Enhanced edge detection using detector incident position

Abstract

Systems and methods for enhanced edge detection in a charged particle beam system, such as a scanning electron microscope. The method uses spatial information of the position of incidence of charged particle arrival events on the detector surface to determine when an edge feature is detected on the sample. An asymmetric parameter, such as a centroid offset of a charged particle arrival event distribution, may be used to determine the presence of an edge feature on a sample surface.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to European application 22186346.7, filed on July 21, 2022 and incorporated herein by reference in its entirety. Technical Field

[0003] The description herein relates to charged particle detectors that may be used 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 Art

[0004] Detectors can be used to sense physically observable phenomena. For example, a charged particle beam tool (such as an electron microscope) can 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 with inspection, and can be used, for example, in a metrology process or to reveal defects in a sample. Metrology involves the precise measurement of sample structures and other micro features. For example, in a semiconductor wafer, metrology can include the measurement of circuit pattern features, such as critical dimensions (the width of the smallest device feature), critical dimension uniformity, line width, overlap, line edge roughness, line end shortening, bottom surface tilt, sidewall angle and other dimensional parameters. Many key elements in the measurement may involve determining the position of the edge or boundary of the pattern feature. These edge features may correspond to changes in the morphology or material properties of the pattern formed on the wafer. In the manufacture of semiconductor devices that may include a large number of densely packaged micro integrated circuit (IC) components, it is also increasingly important to detect defects in samples. Inspection systems can be provided for these and other purposes.

[0005] As semiconductor devices continue to miniaturize, metrology and inspection systems may use lower and lower beam currents in charged particle beam tools. Existing detection systems may be limited by system throughput and signal-to-noise ratio (SNR), especially when the beam current is reduced to, for example, the picoampere range. Electron counting has been proposed to enhance the SNR and increase throughput in electron beam inspection systems, where the intensity of the incoming electron beam is obtained by counting the number of electrons arriving at the detector and then analyzing the frequency of electron arrival events. However, systems operating at lower and lower landing energies (the energy of the primary electrons that strike the sample surface) may require higher electron collection rates to overcome the noise in the system. This results in increased integration times and reduced tool throughput. Summary of the invention

[0006] Embodiments of the present disclosure provide systems and methods for edge detection in charged particle beam processing. Some embodiments of the present disclosure provide a method, including: inspecting a sample surface using a charged particle beam system; obtaining spatial distribution information of the detected charged particle arrival positions on a charged particle detector; determining an asymmetry parameter of the spatial distribution information; and determining edge features on the sample surface based on the asymmetry parameter.

[0007] In some embodiments, the asymmetry parameter may include a localization parameter.The localization parameter may include a deviation of the center of mass (CoM) of the detected charged particle arrival position caused by the edge feature.

[0008] 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 arrival positions of charged particles detected on a charged particle detector within a first time period; obtaining second spatial distribution information of arrival positions of charged particles detected on the charged particle detector within a second time period different from the first time period; determining performance parameters of the charged particle beam system based on the first spatial distribution information and the second spatial distribution information; and performing adjustments to the charged particle system based on the determined performance parameters.

[0009] Some embodiments of the present disclosure provide a charged particle beam method, comprising: 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 of the plurality of sample pixels comprises detecting a plurality of charged particles emitted from the sample pixel; and determining a center of mass deviation map of each of the plurality of charged particles emitted from each of the plurality of sample pixels.

[0010] Some embodiments provide a non-transitory computer readable medium storing an instruction set executable by at least one processor of a device to cause the device to perform the above method. Some embodiments provide a charged particle beam apparatus including a controller configured to control the apparatus to perform the above method. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The above and other aspects of the present disclosure will become more apparent from the description of exemplary embodiments with reference to the attached drawings.

[0012] Figure 1 is a schematic diagram of an exemplary electron beam inspection (EBI) system consistent with embodiments of the present disclosure.

[0013] Figure 2A-2C is a schematic diagram illustrating a charged particle beam apparatus consistent with embodiments of the present disclosure, which may be an example of an electron beam tool.

[0014] Figure 2DAn exemplary electron arrival distribution on a detector in a charged particle beam apparatus consistent with embodiments of the present disclosure is illustrated.

[0015] Figure 3A-3B is a schematic diagram of an exemplary structure of a detector in a charged particle beam apparatus consistent with an embodiment of the present disclosure.

