Image-to-design alignment of images with color or other variations suitable for real-time applications

Abstract

Methods and systems are provided for determining information of a sample. A system includes a model configured to generate a rendered image of an alignment target on a sample from information for a design of the alignment target. The rendered image is a simulation of an image of the alignment target on the sample generated by an imaging subsystem. The system also includes parameters configured to modify the model based on variations in parameters of the imaging subsystem and / or variations in process conditions used to manufacture the sample. After the modification, the computer subsystem is configured to generate an additional rendered image of the alignment target by inputting the information of the design of the alignment target into the model and align the additional rendered image to an image of the alignment target generated by the imaging subsystem.

Description

Technical Field

[0001] The present invention generally relates to methods and systems for determining information of a sample. Certain embodiments relate to modifying a model used to generate a rendered alignment target image based on imaging subsystem parameter variations and / or process condition variations and using the modified model to generate a rendered alignment target image to align with a sample image. Background Art

[0002] The following description and examples are not admitted to be prior art by inclusion in this section.

[0003] The manufacture of semiconductor devices such as logic and memory devices typically includes processing a substrate (e.g., a semiconductor wafer) using a number of semiconductor manufacturing processes to form various features and multiple levels of the semiconductor device. For example, photolithography is a semiconductor manufacturing process that involves transferring a pattern from a reticle to a photoresist arranged on a semiconductor wafer. Additional examples of semiconductor manufacturing processes include, but are not limited to, chemical mechanical polishing (CMP), etching, deposition, and ion implantation. Multiple semiconductor devices may be manufactured in an arrangement on a single semiconductor wafer and then separated into individual semiconductor devices.

[0004] Inspection processes are used at various steps during the semiconductor manufacturing process to detect defects on samples to drive higher yields and therefore higher profits in the manufacturing process. Inspection has always been an important part of manufacturing semiconductor devices. However, as the size of semiconductor devices decreases, inspection becomes more important to the successful manufacture of acceptable semiconductor devices because smaller defects may cause device failure.

[0005] Defect review typically involves re-inspecting defects that were themselves detected by the inspection process and generating additional information about the defects at a higher resolution using a high magnification optical system or a scanning electron microscope (SEM). Thus, defect review is performed at discrete locations on the sample where defects have been detected by inspection. The higher resolution data of defects generated by defect review is more suitable for determining properties of the defects, such as contour, roughness, more accurate size information, etc. Defects can often be more accurately classified into defect types based on the information determined by defect review than by inspection.

[0006] Metrology processes are also used at various steps during the semiconductor manufacturing process to monitor and control the process. Metrology processes differ from inspection processes because, unlike inspection processes in which defects are detected on a sample, metrology processes are used to measure one or more characteristics of a sample that cannot be determined using currently used inspection tools. For example, metrology processes are used to measure one or more characteristics of a sample (e.g., dimensions of features formed on the sample during a process (e.g., line width, thickness, etc.)) so that the performance of the process can be determined from the one or more characteristics. Additionally, if one or more characteristics of a sample are unacceptable (e.g., outside a predetermined range of characteristics), the measurement of the one or more characteristics of the sample can be used to alter one or more parameters of the process so that additional samples manufactured by the process have acceptable characteristics.

[0007] The metrology process also differs from the defect review process because, unlike the defect review process in which defects detected by inspection are revisited in the defect review, the metrology process may be performed at locations where defects have not yet been detected. In other words, unlike defect review, the location at which the metrology process is performed on the sample may be independent of the results of the inspection process performed on the sample. In particular, the location at which the metrology process is performed may be selected independently of the inspection results. Additionally, because the location on the sample at which the metrology is performed may be selected independently of the inspection results, unlike defect review in which the location on the sample at which the defect review is to be performed cannot be determined until the inspection results of the sample are generated and available for use, the location at which the metrology process is performed may be determined before the inspection process has been performed on the sample.

[0008] One aspect of the methods and systems described above that can be difficult is knowing where on a sample a result (e.g., a measurement, a detected defect, a re-detected defect, etc.) was produced. For example, the tools and processes described above are used to determine information about structures and / or defects on a sample. Because structures vary across samples (such that they may form functional devices on the sample), measurement, inspection, or defect review results are generally useless unless it is precisely known where on the sample they were produced. In the metrology example, unless the measurement is performed at a known predetermined location on the sample, the measurement may be invalid if the measurement location does not contain the portion of the sample that is desired to be measured and / or the measurement of one portion of the sample is assigned to another portion of the sample. In the case of inspection, unless defect detection is performed at a known predetermined area on the sample (e.g., in a region of interest (CA)), the inspection may not be performed in the expected manner. In addition, unless the defect location on the sample is determined substantially accurately, the defect location may be inaccurately determined relative to the sample and / or the design of the sample. In any case, an error in the location on the sample where a result is produced can render the result useless, and if the result is used to make changes to the manufacturing process, can even be detrimental to the manufacturing process.

[0009] An image or other output generated for a sample by one of the tools described above can be aligned to a common reference in several different ways. When alignment needs to be performed substantially quickly, many alignment processes attempt to perform alignment faster by aligning one image generated for the sample to another substantially similar image that is available on demand or can be quickly generated if the CA placement is determined when scanning the sample during inspection. For example, in the case of optical inspection, the alignment process can be designed to align the real optical image of the sample generated by the inspection tool to a rendered optical image that was generated and stored prior to the inspection and can be quickly accessed during the inspection. The alignment of the real and rendered optical images can be performed only for the alignment target on the sample and then any coordinate transformations determined thereby can be applied to other real optical images of the sample generated during scanning. When the rendered optical image was previously aligned to a reference coordinate system, the real optical image can also be aligned to the same reference coordinate system as the design coordinates of the design of the sample.

[0010] However, there are several disadvantages in these alignment methods. For example, the image of the sample generated during the process of inspection can change in a way that is difficult to predict. The image of the sample can change from sample to sample or even across samples, which makes it difficult to use the same previously generated and stored alignment target image. For example, the real optical image may be different from the expected alignment of the image to the previously generated and stored alignment target image to a degree that is basically difficult or even unfeasible. Errors in the alignment of the real image to the presented image can have significant and even catastrophic effects on the process described above. For example, if the inspection tool incorrectly aligns the real optical image to the previously generated and stored presented image, the CA may be incorrectly positioned in the real optical image. The incorrectly positioned CA may have several different effects on the inspection results, including but not limited to errors in any results of missing defects, wrongly detected defects, and the analysis of detected defects. If the inspection results with such errors are used to correct the manufacturing process performed on the sample, then this may have even further catastrophic results, such as pushing the manufacturing process that works correctly out of its process window or pushing the manufacturing process outside its process window out of its process window even further.

[0011] Therefore, it would be advantageous to develop systems and methods for determining information of a sample that do not have one or more of the disadvantages described above. Summary of the invention

[0012] The following description of various embodiments should in no way be construed as limiting the subject matter of the appended claims.

[0013] One embodiment relates to a system configured to determine information of a sample. The system includes an imaging subsystem configured to generate an image of the sample. The system also includes a model configured to generate a rendered image of the alignment target on the sample from information for the design of the alignment target. The rendered image is a simulation of the image of the alignment target on the sample generated by the imaging subsystem. The system further includes a computer subsystem configured to modify one or more parameters of the model based on one or more changes in one or more parameters of the imaging subsystem and changes in one or more process conditions for manufacturing the sample. After the modification, the computer subsystem is configured to generate an additional rendered image of the alignment target by inputting the information for the design of the alignment target into the model. In addition, the computer subsystem is configured to align the additional rendered image to at least one of the images of the alignment target generated by the imaging subsystem. The computer subsystem is further configured to determine the information of the sample based on the results of the alignment. The system can be further configured as described herein.

[0014] Another embodiment relates to a method for determining information of a sample. The method includes acquiring an image of the sample generated by an imaging subsystem. The method also includes the modifying, generating, aligning, and determining steps described above performed by a computer subsystem coupled to the imaging subsystem. Each step of the method may be performed as further described herein. The method may include any other steps of any other method described herein. The method may be performed by any system described herein.

[0015] Another embodiment relates to a non-transitory computer-readable medium storing program instructions that can be executed on a computer system to perform a computer-implemented method for determining information of a sample. The computer-implemented method includes the steps of the method described above. The computer-readable medium can be further configured as described herein. The steps of the computer-implemented method can be performed as further described herein. In addition, the computer-implemented method for which the program instructions can be executed can include any other steps of any other method described herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Further advantages of the present invention will become apparent to those skilled in the art with the benefit of the following detailed description of the preferred embodiments and when reference is made to the accompanying drawings, in which:

[0017] Figures 1 to 2 is a schematic diagram illustrating a side view of an embodiment of a system configured as described herein;

[0018] Figure 3an example of a rendered image of an alignment target on a sample that differs from an image of the alignment target produced by an imaging subsystem due to variations in one or more parameters of the imaging subsystem;

[0019] Figure 4 is a schematic diagram illustrating a side view of an embodiment of an imaging subsystem and how an embodiment of a model generates a rendered image of an alignment target on a sample from information for the design of the alignment target;

[0020] Figure 5 Include Figure 3 and examples of additional rendered images of an alignment target on a sample that are substantially similar to an image of the alignment target produced by an imaging subsystem due to modification of one or more parameters of embodiments of the model described herein that may be performed in accordance with embodiments described herein;

[0021] Figure 6 is a flow chart illustrating one embodiment of steps that may be performed to determine whether an image generated by a model or a modified model should be used for image alignment;

[0022] Figure 7 is a plot illustrating examples of results produced using currently used image alignment processes and embodiments of image alignment described herein; and

[0023] Figure 8 is a block diagram illustrating one embodiment of a non-transitory computer-readable medium storing program instructions for causing a computer system to perform the computer-implemented methods described herein.

