Charged particle evaluation method and system

Abstract

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

Description

[0001] Cross - Reference to Related Applications

[0002] This application claims priority to European Application No. 22209971.5, filed on Nov. 28, 2022, the entire content of which is incorporated herein by reference. Technical Field

[0003] Embodiments provided herein generally relate to charged particle evaluation systems and methods of operating a charged particle evaluation system. Background Art

[0004] When manufacturing semiconductor integrated circuit (IC) chips, during manufacturing, unwanted pattern defects inevitably occur on a substrate (i.e., a wafer) or a mask due to, for example, optical effects and incidental particles, thereby reducing the yield. Thus, monitoring the degree of unwanted pattern defects is an important process in IC chip manufacturing. More generally, inspecting and / or measuring the surface of a substrate or other object / material is an important process during and / or after its manufacturing.

[0005] Pattern inspection apparatuses with charged particle beams have been used to inspect objects (which may be referred to as samples), for example, to detect pattern defects. These apparatuses typically use electron microscopy techniques, such as scanning electron microscopy (SEM). In some SEMs, a relatively high-energy primary electron beam is targeted, and a final deceleration step is performed in order to land on the sample with a relatively low landing energy. The electron beam is focused into a probe spot on the sample. The interaction between the material structure at the probe spot and the landing electrons in the electron beam causes signal electrons to be emitted from the surface, such as secondary electrons, backscattered electrons, or Auger electrons. The signal electrons can be emitted from the material structure of the sample. By scanning the primary electron beam as a probe spot over the sample surface, signal electrons can be emitted on the sample surface. By collecting these emitted signal electrons from the sample surface, the pattern inspection apparatus can acquire an image representing the characteristics of the material structure of the sample surface.

[0006] When using a pattern inspection apparatus to detect defects on a sample with high throughput, there may be a significant level of noise in the image data. US 8,712,184 B1 and US 9,436,985 B1 describe methods for reducing the noise in an image obtained from a scanning electron microscope or for improving the signal-to-noise ratio. However, further improvements are desired in terms of increasing throughput and / or reducing noise or the impact of noise. Summary of the Invention

[0007] An object of the present disclosure is to provide embodiments that can increase throughput without increasing or with a reduced increase in noise or the impact of noise in an image (particularly a reference image).

[0008] According to a first 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 over the sample; the method comprising:

[0009] 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;

[0010] acquiring a sample image from a third region of the sample using a charged particle evaluation device; and

[0011] comparing the sample image with the first reference image and the second reference image to identify any candidate defects in the third region;

[0012] wherein the first reference image and / or the second reference image is acquired with a higher fidelity than the sample image.

[0013] 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 over the sample; the method comprising:

[0014] acquiring a reference image from a first region (ideally a reference region) of the sample using a charged particle evaluation device;

[0015] acquiring a sample image from a second region (ideally a sample region) of the sample using a charged particle evaluation device;

[0016] comparing the sample image with the reference image to determine whether a defect may be present in the sample region;

[0017] generating a new reference image by combining the sample image and the reference image;

[0018] acquiring another sample image from another region of the sample using a charged particle evaluation device; and

[0019] comparing the another sample image with the new reference image to determine whether a defect may be present in the another region.

[0020] According to a third aspect of the present invention, there is provided a charged particle evaluation method for detecting defects in a sample by scanning a charged particle beam over the sample; the method comprising:

[0021] acquiring a reference image from a first region of the sample using a charged particle evaluation device;

[0022] acquiring a sample image from a second region of the sample using a charged particle evaluation device;

[0023] comparing the sample image with the reference image to identify any candidate defects in the sample region;

[0024] Wherein the reference image is acquired with a higher fidelity than the sample image.

[0025] According to a fourth aspect of the present invention, there is provided a computer program for controlling a charged particle evaluation apparatus, the computer program including instructions which, when executed by the charged particle evaluation apparatus, cause the charged particle evaluation apparatus to perform the above method.

[0026] According to a fifth aspect of the present invention, there is provided a charged particle evaluation apparatus for identifying candidate defects in a sample by scanning a charged particle beam over the sample; the apparatus comprising:

[0027] a detector unit configured to output a digital detection signal of pixel values in response to signal particles incident from the sample;

[0028] a scanning unit for relatively scanning the sample and the charged particle beam;

[0029] 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 a sample image from a third region of the sample; and

[0030] a comparator configured to compare the sample image with the first reference image and the second reference image to identify any candidate defects in the third region;

[0031] Wherein the first reference image and / or the second reference image is acquired with a higher fidelity than the sample image. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The above and other aspects of the present disclosure will become more apparent from the following description of exemplary embodiments in conjunction with the accompanying drawings.

[0033] Figure 1 is a schematic diagram showing an exemplary charged particle beam inspection system.

[0034] Figure 2 is showing as Figure 1 a schematic diagram of an exemplary multi-beam charged particle evaluation apparatus that is part of the exemplary charged particle beam inspection system.

[0035] Figure 3 is a flowchart showing an exemplary method for evaluating a sample.

[0036] Figure 4 is a flowchart of a method for acquiring a reference image according to an embodiment.

[0037] Figure 5 is a flowchart of a method for acquiring a reference image according to an embodiment.

[0038] Figure 6 It is a flowchart of a method for updating a reference image according to an embodiment.

[0039] Figure 7 It is a diagram of a data processing system according to an embodiment.

[0040] The schematic diagrams and views illustrate the components described below. However, the components depicted in the figures are not drawn to scale. Detailed Description

[0041] Now, reference will be made in detail to exemplary embodiments, which are illustrated in the accompanying drawings. The following description refers to the accompanying drawings, where the same numbers in different drawings represent the same or similar elements, unless otherwise specified. The implementations set forth in the description of the following exemplary embodiments do not represent all implementations consistent with the present invention. Instead, they are merely examples of devices and methods consistent with aspects related to the present invention as recited in the appended claims.

[0042] By significantly increasing the packaging density of circuit components such as transistors, capacitors, diodes, etc. on an IC chip, an enhancement in the computing power of an electronic device can be achieved, and the physical size of the device can be reduced. This can be achieved by increasing the resolution to enable the fabrication of smaller structures. For example, the IC chip of a thumb-sized smartphone available in 2019 or earlier may include more than 2 billion transistors, each transistor being less than 1 / 1000 the size of a human hair. Therefore, it is not surprising that semiconductor IC manufacturing is a complex and time-consuming process with hundreds of individual steps. Even an error in one step can greatly affect the functionality of the final product. The goal of the manufacturing process is to increase the overall yield of the process. For example, to achieve a 75% yield in a 50-step process (where a step may indicate the number of layers formed on a wafer), the yield of each individual step must be greater than 99.4%. If the yield of each individual step is 95%, the overall yield of the entire process will be as low as 7%.

[0043] Although a high process yield is required in an IC chip manufacturing facility, it is also important to maintain a high substrate (i.e., wafer) throughput (defined as the number of substrates processed per hour). The presence of defects can affect both the high process yield and the high substrate throughput. This is especially true if operator intervention is required to inspect for defects. Therefore, high-throughput detection and identification of micron- and nanoscale defects by inspection equipment such as a scanning electron microscope (SEM) are crucial for maintaining high yields and low costs.