[0016] Figure 4A-4B An example probability distribution of electron arrival locations on a detector surface consistent with embodiments of the present disclosure is illustrated.

[0017] Figure 4C Illustrated are example cross-sectional views of line and space patterns on a portion of a wafer consistent with embodiments of the present disclosure.

[0018] Figure 5A-Figure 5B An example of an electron arrival distribution on a detector surface consistent with an embodiment of the present disclosure is illustrated.

[0019] Fig. 6A An example center of mass (CoM) diagram consistent with embodiments of the present disclosure is illustrated.

[0020] Figure 6B An example secondary electron yield graph consistent with embodiments of the present disclosure is illustrated.

[0021] Figure 7A-7B An example of an electron arrival distribution on a detector surface consistent with an embodiment of the present disclosure is illustrated.

[0022] Figure 8 An example graph of CoM deviation versus number of secondary electron arrivals consistent with embodiments of the present disclosure is illustrated.

[0023] Fig. 9 A flow chart illustrating an example method for determining edge features during detection of a charged particle beam consistent with embodiments of the present disclosure is illustrated.

[0024] Fig.10 A flow chart illustrating an example method for determining edge features during detection of a charged particle beam consistent with embodiments of the present disclosure is illustrated. DETAILED DESCRIPTION

[0025] Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. The following description refers to the accompanying drawings, wherein, unless otherwise specified, the same numerals in different drawings represent the same or similar elements. The implementations set forth in the following description of the exemplary embodiments do not represent all implementations consistent with the present invention. Instead, they are merely examples of devices, systems, and methods consistent with various aspects related to the subject matter that may be recited in the appended claims.

[0026] Electronic devices consist of circuits formed on a silicon chip called a substrate. Many circuits can be formed together on the same silicon chip and are called an integrated circuit or IC. As technology has advanced, the size of these circuits has been significantly reduced so that many of them can be mounted on a substrate. For example, an IC chip in a smartphone can be as small as a fingernail and can also include more than 2 billion transistors, each of which is less than 1 / 1000 the size of a human hair.

[0027] Manufacturing these extremely small ICs is a complex, time-consuming and expensive process that typically involves hundreds of individual steps. An error in even one step can result in a defect in the finished IC, rendering it useless. Therefore, one goal of the manufacturing process is to avoid such defects in order to maximize the number of functional ICs manufactured in the process, i.e., to increase the overall yield of the process.

[0028] An integral part of improving yield is monitoring the chip manufacturing process to ensure that a sufficient number of functional integrated circuits are produced. One way to monitor the process is to inspect the chip circuit structures at various stages of their formation. Inspections can be performed using a scanning electron microscope (SEM). The 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 correctly shaped and whether it was formed in the correct location. If the structure is defective, the process can be adjusted so that the defect is less likely to occur again. In order to increase throughput (e.g., the number of samples processed per hour), it is desirable to perform inspections as quickly as possible.

[0029] An image of a wafer can be formed by scanning one or more primary beams (e.g., "probe" beams) of a SEM system across the wafer and collecting particles (e.g., secondary electrons or "SEs") generated from the wafer surface at a detector. The secondary electrons can form one or more secondary beams directed toward the detector. For each secondary beam, the secondary electrons reaching the detector may cause an electrical signal (e.g., current, charge, voltage, etc.) to be generated in the detector. These signals can be output from the detector and can be processed by an image processor to form an image of the sample. Each pixel of the image can be determined by the energy received at the detector when the primary beam illuminates a corresponding point on the sample surface (sample pixel).

[0030] Sometimes, the detection process involves measuring the amplitude of the electrical signal generated when a large number of electrons land on the detector. In another approach, electron counting can be used, where 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 in the detector, which changes in proportion to the change in the intensity of the secondary beam. However, using electron counting, each electron that reaches the detector from the secondary electron beam can be individually determined, and the detection results can be output in digital form. Therefore, the intensity of the beam can be determined by analyzing the frequency of electron arrival events.

