Improved edge detection using detector incidence position

Abstract

A system and method for improved edge detection in charged particle beam systems, such as scanning electron microscopes, uses spatial information of the incident positions of charged particle arrival events on a detector surface to determine when an edge feature is detected on a sample. Asymmetry parameters, such as a shift in the center of mass of the distribution of charged particle arrival events, can be used to determine the presence of an edge feature on the sample surface.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to European Patent Application No. 22186346.7, filed July 21, 2022, which is incorporated herein by reference in its entirety.

[0002] TECHNICAL FIELD

[0002] The description herein relates to charged particle detectors that may be useful in the field of charged particle beam systems, and more particularly to systems and methods for detecting edge features using such charged particle beam detectors. [Background technology]

[0003] Detectors can be used to detect physically observable phenomena. For example, a charged particle beam tool such as an electron microscope may include a detector that receives charged particles projected from a sample and outputs a detection signal. The detection signal can be used to reconstruct an image of the sample structure under inspection, for example, in a metrology process, or to reveal defects in the sample. Metrology relates to the precision measurement of sample structures and other miniaturized features. For example, in semiconductor wafers, metrology can include measurements of circuit pattern features such as critical dimensions (the width of the smallest device feature), critical dimension uniformity, line width, overlay, line edge roughness, line end shortening, floor slope, sidewall angle, and other dimensional parameters. A key element in many measurements can involve determining the location of the edge or boundary of a pattern feature. These edge features can correspond to changes in the topography or material properties of the pattern formed on the wafer. Detecting defects in samples is becoming increasingly important in the manufacture of semiconductor devices, which may contain numerous densely packed and miniaturized integrated circuit (IC) components. Inspection systems may be provided for these and other purposes.

[0004]

[0004] As semiconductor devices become increasingly miniaturized, metrology and inspection systems may use increasingly lower beam currents in charged particle beam tools. Existing detection systems may be limited by signal-to-noise ratios (SNRs) and system throughput, especially when beam currents are reduced, for example, to the picoampere range. To improve the SNR and increase the throughput of electron beam inspection systems, electron counting has been proposed, in which the intensity of an incoming electron beam is obtained by counting the number of electrons that reach a detector and then analyzing the frequency of electron arrival events. However, systems operating at increasingly lower landing energies (energy of the primary electrons that strike the sample surface) may require higher electron collection rates to overcome noise in the system. This increases integration times and reduces tool throughput. Summary of the Invention

[0005]

[0005] Embodiments of the present disclosure provide systems and methods for edge detection in charged particle beam processes. Some embodiments of the present disclosure provide a method that includes inspecting a sample surface using a charged particle beam system, obtaining spatial distribution information of detected charged particle arrival positions on a charged particle detector, determining an asymmetry parameter of the spatial distribution information, and determining an edge feature on the sample surface based on the asymmetry parameter.

[0006] In some embodiments, the asymmetry parameter may include a position parameter, which may include a deviation in the center of mass (CoM) of the position of the detected charged particle arrival, the deviation being due to an edge feature.

[0007]

[0007] Some embodiments of the present disclosure provide a method including inspecting a sample surface using a charged particle beam system, obtaining first spatial distribution information of detected charged particle arrival positions on a charged particle detector during a first period of time, obtaining second spatial distribution information of detected charged particle arrival positions on the charged particle detector during a second period of time different from the first period of time, determining performance parameters of the charged particle beam system based on the first spatial distribution information and the second spatial distribution information, and adjusting the charged particle system based on the determined performance parameters.

[0008]

[0008] Some embodiments of the present disclosure provide a charged particle beam method that includes inspecting a sample surface using a charged particle beam system; detecting a plurality of sample pixels within a field of view of the sample, where detecting each sample pixel of the plurality of sample pixels includes detecting a plurality of charged particles emitted from the sample pixel; and determining a map of center of mass deviations of each of the plurality of charged particles emitted from each sample pixel of the plurality of sample pixels.

[0009] Some embodiments provide a non-transitory computer-readable medium storing a set of instructions executable by at least one processor of a device to cause the device to perform the above-described method. Some embodiments provide a charged particle beam device including a controller configured to control the device to perform the above-described method.

[0010] BRIEF DESCRIPTION OF THE DRAWINGS

[0010] 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. [Brief explanation of the drawings]

[0011] [Figure 1] 1 is a diagrammatic representation of an exemplary electron beam inspection (EBI) system consistent with an embodiment of the present disclosure. [Figure 2A]

[0012] FIG. 1 illustrates a charged particle beam device, which may be an example of an electron beam tool, consistent with embodiments of the present disclosure. [Figure 2B]

[0012] FIG. 1 illustrates a charged particle beam device that may be an example of an electron beam tool consistent with an embodiment of the present disclosure. [Figure 2C]

[0012] FIG. 1 illustrates a charged particle beam device that may be an example of an electron beam tool consistent with an embodiment of the present disclosure. [Figure 2D]

[0013] 1 illustrates an electron arrival distribution on an exemplary detector of a charged particle beam device, consistent with embodiments of the present disclosure. [Figure 3A]

[0014] 1 is a diagrammatic representation of an exemplary structure of a detector of a charged particle beam device, consistent with embodiments of the present disclosure. [Figure 3B] 1 is a diagrammatic representation of an exemplary structure of a detector of a charged particle beam device consistent with an embodiment of the present disclosure. [Figure 4A]

[0015] 1 illustrates an exemplary probability distribution of electron landing positions on a detector surface, consistent with embodiments of the present disclosure. [Figure 4B] 1 illustrates an exemplary probability distribution of electron landing positions on a detector surface consistent with embodiments of the present disclosure. [Figure 4C]

[0016] 1 shows an exemplary cross-sectional view of a line and space pattern on a portion of a wafer, consistent with an embodiment of the present disclosure. [Figure 5A]

[0017] 1 illustrates an exemplary electron arrival distribution on a detector surface, consistent with embodiments of the present disclosure. [Figure 5B] 1 illustrates an exemplary electron arrival distribution on a detector surface consistent with embodiments of the present disclosure. [Figure 6A]

[0018] 1 illustrates an exemplary center of mass (CoM) map consistent with embodiments of the present disclosure. [Figure 6B]

[0019] 1 shows an exemplary secondary electron yield map, consistent with embodiments of the present disclosure. [Figure 7A]

[0020] 1 illustrates an exemplary electron arrival distribution on a detector surface, consistent with embodiments of the present disclosure. [Figure 7B] 1 illustrates an exemplary electron arrival distribution on a detector surface consistent with embodiments of the present disclosure. [Figure 8]

[0021] 10 shows an exemplary graph of CoM deviation versus secondary electron arrival number, consistent with an embodiment of the present disclosure. [Figure 9]

[0022] 1 shows a flowchart of an exemplary method for determining edge features in a charged particle beam detection process, consistent with embodiments of the present disclosure. [Figure 10]

[0023] 1 shows a flowchart of an exemplary method for determining edge features in a charged particle beam detection process, consistent with embodiments of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0012]

[0024] Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the drawings. The following description refers to the accompanying drawings, in which like numbers in different drawings represent the same or similar elements unless otherwise stated. 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, systems, and methods consistent with aspects related to the subject matter recited in the appended claims.

[0013]

[0025] Electronic devices are built with circuits formed on a piece of silicon called a substrate. Many circuits can be formed together on the same piece of silicon, called an integrated circuit, or IC. As technology advances, the size of these circuits has dramatically decreased, allowing more circuits to fit on a substrate. For example, an IC chip in a smartphone may be only about the size of a fingernail, yet it can contain over 2 billion transistors, each less than 1 / 1000 the width of a human hair.

[0014]

[0026] Creating these tiny ICs is a time-consuming, complex, and expensive process, often involving hundreds of individual steps. An error in even one step can result in a defect in the finished IC, rendering it useless. Therefore, one of the goals of a manufacturing process is to avoid such defects in order to maximize the number of functioning ICs produced by the process, i.e., to increase the overall yield of the process.

[0015]

[0027] One factor in improving yield is monitoring the chip creation process to ensure that it produces a sufficient number of functioning integrated circuits. One way to monitor the process is to inspect the chip circuit structures at various stages of their formation. Inspection can be done using a scanning electron microscope (SEM). An SEM can be used to image these extremely small structures, in effect taking a "picture" of the structure. The image can be used to determine whether the structure was formed correctly and can also be used to determine whether the structure was formed in the correct location. If the structure is defective, the process can be adjusted to make the defect less likely to recur. To increase throughput (e.g., number of samples processed per hour), it is desirable to perform the inspection as quickly as possible.

[0016]

[0028] An image of a wafer may be formed by scanning one or more primary beams (e.g., "probe" beams) of an SEM system over the wafer and collecting particles (e.g., secondary electrons, or "SEs") generated from the wafer surface with a detector. The secondary electrons may form one or more secondary beams that are directed toward the detector. For each secondary beam, the secondary electrons that reach the detector may generate an electrical signal (e.g., current, charge, voltage, etc.) at the detector. These signals may be output from the detector and processed by an image processor to form an image of the sample. Each pixel of the image may be determined by the energy received at the detector when the primary beam illuminates a corresponding point on the sample surface (sample pixel).