[0024] Although the invention is susceptible to various modifications and alternative forms, specific embodiments of the invention are shown by way of example in the drawings and described in detail herein. The drawings may not be to scale. However, it should be understood that the drawings and detailed description thereof are not intended to limit the invention to the specific forms disclosed, but on the contrary, are intended to cover all modifications, equivalents and alternatives falling within the spirit and scope of the invention as defined by the appended claims. DETAILED DESCRIPTION

[0025] The terms "design", "design data", and "design information" as used interchangeably herein generally refer to the physical design (layout) of an IC or other semiconductor device and data derived from the physical design by complex simulations or simple geometric and Boolean operations. The design may include any other design data or design data proxy described in co-owned U.S. Pat. No. 7,570,796 issued to Zafar et al. on Aug. 4, 2009 and co-owned U.S. Pat. No. 7,676,077 issued to Kulkarni et al. on Mar. 9, 2010, both of which are incorporated herein by reference as if fully set forth. In addition, the design data may be standard cell library data, integrated layout data, design data for one or more layers, derivatives of the design data, and full or partial chip design data. Furthermore, the "design", "design data", and "design information" described herein refer to information and data generated by a semiconductor device designer in the design process and thus can be used in the embodiments described herein well before the design is printed on any physical samples (e.g., reticles and wafers).

[0026] Referring now to the drawings, it should be noted that the drawings are not drawn to scale. In particular, the proportions of some elements of the drawings are greatly exaggerated to emphasize the characteristics of the elements. It should also be noted that the drawings are not drawn to the same scale. The same reference numerals have been used to indicate similarly configurable elements shown in more than one figure. Unless otherwise mentioned herein, any element described and shown may include any suitable commercially available element.

[0027] In general, the embodiments described herein are systems and methods for determining information of a sample. The embodiments described herein provide improved systems and methods for pixel-to-design (PDA) alignment for applications such as defect detection. The embodiments described herein also provide an adaptive PDA method that can be adapted in several ways further described herein, thereby providing several important improvements over currently used PDA methods and systems. For example, the embodiments described herein improve the accuracy and robustness of existing PDA methods by extending the rendering model accuracy to include defocus and / or by adding adaptive rendering during inspection to account for run-time sample process variations.

[0028] In some embodiments, the sample is a wafer. The wafer may include any wafer known in semiconductor technology. Although some embodiments are described herein with respect to a wafer or a plurality of wafers, the embodiments are not limited to the samples to which they may be applied. For example, the embodiments described herein may be applied to samples such as reticles, flat panels, personal computer (PC) boards, and other semiconductor samples.

[0029] exist Figure 1One embodiment of a system configured for determining information of a sample is shown in . The system includes an imaging subsystem 100 configured for generating an image of the sample. The imaging subsystem includes and / or is coupled to a computer subsystem, such as computer subsystem 36 and / or one or more computer systems 102.

[0030] In general, the imaging subsystems described herein include at least one energy source, a detector, and a scanning subsystem. The energy source is configured to generate energy directed to a sample by the imaging subsystem. The detector is configured to detect energy from the sample and generate an output in response to the detected energy. The scanning subsystem is configured to change the location on the sample to which the energy is directed and from which the energy is detected. In one embodiment, Figure 1 , the imaging subsystem is configured as a light-based subsystem.

[0031] In the light-based imaging subsystems described herein, the energy directed to the sample comprises light, and the energy detected from the sample comprises light. Figure 1 In an embodiment of the system shown in FIG. 1 , the imaging subsystem includes an illumination subsystem configured to direct light to the sample 14. The illumination subsystem includes at least one light source. For example, Figure 1 , the illumination subsystem includes a light source 16. The illumination subsystem is configured to direct light to the sample at one or more incident angles, which may include one or more oblique angles and / or one or more normal angles. Figure 1 , light from light source 16 is directed at an oblique angle of incidence through optical element 18 and then through lens 20 to sample 14. The oblique angle of incidence may include any suitable oblique angle of incidence, which may vary depending on, for example, the characteristics of the sample and the process being performed on the sample.

[0032] The illumination subsystem may be configured to direct light to the sample at different incident angles at different times. For example, the imaging subsystem may be configured to modify one or more characteristics of one or more elements of the illumination subsystem so that light can be directed to the sample at different incident angles. Figure 1 In one such example, the imaging subsystem can be configured to move the light source 16, optical element 18, and lens 20 so that light is directed to the sample at different oblique angles of incidence or normal (or near-normal) angles of incidence.

[0033] In some examples, the imaging subsystem may be configured to direct light to the sample at more than one incident angle simultaneously. For example, the illumination subsystem may include more than one illumination channel, one of which may include, for example, Figure 1, and another of the illumination channels (not shown) may include similar elements that may be configured differently or identically or may include at least one light source and possibly one or more other elements (such as those described further herein). If this light is directed to the sample simultaneously with other light, one or more characteristics (e.g., wavelength, polarization, etc.) of the light directed to the sample at different angles of incidence may be different, so that light resulting from illumination of the sample at different angles of incidence may be distinguished from one another at a detector.

[0034] In another example, the illumination subsystem may include only one light source (e.g., Figure 1 ) and the light from the light source may be separated into different optical paths by one or more optical elements (not shown) of the illumination subsystem (e.g., based on wavelength, polarization, etc.). The light in each of the different optical paths may then be directed to the sample. Multiple illumination channels may be configured to direct light to the sample simultaneously or at different times (e.g., when different illumination channels are used to sequentially illuminate the sample). In another example, the same illumination channel may be configured to direct light with different characteristics to the sample at different times. For example, the optical element 18 may be configured as a spectral filter and the properties of the spectral filter may be changed in a variety of different ways (e.g., by swapping out one spectral filter with another spectral filter) so that light of different wavelengths may be directed to the sample at different times. The illumination subsystem may have any other suitable configuration known in the art for directing light with different or the same characteristics to the sample sequentially or simultaneously at different or the same angles of incidence.

[0035] The light source 16 may include a broadband plasma (BBP) light source. In this manner, the light generated by the light source and directed to the sample may include broadband light. However, the light source may include any other suitable light source, such as any suitable laser known in the art that is configured to generate light of any suitable wavelength. The laser may be configured to generate monochromatic or near-monochromatic light. In this manner, the laser may be a narrowband laser. The light source may also include a polychromatic light source that generates light of multiple discrete wavelengths or bands.

[0036] Light from the optical element 18 can be focused onto the sample 14 by the lens 20. Figure 1 Lens 20 is shown in FIG. 2 as a single refractive optical element, but in practice, lens 20 may include several refractive and / or reflective optical elements that combine to focus light from the optical element onto the sample. Figure 1The illumination subsystem shown in and described herein may include any other suitable optical elements (not shown). Examples of such optical elements include, but are not limited to, polarizing components, spectral filters, spatial filters, reflective optical elements, apodizers, beam splitters, apertures, and the like, which may include any such suitable optical elements known in the art. Additionally, the system may be configured to alter one or more elements of the illumination subsystem based on the type of illumination to be used to generate the image.

[0037] The imaging subsystem may also include a scanning subsystem configured to change the location on the sample to which light is directed and from which light is detected, and possibly cause the light to be scanned across the sample. For example, the imaging subsystem may include a stage 22 on which the sample 14 is placed during imaging. The scanning subsystem may include any suitable mechanical and / or robotic assembly (including the stage 22) that may be configured to move the sample so that light can be directed to different locations on the sample and detected from different locations on the sample. Additionally or alternatively, the imaging subsystem may be configured so that one or more optical elements of the imaging subsystem perform a certain scan of light across the sample so that light can be directed to different locations on the sample and detected from different locations on the sample. In examples where light is scanned across the sample, the light may be scanned across the sample in any suitable manner, such as in a serpentine path or in a spiral path.

