Charged particle evaluation method and system

Abstract

A charged particle evaluation method for identifying candidate defects in a sample by scanning a charged particle beam across the sample, the method including: acquiring a first reference image from a first region of the sample and a second reference image from a second region of the sample using a charged particle evaluation device; acquiring a sample image from a third region of the sample using the charged particle evaluation device; and comparing the sample image with the first reference image and the second reference image to identify any candidate defects in the third region, wherein the first reference image and / or the second reference image are acquired with higher fidelity than the sample image.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to European Patent Application No. 22209971.5, filed November 28, 2022, which is incorporated herein by reference in its entirety.

[0002] FIELD OF THE INVENTION

[0002] Embodiments provided herein generally relate to charged particle characterization systems and methods of operating charged particle characterization systems. [Background technology]

[0003]

[0003] When manufacturing semiconductor integrated circuit (IC) chips, unwanted pattern defects inevitably occur on substrates (i.e., wafers) or masks during the fabrication process, for example as a result of optical effects and accidental particles, thereby reducing yield. Therefore, monitoring the extent of unwanted pattern defects is an important process in the manufacture of IC chips. More generally, inspection and / or measurement of the surface of a substrate or other object / material is an important process during and / or after its manufacture.

[0004] Charged particle beam pattern inspection devices are used to inspect objects, which may be referred to as samples, for example, to detect pattern defects. These devices typically use electron microscopy techniques, such as scanning electron microscopes (SEMs). In some SEMs, a primary electron beam of relatively high-energy electrons is targeted with a final deceleration step to land on the sample with a relatively low landing energy. The electron beam is focused as a probing spot on the sample. Interaction of the landing electrons from the electron beam with material structures at the probing spot causes signal electrons, such as secondary electrons, backscattered electrons, or Auger electrons, to be emitted from the surface. The signal electrons can be emitted from the material structures of the sample. Scanning the primary electron beam as a probing spot across the sample surface can cause signal electrons to be emitted across the surface of the sample. By collecting these emitted signal electrons from the sample surface, the pattern inspection device can obtain an image representative of the characteristics of the material structure of the sample's surface.

[0005]

[0005] When pattern inspection devices are used to detect defects on samples at high throughput, the image data may contain a significant level of noise. U.S. Patent No. 8,712,184 B1 and U.S. Patent No. 9,436,985 B1 describe methods for reducing noise or improving the signal-to-noise ratio in images acquired from scanning electron microscopes. Nevertheless, further improvements in increasing throughput and / or reducing noise or the effects of noise are desirable. Summary of the Invention

[0006]

[0006] An object of the present disclosure is to provide an embodiment that can increase throughput without or with less noise or noise effects in images, particularly reference images.

[0007] According to a first aspect of the present invention, there is provided a charged particle characterization method for identifying candidate defects in a sample by scanning a charged particle beam across the sample, the method comprising: acquiring a first reference image from a first region of the sample and a second reference image from a second region of the sample using a charged particle characterization device; acquiring a sample image from a third region of the sample using a charged particle characterization device; comparing the sample image to the first reference image and the second reference image to identify any candidate defects within the third region; wherein the first reference image and / or the second reference image are acquired with higher fidelity than the sample image.

[0008] According to a second aspect of the present invention, there is provided a charged particle evaluation method for identifying candidate defects in a sample by scanning a charged particle beam across the sample, the method comprising: acquiring a reference image from a first region (preferably a reference region) of the sample using a charged particle characterization device; acquiring a sample image from a second region of the sample (preferably the sample region) using a charged particle characterization device; comparing the sample image with a reference image to determine whether there are defects within the sample area; generating a new reference image by combining the sample image and the reference image; acquiring additional sample images from additional regions of the sample using the charged particle characterization device; and comparing the additional sample image with the new reference image to determine whether there are defects in the additional areas.

[0009] According to a third aspect of the present invention there is provided a charged particle characterisation method for detecting defects in a sample by scanning a charged particle beam across the sample, the method comprising: acquiring a reference image from a first region of the sample using a charged particle characterization device; acquiring an image of the sample from a second region of the sample using a charged particle characterization device; comparing the sample image with the reference image to identify any candidate defects within the sample area; , where the reference image is acquired with higher fidelity than the sample image.

[0010]

[0010] According to a fourth aspect of the present invention, a computer program for controlling a charged particle evaluation apparatus is provided, the computer program including instructions which, when executed by the charged particle evaluation apparatus, cause the charged particle evaluation apparatus to perform the method described above.

[0011] According to a fifth aspect of the present invention, there is provided a charged particle characterization apparatus for identifying candidate defects in a sample by scanning a charged particle beam across the sample, the apparatus comprising: a detector unit configured to output a digital detection signal of pixel values ​​in response to signal particles incident from the sample; a scanning unit for scanning the sample and the charged particle beam relative to one another; a controller configured to control the detector unit and the scanning unit to acquire a first reference image from a first region of the sample and a second reference image from a second region of the sample, and to acquire a sample image from a third region of the sample; a comparator configured to compare the sample image with the first reference image and the second reference image to identify any candidate defects within the third region; wherein the first reference image and / or the second reference image are acquired with higher fidelity than the sample image. [Brief explanation of the drawings]

[0012]

[0012] The above and other aspects of the present disclosure will become more apparent from the description of exemplary embodiments taken in conjunction with the accompanying drawings.

[0013] [Figure 1]

[0013] FIG. 1 is a schematic diagram illustrating an exemplary charged particle beam inspection system. [Figure 2]

[0014] 2 is a schematic diagram illustrating an exemplary multi-beam charged particle characterization apparatus that is part of the exemplary charged particle beam inspection system of FIG. 1. [Figure 3]

[0015] FIG. 1 is a flow diagram illustrating an exemplary method for evaluating a sample. [Figure 4]

[0016] FIG. 1 is a flow diagram of a method for acquiring a reference image according to one embodiment. [Figure 5]

[0017] FIG. 1 is a flow diagram of a method for acquiring a reference image according to one embodiment. [Figure 6]

[0018] FIG. 1 is a flow diagram of a method for updating a reference image according to one embodiment. [Figure 7]

[0019] FIG. 1 is a diagram of a data processing system according to one embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0014]

[0020] The schematic diagrams show the components described below, however, the components depicted in the diagrams are not to scale.

[0015]

[0021] Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. The following description refers to the accompanying drawings, in which, unless otherwise indicated, like numbers in different drawings represent the same or similar elements. The implementations described in the following description of exemplary embodiments do not represent all implementations consistent with the present invention. Instead, the implementations are merely examples of apparatus and methods consistent with aspects related to the present invention, as set forth in the appended claims.

[0016]

[0022] Increased computing power in electronic devices, which reduces the physical size of devices, can be achieved by significantly increasing the packing density of circuit components such as transistors, capacitors, and diodes on IC chips. This has been made possible by improvements in resolution, which allow for the creation of ever-smaller structures. For example, an IC chip in a smartphone the size of a thumbnail, available before 2019, can contain over 2 billion transistors, each less than 1 / 1000 the size of a human hair. It is therefore not surprising that semiconductor IC manufacturing is a complex and time-consuming process with hundreds of individual steps. An error in even a single step can dramatically affect the functionality of the final product. The goal of a manufacturing process is to improve the overall yield of the process. For example, to achieve a 75% yield for a 50-step process (where step can refer to the number of layers formed on a wafer), each individual step must have a yield greater than 99.4%. If each individual step had a 95% yield, the overall process yield would be as low as 7%.

[0017]

[0023] While high process yields are desirable in IC chip manufacturing facilities, maintaining high substrate (i.e., wafer) throughput, defined as the number of substrates processed per hour, is also essential. High process yields and high substrate throughput can be affected by the presence of defects. This is especially true when operator intervention is required to investigate the defects. Therefore, high-throughput detection and identification of microscale and nanoscale defects by inspection devices, such as scanning electron microscopes ("SEMs"), is essential to maintaining high yields and low costs.

