Detecting defects in array region on sample

Abstract

Methods and systems are provided for detecting defects in an array region on a sample. A system includes an inspection subsystem configured to generate an output in response to patterned features formed in an array region on a sample. The system also includes a computer subsystem configured to determine whether a pitch of the patterned features in the output is an integer number of pixels in a detector of the inspection subsystem that produces the output. When the pitch is not an integer number of the pixels, the computer subsystem is configured to interpolate the output to produce an interpolated output having a modified pitch of the patterned features in the interpolated output, the modified pitch being an integer number of the pixels. The computer subsystem is also configured to detect defects in the array region by applying a defect detection method to the interpolated output.

Description

Technical Field

[0001] The present invention generally relates to methods and systems for detecting defects in an array region on a sample in the semiconductor field. Background Art

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

[0003] Fabricating semiconductor devices, such as logic and memory devices, generally involves processing a sample, such as a semiconductor wafer, using a large number of semiconductor processes to form various features and multiple levels of the semiconductor device. For example, lithography is a semiconductor process that typically involves transferring a pattern to a photoresist disposed on a semiconductor wafer. Additional examples of semiconductor processes include, but are not limited to, chemical mechanical polishing, etching, deposition, and ion implantation. Multiple semiconductor devices can be fabricated on a semiconductor wafer and then separated into individual semiconductor devices.

[0004] In the semiconductor industry, inspection using optical or electron beam imaging is an important technique for debugging semiconductor processes, monitoring process variations, and improving production yield. As the scale of modern integrated circuits (ICs) continues to shrink and the processes become increasingly complex, inspection becomes more and more difficult.

[0005] In each processing step performed on a semiconductor wafer, the same circuit pattern is printed in each die. Most wafer inspection systems utilize this fact and use relatively simple die-to-die comparison to detect defects on the wafer. However, the printed circuits in each die may contain many regions of patterned features that are repeated in the x or y direction (e.g., regions of DRAM, SRAM, or FLASH). This type of region is commonly referred to as an "array region" (the remaining regions are referred to as "random" or "logic regions"). To achieve better sensitivity, advanced inspection systems employ different strategies to inspect the array regions and the random or logic regions.

[0006] Array detection algorithms are designed to achieve relatively high sensitivity for DRAM cell regions by exploiting the repeatability of the cell regions. For example, inspection systems configured for array region inspection typically perform cell-to-cell comparison, where the images of different cells in the array region in the same die are subtracted from each other and the differences are checked for defects. This array inspection strategy can achieve much higher sensitivity in the array region than random inspection, which is typically performed by subtracting the image of one die from the image of another die, because it avoids the noise caused by die-to-die variations.

[0007] The currently used cell-to-cell array detection algorithm uses adjacent cells as a baseline to generate a reference image of a test cell. Since the pattern is repetitive and if its pitch is in integer pixels, then in the absence of defects, adjacent cells should have the same pattern as the test cell. A number of adjacent cells can also be selected as a batch, and the median cell can be calculated using the cells in the batch. The median cell can be set as the reference cell for all cells in the batch.

[0008] The currently used methods and systems for defect detection in an array region do have many significant drawbacks. For example, the currently used array inspection algorithm requires the array region to be repetitive in the horizontal dimension. If a wafer has two array regions that are repetitive in two different dimensions (e.g., one region is repetitive in the horizontal dimension and the other region is repetitive in the vertical dimension), then the currently used system requires two passes of inspection with different wafer orientations. The currently used array inspection algorithm also requires the cell pitch to be an integer number of pixels of the detector or an integer number of pixels in the output, which introduces complexity and additional requirements for the image acquisition system. Additionally, the currently used algorithm uses adjacent cells to generate a reference image of a test cell, but does not account for cell-to-cell color variations.

[0009] Therefore, it would be advantageous to develop systems and methods for inspecting an array region on a sample that do not have one or more of the above drawbacks. SUMMARY OF THE INVENTION

[0010] The following description of the various embodiments should not be construed in any way as limiting the subject matter of the appended claims.

[0011] One embodiment relates to a system configured to detect defects in an array region on a sample. The system includes an inspection subsystem configured to generate an output in response to a patterned feature formed in the array region on the sample. The system also includes a computer subsystem configured to determine whether a pitch of the patterned feature in the output is an integer number of pixels of a detector of the inspection subsystem that generated the output. When the pitch is not an integer number of the pixels, the computer subsystem is configured to interpolate the output to generate an interpolated output having a modified pitch of the patterned feature in the output that is an integer number of pixels. The computer subsystem is further configured to detect a defect in the array region by applying a defect detection method to the interpolated output. The system can be further configured as described herein.

[0012] Another embodiment relates to a computer-implemented method for detecting defects in an array region on a sample. The method includes obtaining an output generated by an inspection subsystem in response to a patterned feature formed in the array region on the sample. The method further includes determining whether a pitch of the patterned feature in the output is an integer number of pixels in a detector of the inspection subsystem that generated the output. When the pitch is not an integer number of the pixels, the method includes interpolating the output to produce an interpolated output having a modified pitch of the patterned feature in the interpolated output, the modified pitch being an integer number of the pixels. The method also includes detecting a defect in the array region by applying a defect detection method to the interpolated output. The obtaining, determining, interpolating, and detecting are performed by a computer subsystem coupled to the inspection subsystem. Each step of the method described above can be performed as further described herein. Additionally, embodiments of the method described above can include any other steps of any other method described herein. The method described above can be performed by any of the systems described herein.

[0013] 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 detecting defects in an array region on 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. Additionally, the computer-implemented method for which the program instructions are executable can include any other steps of any other method described herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Those skilled in the art will appreciate further advantages of the present invention after benefiting from the following detailed description of the preferred embodiments and after referring to the accompanying drawings, in which:

[0015] Figure 1 and 1a is a schematic side view illustration of an embodiment of a system configured as described herein;

[0016] Figure 2 is a flowchart illustration of an embodiment of steps that can be performed to detect defects in an array region on a sample;

[0017] Figure 3 includes examples of reference images and difference images that can be generated for a test image using the embodiments and current methods described herein;

[0018] Figure 4A schematic plan view of an example of a portion of a sample, the sample including an array region that repeats in orthogonal dimensions on the sample;

[0019] Figure 5 A schematic plan view of an example of a portion of a sample, the sample including an array region that repeats in orthogonal dimensions on the sample; and

[0020] Figure 6 A block diagram of an embodiment of a non - transitory computer - readable medium storing program instructions for causing a computer system to perform the computer - implemented methods described herein.

[0021] While the present invention is susceptible to various modifications and alternative forms, specific embodiments of the invention are shown by way of example in the drawings and are herein described in detail. The drawings may not be to scale. However, it is to be understood that the drawings and their detailed description are not intended to limit the invention to the particular form disclosed, but on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention as defined by the appended claims. Detailed Description

[0022] Referring now to the drawings, it should be noted that the figures are not to scale. Specifically, the scale of some of the elements of the figures has been greatly enlarged to emphasize the characteristics of the elements. It should also be noted that the figures are not drawn to the same scale. The same element symbols have been used to indicate elements shown in more than one figure that may be similarly configured. Unless otherwise noted herein, any of the elements described and shown may include any suitable commercially available elements.