[0017]

[0029] The detection process may involve measuring the magnitude of the electrical signal generated when a large number of electrons land on the detector. Another approach may use electron counting, in which the detector can count individual electron arrival events as they occur. In either approach, the intensity of the secondary beam can be determined based on the electrical signal generated at the detector, which varies proportionally with changes in the intensity of the secondary beam. However, when electron counting is used, each electron that arrives at the detector from the secondary electron beam can be determined individually, and the detection results can be output in digital form. Thus, by analyzing the frequency of electron arrival events, the intensity of the beam can be determined.

[0018]

[0030] Electron counting can help improve the signal-to-noise ratio (SNR) and throughput of charged particle beam systems. For example, pixelated electron counting detectors consist of an array of small detector elements, each capable of independently detecting electrons at its respective location. Electron counting detectors can track the spatial position or arrival time of electrons on the detector to, for example, filter out some electron arrivals as outliers or false positive detections. However, electron counting detectors do not need to retain information about the spatial distribution of secondary electrons on the detector surface. In some comparative embodiments, spatial information, such as the arrival position of secondary electrons on the detector surface, may be lost after the detection is read out to signal processing circuitry. For details about the use of spatial information in electron counting detectors, see, for example, EP 22168912, the entire contents of which are incorporated herein by reference. Therefore, electron counting can be an attractive method for applications such as metrology and overlay inspection, where the beam current (electron flow rate in the beam) is typically low.

[0019]

[0031] SNR can be a concern, especially at low levels of primary beam current. This is because low electron collection efficiency makes the detector more susceptible to random variations in the spatial distribution of electron arrivals on the detector (shot noise). To overcome shot noise and other SNR challenges, a minimum number of secondary electrons are collected per sample pixel to image pattern features with sufficient accuracy. Achieving a minimum number of secondary electron arrivals at each sample pixel imposes a dwell time. That is, the more secondary electrons required, the longer the primary beam may need to illuminate each sample pixel. Therefore, the time required to complete an SEM process is directly affected by the minimum number of secondary electrons required to form an image pixel.

[0020]

[0032] SNR may be an even greater concern when detecting edge features. Edge features can be detected by observing an increase in secondary electrons compared to flat areas of the sample. At low landing energies, this increase is less pronounced and therefore more difficult to distinguish from shot noise. Future SEM metrology tools may have the ability to operate at very low landing energies (the kinetic energy of the primary electrons as they strike the sample). For example, very low landing energies may be required to obtain sufficient contrast in samples with thin resist layers. For such applications, landing energies of, for example, 200 eV, 150 eV, 100 eV, 50 eV, or even lower may be appropriate. This increases the minimum number of secondary electrons required for accurate measurements, which can increase dwell times and impair throughput. Achieving sufficient imaging accuracy with a smaller minimum number of secondary electrons may thereby increase the overall process speed.

[0021]

[0033] Embodiments of the present disclosure provide systems and methods for reducing the minimum number of secondary electrons required to accurately detect edge features, for example, in SEM metrology processes. The systems capture additional information about edge features by, for example, recording the spatial distribution of electron arrivals on an electron counting detector or other pixelated electron detector. This additional information, combined with traditional SEM information, allows edge features to be detected with a lower minimum number of secondary electrons than would otherwise be required.

[0022]

[0034] As the primary beam scans over the sample pixel location, a cluster (distribution) of secondary electron arrivals can be recorded on the detector surface. If the sample pixel location has an edge feature, this cluster can exhibit an asymmetry that can help identify the edge feature. For example, the asymmetry can be a shift in the center of the cluster from where it should be, or a deformation in the cluster shape. This asymmetry can be used as the additional spatial information described above.

[0023]

[0035] The objects and advantages of the present disclosure can be achieved by the elements and combinations as described in the embodiments discussed herein, but no embodiment of the present disclosure is necessary to achieve such exemplary object or advantage, and some embodiments may not achieve any of the described objects or advantages.

[0024]

[0036] Without limiting the scope of the present disclosure, some embodiments may be described in the context of providing detection systems and methods of detection in systems that utilize electron beams ("e-beams"). However, the disclosure is not so limited. Other types of charged particle beams may be applied as well. Moreover, the systems and methods for detection may be used in other imaging systems, such as optical imaging, photon detection, x-ray detection, ion detection, etc.

[0025]

[0037] As used herein, unless specifically stated otherwise, the term "or" includes all possible combinations unless impracticable. For example, if it is stated that a component includes A or B, then the component may include A or B, or A and B, unless specifically stated otherwise or impracticable. As a second example, if it is stated that a component may include A, B, or C, then the component may include A, or B, or C, or A and B, or A and C, or B and C, or A, B, and C, unless specifically stated otherwise or impracticable.

[0026]

[0038] Referring now to FIG. 1 , FIG. 1 illustrates an exemplary electron beam inspection (EBI) system 10 that can be used for wafer inspection consistent with embodiments of the present disclosure. As shown in FIG. 1 , the EBI system 10 includes a main chamber 11, a load / lock chamber 20, an electron beam tool 100 (e.g., a scanning electron microscope (SEM)), and an equipment front-end module (EFEM) 30. The electron beam tool 100 is located within the main chamber 11 and can be used for imaging. The EFEM 30 includes a first load port 30 a and a second load port 30 b. The EFEM 30 may include additional load ports. The first load port 30 a and the second load port 30 b receive wafer front-opening integrated pods (FOUPs) containing wafers (e.g., semiconductor wafers or wafers made of other materials) or samples to be inspected (wafers and samples may be collectively referred to herein as “wafers”).

[0027]

[0039] One or more robot arms (not shown) of the EFEM 30 can transfer wafers to the load / lock chamber 20. The load / lock chamber 20 is connected to a load / lock vacuum pumping system (not shown), which removes gas molecules from the load / lock chamber 20 to reach a first pressure below atmospheric pressure. After the first pressure is reached, one or more robot arms (not shown) can transfer the wafers from the load / lock chamber 20 to the main chamber 11. The main chamber 11 is connected to a main chamber vacuum pumping system (not shown), which removes gas molecules from the main chamber 11 to reach a second pressure below the first pressure. After the second pressure is reached, the wafers are inspected by the electron beam tool 100. The electron beam tool 100 can be a single-beam system or a multi-beam system. A controller 109 is electronically connected to the electron beam tool 100 and can be electronically connected to other components as well. The controller 109 may be a computer configured to perform various controls of the EBI system 10. In Figure 1, the controller 109 is shown as being external to the structure including the main chamber 11, the load / lock chamber 20, and the EFEM 30, but it is understood that the controller 109 may also be part of the structure.

[0028]

[0040] Charged particle beam microscopes, such as those formed by or included in EBI system 10, may be capable of resolution down to the nanometer scale, for example, and may serve as practical tools for inspecting IC components on wafers. Using an e-beam system, electrons from a primary electron beam can be focused at a probe spot on the wafer under inspection. The interaction of the primary electrons with the wafer can form a secondary particle beam. The secondary particle beam can include backscattered electrons, secondary electrons, Auger electrons, or the like, resulting from the interaction of the primary electrons with the wafer. The characteristics (e.g., intensity) of the secondary particle beam can vary based on the internal or external structure or material properties of the wafer, thereby indicating whether the wafer contains defects.

[0029]

[0041] The intensity of the secondary particle beam can be determined using a detector. The secondary particle beam can form a beam spot on the surface of the detector. The detector can generate an electrical signal (e.g., current, charge, voltage, etc.) representing the intensity of the detected secondary particle beam. The electrical signal can be measured by a measurement circuit, which can include additional components (e.g., an analog-to-digital converter) to obtain a distribution of detected electrons. The electron distribution data collected during the detection time window can be combined with corresponding scan path data of the primary electron beam incident on the wafer surface to reconstruct an image of the wafer structure or material under inspection. The reconstructed image can be used to reveal various features of the internal or external structure or material of the wafer, and can be used to reveal defects that may be present in the wafer.

[0030]

[0042] 2A illustrates an example of a charged particle beam device that may be an example of an electron beam tool 100 consistent with embodiments of the present disclosure. The charged particle beam device 200A may be a multi-beam tool that uses multiple beamlets formed from a primary electron beam to simultaneously scan multiple locations on a wafer.

[0031]

[0043] As shown in FIG. 2A , the electron beam tool 200A may include an electron source 202, a gun aperture 204, a condenser lens 206, a primary electron beam 210 emitted from the electron source 202, a source conversion unit 212, multiple beamlets 214, 216, and 218 of the primary electron beam 210, a primary projection optics 220, a wafer stage (not shown in FIG. 2A ), multiple secondary electron beams 236, 238, and 240, a secondary optics 242, and an electron detection device 244. The electron source 202 may generate primary particles, such as electrons, in the primary electron beam 210. A controller, an image processing system, and the like may be coupled to the electron detection device 244. The primary projection optics 220 may include a beam separator 222, a deflection scanning unit 226, and an objective lens 228. The electron detection device 244 may include detection subregions 246, 248, and 250.

[0032]

[0044] The electron source 202, gun aperture 204, condenser lens 206, source conversion unit 212, beam separator 222, deflection scanning unit 226, and objective lens 228 can be aligned with a primary optical axis 260 of apparatus 200A. The secondary optics 242 and electron detection device 244 can be aligned with a secondary optical axis 252 of apparatus 200A.

[0033]

[0045] The electron source 202 may include a cathode, extractor, or anode, and primary electrons may be emitted from the cathode and then extracted or accelerated to form a primary electron beam 210 with a crossover (virtual or real) 208. The primary electron beam 210 may be visualized as being emitted from the crossover 208. The gun aperture 204 may block electrons at the periphery of the primary electron beam 210 to reduce the size of the probe spots 270, 272, 274.