[0044] An embodiment of an SEM includes a scanning device and a detector device. The scanning device includes an irradiation device, which includes an electron source for generating primary electrons (or charged particles) and a projection device for scanning a sample (such as a substrate) with one or more focused primary electron beams (or multiple beams). The multiple beams can be arranged as a multi-beam. The multiple beams can have a multi-beam arrangement (which can have the form of a grid), and this multi-beam arrangement can be directed towards the sample along a multi-beam path. At least the irradiation device or irradiation system and the projection device or projection system can be collectively referred to as an electron optical system or device. The primary electrons interact with the sample and generate secondary electrons. The detection device captures the secondary electrons from the sample when the sample is scanned so that the SEM can create an image of the scanned area of the sample. For high-volume inspection, some inspection devices use multiple focused primary electron beams, i.e., a multi-beam. The component beams of the multi-beam can be referred to as sub-beams or beamlets. The multi-beam can scan different parts of the sample simultaneously. Thus, a multi-beam inspection device can inspect a sample at a much higher speed than a single-beam inspection device.

[0045] A known implementation of a multi-beam inspection device is described below.

[0046] Although the description and the drawings are directed to an electron optical system, it should be understood that the embodiments are not intended to limit the present disclosure to a particular charged particle. Thus, references to electrons in this document can more generally be considered as references to charged particles, where the charged particles are not necessarily electrons.

[0047] Now referring to Image 1, which is a schematic diagram showing an exemplary charged particle beam evaluation system 100 (or simply referred to as an evaluation system), which can also be called a charged particle beam inspection system or simply referred to as an inspection system or a charged particle metrology system or simply referred to as a metrology system. Figure 1 The charged particle beam evaluation system 100 includes a main chamber 10, a load lock chamber 20, an electron beam system 40, an equipment front end module (EFEM) 30, and a controller 50. The electron beam system 40 is located within the main chamber 10.

[0048] The EFEM 30 includes a first loading port 30a and a second loading port 30b. The EFEM 30 can include additional loading ports. The first loading port 30a and the second loading port 30b can, for example, receive a front-opening unified pod (FOUP) that houses a substrate (such as a semiconductor substrate or a substrate made of other materials) or a sample to be inspected (substrates, wafers, and samples are collectively referred to as "samples" hereinafter). One or more robotic arms (not shown) in the EFEM 30 transport the sample to the load lock chamber 20.

[0049] The load lock chamber 20 is used to remove the gas around the sample. This creates a vacuum, i.e., a local gas pressure that is lower than the pressure of the surrounding environment. The load lock chamber 20 can be connected to a load lock vacuum pump system (not shown), which removes the gas particles within the load lock chamber 20. The operation of the load lock vacuum pump system enables the load lock chamber to reach a first pressure that is lower than atmospheric pressure. After reaching the first pressure, 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 a main chamber vacuum pump system (not shown). The main chamber vacuum pump system removes the gas particles in the main chamber 10 such that the pressure around the sample reaches a second pressure that is lower than the first pressure. After reaching the second pressure, the sample is transported to the electron beam system through which it can be inspected. The electron beam system 40 can include a multi-beam electron optical device (which can be referred to as an electron optical column or apparatus).

[0050] The controller 50 is electrically connected to the electron beam system 40. The controller 50 can be a processor (such as a computer) configured to control the charged particle beam evaluation device 100. The controller 50 can also include circuitry that can be referred to as processing circuitry, which is configured to perform various signal and image processing functions. Although the controller 50 is shown in Figure 1 the figure as being located outside of the structure including the main chamber 10, the load lock chamber 20, and the EFEM 30, it should be understood that the controller 50 can be part of that structure. The controller 50 can be located within one of the constituent components of the charged particle beam inspection device, or it can be distributed across at least two of the constituent components. Although the present disclosure provides an example of a main chamber 10 that houses the electron beam system, it should be noted that aspects of the present disclosure are not limited in the broadest sense to a chamber that houses an electron beam. Instead, it should be understood that the principles described above can also be applied to other devices and other device arrangements that operate at the second pressure. For example, the controller can be a distributed controller that has one or more components at the second pressure and optionally one or more components at the first pressure.

[0051] Now referring to FIG. 2, which is a schematic diagram showing an exemplary electron beam system 40 that includes a multi-beam electron optical system 41, which is Figure 1Part of an exemplary charged particle beam evaluation apparatus 100. The electron beam system 40 includes an electron source 201 and a projection device 230. The electron beam system 40 further includes an actuator stage 209 and a sample holder 207. The electron source 201 and the projection device 230 may be collectively referred to as an electron optical system 41 or an electron optical column. The sample holder 207 is supported by the actuator 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). It should be noted that although an electron beam system including a multi-beam electron optical system is described, this is only one embodiment of the present invention. The invention disclosed herein can be applied to an electron beam system having a single-beam electron optical system.

[0052] The electron source 201 may include a cathode (not shown) and an extractor or an anode (not shown). During 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 the anode to form a primary electron beam 202.

[0053] The projection device 230 is configured to convert the primary electron beam 202 into a plurality of 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 dozens, hundreds, thousands of sub-beams, e.g., approximately ten thousand, tens of thousands or hundreds of thousands of sub-beams. The sub-beams may be referred to as beam waves.

[0054] The controller 50 may be connected to Figure 1 various parts of the charged particle beam evaluation apparatus 100, such as the electron source 201, the detector 240, the projection device 230, and the actuator stage 209 (e.g., an electric stage). The controller 50 may perform various image and signal processing functions. The controller 50 may also generate various control signals to control the operation of the charged particle beam inspection apparatus (including the charged particle multi-beam apparatus).

[0055] The electro - optical device 230 can be configured to focus the sub - beams 211, 212, and 213 onto the sample 208 for inspection and can form probe spots 221, 222, and 223 on the surface of the sample 208 (for this example, three probe spots, one for each sub - beam). The projection device 230 can be configured to deflect the primary sub - beams 211, 212, and 213 to scan the probe spots 221, 222, and 223 over individual scan regions in a portion of the surface of the sample 208. In response to the primary sub - beams 211, 212, and 213 incident on the probe spots 221, 222, and 223 on the sample 208, electrons are generated from the sample 208, which include secondary electrons and backscattered electrons, and these electrons can be referred to as signal particles. The electron energy of the secondary electrons is generally less than or equal to 50 eV. The actual energy of the secondary electrons can be less than 5 eV, but any energy below 50 eV is generally considered a secondary electron. The electron energy of the backscattered electrons is generally between 0 eV and the landing energy of the primary sub - beams 211, 212, and 213. Since electrons with detected energy less than 50 eV are generally considered secondary electrons, a portion of the actual backscattered electrons will be considered secondary electrons.

[0056] The detector 240 is configured to detect signal particles, such as secondary electrons and / or backscattered electrons, and generate corresponding signals, which are sent to the signal processing system 280 for pre - processing, such as analog - to - digital conversion. The detector 240 can be incorporated into the projection device 230. Other details and alternative arrangements of detector modules, sensors, and detector arrays located close to the objective, upstream of the objective's beam, downstream of the objective's beam, or otherwise integrated into the objective can be found in European application number 20216890.2 and PCT application number PCT / EP2021 / 068548, and to the extent that they disclose details of detector modules, sensors, detector arrays, and similar elements, these documents are hereby incorporated by reference.

[0057] The detector can be provided with multiple parts, and more specifically, with multiple detection parts. A detector including multiple parts can be associated with one of the sub-beams 211, 212, 213. Thus, the multiple parts of one detector 240 can be configured to detect signal particles emitted from the sample 208 that are associated with one of the primary beams (which otherwise can be referred to as sub-beams 211, 212, 213). In other words, a detector including multiple parts can be associated with one of the holes in at least one of the electrodes of the objective lens assembly. The multiple parts can be radially and / or angularly arranged segments. More specifically, a detector including multiple parts can be arranged around a single hole, which provides an example of such a detector. As described above, the detection signals from the detector module are used to generate an image. With multiple detection parts, the detection signal includes components from different detection signals, which can be processed as a data set or in a detected image.