[0023] Generally, the embodiments described herein are configured to detect defects in an array region on a sample. Defect inspection in a repeating array region is an important part of wafer inspection. For repeating patterns, using repeatability to generate a reference image can reduce and even minimize the noise introduced by process variations and result in higher detection sensitivity. Currently used detection algorithms for repeating array regions require the pattern to repeat in the horizontal dimension and the repeat pitch of the patterned features to be an integer number of pixels of the detector or an integer number of pixels in the output. Adjacent cells are used to generate a reference image of the test cell. However, cell - to - cell color variations are not considered, which can create problems regardless of the position of the cell, but especially when the test cell is located at the edge of the array region and can be affected by light leakage. The embodiments described herein provide a new cell - to - cell detection system and method that can support both horizontal and vertical repeat regions, handle non - integer and non - uniform pitch in the array region, and improve defect detection sensitivity by reducing and even removing cell - to - cell color variations.

[0024] Although some embodiments are described herein with respect to dynamic random access memory (DRAM) devices, the embodiments described herein can be used for the inspection of any type of memory device and / or device containing a memory region. In one embodiment, the sample is a wafer. The wafer can include any wafer known in the semiconductor art. Although some embodiments can be described herein with respect to one or more wafers, the embodiments are not limited to the samples for which they can be used. For example, the embodiments described herein can be used for samples such as photomasks, flats, personal computer (PC) boards, and other semiconductor samples.

[0025] Figure 1 FIG. shows an embodiment of a system configured to detect defects in an array region on a sample. The system includes an inspection subsystem 100. In Figure 1 the embodiment shown in FIG., the inspection subsystem is configured as an optical-based inspection subsystem. However, in other embodiments described herein, the inspection subsystem is configured as an electron beam or charged particle beam-based inspection subsystem.

[0026] The inspection subsystem is configured to produce an output in response to a patterned feature formed in an array region on the sample. Generally, the inspection subsystems described herein include at least an energy source and a detector. The energy source is configured to produce energy that is directed to the sample. The detector is configured to detect energy from the sample and produce an output in response to the detected energy.

[0027] In an optical-based inspection subsystem, the energy directed to the sample includes light, and the energy detected from the sample includes light. For example, in Figure 1 the embodiment of the system shown in FIG., the inspection subsystem includes an illumination subsystem configured to direct light to the sample 14. The illumination subsystem includes at least one light source. For example, as shown in Figure 1 FIG., the illumination subsystem includes a light source 16. In one embodiment, the illumination subsystem is configured to direct light to the sample at one or more incident angles, which can include one or more oblique angles and / or one or more normal angles. For example, as shown in Figure 1 FIG., light from the light source 16 is directed through an optical element 18 at an oblique incident angle and then through a lens 20 to the sample 14. The oblique incident angle can include any suitable oblique incident angle, which can vary depending on, for example, the characteristics of the sample and the defects to be detected on the sample.

[0028] The illumination subsystem can be configured to direct light to the sample at different incident angles at different times. For example, the inspection subsystem can be configured to change one or more characteristics of one or more elements of the illumination subsystem such that light can be directed to the sample at a different angle than Figure 1The angle of incidence shown therein guides light to the sample. In one such instance, the inspection subsystem may be configured to move the light source 16, the optical element 18, and the lens 20 such that light is guided to the sample at different oblique angles of incidence or at normal (or near-normal) angles of incidence.

[0029] In some examples, the inspection subsystem may be configured to guide light to the sample at more than one angle of incidence simultaneously. For example, the illumination subsystem may include more than one illumination channel, one of the illumination channels may include a light source 16, an optical element 18, and a lens 20 as shown in Figure 1 and another (not shown) of the illumination channels may include similar elements that may be configured differently or the same, or may include at least one light source and possibly one or more other components (such as the components further described herein). If this light is guided to the sample simultaneously with other light, then one or more characteristics (e.g., wavelength, polarization, etc.) of the light guided to the sample at different angles of incidence may be different such that the light generated by illuminating the sample at different angles of incidence may be distinguishable from one another at the detector.

[0030] In another example, the illumination subsystem may include only one light source (e.g., the source 16 shown in Figure 1 and 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.). Then, the light in each of the different optical paths may be guided to the sample. Multiple illumination channels may be configured to guide 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 guide light having different characteristics to the sample at different times. For example, in some examples, the optical element 18 may be configured as a spectral filter and the properties of the spectral filter may be changed in various different ways (e.g., by swapping out one spectral filter for another) such that different wavelengths of light may be guided to the sample at different times. The illumination subsystem may have any other suitable configuration known in the art for guiding light having different or the same characteristics to the sample sequentially or simultaneously at different or the same angles of incidence.

[0031] The light source 16 may include a broadband plasma (BBP) light source. In this way, the light generated by the light source and guided to the sample may include broadband light. However, the light source may include any other suitable light source, such as a laser. The laser may include any suitable laser known in the art and may be configured to generate light having any suitable wavelength known in the art. Additionally, the laser may be configured to generate monochromatic or near-monochromatic light. In this way, the laser may be a narrowband laser. The light source may also include a multicolor light source that generates light having multiple discrete wavelengths or bands.

[0032] Light from the optical element 18 can be focused onto the sample 14 by the lens 20. Although the lens 20 is shown as a single refractive optical element in Figure 1 , in reality, the lens 20 can comprise several refractive and / or reflective optical elements that combinatorially focus the light from the optical element onto the sample. The illumination subsystem shown in Figure 1 and described herein can comprise any other suitable optical elements (not shown). Examples of such optical elements include, but are not limited to, polarization components, spectral filters, spatial filters, reflective optical elements, apodizers, beam splitters, apertures, and the like, which can comprise any such suitable optical elements known in the art. Additionally, the system can be configured to change one or more elements of the illumination subsystem based on the type of illumination to be used for inspection.

[0033] The inspection subsystem can also comprise a scanning subsystem that is configured to change the location on the sample onto which light is directed and from which light is detected and possibly scan the light across the sample. For example, the inspection subsystem can comprise a stage 22 on which the sample 14 is placed during inspection. The scanning subsystem can comprise any suitable mechanical and / or robotic assembly (which includes the stage 22) that can be configured to move the sample such that light can be directed to different locations on the sample and detected from different locations on the sample. Additionally, or alternatively, the inspection subsystem can be configured such that one or more optical elements of the inspection subsystem perform some scanning of the light across the sample such that light can be directed to different locations on the sample and detected from different locations on the sample. In examples where the light is scanned across the sample, the light can be scanned across the sample in any suitable manner (e.g., in a serpentine path or in a spiral path).

[0034] The inspection subsystem further comprises one or more detection channels. At least one of the detection channels comprises a detector that is configured to detect light from the sample attributable to illuminating the sample with the system and to generate an output in response to the detected light. For example, the inspection subsystem shown in Figure 1 comprises two detection channels: one channel is formed by the light collector 24, the element 26, and the detector 28, and the other channel is formed by the light collector 30, the element 32, and the detector 34. As shown in Figure 1 , the 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 of the detection channels can be configured to detect another type of light from the sample (e.g., reflected light).

[0035] As Figure 1Further shown in, the two detection channels are shown as being located in the plane of the paper and the illumination subsystem is also shown as being located in the plane of the paper. Thus, in this embodiment, the two detection channels are located (e.g., centered) in the plane of incidence. However, one or more of the detection channels may be located outside the plane of incidence. For example, the detection channel formed by the light collector 30, element 32, and detector 34 may be configured to collect and detect light scattered out of the plane of incidence. Thus, this detection channel may generally be referred to as a "side" channel, and this side channel may be centered in a plane generally perpendicular to the plane of incidence.