[0038] The imaging subsystem further includes one or more detection channels. At least one of the detection channels includes a detector configured to detect light from the sample as a result of illumination of the sample by the imaging subsystem and to generate an output in response to the detected light. For example, Figure 1 The imaging subsystem shown in FIG. 1 includes two detection channels, one detection channel formed by light collector 24, element 26 and detector 28 and the other detection channel formed by light collector 30, element 32 and detector 34. Figure 1 , two detection channels are configured to collect and detect light at different collection angles. In some examples, the two detection channels are configured to detect scattered light, and the detection channels are configured to detect light scattered from the sample at different angles. However, one or more detection channels can be configured to detect another type of light from the sample (e.g., reflected light).

[0039] like Figure 1As further shown in FIG, two detection channels are shown as being positioned in the plane of the paper and the illumination subsystem is also shown as being positioned in the plane of the paper. Thus, in this embodiment, the two detection channels are positioned (e.g., centered) in the plane of incidence. However, one or more detection channels may be positioned outside the plane of incidence. For example, the detection channel formed by the light collector 30, the element 32, and the detector 34 may be configured to collect and detect light scattered from the plane of incidence. Thus, such detection channels may be collectively referred to as "side" channels, and such side channels may be centered in a plane substantially perpendicular to the plane of incidence.

[0040] Although Figure 1 An embodiment of an imaging subsystem including two detection channels is shown, but the imaging subsystem may include a different number of detection channels (e.g., only one detection channel or two or more detection channels). In one such example, the detection channel formed by the light collector 30, the element 32, and the detector 34 may form a side channel as described above, and the imaging subsystem may include an additional detection channel (not shown) formed as another side channel positioned on the opposite side of the incident plane. Thus, the imaging subsystem may include a detection channel that includes the light collector 24, the element 26, and the detector 28 and is centered in the incident plane and is configured to collect and detect light at a scattering angle normal to or close to normal to the sample surface. Thus, this detection channel may be collectively referred to as a "top" channel, and the imaging subsystem also includes two or more side channels configured as described above. Thus, the imaging subsystem may include at least three channels (i.e., one top channel and two side channels), and each of the at least three channels has its own light collector, each light collector being configured to collect light at a scattering angle different from each other light collector.

[0041] As further described above, each detection channel included in the imaging subsystem can be configured to detect scattered light. Figure 1 The imaging subsystem shown in can be configured for dark field (DF) imaging of the sample. However, the imaging subsystem may also or alternatively include a detection channel configured for bright field (BF) imaging of the sample. In other words, the imaging subsystem may include at least one detection channel configured to detect light specularly reflected from the sample. Thus, the imaging subsystem described herein may be configured for only DF imaging, only BF imaging, or both DF imaging and BF imaging. Although in Figure 1 Each light collector is shown as a single refractive optical element in , but each light collector may include one or more refractive optical elements and / or one or more reflective optical elements.

[0042] One or more detection channels may include any suitable detector known in the art, such as a photomultiplier tube (PMT), a charge coupled device (CCD), and a time-delay integration (TDI) camera. The detector may also include a non-imaging detector or an imaging detector. If the detector is a non-imaging detector, each detector may be configured to detect certain characteristics of the scattered light (e.g., intensity) but may not be configured to detect such characteristics that vary depending on the position within the imaging plane. Thus, the output generated by each detector in each detection channel included in the imaging subsystem may be a signal or data rather than an image signal or image data. In such examples, a computer subsystem (e.g., computer subsystem 36) may be configured to generate an image of the sample from the non-imaging output of the detector. However, in other examples, the detector may be configured as an imaging detector configured to generate an imaging signal or image data. Thus, the imaging subsystem may be configured to generate an image in a number of ways.

[0043] It should be noted that in this article Figure 1 to generally illustrate configurations of imaging subsystems that may be included in embodiments of the systems described herein. Obviously, the imaging subsystem configurations described herein may be altered to optimize the performance of the imaging subsystem as is typically performed when designing commercial systems. Additionally, the systems described herein may be implemented using existing systems (e.g., by adding the functionality described herein to the existing systems) such as the 29xx / 39xx series of tools commercially available from KLA, Inc. of Milpitas, California. For some such systems, the methods described herein may be provided as optional functionality of the system (e.g., in addition to other functionality of the system). Alternatively, the systems described herein may be designed "from the ground up" to provide an entirely new system.

[0044] The computer subsystem 36 may be coupled to the detector of the imaging subsystem in any suitable manner (e.g., via one or more transmission media, which may include "wired" and / or "wireless" transmission media) such that the computer subsystem may receive output generated by the detector. The computer subsystem 36 may be configured to perform a number of functions with or without the output of the detector (including the steps and functions further described herein). Thus, the steps described herein may be performed "on the tool" by a computer subsystem that is coupled to or is part of the imaging subsystem. Additionally or alternatively, the computer system 102 may perform one or more of the steps described herein. Thus, one or more of the steps described herein may be performed "off the tool" by a computer system that is not directly coupled to the imaging subsystem. The computer subsystem 36 and the computer system 102 may be further configured as described herein.

[0045] The computer subsystem 36 (and other computer subsystems described herein) may also be referred to herein as a computer system. Each of the computer subsystems or systems described herein may take various forms, including a personal computer system, an image computer, a mainframe computer system, a workstation, a network appliance, an Internet appliance, or other devices. In general, the term "computer system" may be broadly defined to encompass any device having one or more processors that execute instructions from a memory medium. The computer subsystem or system may also include any suitable processor known in the art (e.g., a parallel processor). In addition, the computer subsystem or system may include a computer platform (as a stand-alone tool or a network-linked tool) with high-speed processing and software.

[0046] If the system includes more than one computer subsystem, the different computer subsystems may be coupled to each other so that images, data, information, instructions, etc. may be sent between the computer subsystems. For example, the computer subsystem 36 may be coupled to the computer subsystem 36 via any suitable transmission media, such as a wireless transmission media, which may include any suitable wired and / or wireless transmission media known in the art. Figure 1 The dashed line in is shown as being coupled to computer system 102. Two or more such computer subsystems may also be operatively coupled via a shared computer-readable storage medium (not shown).

[0047] Although the imaging subsystem is described above as an optical or light-based imaging subsystem, in another embodiment, the imaging subsystem is configured as an electron-based subsystem. In an electron beam imaging subsystem, the energy directed to the sample includes electrons, and the energy detected from the sample includes electrons. Figure 2 In one such embodiment shown in FIG. 1 , the imaging subsystem includes an electron column 122, and the system includes a computer subsystem 124 coupled to the imaging subsystem. The computer subsystem 124 may be configured as described above. In addition, the imaging subsystem may be configured as described above and in Figure 1 can be coupled to another or more computer systems in the same manner as shown in FIG.

[0048] Also like Figure 2 , the electron column includes an electron beam source 126 configured to produce electrons that are focused by one or more elements 130 to a sample 128. The electron beam source may include, for example, a cathode source or emitter tip, and the one or more elements 130 may include, for example, a gun lens, an anode, a beam limiting aperture, a gate valve, a beam current selection aperture, an objective lens, and a scanning subsystem, all of which may include any such suitable elements known in the art.

[0049] Electrons returning from the sample (eg, secondary electrons) may be focused by one or more elements 132 onto a detector 134. One or more elements 132 may include, for example, a scanning subsystem, which may be the same scanning subsystem included in element 130.

[0050] The electron column may include any other suitable elements known in the art. In addition, the electron column may be further configured as described in U.S. Pat. No. 8,664,594 issued to Jiang et al. on April 4, 2014, U.S. Pat. No. 8,692,204 issued to Kojima et al. on April 8, 2014, U.S. Pat. No. 8,698,093 issued to Gubbens et al. on April 15, 2014, and U.S. Pat. No. 8,716,662 issued to MacDonald et al. on May 6, 2014, which are incorporated herein by reference as if fully set forth.

[0051] Although in Figure 2 , the electron beam is shown as being configured so that electrons are directed to the sample at an oblique angle of incidence and scattered from the sample at another oblique angle, but the electron beam may be directed to the sample and scattered from the sample at any suitable angle. In addition, the electron beam imaging subsystem may be configured to use multiple modes (e.g., using different illumination angles, collection angles, etc.) to generate an image of the sample, as further described herein. The multiple modes of the electron beam imaging subsystem may be different in any imaging parameter of the imaging subsystem.

[0052] The computer subsystem 124 may be coupled to a detector 134, as described above. The detector may detect electrons returning from the surface of the sample, thereby forming an electron beam image of the sample (or other output for the sample). The electron beam image may include any suitable electron beam image. The computer subsystem 124 may be configured to determine information about the sample using the output generated by the detector 134, which may be performed as further described herein. The computer subsystem 124 may be configured to perform any additional steps described herein. The computer subsystem 124 may be further configured as described herein to include Figure 2 The imaging subsystem of the system is shown in FIG.

[0053] It should be noted that in this article Figure 2to generally illustrate configurations of electron beam imaging subsystems that may be included in the embodiments described herein. As with the optical subsystems described above, the electron beam subsystem configurations described herein may be modified to optimize the performance of the imaging subsystem as is typically performed when designing a commercial system. Additionally, the systems described herein may be implemented using existing systems such as tools commercially available from KLA (e.g., by adding the functionality described herein to the existing system). For some such systems, the methods described herein may be provided as optional functionality of the system (e.g., in addition to other functionality of the system). Alternatively, the systems described herein may be designed "from scratch" to provide an entirely new system.