[0034]

[0046] The source conversion unit 212 may include an image-forming element array (not shown in FIG. 2A ) and a beam-limiting aperture array (not shown in FIG. 2A ). Examples of the source conversion unit 212 can be found in U.S. Pat. No. 9,691,586, U.S. Patent Application Publication No. 2017 / 0025243, and International Publication No. WO 2018122176, all of which are incorporated by reference in their entirety. The image-forming element array may include a micro-deflector or a micro-lens array. The image-forming element array may form multiple parallel images (virtual or real) of the crossover 208 using multiple beamlets 214, 216, and 218 of the primary electron beam 210. The beam-limiting aperture array may limit the multiple beamlets 214, 216, and 218.

[0035]

[0047] The condenser lens 206 can focus the primary electron beam 210. The currents of the beamlets 214, 216, and 218 downstream of the source conversion unit 212 can be varied by adjusting the focusing power of the condenser lens 206 or by changing the radial size of the corresponding beam-limiting apertures in the beam-limiting aperture array. The condenser lens 206 can be an adjustable condenser lens that can be configured to move the position of its first principal plane. The adjustable condenser lens can be configured to be magnetic, so that the off-axis beamlets 216 and 218 land on the beamlet-limiting apertures at a rotation angle. The rotation angle varies with the focusing power and the position of the first principal plane of the adjustable condenser lens. In some embodiments, the adjustable condenser lens can be an adjustable anti-rotation condenser lens that includes an anti-rotation lens with a movable first principal plane. Examples of adjustable focusing lenses are further described in U.S. Patent Application Publication No. 2017 / 0025241, which is incorporated by reference herein in its entirety.

[0036]

[0048] The objective lens 228 can focus the beamlets 214, 216, 218 onto the wafer 230 for inspection and can form multiple probe spots 270, 272, 274 on the surface of the wafer 230. Secondary electron beamlets 236, 238, 240 can be formed to emit from the wafer 230 and return towards the beam separator 222.

[0037]

[0049] The beam separator 222 may be a Wien filter-type beam separator that generates an electrostatic dipole field and a magnetic dipole field. In some embodiments, when these fields are applied, the force exerted on the electrons of the beamlets 214, 216, and 218 by the electrostatic dipole field may be equal in magnitude and opposite in direction to the force exerted on the electrons by the magnetic dipole field. Therefore, the beamlets 214, 216, and 218 may pass straight through the beam separator 222 with zero deflection angle. However, the total dispersion of the beamlets 214, 216, and 218 generated by the beam separator 222 may be non-zero. The beam separator 222 may separate the secondary electron beams 236, 238, and 240 from the beamlets 214, 216, and 218 and direct the secondary electron beams 236, 238, and 240 toward the secondary optics 242.

[0038]

[0050] The deflection scanning unit 226 can deflect the beamlets 214, 216, 218 to scan the probe spots 270, 272, 274 across the surface area of the wafer 230. In response to the beamlets 214, 216, 218 impinging on the probe spots 270, 272, 274, secondary electron beams 236, 238, 240 can be emitted from the wafer 230. The secondary electron beams 236, 238, 240 can include electrons with a distribution of energies, including secondary electrons and backscattered electrons. The secondary optics 242 can focus the secondary electron beams 236, 238, 240 onto detection subregions 246, 248, 250 of the electron detection device 244. The detection subregions 246, 248, 250 can be configured to detect the corresponding secondary electron beams 236, 238, 240 and generate corresponding signals used to reconstruct an image of the surface of the wafer 230. The detection sub-regions 246, 248, 250 may comprise separate detector packages, separate sensing elements, or separate regions of an array detector. In some embodiments, each detection sub-region may comprise a single sensing element.

[0039]

[0051] 2B illustrates another example of a charged particle beam apparatus consistent with embodiments of the present disclosure. Electron beam tool 200B (also referred to herein as apparatus 200B) may be an example of electron beam tool 100. Electron beam tool 200B may be similar to electron beam tool 200A shown in FIG. 2A. However, unlike apparatus 200A, apparatus 200B may be a single-beam tool that uses one primary electron beam to scan locations on a wafer one at a time.

[0040]

[0052] 2B, apparatus 200B includes a wafer holder 136 supported by a motorized stage 134 for holding a wafer 150 to be inspected. Electron beam tool 200B includes an electron emitter, which may include a cathode 103, an anode 121, and a gun aperture 122. Electron beam tool 200B further includes a beam-limiting aperture 125, a condenser lens 126, a column aperture 135, an objective lens assembly 132, and a detector 144. Objective lens assembly 132 may be a modified SORIL lens in some embodiments and includes a pole piece 132a, a control electrode 132b, a deflector 132c, and an excitation coil 132d. In the detection or imaging process, an electron beam 161 emanating from the tip of the cathode 103 is accelerated by the voltage on the anode 121, passes through the gun aperture 122, the beam limiting aperture 125, the condenser lens 126, and is focused by a modified SORIL lens to a probe spot 170, which can impinge on the surface of the wafer 150. The probe spot 170 can be scanned across the surface of the wafer 150 by a deflector, such as deflector 132c or other deflectors of a SORIL lens. Secondary or scattered particles (such as secondary electrons or scattered primary electrons emanating from the wafer surface) are collected by a detector 144 to determine the intensity of the beam, so that an image of the area of interest on the wafer 150 can be reconstructed.

[0041]

[0053] It is understood that electron beam tools 200A and 200B may include an image processing system 199, including image acquirer 120, storage 130, and controller 109. Image acquirer 120 may include one or more processors. For example, image acquirer 120 may include a computer, a server, a mainframe host, a terminal, a personal computer, any type of mobile computing device, and the like, or a combination thereof. Image acquirer 120 may be connected to detector 144 of electron beam tool 200B through a medium such as electrical conductors, fiber optic cables, portable storage media, IR, Bluetooth, the Internet, a wireless network, a wireless radio, or a combination thereof. Image acquirer 120 may receive signals from detector 144 and construct an image. Thus, image acquirer 120 may acquire an image of wafer 150. Image acquirer 120 may also perform various post-processing functions, such as image averaging, contouring, overlaying indicators on acquired images, and the like. The image acquirer 120 can be configured to perform adjustments such as brightness and contrast of the acquired image. The storage 130 can be a storage medium such as a hard disk, random access memory (RAM), cloud storage, other types of computer-readable memory, and the like. The storage 130 can be coupled to the image acquirer 120 and used to store raw scanned image data as original images or post-processed images. The image acquirer 120 and the storage 130 can be connected to the controller 109. In some embodiments, the image acquirer 120, the storage 130, and the controller 109 can be integrated together as a single electronic control unit.

[0042]

[0054] In some embodiments, the image acquirer 120 can acquire one or more images of the sample based on an imaging signal received from the detector 144. The imaging signal can correspond to a scanning motion to perform charged particle imaging. The acquired image can be a single image including multiple imaging areas that can include various features of the wafer 150. The single image can be stored in the storage 130. The imaging can be performed based on imaging frames.

[0043]

[0055] The collection and illumination optics of an electron beam tool can include or be supplemented by electromagnetic quadrupole electron lenses. For example, as shown in FIG. 2B , electron beam tool 100B can include a first quadrupole lens 148 and a second quadrupole lens 158. In some embodiments, the quadrupole lenses can be used to control the electron beam. For example, first quadrupole lens 148 can be controlled to adjust the beam current, and second quadrupole lens 158 can be controlled to adjust the beam spot size and beam shape.

[0044]

[0056] In some embodiments of the present disclosure, a PIN detector may be used as an in-lens detector in a deceleration objective SEM column of the EBI system 10. The PIN detector may be positioned between a cathode for generating an electron beam and the objective lens. The electron beam emitted from the cathode may be charged to a potential of −BE keV (typically, about −10 kV). Electrons in the electron beam may be immediately accelerated and travel through the column, which may be at ground potential. Thus, electrons may travel with a kinetic energy of BE keV while passing through the aperture 145 of the detector 144. Electrons passing through an objective lens pole piece, such as pole piece 132a of the objective lens assembly 132 in FIG. 2B, may be rapidly decelerated to a landing energy of LE keV because the potential at the wafer surface may be set to −(BE-LE) keV.

[0045]

[0057] FIG. 2C illustrates an example of a charged particle beam device 200C consistent with embodiments of the present disclosure. The charged particle beam device 200C may be, for example, the charged particle beam device 200A of FIG. 2A or the charged particle beam device 200B of FIG. 2B. Emitted electrons 171, including secondary electrons or backscattered electrons, are emitted from the wafer surface by impingement of electrons from the primary electron beam 105. A deceleration field, which may slow the primary electrons as they approach the probe spot 170, may act as an acceleration field, accelerating the emitted electrons backward toward the surface of the PIN detector 144. For example, as shown in FIG. 2C, interaction with the wafer 150 at the probe spot 170 may generate emitted electrons 171 moving backward toward the detector 144. The emitted electrons 171 from the wafer surface moving along the optical axis 105 may arrive at the surface of the detector 144 at a distribution of positions. The landing locations of the emitted electrons may be within a generally circular region having a radius of several millimeters or more, such as 5 mm, 10 mm, or 20 mm or more. The geometric spread may increase, for example, as the landing energy increases. The geometric spread of the landing locations of the emitted electrons may be due to electrons having different trajectories, which may depend, for example, on the initial kinetic energy and emission angle of the electrons. Other factors may also affect the geometric spread or other characteristics of the landing locations.