[0036] Although Figure 1 an embodiment of an inspection subsystem including two detection channels is shown, the inspection 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, element 32, and detector 34 may form one side channel as described above, and the inspection subsystem may include an additional detection channel (not shown) formed as another side channel located on the opposite side of the plane of incidence. Thus, the inspection subsystem may include a detection channel including the light collector 24, element 26, and detector 28 that is centered in the plane of incidence and is configured to collect and detect light at a scattering angle at or near the normal to the sample surface. Thus, this detection channel may generally be referred to as a "top" channel, and the inspection subsystem may also include two or more side channels configured as described above. Thus, the inspection 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 different scattering angle compared to each other light collector.

[0037] As further described above, each detection channel included in the inspection subsystem may be configured to detect scattered light. Thus, Figure 1 the inspection subsystem shown in may be configured for dark field (DF) inspection of a sample. However, the inspection subsystem may also or alternatively include a detection channel configured for bright field (BF) inspection of the sample. In other words, the inspection subsystem may include at least one detection channel configured to detect light specularly reflected from the sample. Thus, the inspection subsystem described herein may be configured to be used for only DF inspection, only BF inspection, or both DF inspection and BF inspection. Although each of the light collectors is shown as a single refractive optical element in Figure 1 it should be understood that each of the light collectors may include one or more refractive optical elements and / or one or more reflective optical elements.

[0038] One or more detection channels may include any suitable detector known in the art. For example, the detector may include 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, then each of the detectors in the detection channel may be configured to detect a specific characteristic (e.g., intensity) of the scattered light, but may not be configured to detect such characteristics that vary according to the position in the imaging plane. Thus, the output generated by each detector included in each detection channel 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, which is configured to generate an imaging signal or image data. Therefore, the inspection subsystem may be configured to generate an image in several ways.

[0039] It should be noted that provided herein Figure 1 to generally illustrate the configuration of the inspection subsystem that may be included in the system embodiments described herein. Obviously, the inspection subsystem configuration described herein may be changed to optimize the performance of the inspection subsystem as is typically done when designing a commercial inspection system. Additionally, the systems described herein may be implemented using existing inspection systems (e.g., by adding the functionality described herein to an existing inspection system) (e.g., the 29xx / 39xx series tools available from KLA Corporation, Milpitas, Calif.). For some such systems, the methods described herein may be provided as an optional functionality of the inspection system (e.g., in addition to other functionality of the inspection system). Alternatively, the inspection systems described herein may be designed "from scratch" to provide a brand-new inspection system.

[0040] The computer subsystem 36 may be coupled to the detector of the inspection 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 can receive the output generated by the detector. The computer subsystem 36 may be configured to perform several functions using the output of the detector as further described herein. The computer subsystem coupled to the inspection subsystem may be further configured as described herein.

[0041] A computer subsystem (and other computer subsystems described herein) coupled to an inspection subsystem 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 host computer system, a workstation, a network device, an Internet device, or other apparatus. In general, the term "computer system" may be broadly defined to cover any apparatus 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, such as a parallel processor. Additionally, the computer subsystem or system may include a computer platform with high-speed processing and software (either as a stand-alone tool or a networked tool).

[0042] If the system includes more than one computer subsystem, then the different computer subsystems may be coupled to each other such that images, data, information, instructions, etc. can be sent between the computer subsystems. For example, computer subsystem 36 may be coupled to computer system 102 via any suitable transmission medium (which may include any suitable wired and / or wireless transmission media known in the art), as shown by the dashed line in Figure 1 . Two or more of such computer subsystems may also be effectively coupled via a shared computer-readable storage medium (not shown).

[0043] Although the inspection subsystem was described above as an optical or light-based inspection subsystem, in another embodiment, the inspection subsystem is configured as an electron beam-based inspection subsystem. In an electron beam type inspection subsystem, the energy directed to the sample includes electrons, and the energy detected from the sample includes electrons. In Figure 1a one such embodiment shown in Figure 1 , the inspection subsystem includes an electron column 122, and the system includes a computer subsystem 124 coupled to the inspection subsystem. The computer subsystem 124 may be configured as described above. Additionally, this inspection subsystem may be coupled to one or more other computer subsystems in the same manner as described above and

[0044] also shown in Figure 1a . As also shown in

[0045] Electrons (e.g., secondary electrons) returned from the sample can be focused onto the detector 134 by one or more elements 132. The one or more elements 132 can include, for example, a scanning subsystem, which can be the same scanning subsystem included in the element 130.

[0046] The electron column can include any other suitable elements known in the art. Additionally, the electron column can be further configured as described in U.S. Patent No. 8,664,594, issued April 4, 2014 to Jiang et al., U.S. Patent No. 8,692,204, issued April 8, 2014 to Kojima et al., U.S. Patent No. 8,698,093, issued April 15, 2014 to Gubbens et al., and U.S. Patent No. 8,716,662, issued May 6, 2014 to MacDonald et al., which are incorporated herein by reference in their entireties.

[0047] Although the electron column is shown in Figure 1a configured such that electrons are directed onto the sample at an oblique angle of incidence and scattered from the sample at another oblique angle, the electron beam can be directed onto the sample and scattered from the sample at any suitable angle. Additionally, the inspection subsystem based on the electron beam can be configured to generate an output of the sample using multiple modes as further described herein (e.g., employing different illumination angles, collection angles, etc.). The multiple modes of the inspection subsystem based on the electron beam can differ in any output generation parameter of the inspection subsystem.

[0048] The computer subsystem 124 can be coupled to the detector 134 as described above. The detector can detect electrons returned from the surface of the sample, thereby forming an electron beam image (or other output) of the sample. The electron beam image can include any suitable electron beam image. The computer subsystem 124 can be configured to perform any of the steps described herein. A system including Figure 1a the inspection subsystem shown in can be further configured as described herein.

[0049] It should be noted that the Figure 1a provided herein is to generally illustrate the configuration of an electron beam inspection subsystem that can be included in the embodiments described herein. Similar to the optical inspection subsystem described above, the configuration of the electron beam inspection subsystem described herein can be modified to optimize the performance of the inspection subsystem as is typically done when designing a commercial inspection system. Additionally, the systems described herein can be implemented using existing inspection systems (e.g., by adding the functionality described herein to an existing inspection system) (e.g., tools available from KLA Corporation). For some such systems, the methods described herein can be provided as an optional functionality of the system (e.g., in addition to other functionality of the system). Alternatively, the systems described herein can be designed "from scratch" to provide a brand new system.

[0050] Although the inspection subsystem was described above as an optical or electron beam inspection subsystem, the inspection subsystem can be an ion beam inspection subsystem. This inspection subsystem can be configured as shown in Figure 1a , except that any suitable ion beam source known in the art can be used to replace the electron beam source. Additionally, the inspection subsystem can include any other suitable ion beam systems, such as the ion beam systems included in commercially available focused ion beam (FIB) systems, helium ion microscope (HIM) systems, and secondary ion mass spectrometry (SIMS) systems.