[0018]

[0024] An embodiment of an SEM includes a scanning device and a detector system. The scanning device includes an illumination system including an electron source for generating primary electrons (or charged particles) and a projection system for scanning a sample, such as a substrate, with one or more focused beams (or multiple beams) of primary electrons. The multiple beams may be arranged as a multibeam. The multiple beams may have a multibeam configuration (which may have the form of a grid) that can be directed along a multibeam path toward the sample. Together, at least the illumination system or illumination system and the projection system or projection system may be referred to as an electron-optical system or apparatus. The primary electrons interact with the sample and generate secondary electrons. The detector system captures the secondary electrons from the sample as it is scanned, allowing the SEM to generate an image of the scanned area of ​​the sample. For high-throughput inspection, some inspection systems use multiple focused beams of primary electrons, i.e., multiple beams. The component beams of a multiple beam may be referred to as subbeams or beamlets. The multiple beams can simultaneously scan different portions of the sample. Thus, a multibeam inspection system can inspect samples much faster than a single-beam inspection system.

[0019]

[0025] Known implementations of multi-beam inspection devices are described below.

[0020]

[0026] Although the description and drawings are directed to electron-optical systems, it is understood that the embodiments are not used to limit the present disclosure to particular charged particles. Thus, throughout this specification, references to electrons can be considered to be references to charged particles more generally, and charged particles are not necessarily electrons.

[0021]

[0027] Reference is now made to Figure 1, which is a schematic diagram illustrating an exemplary charged particle beam characterization system 100 (or simply characterization system), which may also be referred to as a charged particle beam inspection system, or simply an inspection system, or a charged particle metrology system, or simply a metrology system. The charged particle beam characterization system 100 of Figure 1 includes a main chamber 10, a load lock chamber 20, an electron beam system 40, a front-end equipment module (EFEM) 30, and a controller 50. The electron beam system 40 is located within the main chamber 10.

[0022]

[0028] The EFEM 30 includes a first loading port 30a and a second loading port 30b. The EFEM 30 may include one or more additional loading ports. The first loading port 30a and the second loading port 30b may receive, for example, a substrate front-opening unified pod (FOUP) containing a substrate (e.g., a semiconductor substrate or a substrate made of other material) or a sample to be inspected (hereinafter, the substrate, wafer, and sample are collectively referred to as "sample"). One or more robotic arms (not shown) within the EFEM 30 transport the sample to the load lock chamber 20.

[0023]

[0029] The load lock chamber 20 is used to remove gas from around the sample. This creates a vacuum, which is a local gas pressure lower than the pressure of the surrounding environment. The load lock chamber 20 may be connected to a load lock vacuum pumping system (not shown), which removes gas particles within the load lock chamber 20. Operation of the load lock vacuum pumping system allows the load lock chamber to reach a first pressure below atmospheric pressure. After the first pressure is reached, one or more robotic arms (not shown) transport the sample from the load lock chamber 20 to the main chamber 10. The main chamber 10 is connected to the main chamber vacuum pumping system (not shown). The main chamber vacuum pumping system removes gas particles within the main chamber 10 so that the pressure around the sample reaches a second pressure below the first pressure. After the second pressure is reached, the sample is transported to the electron beam system 40, where it can be inspected. The electron beam system 40 may include a multi-beam electron optical device (also referred to as an electron optical column or device).

[0024]

[0030] The controller 50 is electronically connected to the electron beam system 40. The controller 50 may be a processor (e.g., a computer) configured to control the charged particle beam evaluation apparatus 100. The controller 50 may also include circuitry, which may be referred to as processing circuitry, configured to perform various signal and image processing functions. While FIG. 1 illustrates the controller 50 as being external to the structure including the main chamber 10, the load lock chamber 20, and the EFEM 30, it is understood that the controller 50 may be part of the structure. The controller 50 may be located within one of the components of the charged particle beam inspection apparatus, or the controller 50 may be distributed among at least two of the components. While the present disclosure provides an example of a main chamber 10 housing an electron beam system, it should be noted that aspects of the present disclosure, in a broad sense, are not limited to chambers housing electron beam systems. Rather, it is understood that the principles described above may also be applied to other devices and other configurations of apparatus operating under a second pressure. For example, the controller may be a distributed controller having one or more portions of the second pressure and optionally one or more portions of the first pressure.

[0025]

[0031] Reference is now made to FIG. 2, which is a schematic diagram illustrating an exemplary electron beam system 40 including a multi-beam electron optical system 41, which is part of the exemplary charged particle beam evaluation apparatus 100 of FIG. 1. The electron beam system 40 includes an electron source 201 and a projection device 230. The electron beam system 40 further includes a motion stage 209 and a sample holder 207. The electron source 201 and the projection device 230 may collectively be referred to as the electron optical system 41 or an electron optical column. The sample holder 207 is supported by the motion stage 209 to hold a sample 208 (e.g., a substrate or a mask) for inspection. The multi-beam electron optical system 41 further includes a detector 240 (e.g., an electron detection device). While an electron beam system with a multi-beam electron optical system has been described, it should be noted that this is merely one embodiment of the present invention. The inventions disclosed herein may also be applicable to electron beam systems with a single-beam electron optical system.

[0026]

[0032] The electron source 201 may include a cathode (not shown) and an extractor or anode (not shown). In operation, the electron source 201 is configured to emit electrons from the cathode as primary electrons. The primary electrons are extracted or accelerated by the extractor and / or anode to form a primary electron beam 202.

[0027]

[0033] The projection device 230 is configured to convert the primary electron beam 202 into multiple sub-beams 211, 212, 213 and direct each sub-beam onto the sample 208. Although three sub-beams are shown for simplicity, there may be tens, hundreds, or thousands, e.g., about 10,000, tens of thousands, or hundreds of thousands, of sub-beams. The sub-beams may be referred to as beamlets.

[0028]

[0034] 1, such as the electron source 201, the detector 240, the projection device 230, and the motion stage 209 (e.g., a motorized stage). The controller 50 may perform various image and signal processing functions. The controller 50 may also generate various control signals for controlling the operation of the charged particle beam inspection device, including the charged particle multi-beam device.

[0029]

[0035] The electron optical device 230 may be configured to focus the sub-beams 211, 212, and 213 onto the sample 208 for inspection, forming probe spots 221, 222, and 223 (for this example, three probe spots, one for each sub-beam) on the surface of the sample 208. The projection device 230 may be configured to deflect the primary sub-beams 211, 212, and 213 to scan the probe spots 221, 222, and 223 over respective scan areas within a section of the surface of the sample 208. In response to the incidence of the primary sub-beams 211, 212, and 213 on the probe spots 221, 222, and 223 on the sample 208, electrons, including secondary electrons and backscattered electrons, sometimes referred to as signal particles, are generated from the sample 208. Secondary electrons typically have electron energies of 50 eV or less. While actual secondary electrons may have energies less than 5 eV, any energy less than 50 eV is typically considered secondary electrons. Backscattered electrons typically have electron energies between 0 eV and the landing energy of the primary sub-beams 211, 212, 213. Detected electrons with energies less than 50 eV are typically treated as secondary electrons, so that a certain percentage of the actual backscattered electrons are counted as secondary electrons.

[0030]

[0036] The detector 240 is configured to detect signal particles, such as secondary electrons and / or backscattered electrons, and generate corresponding signals that are sent to a signal processing system 280 for preprocessing, e.g., analog-to-digital conversion. The detector 240 may be integrated into the projection device 230. Further details and alternative configurations of detector modules, sensors, and detector arrays positioned close to the objective lens, in the up-beam or down-beam, or integrated into the objective lens, are described in European Patent Application No. 20216890.2 and International Application No. PCT / EP2021 / 068548, each of which is incorporated herein by reference insofar as it discloses details of detector modules, sensors, and detector arrays, and similar elements.

[0031]

[0037] A detector may have multiple portions, more specifically, multiple detectors. A detector with multiple portions may be associated with any one of the sub-beams 211, 212, and 213. Thus, multiple portions of a single detector 240 may be configured to detect signal particles emitted from the sample 208 in association with one primary beam (otherwise referred to as sub-beams 211, 212, and 213). In other words, a detector with multiple portions may be associated with one of the apertures in at least one electrode of the objective lens assembly. The multiple portions may be radially and / or angularly arranged segments. More specifically, a detector with multiple portions may be arranged around a single aperture, which is an example of such a detector. As described above, the detector signal from the detector module is used to generate an image. In multiple detectors, the detector signal includes components from different detector signals that can be processed as a data set or a detector image.