[0046]

[0058] FIG. 2D shows an example of an emitted electron landing spot distribution on the detector surface. While electrons 171a may generally be mostly concentrated around the center of the detector 144 in the absence of a deflection field, they may also land at different points on the detector 144 surface. As discussed above, the emitted electrons may include, for example, secondary electrons or backscattered electrons. In some embodiments, the distribution may include, for example, 60-85% secondary electrons and 40-15% backscattered electrons. The landing spot distribution may shift depending on the emission location and the SEM deflection field (e.g., scanning field). Thus, in some applications, if a specific field of view (FOV) of the SEM image is required, the required size of the in-lens PIN detector may be substantially large. Typically, the detector may be, for example, 10 mm or larger in diameter. In some embodiments, the detector may be, for example, approximately 4-10 mm in diameter.

[0047]

[0059] The detector 144 may be positioned along the optical axis 105. The primary electron beam may be configured to travel along the optical axis 105. Thus, the detector 144 may include a hole 145 in its center to allow the primary electron beam to pass through and reach the wafer 150. FIGS. 2B-2C show examples of a detector 144 having an aperture in its center. However, some embodiments may use a detector positioned off-axis with respect to the optical axis along which the primary electron beam travels. For example, as in the example shown in FIG. 2A, a beam separator 222 may be provided to direct the emitted electron beam toward the off-axis detector. The beam separator 222 may be configured to redirect the emitted electron beam by an angle α toward the electron detection device 244, as shown in FIG. 2A. Thus, in some embodiments of the present disclosure, a detector without a central aperture may be provided.

[0048]

[0060] Detector 244 of FIG. 2A or detector 144 of FIGS. 2B-2D may include a sensing element, such as a diode or a diode-like element, capable of converting incident energy into a measurable signal. For example, the sensing element in the detector may include a SPAD, APD, scintillator, or PIN diode. Although sensing elements may be represented as diodes throughout this disclosure, sensing elements or other components may deviate from the ideal circuit behavior of electrical elements such as diodes, resistors, and capacitors. In embodiments of the present disclosure, a detector in a charged particle beam system may include a pixelated array of multiple sensing elements. In some embodiments, the sensing elements may be configured for charged particle counting. Detector sensing elements that may be useful for charged particle counting are discussed in U.S. Patent Application Publication No. 2019 / 0378682, which is incorporated by reference in its entirety.

[0049]

[0061] To avoid ambiguity and facilitate explanation, some descriptions herein use electrons as an example. However, it should be noted that any charged particle may be used in any embodiment of the present disclosure, without being limited to electrons. For example, a radiation source of a charged particle beam tool may emit one or more charged particles, such as electrons, protons, ions, muons, or any other particle carrying an electric charge. Furthermore, some embodiments of the present disclosure may use photons, such as light in the visible, UV, DUV, EUV, X-ray, or any other wavelength range, instead of charged particles. Thus, although detectors in the present disclosure may be disclosed for detecting electrons, some embodiments of the present disclosure may be directed to detecting other charged particles or photons.

[0050]

[0062] 3A-3B show exemplary structures of pixelated electronic detectors consistent with embodiments of the present disclosure. A detector, such as detector 344a in FIG. 3A or detector 344b in FIG. 3B, may be implemented as detector 244 as shown in FIG. 2A or detector 144 as shown in FIGS. 2B-2D. In FIG. 3A, detector 344a includes a sensor layer 301 and a signal processing layer 302. Sensor layer 301 may include a sensor die configured with multiple sensing elements, including sensing elements 311, 312, 313, and 314. In some embodiments, the multiple sensing elements may be implemented in an array of sensing elements, and each sensing element may have a uniform size, shape, and arrangement.

[0051]

[0063] The signal processing layer 302 may include multiple signal processing circuits, including circuits 321, 322, 323, and 324. The circuits may include interconnects (e.g., wiring paths) configured to communicatively couple the sensing elements. Each sensing element in the sensor layer 301 may have a corresponding signal processing circuit in the signal processing layer 302. The sensing elements and their corresponding circuits may be configured to operate independently. As shown in FIG. 3A , circuits 321, 322, 323, and 324 may be configured to communicatively couple to the outputs of sensing elements 311, 312, 313, and 314, respectively, as indicated by the four dashed lines between the sensor layer 301 and the signal processing layer 302.

[0052]

[0064] In some embodiments, the signal processing layer 302 may be configured as a single die with multiple circuits disposed thereon. The sensor layer 301 and the signal processing layer 302 may be in direct contact. In some embodiments, components and functionality of different layers may be combined or omitted. For example, the signal processing layer 302 may be combined with the sensor layer 301 into a single layer. Furthermore, the circuitry for charged particle counting may be integrated in various locations of the detector, for example, in a separate readout layer of the detector or on a separate chip. Further details of the electronic counting circuitry, as well as alternative structures for the sensor layer 301 and the signal processing layer 302, can be found in WO 2022 / 008518, which is incorporated herein by reference in its entirety.

[0053]

[0065] As shown in FIG. 3B, a detector 344b may be provided having an array of sensing elements 311. Detector 344b may be a pixelated electron detector, such as a pixelated electron counting detector. Detector 344b may include a sensor layer 301 and a signal processing layer 302, as seen in FIG. 3A. The detector circuitry may include separate electron counting circuits for each sensing element. Detector 344b may include a plate 351 on which multiple sensing elements 311 are formed. Plate 351 may include an opening 345 to allow the primary electron beam to pass through plate 351.

[0054]

[0066] Individual electron counting can be achieved when the individual sensing elements 311 of a detector are made small compared to the geometric extent of the emitted electrons incident on the detector. For example, each sensing element can have its own counting unit including circuitry configured to measure the output signal from the sensing element. Making the sensing elements smaller reduces the electron arrival rate at each sensing element, which can enable electron counting at each sensing element. Furthermore, the capacitance of a detector can be proportional to the area of the detector surface. Some noise sources, such as those due to components coupled to the detector (e.g., amplifiers), can be related to capacitance. The small area of the individual elements in a pixelated electron counting detector allows for much lower capacitance than, for example, a large continuous sensing surface. For example, the individual sensing elements can be square or other shapes, with dimensions of, for example, 5 μm, 10 μm, 25 μm, 50 μm, 100 μm, 200 μm, or 300 μm on a side. The sensing elements can also be larger, for example, on the order of millimeters. A typical detector may include, for example, 100, 500, 1,000, 5,000, 10,000, 50,000, or 100,000 or more sensing elements.

[0055]

[0067] Some charged particle beam processes, such as high-resolution SEM, require very low primary beam currents (e.g., down to 40 pA) and high operating speeds (e.g., 400 megapixels per second). Such low primary beam currents can result in a very small arrival rate of emitted electrons at the detector, which can result in long dwell times required to reach a sufficient number of electrons for an accurate reading. For example, the entire detector can only record one electron event per clock cycle (2.5 ns = 1 / 400 MHz). Therefore, high operating speeds may not be possible when a large number of emitted electrons is required.

[0056]

[0068] Additionally, this low primary beam current can make it increasingly difficult to overcome shot noise and other noise sources. Shot noise can refer to the stochastic nature of the spatial and temporal distribution of electron arrivals on the detector surface. Each electron landing event can occur on the detector surface with some probability. For example, in a simple situation, the probability of an electron arrival occurring at the center of the detector can be high, decreasing as the distance from the center increases. In addition, the number of electrons detected during a given period of time also varies according to a probability function. When a sufficiently large number of electrons are collected over a sufficient period of time, the random fluctuations in the spatial and temporal distribution tend to average out, and an expected distribution of electron arrival events emerges. However, when only a small number of electrons are collected, this averaging cannot occur, and the electron arrival distribution is unlikely to reflect the expected distribution.

[0057]

[0069] Another noise source can be dark current, which can cause false detections even in the absence of incident illumination. Dark current can arise due to defects in the material forming the detector, such as imperfections in the crystalline structure of the sensing diode. The term "dark" current can refer to the fact that current fluctuations are unrelated to incoming electrons, yet can be interpreted as arrival events. Various noise sources, such as dark current, thermal energy, and external radiation, can cause unintended current fluctuations in the detector output. Dark current and noise sources can generate signals at locations on the detector where the probability of recording an actual electron arrival event is low.

[0058]

[0070] Shot noise issues can be particularly problematic when attempting to detect edge features in low beam current configurations. In comparative embodiments, the presence of an edge feature can be inferred, at least in part, by observing an increase in emitted electrons as the primary beam scans over the edge of a pattern feature. However, this increase may not be as dramatic at low beam currents. Therefore, more emitted electrons may need to be collected to distinguish signal from noise. As an example, a conventional SEM tool may require a minimum collection rate in the range of, for example, 40-70, 70-100, 100-150, or more electrons per sample pixel at the expected edge feature location. As discussed above, this higher collection rate can adversely affect operating speed.

[0059]

[0071] Embodiments of the present disclosure utilize additional information collected during the detection process to more efficiently characterize pattern features. In particular, the use of spatial information of electron arrival on the detector can help detect edge features with fewer electrons than required in comparative embodiments. In some embodiments of the present disclosure, the spatial information includes asymmetry information. The asymmetry information can include a measured shift in the position of the emitted electron arrival distribution, which can be used to determine the edge feature corresponding to the measured shift. The spatial information can be combined with other information to determine the presence of an edge feature. For example, the spatial information can be combined with an emitted electron yield map.