[0051] The inspection subsystem described herein can be configured to produce an output (e.g., an image) of the sample in multiple modes. Generally, a "mode" is defined by the value of a parameter of the inspection subsystem used to produce the output and / or image of the sample (or the output used to produce the image of the sample). Thus, the modes can differ in the value of at least one of the parameters of the inspection subsystem (except for the location on the sample where the output is produced). For example, in an optical subsystem, different modes can use light of different wavelengths for illumination. The modes can differ in the illumination wavelength as further described herein (e.g., by using different light sources, different spectral filters, etc. for different modes). In another example, different modes can use different illumination channels of the optical subsystem. For instance, as mentioned above, the optical subsystem can include more than one illumination channel. Thus, different illumination channels can be used for different modes. The modes can also or alternatively differ in one or more collection / detection parameters of the optical subsystem. The modes can differ in any one or more changeable parameters of the system (e.g., illumination polarization, angle, wavelength, etc., detection polarization, angle, wavelength, etc.). For example, depending on the ability to scan the sample using multiple modes simultaneously, the inspection subsystem can be configured to scan the sample in different modes in the same scan or different scans.

[0052] In a similar manner, the output produced by the electron beam subsystem can include an output (e.g., an image) produced by the electron beam subsystem using two or more different values of the parameters of the electron beam subsystem. The multiple modes of the electron beam subsystem can be defined by the values of the parameters of the electron beam subsystem used to produce the output and / or image of the sample. Thus, the modes can differ in the value of at least one of the electron beam parameters of the electron beam subsystem. For example, different modes can use different incident angles for illumination.

[0053] As mentioned above, the inspection subsystem is configured to scan energy (e.g., light, electrons, etc.) over a physical version of the sample, thereby producing an output of the physical version of the sample. In this way, the inspection subsystem can be configured as an "actual" subsystem rather than a "virtual" subsystem. However, Figure 1The storage medium (not shown) and computer subsystem 102 shown in the figure may be configured as a “virtual” system. Specifically, the storage medium and the computer subsystem may be configured as a “virtual” inspection system as described in the following co-assigned patents: U.S. Patent No. 8,126,255, issued to Bhaskar et al. on February 28, 2012, and U.S. Patent No. 9,222,895, issued to Duffy et al. on December 29, 2015. The two patents are hereby incorporated by reference in their entireties. The embodiments described herein may be further configured as described in these patents.

[0054] As Figure 2 shown in step 200 of, the computer subsystem may obtain an output in response to a patterned feature formed in an array region on a sample. Obtaining the output may include generating the output with an inspection subsystem configured as described herein. This output obtaining may occur when the computer subsystem and the inspection subsystem are coupled in a single tool, and possibly when the defect detection described herein is being performed on the tool and / or when the output is being generated. In other examples, the computer subsystem may obtain the output from another method, system, or storage medium. For example, the computer subsystem and the inspection subsystem may or may not be coupled to a single tool, and the inspection subsystem, the computer subsystem, or another computer subsystem may store the output generated by the inspection subsystem. The computer subsystem may then obtain the output from the storage medium storing the output. This output obtaining may occur when the computer subsystem is performing the steps described herein outside of the tool and / or after all (or at least some) of the output has been generated. The various elements described above may be configured as further described and shown herein.

[0055] In one embodiment, the array region forms part of a memory device fabricated on a sample. The memory device may include any memory device known in the art, including DRAM. The embodiments described herein present novel cell-to-cell detection methods to improve the sensitivity of the array region. Compared to currently used systems and methods for array region inspection, the embodiments provide several important improvements (which are discussed in further detail herein).

[0056] In one embodiment, the patterned feature and inspection subsystem combinatorially cause the output in response to the patterned feature to have a repeating and non-constant intensity. For example, the embodiments described herein provide novel inspection methods and systems for distinguishable repeating array regions. For the embodiments described herein, a "distinguishable repeating pattern" does not necessarily mean that the pattern on the sample is distinguishable to the inspection subsystem. In fact, in many cases, many wafer patterns are only partially distinguishable to the inspection subsystem. Instead, in the embodiments described herein, "distinguishable" means that the acquired image has a repeating and non-constant intensity. In other words, within each unit cell (the basic repeating pattern of the array region), the image gray levels as seen by the inspection subsystem have some variation that is not caused by noise.

[0057] As Figure 2 shown in step 202 of, the computer subsystem is configured to determine whether the pitch of the patterned feature in the output is an integer number of pixels in the detector of the inspection subsystem that produces the output. The "pitch between the patterned features in the output" does not necessarily have to be the same as the "pitch between the patterned features on the sample". For example, for obvious reasons, the pitch between the imaged patterned features can be different from the physical patterned feature pitch due to the imaging process. The embodiments described herein are primarily concerned with changes in pitch between integer numbers of pixels, regardless of the reason for such changes. For example, even if an inspection recipe can be generated that would result in the patterned features having an integer number of pixels in the output, variations in the performance of the inspection subsystem can cause the imaged patterned features to have a pitch that is not an integer number of pixels.

[0058] Determining whether the pitch between the patterned features in the output is an integer number of pixels can be performed in any suitable manner known in the art. As further described herein, the relationship between the pitch of the patterned features and the output pixels can change from cell to cell, which can be caused by, for example, perturbations or drifts in the inspection subsystem. Thus, this determination step can be performed separately and independently for each portion of the output corresponding to a cell in the array region. However, it is not necessary to perform the determination step for every cell being inspected. For example, the determination step can be performed for the first few cells to establish the relationship between the patterned feature pitch and the output pixels, and then the determination step can be performed for every xth cell thereafter. Specifically, while it may be desirable to check the relationship between the patterned feature pitch and the output pixels for each cell, the determination step can be performed for fewer than all cells in order to save time and money. The steps then performed for each of those portions of the output described herein can then vary depending on whether the pitch between the patterned features in the output is an integer number of pixels.

[0059] When comparing repeating regions other than cells for defect detection as further described herein, the determination steps described above may be performed in the same manner for each of those repeating regions. In other words, although embodiments may be described herein with respect to cell-to-cell detection, the embodiments are not limited to such detection and may be used for defect detection comparing one repeating region to another. Additionally, although the embodiments described herein may be particularly useful for defect detection in an array region where all (or nearly all) of the patterned features contained therein are designed to have the same pitch, the embodiments described herein are not limited to array region inspection. For example, only a portion of the output of a repeating region may be used to perform the determination steps described above, where the pitch between the patterned features should be an integer number of pixels. Depending on whether the pitch between the patterned features in the portion of the output is an integer number of pixels, other steps further described herein (e.g., interpolation and dynamic compensation) may be performed on the entire output generated for the repeating region.

[0060] When the pitch is not an integer number of pixels, the computer subsystem is configured to interpolate the output to produce an interpolated output having a modified pitch of the patterned features in the interpolated output that is an integer number of pixels. The embodiments described herein advantageously use interpolation to handle non-integer and non-uniform cell pitches. For example, when Figure 2 step 202 in [reference] indicates that the pitch between the patterned features is not an integer number of pixels, the computer subsystem performs interpolation step 204. By interpolation, there are no special restrictions in the image acquisition step, and interpolation can reduce the complexity of the system and make the system easier to use. In other words, the system does not have to be configured such that the pitch between the patterned features in the output is an integer number of pixels. Additionally, if the pitch between the patterned features in the output becomes a non-integer number of pixels for any reason (e.g., perturbations or drifts in the tool), then the embodiments described herein can still use the output for defect inspection (e.g., after the interpolation step has been performed on the output).