[0032]

[0038] The objective lens may be an objective lens array and may include multiple planar electrodes or plates with apertures for each path of the beams of the multi-beam configuration. Each plate may extend across the multi-beam configuration. The objective lens may include at least two electrodes that can be connected and controlled to respective potentials. There may be additional plates, each for controlling additional degrees of freedom. The detector may be a plate associated with or connected to the objective lens with an aperture for each path of the beams of the multi-beam configuration. The detector may be located above, below, or inside the objective lens.

[0033]

[0039] The scan deflector may be associated with the objective lens, for example, as an array of scan deflectors, or may be integrated into the objective lens. An array of scan deflectors may also be referred to as a deflector array. In some configurations, the scan deflector may be positioned in the up-beam of the objective lens. In configurations in which the path of the primary beam is collimated in the up-beam of the objective lens, the scan deflector may be positioned in the up-beam of the objective lens. In configurations in which multiple beams are generated from a collimated primary beam from a source by a beam-limiting aperture array in or associated with the objective lens, the scan deflector may be a macro scan deflector positioned in the up-beam of the objective lens to act on the collimated primary beam. Other electron-optical configurations including one or more elements described herein may also be envisioned. Such scan deflectors may be controlled by a controller to deflect the beams of the multiple beams along one axis in the plane of the sample or along both primary axes on the surface of the sample, e.g., in the plane of the sample (these axes may be orthogonal to each other).

[0034]

[0040] It should be noted that embodiments of scan deflectors close to the sample, such as those integrated into or close to the objective lens, may have a limited range of scan deflection, but scan deflectors close to the sample may be precisely controlled and have a fast response compared to other types of scan actuators, such as actuation stages.

[0035]

[0041] The controller 50 can control the actuation stage 209 to move the sample 208 during inspection of the sample 208. The controller 50 can enable the actuation stage 209 to move the sample 208 in a direction, e.g., at a constant speed, preferably continuously, at least during inspection of the sample, which may be referred to as a type of scan. The speed of the actuation stage may also be referred to as a movement speed. The controller 50 can control the movement of the actuation stage 209 such that the actuation stage 209 varies the speed of movement of the sample 208 relative to the path of the multi-beam depending on various parameters. The controller 50 can control the deflection of the scan deflector to move the path of the multi-beam relative to the stage, and thus move over the sample surface. The controller 50 can vary the beam deflection of the scan deflector depending on various parameters, thereby varying the scan of the beam over the sample surface. For example, the controller 50 may control the stage velocity (including its direction) and / or the scan deflector depending on the characteristics of the inspection scan element and step in the scanning process and / or scan of the scanning process, as disclosed, for example, in European Patent Application Publication No. A21171877.0, filed May 3, 2021. The contents of this application are incorporated herein insofar as they disclose at least the combined step and scan strategy of the stage and scan deflector. Thus, the movement speed may include the stepping frequency and / or the stage scan speed at different times.

[0036]

[0042] To acquire a two-dimensional image of a sample, the probe beam (or each probe beam) is scanned across the sample's surface in a two-dimensional raster pattern. This involves beam movement in two directions: the main scan direction and the sub-scan direction, which are different (e.g., orthogonal). The main scan direction is also called the fast scan direction. For example, a scanning deflector can be controlled to move the primary beam (e.g., multi-beam) in the fast direction. The sub-scan direction is sometimes called the slow scan direction. For example, a stage can be controlled to move the sample relative to the path of the primary beam, and a scanning deflector can be controlled to move the path of the beam on the sample surface in the slow direction, or both the stage and the scanning deflector can be operated to achieve scanning in the slow direction. The stage is preferably used only in the slow direction because its large mass makes fast-direction scanning, such as acceleration, more difficult to achieve than alternatives such as a scanning deflector.

[0037]

[0043] Known multi-beam systems, such as the electron beam system 40 and charged particle beam evaluation apparatus 100 described above, are disclosed in U.S. Patent Application Publication No. 2020 / 118784, U.S. Patent Application Publication No. 202002 / 03116, U.S. Patent Application Publication No. 2019 / 0259564, and International Publication No. WO2021078352, which are incorporated herein by reference.

[0038]

[0044] The electron beam system 40 may include a projection assembly for illuminating the sample 208 and thereby adjusting the accumulated charge on the sample.

[0039]

[0045] Images output from a charged particle evaluation device, such as the electron beam system 40, are desirably automatically processed by a data processing device to detect defects in the sample being evaluated. The data processing device, or at least a portion of the data processing device, may be incorporated as part of the controller 50, as part of another computer in the fab, or elsewhere in the charged particle evaluation device. Because charged particle evaluation devices, particularly those using multiple charged particle beams, can generate very large amounts of data representing images of the sample, it is desirable to perform some initial data processing, such as initial identification of candidate defects, within the charged particle evaluation device. When this is done, only data relating to candidate defects (e.g., image clips) need be transmitted from the charged particle evaluation device for further analysis. Thus, the amount of data that needs to be output from the charged particle evaluation device is significantly reduced, and the data transmission rate does not limit the throughput of the charged particle evaluation device.

[0040]

[0046] To detect defects in an image generated by a charged particle evaluation device, various techniques can be employed. A common technique is to compare an image of a portion of a sample, referred to herein as a sample image, with one or more reference images. In effect, data points of a data stream representing the sample image are compared with data points of a reference image retrieved from memory or delivered in a parallel data stream. For simplicity, this process will be referred to hereinafter as comparing images, and the data points can be referred to as pixels.

[0041]

[0047] The result of the comparison between the sample image and the reference image can be a simple binary value representing the difference or agreement (i.e., match) between the sample image and the reference image. Preferably, the result of the comparison is a difference value representing the magnitude of the difference between the sample image and the reference image. More preferably, the result of the comparison is a difference value per pixel (or group of adjacent pixels, sometimes called a "region of pixels") so that defects in the source image can be located with greater precision.

[0042]

[0048] To determine whether a difference between a pixel or a region of pixels between the source image and the reference image represents a candidate defect in the pattern being inspected, a threshold value can be applied to the difference value corresponding to the pixel or region of pixels. The threshold value can be pre-fixed, for example, for a particular charged particle beam system or a particular pattern being inspected. The threshold value can be a user-set parameter or dependent on other conditions, e.g., the threshold value is updated over time depending on the application or evaluation. The threshold value can be dynamically determined, updated during processing, or both. Alternatively, a predetermined number of locations with the highest difference values ​​can be selected as candidate defects for further inspection. Adjacent pixels with difference values ​​higher than the threshold value may be considered a single defect or candidate defect. All pixels of a single defect may be attributed the same difference value. Such adjacent pixels and all pixels of a single defect may also be referred to as a region of pixels.

[0043]

[0049] False positives, i.e., samples labeled as having candidate defects when no significant defects are actually present, can occur due to, for example, noise. The false positive rate can be influenced by appropriate selection of a threshold for determining the presence of a defect. The false positive rate can be further controlled by applying noise reduction to either or both the reference image and the sample image. However, noise reduction increases the amount of processing required to detect defects.

[0044]

[0050] If it is desirable to reduce noise in a sample image (or reduce the effect of noise in an image), filtering, such as averaging the noise, can be applied. An efficient and effective technique that can be used is to apply a simple filter by convolution, such as a uniform filter (convolution with a uniform kernel). The efficiency and effectiveness of noise reduction in a sample image can be optimized by appropriately selecting the size of the (uniform) filter. The optimal size of the filter may depend on factors such as the size of the features on the sample, the size of the defects to be detected, the resolution of the charged particle evaluation device, the amount of noise in the image, and the desired compromise between sensitivity and selectivity. The size of the kernel used to implement the filter may be equal to a non-integer number of pixels. Kernel widths in the range of 1.1 to 5 pixels, preferably 1.4 to 3.8 pixels, are suitable for various use cases. Further details of filtering sample image data are described in International Application No. PCT / EP2022 / 060622, filed April 21, 2022, which is incorporated herein by reference at least for the description of the filter and filtering to reduce noise. Such filtering may complement or be an alternative to the inventions disclosed herein. Because improved filtering allows for greater tolerance of noise in the raw image, filtering is an alternative to the disclosed invention, allowing for increased throughput at lower signal-to-noise ratios (SNRs). However, filtering and the disclosed invention can both be applied to the same evaluation process, and therefore can be considered complementary. Simultaneous application of filtering and the disclosed invention can be combined to achieve greater throughput at lower SNRs.

