Pupil imaging through anderson localization based multimode fibers

Abstract

Systems, methods, and computer software are provided for determining deviations of a target, such as in a photolithography process. One metrology system (400) includes a radiation source (412) configured to irradiate a target (418) to generate scattered radiation from the target (419), an optical fibre (460) positioned to transmit the scattered radiation (419) to a detector (430, 430'), a programmable processor (432), and a non-transitory computer readable medium having instructions recorded thereon. The instructions, when executed by a computer having the programmable processor (430), cause operations including generating a fibre input image (462) of at least a portion of the target, determining a distortion of the fibre input image (462), determining a deviation of the target (418) based at least on correcting for the distortion.

Description

PUPIL IMAGING THROUGH ANDERSON LOCALIZATION BASED MULTIMODE FIBERSCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority of US application 63 / 681,127 which was filed on August 8, 2024 and which is incorporated herein in its entirety by reference.TECHNICAL FIELD

[0002] The description herein relates generally to obtaining imaging input, such as for use by a wafer alignment sensor. More particularly, the disclosure includes systems, methods, and computer programs for utilization of Anderson-localized fiberoptics to provide imaging input for determining deviations in a measured target.BACKGROUND

[0003] A lithographic apparatus is a machine that applies a desired pattern onto a substrate, usually onto a target portion of the substrate. A lithographic apparatus can be used, for example, in the manufacture of integrated circuits (ICs). In that instance, a patterning device, which can be 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., comprising part of, one, or several dies) on a substrate (e.g., a silicon wafer). Transfer of the pattern is typically via imaging onto a layer of radiation sensitive material (photoresist or simply “resist”) provided on the substrate. In general, a single substrate will contain a network of adjacent target portions that are successively patterned. Known lithographic apparatuses include so-called steppers, in which each target portion is irradiated by exposing an entire pattern onto the target portion at one time, and so-called scanners, in which each target portion is irradiated by scanning the pattern through a radiation beam in a given direction (the “scanning” direction) while synchronously scanning the target portions parallel or anti-parallel to this scanning direction. It is also possible to transfer the pattern from the patterning device to the substrate by imprinting the pattern onto the substrate.

[0004] During lithographic operation, different processing steps can entail different layers to be sequentially formed on the substrate. Accordingly, it can be necessary to position the substrate relative to prior patterns formed thereon with a high degree of accuracy. Generally, alignment marks are placed on the substrate to be aligned and are located with reference to a second object. A lithographic apparatus can use an alignment apparatus for detecting positions of the alignment marks and for aligning the substrate using the alignment marks to ensure accurate exposure from a mask. Misalignment between the alignment marks at two different layers is measured as overlay error.

[0005] Variations in the alignment apparatus and substrate can produce errors in assessing the true location of the alignment marks. Such errors are known as “on-process” accuracy errors. Alignment apparatus optics contain manufacturing aberrations and, thus, cannot be made identical. Further,diffraction-based alignment apparatus optics cannot differentiate between phase offsets induced by asymmetry variations in an alignment target and phase differences among diffraction orders of the alignment target. Substrates (e.g., wafer stacks), likewise, have properties variations stemming from manufacturing and post-manufacturing processes. Asymmetry variations in an alignment target from processing can cause alignment errors as large as several nanometers and are difficult to predict or calibrate. This “on-process” accuracy problem limits the robustness of the alignment apparatus.SUMMARY

[0006] Systems, methods, and computer software are provided for determining deviations of a target, such as in a photolithography process. One metrology system includes a radiation source configured to irradiate a target to generate scattered radiation from the target, an optical fiber positioned to transmit the scattered radiation to a detector, a programmable processor, and a non-transitory computer readable medium having instructions recorded thereon. The instructions, when executed by a computer having the programmable processor, cause operations including generating a fiber input image of at least a portion of the target, determining a distortion of the fiber input image, determining a deviation of the target based at least on correcting for the distortion.

[0007] In some embodiments, the fiber input image can be of a beam profile of the scattered radiation. The deviation can be an alignment position deviation or can be an overlay. The distortion can be a shift in a center of gravity (COG) of the fiber input image with the operations further comprising determining the COG of the fiber input image based on a fiber output image.

[0008] In some embodiments, the operations can include reconstructing, by a first machine -leaning model, a fiber input image from the fiber output image. A COG of the fiber input image can be determined. The distortion can be calculated as a difference between the COG of the fiber output image and the COG of the fiber input image.

[0009] In some embodiments, the operations can include predicting, by a second machine -learning model, the COG of the fiber input image. The second machine-learning model can be a convolutional neural network or can be a dense neural network having at least two hidden layers.

[0010] In some embodiments, the optical fiber is an Anderson localization (AL) optical fiber. The AL optical fiber can have a fill ratio of between 20% and 55% or can have a fill ratio of between 46% and 52%.

[0011] In some embodiments, the AL optical fiber can include a bent portion. Determining the distortion in the fiber input image can include utilizing a machine-learning model trained with data from the AL optical fiber with the bent portion to calculate or predict the distortion. Also, the machinelearning model can be trained with the AL optical fiber with the bent portion that is also used for obtaining the scattered radiation from the target.

[0012] In an interrelated aspect, a semiconductor device manufacturing method can include receiving a substrate with a photoresist layer with the method including directing (EUV / DUV) radiation from aradiation source to transfer a pattern from a mask onto the photoresist layer. A portion of the photoresist layer can be removed to form the pattern over the substrate. A fiber input image of at least a portion of the substrate can be generated. A distortion of the fiber input image can be determined, and a deviation of the substrate can be determined based at least on correcting for the distortion.BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The accompanying drawings, which are incorporated in and constitute a part of this specification, show certain aspects of the subject matter disclosed herein and, together with the description, help explain some of the principles associated with the disclosed implementations. In the drawings,Figure 1A shows a reflective lithographic apparatus, according to some aspects of the present disclosure.Figure 1 B shows a transmissive lithographic apparatus, according to some aspects of the present disclosure.Figure 2 shows more details of a reflective lithographic apparatus, according to some aspects of the present disclosure.Figure 3 shows a lithographic cell, according to some aspects of the present disclosure.Figures 4A and 4B show inspection apparatuses, according to some aspects of the present disclosure.Figure 4C Figure 4C is a diagram illustrating an example of a target and beam analyzer connected via a fiber optic, according to some aspects of the present disclosure. \Figure 5A depicts an AL optical fiber comprised of a collection of randomized fiber cores having two refractive indices, according to some aspects of the present disclosure.Figure 5B depicts an example of an AL optical fiber comprised of fibers cores having randomized sizes, according to some aspects of the present disclosure.Figure 6 is a process flow diagram depicting a method of determining deviations of a target, according to some aspects of the present disclosure.Figure 7 is a diagram illustrating a machine learning model for generating predictions of fiber input images, according to some aspects of the present disclosure.DETAILED DESCRIPTION

[0014] The aspects described herein, and references in the specification to “one aspect,” “an aspect,” “an exemplary aspect,” “an example aspect,” etc., indicate that the aspects described can include a particular feature, structure, or characteristic, but every aspect may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same aspect. Further, when a particular feature, structure, or characteristic is described in connection with anaspect, it is understood that it is within the knowledge of those skilled in the art to effect such feature, structure, or characteristic in connection with other aspects whether or not explicitly described.

[0015] Spatially relative terms, such as “beneath,” “below,” “lower,” “above,” “on,” “upper” and the like, can be used herein for ease of description to describe one element or feature’s relationship to another element(s) or feature(s) as illustrated in the figures. The spatially relative terms are intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures. The apparatus can be otherwise oriented (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein can likewise be interpreted accordingly.