[0058] The objective lens can be an objective lens array and can include multiple planar electrodes or plates that include holes for the respective paths of the beams of the multi-beams. Each plate can extend through the multi-beam arrangement. The objective lens can include at least two electrodes that can be connected to and controlled by respective electric potentials. There can be additional plates, and each plate can control an additional degree of freedom. The detector can be a plate associated with or connected to the objective lens that has a hole for each path of the beams of the multi-beams. The detector can be located above, below, or inside the objective lens.

[0059] The scanning deflector can be associated with the objective lens or even integrated into the objective lens, such as an array of scanning deflectors. The array of scanning deflectors can be referred to as a deflector array. In one arrangement, the scanning deflector can be located upstream of the beam of the objective lens. In an arrangement where the path of the primary beam is collimated upstream of the beam of the objective lens, the scanning deflector can be positioned upstream of the beam of the objective lens. In an arrangement where the multi-beams are generated from a primary beam that is collimated by an array of beam limiting holes of the objective lens or an array of beam limiting holes associated with the objective lens, the scanning deflector can be a macro scanning deflector that is located upstream of the beam of the objective lens to operate on the collimated primary beam. Other electro-optical arrangements including one or more of the elements described herein can be envisioned. Such a scanning deflector can be controlled by a controller to deflect the beams of the multi-beams along one axis in the plane of the sample or two principal axes on the surface of the sample (e.g., in the plane of the sample (which can be orthogonal to each other)).

[0060] It should be noted that embodiments of the scanning deflector close to the sample (e.g., a scanning deflector integrated into or close to the objective lens) can have a limited scanning deflection range. However, a scanning deflector close to the sample can be precisely controlled and has a fast response relative to other types of scanning actuators such as an actuating stage.

[0061] During the inspection of sample 208, the controller 50 can control the actuator stage 209 to move the sample 208. The controller 50 can cause the actuator stage 209 to move the sample 208 preferably continuously (e.g., at a constant speed) in one direction at least during sample inspection, which can be referred to as a type of scanning. The speed of the actuator stage can be referred to as the movement rate. The controller 50 can control the movement of the actuator stage 209 such that its movement speed of the sample 208 relative to the path of the multi-beams changes according to various parameters. The controller 50 can control the deflection of the scan deflector such that the path of the multi-beams moves relative to the stage and thus moves on the sample surface. The controller 50 can change the beam deflection of the scan deflector according to various parameters and thus change the scan of the beam on the sample surface. For example, the controller 50 can control the stage speed (including its direction) and / or the scan deflector according to the characteristics of the inspection scan elements and steps, e.g., during the scan process and / or the scan of the scan process, as disclosed in EPA 21171877.0 filed on May 3, 2021. Insofar as such an application discloses at least a combined stepping and scanning strategy of the stage and the scan deflector, the content of the application is incorporated herein. Thus, the movement rate can include the stepping frequency and / or the stage scan rate at different times.

[0062] To acquire a two-dimensional image of the sample, each probe beam is scanned (or rastered) on the sample surface in a two-dimensional raster pattern. This involves movement of the beam in two directions: the main scan direction and the sub-scan direction, which have different orientations, e.g., orthogonal. The main scan direction can be referred to as the fast scan direction. For example, the scan deflector can be controlled to actuate the primary beam (e.g., multi-beam) in the fast direction. The sub-scan direction can be referred to as the slow scan direction. For example, the stage can be controlled to actuate the sample relative to the path of the primary beam; the scan deflector can be controlled to actuate the path of the beam on the sample surface in the slow direction; or both the stage and the scan deflector can be actuated to achieve the scan in the slow direction. The stage is preferably used only in the slow direction because the inertia of its large mass makes it more challenging to achieve scanning movement (e.g., acceleration) in the fast direction than alternatives such as the scan deflector.

[0063] Known multi-beam systems (such as the above-described electron beam system 40 and charged particle beam evaluation device 100) are disclosed in US2020 / 118784, US202002 / 03116, US2019 / 0259564, and WO2021078352, which are incorporated herein by reference.

[0064] The electron beam system 40 can include a projection assembly to adjust the accumulated charge on the sample by irradiating the sample 208.

[0065] Ideally, the images output from a charged particle evaluation device (e.g., electron beam system 40) are automatically processed by a data processing device to detect defects in the sample to be evaluated. The data processing device or at least a part of the data processing device can be part of a controller 50, part of another computer in a fab, or elsewhere integrated in the charged particle evaluation device. Since a charged particle evaluation device, particularly a charged particle evaluation device using multiple charged particle beams, can generate a large amount of data representing a sample image, it is desirable to perform some initial data processing within the charged particle evaluation device, such as an initial identification of candidate defects. If this is done, only the data relevant to the candidate defects (e.g., image clips) needs to be transferred out of the charged particle evaluation device for further analysis. Thus, the amount of data that must be output from the charged particle evaluation device is greatly reduced, and the data transfer rate does not limit the throughput of the charged particle evaluation device.

[0066] Various methods can be employed to detect defects in the images generated by a charged particle evaluation device. A common method is to compare an image of a portion of the sample (referred to herein as the sample image) with one or more reference images. In practice, the data points of the data stream representing the sample image are compared with the data points of the reference images retrieved from memory or delivered in a parallel data stream. For the sake of brevity, this process may be referred to below as comparing images; the data points may be referred to as pixels.

[0067] The result of the comparison of the sample image with the reference image can be a simple binary value representing the difference or correspondence (i.e., match) between the sample image and the reference image. Ideally, the result of the comparison is a difference value representing the magnitude of the difference between the sample image and the reference image. More ideally, the result of the comparison is the difference for each pixel (or each group of adjacent pixels that may be referred to as a "pixel region"), so that the location of the defect within the source image can be determined more precisely.

[0068] To determine whether the difference in pixels or pixel regions between the source image and the reference image represents a candidate defect in the pattern being inspected, a threshold can be applied to the difference corresponding to the pixel or pixel region. The threshold can be pre-fixed, e.g., for a specific charged particle beam system or for a specific pattern to be inspected. The threshold can be a user-set parameter or determined according to other conditions, e.g., it is updated according to the application or evaluation from time to time. The threshold can be determined dynamically, updated during the processing, or both. Alternatively, a predetermined number of locations with the highest differences can be selected as candidate defects for further inspection. Adjacent pixels with differences higher than the threshold can be considered as a single defect or candidate defect. All pixels of a single defect can be given the same difference. The adjacent pixels and all pixels of such a single defect can be referred to as a pixel region.

[0069] False positives (i.e., samples marked as having a candidate defect but actually having no apparent defect) can occur, for example due to noise. By appropriately selecting the threshold used to determine the presence of a defect, the false positive rate can be influenced. By applying noise reduction to either or both of the reference image and the sample image, the false positive rate is further controlled. However, noise reduction increases the amount of processing required to detect defects.

[0070] If it is desired to reduce the noise in the sample image (or reduce the impact of noise in the image), filtering can be applied, such as by averaging the noise. An efficient and effective method that can be used is to apply a simple filter through convolution, such as a uniform filter (convolution with a uniform kernel). By appropriately selecting the size of the (uniform) filter, the efficiency and effectiveness of noise reduction in the sample image can be optimized. The optimal size of the filter can depend on various 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 trade-off between sensitivity and selectivity. The size of the kernel used to implement the filter can be equal to a non-integer number of pixels. A kernel width in the range of 1.1 to 5 pixels, ideally in the range of 1.4 to 3.8 pixels, is suitable for various use cases. Other details of the filtering of the sample image data are given in the international application PCT / EP2022 / 060622 filed on April 21, 2022, which is incorporated herein by reference, at least with respect to the description of filters and filtering to reduce noise. Such filtering can be supplementary or alternative to the invention disclosed herein. Better filtering can tolerate more noise in the original image, so filtering is an alternative to the disclosed invention, which can increase throughput at a lower signal-to-noise ratio (SNR). However, filtering and the disclosed invention can be considered complementary because they can both be applied in the same evaluation process. Applying filtering and the disclosed invention simultaneously can be combined to reduce the SNR, thereby achieving a greater throughput.