[0045]

[0051] A method for evaluating a sample according to one embodiment is shown in FIG. 3. In this method, a sample image is compared to two reference images acquired from different portions of the same sample. (Note that the sample image is sometimes referred to as a "test image.") The method begins by acquiring a first reference image S1 and a second reference image S2. Details of acquiring the reference images are described below. In a multi-beam or multi-column charged particle evaluation device, the two reference images can be acquired in parallel, for example, in a single scan of the multiple beams on the same surface. The two reference images may be scanned by two different beams from the multiple beams. At least two reference images cover a surface area of ​​the sample that is within the field of view of the multiple beams on the sample surface. In another embodiment, the two reference images are scanned in two separate scans or reference scans. Note that when a single-beam charged particle evaluation device is used, the two reference areas are scanned in separate scans. The sample area (also referred to as the test area) is scanned (S3) to acquire the sample image.

[0046]

[0052] The sample area is compared to the two reference images in S4. The comparison can be performed pixel by pixel or by groups of pixels. An alignment process may be performed before the comparison. In S5, a decision is made whether the flow proceeds to steps S6, S7, or S8. The decision in S5 is whether the comparison reveals: A) no differences between the sample image and the reference images (0 differences), then the flow proceeds to S6; B) there is a difference between the sample image and one of the reference images (1 difference), then the flow proceeds to S7; C) there are differences between the sample image and both reference images (2 differences), then the flow proceeds to S8. The sample and reference images are preferably multi-thresholded so that a difference is recognized if the difference between pixel values ​​is greater than a threshold. If the comparison is performed based on groups of pixels, then a threshold can be applied to the different number of pixels in the group.

[0047]

[0053] If there are no differences between the sample image and the reference image, the sample image is deemed to be free of defects and the sample area may be flagged as free of defects S6. A new sample area is scanned and the process is repeated until all areas to be evaluated have been processed.

[0048]

[0054] If there are differences between the sample image and one of the reference images, it is assumed that one of the reference images has an obvious defect, for example due to noise, and the reference area is flagged accordingly S7. The process continues, scanning a new sample area.

[0049]

[0055] If there are differences between the sample image and both reference images at the same location in the pattern, the sample image is deemed to represent a candidate defect on the sample, and the sample area is flagged accordingly S8. Data such as a data set (e.g., an image clip) representing the candidate defect may be sent to an external device for further analysis S9. The process continues, scanning a new sample area.

[0050]

[0056] While conventional methods capture the reference and sample images under the same conditions, the two reference images are captured with higher fidelity than the sample images. Image fidelity, in this context, refers to the degree to which the image represents the actual characteristics of the corresponding region of the sample. In other words, the reference images are more accurate representations of the corresponding region of the sample. Preferably, the reference images have a higher signal-to-noise ratio than the sample images. Preferably, the reference images have a lower distortion level than the sample images. Preferably, the reference images have a higher contrast-to-noise ratio than the sample images (as further described below). Preferably, the reference images have fewer nuisance defects (defects that appear to be present in the image but do not represent actual defects on the sample). In general, the reference images may be improved in terms of reducing false positives and / or false negatives when comparing the sample image with the reference image.

[0051]

[0057] Several different techniques can be used to obtain a reference image with higher fidelity than the sample image. For example, as described below with reference to FIG. 4, a reference image may be obtained by scanning a portion of the sample designated as a reference area at a slower speed than that used to obtain the sample image. A reference image can also be obtained by scanning a portion of the sample designated as a reference multiple times and combining the results of the multiple scans, as described below with reference to FIG. 5. Another technique is to improve the fidelity of the reference image during the evaluation process by averaging the reference image with a newly acquired sample image, as described below with reference to FIG. 6. These different techniques can be used individually or in combination with one or more different techniques, as long as the combined techniques are compatible with each other. Whatever the definition of fidelity, by comparing a sample image to a reference image, with the caveat that the definition of fidelity applies to all three images, it should be noted that the comparison will show differences between each reference image and the sample image that are independent of the fidelity of either or both images.

[0052]

[0058] Optionally, the same beam (from the same column in the case of a multi-column system) is used to generate the sample image and the two reference images. This has the advantage that column-to-column and beam-to-beam corrections are not required, simplifying data routing. For example, it avoids the need to calibrate the beam's relative position to the ideal beam position.

[0053]

[0059] Embodiments of the present invention allow for increased throughput of charged particle characterization devices while maintaining a desired capture / disturbance ratio. Users of charged particle characterization devices may desire to detect at least a certain percentage (e.g., 90%) of true defects on a sample (referred to as the capture rate), while ensuring that no more than a certain percentage (e.g., 10%) of detected candidate defects are false positives (disturbance rate). A trade-off between capture rate and disturbance rate can be made by varying the threshold difference between the sample image and the reference image for detecting candidate defects. Increasing the threshold may desirably reduce the disturbance rate, but may undesirably reduce the capture rate, or vice versa.

[0054]

[0060] Reducing noise in the reference and sample images reduces the interference rate without reducing the capture rate. However, reducing noise (beyond what can be achieved with signal processing) generally reduces throughput, for example, by requiring a slower scan rate. It has generally been assumed that to enable a valid comparison, i.e., a like-to-like comparison, the reference image must be acquired under the same conditions used to acquire the sample image. However, the inventors have shown that by investing time in improving the fidelity of the reference image (e.g., by using a slower scan rate or performing multiple scans), it is possible to save time scanning the sample image (e.g., by scanning at a faster rate than would otherwise be possible) without compromising the capture rate and interference rate, thereby improving throughput. The amount of throughput that can be achieved depends on the number of reference and sample images used. The more sample images, the greater the increase in throughput. Alternatively, it is possible to maintain throughput (compared to scanning the reference and sample images under the same conditions) and improve the capture rate and interference rate.

[0055]

[0061] As mentioned above, a first technique for improving the fidelity of the reference image is to scan it at a slower speed than that used to scan the sample image. This is illustrated in FIG. 4. In step S41, a reference scan speed is set. The reference scan speed is an integer fraction of the sample scan speed (in other words, the sample scan speed is n times the reference scan speed, where n is a positive integer, such as 2 or 3). In step S42, the reference region is scanned at the reference scan speed to generate a high-resolution reference image. In step S43, the high-resolution reference image is downsampled to the same resolution as the sample image. If the reference scan speed is an integer fraction of the sample scan speed, downsampling can be performed by simply averaging n adjacent pixels. If the reference scan speed is not an integer fraction of the sample scan speed, interpolation may be performed. It is advantageous for the reference scan speed to be an integer fraction of the sample scan speed, as simple averaging requires less processing. Downsampling increases the signal-to-noise ratio (SNR) and / or contrast-to-noise ratio (CNR). This results in a higher fidelity reference image than would be obtained at the scan speed of the sample image. Scanning the reference image at a slower speed for improved fidelity allows the sample image to be scanned at a faster scan speed than would be possible if the reference and sample images were scanned at the same scan speed, while still achieving the same defect detection performance. This provides a throughput advantage in most cases, although the magnitude of the advantage depends on other factors such as the number of sample images scanned, different scan speeds, and routing between the reference and sample areas. Because embodiments can be implemented only by a software upgrade, even small advantages (e.g., increased throughput) are cost-effective and easy to implement.

[0056]

[0062] For example, consider a use case in which the sample scan rate is increased and the reference scan rate is decreased compared to known techniques of scanning sample and reference images at the same scan rate. (As a specific example, the factor for decreasing the same scan rate for the reference image is the same as the factor for increasing the scan rate for the sample, although in most cases this relationship does not apply.) The net time it takes to scan two reference images using the present invention will generally be longer than the time it takes to scan two reference images using known techniques. However, as the number of sample images scanned increases, the time required to scan two reference images and all sample images will be shorter than scanning two reference images and all sample images as with conventional known techniques. The scan rate for the reference images relative to the scan rate for the sample images may depend on the number of sample images scanned (or acquired).