[0031] Electron counting may help improve the throughput and signal-to-noise ratio (SNR) of charged particle beam systems. For example, a pixelated electron counting detector consists of an array of small sensing elements, each of which can independently detect electrons at its own position. The electron counting detector can track the spatial position or arrival time of electrons on the detector, so as to, for example, filter some electron arrivals as outliers or false positive detections. However, it is not necessary for the electron counting detector to retain any information about the spatial distribution of secondary electrons on the detector surface. In some comparative embodiments, after the detection is read out to the signal processing circuit, spatial information such as the arrival position of secondary electrons on the detector surface may be lost. For more information on the spatial information of the electron counting detector, see, for example, EP22168912, which is incorporated herein by reference in its entirety. Therefore, electron counting may be an attractive method in applications such as metrology and overlap inspection, where the beam current (the rate of electron flow in the beam) is typically low.

[0032] SNR can be an issue, especially at low primary beam current levels. This is because low electron collection rates are more susceptible to random fluctuations in the spatial distribution of electron arrivals on the detector (shot noise). To overcome shot noise and other SNR issues, a certain number of secondary electrons are collected for each sample pixel in order to image pattern features with sufficient accuracy. A certain dwell time is required to achieve the minimum number of secondary electrons arriving at each sample pixel, i.e., the more secondary electrons are required, the longer the primary beam needs to illuminate each sample pixel. Therefore, the amount of time required to complete the SEM process is directly affected by the minimum number of secondary electrons required to form an image pixel.

[0033] SNR can be a bigger issue 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 noticeable and is therefore more difficult to distinguish from shot noise. Future SEM metrology tools may be able to operate with very low landing energies (the kinetic energy of the primary electron when it hits the sample). For example, in samples with thin resist layers, very low landing energies may be required to achieve sufficient contrast. For such applications, landing energies of, for example, 200eV, 150eV, 100eV, 50eV, or lower may be appropriate. This may increase the minimum number of secondary electrons required for accurate measurement, resulting in longer dwell times and compromising throughput. Achieving sufficient imaging accuracy with a lower minimum number of secondary electrons can therefore increase the speed of the entire process.

[0034] Embodiments of the present disclosure provide a system and method for reducing the minimum number of secondary electrons required to accurately detect edge features in, for example, SEM metrology processes. The system captures additional information about edge features by recording the spatial distribution of electron arrivals on, for example, an electron counting detector or other pixelated electron detector. This additional information can be combined with conventional SEM information to detect edge features with a lower minimum number of secondary electrons than would otherwise be required.

[0035] As the primary beam scans the sample pixel location, the clusters (distributions) of secondary electron arrivals can be recorded at the detector surface. If the sample pixel location has edge features, the clusters can show asymmetry, which can help identify the edge features. For example, the asymmetry may be a shift in the center of the cluster from where it originally was, or it may be a deformation of the cluster shape. This asymmetry can then be used as additional spatial information as discussed above.

[0036] The objects and advantages of the present disclosure can be achieved by the elements and combinations set forth in the embodiments discussed herein. However, the embodiments of the present disclosure do not necessarily need to achieve such exemplary objects or advantages, and some embodiments may not achieve any of the objects or advantages.

[0037] Without limiting the scope of the present disclosure, some embodiments may be described in the context of providing detection systems and detection methods in systems utilizing an electron beam ("e-beam"). However, the present disclosure is not so limited. Other types of charged particle beams may be similarly applied. In addition, the detection systems and methods may be used in other imaging systems, such as optical imaging, photon detection, X-ray detection, ion detection, and the like.

[0038] As used herein, unless otherwise specifically stated, the term "or" encompasses all possible combinations unless not feasible. For example, if a component is described as including A or B, then, unless otherwise specifically stated or not feasible, the component may include A or B, or A and B. As a second example, if a component is described as including A, B, or C, then, unless otherwise specifically stated or not feasible, 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.

[0039] Now to Figure 1 Reference is made to , which illustrates an exemplary electron beam inspection (EBI) system 10 that may be used for wafer inspection consistent with embodiments of the present disclosure. Figure 1 As shown in , 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 in the main chamber 11 and can be used for imaging. The EFEM 30 includes a first loading port 30a and a second loading port 30b. The EFEM 30 may include additional loading ports. The first loading port 30a and the second loading port 30b receive a wafer front opening transport box (FOUP), which contains a wafer to be inspected (e.g., a semiconductor wafer or a wafer made of other materials) or a sample (wafers and samples may be collectively referred to as "wafers" in this article).