[0071] Figure 3A method for evaluating a sample according to an embodiment is depicted. In this method, a sample image is compared with two reference images obtained from different parts of the same sample as the sample image. (Note that the sample image may be referred to as a "test image".) The method begins with obtaining S1 a first reference image and obtaining S2 a second reference image. Details of reference image acquisition 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 multiple beams on the same surface. The two reference images can be scanned by two different beams out of multiple beams. At least two reference images cover a surface area of the sample within the field of view region of the multiple beams on the sample surface. In different embodiments, the two reference images are scanned in two separate scans or reference scans; note that when using a single-beam charged particle evaluation device, the separate scans scan two reference regions. The sample region (which may also be referred to as the test region) is scanned S3 to obtain a sample image.

[0072] The sample region is compared S4 with the two reference images. The comparison can be performed pixel by pixel or by pixel groups. An alignment process can be performed before the comparison. At S5, a determination is made, and as a result, the process proceeds to step S6, S7, or S8. The determination at S5 is whether the comparison reveals: A) no difference (0 difference) between the sample image and the reference images, in which case the process transfers to S6; B) a difference (one (1) difference) between the sample image and one of the reference images, in which case the process transfers to S7; and C) a difference (two (2) differences) between the sample image and the two reference images, in which case the process transfers to S8. The sample image and the reference images are ideally multi-valued such that a difference can be identified if the difference between pixel values is greater than a threshold. If the comparison is performed based on a group of pixels, a threshold can be applied to different numbers of pixels in the group.

[0073] If there is no difference between the sample image and the reference images, the sample image is considered to be free of defects, and the sample region can be marked S6 as being free of defects. A new sample region is scanned, and the process is repeated until all regions to be evaluated have been processed.

[0074] If there is a difference between the sample image and one of the reference images, it is assumed that one of the reference images has an obvious defect, such as due to noise, and the reference region is marked S7 accordingly. The process continues with scanning a new sample region.

[0075] If there is a difference between the sample image and two reference images at the same location in the pattern, the sample image is assumed to represent a candidate defect on the sample, and the S8 sample region is marked accordingly. Data representing the candidate defect (such as a data set, e.g., an image clip) can be transmitted S9 to an external device for further analysis. The process continues to scan new sample regions.

[0076] The two reference images are acquired with a higher fidelity than the sample image, whereas in previous methods, the reference image and the sample image were acquired under the same conditions. Here, the fidelity of an image can indicate the degree to which the image shows the true features of the corresponding region of the sample. In other words, the reference image is a more accurate representation of the corresponding region of the sample. Ideally, the reference image has a higher signal-to-noise ratio than the sample image. Ideally, the reference image has a lower distortion level than the sample image. Ideally, the reference image has a higher contrast-to-noise ratio (as described further below) than the sample image. Ideally, the reference image has fewer interfering defects (i.e., defects that appear to be in the image but do not represent actual defects on the sample). Generally, when comparing the sample image with the reference image, the reference image can be improved in any feature that reduces false positives and / or false negatives.

[0077] Several different methods can be used to acquire reference images with a higher fidelity than the sample image. For example, a reference image can be acquired by scanning a portion of the sample designated as the reference region at a slower rate than the rate used to acquire the sample image, as described below for reference image 4. A reference image can be acquired by scanning the portion of the sample designated as the reference multiple times and combining the results of the multiple scans, as described below for reference image 5. Another method 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 for reference image 6. These different methods can be used alone or in combination with one or more different methods, as long as the combined methods are compatible with each other. It should be noted that regardless of the definition of fidelity, by comparing the sample image with the reference image and noting that the definition of fidelity applies to all three images, the comparison shows the differences between each reference image and the sample image; this is independent of the fidelity of one or both of the images.

[0078] Optionally, the same beam (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 and data routing can be simplified. For example, calibration of the relative position of the beam with respect to the ideal beam position can be avoided.

[0079] Embodiments of the present invention can increase the throughput of a charged particle evaluation apparatus while maintaining a desired capture / interference ratio. A user of a charged particle evaluation apparatus may desire to detect at least a certain percentage (e.g., 90%) of the true defects on a sample (referred to as the capture rate), but at the same time, the false positives (interference rate) among the detected candidate defects do not exceed a certain percentage (e.g., 10%). By varying the threshold difference between the sample image and the reference image to detect candidate defects, a trade-off can be made between the capture rate and the interference rate. Increasing the threshold ideally reduces the interference rate but undesirably reduces the capture rate, and vice versa.

[0080] Reducing the noise in the reference image and the sample image reduces the interference rate without reducing the capture rate. However, reducing the noise (beyond what can be achieved by signal processing) generally reduces the throughput, e.g., because the scan speed must be reduced. It is generally assumed that the reference image must be acquired under the same conditions as those used to acquire the sample image in order to enable an effective comparison, i.e., a like-for-like comparison. However, the present inventors have determined that by investing time to improve the fidelity of the reference image (e.g., by using a slower scan speed or performing multiple scans), the time for scanning the sample image can be saved (e.g., by scanning at a faster rate than otherwise) without compromising the capture rate and the interference rate, thereby increasing the throughput. The amount of throughput gain depends on the number of reference images and sample images used; the more sample images, the greater the throughput gain. Alternatively, the throughput can be maintained (compared to scanning the reference image and the sample image under the same conditions), and the capture rate and the interference rate can be improved.

[0081] As described above, a first method of improving the fidelity of the reference image is to scan at a rate slower than the rate used to scan the sample image. This is in Figure 4As shown in. In step S41, a reference scan rate is set. The reference scan rate can be an integer multiple of the sample scan rate (in other words, the sample scan rate is n times the reference scan rate, where n is a positive integer, such as 2 or 3). In step S42, the reference area is scanned at the reference scan rate 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. In the case where the reference scan rate is an integer multiple of the sample scan speed, downsampling can be performed by simply averaging n adjacent pixels. If the reference scan rate is not an integer multiple of the sample scan speed, interpolation can also be performed. Simple averaging requires less processing, so it is advantageous for the reference scan rate to be an integer multiple of the sample scan speed. Downsampling increases the signal-to-noise ratio (SNR) and / or the contrast-to-noise ratio (CNR). This makes the reference image have higher fidelity than the reference image obtained at the scan rate of the sample image. Scanning the reference image at a slower speed to improve fidelity can enable the sample image to be scanned at a faster scan rate than when scanning the reference image and the sample image at the same scan rate, while still achieving the same defect detection performance. In most cases, this provides a throughput advantage, but the magnitude of the advantage will depend on the number of sample images scanned, the different scan rates, and other factors such as the routing between the reference area and the sample area. Since the embodiments are implemented only by software upgrade, even a small benefit (such as increased throughput) will be cost-effective and easy to implement.

[0082] Take the use case of increasing the sample scan rate and decreasing the reference scan rate relative to the known art of scanning the sample image and the reference image at a scan rate as an example. (For a specific example, the reduction factor of the reference image at the same scan rate is the same as the increase factor of the sample scan rate; but in most cases, this relationship does not apply.) The net time spent scanning two reference images using the present invention is generally longer than the net time spent scanning two reference images using the known art. However, as the number of sample images scanned increases, the time required to scan two reference images and all the sample images is shorter than the time required to scan two reference images and all the sample images in the previously known art. The scan rate of the reference image relative to the scan rate of the sample image can depend on the number of sample images to be scanned (or acquired).