[0061] Interpolating the output generally may include interpolating the image gray scale intensity, although interpolation may be performed on any aspect of the inspection subsystem output. Interpolating the output may include any suitable type of interpolation known in the art and may be performed in any suitable manner known in the art. For example, although it is important that "interpolation" gives as accurate a result as possible, there are different interpolation methods. The interpolation method used in the embodiments may be selected based on the desired accuracy and throughput of the embodiments compared to the accuracy and throughput of the various interpolation methods known in the art.

[0062] The following non - limiting examples illustrate how and why interpolation is important for the embodiments described herein. Assume that the pattern repeat pitch is 10.3 pixels (i.e., a non - integer pitch). Then, ideally, the image gray levels at x = 6 pixels and x = 16.3 pixels should be the same, and the value at x = 16.3 pixels can be used as a reference for the gray level at x = 6 pixels. For all digital images, gray level values exist only at all integer pixel positions. In other words, the gray level value at x = 16.3 pixels cannot be obtained from the input digital image, and it must be obtained in another way. The inventors have found that interpolation is a fast, simple, and useful way to obtain values at non - integer pixel positions such as 16.3 pixels.

[0063] In one embodiment, the setup of the inspection subsystem for generating the output is not selected based on the pitch of the patterned features on the sample or the pitch between the patterned features in the output. For example, in a repeating array region, adjacent cells are used to generate a reference image of the test cell. Typically, when acquiring an image, the inspection subsystem is set up to ensure that the pattern repeats in the horizontal dimension and the pitch is in integer pixels. With interpolation, there are no special restrictions in the image acquisition step, which can reduce the complexity of the system and make the system easier to use.

[0064] In another embodiment, due to perturbations in the inspection subsystem, the pitch between the patterned features in the output changes from a first repeating region to a second repeating region within the array region. For example, perturbations in the inspection subsystem can cause relatively small pixel size variations and result in non - uniform cell pitch. The embodiments described herein can handle non - uniform cell pitch situations better than currently used array region inspection methods and systems. For example, the steps described herein can be performed on a cell - by - cell (or repeating region - by - repeating region) basis, such that even if some cells (or repeating regions) have non - integer pitch, they can still be successfully used for defect detection.

[0065] In some embodiments, before applying the defect detection method, the computer subsystem is configured to dynamically compensate the interpolated output in response to the patterned features in the first repeating region of the array region to the interpolated output or output in response to the patterned features in the second repeating region of the array region. As Figure 2As shown, the result of the interpolation step 204 can be input into the dynamic compensation step 206. In some array inspection methods, a median cell generated from several adjacent cells can be used as a reference image for the test cell. The median operation helps reduce some noise and variations between adjacent cells. However, it may not be powerful enough to handle cell-to-cell color variations. However, the embodiments described herein can remove cell-to-cell gray-scale variations by performing dynamic compensation, which reduces noise and improves sensitivity. For example, dynamic compensation can be performed to correct color variations between cells. In other words, dynamic compensation minimizes the noise (or differences) between the test image and the reference image. In one such example, dynamic compensation can be performed by adjusting the gray-scale values of the reference image in a systematic manner such that the difference between the test image and the reference image becomes smaller. Motion compensation is performed as part of image processing and can be performed in any suitable manner known in the art.

[0066] In one such embodiment, dynamic compensation reduces the difference between the interpolated output in response to the patterned features in the first repeat region and the interpolated output or output in response to the patterned features in the second repeat region attributed to color variations on the sample. For example, dynamic compensation can be used to handle cell-to-cell color variations by making the reference image more similar to the test image. A better reference image means lower noise and higher detection sensitivity.

[0067] Figure 3 Illustrates how the proposed embodiments can handle cell-to-cell color variations and result in a cleaner difference image and higher detection sensitivity. Image 300 is an example of a test image of an SRAM region where the right-edge cells are brighter than the left cells. This brightness variation across the test image can be caused by color variations on the sample. Images 302 and 306 are the reference image and the difference image, respectively, generated by the currently used method (without using dynamic compensation). As shown by the difference image 306, the cell-to-cell color variations cause relatively large noise on the difference image, which can then be misdetected as defects.

[0068] In contrast, images 304 and 308 are the reference image and the difference image, respectively, generated by the proposed embodiment (using dynamic compensation). As can be seen by comparing the test image 300 with the reference image 304, the color variations present between the test image 300 and the reference image 302 are substantially removed by dynamic compensation. In other words, the brightness variation between the test image 300 and the reference image 304 is much smaller than the brightness variation between the test image 300 and the reference image 302.

[0069] In this manner, using reference image 304 instead of reference image 302 for defect detection reduces the impact of color variations on the inspection. For example, as can be seen by comparing difference image 308 generated by subtracting reference image 304 from test image 300 with difference image 306 generated by subtracting reference image 302 from test image 300, difference image 308 is much cleaner than difference image 306. In other words, difference image 308 contains much less noise than difference image 306. Therefore, any defect detection performed using difference image 308 will detect fewer spurious points than defect detection performed using difference image 306.

[0070] A "spurious point" (which is sometimes used interchangeably with "spurious point defect") as used herein is generally defined as an event detected on a sample that is not in fact an actual defect on the sample. Spurious points that are not actually defects can be detected as being attributable to non-defect noise sources on the sample (e.g., die in metal lines on the sample, signals from underlying layers or materials on the sample, line edge roughness (LER), relatively small critical dimensions (CDs) in patterned features, thickness variations, etc.) and / or to marginality of the inspection system itself or its configuration used for the inspection.

[0071] The computer subsystem is also configured to detect defects in the array region by applying a defect detection method to the interpolated output. For example, as Figure 2 shown, the computer subsystem can perform defect detection step 208 on the result of dynamic compensation step 206. In this manner, the embodiments described herein are capable of inspecting resolvable repeating patterns with non-integer pitch in pixels via the interpolation steps further described herein. Applying the defect detection method to the interpolated output can be performed as further described herein or in any other manner known in the art. Additionally, the defect detection method can include any defect detection method known in the art, such as MDAT, which is a defect detection algorithm used by some inspection systems commercially available from KLA, or another suitable commercially available defect detection method and / or algorithm.

[0072] In one embodiment, the defect detection method includes comparing the interpolated output generated for one cell in the array region with the output or interpolated output generated for a different cell in the array region. For example, the defect detection method can include comparing the interpolated output generated for one cell with the interpolated or original output for another cell, and the different cells can be located in the same array region or the same die. Comparing different cells with each other can include generating a difference image. For example, the computer subsystem can generate a difference image by subtracting reference image 304 from test image 300, such as Figure 3 difference image 308 shown (thus essentially comparing the two images).

[0073] Both a reference image and a test image that subtracts the reference image therefrom can be generated for the same array region on a sample (and will thus necessarily be located in the same die on the sample). For example, the reference image and the test image can be images of different cells in the same array region. When a die contains multiple array regions, the reference image and the test image can also be images of different cells in different array regions. However, preferably, the reference image and the test image are not images of array regions in different dies, because this can introduce noise into defect detection (since different dies are spaced farther apart than cells or array regions in the same die, cross-sample variations can introduce noise in the comparison; and different dies can be processed separately in one or more steps such as lithographic exposure, which can also introduce differences in the dies that can generate noise in the comparison).