[0054] Although the imaging subsystem is described above as a light or electron beam subsystem, the imaging subsystem may be an ion beam imaging subsystem. Figure 2 This imaging subsystem is configured as shown in FIG. 1 , except that any suitable ion beam source known in the art may be used in place of the electron beam source. Additionally, the imaging subsystem may include any other suitable ion beam imaging system, such as those included in commercially available focused ion beam (FIB) systems, helium ion microscope (HIM) systems, and secondary ion mass spectrometer (SIMS) systems.

[0055] As further mentioned above, the imaging subsystem may be configured to have multiple modes. In general, a "mode" is defined by the value of a parameter of the imaging subsystem used to generate an image of the sample. Thus, different modes may differ in the value of at least one imaging parameter of the imaging subsystem (in addition to the location on the sample at which the image is generated). For example, for a light-based imaging subsystem, different modes may use light of different wavelengths. The modes may differ in the wavelength of light directed to the sample (e.g., by using different light sources, different spectral filters, etc. for different modes), as further described herein. In another embodiment, different modes may use different illumination channels. For example, as mentioned above, the imaging subsystem may include more than one illumination channel. Thus, different illumination channels may be used for different modes.

[0056] The multiple modes may also differ in illumination and / or light collection / detection. For example, as further described above, the imaging subsystem may include multiple detectors. Thus, one detector may be used for one mode and another detector may be used for another mode. In addition, the modes may differ from each other in more than one manner described herein (e.g., different modes may have one or more different illumination parameters and one or more different detection parameters). In addition, the multiple modes may differ in angle, meaning having either or both of different angles of incidence and collection angles, which may be achieved as further described above. For example, depending on the ability to scan a sample simultaneously using multiple modes, the imaging subsystem may be configured to scan a sample using different modes in the same scan or in different scans.

[0057] In another embodiment, the imaging subsystem is configured as an inspection subsystem. The inspection subsystem can be configured to perform inspection using light, electrons, or another energy type (e.g., ions). Figure 1 and 2 . In a system where the imaging subsystem is configured as an inspection subsystem, the computer subsystem may be configured to detect defects on a sample based on the output generated by the imaging subsystem. For example, in the simplest possible scenario, the computer subsystem may subtract a reference from an image, thereby generating a differential image and then applying a threshold to the differential image. The computer subsystem may determine that any differential image having a value above the threshold contains a defect or potential defect and any differential image having a value below the threshold does not contain a defect or potential defect. Of course, many defect detection methods and algorithms used on commercially available inspection tools are much more complex than this example, and any such method or algorithm may be applied to the output generated by an imaging subsystem configured as an inspection subsystem.

[0058] The systems described herein may also or alternatively be configured as another type of semiconductor-related quality control system, such as a defect inspection system and a metrology system. For example, the systems described herein and described in the examples may be modified in terms of one or more parameters. Figures 1 to 2 The embodiments of the imaging subsystem shown in FIG. 1 provide different imaging capabilities depending on the application in which it is to be used. In one embodiment, the imaging subsystem is configured as an electron beam defect inspection subsystem. For example, Figure 2 The imaging subsystem shown in FIG. 1 may be configured to have higher resolution in the case where it is to be used for defect inspection or metrology rather than for inspection. In other words, Figures 1 to 2 The embodiments of the imaging subsystem shown in describe some general and various configurations of the imaging subsystem, which can be customized in a number of ways that will be apparent to those skilled in the art to produce imaging subsystems with different imaging capabilities that are more or less suitable for different applications.

[0059] As mentioned above, the imaging subsystem may be configured to direct energy (e.g., light, electrons) to and / or scan energy across a physical version of the sample, thereby producing an actual (or "real") image of the physical version of the sample. In this manner, the imaging subsystem may be configured as a "real" imaging system rather than a "virtual" system. However, Figure 1The storage medium (not shown) and computer subsystem 102 shown in and / or other computer subsystems shown and described herein may be configured as a "virtual" system. In particular, the storage medium and computer system 102 are not part of the imaging subsystem 100 and do not have any capabilities for handling physical versions of the sample but may be configured as a virtual inspector that performs inspection-like functions using stored detector outputs, a virtual metrology system that performs metrology-like functions, a virtual defect review tool that performs defect review-like functions, etc. Systems and methods configured as "virtual" systems are described in the commonly assigned U.S. Patent No. 8,126,255 issued to Bhaskar et al. on February 28, 2012; U.S. Patent No. 9,222,895 issued to Duffy et al. on December 29, 2015; and U.S. Patent No. 9,816,939 issued to Duffy et al. on November 14, 2017, which are incorporated herein by reference as if fully set forth. The embodiments described herein may be further configured as described in these patents. For example, the computer subsystems described herein may be further configured as described in these patents.

[0060] A system consists of one or more components that are executed by a computer subsystem. Figure 1 1, the system includes one or more components 104 executed by computer subsystem 36 and / or computer system 102. The systems shown in other figures described herein may be configured to include similar elements. One or more components may be executed by the computer subsystem as further described herein or in any other suitable manner known in the art. At least part of executing one or more components may include inputting one or more inputs (e.g., images, data, etc.) into the one or more components. The computer subsystem may be configured to input any design data, information, etc. into the one or more components in any suitable manner.

[0061] Although some embodiments are described herein with respect to "alignment targets", it is apparent that the embodiments described herein may be performed on the same sample and in the same procedure for more than one alignment target. One or more of the alignment targets on the sample may be different, or all of the alignment targets may be the same. The alignment target may be any suitable alignment target known in the art that may be selected in any suitable manner known in the art. Information for alignment targets that may be used for one or more steps described herein may be obtained by the embodiments described herein in any suitable manner. For example, a computer subsystem configured as described herein may obtain information for alignment targets from a storage medium in which information has been stored by the computer subsystem itself or by another system or method. In some examples, the results generated by the embodiments described herein may be applied to or used for more than one instance of an alignment target having the same design and formed in more than one position on the sample. For example, a rendered image generated for an alignment target on a sample may be used for each instance of an alignment target on a sample having the same design.

[0062] One or more components include a model configured to generate a rendered image of an alignment target on a sample from information about the design of the alignment target. The rendered image is a simulation of an image of the alignment target on the sample generated by the imaging subsystem. For example, Figure 1 , one or more components 104 include a model 106. The input to the model may be any information specific to the design, including the design data itself. The output of the model is a rendered image that simulates how the alignment target will look in an image of the portion of the sample in which the alignment target is formed. Thus, the model performs a design-to-optical transformation. (While some embodiments may be described herein with respect to optical images or optical use cases, embodiments may be equally configured for other images described herein or other imaging processes described herein.)

[0063] The rendered image may differ substantially from the design of the alignment target and how the alignment target is actually formed on the sample. For example, marginalities in the process used to form the alignment target on the sample may cause the alignment target on the sample to differ substantially, or at least slightly, from the design of the alignment target. Additionally, marginalities in the imaging subsystem used to generate the image of the alignment target on the sample may cause the image of the alignment target to appear substantially, or at least slightly, different from both the design of the alignment target and the alignment target formed on the sample.

[0064] In one embodiment, the model is a partially coherent physical model (PCM), which may have any format, configuration or architecture known in the art. The embodiments described herein provide a new rendering model concept. When rendering, a numerical model (developed from optical theory) is used to generate a rendered image via a simulation of an imaging process. In other words, the model is a physical model of a simulated imaging process. The model can also perform multi-layer rendering. The model can be set by an iterative optimization process designed to minimize the difference between the real sample image and the rendered sample image. This setting or training can be performed in any suitable manner known in the art.

[0065] Figure 4 A simple version of the imaging subsystem described herein is illustrated using a diagram showing how the model simulates the imaging process. In this imaging subsystem, a sample 400 may include a substrate 402, such as a silicon substrate on which layers 404, 406, and 408 are formed, which may include any suitable layers known in the art, such as dielectric layers. Figure 4 As shown in FIG. 1 , patterned regions may be formed within these layers (here Figure 4 However, one or more layers may not be patterned. Additionally, the sample may include Figure 4 A different number of layers may be shown in the embodiment, for example, less than three layers or more than three layers.

[0066] This simplified version of the imaging subsystem is shown to include a light source 412 that produces light 414 that is directed to an illumination aperture 416 having a number of apertures 418 formed therein. Light 420 that travels through the apertures 418 may then be directed to the upper surface 410 of the sample 400. The near field 422 produced by the illumination of the upper surface 410 of the sample 400 may be collected by an imaging lens 424 that focuses light 426 to a detector 428. The imaging lens 424 may have a focal length d 430. Each of these components of the imaging subsystem may be further configured as described herein. Additionally, this version of the imaging subsystem may be further configured as described herein.