[0016] The terms “about,” “approximately,” or the like can be used herein to indicate the value of a given quantity that can vary based on a particular technology. Based on the particular technology, the terms “about,” “approximately,” or the like can indicate a value of a given quantity that varies within, for example, 10-30% of the value (e.g., ±10%, ±20%, or ±30% of the value).

[0017] Aspects of the present disclosure can be implemented in hardware, firmware, software, or any combination thereof. Aspects of the disclosure can also be implemented as instructions stored on a computer-readable medium, which can be read and executed by one or more processors. A machine- readable medium can include any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computing device). For example, a machine-readable medium can include read only memory (ROM); random access memory (RAM); magnetic disk storage media; optical storage media; flash memory devices; electrical, optical, acoustical or other forms of propagated signals (e.g., carrier waves, infrared signals, digital signals, etc.), and others. Furthermore, firmware, software, routines, and / or instructions can be described herein as performing certain actions. However, it should be appreciated that such descriptions are merely for convenience and that such actions result from computing devices, processors, controllers, or other devices executing the firmware, software, routines, instructions, etc. The term “machine-readable medium” can be interchangeable with similar terms, for example, “computer program product,” “computer-readable medium,” “non-transitory computer readable medium,” or the like. The term “non-transitory” can be used herein to characterize one or more forms of computer readable media except for a transitory, propagating signal.

[0018] Before describing such aspects in more detail, however, it is instructive to present an example environment in which aspects of the present disclosure can be implemented.

[0019] FIGS. 1A and IB show a lithographic apparatus 100 and a lithographic apparatus 100’, respectively, in which aspects of the present disclosure can be implemented. Lithographic apparatus 100 and lithographic apparatus 100’ each include the following: an illumination system (illuminator) IL configured to condition a radiation beam B (for example, deep ultra violet or extreme ultra violet radiation); a support structure (for example, a mask table) MT configured to support a patterning device (for example, a mask, a reticle, or a dynamic patterning device) MA and connected to a first positioner PM configured to accurately position the patterning device MA; and, a substrate table (for example, a wafer table) WT configured to hold a substrate (for example, a resist coated wafer) W and connected toa second positioner PW configured to accurately position the substrate W. Lithographic apparatus 100 and 100’ also have a projection system PS configured to project a pattern imparted to the radiation beam B by patterning device MA onto a target portion (for example, comprising one or more dies) C of the substrate W. In lithographic apparatus 100, the patterning device MA and the projection system PS are reflective. In lithographic apparatus 100’, the patterning device MA and the projection system PS are transmissive.

[0020] The illumination system IL can include various types of optical components, such as refractive, reflective, catadioptric, magnetic, electromagnetic, electrostatic, or other types of optical components, or any combination thereof, for directing, shaping, or controlling the radiation beam B.

[0021] The support structure MT holds the patterning device MA in a manner that depends on the orientation of the patterning device MA with respect to a reference frame, the design of at least one of the lithographic apparatus 100 and 100’, and other conditions, such as whether or not the patterning device MA is held in a vacuum environment. The support structure MT can use mechanical, vacuum, electrostatic, or other clamping techniques to hold the patterning device MA. The support structure MT can be a frame or a table, for example, which can be fixed or movable. By using sensors, the support structure MT can ensure that the patterning device MA is at a desired position, for example, with respect to the projection system PS.

[0022] The term “patterning device” MA should be broadly interpreted as referring to any device that can be used to impart a radiation beam B with a pattern in its cross-section, such as to create a pattern in the target portion C of the substrate W. The pattern imparted to radiation beam B can correspond to a particular functional layer in a device being created in the target portion C to form an integrated circuit.

[0023] The patterning device MA can be transmissive (as in lithographic apparatus 100’ of FIG. IB) or reflective (as in lithographic apparatus 100 of FIG. 1A). Examples of patterning devices MA include reticles, masks, programmable mirror arrays, or programmable LCD panels. Masks are well known in lithography, and include mask types such as binary, alternating phase shift, or attenuated phase shift, as well as various hybrid mask types. An example of a programmable mirror array employs a matrix arrangement of small mirrors, each of which can be individually tilted so as to reflect an incoming radiation beam in different directions. The tilted mirrors impart a pattern in the radiation beam B, which is reflected by a matrix of small mirrors.

[0024] The term “projection system” PS can encompass 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 being used, or for other factors, such as the use of an immersion liquid on the substrate W or the use of a vacuum. A vacuum environment can be used for EUV or electron beam radiation since other gases can absorb too much radiation or electrons. A vacuum environment can therefore be provided to the whole beam path with the aid of a vacuum wall and vacuum pumps.

[0025] Lithographic apparatus 100 and / or lithographic apparatus 100’ can be of a type having two (dual stage) or more substrate tables WT (and / or two or more mask tables). In such “multiple stage” machines, the additional substrate tables WT can be used in parallel, or preparatory steps can be carried out on one or more tables while one or more other substrate tables WT are being used for exposure. In some situations, the additional table may not be a substrate table WT.

[0026] The lithographic apparatus can also be of a type wherein at least a portion of the substrate can be covered by a liquid having a relatively high refractive index, e.g., water, so as to fill a space between the projection system and the substrate. An immersion liquid can also be applied to other spaces in the lithographic apparatus, for example, between the mask and the projection system. Immersion techniques are well known in the art for increasing the numerical aperture of projection systems. The term “immersion” as used herein does not mean that a structure, such as a substrate, must be submerged in liquid. For example, a liquid can be located between the projection system and the substrate during exposure.

[0027] Referring to FIGS. 1A and IB, the illuminator IL receives a radiation beam from a radiation source SO. The source SO and the lithographic apparatus 100, 100’ can be separate physical entities, for example, when the source SO is an excimer laser. In such cases, the source SO is not considered to form part of the lithographic apparatus 100 or 100’, and the radiation beam B passes from the source SO to the illuminator IL with the aid of a beam delivery system BD (in FIG. IB) including, for example, suitable directing mirrors and / or a beam expander. In other cases, the source SO can be an integral part of the lithographic apparatus 100, 100’, for example, when the source SO is a mercury lamp. A radiation system can comprise the source SO, the illuminator IL, and / or the beam delivery system BD.

[0028] The illuminator IL can include an adjuster AD (in FIG. IB) for adjusting the angular intensity distribution of the radiation beam. Generally, at least the outer and / or inner radial extent (commonly referred to as “n-outer” and “n-inner,” respectively) of the intensity distribution in a pupil plane of the illuminator can be adjusted. In addition, the illuminator IL can comprise various other components (in FIG. IB), such as an integrator IN and a condenser CO. The illuminator IL can be used to condition the radiation beam B to have a desired uniformity and intensity distribution in its cross section.

[0029] Referring to FIG. 1 A, radiation beam B is incident on the patterning device (for example, mask) MA, which is held on the support structure (for example, mask table) MT, and is patterned by the patterning device MA. In lithographic apparatus 100, the radiation beam B is reflected from the patterning device (for example, mask) MA. After being reflected from the patterning device (for example, mask) MA, the radiation beam B passes through the projection system PS, which focuses the radiation beam B onto a target portion C of the substrate W. With the aid of the second positioner PW and position sensor IF2 (for example, an interferometric device, linear encoder, or capacitive sensor), the substrate table WT can be moved accurately (for example, so as to position different target portions C in the path of the radiation beam B). Similarly, the first positioner PM and another position sensor IF1 can be used to accurately position the patterning device (for example, mask) MA with respect tothe path of the radiation beam B. Patterning device (for example, mask) MA and substrate W can be aligned using mask alignment marks Ml, M2 and substrate alignment marks Pl, P2.

[0030] Referring to FIG. IB, the radiation beam B is incident on the patterning device (for example, mask MA), which is held on the support structure (for example, mask table MT), and is patterned by the patterning device. Having traversed the 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. The projection system has a pupil conjugate PPU to an illumination system pupil IPU. Portions of radiation emanate from the intensity distribution at the illumination system pupil IPU and traverse a mask pattern without being affected by diffraction at the mask pattern and create an image of the intensity distribution at the illumination system pupil IPU.