[0040] One or more robotic arms (not shown) in the EFEM 30 can transfer the wafer to the load / lock chamber 20. The load / lock chamber 20 is connected to a load / lock vacuum pump system (not shown), which removes gas molecules in the load / lock chamber 20 to reach a first pressure lower than atmospheric pressure. After reaching the first pressure, one or more robotic arms (not shown) can transfer the wafer from the load / lock chamber 20 to the main chamber 11. The main chamber 11 is connected to a main chamber vacuum pump system (not shown), which removes gas molecules in the main chamber 11 to reach a second pressure lower than the first pressure. After reaching the second pressure, the wafer will be inspected by the electron beam tool 100. The electron beam tool 100 can be a single beam system or a multi-beam system. The controller 109 is electrically connected to the electron beam tool 100 and can also be electrically connected to other components. The controller 109 can be a computer configured to perform various controls of the EBI system 10. Although the controller 109 is Figure 1 1 is shown as being outside the structure including the main chamber 11, the load / lock chamber 20 and the EFEM 30, but it should be understood that the controller 109 can be a part of the structure.

[0041] Charged particle beam microscope (such as formed by EBI system 10 or can be included in the charged particle beam microscope of EBI system 10) can have resolution as low as nanometer level, for example, and can be used as a practical tool for checking IC components on wafer.Using e-beam system, the electrons of primary electron beam can be focused on the detection spot on the wafer being inspected.The interaction of primary electron and wafer can cause secondary particle beam to be formed.Secondary particle beam can include backscattered electrons, secondary electrons or Auger (Auger) electrons etc. produced by the interaction of primary electron and wafer.The characteristic (such as intensity) of secondary particle beam can change based on the property of internal or external structure or material of wafer, therefore can indicate whether wafer includes defect.

[0042] Detectors can be used to determine the intensity of secondary particle beams. Secondary particle beams can form beam spots on the surface of detectors. Detectors can generate electrical signals (such as electric current, charge, voltage, etc.) representing the intensity of detected secondary particle beams. Electrical signals can be measured using a measurement circuit system, which can include other components (such as analog-to-digital converters) to obtain the distribution of detected electrons. The electronic distribution data collected during the detection time window is combined with the corresponding scan path data of the primary electron beam incident on the wafer surface, and can be used to reconstruct the image of the wafer structure or material being inspected. The reconstructed image can be used to reveal the various features of the internal or external structure or material of the wafer, and can be used to reveal defects that may exist in the wafer.

[0043] Figure 2A An example of a charged particle beam apparatus consistent with embodiments of the present disclosure is illustrated, which may be an example of an electron beam tool 100. The charged particle beam apparatus 200A may be a multi-beam tool that simultaneously scans multiple locations on a wafer using multiple beamlets formed from a primary electron beam.

[0044] like Figure 2A As shown in FIG. 1 , the electron beam tool 200A may include an electron source 202, a gun hole 204, a focusing lens 206, a primary electron beam 210 emitted from the electron source 202, a source conversion unit 212, a plurality of sub-beams 214, 216 and 218 of the primary electron beam 210, a primary projection optical system 220, a wafer stage ( Figure 2A ), a plurality of secondary electron beams 236, 238 and 240, a secondary optical system 242 and an electron detection device 244. The electron source 202 can generate primary particles, such as electrons of the primary electron beam 210. A controller, an image processing system, etc. can be coupled to the electron detection device 244. The primary projection optical system 220 can include a beam splitter 222, a deflection scanning unit 226 and an objective lens 228. The electron detection device 244 can include detection sub-areas 246, 248 and 250.

[0045] Electron source 202, gun aperture 204, condenser lens 206, source conversion unit 212, beam splitter 222, deflection scanning unit 226 and objective lens 228 can be aligned with the primary optical axis 260 of apparatus 200A. Secondary optical system 242 and electron detection device 244 can be aligned with the secondary optical axis 252 of apparatus 200A.

[0046] The electron source 202 may include a cathode, an extractor, or an anode, where primary electrons may be emitted from the cathode and extracted or accelerated to form a primary electron beam 210 having an intersection point (virtual or real image) 208. The primary electron beam 210 may be visualized as being emitted from the intersection point 208. The gun aperture 204 may block peripheral electrons of the primary electron beam 210 to reduce the size of the detection spots 270, 272, and 274.