[0057]

[0063] The method of Figure 4 assumes that the detector sampling rate is kept constant and that a higher resolution image is obtained by reducing the scan rate. The detector sampling rate can also be reduced, preferably at the same rate as the scan rate. In this case, the image resolution does not change and the pixel averaging step S43 can be omitted. In practice, pixel averaging is performed within the detector. The two reference images can be acquired at different scan rates and / or different sampling rates, as long as the reference image is processed to an image of the same resolution as the sample image to which it is being compared.

[0058]

[0064] A second technique for improving the fidelity of the reference image is to scan the reference area multiple times (e.g., two or three times). This is illustrated in FIG. 5. In step S51, the reference area is scanned. In step S52, the reference area is scanned again to obtain multiple overlapping images of the reference area. In step S53, the overlapping images are averaged. Before averaging the multiple overlapping images, an alignment process can be performed. This process is repeated for another reference area. Depending on the location of the reference area, it may be more efficient to obtain a first image of each reference area and then a second image of each reference area, rather than obtaining two images of one reference area and then two images of the second reference area. Obtaining multiple images of each reference area and combining them (e.g., by averaging) improves the signal-to-noise ratio (SNR) and / or contrast-to-noise ratio (CNR), thereby improving fidelity. Therefore, increasing the number of images used for each reference area to generate the reference image increases the fidelity of the reference image. Again, this will provide a throughput advantage in most cases, but the magnitude of the advantage will depend on other factors such as the number of sample images scanned, the number of scans of each reference area, different scan speeds, and routing between the reference and sample areas.

[0059]

[0065] It will be appreciated that the first and second techniques can be combined, i.e., multiple images of the reference area are acquired at a slower scan rate than that used for the sample images, but improvements in the reference images may be subject to diminishing returns.

[0060]

[0066] A third approach to improving the fidelity of the reference image is to update the reference image(s) during evaluation of the sample area. This is illustrated in FIG. 6. The reference area is scanned to generate a reference image S61, and the sample area is scanned to generate a sample image S62. These steps can be performed in either order, or simultaneously if a multi-beam evaluation system is used. The sample image is compared to the reference image S63 to determine if there are any differences (e.g., by applying a threshold as described above) S64. An alignment process may be performed before the comparison. If there are significant differences indicative of a candidate defect, the sample area is flagged and the data (e.g., clip) is sent for further analysis, as described above with reference to steps S8 and S9 of FIG. 3. If there are no significant differences, the sample area is flagged as defect-free S65, and the reference image is updated S66. The process is repeated, scanning a new sample area as a new iteration. Note that this approach uses a single reference. Because the reference image is an average of multiple sample images, a single reference may be sufficient after inspecting multiple sample images. For example, differences due to false positives are statistically reduced (e.g., averaged out). However, to mitigate the risk of false positives being present in the reference image, two reference images may be used initially. Multiple different reference images may be used until the contribution of differences such as false positives from the reference image is statistically reduced to have little or no meaningful statistical contribution to the reference image.

[0061]

[0067] Updating the reference image may include generating a combination (e.g., an average) of the previous reference image and the current sample image. The average may be a weighted average. The weight given to the sample image may change (e.g., decrease) with each iteration. For example, if the reference image is updated for the nth time, the weight of the sample image may be proportional to 1 / n. Updating the reference image need not be performed every time a new sample image is found to be defect-free. Updating the reference image increases the signal-to-noise ratio (SNR) and / or contrast-to-noise ratio (CNR). Thus, each update of the reference image improves the fidelity of the reference image for comparison with subsequently acquired sample images.

[0062]

[0068] The concept of improving fidelity by updating the reference image each time a new sample image is acquired can also be applied starting with only one reference image. Preferably, the initial reference image is acquired with higher fidelity than the sample image. Preferably, multiple sample images are acquired from different regions of the sample.

[0063]

[0069] Each sample image can be compared to the reference image to generate a dataset indicative of candidate defects present in the sample image. The fidelity of the reference image can be further improved by validating candidate defects in the dataset by removing candidate defects present in a selection of the datasets (preferably all of the datasets); preferably, validation includes comparing a selection of the datasets and / or generating a removal defect set of possible defects present in all of the selected datasets. For example, if a candidate defect is identified in the same location in many sample images, it is likely that the reference image also contains a defect at that location. The reference image can then be improved by updating it as an updated reference (or new reference image) by removing candidate defects present in the removal defect set from the reference image. The method can then continue by obtaining a further sample image of the sample area of ​​the sample and comparing the further sample image to the updated reference to identify any candidate defects in the sample area. Preferably, the dataset of candidate defects can be used to remove false positives from the reference image for evaluating further sample images of the sample.

[0064]

[0070] Other techniques for improving the fidelity of the reference image can also be employed, such as increasing the beam current. For example, the reference image is scanned using a higher reference beam current than the sample beam current used to scan the sample image. While increasing the beam current generally improves image quality, the relationship is not linear due to surface charging and stochastic effects. In one embodiment, the beam current is related to the intended resolution. For example, a high current beam can be used for greater resolution, while a low current beam can be used for less resolution. Using a lower beam current may be more susceptible to noise than a higher beam current. In this technique, by scanning the reference image using a higher beam current than when scanning the sample image, the reference image and the sample image can be scanned at similar or the same resolution. As a result, the noise impact on a reference sample image scanned with a higher beam current may be less than the impact on a sample image scanned with a lower beam current.

[0065]

[0071] Embodiments of the present invention are particularly useful when the pattern formed on each die of a sample does not have large repeating elements and / or the area of ​​the pattern to be inspected does not have repeating elements. Such samples are sometimes said to have a "random" pattern, although of course the pattern is designed and not random. However, the pattern is repeated from die to die. That is, all dies on a sample are conceptually identical. The present invention is not limited as to which dies of the sample are selected to be scanned as the reference area and which dies are scanned as the sample area. However, it may be advantageous to select an area of ​​the sample from the reference area that has historically had a low defect rate. For example, it may be desirable to select a non-edge die as the reference area.

[0066]

[0072] The described invention relates to a charged particle electron optical system configured to project multiple beams toward a sample. The invention is equally applicable to charged particle systems configured to project a single beam of charged particles toward a sample. The inventors have demonstrated that the effective improvement of the invention over multi-beam and single-beam systems is proportionally the same. However, because the area of ​​each region scanned by a multi-beam system is generally larger than that of a single-beam system, the area processed using a multi-beam system can be larger. A net higher throughput can be achieved using a multi-beam system than a single-beam system. The magnitude of the throughput advantage depends on other factors, such as the number of sample images scanned, the number of scans of each reference region, different scan speeds, and routing between the reference region and the sample region.

[0067]

[0073] It should be noted that there are exceptions where a multi-beam system can ensure improvements beyond those achieved by implementing the present invention in a single-beam system. That is, when scanning two reference areas, the reference areas are scanned in a single scan of the multiple beams. In such cases, by acquiring the reference image in a single scan rather than two scans, the time required for the slow reference scan is halved. It should be noted that in general, there is a clear increase in throughput that is more noticeable when scanning a small number of sample areas, e.g., less than 10.

[0068]

[0074] 7, a data processing device 500 that can be used to analyze sample images includes a filter module 501 that receives and filters the sample image from the detector module 240, reference image stores 503a, 503b that provide reference images based on the source image, comparators 502a, 502b that compare the filtered sample image with the reference image, and an output module 504 that processes and outputs the results of the comparison. Alignment of the sample and reference images can be performed as a separate step before or after the filtering step, or as part of the comparison step.

[0069]

[0075] As described above, the filter module 501 applies a filter to the input data. The filter module 501 is advantageously implemented by dedicated hardware, such as an FPGA or an ASIC. Such dedicated hardware can be more efficient and economical than a programmable general-purpose computing device, such as a standard or common type of CPU architecture. While the processor may not be as powerful as a CPU, it may have an architecture suited to processing software for processing the detection signal data, i.e., images, so that the image can be processed in the same time as or less than a CPU. Although such a detection processing architecture has lower processing power than most contemporary CPUs, it may be faster to process data due to the more efficient data architecture of the dedicated processing architecture. A general-purpose CPU may be advantageous in that the filter can be easily changed.