[0031] The projection system PS projects an image of the mask pattern MP, where the image is formed by diffracted beams produced from the mark pattern MP by radiation from the intensity distribution, onto a photoresist layer coated on the substrate W. For example, the mask pattern MP can include an array of lines and spaces. A diffraction of radiation at the array and different from zeroth order diffraction generates diverted diffracted beams with a change of direction in a direction perpendicular to the lines. Undiffracted beams (i.e., so-called zeroth order diffracted beams) traverse the pattern without any change in propagation direction. The zeroth order diffracted beams traverse an upper lens or upper lens group of the projection system PS, upstream of the pupil conjugate PPU of the projection system PS, to reach the pupil conjugate PPU. The portion of the intensity distribution in the plane of the pupil conjugate PPU and associated with the zeroth order diffracted beams is an image of the intensity distribution in the illumination system pupil IPU of the illumination system IU. The aperture device PD, for example, is disposed at or substantially at a plane that includes the pupil conjugate PPU of the projection system PS.

[0032] The projection system PS is arranged to capture (e.g., using a lens or lens group U) the zeroth order diffracted beams, first order diffracted beams, and / or higher order diffracted beams (not shown). In some aspects, dipole illumination for imaging line patterns extending in a direction perpendicular to a line can be used to utilize the resolution enhancement effect of dipole illumination. For example, first order diffracted beams interfere with corresponding zeroth-order diffracted beams at the level of the wafer W to create an image of the line pattern MP at highest possible resolution and process window (i.e., usable depth of focus in combination with tolerable exposure dose deviations). In some aspects, astigmatism aberration can be reduced by providing radiation poles (not shown) in opposite quadrants of the illumination system pupil IPU. Further, in some aspects, astigmatism aberration can be reduced by blocking the zeroth order beams in the pupil conjugate PPU of the projection system associated with radiation poles in opposite quadrants. This is described in more detail in US 7,511,799 B2, issued Mar. 31, 2009, which is incorporated by reference herein in its entirety.

[0033] With the aid of the second positioner PW and position sensor IFD (for example, an interferometric device, linear encoder, or capacitive sensor), the substrate table WT can be movedaccurately (for example, so as to position different target portions C in the path of the radiation beam B). Similarly, the first positioner PM and another position sensor (not shown in FIG. IB) can be used to accurately position the mask MA with respect to the path of the radiation beam B (for example, after mechanical retrieval from a mask library or during a scan).

[0034] In general, movement of the mask table MT can be realized with the aid of a long-stroke module (coarse positioning) and a short-stroke module (fine positioning), which form part of the first positioner PM. Similarly, movement of the substrate table WT can be realized using a long-stroke module and a short-stroke module, which form part of the second positioner PW. In the case of a stepper (as opposed to a scanner), the mask table MT can be connected to a short-stroke actuator or can be fixed. Mask MA and substrate W can be aligned using mask alignment marks Ml, M2, and substrate alignment marks Pl, P2. Although the substrate alignment marks (as illustrated) occupy dedicated target portions, they can be located in spaces between target portions (known as scribe-lane alignment marks). Similarly, in situations in which more than one die is provided on the mask MA, the mask alignment marks can be located between the dies.

[0035] Mask table MT and patterning device MA can be in a vacuum chamber V, where an in-vacuum robot IVR can be used to move patterning devices such as a mask in and out of vacuum chamber. Alternatively, when mask table MT and patterning device MA are outside of the vacuum chamber, an out-of-vacuum robot can be used for various transportation operations, similar to the in-vacuum robot IVR. Both the in-vacuum and out-of-vacuum robots can be calibrated for a smooth transfer of any payload (e.g., mask) to a fixed kinematic mount of a transfer station.

[0036] The lithographic apparatus 100 and 100’ can be used in at least one of the following modes:1. In step mode, the support structure (for example, mask table) MT and the substrate table WT are kept essentially stationary, while an entire pattern imparted to the radiation beam B is projected onto a target portion C at one time (i.e., a single static exposure). The substrate table WT is then shifted in the X and / or Y direction so that a different target portion C can be exposed.2. In scan mode, the support structure (for example, mask table) MT and the substrate table WT are scanned synchronously while a pattern imparted to the radiation beam B is projected onto a target portion C (i.e., a single dynamic exposure). The velocity and direction of the substrate table WT relative to the support structure (for example, mask table) MT can be determined by the (de-)magnification and image reversal characteristics of the projection system PS.3. In another mode, the support structure (for example, mask table) MT is kept substantially stationary holding a programmable patterning device, and the substrate table WT is moved or scanned while a pattern imparted to the radiation beam B is projected onto a target portion C. A pulsed radiation source SO can be employed and the programmable patterning device is updated as needed after each movement of the substrate table WT or in between successive radiation pulses during a scan. This mode of operation can be readily applied to maskless lithography that utilizes a programmable patterning device, such as a programmable mirror array.

[0037] Combinations and / or variations on the described modes of use or entirely different modes of use can also be employed.

[0038] In some aspects, lithographic apparatus 100 includes an extreme ultraviolet (EUV) source, which is configured to generate a beam of EUV radiation for EUV lithography. In general, the EUV source is configured in a radiation system, and a corresponding illumination system is configured to condition the EUV radiation beam of the EUV source.

[0039] In some aspects, lithographic apparatus 100’ includes a deep ultraviolet (DUV) source, which is configured to generate a beam of DUV radiation for DUV lithography. In general, the DUV source is configured in a radiation system, and a corresponding illumination system is configured to condition the DUV radiation beam of the DUV source.

[0040] FIG. 2 shows the lithographic apparatus 100’ in more detail, including the source collector apparatus SO, the illumination system IL, and the projection system PS. The source collector apparatus SO is constructed and arranged such that a vacuum environment can be maintained in an enclosing structure 220 of the source collector apparatus SO. An EUV radiation emitting plasma 210 can be formed by a discharge produced plasma source. EUV radiation can be produced by a gas or vapor, for example Xe gas, Li vapor, or Sn vapor in which EUV radiation emitting plasma 210 is created to emit radiation in the EUV range of the electromagnetic spectrum. The EUV radiation emitting plasma 210 is created by, for example, an electrical discharge causing at least a partially ionized plasma. Partial pressures of, for example, 10 Pa of Xe, Li, Sn vapor, or any other suitable gas or vapor can be used for efficient generation of the radiation. In some aspects, a plasma of excited tin (Sn) (e.g., excited via a laser) is provided to produce EUV radiation.

[0041] The radiation emitted by the EUV radiation emitting plasma 210 is passed from a source chamber 211 into a collector chamber 212 via an optional gas barrier or contaminant trap 230 (in some cases also referred to as contaminant barrier or foil trap), which is positioned in or behind an opening in source chamber 211. The contaminant trap 230 can include a channel structure. Contaminant trap 230 can also include a gas barrier or a combination of a gas barrier and a channel structure. The contaminant trap 230 further indicated herein at least includes a channel structure.

[0042] The collector chamber 212 can include a radiation collector CO, which can be a so-called grazing incidence collector. Radiation collector CO has an upstream radiation collector side 251 and a downstream radiation collector side 252. Radiation that traverses collector CO can be reflected off a grating spectral fdter 240 to be focused in a virtual source point INTF. The virtual source point INTF is commonly referred to as the intermediate focus, and the source collector apparatus is arranged such that the intermediate focus INTF is located at or near an opening 219 in the enclosing structure 220. The virtual source point INTF is an image of the EUV radiation emitting plasma 210. Grating spectral filter 240 is used in particular for suppressing infra-red (IR) radiation.