[0083] In Figure 4In the method, it is assumed that the detector sampling rate remains constant, such that reducing the scan rate results in a higher resolution image. The detector sampling rate can also be reduced, ideally, in the same proportion as the scan rate. In this case, the image resolution remains unchanged, and the pixel averaging step S43 can be omitted. In practice, pixel averaging is performed in the detector. Two reference images can be acquired at different scan rates and / or different sampling rates, provided that the reference images are processed to have the same resolution as the sample images with which they will be compared.

[0084] A second method for improving the fidelity of the reference image is to scan the reference region multiple times, e.g., two to three times. This is depicted in Figure 5 In step S51, the reference region is scanned. In step S52, the reference region is scanned again, thereby acquiring multiple overlapping images of the reference region. In step S53, the multiple overlapping images are averaged. An alignment process can be performed before averaging the multiple overlapping images. This process is repeated for another reference region. Depending on the location of the reference regions, it may be more efficient to acquire a first image of each reference region, and then a second image of each reference region, rather than acquiring two images of one reference region and then two images of a second reference region. Acquiring multiple images of each reference region and then combining them (e.g., by averaging) will increase the signal-to-noise ratio (SNR) and / or the contrast-to-noise ratio (CNR), thereby improving the fidelity. Thus, increasing the number of images used to generate the reference image for each reference region improves the fidelity of the reference image. Similarly, in most cases, this provides a throughput advantage, but the magnitude of the advantage will depend on the number of sample images scanned, the number of scans per reference region, different scan rates, and other factors such as the routing between the reference region and the sample region.

[0085] It should be understood that the first and second methods can be combined, i.e., multiple images of the reference region are acquired at a scan rate slower than the scan rate used for the sample images. However, the improvement of the reference image may be subject to diminishing returns.

[0086] A third method for improving the fidelity of the reference image is to update the reference image(s) during the evaluation of the sample region. This is depicted in Figure 6Shown in. The reference region is scanned S61 to generate a reference image, and the sample region is scanned S62 to generate a sample image. If a multi-beam evaluation device is used, these steps can be performed sequentially or simultaneously. The sample image is compared with the reference image S63, and it is determined S64 whether there are differences (e.g., applying a threshold as described above). An alignment process can be performed before the comparison. If there are significant differences indicating candidate defects, the sample region can be marked and data (e.g., a clip) can be sent for further analysis, as described in steps S8 and S9 of reference image 3 above. If there are no significant differences, the sample region is marked S65 as defect-free, and the reference image is updated S66. The process is repeated to scan a new sample region as a new iteration. It should be noted that this method seems to use only a single reference. After examining multiple sample images, a single reference is sufficient because the reference image is the average of multiple samples; differences due to, for example, false positives are statistically reduced (e.g., averaged). However, initially two reference images can be used to reduce the risk of false positives in the reference image. Multiple different reference images can be used until the contribution of differences (such as false positives in the reference image) is statistically reduced to have little or even no meaningful statistical contribution to the reference image.

[0087] Updating the reference image can include generating a combination (e.g., an average) of the previous reference image and the current sample image. The average can be a weighted average. The weight given to the sample image can vary between iterations, e.g., decrease. For example, when the reference image is updated for the nth time, the weight of the sample image can be proportional to 1 / n. It is not necessary to update the reference image 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 the contrast-to-noise ratio (CNR). Thus, each update of the reference image improves the fidelity of the reference image for comparison with sample images acquired later.

[0088] The concept of improving fidelity by updating the reference image when acquiring a new sample image can also be applied starting from a single reference image. Ideally, the initial reference image is acquired with a higher fidelity than the sample images. Ideally, multiple sample images are acquired from different regions of the sample.

[0089] Comparing each sample image with a reference image can generate a dataset indicating candidate defects present in the sample image. The fidelity of the reference image can be further improved by validating the candidate defects in the dataset, which is done by removing a selection dataset from the dataset, ideally all candidate defects present in all datasets. Ideally, the validation includes comparing the selection dataset of the dataset and / or generating a removal defect set of defects that may be present in all selected datasets. For example, if candidate defects are identified at the same location in many sample images, it is more likely that there is a defect at that location in the reference image. In such a case, the reference image can be improved by removing the candidate defects present in the removal defect set from the reference image to update the reference image to an updated reference (or new reference image). Then, the method can continue by acquiring another sample image of a sample region of the sample and comparing the other sample image with the updated reference to identify any candidate defects in the sample region. Ideally, the dataset of candidate defects can be used to remove false positives from the reference image to evaluate other sample images of the sample.

[0090] Other methods can also be employed to improve the fidelity of the reference image, such as by increasing the beam current, e.g., scanning the reference image using a reference beam current that is higher than the sample beam current used to scan the sample image. While increasing the beam current generally improves the image quality, due to surface charging effects and random effects, it is not a linear relationship. In one embodiment, the beam current is related to the expected resolution. For example, a high-current beam can be used for high resolution. A low-current beam can be used for low resolution. The effect of noise can be more significant when using a low beam current than when using a high beam current. In the present method, scanning the reference image using a beam current higher than that used to scan the sample image allows the reference image and the sample image to be scanned at a similar or even the same resolution. Therefore, the effect of noise on the reference sample image scanned at a higher beam current can be less than the effect on the sample image scanned at a lower beam current.

[0091] Embodiments of the present invention are particularly useful in cases where the patterns formed in each die of the sample do not have significant repeating elements and / or the pattern regions to be inspected do not have repeating elements. Such a sample can be referred to as having a "random" pattern, although the pattern is designed and not random. However, the pattern does repeat between dies, in other words, all dies on the sample are conceptually the same. The present invention does not limit which dies of the sample are selected as the reference region for scanning, nor which dies will be scanned as the sample region. However, it can be advantageous to select regions with a historically lower defect rate from the reference region of the sample. For example, it may be desirable to select non-edge dies as the reference region.

[0092] Although the described invention is directed to a charged particle electron optical system configured to project multiple beams onto a sample, the invention is equally applicable to a charged particle system configured to project a single beam of charged particles onto a sample. The inventors have demonstrated that the effective improvements of the present invention for multi-beam and single-beam systems are the same in proportion. However, the area that can be processed using a multi-beam system can be larger because the area of each region scanned by a multi-beam system is generally larger than that of a single-beam system. A multi-beam system can be used to achieve a higher net throughput than a single-beam system. The magnitude of the throughput advantage will depend on the number of sample images scanned, the number of scans of each reference region, different scan rates, and other factors such as the routing between the reference region and the sample region.

[0093] Note that there are exceptions when a multi-beam system can ensure better improvements than those achieved by the present invention in a single-beam system. That is, when scanning two reference regions, the reference regions are scanned in a single scan of the multi-beam. In this case, the time required for the slower reference scan is halved by obtaining the reference image in a single scan instead of two scans. It should be noted that generally, there will be a significant increase in throughput, which is more significant when scanning a small number of sample regions (e.g., less than ten).

[0094] As Figure 7 shown, the data processing device 500 that can be used to analyze a sample image includes a filter module 501 that receives the sample image from the detector module 240 and filters it, reference image storage units 503a, 503b that provide reference images based on source images, comparators 502a, 502b that compare the filtered sample image with the reference images, and an output module 504 that processes and outputs the comparison result. Alignment of the sample image and the reference image can be performed as a separate step before or after the filtering step or as part of the comparison step.