[0060]

[0072] 4A-4B show two simulated arrival event distributions 444 on a charged particle detector (e.g., detector 144 of FIGS. 2A-2D and detectors 344a and 344b of FIGS. 3A-3B) consistent with embodiments of the present disclosure. The arrival events may be, for example, emitted electron arrivals, and the charged particle detector may be an electron detector, such as a pixelated electron-counting detector. The scale to the right of each distribution is a logarithmic gray-tone scale of the probability of an electron arrival event at each detector pixel. White or light-colored pixels indicate a high probability of electron arrival, while dark pixels indicate a low or zero probability. Note that in the figures, the dark pixel in the center indicates a hole in the detector, similar to primary beam hole 345 of FIG. 3; at a hole, no arrival event can occur and therefore the probability is zero. While such a hole may not be present in all embodiments of a charged particle detector, it serves as a useful visual reference point for the shifts shown in FIGS. 4A-4B.

[0061]

[0073] FIG. 4C illustrates a cross-sectional view of pattern features 432 / 433 on a portion of a sample 430 undergoing a charged particle beam process, such as SEM scanning, consistent with embodiments of the present disclosure. The sample 430 may be, for example, a semiconductor wafer having integrated circuit pattern features. The pattern features may include a series of alternating lines 431 and spaces 433 extending perpendicular to the plane of the page. An edge 432 may be found at the interface between each line 431 and each space 433. Flat regions of the surface topography, such as the top surfaces of the lines 431 or spaces 433, may be scanned as flat sample pixels Pf. Transitional topography may be scanned as edge sample pixels Pe.

[0062]

[0074] FIG. 4A illustrates an arrival distribution for one of the flat sample pixels Pf of FIG. 4C, for example, consistent with an embodiment of the present disclosure. This distribution may have a substantially symmetric shape and be centered on the surface of the detector 444. Such a characteristic may indicate that the location of the sample pixel has a substantially flat topography. The term "centered" may refer, for example, to the centroid or geometric center of the distribution of arrival events (or the probability of arrival events). The center may be, for example, a weighted spatial average of the arrival events, or it may exclude outliers. This spatial center of arrival may be similar to the center of mass (CoM) of a group of point objects and thus may be referred to herein as the CoM of the emitted electron arrival distribution. In FIG. 4A, the CoM of the emitted electron arrival distribution is centered on the detector for the flat sample pixel Pf.

[0063]

[0075] Note that the "centered" detector characteristic of Figure 4A may be affected by other known parameters of the charged particle beam process. For example, the primary electron beam in a scanning process may be deflected two-dimensionally to scan across the entire field of view (FoV) of the sample. The primary beam may be deflected to scan in a line-by-line, zigzag, or serpentine fashion across, for example, a rectangular FoV. This scanning may result in a primary beam spot at each sample pixel location within the FoV. Due to the deflection, the primary beam may not necessarily strike the sample surface at normal incidence. This may result in a shift or deformation of the arrival distribution of emitted electrons on the detector surface. Aberrations from the lens system may also contribute to the shift and deformation. Thus, rather than having a CoM at the center of the detector surface, the arrival distribution of a flat topography may have a CoM at an expected location on the detector surface after considering common known parameters such as scan deflection. Additionally, the symmetry shown in Figure 4A may be deformed as expected given these same known parameters. Thus, as discussed further below, a shift or deformation in the emitted electron arrival distribution may be a shift or deformation from an expected location and expected shape, respectively. For example, the deviation of the CoM of an edge sample pixel may be a deviation from the CoM expected if the sample pixel had a flat topography. A shift, deformation, or other spatial change from an expected parameter may be referred to as an asymmetry parameter, which may be due to the presence of an edge feature at the sample pixel.

[0064]

[0076] There are also fixed parameters associated with charged particle beam systems that can affect the location and distribution of electron arrival events on the detector surface, such as electrodes, landing energy, and detector height. Deflection electrodes, focusing electrodes, or Wien filters can affect the location or shape of the electron distribution. The voltage on the deflector electrodes can affect the emittance of electrons as they travel from the sample toward the detector. Focusing electrodes of separate detector branches (such as 242 in FIG. 2A) can also affect the location or shape. Wien filters may also be used to offset incident electrons from the center of the detector, for example, to minimize electron losses through the primary beam hole. As mentioned above, the geometric spread of electron arrivals can similarly increase with increasing landing energy. Additionally, increasing detector height results in a greater spread of electrons for a given emittance value.

[0065]

[0077] FIG. 4B shows the emitted electron arrival distribution for the right edge sample pixel Pe of FIG. 4C , consistent with an embodiment of the present disclosure. The presence of an edge feature at the edge sample pixel Pe introduces an asymmetry parameter into the distribution. In FIG. 4B , the CoM of the distribution has shifted away from its expected location at the detector center, and the shape of the distribution is slightly skewed toward the upper right corner. For example, the distribution shown may correspond to the edge sample pixel Pe on the right edge of line 431, as shown in FIG. 4C . The distribution corresponding to the left edge sample pixel Pe may exhibit a similar asymmetry shift in a different direction on the detector surface, e.g., to the left or diagonally in the opposite direction. Such asymmetry parameters on the detector surface can be utilized in charged particle beam processes to determine that a sample pixel contains an edge feature.

[0066]

[0078] In general, an asymmetry parameter, such as a first CoM deviation, may shift to one side of the detector surface as a first edge feature is scanned. The CoM deviation may then return to a zero or center position as a flat region is scanned past the edge. Then, as a second (opposite) edge region is scanned, a second CoM deviation may appear on the detector, shifted in the opposite direction from the first CoM deviation. The orientation of the CoM deviation on the detector surface may be used to gain further knowledge about the sample topography, such as to distinguish between lines and spaces in a CoM map by determining whether an edge represents the beginning or end of such a line / space.

[0067]

[0079] 4A-4B show a large number of emitted electron arrivals for illustrative purposes. In some embodiments of the present disclosure, the number of emitted electron arrivals collected for a given sample pixel may be much smaller.

[0068]

[0080] Additionally, a sample pixel may be the summation of one or more short electron collection periods or frames to yield sufficient information about the pixel. For example, a single frame may include, for example, 0 to 100 detected electron arrival events. A summation may include, for example, 2 to 200 frames. In some embodiments of the present disclosure, a sample pixel may include, for example, 25 to several hundred or more detected electron arrival events. However, at low beam currents, collection rates may be at the low end of these ranges.

[0069]

[0081] 5A-5B illustrate principles similar to those illustrated in FIGS. 4A-4B for the surface of an exemplary detector 544 (e.g., detector 144 of FIGS. 2A-2D and detectors 344a and 344b of FIGS. 3A-3B) in low beam current applications consistent with embodiments of the present disclosure. In FIG. 5A, a small number of emitted electron arrivals 571a are collected on the detector surface 544 for a flat topography, such as flat sample pixel Pf of FIG. 4C. The CoM of the distribution of emitted electron arrivals 571a is located substantially at the center of the detector 544, which is indicated by the central primary beam hole. As previously mentioned, this hole may not exist in some detectors. FIG. 5B illustrates the distribution of emitted electron arrivals 571b for an edge sample pixel, such as Pe of FIG. 4C, where the CoM is offset from the center of the detector by a displacement d. Additionally, the shape of the distribution of emitted electron arrivals 571b is distorted relative to the distribution shown in FIG. 5A. Finally, the number of emitted electron arrivals 571b for edge sample pixel Pe is greater than the number of emitted electron arrivals 571a for flat sample pixel Pf.

[0070]

[0082] Asymmetry parameters, such as the CoM deviation (or shape deformation) at each sample pixel within the FoV, can be compiled into a CoM map, as shown in FIG. 6A. Each point on the CoM map (i.e., map pixel) corresponds to a sample pixel within the FoV. Thus, each map pixel represents the emitted electron distribution on the detector surface for one sample pixel, such as the distributions shown in FIGS. 5A-5B. A darker map pixel indicates a larger CoM deviation from the detector center (e.g., FIG. 5B). A brighter map pixel indicates a smaller CoM deviation from the detector center (e.g., FIG. 5A).

[0071]

[0083] The CoM map of Figure 6A can be obtained from an inspection of the line and space topography, as shown in Figure 6C, where each line of the CoM map corresponds to a vertical edge 632 at the transition between a line 631 and a space 633.

[0072]

[0084] The continuous background color of the CoM map becomes gradually darker as one moves away from the center of the FoV. This low spatial frequency variation in the CoM map across the FoV may be due to known parameters such as lens aberrations and beam scanning deflection, as discussed above. However, the CoM map also reveals high spatial frequency components in the form of a series of vertical lines. This regularly spaced CoM deviation may be due to or caused by an edge 632 in a line and space pattern (similar to edge 432 in FIG. 4C). Edge 632 may be identified by a controller, such as controller 109 in FIGS. 1 and 2B. For example, the controller may identify pattern edge 632 by applying a contour fitting algorithm to the CoM map in combination with predetermined information, such as pattern layout data.