[0043] Subsequently the radiation traverses the illumination system IL, which can include a faceted field mirror device 222 and a faceted pupil mirror device 224 arranged to provide a desired angulardistribution of the radiation beam 221, at the patterning device MA, as well as a desired uniformity of radiation intensity at the patterning device MA. Upon reflection of radiation beam 221 at the patterning device MA, held by the support structure MT, a patterned beam 226 is formed and the patterned beam 226 is imaged by the projection system PS via reflective elements 228, 229 onto a substrate W held by the wafer stage or substrate table WT.

[0044] More elements than shown can generally be present in illumination optics unit IL and projection system PS. The grating spectral fdter 240 can optionally be present, depending upon the type of lithographic apparatus. Further, there can be more mirrors present than those shown in the FIG. 2, for example there can be one to six additional reflective elements present in the projection system PS than shown in FIG. 2.

[0045] Collector optic CO, as illustrated in FIG. 2, 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 disposed axially symmetric around an optical axis O and a collector optic CO of this type is preferably used in combination with a discharge produced plasma source, often called a DPP source.

[0046] The lithographic apparatus 100 or 100’ and radiation source SO described herein can be used in a method for manufacturing a semiconductor device. A semiconductor device manufacturing method comprises receiving a substrate W with a photoresist layer. The method further comprises directing a radiation beam from radiation source SO to transfer a pattern from a mask onto the photoresist layer. This could be achieved by a patterning device which is configured to form a patterned radiation beam, imparting the patterned radiation beam onto the photoresist layer. The method for manufacturing a semiconductor device further comprises the step of removing a portion of the photoresist layer to form the pattern over the substrate W.

[0047] The substrate W may be made of silicon or other semiconductor materials. Alternatively or additionally, the substrate W may include other semiconductor materials such as germanium (Ge) or carbon (C). In some embodiments, the semiconductor substrate is made of a compound semiconductor such as III-V compound semiconductors, II-V compound semiconductors, and / or any suitable integration of Group IV materials. In some embodiments, the substrate W may be a silicon-on-insulator (SOI) or a germanium -on-insulator (GOI) substrate.

[0048] The semiconductor device made from the substrate W may have various device elements. Examples of semiconductor device elements that are formed over the substrate W include transistors (e.g., planar or non-planar metal oxide semiconductor field effect transistors (MOSFET), bipolar junction transistors (BJT), high-voltage transistors, high-frequency transistors, etc.), diodes, CMOS image sensors, passive devices, and / or other applicable elements. Various processes may be performed to form the semiconductor device elements, such as deposition, etching, implantation, epitaxial growth, polishing, thermal treatment, and / or other suitable processes. In some embodiments, the substrate W is coated with a photoresist layer sensitive to the EUV light.

[0049] Figure 3 shows a lithographic cell 300, also sometimes referred to a lithocell or cluster, according to some aspects. Lithographic apparatus 100 or 100’ can form part of lithographic cell 300. Lithographic cell 300 can also include one or more apparatuses to perform pre- and post-exposure processes on a substrate. Conventionally these include spin coaters SC to deposit resist layers, developers DE to develop exposed resist, chill plates CH, and bake plates BK. A substrate handler, or robot, RO picks up substrates from input / output ports I / Ol, I / O2, moves them between the different process apparatuses and delivers them to the loading bay LB of the lithographic apparatus 100 or 100’. These devices, which are often collectively referred to as the track, are under the control of a track control unit TCU, which is itself controlled by a supervisory control system SCS, which also controls the lithographic apparatus via lithography control unit LACU. Thus, the different apparatuses can be operated to maximize throughput and processing efficiency.

[0050] In order to control the lithographic process to place device features accurately on the substrate, alignment marks are generally provided on the substrate, and the lithographic apparatus includes one or more inspection apparatuses for accurate positioning of marks on a substrate. These alignment apparatuses are effectively position measuring apparatuses. Different types of marks and different types of alignment apparatuses and / or systems are known from different times and different manufacturers. A type of system widely used in current lithographic apparatus is based on a self-referencing interferometer as described in U.S. Patent No. 6,961,116 (den Boef et al.). Generally marks are measured separately to obtain X- and Y-positions. A combined X- and Y-measurement can be performed using the techniques described in U.S. Publication No. 2009 / 195768 A (Bijnen et al.), however. The full contents of both of these disclosures are incorporated herein by reference.

[0051] Figure 4A shows a cross-sectional view of an inspection apparatus 400 that can be implemented as a part of lithographic apparatus 100 or 100’, according to some aspects. In some aspects, inspection apparatus 400 can be configured to align a substrate (e.g., substrate W) with respect to a patterning device (e.g., patterning device MA). Inspection apparatus 400 can be further configured to detect positions of alignment marks on the substrate and to align the substrate with respect to the patterning device or other components of lithographic apparatus 100 or 100’ using the detected positions of the alignment marks. Such alignment of the substrate can ensure accurate exposure of one or more patterns on the substrate.

[0052] The terms “inspection apparatus,” “metrology system,” or the like can be used herein to refer to, e.g., a device used for measuring a property of a structure (e.g., overlay sensor, critical dimension sensor, or the like), a device or system used in a lithographic apparatus to inspect an alignment of a wafer (e.g., alignment sensor), or the like.

[0053] In some aspects, inspection apparatus 400 can include an illumination system 412, a beam splitter 414, an interferometer 426, a detector 428, a beam analyzer 430, and a processor 432. Illumination system 412 can be configured to provide an electromagnetic, narrow-band, radiation beam 413 having one or more passbands. In an example, the one or more passbands can be within a spectrumof wavelengths between about 500 nm to about 900 nm. In another example, the one or more passbands can be discrete narrow passbands within a spectrum of wavelengths between about 500 nm to about 900 nm. Illumination system 412 can be further configured to provide one or more passbands having substantially constant center wavelength (CWL) values over a long period of time (e.g., over a lifetime of illumination system 412). Such configuration of illumination system 412 can help to prevent the shift of the actual CWL values from the desired CWL values, as discussed above, in current alignment systems. And, as a result, the use of constant CWL values can improve long-term stability and accuracy of alignment systems (e.g., inspection apparatus 400) compared to the current alignment apparatuses.

[0054] In some aspects, beam splitter 414 can be configured to receive radiation beam 413 and split radiation beam 413 into at least two radiation sub-beams. For example, radiation beam 413 can be split into radiation sub-beams 417a and 417b, as shown in FIG. 4A. Beam splitter 414 can be further configured to direct radiation sub-beam 417a onto a substrate 420 placed on a stage 422. In one example, the stage 422 is movable along direction 424. Radiation sub-beam 417a can be configured to illuminate an alignment mark or a target 418 located on substrate 420. Alignment mark or target 418 can be coated with a radiation sensitive film. In some aspects, alignment mark or target 418 can have one hundred and eighty degrees (i.e., 180°) symmetry. That is, when alignment mark or target 418 is rotated 180° about an axis of symmetry perpendicular to a plane of alignment mark or target 418, rotated alignment mark or target 418 can be substantially identical to an unrotated alignment mark or target 418. The target 418 on substrate 420 can be (a) a resist layer grating comprising bars that are formed of solid resist lines, or (b) a product layer grating, or (c) a composite grating stack in an overlay target structure comprising a resist grating overlaid or interleaved on a product layer grating. The bars can alternatively be etched into the substrate. This pattern is sensitive to chromatic aberrations in the lithographic projection apparatus, particularly the projection system PL, and illumination symmetry and the presence of such aberrations will manifest themselves in a variation in the printed grating. One in-line method used in device manufacturing for measurements of line width, pitch, and critical dimension makes use of a technique known as “scatterometry”. Methods of scatterometry are described in Raymond et al., “Multiparameter Grating Metrology Using Optical Scatterometry”, J. Vac. Sci. Tech. B, Vol. 15, no. 2, pp. 361-368 (1997) and Niu et al., “Specular Spectroscopic Scatterometry in DUV Lithography”, SPIE, Vol. 3677 (1999), which are both incorporated by reference herein in their entireties. In scatterometry, light is reflected by periodic structures in the target, and the resulting reflection spectrum at a given angle is detected. The structure giving rise to the reflection spectrum is reconstructed, e.g. using Rigorous Coupled-Wave Analysis (RCWA) or by comparison to a library of patterns derived by simulation. Accordingly, the scatterometry data of the printed gratings is used to reconstruct the gratings. The parameters of the grating, such as line widths and shapes, can be input to the reconstruction process, performed by processing unit PU, from knowledge of the printing step and / or other scatterometry processes.