[0095] As described above, the filter module 501 applies a filter to the input data. The filter module 501 is conveniently implemented by dedicated hardware (e.g., FPGA or ASIC). Such dedicated hardware can be more efficient and cost-effective than a programmed general-purpose computing device (such as a standard or common type of CPU architecture). The processor may not be as powerful as a CPU but can have an architecture suitable for processing software for detecting signal data (i.e., images) and thus be able to process images in the same or less time than a CPU. Although the processing power of such a detected processing architecture is lower than that of most contemporary CPUs, it can be equally fast in processing data because the data architecture of the dedicated processing architecture is more efficient. A general-purpose CPU can be advantageous because it allows for easy replacement of the filter.

[0096] Referring again to Image 7, comparators 502a, 502b can be any logic circuit capable of comparing two values, such as an XOR gate or a subtractor. Comparators 502a, 502b are also suitable for implementation by dedicated hardware, such as an FPGA or an ASIC. Such dedicated hardware is more efficient and economical than a programmed general-purpose computing device (e.g., a CPU). Ideally, comparators 502a, 502b are implemented on the same dedicated hardware as filter module 501.

[0097] In some cases, reference image storage units 503a, 503b can also be implemented in dedicated hardware. In such a case, it is desirable for the reference image generator to be implemented in the same dedicated hardware as the comparator and / or filter module.

[0098] Output module 504 receives the result output by comparator 502 and prepares it for output to the user, other fab systems, or for further processing within the inspection system. The output can be in any of several different forms. In the simplest option, the output can simply be an indication of whether the sample has a defect or not. However, since almost all samples will have at least one potential defect, more detailed information is needed, such as as a data set, such as an image (e.g., a data set that can be rendered as an image). Thus, the output can include, for example, a defect location map, a deviation image, pixel data clips (e.g., an image and a clip of the reference image or the reference image), and / or information about the severity of a possible defect represented by the magnitude of the difference between the sample image and the reference image, such as how much the sample image deviates from the reference image.

[0099] Output module 504 can also filter potential defects, e.g., only output the defect locations where the magnitude of the difference between the sample image and the reference is greater than a threshold or the pixel density showing the difference is higher than a threshold. Another possibility is to only output a predetermined number of the most severe defect sites, represented by the magnitude of the difference. This can be achieved by storing the defect sites in buffer 510 and, when the buffer is full, overwriting the lowest magnitude defect if a higher magnitude defect is detected.

[0100] Any suitable format can be used to output the defect information, such as a list, a data set, an image, or a map. Ideally, output module 504 can output a clip, i.e., an image of the area of the sample where a potential defect was detected. This allows further examination of the potential defect to determine if the defect is real and severe enough to affect the operation of the device formed or present on the sample. The rest of the source image (i.e., the part not saved as a clip) can be discarded to save data storage and transmission requirements. Thus, the data set can be a set of clips; the image can include the set of clips.

[0101] The data processing device 500 can be remote from the detector array, e.g., within a vacuum chamber. The data processing device can be part of an electro - optical assembly of an electro - optical column; such an assembly can include a detector (such as a detector array) and an objective lens (such as an objective lens array). The detector can be in the path of the beam grid, and the data processing device can be remote from the path of the beam grid. The data processing device can be separate from, but electrically connected to, the detector. In different embodiments, at least a portion (if not all) of the data processing device is remote from the electro - optical column, such as remote from the electro - optical assembly, even outside the vacuum chamber including the electro - optical column. At least a portion of the data processing device can signal communicate with the detector through a feed - through in the wall of the chamber.

[0102] References to upper and lower, up and down, above and below, etc. should be understood to refer to directions parallel to (usually but not always perpendicular to) the beam - upstream and beam - downstream directions of the electron beam or beams impinging on the sample 208. Thus, references to beam - upstream and beam - downstream are intended to refer to directions of the beam path independent of any current gravitational field.

[0103] The embodiments described herein can take the form of a series of hole arrays or electro - optical elements arranged in an array along the beam or beams path. Such electro - optical elements can be electrostatic. In one embodiment, all electro - optical elements (e.g., from the beam - limiting hole array to the last electro - optical element in the sub - beam path before the sample) can be electrostatic and / or can be in the form of a hole array or a plate array. In some arrangements, one or more electro - optical elements are fabricated as micro - electro - mechanical systems (MEMS) (i.e., using MEMS fabrication techniques). The electro - optical elements can have magnetic and electrostatic elements. For example, a compound array lens can feature a macro - magnetic lens that surrounds the multi - beam path, has upper and lower plates within the magnetic lens, and is arranged along the multi - beam path. The plates can be a hole array for the beam path of the multi - beam. Electrodes can be present above, below, or between the plates to control and optimize the electromagnetic field of the compound lens array.

[0104] Although the embodiments described herein are multi-beam electron optical systems characterized by electrostatic electron optics, such as characterized by electrode plates with holes for operating on different beams in a multi-beam, the evaluation system can be characterized by a multi-beam electron optical system including magnetic components. For example, the electron optical system can include at least one of the following: a macro magnetic condenser lens that can be set in a non-rotating setting; a stack of electron optical arrays for fine operation on the beams of the multi-beam; a beam limiting aperture array for generating and / or shaping the multiple beams of the multi-beam, which can be a plate upstream of the beam of the condenser lens and / or a plate downstream of the beam between the condenser lens and the stack of electron optical arrays; a macro magnetic objective lens for projecting the multiple beams onto a sample and characterized by electrostatic elements; a Wien filter for allowing the primary beam to be directed towards the sample and for guiding signal particles from the sample to a detector that can be located in a secondary column; and a detector in the secondary column. In another arrangement of the evaluation system, the electron optical system can be designed to project a single beam onto the sample. Such a single-beam design can be similar to a multi-beam electron optical system characterized by a magnetic condenser lens; in a variant, the detector is located in the main column (i.e., there is no secondary column or Wien filter), for example facing the sample location and / or located between the condenser lens and the objective lens.

[0105] The terms "sub-beam" and "beam wave" can be used interchangeably herein, and both are understood to include any radiation beam derived from a parent radiation beam by dividing or splitting the parent radiation beam. The term "manipulator" is used to cover any element that affects the path of a sub-beam or beam wave, such as a lens or deflector. A reference to an element aligned along a beam path or sub-beam path is understood to mean that the corresponding element is located along the beam path or sub-beam path. A reference to an optical device is understood to refer to an electro-optical device.

[0106] An evaluation tool or evaluation system according to the present disclosure can include a device for qualitatively evaluating a sample (e.g., pass / fail), a device for quantitatively measuring a sample (e.g., the size of a feature), or a device for generating a map image of the sample. Examples of evaluation tools or systems are inspection tools (e.g., for identifying defects), review tools (e.g., for classifying defects), and metrology tools, or any combination of tools capable of performing evaluation functions related to inspection tools, review tools, or metrology tools (e.g., subway inspection tools).

[0107] References to assemblies or systems of components or elements that can be controlled to manipulate a charged particle beam in some manner include configuring a controller or control system or control unit to control the assembly to manipulate the charged particle beam in the above manner, and optionally using other controllers or devices (e.g., a voltage source) to control the assembly to manipulate the charged ion beam in this way. For example, a voltage source can be electrically connected to one or more components to apply an electrical potential to the components under the control of a controller or control system or control unit, such as applying an electrical potential to the electrodes of a control lens array and an objective lens array. An actuatable member (such as a stage) can use one or more controllers, control systems or control units to control the actuation of the member so as to move and thus relative to another member (such as a beam path).

[0108] The method of the present invention can be executed by a computer system including one or more computers. The computers for implementing the present invention can 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 dedicated processors. As described above, in some cases, a particular type of processor can provide advantages in reducing costs and / or increasing processing speed, and the method of the present invention can be applicable to the use of a particular processor type. Certain steps of the method of the present invention involve parallel computations that are easily implemented on a processor capable of parallel computing (e.g., a GPU).