[0047] The source conversion unit 212 may include an image forming element array ( Figure 2A not shown) and the beam limiting aperture array ( Figure 2A 216 and 218). An example of the source conversion unit 212 can be found in U.S. Patent No. 9,691,586; U.S. Publication No. 2017 / 0025243; and International Publication No. WO / 2018122176, all of which are incorporated herein by reference in their entirety. The array of image forming elements may include an array of microdeflectors or microlenses. The array of image forming elements may form multiple parallel images (virtual or real images) of the intersection 208 and the multiple sub-beams 214, 216, and 218 of the primary electron beam 210. The array of beam limiting apertures may limit the multiple sub-beams 214, 216, and 218.

[0048] The condenser lens 206 can focus the primary electron beam 210. The current of the sub-beams 214, 216 and 218 downstream of the source conversion unit 212 can be changed by adjusting the focusing ability of the condenser lens 206 or by changing the radial size of the corresponding beam limiting holes in the beam limiting hole array. The condenser lens 206 can be an adjustable condenser lens, which can be configured so that the position of its first principal plane is movable. The adjustable condenser lens can be configured to be magnetic, which can cause the off-axis sub-beams 216 and 218 to land on the sub-beam limiting holes at a rotation angle. The rotation angle varies with the position and focusing ability 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, which involves an anti-rotation lens with a movable first principal plane. Examples of adjustable condenser lenses are further described in U.S. Publication No. 2017 / 0025241, which is incorporated herein by reference in its entirety.

[0049] Objective lens 228 can focus beamlets 214, 216, and 218 onto wafer 230 for inspection and can form a plurality of detection spots 270, 272, and 274 on the surface of wafer 230. Secondary electron beamlets 236, 238, and 240 emitted from wafer 230 and returned to beam splitter 222 can be formed.

[0050] The beam splitter 222 may be a Wien filter type beam splitter that generates an electrostatic dipole field and a magnetic dipole field. In some embodiments, if they are applied, the force applied by the electrostatic dipole field to the electrons of the sub-beams 214, 216, and 218 may be equal in magnitude and opposite in direction to the force applied by the magnetic dipole field to the electrons. Therefore, the sub-beams 214, 216, and 218 may pass straight through the beam splitter 222 with a zero deflection angle. However, the total dispersion of the sub-beams 214, 216, and 218 generated by the beam splitter 222 may also be non-zero. The beam splitter 222 may separate the secondary electron beams 236, 238, and 240 from the sub-beams 214, 216, and 218 and direct the secondary electron beams 236, 238, and 240 toward the secondary optical system 242.

[0051] The deflection scanning unit 226 can deflect the sub-beams 214, 216 and 218 to scan the detection spots 270, 272 and 274 over the area on the surface of the wafer 230. In response to the incidence of the sub-beams 214, 216 and 218 at the detection spots 270, 272 and 274, secondary electron beams 236, 238 and 240 can be emitted from the wafer 230. The secondary electron beams 236, 238 and 240 can include electrons with energy distribution, including secondary electrons and backscattered electrons. The secondary optical system 242 can focus the secondary electron beams 236, 238 and 240 onto the detection sub-areas 246, 248 and 250 of the electron detection device 244. The detection sub-areas 246, 248 and 250 can be configured to detect the corresponding secondary electron beams 236, 238 and 240 and generate corresponding signals used to reconstruct the surface image of the wafer 230. Detection sub-regions 246, 248, and 250 may include separate detector packets, separate sensing elements, or separate regions of an array detector. In some embodiments, each detection sub-region may include a single sensing element.

[0052] Figure 2B 200B (also referred to herein as apparatus 200B) may be an example of an electron beam tool 100. The electron beam tool 200B may be similar to Figure 2A However, unlike the apparatus 200A, the apparatus 200B may be a single beam tool that uses one primary electron beam to scan one location on the wafer at a time.

[0053] like Figure 2B As shown in , the apparatus 200B includes a wafer holder 136 supported by a motorized stage 134 to fix a wafer 150 to be inspected. The electron beam tool 200B includes an electron emitter, which may include a cathode 103, an anode 121, and a gun hole 122. The electron beam tool 200B also includes a beam limiting hole 125, a focusing lens 126, a column hole 135, an objective lens assembly 132, and a detector 144. In some embodiments, the objective lens assembly 132 may be a modified SORIL lens, which includes a pole piece 132a, a control electrode 132b, a deflector 132c, and an excitation coil 132d. During the detection or imaging process, the electron beam 161 emitted from the tip of the cathode 103 may be accelerated by the anode 121 voltage, pass through the gun hole 122, the beam limiting hole 125, the focusing lens 126, and be focused into a detection spot 170 by the modified SORIL lens, and impact the surface of the wafer 150. The detection spot 170 can be scanned by a deflector (such as deflector 132c or other deflectors in a SORIL lens) across the surface of the wafer 150. The detector 144 can collect secondary or scattered particles (e.g., secondary electrons or scattered primary electrons) emitted from the wafer surface to determine the intensity of the beam so that an image of a region of interest on the wafer 150 can be reconstructed.