[0055] In some aspects, beam splitter 414 can be further configured to receive diffraction radiation beam 419 and split diffraction radiation beam 419 into at least two radiation sub-beams, according to an aspect. Diffraction radiation beam 419 can be split into diffracted radiation sub-beam 429 and 439, as shown in Figure 4A.

[0056] It should be noted that even though beam splitter 414 is shown to direct radiation sub-beam 417a towards alignment mark or target 418 and to direct diffracted radiation sub-beam 429 towards interferometer 426, the disclosure is not so limiting. Other optical arrangements can be used to obtain the similar result of illuminating alignment mark or target 418 on substrate 420 and detecting an image of alignment mark or target 418.

[0057] As illustrated in FIG. 4A, interferometer 426 can be configured to receive radiation sub-beam 417 and diffracted radiation sub-beam 429 through beam splitter 414. In an example aspect, diffracted radiation sub-beam 429 can be at least a portion of radiation sub-beam 417a that can be reflected from alignment mark or target 418. In an example of this aspect, interferometer 426 comprises any appropriate set of optical -elements, for example, a combination of prisms that can be configured to form two images of alignment mark or target 418 based on the received diffracted radiation sub-beam 429. It should be appreciated that a good quality image need not be formed. It can be enough to have the features of the alignment mark resolved. Interferometer 426 can be further configured to rotate one of the two images with respect to the other of the two images 180° and recombine the rotated and unrotated images interferometrically.

[0058] In some aspects, detector 428 can be configured to receive the recombined image via interferometer signal 427 and detect interference as a result of the recombined image when alignment axis 421 of inspection apparatus 400 passes through a center of symmetry (not shown) of alignment mark or target 418. Such interference can be due to alignment mark or target 418 being 180° symmetrical, and the recombined image interfering constructively or destructively, according to an example aspect. Based on the detected interference, detector 428 can be further configured to determine a position of the center of symmetry of alignment mark or target 418 and consequently, detect a position of substrate 420. The determination can be made by, for example, an on-board processor of the detector or another processor or computing device (e.g., processor 432). According to an example, alignment axis 421 can be aligned with an optical beam perpendicular to substrate 420 and passing through a center of image rotation interferometer 426. Detector 428 can be further configured to estimate the positions of alignment mark or target 418 by implementing sensor characteristics and interacting with wafer mark process variations.

[0059] In a further aspect, detector 428 determines the position of the center of symmetry of alignment mark or target 418 by performing one or more of the following measurements:1. measuring position variations for various wavelengths (position shift between colors);2. measuring position variations for various orders (position shift between diffraction orders); and3. measuring position variations for various polarizations (position shift between polarizations).

[0060] This data can be obtained using any type of alignment sensor, for example, as described in U.S. Patent No. 6,961,116 that employs a self-referencing interferometer with a single detector and four different wavelengths, and extracts the alignment signal in software, or as described in U.S. Patent No. 6,297,876, which directs each of seven diffraction orders to a dedicated detector, which are both incorporated by reference herein in their entireties.

[0061] In some aspects, beam analyzer 430 can be configured to receive and determine an optical state of diffracted radiation sub-beam 439. The optical state can be a measure of beam wavelength, polarization, or beam profile. Beam analyzer 430 can be further configured to determine a position of stage 422 and correlate the position of stage 422 with the position of the center of symmetry of alignment mark or target 418. As such, the position of alignment mark or target 418 and, consequently, the position of substrate 420 can be accurately known with reference to stage 422. Alternatively, beam analyzer 430 can be configured to determine a position of inspection apparatus 400 or any other reference element such that the center of symmetry of alignment mark or target 418 can be known with reference to inspection apparatus 400 or any other reference element. Beam analyzer 430 can be a point or an imaging polarimeter with some form of wavelength-band selectivity. In some aspects, beam analyzer 430 can be directly integrated into inspection apparatus 400, or connected via optical fiber 460, which can be any one of several types: polarization preserving single mode, multimode, or imaging, according to other aspects. The present disclosure also describes embodiments where optical fiber 460 is a type of fiber optic known as an Anderson localization fiber.

[0062] In some aspects, beam analyzer 430 can be further configured to determine the overlay data between two patterns on substrate 420. One of these patterns can be a reference pattern on a reference layer. The other pattern can be an exposed pattern on an exposed layer. The reference layer can be an etched layer already present on substrate 420. The reference layer can be generated by a reference pattern exposed on the substrate by lithographic apparatus 100 and / or 100’. The exposed layer can be a resist layer exposed adjacent to the reference layer. The exposed layer can be generated by an exposure pattern exposed on substrate 420 by lithographic apparatus 100 or 100’. The exposed pattern on substrate 420 can correspond to a movement of substrate 420 by stage 422. In some aspects, the measured overlay data can also indicate an offset between the reference pattern and the exposure pattern. The measured overlay data can be used as calibration data to calibrate the exposure pattern exposed by lithographic apparatus 100 or 100’, such that after the calibration, the offset between the exposed layer and the reference layer can be minimized.

[0063] In some aspects, beam analyzer 430 can be further configured to determine a model of the product stack profile of substrate 420, and can be configured to measure overlay, critical dimension, and focus of target 418 in a single measurement. The product stack profile contains information on the stacked product such as alignment mark, target 418, or substrate 420, and can include mark process variation-induced optical signature metrology that is a function of illumination variation. The productstack profile can also include product grating profile, mark stack profile, and mark asymmetry information. An example of beam analyzer 430 is described in U.S. Patent No. 8,706,442, which is incorporated by reference herein in its entirety. Beam analyzer 430 can be further configured to process information related to a particular property of an exposed pattern in that layer. For example, beam analyzer 430 can process an overlay parameter (an indication of the positioning accuracy of the layer with respect to a previous layer on the substrate or the positioning accuracy of the first layer with respective to marks on the substrate), a focus parameter, and / or a critical dimension parameter (e.g., line width and its variations) of the depicted image in the layer. Other parameters are image parameters relating to the quality of the depicted image of the exposed pattern.

[0064] In some aspects, an array of detectors (not shown) can be connected to beam analyzer 430, and allows the possibility of accurate stack profile detection as discussed below. For example, detector 428 can be an array of detectors. For the detector array, a number of options are possible: a bundle of multimode fibers, discrete pin detectors per channel, or CCD or CMOS (linear) arrays. The use of a bundle of multimode fibers enables any dissipating elements to be remotely located for stability reasons. Discrete PIN detectors offer a large dynamic range but each need separate pre-amps. The number of elements is therefore limited. CCD linear arrays offer many elements that can be read-out at high speed and are especially of interest if phase -stepping detection is used.