[0109] The computers for implementing the present invention can be physical or virtual. The computers for implementing the present invention can be a server, a client or a workstation. Multiple computers for implementing the present invention can be distributed and interconnected via a local area network (LAN) or a wide area network (WAN). The results of the method of the present invention can be displayed to a user or stored in any suitable storage medium. The present invention can be embodied in a non-transitory computer-readable storage medium storing instructions for executing the method of the present invention. The present invention can be embodied in a computer system that includes one or more processors and a memory or storage device storing instructions for executing the method of the present invention.

[0110] The functions provided by a computer and a processor (such as a controller or a control system or a control unit) can be implemented by a computer. Any suitable combination of elements can be used to provide the required functions, including, for example, a CPU, RAM, SSD, motherboard, network connection, firmware, software, and / or other elements known in the art that allow the execution of the required computational operations. The required computational operations can be defined by one or more computer programs. Such computer programs can take the form of multiple computer programs, which can be implemented, for example, by different processors. One or more computer programs can be provided in the form of a medium storing computer-readable instructions, optionally a non-transitory medium. When the computer reads the computer-readable instructions, the computer performs the required method steps. The computer can consist of a self-contained unit or a distributed computing system having multiple different computers connected to each other via a network.

[0111] As used herein, the term "image" is intended to refer to any data structure of values, where each value is related to a sample at a location, and the arrangement of the values in the array corresponds to the spatial arrangement of the sampling locations. The term "data map" can be used to describe such a data structure. An image can include a single layer or multiple layers. In the case of a multi-layer image, each layer (also called a channel) represents a different sample at the location. The term "pixel" is intended to refer to a single value of the array, or in the case of a multi-layer image, a set of values corresponding to a single location. An image can be stored in a computer-readable storage medium in any convenient format.

[0112] Embodiments of the present invention are described in the following numbered clauses.

[0113] Clause 1. A charged particle evaluation method for identifying candidate defects in a sample by scanning a charged particle beam over the sample; the method comprising:

[0114] 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;

[0115] acquiring a sample image from a third region of the sample using the charged particle evaluation device; and

[0116] comparing the sample image with the first reference image and the second reference image to identify any candidate defects in the third region;

[0117] wherein the first reference image and / or the second reference image is acquired with a higher fidelity than the sample image.

[0118] Clause 2. The charged particle evaluation method according to Clause 1, wherein:

[0119] Obtaining the first reference image and the second reference image includes relatively scanning the sample and the charged particle beam at a reference scanning rate;

[0120] Obtaining the sample image includes relatively scanning the sample and the charged particle beam at a sample scanning rate; and

[0121] The reference scanning rate is slower than the sample scanning rate, such that the reference image has a higher fidelity than the sample image.

[0122] Clause 3. The charged particle evaluation method according to Clause 2, wherein obtaining 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 scanning rate, and downsampling the first high-resolution reference image and / or the second high-resolution reference image to respectively generate the first reference image and / or the second reference image having a resolution equal to that of the sample image.

[0123] Clause 4. The charged particle evaluation method according to Clause 2 or 3, wherein the sample scanning rate is an integer multiple of the reference scanning rate.

[0124] Clause 5. The charged particle evaluation method according to Clause 4, wherein downsampling includes averaging the pixel values of the first high-resolution reference image and / or averaging the pixel values of the second high-resolution reference image.

[0125] Clause 6. The charged particle evaluation method according to Clause 2 or 3, wherein the sample scanning rate is a non-integer multiple of the reference scanning rate.

[0126] Clause 7. The charged particle evaluation method according to Clause 6, wherein downsampling includes interpolating the pixel values of the first high-resolution reference image and / or the second high-resolution reference image.

[0127] Clause 8. The charged particle evaluation method according to any one of Clauses 2 to 7, wherein relatively scanning the sample and the charged particle beam includes: moving the sample at a moving rate using an actuating stage, and scanning the charged particle beam at a scanning deflector rate using a scanning deflector, and at least one of the moving rate and the scanning deflector rate when obtaining the reference image is higher than when obtaining the sample image, desirably, the moving rate includes a step frequency and / or a stage scanning rate.

[0128] Clause 9. The charged particle evaluation method according to any one of the preceding clauses, wherein:

[0129] Obtaining the first reference image and the second reference image includes: obtaining a plurality of overlapping images of the first region and the second region, and averaging the plurality of overlapping images to respectively obtain the first reference image and the second reference image having a fidelity higher than that of the sample image.

[0130] Clause 10. The charged particle evaluation method according to any one of the foregoing clauses, wherein:

[0131] The first reference image and the second reference image are obtained using a reference beam current; and

[0132] The sample image is obtained using a sample beam current;

[0133] wherein the reference beam current is higher than the sample beam current.

[0134] Clause 11. The charged particle evaluation method according to any one of the foregoing clauses, further comprising:

[0135] Generating a new reference image by combining the sample image with one of the first reference image and the second reference image;

[0136] Obtaining another sample image from another region of the sample using the charged particle evaluation device; and

[0137] Comparing the another sample image with the new reference image to identify any candidate defects in the another region.

[0138] Clause 12. The charged particle evaluation method according to Clause 11, wherein generating the new reference image includes: calculating an average value, desirably a weighted average value, of the sample image and one of the first reference image and the second reference image.

[0139] Clause 13. The charged particle evaluation method according to Clause 11 or 12, further comprising repeating the following steps: generating a new reference image; obtaining another sample image; and comparing the another sample image.

[0140] Clause 14. The charged particle evaluation method according to any one of the foregoing clauses, 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, wherein the reference signal-to-noise ratio is higher than the sample signal-to-noise ratio.

[0141] Clause 15. A charged particle evaluation method for identifying candidate defects in a sample by scanning a charged particle beam over the sample; the method includes:

[0142] Obtain a reference image from a first region (ideally a reference region) of the sample using a charged particle evaluation device;

[0143] Obtain a sample image from a second region (ideally a sample region) of the sample using the charged particle evaluation device;

[0144] Compare the sample image with the reference image to determine whether there may be a defect in the sample region;

[0145] Generate a new reference image by combining the sample image and the reference image;

[0146] Obtain another sample image from another region of the sample using the charged particle evaluation device; and

[0147] Compare the another sample image with the new reference image to determine whether there may be a defect in the another region.

[0148] Clause 16. A charged particle evaluation method for detecting a defect in a sample by scanning a charged particle beam over the sample; the method includes:

[0149] Obtain a reference image from a first region of the sample using a charged particle evaluation device;

[0150] Obtain a sample image from a second region of the sample using the charged particle evaluation device;

[0151] Compare the sample image with the reference image to identify any candidate defects in the sample region;

[0152] Wherein the reference image is obtained with a higher fidelity than the sample image.

[0153] Clause 17. The particle evaluation method according to Clause 16, further comprising: obtaining a plurality of sample images from different regions of the sample.

[0154] Clause 18. The particle evaluation method according to Clause 17, wherein comparing each sample image with the reference image includes: generating a data set indicating candidate defects present in the sample image.

[0155] Clause 19. The particle evaluation method according to Clause 18, further comprising: verifying the candidate defects in the data set by removing a selected data set from the data set, ideally candidate defects present in all data sets; ideally, the verification includes comparing the selected data set of the data set and / or generating a set of removed defects of possible defects present in all selected data sets.

[0156] Clause 20. The particle evaluation method according to Clause 19 further includes: updating the reference image to an updated reference (or new reference image) by removing candidate defects present in the removal defect set from the reference image.

[0157] Clause 21. The particle evaluation method according to Clause 20 further includes: obtaining another sample image of a sample region of the sample and comparing the another sample image with the updated reference to identify any candidate defects in the sample region.

[0158] Clause 22. The particle evaluation method according to any one of Clauses 18 to 21 includes: using a data set of the candidate defects to remove false positives from the reference image for evaluating other sample images of the sample.