[0054] It should be understood that the electron beam tools 200A and 200B may include an image processing system 199, which includes an image acquisition device 120, a storage device 130, and a controller 109. The image acquisition device 120 may include one or more processors. For example, the image acquisition device 120 may include a computer, a server, a mainframe, a terminal, a personal computer, any type of mobile computing device, etc., or a combination thereof. The image acquisition device 120 may be connected to the detector 144 of the electron beam tool 200B through a medium such as an electrical conductor, a fiber optic cable, a portable storage medium, IR, Bluetooth, the Internet, a wireless network, radio, or a combination thereof. The image acquisition device 120 may receive a signal from the detector 144 and may construct an image. Thus, the image acquisition device 120 may acquire an image of the wafer 150. The image acquisition device 120 may also perform various post-processing functions, such as image averaging, generating contours, superimposing indicators on the acquired image, etc. The image acquisition device 120 may be configured to perform adjustments such as brightness and contrast on the acquired image. The storage device 130 may be a storage medium such as a hard disk, a random access memory (RAM), a cloud storage, other types of computer-readable memory, etc. The storage device 130 may be coupled to the image acquirer 120 and may be used to save the scanned raw image data as a raw image and a post-processed image. The image acquirer 120 and the storage device 130 may be connected to the controller 109. In some embodiments, the image acquirer 120, the storage device 130, and the controller 109 may be integrated as an electronic control unit.

[0055] In some embodiments, the image acquirer 120 may acquire one or more images of the sample based on the imaging signal received from the detector 144. The imaging signal may correspond to a scanning operation for implementing charged particle imaging. The acquired image may be a single image including a plurality of imaging regions, which may include various features of the wafer 150. The single image may be stored in the storage device 130. Imaging may be performed based on imaging frames.

[0056] The condenser and illumination optics of an electron beam tool may include or be supplemented by an electromagnetic quadrupole electron lens. Figure 2B As shown in FIG. 1 , the electron beam tool 200B may include a first quadrupole lens 148 and a second quadrupole lens 158. In some embodiments, the quadrupole lenses may be used to control the electron beam. For example, the first quadrupole lens 148 may be controlled to adjust the beam current, and the second quadrupole lens 158 may be controlled to adjust the beam spot size and beam shape.

[0057] In some embodiments of the present disclosure, a PIN detector can be used as an in-lens detector in a deceleration objective SEM column of an EBI system 10. The PIN detector can be placed between a cathode for generating an electron beam and the objective lens. The electron beam emitted from the cathode can be potentiated at -BE keV (typically about -10 kV). The electrons of the electron beam can be immediately accelerated and pass through the column. The column can be at ground potential. Therefore, the electrons can have a kinetic energy of BE keV when passing through the opening 145 of the detector 144. Since the wafer surface potential can be set to -(BE-LE) keV, the pole piece (such as Figure 2B Electrons entering the pole piece 132a of the objective lens assembly 132 can be rapidly decelerated to a landing energy of LE keV.

[0058] Figure 2C An example of a charged particle beam device 200C consistent with an embodiment of the present disclosure is shown. The charged particle beam device 200C may be, for example, Figure 2A The charged particle beam device 200A or Figure 2B 200B in FIG. Emitted electrons 171 (including, for example, secondary electrons or backscattered electrons) are emitted from the wafer surface by electron impact of the primary electron beam 105. The deceleration electric field can slow down the primary electrons as they approach the detection spot 170, and the deceleration electric field can act as an accelerating electric field to accelerate the emitted electrons backward toward the surface of the PIN detector 144. For example, Figure 2C As shown in , due to the interaction with the wafer 150 at the detection spot 170, an emitted electron 171 traveling backward toward the detector 144 can be generated. The emitted electrons 171 traveling along the optical axis 105 from the wafer surface can arrive at the surface of the detector 144 in the form of a position distribution. The arrival positions of the emitted electrons may be located in a roughly circular area, whose radius is, for example, a few millimeters or larger, such as 5 millimeters, 10 millimeters, or 20 millimeters or larger. The geometric spread may increase with increasing landing energy. The geometric spread of the arrival positions of the emitted electrons may be due to the electrons having different trajectories, which may depend on, for example, the initial kinetic energy and the emission angle of the electrons. Other factors may affect the geometric spread or other characteristics of the arrival positions.