[0067] Layer image L 432 can be input to Figure 1 The model 106 shown in FIG. 1 may first present a near field 436. The layer image may be generated in any suitable manner. For example, information about the design of the sample (e.g., design polygons) may be input into a database rasterization step that generates the layer image. This near field rendering simulation then approximates the portion 434 of the near field from the layer image L to the upper surface 410 of the sample 400 of the imaging process. The model may simulate the near field as where n consumes the excitation information. The near field 436 can be used to simulate a rendered image I 440 by simulating a portion 438 of the imaging process from the near field to the image plane at the detector. This portion of the imaging process can be simulated by simulation, where f consumes wavelength, numerical aperture (NA), excitation mode, etc.

[0068] In currently used PDAs ("POR PDAs"), f always assumes that the defocus is 0, i.e., d = focal length. Additionally, η does not consume polarization information. Thus, when focal length changes and / or polarization differs from that expected, the optical image simulated by the POR PDA may differ sufficiently from the image produced by the imaging subsystem to thereby cause errors in the PDA or even prevent the PDA from being executed altogether.

[0069] Figure 3 An example of a real optical image 300 that can be generated by the imaging subsystem described herein for an alignment target site is shown. The POR PDA can generate a rendered image 302 for this same alignment target site. As shown by the rendered image 302, the image is focused and the horizontal and vertical edges look the same. In contrast, the real optical image 300 is obviously not focused, as evidenced by the blurriness of the image, and the polarization is different from what is expected, because the horizontal and vertical edges in the real optical image are obviously different. For example, the horizontal edge is slightly blurred in the real optical image compared to the same horizontal edge in the rendered image, but the vertical image is completely different in the real optical image and the rendered image, for example, in addition to being more blurred in the optical image than in the rendered image, it is also different in color or contrast. In this way, the alignment of the optical image 300 to the rendered image 302 may be difficult or even impossible, and any image alignment performed based on the results of this alignment may be wrong.

[0070] The computer subsystem is configured to modify one or more parameters of the model based on one or more changes in one or more parameters of the imaging subsystem and one or more changes in one or more process conditions used to manufacture the sample. For example, the embodiments described herein may be configured to improve the accuracy of the presented image in several different ways and accommodate several different ways in which the real optical image may be different from the expected. One of the ways in which the real image may be different from the presented image is due to changes in the imaging subsystem, for example, when the imaging subsystem defocus and / or focus settings are changed. Another of the ways in which the real image may be different from the presented image is due to changes in the sample caused by changing process conditions, which may therefore affect the real image of the sample produced by the imaging subsystem. The embodiments described herein may be configured to modify the parameters of the model based only on changes in the parameters of the imaging subsystem or only on changes in the process conditions. However, the embodiments may also or alternatively be configured to modify the parameters of the model based on both changes in the parameters of the imaging subsystem and changes in the process conditions.

[0071] Modifying the parameters of the model based on changes in the parameters of the imaging subsystem may include adding focus and / or polarization terms to the PDA algorithm presentation model, i.e., the PCM model or another suitable model configured as described herein. Thus, in one embodiment, modifying one or more parameters of the model includes adding a defocus term to the model. For example, the computer subsystem may add a defocus term to the f and η described above, which may be performed in any suitable manner known in the art. In another embodiment, one or more parameters of the imaging subsystem include a focus setting for the imaging subsystem. For example, if the model includes a defocus term or is modified to include a defocus term, as described above, then the computer subsystem may modify the defocus term based on the focus setting of the imaging subsystem, which may be performed in any suitable manner known in the art.

[0072] In some embodiments, modifying one or more parameters of the model includes adding a polarization term to the model. For example, the computer subsystem may add a polarization term to the f and n described above, which may be performed in any suitable manner known in the art. In a further embodiment, one or more parameters of the imaging subsystem include a polarization setting for the imaging subsystem. For example, if the model includes a polarization term or is modified to include a polarization term, as described above, the computer subsystem may modify the polarization term based on the polarization setting of the imaging subsystem, which may be performed in any suitable manner known in the art. Unlike the embodiments described herein, the current presentation model for the PDA does not take into account optical image defocus that may result in a poor match between the acquired optical image and the presented image, thereby resulting in relatively poor PDA alignment. The currently used method also assumes that the focus error is zero and does not take into account polarization. When there is some defocus in the real optical image, polarization may need to be considered. For example, when the sample image is in focus, the original model (without polarization term) works well, but when there is some defocus in the imaging process, the polarization used for imaging may cause the real optical image to look substantially different from the presented image.

[0073] Figure 5 An example of an image obtained using a new rendering model generated by modifying one or more parameters of the model as described herein is shown. In this embodiment, the POR PDA can generate a rendered image 500 for a focus condition having an expected polarization. As further described above, this rendered image has significant differences from the true optical image 502. Therefore, the rendered image is a relatively poor approximation of the true optical image, and the images will most likely be misaligned with each other in any alignment performed therefor.

[0074] In contrast, a model modified as described herein to account for changes in the focus settings and polarization of the imaging process will produce a rendered image 504 that is a far better representation of the real optical image 506 (real optical images 502 and 506 are the same in this example). As can be seen from rendered image 504 and optical image 506, the rendered image looks far more similar to the optical image than rendered image 500. Therefore, the alignment of images 504 and 506 will most likely be successful, and can therefore be successfully used to align other images to each other. For example, experimental results produced by the inventors using the new rendering model described herein (produced by modifying the current model) have shown that images rendered using the new rendering model can be successfully aligned to the real optical image for different modes, different wafers, and different focus settings from 0 to ±300 or even +400. In addition, experimental results have shown that the new PDA method and system described herein can improve performance without sacrificing processing power (e.g., the average time to generate a PDA using the embodiments described herein is about the same and even a little faster than the currently used method).

[0075] In one embodiment, the computer subsystem is further configured to obtain one or more parameters of the imaging subsystem from the recipe of the process for determining the information of the sample. For example, focus and polarization are determined by the optical mode used on the tool. These values ​​can be passed from the recipe parameters to the model. In particular, since the model is modified to include terms for focus and polarization, these settings can be directly input to the model from the recipe for the process (e.g., inspection, metrology, etc.). "Recipe" is generally defined in the art as an instruction that can be used to implement a process. Therefore, the recipe for one of the processes described herein may include information for various imaging subsystem parameters to be used for the process and any other information required to perform the process in the expected manner. In some such embodiments, the computer subsystem may access the recipe from a storage medium (not shown) in which the recipe is stored (which may be a storage medium in the computer subsystem itself) and import the recipe or the information contained therein into the model. Of course, there are various other ways in which recipe parameter information can be input into the model, and any of such ways can be used in the embodiments described herein.

[0076] As described above, embodiments may take into account process variations and the effects that process variations may have on the PDA. For example, a PDA run time may fail for a sample with a relatively strong process variation from setting up the sample. In particular, due to process variations, the run time image may look significantly different from the setup image. In order to mitigate the effects of process variations on the PDA run time process, embodiments described herein may enable the PDA to adapt during run time. For example, if process variations exist on the sample, the run time image may be significantly different from the setup image. Therefore, by determining whether such image differences exist before performing alignment, alignment failures may be avoided by generating a new alignment target through a presented image. Adapting the PDA run time process also means presenting an image during run time (or at least after the setup has been completed and the run time has begun).

[0077] In an embodiment, the computer subsystem is configured to determine whether at least one of the images aligned to the target is blurred and only perform modifications when at least one of the images aligned to the target is blurred, generate additional rendered images as further described herein, and align additional rendered images as further described herein. In this way, the embodiments described herein can perform image rendering only when needed. For example, a sample image may appear blurred when it is out of focus. In particular, PDA images may be initially generated (e.g., during setup) for focus and expected polarization settings. These images may be useful for the PDA used to align the target unless the real optical image becomes different than expected. In some such cases, the computer subsystem may acquire a real optical image aligned to the target and perform some image analysis to determine the degree of blur of the image. If there is a certain blur in the image (which can be quantified and compared to a certain threshold that separates acceptable and unacceptable levels in any suitable manner known in the art), the computer subsystem may modify one or more parameters of the model and generate one or more additional rendered images for aligning to an optical image that exhibits a certain blur. In this way, the image characteristics of real optical images can be examined to determine if they deviate from expectations and then new rendered PDA images can be generated for those images that exhibit deviations.

[0078] In another embodiment, the computer subsystem is configured to determine whether the horizontal and vertical features in at least one of the images of the alignment target appear different from each other and perform modifications only when the horizontal and vertical features appear different from each other, generate additional rendered images as further described herein, and align the additional rendered images as further described herein. For example, when the horizontal and vertical lines appear different in the sample image, the polarization of the imaging subsystem may have shifted. In this way, the embodiments described herein can perform image rendering only when needed. In particular, PDA images can be initially generated for focus and expected polarization settings. These images can be useful for the PDA used to align the target unless the real optical image becomes different from what is expected. In some such cases, the computer subsystem can obtain the real optical image of the alignment target and perform some image analysis to determine how different the horizontal and vertical lines appear in the real optical image. If there is some difference in the horizontal and vertical lines in the image (which can be quantified and compared to some threshold that separates acceptable from unacceptable levels of difference in any suitable manner known in the art), the computer subsystem can modify one or more parameters of the model and generate one or more additional rendered images for alignment to the optical image that exhibits some difference. In this way, the image characteristics of the real optical image can be examined to determine if they deviate from expectations and then new rendered PDA images can be generated for those images that exhibit deviations.