[0159] Clause 23. A computer program for controlling a charged particle evaluation device, the computer program including instructions which, when executed by the charged particle evaluation device, cause the charged particle evaluation device to execute the method according to any one of the preceding clauses.

[0160] Clause 24. A charged particle evaluation device for identifying candidate defects in a sample by scanning a charged particle beam over the sample; the device includes:

[0161] A detector unit configured to output a digital detection signal of pixel values in response to signal particles incident from the sample;

[0162] A scanning unit for relatively scanning the sample and the charged particle beam;

[0163] A controller configured to control the detector unit and the scanning unit to obtain a first reference image from a first region of the sample, and a second reference image from a second region of the sample, and a sample image from a third region of the sample; and

[0164] A comparator configured to compare the sample image with the first reference image and the second reference image to identify any candidate defects in the third region;

[0165] wherein the first reference image and / or the second reference image is obtained with a higher fidelity than the sample image.

[0166] Clause 25. The charged particle evaluation device according to Clause 24, wherein the scanning unit includes:

[0167] A charged particle device configured to direct a charged particle beam towards the sample; and

[0168] A stage, configured to support the sample, and the charged particle device and the stage are configured to scan the surface of the sample with the charged particle beam.

[0169] Clause 26. The charged particle evaluation device according to Clause 24 or 25, wherein the controller is configured to control the detector unit and the scanning unit to:

[0170] Obtain the first reference image and the second reference image by relatively scanning the sample and the charged particle beam at a reference scanning rate;

[0171] Obtain the sample image by relatively scanning the sample and the charged particle beam at a sample scanning rate; and

[0172] The reference scanning rate is slower than the sample scanning rate, such that the reference image has a higher fidelity than the sample image.

[0173] Clause 27. The charged particle evaluation device according to Clause 26, wherein the controller is configured to control the detector unit and the scanning unit to obtain the first reference image and the second reference image by:

[0174] Generate a first high-resolution reference image and / or a second high-resolution reference image at the reference scanning rate, and downsample the first high-resolution reference image and / or the second high-resolution reference image to respectively generate the first reference image and / or the second reference image having a resolution equal to that of the sample image.

[0175] Clause 28. The charged particle evaluation device according to Clause 26 or 27, wherein the sample scanning rate is an integer multiple of the reference scanning rate.

[0176] Clause 29. The charged particle evaluation device according to Clause 28, wherein downsampling includes averaging the pixel values of the first high-resolution reference image and / or averaging the pixel values of the second high-resolution reference image.

[0177] Clause 30. The charged particle evaluation device according to Clause 26 or 27, wherein the sample scanning rate is a non-integer multiple of the reference scanning rate.

[0178] Clause 31. The charged particle evaluation device according to Clause 30, wherein downsampling includes interpolating the pixel values of the first high-resolution reference image and / or the second high-resolution reference image.

[0179] Clause 32. The charged particle evaluation device according to any one of Clauses 25 to 31, wherein the controller is configured to control the detector unit and the scanning unit to obtain the first reference image and the second reference image in the following manner:

[0180] Obtain a plurality of overlapping images of the first region and the second region, and average the plurality of overlapping images to respectively obtain the first reference image and the second reference image having a higher fidelity than the sample image.

[0181] Clause 33. The charged particle evaluation device according to any one of Clauses 25 to 32, wherein the controller is configured to control the detector unit and the scanning unit to:

[0182] Obtain the first reference image and the second reference image using a reference beam current; and

[0183] Obtain the sample image using a sample beam current;

[0184] wherein the reference beam current is higher than the sample beam current.

[0185] Clause 34. The charged particle evaluation device according to any one of Clauses 25 to 33, wherein the controller is further configured to control the detector unit and the scanning unit to:

[0186] Generate a new reference image by combining the sample image with one of the first reference image and the second reference image;

[0187] Obtain another sample image from another region of the sample; and

[0188] Compare the another sample image with the new reference image to identify any candidate defects in the another region.

[0189] Clause 35. The charged particle evaluation device according to Clause 34, wherein the controller is configured to control the detector unit and the scanning unit to generate a new reference image in the following manner: calculate the average value, desirably a weighted average value, of the sample image and one of the first reference image and the second reference image.

[0190] Clause 36. The charged particle evaluation device according to Clause 34 or 35, wherein the controller is further configured to control the detector unit and the scanning unit to repeat the following steps: generate a new reference image; obtain another sample image; and compare the another sample image.

[0191] Clause 37. The charged particle evaluation device according to any one 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 wherein the reference signal-to-noise ratio is higher than the sample signal-to-noise ratio.

[0192] Although the invention has been described in connection with various embodiments, other embodiments of the invention will be apparent to those skilled in the art upon 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 the true scope and spirit of the invention being indicated by the appended claims.

Claims

1. A charged particle evaluation method for identifying candidate defects in a sample by scanning a charged particle beam over the sample; the method comprising: Obtaining 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; Obtaining 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 obtained with a higher fidelity than the sample image.

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

3. The charged particle evaluation method according to claim 2, wherein obtaining 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 respectively generate the first reference image and / or the second reference image having a resolution equal to that of the sample image.

4. The charged particle evaluation method according to claim 2 or 3, wherein the sample scan rate is an integer multiple of the reference scan rate, or wherein the sample scan rate is a non-integer multiple of the reference scan rate.

5. The charged particle evaluation method according to claim 4, wherein downsampling includes averaging the pixel values of the first high-resolution reference image and / or averaging the pixel values of the second high-resolution reference image.

6. The charged particle evaluation method according to claim 4, wherein downsampling includes interpolating the pixel values of the first high-resolution reference image and / or the second high-resolution reference image.

7. The charged particle evaluation method according to any one of claims 2 to 6, wherein relatively scanning the sample and the charged particle beam comprises: Moving the sample at a movement rate using an actuating stage and scanning the charged particle beam at a scanner deflector rate using a scanner deflector, and at least one of the movement rate and the scanner deflector rate when obtaining the reference image is higher than when obtaining the sample image, desirably, the movement rate includes a step frequency and / or a stage scan rate.

8. The charged particle evaluation method according to any one of the preceding claims, wherein: Obtaining the first reference image and the second reference image includes: obtaining a plurality of overlapping images of the first region and the second region and averaging the plurality of overlapping images to respectively obtain the first reference image and the second reference image having a higher fidelity than the sample image.

9. The charged particle evaluation method according to any one of the preceding claims, wherein: The first reference image and the second reference image are obtained using a reference beam current; and The sample image is acquired using a sample beam current; wherein the reference beam current is higher than the sample beam current.

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

11. The charged particle evaluation method according to claim 10, wherein generating a new reference image includes: Calculating an average value of the sample image and one of the first reference image and the second reference image, desirably a weighted average value.

12. The charged particle evaluation method according to claim 10 or 11, further comprising repeating the following steps: generating a new reference image; acquiring another sample image; and comparing the another sample image.

13. The charged particle evaluation method according to any one of the preceding claims, 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. A charged particle evaluation device for identifying candidate defects in a sample by scanning a charged particle beam over the sample; the device 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 relatively scanning the sample and the charged particle beam; 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 a sample image from a third region of the sample; and a comparator configured to compare 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 a higher fidelity than the sample image.

15. The charged particle evaluation device according to claim 14, wherein the controller is configured to control the detector unit and the scanning unit to: acquire the first reference image and the second reference image by relatively scanning the sample and the charged particle beam at a reference scanning rate; acquire the sample image by relatively scanning the sample and the charged particle beam at a sample scanning rate; and the reference scanning rate is slower than the sample scanning rate such that the reference image has a higher fidelity than the sample image.

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