from each of the intensity metrics, respectively.

12. The method according to claim 11, wherein each measurement condition relates to a different wavelength or combination of wavelengths.

13. The method according to claim 1, wherein the method includes an initial calibration step for calibrating each intensity metric of the at least one intensity metric to a corresponding one of the at least one local uniformity metric.

14. The method according to claim 13, Wherein, the calibration step includes: using a metrology tool of a type similar to or the same as the metrology tool used to obtain the intensity data, calibrating first calibration data measured from a target into second calibration data including a direct measurement result of the at least one local uniformity metric.

15. A computer program product including machine-readable instructions configured to infer a value of at least one local uniformity metric associated with a product structure, the instructions being configured to: obtain intensity data including an intensity image associated with at least one diffraction order obtained based on a measurement result regarding a target; obtain at least one intensity distribution based on the intensity image; determine an intensity index based on the at least one intensity distribution, the intensity index representing a change in intensity on the at least one diffraction order or a change in an intensity difference between two complementary diffraction orders on the intensity image; and infer the value of the at least one local uniformity metric based on the intensity index.

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