[0074] The reference image can be an output of neighboring cells or an interpolated output, or the computer subsystem can generate the reference image from the outputs and / or interpolated outputs of multiple cells neighboring or near the test cell. For example, considering the above-mentioned example where the pattern repeats every 10.3 pixels, if x = 6 pixels is a test image pixel, then by interpolation, the computer subsystem can generate a first reference image pixel of x = 16.3 pixels. In a similar manner, the computer subsystem can also obtain a second reference image pixel of x = 26.6 pixels and a third reference image pixel of x = 36.9 pixels (by adding the spacing between 10.3 pixels to the test image pixel and then to each reference image pixel). After generating multiple reference images by interpolation, the median of this multiple of reference images can be generated and used as the final reference image for comparison with the original test image. The defect detection method can also include applying a threshold to the difference image and determining that any pixel in the difference image having a value higher than the threshold corresponds to a defect, while any pixel in the difference image having a value lower than the threshold does not correspond to a defect.

[0075] In one embodiment, when the spacing is an integer number of pixels, the computer subsystem is configured to detect defects in the array region by applying the defect detection method to the output. For example, when the cell spacing is a non-integer number of pixels, the embodiments described herein can always perform the interpolation step described above. However, when the cell spacing is an integer number of pixels, the interpolation step can be skipped. In one such example, as Figure 2 shown, when the spacing between the patterned features is determined to be an integer number of pixels in step 202, the output can be input to the dynamic compensation step 210 and then to the defect detection step 208 without performing any interpolation step on the output. However, even when interpolation is performed for less than all of the output (i.e., only a portion of the output), the input to the interpolation step described above can still be the entire output (such as a complete digital image).

[0076] The defect detection method can be applied to the output (when interpolation of the output is not required) and can be performed in other ways as described herein. Additionally, interpolated outputs and outputs for which interpolation is not performed can be jointly input to the defect detection method. For example, the defect detection method should process interpolated and non-interpolated outputs in the same way. In other words, in defect detection, whether the input is interpolated should be immaterial. Thus, the defect detection method need not distinguish between interpolated and non-interpolated outputs or process interpolated and non-interpolated outputs differently.

[0077] Additionally, depending on the repeating region for which interpolated or non-interpolated output is generated, the defect detection method may require both interpolated and non-interpolated outputs for defect detection. For example, for a first cell, interpolation may not be required and thus the test image of the cell used in defect detection may be the original, non-interpolated output. However, the reference for the first cell may be generated from the interpolated output generated for a second cell adjacent to the first cell and the original, non-interpolated output generated for a third cell also adjacent to the first cell. Then, the defect detection method may require the interpolated and non-interpolated outputs generated for the second and third cells, respectively, to generate a reference, subtract the reference from the test image (the non-interpolated output of the first cell), and apply a threshold to the resulting difference image. Then, as can be seen from this example, providing both interpolated and non-interpolated or original outputs to the defect detection method can be advantageous such that the defect detection method has any and all inputs required to perform defect detection.

[0078] In another embodiment, before applying the defect detection method to the output, the computer subsystem is configured to dynamically compensate an output responsive to a patterned feature in a first repeating region in the array area to an interpolated output or output responsive to a patterned feature in a second repeating region in the array area. For example, the embodiments described herein can perform dynamic compensation for interpolated outputs and any outputs that do not require interpolation as further described herein. In other words, the embodiments described herein can perform dynamic compensation for all outputs used for inspection without exception, regardless of whether the output used for defect detection has been interpolated. As Figure 2 shown, for example, the computer subsystem can perform a dynamic compensation step 206 for the interpolated output and a dynamic compensation step 210 for the non-interpolated (or original) output. Generally, to simplify the process, the dynamic compensation performed in steps 206 and 210 can be performed in the same way (e.g., using the same dynamic compensation method or algorithm), although this is not necessary. Additionally, although the dynamic compensation steps 206 and 210 are Figure 2 shown as separate steps, the dynamic compensation need not be performed separately, and all outputs (interpolated or non-interpolated) can be input to the same dynamic compensation step. The dynamic compensation 210 can be performed in other ways as further described herein.

[0079] In a further embodiment, dynamic compensation reduces the difference between the output in response to the patterned features in the first repeat region and the interpolated output or output in response to the patterned features in the second repeat region that is attributable to color variations on the sample. For example, dynamic compensation step 210 has the same benefits as dynamic compensation step 206 described further above.

[0080] When a wafer is loaded onto an inspection tool in a fixed orientation, some patterns repeat only along the x-dimension. Some patterns repeat only along the y-dimension. Some patterns may also repeat along both the x-dimension and the y-dimension. The dimension across which a pattern on a wafer repeats is wafer-dependent and can vary depending on the design of the wafer. The embodiments described herein have several advantages for samples having patterns that repeat in two orthogonal dimensions. When setting up an inspection recipe, the user can indicate whether the pattern repeats in the x, y, or both x and y. The embodiments described herein can then process different repeating patterns in the same pass or even simultaneously.

[0081] In some embodiments, an array region repeats on a first dimension on a sample, an additional array region repeats on a second dimension on the sample that is orthogonal to the first dimension, and the defect detection method includes comparing repeat regions within the array region to each other and comparing repeat regions within the additional array region to each other, and performing determination, interpolation, and detection steps for the array region and the additional array region using outputs generated by an inspection subsystem in a single pass of the sample. In this way, the embodiments can support both horizontally repeating array patterns and vertically repeating array patterns.

[0082] In one such example, Figure 4 A hypothetical and non-limiting example of a portion 400 of a sample on which array regions 402 and 404 are formed is shown. Array region 402 repeats on a first dimension (x-dimension) on the sample, and array region 404 repeats on a second dimension (y-dimension) on the sample that is orthogonal to the first dimension. For example, if each rectangular region shown within each array region is considered a repeat region, then the repeat regions within array region 402 repeat in the x-dimension, and the repeat regions within array region 404 repeat in the y-dimension. The array regions may also differ in aspects other than the dimension along which they exactly repeat. For example, array regions 402 and 404 may include different types of patterned features or the same type of patterned features but having one or more different characteristics (such as size and / or pitch).

[0083] However, in general, even if the array regions 402 and 404 contain the same type of patterned features with all the same characteristics, the images of the array regions cannot be compared to each other for defect detection because they repeat in different dimensions. However, in the embodiments described herein, the inspection subsystem can produce outputs for both of the array regions in the same pass of the sample. In other words, after scanning one of the scanned array regions and before scanning the other array region, the inspection subsystem does not stop or pause the scan and reposition or reorient the sample. Instead, in other steps described herein, the outputs produced for different array regions in the same scan can be processed separately and independently. For example, interpolation, dynamic compensation, and defect detection steps can be performed on an array region using only the output produced for that array region. Then interpolation, dynamic compensation, and defect detection steps can be performed on the other array region using only the output produced for that other array region. However, these steps can be performed as further described herein, regardless of the array region for which the steps are performed.

[0084] One benefit of this capability is that the proposed embodiments do not have an array orientation limitation. If a sample has two array regions that repeat in different dimensions, then with the embodiments described herein, the system does not need to perform two passes of inspection with two different sample orientations as in currently used systems and methods. The system can complete the inspection of both array regions in the same pass, which means that the throughput can be 2 times that of currently used systems and methods. Depending on the user's preference, defects detected in different array regions can be reported separately or jointly.