[0079] After modifying one or more parameters of the model, the computer subsystem is configured to generate additional rendered images of the alignment target by inputting information designed for the alignment target into the model. For example, once the parameters of the model have been modified in one or more of the ways described herein, the model can be used to generate new rendered images of the alignment target, which can then be used for alignment, as further described herein. The information designed for the alignment target can include any information described herein and can be input to the model in any suitable manner known in the art.

[0080] In one embodiment, the computer subsystem is configured to obtain information designed for the alignment target from a storage medium and input the obtained information into the model without modifying the obtained information. For example, information input to the model to generate a rendered image does not need to be changed to make the rendered image look more similar to a real image. In other words, once the model has been modified as described herein, changes to the input do not need to be made. In this way, the same information originally used to generate the rendered alignment target image can be reused without modification to generate a new rendered alignment target image. As further described herein, for the embodiments described herein, being able to reuse the model input without modification has advantages.

[0081] The computer subsystem is further configured to align the additional rendered image to at least one of the images of the alignment target generated by the imaging subsystem. In this manner, the image alignment step performed by the embodiments described herein is an alignment between the real image of the alignment target and the rendered image of the alignment target. In addition to using the new rendered image described herein, the alignment may be additionally performed in any suitable manner known in the art. In other words, the embodiments described herein and the rendered images they generate are not specific to any type of alignment process.

[0082] Before the process is performed on the sample, the rendered image may have been aligned to the design of the sample. In other words, during setup, a computer subsystem or another system or method may align the rendered image of the alignment target to the design of the sample. Based on the result of this alignment, the coordinates of the design aligned to the rendered alignment target image may be assigned to the rendered alignment target image or a certain coordinate displacement between the rendered alignment target image and the design may be established. (As used herein, the term "displacement" is defined as the absolute distance from the design, which is different from the "offset" defined as the relative distance between two optical images in this article.) Then, during runtime, the rendered alignment target image may be aligned to the real alignment target image, whereby, for example, the real alignment target image is aligned to the design based on information generated by aligning the rendered alignment target image to the design during setup. In this way, during runtime, the alignment step may be an optical to rendered optical alignment step that results in optical to design alignment. Performing alignment in this way during runtime makes the process much faster and the processing capacity of the process much better.

[0083] Unlike the embodiments described herein, the POR PDA performs all rendering for the PDA sites on the sample before inspection using the known locations of the PDA image sites. Therefore, these methods and systems fail to account for process variations (intra-wafer or wafer-to-wafer) that may occur and degrade the match between the optical and rendered PDA images. In contrast, the embodiments described herein provide a new PDA method that may include runtime real-time PDA functionality that can be used to adaptively render images to handle optical process variations on a sample.

[0084] As described above, one way in which the embodiments described herein may be configured to generate a new rendered image for a real-time PDA may be to examine a certain characteristic of the real optical image to be aligned to the rendered image. Another method for a real-time PDA is also provided herein. Figure 6One such embodiment is shown in FIG. 6. In step 600, the computer subsystem acquires runtime images, which may include real optical images and one or more rendered images. The rendered images may include POR PDA rendered images (e.g., PDA images generated for a focus condition and an expected polarization) and new PDA rendered images (e.g., generated for a different focus setting and a different polarization).

[0085] The images produced by the models in the embodiments described herein may be suitable for coarse alignment only or for both coarse and fine alignment. In instances where the rendered image is suitable for coarse alignment only, the model or another model configured as described herein may be used to produce a rendered image suitable for fine alignment. The coarse and fine alignment described herein may also differ in ways other than just the images used for these steps. For example, coarse alignment may be performed for far fewer alignment targets and / or far fewer instances of the same alignment target than for fine alignment. The alignment method may also be different for coarse and fine alignment and may include any suitable alignment method known in the art.

[0086] In one embodiment, aligning the additional rendered images includes a coarse alignment, and the computer subsystem is configured to perform an additional coarse alignment of the stored rendered image of the alignment target to at least one of the images of the alignment target and determine a difference between the coarse alignment and the results of the additional coarse alignment. In this way, the computer subsystem can perform two different coarse alignments, one using the POR PDA rendered images and another using the new PDA rendered images. For example, if Figure 6 , the computer subsystem may perform an additional coarse alignment of a stored rendered image of the alignment target (i.e., the POR PDA rendered image) to at least one image of the alignment target (i.e., the real optical image of the alignment target), which is a POR coarse alignment step 602. Additionally, the computer subsystem may perform a coarse alignment of a new rendered image of the alignment target (i.e., the new PDA rendered image) to at least one image of the alignment target (i.e., the same real optical image of the alignment target), which is a rendering and coarse alignment step 604. Both of these coarse alignment steps may additionally be performed in any suitable manner known in the art.

[0087] The output of the POR coarse alignment step 602 may be a displacement S p 606 (ie, the offset between the runtime image and the rendered image), and the output of the rendering and coarse alignment step 604 may be the displacement S R 608. The two displacements may be input to step 610 where the difference between the displacements is calculated as the variation introduced displacement (VIS) VIS = |S p -S R|. The difference between the displacements is an indicator of process variation. Ideally, the VIS will be close to 0, meaning there is no difference between the two displacements. The computer subsystem will calculate the VIS for each scan band of the image scanned on the sample.

[0088] In one such embodiment, the computer subsystem is configured to compare the difference between the results of the coarse alignment and the additional coarse alignment to a threshold and when the difference is less than the threshold, perform fine alignment using the stored rendered image of the alignment target or the stored finely aligned rendered image. Figure 6 As shown in step 612 of , the computer subsystem may determine whether the VIS is greater than a threshold value T, e.g., T=0.5 pixels. If the VIS is not greater than T, the computer subsystem may perform a POR fine alignment, as shown in step 614. In other words, the computer subsystem may perform fine alignment using a POR PDA rendered image or a POR PDA rendered image generated specifically for fine alignment. In this manner, coarse and fine alignment may be performed using the same POR PDA rendered image or using different POR PDA rendered images generated specifically for coarse and fine alignment. This and other fine alignment steps described herein may be additionally performed in any suitable manner known in the art.

[0089] In another such embodiment, the computer subsystem is configured to compare the difference between the results of the coarse alignment and the additional coarse alignment to a threshold and when the difference is greater than the threshold, perform fine alignment using a finely aligned rendered image of the alignment target. Figure 6 As shown in step 612 of , the computer subsystem may determine whether the VIS is greater than a threshold value T. If the VIS is greater than T, the computer subsystem may report a process variation because a non-optimal alignment result has been detected. If the VIS is greater than T, the computer subsystem may also perform rendering and fine alignment as shown in step 616. In other words, the computer subsystem may perform fine alignment using a PDA image rendered using a model modified as described herein or a PDA image rendered using a model modified as described herein and generated specifically for fine alignment. In this way, coarse and fine alignment may be performed using the same new PDA rendered image or using different new PDA rendered images generated specifically for coarse and fine alignment.

[0090] In some embodiments, after modifying the parameters of the model, the computer subsystem is configured to generate a fine alignment rendering image by inputting information designed for the alignment target into the model. In this way, the same model that is modified and used to generate the coarse alignment rendering image can also be used to generate the fine alignment rendering image. The fine alignment rendering image can be additionally generated as further described herein.

[0091] In such embodiments, the same information initially used to render an alignment target image may also be used to render a new alignment target image adaptively and / or during runtime. For example, the parameters of the model may be modified, but the design (and possibly other) information used for the rendering will remain the same. Thus, all of the information initially used for the alignment target image rendering may be stored and reused for additional alignment target image renderings. Being able to store and reuse inputs to the model may have significant benefits for the embodiments described herein, including minimizing any impact that additional alignment target image renderings may have on the processing capabilities of the process performed on the sample.

[0092] Depending on the configuration of the system, the design information input to the model can be made available in several different ways. One way is to retrieve the design information after it has been determined that a new image rendering requires it. Another way is to retrieve it depending on what alignment target is being processed so that it is available for rendering when a need for a new rendered image is detected. For example, runtime may include a frame data preparation stage in which runtime optical images are grabbed based on target positions and their corresponding setup optical images and layer images are simultaneously unpacked.