[0070]

[0076] 7, the comparators 502a, 502b may be any logic circuit capable of comparing two values, such as an XOR gate or a subtractor. The comparators 502a, 502b are also suitable for implementation using dedicated hardware, such as an FPGA or ASIC. Such dedicated hardware may be more efficient and economical than a programmable general-purpose computing device, such as a CPU. Preferably, the comparators 502a, 502b are implemented on the same dedicated hardware as the filter module 501.

[0071]

[0077] In some cases, the reference image stores 503a, 503b may be implemented in dedicated hardware, in which case the reference image generator is preferably implemented in the same dedicated hardware as the comparator and / or filter modules.

[0072]

[0078] An output module 504 receives the results output by the comparator 502 and prepares the output for output to a user, another manufacturing system, or for further processing within the inspection system. The output may be in any of several different forms. In the simplest option, the output may simply be an indication that the sample does or does not have a defect. However, because nearly all samples have at least one potential defect, more detailed information, such as a dataset (e.g., a dataset representable as an image), is desirable. Thus, the output may include, for example, a map of defect locations, a deviation image, a clip of pixel data (e.g., of the image and the reference image, or of the reference image), and / or information regarding the severity of possible defects represented by the magnitude of the difference between the sample image and the reference image (e.g., how much the sample image deviates from the reference image).

[0073]

[0079] The output module 504 can also filter potential defects, for example, by outputting only defect locations where the magnitude of the difference between the sample image and the reference image is greater than a threshold, or where the density of pixels showing the difference is greater than a threshold. Another possibility is to output only a predetermined number of the most severe defect sites, as indicated by the magnitude of the difference. This can be done by storing the defect sites in a buffer 510, and when the buffer is full, overwriting the smallest defects if larger defects are detected.

[0074]

[0080] Any suitable format for output of defect information may be used, such as a list, a dataset, an image, or a map. Desirably, the output module 504 may output clips, which are images of areas of the sample where potential defects are detected. This allows the potential defects to be further inspected to determine whether they are actually present and severe enough to affect the operation of devices formed on or within the sample. The remainder of the source image, i.e., the portion not saved as a clip, may be discarded to reduce data storage and transfer requirements. Thus, a dataset may be a set of clips, and an image may include a set of clips.

[0075]

[0081] The data processing device 500 may be located remotely from the detector array, for example, within a vacuum chamber. The data processing device may be part of an electron-optical assembly of an electron-optical column, and such an assembly may include a detector (e.g., a detector array) and an objective lens (e.g., an objective lens array). The detector may be in the path of the beam grid, and the data processing device may be remote from the path of the beam grid. The data processing device may be separate from the detector but electrically connected to it. In another embodiment, at least some, if not all, of the data processing device is remote from the electron-optical column, for example, remote from the electron-optical assembly, and even external to the vacuum chamber containing the electron-optical column. At least some of the data processing device may be in signal communication with the detector via a feedthrough in a wall of the chamber.

[0076]

[0082] References to "upper" and "lower", "up" and "down", "above" and "below", etc. should be understood as referring to directions parallel to the (typically, but not always perpendicular) up-beam and down-beam directions of the electron beam or multi-beam impinging on the sample 208. References to up-beam and down-beam are therefore intended to refer to directions relative to the beam path, independent of any prevailing gravitational field.

[0077]

[0083] The embodiments described herein can take the form of a series of aperture arrays or electron-optical elements arranged in an array along the beam path or multi-beam path. Such electron-optical elements may be electrostatic. In one embodiment, for example, all electron-optical elements from the beam-limiting aperture array to the final electron-optical element in the sub-beam path before the sample may be electrostatic and / or in the form of aperture arrays or plate arrays. In some configurations, one or more of the electron-optical elements are fabricated as microelectromechanical systems (MEMS) (i.e., by using MEMS fabrication techniques). The electron-optical elements may have magnetic and electrostatic elements. For example, a compound array lens may contain the multi-beam path with upper and lower pole plates within the magnetic lens and feature a macro-magnetic lens positioned along the multi-beam path. Within the pole plates may be an array of apertures for the beam paths of the multi-beams. Electrodes may be present above, below, or between the pole plates to control and optimize the electromagnetic field of the compound lens array.

[0078]

[0084] Although the embodiments described herein are multi-beam electron-optical systems featuring electrostatic electron optics, e.g., electrode plates with apertures that act on different beams of the multi-beam system, the evaluation system may also feature multi-beam electron-optical systems that include magnetic components. For example, the electron-optical system may include at least one of the following: a macro-magnetic focusing lens that can be set to a non-rotating configuration; an electron-optical array stack for fine manipulation of the multi-beam beams; a beam-limiting aperture array for generating and / or shaping multiple beams of the multi-beam, which may be a plate-up beam of the focusing lens and / or a plate-down beam between the focusing lens and the electron-optical array stack; a macro-magnetic objective lens (which may feature electrostatic elements) for projecting the multiple beams onto the sample; a Wien filter for directing the primary beam toward the sample and signal particles from the sample toward a detector, which may be in a secondary column; and a detector in the secondary column. In another configuration of the evaluation system, the electron-optical system may be designed to project a single beam toward the sample. Such single-beam designs may resemble multi-beam electron-optical systems featuring magnetic focusing lenses, and in variants, the detector is located within the main column (i.e., no secondary column or Wien filter), e.g., facing the sample position and / or between the focusing lens and the objective lens.

[0079]

[0085] The terms "sub-beam" and "beamlet" are used interchangeably herein and are both understood to encompass any radiation beam derived from a parent radiation beam by splitting or separating the parent radiation beam. The term "manipulator" is used to encompass any element that affects the path of a sub-beam or beamlet, such as a lens or deflector. References to elements that are aligned along a beam path or sub-beam path are understood to mean that the respective element is positioned along the beam path or sub-beam path. References to optics are understood to mean electron optics.

[0080]

[0086] An evaluation tool or evaluation system according to the present disclosure can include a device that performs a qualitative evaluation (e.g., pass / fail) of a sample, a device that performs a quantitative measurement (e.g., size of features) of a sample, or a device that generates an image of a map of a sample. Examples of evaluation tools or systems are inspection tools (e.g., to identify defects), review tools (e.g., to classify defects), and metrology tools or tools that can perform any combination of evaluation functions associated with an inspection tool, review tool, or metrology tool (e.g., metro inspection tool).

[0081]

[0087] References to a component or system of components or elements controllable to manipulate a charged particle beam in a certain manner include configuring a controller, control system, or control unit to control the component to manipulate the charged particle beam in the manner described above, as well as optionally using other controllers or devices (e.g., voltage sources) to control the component to manipulate the charged particle beam in this manner. For example, a voltage source may be electrically connected to one or more components, such as electrodes of the control lens array and objective lens array, to apply an electric potential to the component under the control of the controller, control system, or control unit. An actuatable component, such as a stage, may be controllable to be actuated and thus moved relative to another component, such as the beam path, using one or more controllers, control systems, or control units to control the actuation of the component.

[0082]

[0088] The methods of the present invention can be performed by a computer system including one or more computers. A computer used to implement the present invention may include one or more processors, including a general-purpose CPU, a graphics processing unit (GPU), a field programmable gate array (FPGA), an application-specific integrated circuit (ASIC), or other special-purpose processor. As discussed above, in some cases, a particular type of processor may offer advantages in terms of reduced cost and / or increased processing speed, and the methods of the present invention may be adapted for use with a particular processor type. Certain steps of the methods of the present invention involve parallel computation, which is likely to be performed on a processor capable of parallel computation, such as a GPU.

[0083]

[0089] The computer used to implement the present invention may be physical or virtual. The computer used to implement the present invention may be a server, client, or workstation. Multiple computers used to implement the present invention may be distributed and interconnected via a local area network (LAN) or a wide area network (WAN). The results of the methods of the present invention may be displayed to a user or stored in any suitable storage medium. The present invention may be embodied in a non-transitory computer-readable storage medium that stores instructions for performing the methods of the present invention. The present invention may be embodied in a computer system including one or more processors and memory or storage that stores instructions for performing the methods of the present invention.