[0085] In this way, through the interpolation steps described herein, the embodiments can simultaneously inspect horizontal and vertical repeating patterns in 1 scan pass, which doubles the throughput. A DRAM wafer is a good example of why this is useful. In one such embodiment, the array region is the sense amplifier (SA) region of a DRAM array, and the additional array region is the sub-word line driver (SWD) region of the DRAM array. For example, DRAM wafers typically have repeating SA and SWD regions. However, the SA and SWD are always orthogonal to each other. In currently used systems and methods, this wafer is loaded, one of those regions is inspected, then the wafer is unloaded and rotated, and then the other region is inspected. However, in the embodiments described herein, the inspection of the SA and SWD regions can be performed in 1 pass, as long as the optical mode allows it. In other words, as long as the outputs for the inspection of the two regions can be produced in the same pass, regardless of whether this means using only a single mode or multiple modes simultaneously, regions that repeat in orthogonal directions can be inspected using the outputs with the embodiments described herein.

[0086] In another embodiment, the array region repeats in a first dimension on the sample and a second dimension on the sample that is orthogonal to the first dimension. The defect detection method includes comparing a first repeating region in the array region with second and third repeating regions in the array region, where the first and second repeating regions repeat in the first dimension and the first and third repeating regions repeat in the second dimension. In this way, the embodiment can support both horizontally repeating array patterns and vertically repeating array patterns.

[0087] In one such example, Figure 5 A hypothetical and non-limiting example of a portion 500 of a sample on which an array region 502 is formed is shown. The array region 502 repeats in a first dimension (x-dimension) on the sample and a second dimension (y-dimension) on the sample that is orthogonal to the first dimension. For example, if each square region shown in the array region 502 is considered a repeating region, then the repeating regions in the array region 502 repeat in the x and y dimensions.

[0088] For this array region, defect detection performed by the embodiments described herein can include comparing the output (interpolated or non-interpolated) generated for a first one of the repeating regions (e.g., a cell) with the output of at least one other repeating region to the left and / or right of the first repeating region and comparing the output of the first one of the repeating regions with the output of at least one other repeating region above and / or below the first repeating region (interpolated or non-interpolated). Each of these comparisons can include subtracting a reference image (from a repeating region other than the first repeating region) from the test image of the first repeating region to thereby generate a difference image.

[0089] In some examples, the reference image for the first comparison (in the first repeating dimension) can be generated from the output generated for more than one repeating region in the first repeating dimension. For example, for a test cell in the first row of cells that repeats in the x-dimension, a median reference cell can be generated from all other cells in the first row. The reference image may or may not be generated from the output generated for more than one repeating region in the second repeating dimension for the second comparison (in the second repeating dimension). For example, for a test cell in the first column of cells that repeats in the y-dimension, a median reference cell can be generated from all other cells in the first column. Alternatively, for a test cell in the first column of cells that repeats in the y-dimension, a single, neighboring cell in the first column can be used as the reference cell. In this way, the reference images for the comparisons performed for different repeating dimensions may or may not be generated in the same way. Other parameters for defect detection performed on cells that repeat in different dimensions can also be different or the same.

[0090] In one such embodiment, the defect detection method includes determining that a defect exists at a location in the first repeat region only if the result of comparing the first repeat region with both the second and third repeat regions indicates the presence of a defect at the location in the first repeat region. In this way, the embodiments described herein can be configured for dual detection, where each detection is performed in a different repeat dimension. For example, as described above, a first difference image can be generated for a test cell from the test cell and at least one other cell repeated in a first dimension, and a second difference image can be generated for the test cell from the test cell and at least one other cell repeated in a second dimension. Then, a threshold can be applied to both the first and second difference images. A defect can be reported at a location in the test cell only if the first and second difference images have values above the threshold at the corresponding location. One benefit of this capability is that when the array region is repeated in both the horizontal and vertical dimensions, the proposed embodiments can generate two reference images by leveraging the horizontal and vertical repeatability. Dual detection can be used, and spurious points can be further suppressed.

[0091] The computer subsystem can generate inspection results that can include the results of any of the steps described herein. The inspection results can include information about the detected defect (e.g., defect ID, location of the bounding box of the detected defect, etc.), size, detection score, information about the defect classification (e.g., class label or ID, etc.), or any such suitable information known in the art. The results of the defect can be generated by the computer subsystem in any suitable manner. The results of the defect can have any suitable form or format (e.g., standard file type). The computer subsystem can generate and store the results such that the computer subsystem and / or another system or method can use the results to perform one or more functions for the sample or another sample of the same type.

[0092] The computer subsystem can be configured to store the information about the detected defect in any suitable computer-readable storage medium. The information can be stored together with any of the results described herein and can be stored in any manner known in the art. The storage medium can include any of the storage media described herein or any other suitable storage medium known in the art. After the information has been stored, the information can be accessed in the storage medium and used by any of the method or system embodiments described herein, formatted to be displayed to the user, used by another software module, method, or system, etc.

[0093] The results and information generated by performing an inspection on a sample can be used in various ways through the embodiments described herein and / or other systems and methods. Such functions include (but are not limited to) changing a process (e.g., a manufacturing process or step) that has been or will be performed on the inspected sample or another sample in a feedback or feedforward manner. For example, a computer subsystem can be configured to determine one or more changes to a process that has been or will be performed on a sample inspected as described herein based on detected defects. The change to the process can include any suitable change to one or more parameters of the process. The computer subsystem preferably determines those changes such that defects can be reduced or prevented on other samples on which the revised process is performed, defects can be corrected or eliminated on a sample in another process performed on the sample, defects can be compensated for in another process performed on the sample, etc. The computer subsystem can determine such changes in any suitable manner known in the art.

[0094] Those changes can then be sent to a semiconductor manufacturing system (not shown) or a storage medium (not shown) accessible to 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 computer subsystem and / or inspection subsystem described herein can be coupled to a semiconductor manufacturing system (e.g.) via one or more common elements such as a housing, a power supply, a sample handling device or mechanism, etc. The semiconductor manufacturing system can 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.

[0095] Compared to other methods and systems for detecting defects in an array region on a sample, the embodiments described herein have many advantages. For example, the embodiments described herein can handle non-integer and non-uniform spacing in a repeating array region. Additionally, the embodiments described herein can remove cell-to-cell color variations between a test image and a reference image. Further, when a sample has two different array regions that repeat in different dimensions, the embodiments described herein can streamline the currently used two-pass inspection into a one-pass inspection, resulting in a two-fold throughput. In additional instances, when the array region repeats simultaneously in both the horizontal and vertical dimensions, double detection can help further suppress spurious points.

[0096] The advantages described above are achieved by many important new features of the embodiments described herein. For example, the embodiments described herein provide new reference generation and defect detection methods for distinguishable repetitive array regions to improve detection sensitivity in the inspection of array regions. One new feature of the embodiments described herein is the use of interpolation to handle non-integer and non-uniform cell pitches. Another new feature of the embodiments described herein is the use of dynamic compensation to remove cell-to-cell color variations. An additional new feature of the embodiments described herein is the support for the detection of both vertically repetitive array regions and horizontally repetitive array regions. Yet another new feature of the embodiments described herein is the use of dual detection to suppress spurious points when the array region repeats in both the horizontal dimension and the vertical dimension simultaneously.

[0097] Each embodiment of the system described above can be combined together into a single embodiment. In other words, unless otherwise mentioned herein, system embodiments are not mutually exclusive with any other system embodiments.