[0093] like Figure 6 6, the information for the design of the alignment target can be stored in the storage medium 618 by the computer subsystem or another system or method. The storage medium 618 can be further configured as described herein. In some examples, the storage medium 618 can be configured as a cache database containing information of the target and design layer for the sample. In this way, the information can be provided to the various rendering and alignment steps described herein. For example, the computer subsystem can be configured to obtain the target, design layer 620 from the storage medium 618 and input the information to the rendering and rough alignment step 604 to thereby generate a rendered rough alignment PDA image. In a similar manner, the computer subsystem can be configured to obtain the target, design layer 622 from the storage medium 618 and input the information to the rendering and fine alignment step 616 to thereby generate a rendered fine alignment PDA image. In some examples, the target, design layer 620 and the target, design layer 622 may include the same information and the model can generate a rough alignment image or a fine alignment image from the information. In other examples, target, design layer 620 and target, design layer 622 may include different information suitable for generating a rendered coarsely aligned PDA image or a rendered finely aligned PDA image.

[0094] In another embodiment, the computer subsystem is configured to modify one or more parameters of the additional model based on one or more of the changes in one or more parameters of the imaging subsystem and one or more of the changes in the process conditions and after modifying the one or more parameters of the additional model, generate a fine alignment rendering image by inputting information designed for the alignment target into the additional model and perform fine alignment by aligning the fine alignment rendering image to at least one of the images of the alignment target. For example, the system may include Figure 1 106 may be configured to generate a rendered image suitable for coarse alignment, and model 108 may be configured to generate a rendered image suitable for fine alignment. In addition to being configured to generate a rendered image for fine alignment, additional model 108 may be configured as further described herein. For example, both models 106 and 108 may be configured to perform the following steps: Figure 4 . In this case, one or more parameters of the fine alignment model may be modified as described herein to account for one or more variations described herein. The new fine alignment rendering image generated by the additional model may then be used for fine alignment to a real optical (or other) alignment target image as described herein. Fine alignment may be performed in any suitable manner known in the art.

[0095] Thus, the embodiments described herein may involve generating additional rendered images and / or generating new rendered images in real time. Thus, one consideration that may be made is how this additional image rendering affects the processing power of the process executing the PDA. In general, the inventors believe that any impact on processing power will be minimal or can be reduced in several important ways described herein. For example, in PDA training, the bottleneck of processing power may be the generation of design polygons. However, the embodiments described herein do not require the regeneration of polygons in the rendering process. Alternatively, the embodiments described herein may directly use the target and design layer images stored in the database in PDA training. For example, Figure 6 The target, design layer 620 and target, design layer 622 shown in FIG. 6 may be generated during PDA training and stored in Figure 6 In this way, this information can be easily accessed and reused for any runtime image rendering, which will significantly improve the processing power of the PDA process and alleviate any impact that the additional rendering has on the overall process.

[0096] The computer subsystem is further configured to determine information of the sample based on the results of the alignment. For example, the results of the alignment can be used to align other images to a common reference (e.g., a design of the sample). In other words, once the real alignment target image has been aligned to the rendered alignment target image, any offsets determined therefrom can be used to align other real sample images to the design of the sample. The image alignment can then be used to determine other information of the sample, such as region of interest (CA) placement and detection of defects in the CA, determining locations on the sample where metrology measurements are to be performed and then performing the measurements, etc.

[0097] In one embodiment, the computer subsystem is further configured to determine the CA placement for the determining step based on the results of the alignment. The PDA is critical to the performance of defect inspection. For example, a PDA image is rendered from a design image using one of the models described herein (e.g., a PCM model). The rendered image is then aligned with a real optical image from a sample to determine the (x, y) position offset between the two images and thereby the (x, y) position displacement between the real design position and the sample coordinates. This position displacement is applied as a coordinate correction for real CA placement and defect reporting.

[0098] Accurate CA placement is required for almost all inspection processes performed today and is important for several reasons. For example, if the inspection is performed on the entire image frame generated by the inspection process, defects can be buried in the noise in the image frame. In order to enhance the sensitivity of the inspection process, CA is used to exclude noise from the area of ​​interest and it should be as small as possible to exclude as much noise as possible. Due to the time involved and the relatively low accuracy of such methods, the placement of essentially small CAs (e.g., as small as a single pixel) used today is essentially impossible to do manually. Therefore, most CA methods and systems used today are based on designs that, when properly configured, can make sub-pixel accuracy feasible and achieve the location of hot spots. In order to make this CA placement feasible, the sample image must be mapped to the design coordinates, which is what the PDA does. The embodiments described herein make the accuracy of CA placement required by many currently used inspection methods and systems more achievable than the currently used methods and systems for image-to-design alignment.

[0099] Accurate CA placement requires accurate PDA, which in turn is used to implement extremely sensitive defect detection algorithms and / or methods. In addition, the embodiments described herein can be used to improve any PDA-type method or system that involves or uses a presented optical image to align to a real optical image. For example, the embodiments described herein can be used to improve PDA-type methods and systems for manually generating regions of interest, which can be relatively large as well as much smaller CAs, such as 5x5 pixel CAs, 3x 3 pixel CAs, and even 1x 1 pixel CAs. In addition, the embodiments described herein can be used with any other PDA-type methods and systems, including PDA-type methods and systems that have been developed to be more robust to other types of image changes, such as changes in image contrast. In this way, the embodiments described herein can be used to improve any type of optical image to presented image alignment process in which alignment may fail when there is a relatively large defocus and / or when alignment may fail for samples with relatively strong process variations.

[0100] Once the CA has been placed based on the results of the alignment, defect detection may be performed by the embodiments described herein. In one suitable defect detection method, a reference may be subtracted from a test image to thereby produce a differential image. A threshold may be applied to pixels in the differential image. Any pixel in the differential image having a value above the threshold may be identified as a defect, defect candidate, or potential defect while any pixel in the differential image not having a value above the threshold may not be so identified. Of course, this may be the simplest method that may be used for defect detection, and the embodiments described herein may be configured to use any suitable defect detection method and / or algorithm for determining information for a sample. In this way, the information determined for a sample may include information for any defects, defect candidates, or potential defects detected on the sample.

[0101] In a similar manner, when the process is another process like metrology, once the image has been aligned to a design or another common reference by the embodiments described herein, the metrology or other process can be performed at the desired location on the sample. The embodiments described herein can be configured to perform any suitable metrology method or process on the sample using any suitable measurement algorithm or method known in the art. In this manner, the information determined for the sample by the embodiments described herein can include any results of any measurements performed on the sample.

[0102] The computer subsystem may also be configured to generate a result containing determined information, which may include any result or information described herein. The result of determining information may be generated by the computer subsystem in any suitable manner. All embodiments described herein may be configured to store the result of one or more steps of the embodiment in a computer-readable storage medium. The result may include any result described herein and may be stored in any manner known in the art. The result containing determined information may have any suitable form or format, such as a standard file type. The storage medium may include any storage medium described herein or any other suitable storage medium known in the art.

[0103] After the results have been stored, the results may be accessed in a storage medium and used by any method or system embodiment described herein, formatted for display to a user, used by another software module, method or system, etc. to perform one or more functions on the sample or another sample of the same type. For example, the results of an alignment step, information on detected defects, etc. may be stored and used as described herein or in any other suitable manner. Such results generated by the computer subsystem may include information on any defects detected on the sample, such as the location of a bounding box of a detected defect, etc., a detection score, information about defect classification (e.g., a class label or ID), any defect attributes determined from any image, etc., sample structure measurements, sizes, shapes, etc., or any such suitable information known in the art. The information may be used by the computer subsystem or another system or method for performing additional functions on the sample and / or detected defects, such as sampling defects for defect review or other analysis, determining the root cause of a defect, etc.

[0104] Such functions also include, but are not limited to, changing a process, such as a manufacturing process or step that is or will be performed on a sample in a feedback or feedforward manner, etc. For example, the computer subsystem may be configured to determine one or more changes to a process performed on a sample and / or to be performed on a sample based on the determined information. The changes to a process may include any suitable changes to one or more parameters of a process. In one such example, the computer subsystem preferably determines the changes so that defects on other samples on which the revised process is performed can be reduced or prevented, defects on the sample can be corrected or eliminated in another process performed on the sample, defects can be compensated in another process performed on the sample, etc. The computer subsystem may determine such changes in any suitable manner known in the art.

[0105] The changes may then be sent to a semiconductor manufacturing system (not shown) or a storage medium (not shown) accessible to both the computer subsystem and the semiconductor manufacturing system. The semiconductor manufacturing system may or may not be part of the system embodiments described herein. For example, the imaging subsystem and / or the computer subsystem described herein may be coupled to the semiconductor manufacturing system, for example, via one or more common elements such as a housing, a power supply, a sample handling device or mechanism, etc. The semiconductor manufacturing system may include any semiconductor manufacturing system known in the art, such as a lithography tool, an etching tool, a chemical-mechanical polishing (CMP) tool, a deposition tool, and the like.