[0084]

[0090] The functions provided by a computer and processor, such as a controller, control system, or control unit, may be implemented by a computer. Any suitable combination of elements may be used to provide the required functionality, including, for example, a CPU, RAM, SSD, motherboard, network connection, firmware, software, and / or other elements known in the art that enable the required computing operations to be performed. The required computing operations may be defined by one or more computer programs. Such computer programs may take the form of multiple computer programs that may be distributed for execution by different processors. One or more computer programs may be provided in the form of a medium, optionally a non-transitory medium, that stores computer-readable instructions. When the computer-readable instructions are read by the computer, the computer performs the required method steps. The computer may be comprised of a distributed computing system having multiple different computers, either self-contained or connected to each other via a network.

[0085]

[0091] As used herein, the term "image" is intended to refer to any data structure of values, where each value relates to a sample at a location, and the arrangement of values ​​in the array corresponds to the spatial arrangement of the sampled locations. The term "data map" may be used to describe such a data structure. An image may include a single layer or multiple layers. In the case of a multiple layer image, each layer, which may also be called a channel, represents a different sample at some location. The term "pixel" is intended to refer to a single value in an array or, in the case of a multiple layer image, a group of values ​​corresponding to a single location. Images may be stored in any convenient format in a computer-readable storage medium.

[0086]

[0092] Embodiments of the present invention are described in the following numbered clauses.

[0087]

[0093] Clause 1. A charged particle evaluation method for identifying candidate defects in a sample by scanning a charged particle beam across the sample, the method comprising: acquiring a first reference image from a first region of the sample and a second reference image from a second region of the sample using a charged particle characterization device; acquiring a sample image from a third region of the sample using a charged particle characterization device; comparing the sample image to the first reference image and the second reference image to identify any candidate defects within the third region; wherein the first reference image and / or the second reference image are acquired with higher fidelity than the sample image.

[0088]

[0094] Clause 2. Acquiring the first reference image and the second reference image includes relatively scanning the sample and the charged particle beam at a reference scan speed; acquiring the sample image includes relatively scanning the sample and the charged particle beam at a sample scan rate; 10. The charged particle evaluation method of claim 1, wherein the reference scan rate is slower than the sample scan rate such that the reference image has higher fidelity than the sample image.

[0089]

[0095] Clause 3. The charged particle evaluation method described in Clause 2, wherein acquiring the first reference image and the second reference image includes generating the first high-resolution reference image and / or the second high-resolution reference image at a reference scan rate, and downsampling the first high-resolution reference image and / or the second high-resolution reference image to generate the first reference image and / or the second reference image, respectively, having a resolution equivalent to that of the sample image.

[0090]

[0096] Clause 4. A charged particle evaluation method according to clause 2 or 3, wherein the sample scan speed is an integer multiple of the reference scan speed.

[0091]

[0097] Clause 5. The charged particle evaluation method of clause 4, wherein downsampling comprises averaging pixel values ​​of the first high resolution reference image and / or averaging pixel values ​​of the second high resolution reference image.

[0092]

[0098] Clause 6. A charged particle evaluation method according to clause 2 or 3, wherein the sample scan rate is a non-integer multiple of the reference scan rate.

[0093]

[0099] Clause 7. The charged particle evaluation method of clause 6, wherein downsampling comprises interpolating pixel values ​​of the first high resolution reference image and / or the second high resolution reference image.

[0094]

[0100] Clause 8. A charged particle evaluation method described in any of clauses 2 to 7, wherein scanning the sample and the charged particle beam relatively includes moving the sample at a moving speed using a moving stage and scanning the charged particle beam at a scan deflector speed using a scan deflector, and when acquiring the reference image, at least one of the moving speed and the scan deflector speed is higher than when acquiring the sample image, and preferably the moving speed includes a stepping frequency and / or a stage scan speed.

[0095]

[0101] Clause 9. A charged particle evaluation method described in any of clauses 1 to 8, wherein acquiring a first reference image and a second reference image includes acquiring multiple overlapping images of the first region and the second region and averaging the multiple overlapping images to acquire a first reference image and a second reference image, respectively, having higher fidelity than the sample image.

[0096]

[0102] Clause 10. A charged particle evaluation method described in any of clauses 1 to 9, wherein the first reference image and the second reference image are acquired using a reference beam current, and the sample image is acquired using a sample beam current, and the reference beam current is higher than the sample beam current.

[0097]

[0103] Clause 11. Generating a new reference image by combining the sample image with one of the first reference image and the second reference image; acquiring additional sample images from additional regions of the sample using the charged particle characterization device; comparing the further sample image with the new reference image to identify any candidate defects within the further region; 11. The charged particle evaluation method according to any one of clauses 1 to 10, further comprising:

[0098]

[0104] Clause 12. A charged particle evaluation method as described in clause 11, wherein generating a new reference image includes calculating an average, preferably a weighted average, of the sample image and one of the first reference image and the second reference image.

[0099]

[0105] Clause 13. A charged particle evaluation method according to clause 11 or 12, further comprising repeating the steps of generating a new reference image, acquiring a further sample image, and comparing the further sample image.

[0100]

[0106] Clause 14. A charged particle evaluation method described in any one of clauses 1 to 13, wherein the first reference image and the second reference image have a reference signal-to-noise ratio, and the sample image has a sample signal-to-noise ratio, and the reference signal-to-noise ratio is higher than the sample signal-to-noise ratio.

[0101]

[0107] Clause 15. A charged particle evaluation method for identifying candidate defects in a sample by scanning a charged particle beam across the sample, the method comprising: acquiring a reference image from a first region (preferably a reference region) of the sample using a charged particle characterization device; acquiring a sample image from a second region of the sample (preferably the sample region) using a charged particle characterization device; comparing the sample image with a reference image to determine whether there are defects within the sample area; generating a new reference image by combining the sample image and the reference image; acquiring additional sample images from additional regions of the sample using the charged particle characterization device; comparing the additional sample image with the new reference image to determine whether defects are present in the additional areas.

[0102]

[0108] Clause 16. A charged particle evaluation method for detecting defects in a sample by scanning a charged particle beam across the sample, the method comprising: acquiring a reference image from a first region of the sample using a charged particle characterization device; acquiring an image of the sample from a second region of the sample using a charged particle characterization device; comparing the sample image with the reference image to identify any candidate defects within the sample area; wherein the reference image is acquired with higher fidelity than the sample image.

[0103]

[0109] Clause 17. The particle characterization method of clause 16, further comprising obtaining a plurality of sample images from different regions of the sample.

[0104]

[0110] Clause 18. The particle evaluation method of clause 17, wherein comparing each sample image with the reference image includes generating a data set indicative of candidate defects present in the sample image.

[0105]

[0111] Clause 19. The particle evaluation method of clause 18, further comprising validating candidate defects in the dataset by selecting a dataset, preferably eliminating candidate defects present in all datasets, preferably wherein the validation includes comparing a selection of datasets and / or generating an eliminated defect set of possible defects present in all selected datasets.

[0106]

[0112] Clause 20. The particle evaluation method of clause 19, further comprising updating the reference image as an updated reference (or new reference image) by removing candidate defects present in the removed defect set from the reference image.

[0107]

[0113] Clause 21. The particle evaluation method of clause 20, further comprising obtaining a further sample image of the sample area of ​​the sample and comparing the further sample image with the updated reference to identify any candidate defects within the sample area.

[0108]

[0114] Clause 22. A particle evaluation method according to any of clauses 18 to 21, comprising removing false positives from the reference image using the dataset of candidate defects to evaluate further sample images of the sample.

[0109]

[0115] Clause 23. A computer program for controlling a charged particle evaluation apparatus, the computer program including instructions that, when executed by the charged particle evaluation apparatus, cause the charged particle evaluation apparatus to perform the method described in any one of clauses 1 to 22.

[0110]

[0116] Clause 24. A charged particle characterization apparatus for identifying candidate defects in a sample by scanning a charged particle beam across the sample, the apparatus comprising: a detector unit configured to output a digital detection signal of pixel values ​​in response to signal particles incident from the sample; a scanning unit for scanning the sample and the charged particle beam relative to one another; a controller configured to control the detector unit and the scanning unit to acquire a first reference image from a first region of the sample and a second reference image from a second region of the sample, and to acquire a sample image from a third region of the sample; a comparator configured to compare the sample image with the first reference image and the second reference image to identify any candidate defects within the third region; wherein the first reference image and / or the second reference image are acquired with higher fidelity than the sample image.