[0098] Another embodiment relates to a computer-implemented method for detecting defects in an array region on a sample. The method includes obtaining an output generated by an inspection subsystem in response to a patterned feature formed in the array region on the sample. The method further includes determining whether the pitch of the patterned feature in the output is an integer number of pixels in a detector of the inspection subsystem that generated the output. When the pitch is not an integer number of the pixels, the method includes interpolating the output to produce an interpolated output having a modified pitch of the patterned feature in the interpolated output that is an integer number of pixels. The method further includes detecting a defect in the array region by applying a defect detection method to the interpolated output. The obtaining, determining, interpolating, and detecting steps are performed by a computer subsystem coupled to the inspection subsystem, and the computer subsystem can be configured according to any one of the embodiments described herein.

[0099] Each step of the method can be performed as further described herein. The method can further include any other steps that can be performed by the inspection subsystem and / or the computer subsystem described herein. Additionally, the method described above can be performed by any one of the system embodiments described herein.

[0100] An additional 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 detecting defects in an array region on a sample. One such embodiment is shown in Figure 6 . Specifically, as Figure 6As shown, non-transitory computer-readable medium 600 includes program instructions 602 that can be executed on computer system 604. A computer-implemented method can include any steps of any of the methods described herein.

[0101] Program instructions 602 for implementing methods such as those described herein can be stored on computer-readable medium 600. The computer-readable medium can be a storage medium such as a magnetic disk or optical disk, magnetic tape, or any other suitable non-transitory computer-readable medium known in the art.

[0102] The program instructions can 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 can be implemented using ActiveX controls, C++ objects, JavaBeans, Microsoft Foundation Classes (“MFC”), SSE (Streaming SIMD Extensions), or other techniques or methods as needed.

[0103] Computer system 604 can be configured according to any of the embodiments described herein.

[0104] In view of this description, those skilled in the art will appreciate further modifications and alternative embodiments of various aspects of the present invention. For example, methods and systems are provided for detecting defects in an array region on a sample. Accordingly, this description should be construed as illustrative only and for the purpose of teaching those skilled in the art the general manner of carrying out the present invention. It will be understood that the forms of the present invention shown and described herein are to be taken as the presently preferred embodiments. As will be apparent to those skilled in the art after having the benefit of this description of the present invention, elements and materials can be substituted for those illustrated and described herein, parts and processes can be reversed, and certain properties of the present invention can be utilized alone. Changes can be made to the elements herein without departing from the spirit and scope of the present invention as described in the appended claims.

Claims

1. A system configured to detect defects in an array region on a sample, comprising: An inspection subsystem configured to generate an output in response to a patterned feature formed in the array region on the sample; And A computer subsystem configured to: Determine whether the pitch of the patterned feature in the output is an integer number of pixels in a detector of the inspection subsystem that generates the output; When the pitch is not an integer number of the pixels, interpolate the output to generate an interpolated output having a modified pitch of the patterned feature in the interpolated output, the modified pitch being an integer number of the pixels; And Detect defects in the array region by applying a defect detection method to the interpolated output.

2. The system according to claim 1, wherein the patterned feature and the inspection subsystem jointly cause the output in response to the patterned feature to have a repetitive and non-constant intensity.

3. The system according to claim 1, wherein the defect detection method includes comparing the output generated for one cell in the array region with the output generated for a different cell in the array region.

4. The system according to claim 1, wherein the setting of the inspection subsystem for the generation is not selected based on the pitch of the patterned feature on the sample or the pitch of the patterned feature in the output.

5. The system according to claim 1, wherein due to perturbations in the inspection subsystem, the pitch of the patterned feature in the output changes from a first repeating region to a second repeating region within the array region.

6. The system according to claim 1, wherein before applying the defect detection method, the computer subsystem is further configured to dynamically compensate the interpolated output in response to the patterned feature in a first repeating region of the array region to the interpolated output or the output in response to the patterned feature in a second repeating region of the array region.

7. The system according to claim 6, wherein the dynamic compensation reduces the difference between the interpolated output in response to the patterned feature in the first repeating region of the sample and the interpolated output or the output in response to the patterned feature in the second repeating region of the sample due to color variations on the sample.

8. The system according to claim 1, wherein when the pitch is an integer number of the pixels, the computer subsystem is further configured to detect defects in the array region by applying the defect detection method to the output.

9. The system according to claim 8, wherein before applying the defect detection method to the output, the computer subsystem is further configured to dynamically compensate the output in response to the patterned feature in a first repeating region of the array region to the interpolated output or the output in response to the patterned feature in a second repeating region of the array region.

10. The system according to claim 9, wherein the dynamic compensation reduces the difference between the output in response to the patterned feature in the first repeat region and the interpolated output or the output in response to the patterned feature in the second repeat region attributable to color variations on the sample.

11. The system according to claim 1, wherein the array region repeats in a first dimension on the sample, wherein an additional array region repeats in a second dimension on the sample orthogonal to the first dimension, wherein the defect detection method includes comparing repeat regions in the array region with each other and comparing repeat regions in the additional array region with each other, and wherein the determination, interpolation, and detection are performed on the array region and the additional array region using the output generated by the inspection subsystem in a single pass over the sample.

12. The system according to claim 11, wherein the array region is a sense amplifier region of a dynamic random access memory array, and wherein the additional array region is a sub-word line driver region of the dynamic random access memory array.

13. The system according to claim 1, wherein the array region repeats in a first dimension on the sample and in a second dimension on the sample orthogonal to the first dimension, wherein the defect detection method includes comparing a first repeat region in the array region with second and third repeat regions in the array region, wherein the first and second repeat regions repeat in the first dimension, and wherein the first and third repeat regions repeat in the second dimension.

14. The system according to claim 13, wherein the defect detection method further includes determining that a defect exists at a location only if the results of comparing the first repeat region with both of the second and third repeat regions indicate the presence of a defect at the location in the first repeat region.

15. The system according to claim 1, wherein the array region forms part of a memory device fabricated on the sample.

16. The system according to claim 1, wherein the sample includes a wafer.

17. The system according to claim 1, wherein the inspection subsystem is further configured to be an inspection subsystem based on light.

18. The system according to claim 1, wherein the inspection subsystem is further configured to be an inspection subsystem based on an electron beam.

19. A non-transitory computer-readable medium storing program instructions that can be executed on a computer system to perform a computer-implemented method for detecting defects in an array region on a sample, wherein the computer-implemented method includes: obtaining an output generated by an inspection subsystem in response to a patterned feature formed in an array region on a sample; determining whether a pitch of the patterned feature in the output is an integer number of pixels in a detector of the inspection subsystem that generated the output; When the pitch is not an integer number of the pixels, interpolate the output to produce an interpolated output having a modified pitch of the patterned feature in the interpolated output, the modified pitch being an integer number of the pixels; and detect defects in the array region by applying a defect detection method to the interpolated output.

20. A computer-implemented method for detecting defects in an array region on a sample, comprising: obtaining an output produced by an inspection subsystem in response to a patterned feature formed in an array region on a sample; determining whether a pitch of the patterned feature in the output is an integer number of pixels in a detector of the inspection subsystem that produced the output; when the pitch is not an integer number of the pixels, interpolate the output to produce an interpolated output having a modified pitch of the patterned feature in the interpolated output, the modified pitch being an integer number of the pixels; and detecting defects in the array region by applying a defect detection method to the interpolated output, wherein the obtaining, determining, interpolating, and detecting are performed by a computer subsystem coupled to the inspection subsystem.

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