[0073]

[0085] Instead of the CoM deviation, the CoM map may represent another parameter, such as the shape of the emitted electron distribution or other asymmetry parameters. Alternatively, the CoM map of FIG. 6A may only convey the magnitude of the deviation and not other information, such as the direction of the deviation, although such additional information may be encoded on the CoM map. As a visual example, a medium gray value may represent zero deviation, pixels darker than medium indicate deviation in a first (e.g., negative) direction, and pixels lighter than medium indicate deviation in a second (e.g., positive) direction. The map may be color-coded to indicate additional directional or shape information, for example. Furthermore, the CoM map need not be embodied as a visual indicator at all. In general, the CoM map may be a representation of CoM parameters (such as CoM deviation and shape) for a group of sample pixels within an area (such as the FoV of the charged particle beam, the system, a single die on a wafer, an entire wafer, or another sample).

[0074]

[0086] As a further alternative to the CoM map shown in FIG. 6A, an aberration-corrected CoM map may be derived. For example, a CoM map may be created in which the background aberration components of FIG. 6A are subtracted from the map or otherwise compensated for or accounted for. In such cases, the CoM values may not represent deviations from the center of the detector, but rather deviations from the expected position on the detector given such aberration factors. In either case, the objective may be to determine deviations due to edge features rather than other factors.

[0075]

[0087] As mentioned above, spatial parameters of the electron arrival distribution are not the only indicator of edge features. As the primary beam spot scans over edge features on the sample, the number of emitted electrons received on the detector surface may also increase. The number of emitted electron arrivals may be recorded at each sample pixel within the FoV to generate an emitted electron yield map such as that shown in FIG. 6B. Here, darker map pixels on the yield map correspond to sample pixels where a higher number of emitted electrons were collected on the detector surface (e.g., FIG. 5B). Brighter map pixels on the yield map indicate that a lower number of emitted electrons were collected on the detector surface (e.g., FIG. 5A).

[0076]

[0088] The uniform background color of the yield map indicates that the average emitted electron collection over flat topography within the FoV is substantially constant. However, this uniformity, compared to the continuously varying background of FIG. 6A , is shown for illustrative purposes only. In reality, a greater degree of non-uniformity in emitted electron yield may exist. Similar to the CoM map, the yield map reveals a series of vertical lines with discernible increases in emitted electron yield. These lines may correspond to the same edges 632 of the line and space pattern in FIG. 6A . A controller (e.g., controller 109) may identify edge features by applying a contour fitting algorithm to the yield map in a manner similar to the CoM map described above.

[0077]

[0089] In comparative embodiments, the yield map of FIG. 6B may be the primary indicator of edge features. For example, in comparative embodiments, the difference in spatial distribution between emitted electron arrivals 571a and 571b in FIGS. 5A-5B may not be recorded, and information may be lost during signal readout. In such cases, edge features may be resolved primarily based on the difference in the number of electron arrivals obtained at each sample pixel. Due to this limited information, the minimum number of emitted electrons required to achieve adequate contrast may be greater than the minimum number required if a CoM map were also available.

[0078]

[0090] In some embodiments of the present disclosure, the minimum number of emitted electrons can be reduced by deriving both a CoM map and an emitted electron yield map for the same FoV. The two maps can be compared to each other or otherwise combined to provide more information about the edge feature 632. For example, the two maps can be added, averaged, weighted, scaled, or the like to provide information about the edge feature 632. The two maps can be combined to form a combined map. Alternatively, the first of the two maps can be used to fill in areas of low confidence in the second of the two maps. Using both maps can allow edge features to be detected with a smaller minimum number of emitted electrons. This smaller minimum number results in a shorter dwell time at each sample pixel, thereby increasing the throughput of charged particle beam processes without sacrificing accuracy. For example, if the minimum required number of electron arrivals in a low beam current application could be reduced from, for example, 100 to 75, it would represent a 25% increase in throughput.

[0079]

[0091] In some embodiments of the present disclosure, the detector may be configured to determine not only the location of individual electron arrival events, but also the energy of the arrival events. For example, each sensing element may be configured to generate a signal proportional to the energy of the electron arrival. This information may be further used to derive an energy-weighted CoM map by assigning weighting coefficients to individual arrival events.

[0080]

[0092] The spatial information can also be utilized to determine aberrations or other system parameters that can be used later to better analyze the results of the emitted electron yield map. In such cases, the CoM map is not directly combined with the emitted electron yield map, but instead may be used to determine system parameters for calculating corrections or adjustments to the emitted electron yield map. The reverse is also possible, where the yield map can be used to determine corrections for the CoM map.

[0081]

[0093] For example, to monitor system drift, a CoM map can be used to characterize the low spatial frequency components of CoM deviations. Low spatial frequency CoM variations remain substantially unchanged across multiple (similar) FoVs because they represent system, not sample, characteristics. Therefore, system stability can be monitored by comparing low spatial frequency CoM variations across multiple scanned FoVs. Multiple FoVs may be scanned sequentially. Alternatively, FoVs from different regions may be compared based on expected similarities, such as similar pattern data or other parameters. By comparing CoM information from a first FoV acquired during a first period with CoM information from a second FoV acquired during a second period, system performance parameters (e.g., lens aberrations, beam conditions, scanning conditions) can be monitored and corrected. Feedforward or feedback corrections can be applied to the system in real time based on this comparison.

[0082]

[0094] Additionally, the above disclosure is made with reference to a single distribution of emitted electron arrival for a single emitted electron beam having only one CoM deviation. However, embodiments of the present disclosure may be applicable to multi-beam configurations, such as multi-beam tool 200A of FIG. 2A. In such cases, there may be multiple emitted electron arrival distributions on multiple different detectors or multiple different regions of a single detector, each distribution having a distinct CoM deviation. Additionally, in such cases, references to the "center" of the detector above may instead refer to the center of the detector region on which one of the individual distributions of emitted electron arrival is incident.

[0083]

[0095] In addition to pixelated electron detectors, spatial information may be obtained using segmented detectors. For example, the detector surface may be segmented into two halves, four quadrants, etc. By detecting the signal difference between one segment and another, the CoM deviation can be determined. FIGS. 7A-7B illustrate this principle using the same distribution as shown in FIGS. 4A-4B on a segmented detector 744, consistent with an embodiment of the present disclosure. The segmented detector 744 includes four quadrants: A, B, C, and D. Each quadrant outputs a signal proportional to the sum of the electron arrivals occurring within that quadrant. Thus, even when individual arrival events cannot be distinguished, the segmented detector is still configured to obtain sufficient spatial information about the electron arrivals to determine the CoM deviation by finding the difference between the quadrants.

[0084]

[0096] For example, the controller can determine the difference between quadrant B and quadrant C (BC), or measure the difference between the two halves: (B+D)-(A+C). The difference between any pair of segments or all pairs can be determined. For flat sample pixels, such as those shown in FIG. 7A, the results of these subtractions will be low or zero due to the symmetry of electron arrival. However, the distribution of edge sample pixels, such as in FIG. 7B, will result in both the magnitude and direction of CoM deviation. The results for each sample pixel can be compiled into a CoM map and a yield map, as described above with respect to FIGS. 6A-6C.

[0085]

[0097] FIG. 8 shows a schematic diagram of an experimental graph of CoM deviation (in mm) of emitted electron arrival on a detector, consistent with an embodiment of the present disclosure. The detector may be, for example, approximately 4-10 mm in diameter. The graph shows CoM deviation for both edge and flat regions of the sample for a range of electron arrivals up to 250°. The deviation shown may represent a component of the total deviation, such as a horizontal or vertical component, or it may represent the total deviation. The deviation may be from the center of the detector. Alternatively, it may represent deviation from the expected position when considering system parameters other than topography, such as beam deflection and lens aberrations. The zero mark on the ordinate axis indicates a reference point for CoM deviation, such as the center of the detector. The ordinate axis extends from zero in both positive and negative directions. However, either the positive or negative direction simply indicates the magnitude of the distance from the zero mark.

[0086]

[0098] The graph in Figure 8 shows consistent CoM differences between the edge and flat regions of the sample starting from the first data point of approximately 25 electron arrival events. At this level, the CoM of emitted electron arrivals on the edge region is approximately 0.3 mm from zero, while the CoM of the flat region is offset by approximately 0.1 mm. The 50 arrival mark shows a large difference in the CoM of the edge region, consistent with the uncertainty associated with a small number of electron arrivals. However, even with this variation, a clear difference exists between the edge and flat topography. As the number of arrivals increases, the edge / flat CoM values diverge from each other, confirming the relationship between detector surface topography and CoM deviation. However, even with a small number of arrivals, such as 25 or 50, the CoM map can be used to distinguish between edge features and flat portions of the sample surface.

[0087]

[0099] 9 shows a flowchart of an exemplary method 900 for determining edge features on a sample surface using a charged particle detector, consistent with embodiments of the present disclosure. The charged particle detector may be part of a charged particle beam device. For example, the charged particle beam detector may be a pixelated electron-counting detector of an SEM used for scanning inspection of samples such as semiconductor wafers. The method may be performed by a processor and memory of a controller configured to control the charged particle beam device to perform the method.

[0088]

[0100] In step 910, a charged particle detector detects a plurality of charged particles on the surface. The detector may be, for example, detector 244 of Figure 2A, detector 144 of Figures 2B-2D, detector 344a of Figure 3A, detector 344b of Figure 3B, or detector 544 of Figures 5A-5B.