[0111]

[0117] Article 25. The scanning unit a charged particle device configured to direct a charged particle beam towards the sample; and a stage configured to support the sample, wherein the charged particle device and stage are configured to scan a surface of the sample with the charged particle beam.

[0112]

[0118] Article 26. The Controller acquiring a first reference image and a second reference image by relatively scanning the sample and the charged particle beam at a reference scan speed; acquiring an image of the sample by scanning the sample and the charged particle beam relatively at a sample scan rate; 26. The charged particle evaluation apparatus of claim 24 or 25, configured to control the detector unit and the scan unit to perform a reference scan rate that is slower than the sample scan rate, such that the reference image has higher fidelity than the sample image.

[0113]

[0119] Clause 27. A charged particle evaluation device as described in Clause 26, wherein the controller is configured to control the detector unit and the scan unit to acquire the first reference image and the second reference image by generating the first high-resolution reference image and / or the second high-resolution reference image at a reference scan rate and down-sampling the first high-resolution reference image and / or the second high-resolution reference image to generate the first reference image and / or the second reference image, respectively, having a resolution equivalent to that of the sample image.

[0114]

[0120] Clause 28. A charged particle evaluation device according to clause 26 or 27, wherein the sample scan speed is an integer multiple of the reference scan speed.

[0115]

[0121] Clause 29. A charged particle evaluation device according to clause 28, wherein downsampling comprises averaging pixel values ​​of the first high resolution reference image and / or averaging pixel values ​​of the second high resolution reference image.

[0116]

[0122] Clause 30. A charged particle evaluation device according to clause 26 or 27, wherein the sample scan rate is a non-integer multiple of the reference scan rate.

[0117]

[0123] Clause 31. A charged particle evaluation device according to clause 30, wherein downsampling comprises interpolating pixel values ​​of the first high resolution reference image and / or the second high resolution reference image.

[0118]

[0124] Clause 32. A charged particle evaluation device described in any of Clauses 25 to 31, wherein the controller is configured to control the detector unit and the scan unit to acquire a first reference image and a second reference image, respectively, by acquiring multiple overlapping images of a first region and a second region and averaging the multiple overlapping images to acquire a first reference image and a second reference image having higher fidelity than the sample image.

[0119]

[0125] Clause 33. A charged particle evaluation device described in any of Clauses 25 to 32, wherein the controller is configured to control the detector unit and the scan unit to acquire a first reference image and a second reference image using a reference beam current, and to acquire a sample image using a sample beam current, wherein the reference beam current is higher than the sample beam current.

[0120]

[0126] Article 34. The Controller generating a new reference image by combining the sample image with one of the first reference image and the second reference image; acquiring a further sample image from a further area of ​​the sample; comparing the further sample image with the new reference image to identify any candidate defects within the further region; 34. The charged particle evaluation device according to any one of clauses 25 to 33, further configured to control the detector unit and the scan unit to perform the above.

[0121]

[0127] Clause 35. A charged particle evaluation device as described in Clause 34, wherein the controller is configured to control the detector unit and the scanning unit to generate a new reference image by calculating an average, preferably a weighted average, of the sample image and one of the first reference image and the second reference image.

[0122]

[0128] Clause 36. A charged particle evaluation device as described in clause 34 or 35, wherein the controller is further configured to control the detector unit and the scanning unit to repeat the steps of generating a new reference image, acquiring a further sample image, and comparing the further sample image.

[0123]

[0129] Clause 37. A charged particle evaluation device described in any of clauses 25 to 36, wherein the first reference image and the second reference image have a reference signal-to-noise ratio, and the sample image has a sample signal-to-noise ratio, and the reference signal-to-noise ratio is higher than the sample signal-to-noise ratio.

[0124]

[0130] While the invention has been described in connection with various embodiments, other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.

Claims

1. 1. A charged particle evaluation method for identifying candidate defects in a sample by scanning a charged particle beam across the sample, the method comprising: acquiring a first reference image from a first region of the sample and a second reference image from a second region of the sample using a charged particle characterization device; acquiring a sample image from a third region of the sample using the charged particle characterization device; comparing the sample image with the first reference image and the second reference image to identify any candidate defects within the third region; wherein the first reference image and / or the second reference image are acquired with higher fidelity than the sample image.

2. acquiring the first reference image and the second reference image includes relatively scanning the sample and the charged particle beam at a reference scan rate; acquiring the sample image includes relatively scanning the sample and the charged particle beam at a sample scan rate; 2. The charged particle characterization method of claim 1, wherein the reference scan rate is slower than the sample scan rate such that the reference image has higher fidelity than the sample image.

3. 3. The charged particle evaluation method of claim 2, wherein acquiring the first reference image and the second reference image includes generating a first high-resolution reference image and / or a second high-resolution reference image at the reference scan rate, and downsampling the first high-resolution reference image and / or the second high-resolution reference image to generate the first reference image and / or the second reference image, respectively, having a resolution equivalent to that of the sample image.

4. 4. The charged particle evaluation method according to claim 2, wherein the sample scan speed is an integer multiple of the reference scan speed, or the sample scan speed is a non-integer multiple of the reference scan speed.

5. The charged particle characterization method of claim 4 , wherein downsampling comprises averaging pixel values ​​of the first high resolution reference image and / or averaging pixel values ​​of the second high resolution reference image.

6. The charged particle characterization method of claim 4 , wherein downsampling comprises interpolating pixel values ​​of the first high resolution reference image and / or the second high resolution reference image.

7. A charged particle evaluation method according to any one of claims 2 to 6, wherein scanning the sample and the charged particle beam relatively includes moving the sample at a movement speed using a moving stage and scanning the charged particle beam at a scan deflector speed using a scan deflector, and when acquiring the reference image, at least one of the movement speed and the scan deflector speed is higher than when acquiring the sample image, and preferably the movement speed includes a stepping frequency and / or a stage scan speed.

8. The charged particle evaluation method of any one of claims 1 to 7, wherein acquiring the first reference image and the second reference image includes acquiring a plurality of overlapping images of the first region and the second region, and averaging the plurality of overlapping images to acquire the first reference image and the second reference image, respectively, having higher fidelity than the sample image.

9. A charged particle evaluation method according to any one of claims 1 to 8, wherein the first reference image and the second reference image are acquired using a reference beam current, and the sample image is acquired using a sample beam current, and the reference beam current is higher than the sample beam current.

10. generating a new reference image by combining the sample image with one of the first reference image and the second reference image; acquiring additional sample images from additional areas of the sample using the charged particle characterization device; comparing the further sample image to the new reference image to identify any candidate defects within the further region; The charged particle evaluation method according to any one of claims 1 to 9, further comprising:

11. 11. The charged particle evaluation method of claim 10, wherein generating a new reference image comprises calculating an average, preferably a weighted average, of the sample image and one of the first reference image and the second reference image.

12. 12. The charged particle evaluation method of claim 10 or 11, further comprising repeating the steps of generating a new reference image, acquiring a further sample image, and comparing the further sample image.

13. A charged particle evaluation method according to any one of claims 1 to 12, wherein the first reference image and the second reference image have a reference signal-to-noise ratio, and the sample image has a sample signal-to-noise ratio, and the reference signal-to-noise ratio is higher than the sample signal-to-noise ratio.

14. 1. A charged particle characterization apparatus for identifying candidate defects in a sample by scanning a charged particle beam across the sample, the apparatus comprising: a detector unit configured to output a digital detection signal of a pixel value in response to a signal particle incident from the sample; a scanning unit for scanning the sample and the charged particle beam relative to one another; a controller configured to control the detector unit and the scanning unit to acquire a first reference image from a first region of the sample and a second reference image from a second region of the sample, and to acquire a sample image from a third region of the sample; a comparator configured to compare the sample image with the first reference image and the second reference image to identify any candidate defects within the third region; wherein the first reference image and / or the second reference image are acquired with higher fidelity than the sample image.

15. The controller acquiring the first reference image and the second reference image by relatively scanning the sample and the charged particle beam at a reference scan speed; acquiring an image of the sample by scanning the sample and the charged particle beam relative to one another at a sample scan rate; 15. The charged particle evaluation device of claim 14, configured to control the detector unit and the scan unit to perform the above, wherein the reference scan speed is slower than the sample scan speed so that the reference image has higher fidelity than the sample image.

Images