[0065] In some aspects, a second beam analyzer 430’ can be configured to receive and determine an optical state of diffracted radiation sub-beam 429, as shown in Figure 4B. The optical state can be a measure of beam wavelength, polarization, or beam profile. Second beam analyzer 430’ can be identical to beam analyzer 430. Alternatively, second beam analyzer 430’ can be configured to perform one or more of the functions of beam analyzer 430, such as determining a position of stage 422 and correlating the position of stage 422 with the position of the center of symmetry of alignment mark or target 418. As such, the position of alignment mark or target 418 and, consequently, the position of substrate 420, can be accurately known with reference to stage 422. Second beam analyzer 430’ can also be configured to determine a position of inspection apparatus 400, or any other reference element, such that the center of symmetry of alignment mark or target 418 can be known with reference to inspection apparatus 400, or any other reference element. Second beam analyzer 430’ can be further configured to determine the overlay data between two patterns and a model of the product stack profile of substrate 420. Second beam analyzer 430’ can also be configured to measure overlay, critical dimension, and focus of target 418 in a single measurement.

[0066] In some aspects, second beam analyzer 430’ can be directly integrated into inspection apparatus 400, or it can be connected via fiber optics of several types: polarization preserving single mode, multimode, or imaging, according to other aspects. Alternatively, second beam analyzer 430’ and beam analyzer 430 can be combined to form a single analyzer (not shown) configured to receive and determine the optical states of both diffracted radiation sub-beam 429 and 439.

[0067] In some aspects, processor 432 receives information from detector 428 and beam analyzer 430. For example, processor 432 can be an overlay calculation processor. The information can comprise a model of the product stack profde constructed by beam analyzer 430. Alternatively, processor 432 can construct a model of the product mark profile using the received information about the product mark. In either case, processor 432 constructs a model of the stacked product and overlay mark profile using or incorporating a model of the product mark profile. The stack model is then used to determine the overlay offset and minimizes the spectral effect on the overlay offset measurement. Processor 432 can create a basic correction algorithm based on the information received from detector 428 and beam analyzer 430, including but not limited to the optical state of the illumination beam, the alignment signals, associated position estimates, and the optical state in the pupil, image, and additional planes. The pupil plane is the plane in which the radial position of radiation defines the angle of incidence and the angular position defines the azimuth angle of the radiation. Processor 432 can utilize the basic correction algorithm to characterize the inspection apparatus 400 with reference to wafer marks and / or alignment marks.

[0068] In some aspects, processor 432 can be further configured to determine printed pattern position offset error with respect to the sensor estimate for each mark based on the information received from detector 428 and beam analyzer 430. The information includes but is not limited to the product stack profile, measurements of overlay, critical dimension, and focus of each alignment marks or target 418 on substrate 420. Processor 432 can utilize a clustering algorithm to group the marks into sets of similar constant offset error, and create an alignment error offset correction table based on the information.

[0069] In some aspects, processor 432 can determine corrections for each mark and feed the corrections back to lithographic apparatus 100 or 100’ for correcting errors in alignment / overlay, for example, by feeding corrections into the inspection apparatus 400.

[0070] Figure 4C is a diagram illustrating an example of a target and beam analyzer connected via a fiber optic. In some embodiments, beam splitter 414 receives radiation beam 413 and focuses radiation beam 413 via focusing optic 454 onto target 418 to produce a first order beam as well as second diffraction order sub-beam 415 and third diffraction order sub-beam 416. Second diffraction order subbeam 415 includes measured second diffraction order sub-beam 415a and reference second diffraction order sub-beam 415b (i.e., determined by a known reference diffraction grating with identical pitch to target 418). Third diffraction order sub-beam 416 includes measured third diffraction order sub-beam 416a and reference third diffraction order sub-beam 416b (i.e., determined by a known reference diffraction grating with identical pitch to target 418). As shown in Figure 4C, pupil plane phase distribution 450 is produced at pupil plane 452 by target 418, first overlay layer 418a, and second overlay layer 418b and detected by beam analyzer 430. In some embodiments, first overlay layer 418a and / or second overlay layer 418b can be omitted.

[0071] First diffraction order sub-beam and measured second diffraction order sub-beam 415a and measured third diffraction order sub-beam 416a produce pupil plane phase distribution 450 at pupilplane 452. The differences between measured second diffraction order sub-beam 415a and reference second diffraction order sub-beam 415b and measured third diffraction order sub-beam 416a and reference third diffraction order sub-beam 416b, respectively, can be correlated to determine an alignment position error, stack thickness error, and / or a sensor response function of the system. The collected light at first optic 462 can direct light into optical fiber 460. Light emerging from optical fiber 460 can be expanded by second optic 464 and into beam analyzer 430. Beam analyzer 430 can measure center of gravity shifts of second diffraction order sub-beams 415 and third diffraction order sub-beam 416 (i.e., compare shift of measured center of gravity from reference center of gravity) to determine an alignment position error, stack thickness error, and / or a sensor response function of the system. Beam analyzer 430 can have demultiplexer 430a, which can be configured to separate light into various wavelengths. The separated light can be delivered to any number of cameras for analysis, including first camera 430b (e.g., configured to image a first wavelength), second camera 430c (e.g., configured to image a second wavelength), etc.

[0072] In some embodiments, beam analyzer 430 can be an external stand-alone apparatus configured to measure pupil plane phase distribution 450, for example, based on a reference irradiance distribution (i.e., reference second diffraction order sub-beam 415b and reference third diffraction order sub-beam 416b). The reference irradiance distribution can be based on an aberration map. In some embodiments, beam analyzer 430 can be configured to determine a sensor response function of beam analyzer 430 based on a shift in pupil plane phase distribution 450. In some embodiments, the system can be configured to correct an alignment position error of beam analyzer 430 based on the sensor response function. For example, the system can correct the alignment position error by calculating a first center of gravity shift between measured second diffraction order sub-beam 415a and reference second diffraction order sub-beam 415b and a second center of gravity shift between measured second diffraction order sub-beam 415a and reference third diffraction order sub-beam 416b. In some embodiments, first and second gravity shifts can be calculated as a function of one or more wavelengths of radiation beam 413. For example, first and second gravity shifts can be calculated as a function of wavelengths of about 532 run, 636 nm, 780 nm, and / or 850 nm.

[0073] Due to wafer process variations, the intensity distribution within diffracted radiation sub-beam 429 (or 439) from the target (e.g., an alignment mark) can vary. This variation can cause an additional error when combined with the residual optical aberration in the alignment sensor, especially for low wafer quality (W Q) use cases. The effect of aberrations at the objective is depicted by pupil plane phase distribution 450, which is shown as varying going away from the optical axis. Diffracted light is shown being reflected from target, with some portion (e.g., +1 order diffracted light) collected by optical fiber 460 that is located off the optical axis. Output image 480 shows an example of light intensity at the output of the optical fiber. Were there no aberrations, for an ideal alignment mark, the intensity measured at input image 470 would be nearly constant (or at least known from the predicted intensityof diffracted light vs. linear distance from the optical axis). With the aberration, phase shifts can be introduced and cause the center of intensity to have shift 472.

[0074] The fiber optic that receives the diffracted light can be a multimode fiber, but such use of single core multimode fibers can suffer from delocalization of fiber modes across the fiber and cause output image 480 to be distorted, making an accurate determination of shift 472 difficult. For example, the scrambling of light output from optical fiber 460 can affect determination of shift 472 by appearing instead as shift 482, based on analysis or processing of output image 480. As one way of addressing this issue, the present disclosure contemplates the use of Anderson localized fibers to reduce this delocalization such that output image 480 remains closer to input image 470. This improvement in output image transmission accuracy can facilitate additional improvements, such as a reduction in the needed training of machine learning models that interpret the output images. Other benefits can include robustness even when utilized with curved fiber optics, because curves in optical fibers can further contribute to delocalization and in a way that is specific to fiber geometry or setup, which may be unknown or vary. The present disclosure thereby reduces the need to retrain machine -learning models for different fiber geometries when determining the accurate position of a target.

[0075] Figure 5A depicts an AL optical fiber comprised of a collection of randomized fiber cores having two refractive indices.