[0089]

[0101] In step 920, the controller acquires spatial distribution information of detected charged particle landing positions on the surface of the charged particle detector for a plurality of sample pixels within the FoV of the sample surface. For example, the spatial distribution information may include landing positions of a plurality of emitted electrons on the detector surface. The detector may be configured to individually determine the energy of each emitted electron landing, in which case the spatial distribution information may include an energy-weighted distribution.

[0090]

[0102] In step 930, the spatial distribution information can be used to determine an asymmetry parameter. For example, the asymmetry parameter can be the deviation of the shape of the spatial distribution of emitted electron arrival events on the detector surface. The asymmetry parameter can be the deviation of the CoM of the spatial distribution from the center of the detector or from the center of the beam spot area of a multi-beam detector. Alternatively, the asymmetry parameter can be the deviation of the CoM of the spatial distribution from the expected location on the detector when considering, for example, beam deflection, lens aberrations, or other system parameters. The CoM can include the centroid or geometric center of the distribution of electron arrival events, or a weighted spatial average of the arrival events. The CoM can include the centroid or geometric center of a subset of emitted electron arrivals excluding outliers or potential false positives. The asymmetry parameter can include a CoM map of the asymmetry parameter across the FoV of the charged particle beam device. The CoM map can include, for example, a CoM map such as that shown in FIG. 6A.

[0091]

[0103] In step 940, edge features on the sample surface are determined based on the asymmetry parameters. For example, a contour fitting algorithm may be applied to the CoM map in combination with predetermined information, such as pattern layout data. The edge features may be used in the metrology process to determine metrology parameters, for example, critical dimension, critical dimension uniformity, line width, overlay, line edge roughness, line end shortening, floor slope, sidewall angle, and other dimensional parameters.

[0092]

[0104] FIG. 10 shows a flowchart of an exemplary method 1000 for determining edge features of a sample surface using a charged particle detector, consistent with embodiments of the present disclosure. The charged particle detector may be part of a charged particle beam device. For example, the charged particle beam detector may be a pixelated electron detector, such as a pixelated electron counting detector in an SEM used for scanning inspection of samples such as semiconductor wafers. The method may be performed by a processor and memory of a controller configured to control the charged particle beam device to implement the method. Steps 1010-1030 may correspond to steps 910-930 of method 900 above. Step 1040 may correspond to a modified version of step 940 of method 900 above. Method 1000 further includes the following additional steps:

[0093]

[0105] After the charged particles are detected at the detector surface in step 1010, in step 1025 the controller obtains charged particle count information for a number of sample pixels within the FoV of the sample surface.

[0094]

[0106] In step 1035, a yield parameter of the charged particle count information is obtained. For example, the yield parameter may be an emitted electron yield map. The emitted electron yield map may be, for example, the yield map of FIG. 6B.

[0095]

[0107] In step 1040, edge features of the sample surface are determined based on the yield parameters obtained in step 1035 and the asymmetry parameters obtained in step 1030. For example, a contour fitting algorithm may be applied separately to the CoM map and the emitted electron yield map in combination with predetermined information such as pattern layout data. The edge features may be used in the metrology process to determine metrology parameters, for example. The metrology parameters may include, for example, critical dimension, critical dimension uniformity, line width, overlay, line edge roughness, line end shortening, floor slope, sidewall angle, and other dimensional parameters.

[0096]

[0108] A non-transitory computer-readable medium may be provided that stores instructions for a processor of a controller (e.g., controller 109 of FIG. 1 ) for determining edge features (such as the techniques illustrated above in FIGS. 4A-9 ) in embodiments of the present disclosure. For example, the instructions stored on the non-transitory computer-readable medium may be executed by circuitry of the controller to implement method 900 or 1000, in part or in whole. Common forms of non-transitory medium include, for example, a floppy disk, a flexible disk, a hard disk, a solid-state drive, a magnetic tape or any other magnetic data storage medium, a compact disk read-only memory (CD-ROM), any other optical data storage medium, any physical medium having a pattern of holes, random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), flash EPROM or any other flash memory, non-volatile random access memory (NVRAM), cache, registers, any other memory chip or cartridge, and network-connected versions thereof.

[0097]

[0109] The embodiments may be further described using the following clauses. 1. A non-transitory computer-readable medium storing a set of instructions executable by at least one processor of a device to cause the device to perform a method comprising: Inspecting a surface of a sample using a charged particle beam system; Obtaining spatial distribution information of the positions of arrival of the detected charged particles on the charged particle detector; determining an asymmetry parameter of the spatial distribution information; determining an edge feature on the sample surface based on the asymmetry parameter; 1. A non-transitory computer-readable medium, comprising: 2. The non-transitory computer-readable medium of clause 1, wherein the asymmetry parameter comprises a position parameter of a position of the detected charged particle arrival on the charged particle detector. 3. The non-transitory computer-readable medium of clause 2, wherein the position parameters include a deviation in the center of mass (CoM) of the position of the detected charged particle arrival, the deviation being attributable to an edge feature. 4. The non-transitory computer-readable medium of clause 1, wherein the asymmetry parameters include shape parameters of the positions of the detected charged particle arrivals on the charged particle detector. 5. The non-transitory computer-readable medium of clause 4, wherein the shape parameters include deviations in the shape of the detected charged particle arrival positions on the charged particle detector, the deviations being due to edge features. 6. A set of instructions executable by at least one processor comprising: and further causing the device to determine a CoM map based on the asymmetry parameters of the positions of the detected charged particle arrivals; 10. The non-transitory computer-readable medium of claim 1, wherein determining the edge features is based on a CoM map. 7. A set of instructions executable by at least one processor comprising: Obtaining yield information of the detected charged particle arrivals; determining a yield parameter of the detected charged particle arrivals based on the yield information; and further configuring the device to perform 10. The non-transitory computer-readable medium of clause 1, wherein determining the edge feature is based on both a yield parameter and an asymmetry parameter. 8. The non-transitory computer-readable medium of clause 7, wherein the yield parameters include a charged particle yield map. 9. The non-transitory computer-readable medium of clause 7, wherein the asymmetry parameters include a CoM map. 10. The non-transitory computer-readable medium of clause 1, wherein the spatial distribution information comprises fewer than 120 locations of detected charged particle arrivals. 11. The non-transitory computer-readable medium of clause 10, wherein the spatial distribution information comprises fewer than 50 locations of detected charged particle arrivals. 12. The non-transitory computer-readable medium of clause 1, wherein the charged particle detector is an electron detector. 13. The non-transitory computer-readable medium of clause 12, wherein the electronic detector is one of a four-quadrant segmented detector, a two-half segmented detector, and a pixelated electronic counting detector. 14. The non-transitory computer-readable medium of clause 1, wherein the charged particle beam device comprises a scanning electron microscope. 15. A method for determining edge features on a sample surface, comprising: Inspecting a surface of a sample using a charged particle beam system; Obtaining spatial distribution information of the positions of arrival of the detected charged particles on the charged particle detector; determining an asymmetry parameter of the spatial distribution information; determining an edge feature on the sample surface based on the asymmetry parameter; A method comprising: 16. The method of clause 15, wherein the asymmetry parameter comprises a position parameter of the position of the detected charged particle arrival on the charged particle detector. 17. The method of clause 16, wherein the position parameters include deviations in CoM of the positions of detected charged particle arrivals, the deviations being attributable to edge features. 18. The method of clause 15, wherein the asymmetry parameter comprises a shape parameter of the position of the detected charged particle arrival on the charged particle detector. 19. The method of clause 18, wherein the shape parameters include deviations in the shape of the detected charged particle arrival positions on the charged particle detector, the deviations being due to edge features. 20. Further comprising determining a CoM map based on the asymmetry parameters of the positions of the detected charged particle arrivals; 16. The method of clause 15, wherein determining edge features is based on a CoM map. 21. Obtaining yield information of detected charged particle arrivals; determining a yield parameter of the detected charged particle arrivals; Further comprising: 16. The method of clause 15, wherein determining the edge feature is based on both a yield parameter and an asymmetry parameter. 22. The method of clause 21, wherein the yield parameters include a charged particle yield map. 23. The method of clause 21, wherein the asymmetry parameters include a CoM map. 24. The method of clause 15, wherein the spatial distribution information comprises fewer than 120 positions of detected charged particle arrivals. 25. The method of clause 24, wherein the spatial distribution information comprises fewer than 50 locations of detected charged particle arrivals. 26. The method of clause 15, wherein the charged particle detector is one of an electron detector or a proton detector. 27. The method of clause 26, wherein the electronic detector is one of a four-quadrant segmented detector, a two-equal segmented detector, and a pixelated electronic counting detector. 28. The method of clause 15, wherein the charged particle beam device comprises a scanning electron microscope. 29. A charged particle beam source configured to generate a primary charged particle beam; an optical system configured to direct the primary charged particle beam to a sample surface for inspecting the sample surface; a charged particle detector configured to detect a spatial distribution of the detected charged particles returned from the sample surface; A controller including one or more processors, Obtaining spatial distribution information of the positions of arrival of the detected charged particles on the charged particle detector; determining an asymmetry parameter of the spatial distribution information; determining an edge feature on the sample surface based on the asymmetry parameter; a controller configured to cause the charged particle beam device to perform 1. A charged particle beam device comprising: 30. Charged particle beam device according to clause 29, wherein the asymmetry parameter comprises a position parameter of the position of the detected charged particle arrival on the charged particle detector. 31. A charged particle beam device according to clause 30, wherein the position parameters include deviations in CoM of the positions of detected charged particle arrivals, the deviations being attributable to edge features. 32. Charged particle beam device according to clause 29, wherein the asymmetry parameters include shape parameters of the positions of detected charged particle arrivals on the charged particle detector. 33. A charged particle beam device according to clause 32, wherein the shape parameters include deviations in the shape of the detected positions of the charged particle arrivals on the charged particle detector, the deviations being due to edge features. 34. The controller and further configured to cause the charged particle beam device to determine a CoM map based on the asymmetry parameters of the detected charged particle arrival positions; 30. The charged particle beam device of clause 29, wherein determining the edge features is based on a CoM map. 35. The controller Obtaining yield information of the detected charged particle arrivals; determining a yield parameter of the detected charged particle arrivals; and further configured to cause the charged particle beam device to perform 30. The charged particle beam device of clause 29, wherein determining the edge feature is based on both a yield parameter and an asymmetry parameter. 36. A charged particle beam device according to clause 35, wherein the yield parameters include a charged particle yield map. 37. A charged particle beam device according to clause 35, wherein the asymmetry parameters include a CoM map. 38. A charged particle beam device according to clause 29, wherein the spatial distribution information comprises fewer than 120 positions of detected charged particle arrivals. 39. A charged particle beam device according to clause 38, wherein the spatial distribution information comprises fewer than 50 positions of detected charged particle arrivals. 40. A charged particle beam device according to clause 29, wherein the charged particle detector is one of an electron detector or a proton detector. 41. A charged particle beam device according to clause 40, wherein the electron detector is one of a four-quadrant segmented detector, a two-equal segmented detector, and a pixelated electron counting detector. 42. A charged particle beam device according to clause 29, wherein the charged particle beam device comprises a scanning electron microscope. 43. A non-transitory computer-readable medium storing a set of instructions executable by at least one processor of a device to cause the device to perform a method comprising: Inspecting a surface of a sample using a charged particle beam system; acquiring first spatial distribution information of positions of detected charged particle arrivals on the charged particle detector during a first time period; acquiring second spatial distribution information of the detected charged particle arrival positions on the charged particle detector during a second time period different from the first time period; determining a performance parameter of the charged particle beam system based on the first spatial distribution information and the second spatial distribution information; adjusting the charged particle system based on the determined performance parameters; 1. A non-transitory computer-readable medium, comprising: 44. Inspecting a sample surface using a charged particle beam system; acquiring first spatial distribution information of positions of detected charged particle arrivals on the charged particle detector during a first time period; acquiring second spatial distribution information of the detected charged particle arrival positions on the charged particle detector during a second time period different from the first time period; determining a performance parameter of the charged particle beam system based on the first spatial distribution information and the second spatial distribution information; adjusting the charged particle system based on the determined performance parameters; A charged particle beam method comprising: 45. A charged particle beam source configured to generate a primary charged particle beam; an optical system configured to direct the primary charged particle beam to a sample surface for inspecting the sample surface; a charged particle detector configured to detect a spatial distribution of the detected charged particles returned from the sample surface; A controller including one or more processors, acquiring first spatial distribution information of positions of detected charged particle arrivals on the charged particle detector during a first time period; acquiring second spatial distribution information of the detected charged particle arrival positions on the charged particle detector during a second time period different from the first time period; determining a performance parameter of the charged particle beam system based on the first spatial distribution information and the second spatial distribution information; adjusting the charged particle system based on the determined performance parameters; a controller configured to cause the charged particle beam device to perform 1. A charged particle beam device comprising: 46. A non-transitory computer-readable medium storing a set of instructions executable by at least one processor of a device to cause the device to perform the following method, the method comprising: Inspecting a surface of a sample using a charged particle beam system; detecting a plurality of sample pixels within a field of view of the sample, wherein detecting each sample pixel of the plurality of sample pixels includes detecting a plurality of charged particles emitted from the sample pixel; determining a map of center of mass deviations of each of the plurality of charged particles emitted from each sample pixel of the plurality of sample pixels; 1. A non-transitory computer-readable medium, comprising: 47. Inspecting a sample surface using a charged particle beam system; detecting a plurality of sample pixels within a field of view of the sample, wherein detecting each sample pixel of the plurality of sample pixels includes detecting a plurality of charged particles emitted from the sample pixel; determining a map of center of mass deviations of each of the plurality of charged particles emitted from each sample pixel of the plurality of sample pixels; A charged particle beam method comprising: 48. A charged particle beam source configured to generate a primary charged particle beam; an optical system configured to direct the primary charged particle beam to a sample surface for inspecting the sample surface; a charged particle detector configured to detect charged particles returned from the sample surface; one or more processors; and detecting a plurality of sample pixels within a field of view of the sample, wherein detecting each sample pixel of the plurality of sample pixels includes detecting a plurality of charged particles emitted from the sample pixel; determining a map of center of mass deviations of each of the plurality of charged particles emitted from each sample pixel of the plurality of sample pixels; a controller configured to cause the charged particle beam device to perform 1. A charged particle beam device comprising:

[0098]

[0110] Some embodiments of the present disclosure have been described with respect to an electron beam system, such as an SEM, having an electron detector for detecting electron arrival. However, the present disclosure is not limited thereto. It should be understood that the above-disclosed embodiments may be applicable to other systems, such as other non-SEM electron beam systems or non-electron-based charged particle beam systems. It should also be understood that other charged particles or other classes of electrons are contemplated within the scope of the present disclosure.

[0099]

[0111] The block diagrams in the figures may illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer hardware or software products according to various exemplary embodiments of the present disclosure. In this regard, each block in the schematic diagrams may represent an arithmetic or logical operation that can be implemented using hardware, such as electronic circuits. A block may also represent a module, segment, or portion of code that includes one or more executable instructions for implementing the specified logical function(s). It should be understood that in some alternative implementations, the functions shown in the blocks may occur out of the order depicted in the figures. For example, two blocks shown in succession may be executed or performed substantially simultaneously, or the two blocks may be executed in the reverse order, depending on the functionality involved. Some blocks may also be omitted. It should also be understood that each block and block k of the block diagrams can be implemented by a special-purpose hardware-based system that performs the specified functions or acts, or by a combination of special-purpose hardware and computer instructions.

[0100]

[0112] It will be understood that embodiments of the present disclosure are not limited to the exact structures described above and illustrated in the accompanying drawings, and that various modifications and variations can be made without departing from the scope thereof. For example, a charged particle inspection system may be just one example of a charged particle beam system consistent with embodiments of the present disclosure.

Claims

1. 1. A non-transitory computer-readable medium storing a set of instructions executable by at least one processor of a device to cause the device to perform a method comprising: Inspecting a surface of a sample using a charged particle beam system; Obtaining spatial distribution information of the positions of the detected charged particle arrivals on the charged particle detector; determining an asymmetry parameter of the spatial distribution information; determining edge features on the sample surface based on the asymmetry parameters; and 1. A non-transitory computer-readable medium, comprising:

2. The non-transitory computer-readable medium of claim 1 , wherein the asymmetry parameter comprises a position parameter of a position of the detected charged particle arrival on the charged particle detector.

3. the position parameters include deviations of the center of mass (CoM) of the detected charged particle arrival positions; The non-transitory computer-readable medium of claim 2 , wherein the deviation is due to the edge feature.

4. The non-transitory computer-readable medium of claim 1 , wherein the asymmetry parameter comprises a shape parameter of a position of the detected charged particle arrival on the charged particle detector.

5. the shape parameters include deviations in shape of the detected charged particle arrival positions on the charged particle detector; The non-transitory computer-readable medium of claim 4 , wherein the deviation is due to the edge feature.

6. the set of instructions executable by the at least one processor: and further causing the device to determine a CoM map based on the asymmetry parameter of the detected charged particle arrival positions; The non-transitory computer-readable medium of claim 1 , wherein determining the edge features is based on the CoM map.

7. the set of instructions executable by the at least one processor: Obtaining yield information of the detected charged particle arrivals; determining a yield parameter of the detected charged particle arrivals based on the yield information; and further configuring the device to perform The non-transitory computer-readable medium of claim 1 , wherein determining the edge feature is based on both the yield parameter and the asymmetry parameter.

8. The non-transitory computer-readable medium of claim 7 , wherein the yield parameters include a charged particle yield map.

9. The non-transitory computer-readable medium of claim 7 , wherein the asymmetry parameters include a CoM map.

10. The non-transitory computer-readable medium of claim 1 , wherein the spatial distribution information comprises fewer than 120 positions of detected charged particle arrivals.

11. The non-transitory computer-readable medium of claim 10 , wherein the spatial distribution information comprises fewer than 50 locations of detected charged particle arrivals.

12. The non-transitory computer-readable medium of claim 1 , wherein the charged particle detector is an electron detector.

13. 13. The non-transitory computer-readable medium of claim 12, wherein the electronic detector is one of a four-quadrant segmented detector, a two-equal segmented detector, and a pixelated electronic counting detector.

14. The non-transitory computer-readable medium of claim 1 , wherein the charged particle beam device comprises a scanning electron microscope.

15. 1. A method for determining edge features on a sample surface, comprising: Inspecting the sample surface using a charged particle beam system; Obtaining spatial distribution information of the positions of arrival of the detected charged particles on the charged particle detector; determining an asymmetry parameter of the spatial distribution information; determining edge features on the sample surface based on the asymmetry parameters; and A method comprising:

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