[0106] In addition to the advantages already described, the embodiments described herein have several advantages. For example, as further described herein, the embodiments provide improved PDA presentation accuracy through new PCM model terms for defocus and / or polarization and / or an adaptive algorithm for real-time presentation of images to account for process variations. The embodiments described herein are also fully customizable and flexible. For example, new PCM model terms for defocus and / or polarization can be used separately from an adaptive algorithm for real-time presentation of images to account for process variations. In addition, the embodiments described herein provide improved PDA robustness. In addition, the embodiments described herein provide improved PDA alignment performance. The embodiments described herein can be used to improve PDA accuracy on inspection tools, which can directly lead to improved sensitivity performance and increase the authority of defect detection on the tool. These and other advantages described herein are achieved through several important new features, including but not limited to extending the PCM model to include focus and / or polarization and adaptive PDA presentation.

[0107] It is also expected that the real-time PDA embodiments described herein have very little impact on the processing capacity of the PDA process and the overall process. In addition, it is expected that the real-time PDA embodiments described herein have little or no impact on the sensitivity of the PDA process. For example, Figure 7 is a plot showing the alignment offsets (only X offsets are shown) determined for samples with no process variations using the currently used process (POR PDA) and the real-time PDA embodiment described herein. As can be seen in this plot, the alignment offsets determined by the two methods are substantially similar, indicating that the sensitivity of the POR PDA method is substantially the same as the real-time PDA embodiment described herein. In other words, for good wafers (wafers with no process variations), the embodiments described herein have the same performance as the currently used method.

[0108] Each of the embodiments of each of the systems described above may be combined together into a single embodiment.

[0109] Another embodiment relates to a method for determining information of a sample. The method includes acquiring an image of the sample generated by an imaging subsystem, which can be performed as further described herein. The method also includes the steps of modifying one or more parameters, generating additional rendered images, aligning additional rendered images, and determining information described herein, which are performed by a computer subsystem coupled to the imaging subsystem.

[0110] Each step of the method may be performed as further described herein. The method may also include any other steps that may be performed by the system, imaging subsystem, model, and computer subsystem described herein. The system, imaging subsystem, model, and computer subsystem may be configured according to any embodiment described herein. The method may be performed by any system embodiment described herein.

[0111] Additional embodiments relate to a non-transitory computer-readable medium storing program instructions executable on a computer system to perform a computer-implemented method for determining information of a sample. Figure 8 One such embodiment is shown in FIG. Figure 8 , a non-transitory computer readable medium 800 includes program instructions 802 that can be executed on a computer system 804. The computer-implemented method includes the steps described above. The computer-implemented method may further include any steps of any method described herein.

[0112] Program instructions 802 implementing methods such as those described herein may be stored on computer readable medium 800. The computer readable medium may be a storage medium such as a magnetic or optical disk, tape, or any other suitable non-transitory computer readable medium known in the art.

[0113] The program instructions may be implemented in any of a variety of ways, including process-based techniques, component-based techniques, and / or object-oriented techniques, etc. For example, the program instructions may be implemented using ActiveX controls, C++ objects, JavaBeans, Microsoft Foundation Classes ("MFC"), SSE (Streaming SIMD Extensions), or other techniques or methodologies, as desired.

[0114] Computer system 804 may be configured according to any of the embodiments described herein.

[0115] In view of this description, it will be understood by those skilled in the art that further modifications and alternative embodiments of various aspects of the present invention. For example, methods and systems for determining the information of a sample are provided. Therefore, this description should be interpreted only as illustrative and for the purpose of teaching the general manner of implementing the present invention to those skilled in the art. It should be understood that the form of the present invention shown and described herein should be considered as the current preferred embodiment. As will be understood by those skilled in the art after benefiting from this description of the present invention, elements and materials can replace the elements and materials illustrated and described herein, parts and processes can be reversed, and the specific features of the present invention can be utilized independently. Changes can be made to the elements described herein without departing from the spirit and scope of the present invention as described in the appended claims.

Claims

1. A system configured to determine information of a sample, comprising: an imaging subsystem configured to generate an image of the sample; a model configured to generate a rendered image of an alignment target on the sample from information for a design of the alignment target, wherein the rendered image is a simulation of the image of the alignment target on the sample generated by the imaging subsystem; and A computer subsystem configured to: modifying one or more parameters of the model based on one or more of a change in one or more parameters of the imaging subsystem and a change in one or more process conditions used to manufacture the sample; generating, after the modifying, an additional rendered image of the alignment target by inputting the information for the design of the alignment target into the model; aligning the additional rendered image to at least one of the images of the alignment target produced by the imaging subsystem; and Information of the sample is determined based on a result of the alignment.

2. A system according to claim 1, wherein the model is a partially coherent physics model.

3. The system of claim 1, wherein the modifying comprises adding an out-of-focus term to the model. 4 . The system of claim 1 , wherein the one or more parameters of the imaging subsystem include a focus setting of the imaging subsystem.

5. The system of claim 1, wherein the modifying comprises adding a polarizing term to the model.

6. The system of claim 1, wherein the one or more parameters of the imaging subsystem include a polarization setting of the imaging subsystem.

7. The system of claim 1, the computer subsystem further configured to obtain the one or more parameters of the imaging subsystem from a recipe for the determined process.

8. A system according to claim 1, wherein the computer subsystem is further configured to determine whether at least one of the images of the alignment target is blurred and perform the modification only when the at least one of the images of the alignment target is blurred, generate the additional rendered image, and align the additional rendered image.

9. A system according to claim 1, wherein the computer subsystem is further configured to determine whether horizontal and vertical features in at least one of the images of the alignment target appear different from each other and perform the modification only when the horizontal and vertical features appear different from each other, generate the additional rendered image, and align the additional rendered image.

10. The system of claim 1, wherein the computer subsystem is further configured to retrieve the information of the design for the alignment target from a storage medium and input the retrieved information into the model without modifying the retrieved information.

11. A system according to claim 1, wherein aligning the additional rendered image includes a coarse alignment, and wherein the computer subsystem is further configured to perform an additional coarse alignment of the stored rendered image of the alignment target to the at least one of the images of the alignment target and determine a difference between the coarse alignment and the results of the additional coarse alignment.

12. A system according to claim 11, wherein the computer subsystem is further configured to compare the difference between the results of the coarse alignment and the additional coarse alignment with a threshold and when the difference is less than the threshold, perform fine alignment using the stored rendered image or the stored fine alignment rendered image of the alignment target.

13. The system of claim 11, wherein the computer subsystem is further configured to compare the difference between the results of the coarse alignment and the additional coarse alignment with a threshold and when the difference is greater than the threshold, perform fine alignment using a fine alignment presentation image of the alignment target.

14. The system of claim 13, wherein after the modifying, the computer subsystem is further configured to generate the fine alignment rendering image by inputting the information of the design for the alignment target into the model.

15. The system of claim 13 , wherein the computer subsystem is further configured to modify one or more parameters of an additional model based on the changes in the one or more parameters of the imaging subsystem and the one or more of the changes in the one or more of the process conditions, generate the fine alignment rendering image by inputting the information of the design for the alignment target into the additional model after modifying the one or more parameters of the additional model, and perform the fine alignment by aligning the fine alignment rendering image to the at least one of the images of the alignment target.

16. The system of claim 1, wherein the computer subsystem is further configured to determine a region of interest placement for the determining step based on the results of the aligning.

17. The system of claim 1, wherein the imaging subsystem is further configured as an inspection subsystem.

18. The system of claim 1, wherein the imaging subsystem is a light-based subsystem.

19. A non-transitory computer readable medium storing program instructions executable on a computer system to perform a computer-implemented method for determining information of a sample, wherein the computer-implemented method comprises: acquiring an image of the sample generated by an imaging subsystem; modifying one or more parameters of a model based on one or more of a change in one or more parameters of the imaging subsystem and a change in one or more process conditions used to fabricate the sample, wherein the model is configured to generate a rendered image of an alignment target on the sample from information for a design of the alignment target, and wherein the rendered image is a simulation of the image of the alignment target on the sample generated by the imaging subsystem; generating, after the modifying, an additional rendered image of the alignment target by inputting the information for the design of the alignment target into the model; aligning the additional rendered image to at least one of the images of the alignment target produced by the imaging subsystem; and The information of the sample is determined based on the result of the alignment, wherein the acquiring, modifying, generating, aligning and determining are performed by the computer system.

20. A method for determining information about a sample, comprising: acquiring an image of the sample generated by an imaging subsystem; modifying one or more parameters of a model based on one or more of a change in one or more parameters of the imaging subsystem and a change in one or more process conditions used to fabricate the sample, wherein the model is configured to generate a rendered image of an alignment target on the sample from information for a design of the alignment target, and wherein the rendered image is a simulation of the image of the alignment target on the sample generated by the imaging subsystem; generating, after the modifying, an additional rendered image of the alignment target by inputting the information for the design of the alignment target into the model; aligning the additional rendered image to at least one of the images of the alignment target produced by the imaging subsystem; and The information of the sample is determined based on the result of the alignment, wherein the acquiring, modifying, generating, aligning and determining are performed by a computer subsystem coupled to the imaging subsystem.

Images