[0076] As an introduction to Anderson localized optical fibers, in general they have a refractive index profile that is random (or quasi-random) in the transverse direction (radially or X / Y) but is substantially constant in the longitudinal (lengthwise or Z) direction. AL optical fibers do not rely on total internal reflection as in conventional fibers but instead by the absence of diffusive wave transport due to the randomized refractive index.

[0077] The refractive index across the example AL optical fiber shown in Figure 5A can be discretized into squares 510 of nearly wavelength-size side-widths. Each fiber has a refractive index of nl (white) or n2 (black) with an approximately 50-50 chance. This randomizes the transverse refractive index profile while the refractive index remains constant in the longitudinal direction. Without this randomization (e.g., in conventional fibers made of the same core material throughout) light diffracts as it propagates along the fiber and fills the fiber volume. However, in the AL optical fiber, light scatters strongly in the transverse direction due to the randomization and thus remains predominantly localized to that particular fiber (after a brief expansion or diffusion), while it is allowed to freely propagate in the longitudinal direction. The effective localization can be increased by increasing the scattering crosssection. This can be done by increasing the difference in refractive index An = |n2 - n 11 between the two fiber materials. While the depicted squares are illustrated somewhat coarsely, an actual AL optical fiber can have dozens or hundreds of fibers in the transverse direction.

[0078] Figure 5B depicts an example of an AL optical fiber comprised of fibers cores having randomized sizes. The differing sizes of the fibers 520 support optical modes with different propagation constants. As such, the modes cannot efficiently couple and the amplitude of optical wave in one fiberexponentially decreases in its neighboring fibers. The coupling efficiency also increases with increasing randomness of the fiber collection. Here also, the number and sizes of the fibers are shown more coarsely than would be in an actual AL optical fiber. Also depicted is a simplified representation of multiple indices of refraction, similar to that shown in Figure 5A. Here, three different indices are depicted by the shading of randomized fibers. While three indices are depicted, any number of indices can be utilized, e.g., two, four, five, etc.

[0079] Accordingly, the present disclosure contemplates that in any of the disclosed metrology systems, the optical fiber (e.g., used to transmit diffracted radiation sub-beam 429 (or 439) can be an AL optical fiber. An AL optical fiber can have a parameter referred to herein as a “fill ratio,” which as used herein is the ratio of the areas of the fiber that have the two different refractive indices (and does not include other areas such as for cladding). In various embodiments, the AL optical fiber can have a fill ratio of between 20% and 55%, which can be suitable for some applications and more straightforward to structurally obtain in practice. In some embodiments, a more even distribution of the different refractive indices can be beneficial, for example having a fill ratio between 46% and 52%. While more challenging to obtain structurally in an AL optical fiber, this can provide additional benefits in terms of accurate image propagation.

[0080] In other variations, such as of the type depicted in Figure 5B, the degree of randomness (e.g., of sizes) can be parameterized as disorder strength. For a normal distribution of sizes, the disorder strength can be related to the standard deviation of the distribution.

[0081] The improved robustness of using AL optical fiber enables using AL optical fiber with bent portion(s) (i.e., not purely straight). As described herein, AL optical fiber’s improved image transmission can compensate for degradation that might occur from using non-straight AL optical fiber. To obtain accurate input images, when determining the distortion in the fiber input image, the present disclosure contemplates utilizing a machine-learning model trained with data from the AL optical fiber with the bent portion to calculate or predict the distortion as it appears in the fiber output image (e.g., at a CCD or other detector at the output of the optical fiber). Further, in some embodiments, the AL optical fiber, the optics setup, etc., from the actual metrology device can be used to train the machinelearning model, thus providing fewer deviations between training and application. As such, the machine-learning model can be trained with the AL optical fiber with the bent portion that is also used for obtaining the scattered radiation from the target.

[0082] Figure 6 is a process flow diagram depicting a method of determining deviations of a target. In an embodiment, a metrology system can include a radiation source configured to irradiate a target to generate scattered radiation from the target, for example as depicted in Figures 4A and 4B. An optical fiber can be positioned to transmit the scattered radiation to a detector. The detector and associated processing systems can perform operations including, at 610, generating a fiber input image of at least a portion of the target. For example, the fiber input image can be of a beam profile of the scattered radiation. At 620, a distortion of the fiber input image can be determined, for example as depicted inFigure 4C. At 630, a deviation of the target (e.g., an alignment position deviation, overlay, etc.) can be determined based at least on correcting for the distortion.

[0083] Distortion of the fiber input image can be a shift in the intensity (or amplitude) weighted center of the fiber output image, a rotation, a magnification, a shape distortion, etc. As one example detailed here, the shift can be in the intensity or amplitude weighted center (referred to herein as a center of gravity (COG)) of the fiber output image. The operations to determine a deviation of the target can include determining the COG of the fiber input image, which can vary due to misalignment of the target or manufacturing process variations. As one example, for a 2x2 pixel grid with the four pixels having intensities 11-14, the x and y coordinates of the COG can be expressed as:COGx = (Ii *XI+I2*X2+I3*XI+I4*X2) / (II+I2+I3+I4), andCOGy = (Ii*yi+l2*y2+l3*yi+l4*y2) / ( I1+I2+I3+I4) .The above determination can also be generalized to a grid of arbitrary size in the x and y dimensions. The determination of the fiber input image can be based on the fiber output image and performed in numerous ways, with several examples detailed herein.

[0084] In an embodiment, a machine -learning model can be utilized to determine fiber input images, which may be distorted after transmission through a fiber optic. With an accurately determined fiber input image and a characterized measurement system (e.g., including known aberrations at the objective), a determination of the deviation of the target can be made. An example process can include reconstructing, by a first machine-leaning model, a fiber input image from the fiber output image. A COG of the fiber input image can be determined, for example as described above. The distortion due to fiber transmission can be calculated as a difference between the COG of the fiber output image and the COG of the fiber input image. In some embodiments, the machine -learning model can be Unet or pix2pix (CGAN).

[0085] Figure 7 is a diagram illustrating a machine learning model for generating predictions of fiber input images. In other embodiments, a machine -learning model can predict the COG of the fiber input image without having to reconstruct the fiber input image. Here, the operations can include predicting, by a second machine-learning model 710 (e.g., one configured and trained for image prediction), the COG of the fiber input image. Second machine-learning model can, for example, be a convolutional neural network. For a predictive machine-learning model, some embodiments can include those where the second machine-learning model is a dense neural network having at least two hidden layers. For example, there can be a single input layer 720 (e.g., having 128x128 neurons - with 4 shown in the example of Figure 7), two hidden layers 730 (e.g., having 256 neurons on the first hidden layer and 512 neurons on the second hidden layer - not all shown in Figure 7), and one output layer 740 (e.g., having two neurons). The number of input neurons can be based, for example, on the image resolution. Forexample, with an input resolution of 128x128, input layer 720 can have a corresponding 128x128 neurons. While a 1: 1 correspondence can be utilized, in other embodiments down sampling or up sampling can be performed so as not to require a 1: 1 correspondence. In some embodiments, the number of output neurons can be based on the desired number of coordinates (e.g., x and y would correspond to two output neurons). Other numbers of output numbers are possible, e.g., 3 if additional information is desired. In some embodiments, the dense neural network can be trained with two datasets, a simulated dataset and a dataset from an actual lithography system. The addition of hidden layers can enable the machine -learning model to account for more non-linear features. In some embodiments, the number of hidden layers can be increased to 3, 4, or 5. In some embodiments, the number of hidden layers can be limited to a number such that the accuracy improvement of the prediction plateaus with the addition of further hidden layers. Such machine-learning model design is optimized for the accuracy of the model in view of the increased processing overhead of adding more hidden layers.

[0086] The lithographic apparatus LA and radiation source SO described herein can be used in a method for manufacturing a semiconductor device. A semiconductor device manufacturing method comprises receiving a substrate W with a photoresist layer. The method further comprises directing a radiation beam (e.g., EUV or DUV light) from radiation source SO to transfer a pattern from a mask onto the photoresist layer. This could be achieved by a patterning device which is configured to form a patterned radiation beam, imparting the patterned radiation beam onto the photoresist layer. The method for manufacturing a semiconductor device further comprises the step of removing a portion of the photoresist layer to form the pattern over the substrate W.

[0087] The substrate W may be made of silicon or other semiconductor materials. Alternatively or additionally, the substrate W may include other semiconductor materials such as germanium (Ge) or carbon (C). In some embodiments, the semiconductor substrate is made of a compound semiconductor such as III-V compound semiconductors, II-V compound semiconductors, and / or any suitable integration of Group IV materials. In some embodiments, the substrate W may be a silicon-on-insulator (SOI) or a germanium -on-insulator (GOI) substrate.

[0088] The semiconductor device made from the substrate W may have various device elements. Examples of semiconductor device elements that are formed over the substrate W include transistors (e.g., planar or non-planar metal oxide semiconductor field effect transistors (MOSFET), bipolar junction transistors (BJT), high-voltage transistors, high-frequency transistors, etc.), diodes, CMOS image sensors, passive devices, and / or other applicable elements. Various processes may be performed to form the semiconductor device elements, such as deposition, etching, implantation, epitaxial growth, polishing, thermal treatment, and / or other suitable processes. In some embodiments, the substrate W is coated with a photoresist layer sensitive to the EUV light.

[0089] The embodiments may further be described using the following clauses:1. A metrology system comprising:a radiation source configured to irradiate a target to generate scattered radiation from the target; an optical fiber positioned to transmit the scattered radiation to a detector; a programmable processor; and a non-transitory computer readable medium having instructions recorded thereon, the instructions when executed by a computer having the programmable processor causing operations comprising: generating a fiber input image of at least a portion of the target; and determining a distortion of the fiber input image; and determining a deviation of the target based at least on correcting for the distortion.2. The metrology system of clause 1, wherein the fiber input image is of a beam profile of the scattered radiation.3. The metrology system of clause 1, wherein the deviation is an alignment position deviation.4. The metrology system of clause 1, wherein the deviation is an overlay.5. The metrology system of clause 1, wherein the distortion is a shift in a center of gravity(COG) of the fiber input image and the operations further comprising determining the COG of the fiber input image based on a fiber output image.6. The metrology system of clause 5, the operations further comprising: reconstructing, by a first machine-leaning model, a fiber input image from the fiber output image; determining a COG of the fiber input image; and calculating the distortion as a difference between the COG of the fiber output image and the COG of the fiber input image.7. The metrology system of clause 5, the operations further comprising predicting, by a second machine-learning model, the COG of the fiber input image.8. The metrology system of clause 7, wherein the second machine-learning model is a convolutional neural network.9. The metrology system of clause 7, wherein the second machine-learning model is a dense neural network having at least two hidden layers.10. The metrology system of clause 1, wherein the optical fiber is an Anderson localization (AL) optical fiber.11. The metrology system of clause 10, wherein the AL optical fiber has a fill ratio of between 20% and 55%.12. The metrology system of clause 11, wherein the AL optical fiber has a fill ratio of between 46% and 52%.13. The metrology system of clause 10, wherein the AL optical fiber comprises a bent portion.14. The metrology system of clause 13, wherein determining the distortion in the fiber input image comprises utilizing a machine -learning model trained with data from the AL optical fiber with the bent portion to calculate or predict the distortion.15. The metrology system of clause 14, wherein the machine -learning model is trained with the AL optical fiber with the bent portion that is also used for obtaining the scattered radiation from the target.16. A non-transitory computer readable medium having instructions recorded thereon, the instructions when executed by a computer having the programmable processor causing operations comprising: generating a fiber input image of at least a portion of the target; and determining a distortion of the fiber input image; and determining a deviation of the target based at least on correcting for the distortion.17. The computer readable medium of clause 16, wherein the distortion is a shift in a center of gravity (COG) of the fiber input image and the operations further comprising determining the COG of the fiber input image based on a fiber output image.18. The computer readable medium of clause 16, wherein the optical fiber is an Anderson localization (AL) optical fiber and the AL optical fiber comprises a bent portion, the operations further comprising determining the distortion in the fiber input image comprises utilizing a machinelearning model trained with data from the AL optical fiber with the bent portion to calculate or predict the distortion.19. The computer readable medium of clause 16, the operations further comprising training the machine-learning model with the AL optical fiber with the bent portion that is also used for obtaining the scattered radiation from the target.20. A semiconductor device manufacturing method comprising receiving a substrate with a photoresist layer, the method comprising: directing (EUV / DUV) radiation from a radiation source to transfer a pattern from a mask onto the photoresist layer; removing a portion of the photoresist layer to form the pattern over the substrate; generating a fiber input image of at least a portion of the substrate; determining a distortion of the fiber input image; and determining a deviation of the substrate based at least on correcting for the distortion.

[0090] While the concepts disclosed herein may be used for imaging on a substrate such as a silicon wafer, it shall be understood that the disclosed concepts may be used with any type of lithographic imaging systems, e.g., those used for imaging on substrates other than silicon wafers.

[0091] The combinations and sub-combinations of the elements disclosed herein constitute separate embodiments and are provided as examples only. Also, the descriptions above are intended to beillustrative, not limiting. Thus, it will be apparent to one skilled in the art that modifications may be made as described without departing from the scope of the claims set out below.

Claims

CLAIMS1. A metrology system comprising: a radiation source configured to irradiate a target to generate scattered radiation from the target; an optical fiber positioned to transmit the scattered radiation to a detector; a programmable processor; and a non-transitory computer readable medium having instructions recorded thereon, the instructions when executed by a computer having the programmable processor causing operations comprising: generating a fiber input image of at least a portion of the target; and determining a distortion of the fiber input image; and determining a deviation of the target based at least on correcting for the distortion.

2. The metrology system of claim 1, wherein the fiber input image is of a beam profile of the scattered radiation.

3. The metrology system of claim 1, wherein the deviation is an alignment position deviation.

4. The metrology system of claim 1, wherein the deviation is an overlay.

5. The metrology system of claim 1, wherein the distortion is a shift in a center of gravity(COG) of the fiber input image and the operations further comprising determining the COG of the fiber input image based on a fiber output image.

6. The metrology system of claim 5, the operations further comprising: reconstructing, by a first machine-leaning model, a fiber input image from the fiber output image; determining a COG of the fiber input image; and calculating the distortion as a difference between the COG of the fiber output image and the COG of the fiber input image.

7. The metrology system of claim 5, the operations further comprising predicting, by a second machine-learning model, the COG of the fiber input image.

8. The metrology system of claim 7, wherein the second machine -learning model is a convolutional neural network.

9. The metrology system of claim 7, wherein the second machine -learning model is a dense neural network having at least two hidden layers.

10. The metrology system of claim 1, wherein the optical fiber is an Anderson localization (AL) optical fiber.

11. The metrology system of claim 10, wherein the AL optical fiber has a fill ratio of between 20% and 55%.

12. The metrology system of claim 11, wherein the AL optical fiber has a fill ratio of between 46% and 52%.

13. The metrology system of claim 10, wherein the AL optical fiber comprises a bent portion.

14. The metrology system of claim 13, wherein determining the distortion in the fiber input image comprises utilizing a machine-learning model trained with data from the AL optical fiber with the bent portion to calculate or predict the distortion.

15. The metrology system of claim 14, wherein the machine-learning model is trained with the AL optical fiber with the bent portion that is also used for obtaining the scattered radiation from the target.

Images