[0059] Figure 2DAn example of the distribution of the arrival points of the emitted electrons on the detector surface is illustrated. The electrons 171a may land at different points on the surface of the detector 144, and typically, when there is no deflection field, most of the electrons can be gathered around the central portion of the detector 144. As discussed above, the emitted electrons may include, for example, secondary electrons or backscattered electrons. In some embodiments, for example, the distribution may include between 60-85% secondary electrons and between 40-15% backscattered electrons. The arrival point distribution may be offset depending on the emission position and the SEM deflection field (e.g., scanning field). Therefore, in some applications, if a certain field of view (FOV) of the SEM image is required, the size of the required in-lens PIN detector may be quite large. Typically, the diameter of the detector may be, for example, 10 mm or larger. In some embodiments, the diameter of the detector may be, for example, about 4 to 10 mm.

[0060] The detector 144 may be placed 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 at its center so that the primary electron beam may pass through to reach the wafer 150. Figure 2B-2C An example of a detector 144 having an opening at its center is shown. However, some embodiments may use a detector that is placed off-axis relative to the optical axis along which the primary electron beam travels. For example, Figure 2A As in the example shown in FIG. 2 , a beam splitter 222 may be provided to direct the emitted electron beam toward an off-axis positioned detector. The beam splitter 222 may be configured to steer the emitted electron beam toward the electron detection device 244 at an angle α, such as Figure 2A Therefore, in some embodiments of the present disclosure, a detector without a central opening may be provided.

[0061] Figure 2A Detector 244 or Figure 2B-Figure 2D The detector 144 may include a sensing element such as a diode or a diode-like element that can convert incident energy into a measurable signal. For example, the sensing element in the detector may include a SPAD, an APD, a scintillator, or a PIN diode. Throughout this disclosure, the sensing element may be represented as a diode, although the sensing element or other components may deviate from the ideal circuit behavior of electrical elements such as diodes, resistors, capacitors, and the like. In an embodiment of the present disclosure, the detector in the charged particle beam system may include a pixelated array of multiple sensing elements. In some embodiments, the sensing element may be configured for charged particle counting. Sensing elements of detectors that can be used for charged particle counting are discussed in U.S. Publication No. 2019 / 0378682, which is incorporated herein by reference in its entirety.

[0062] For ease of explanation and without ambiguity, electrons are used as examples in some descriptions herein. However, it should be noted that any charged particles can be used in any embodiment of the present disclosure, and are not limited to electrons. For example, the source in a charged particle beam tool can emit one or more charged particles, such as electrons, protons, ions, muons, or any other particles carrying an electric charge. In addition, some embodiments of the present disclosure can use photons instead of charged particles, such as visible light, UV, DUV, EUV, X-rays, or light within any other wavelength range. Therefore, although the detector in the present disclosure may be disclosed for electron detection, some embodiments of the present disclosure may be directed to detecting other charged particles or photons.

[0063] Figure 3A-3B An exemplary structure of a pixelated electron detector consistent with an embodiment of the present disclosure is illustrated. Figure 3A Detector 344a or Figure 3B The 344b class detector can be provided as Figure 2A The detector 244 shown in or Figure 2B-Figure 2D The detector 144 shown in FIG. Figure 3A , detector 344a includes a sensor layer 301 and a signal processing layer 302. Sensor layer 301 may include a sensor die consisting of a plurality of sensing elements, including sensing elements 311, 312, 313, and 314. In some embodiments, a plurality of sensing elements may be provided in a sensing element array, each sensing element may have a uniform size, shape, and arrangement.

[0064] Signal processing layer 302 may include a plurality of signal processing circuits, including circuits 321, 322, 323, and 324. The circuits may include interconnects (e.g., wiring paths) configured to communicatively couple sensing elements. Each sensing element of sensor layer 301 may have a corresponding signal processing circuit in signal processing layer 302. The sensing elements and their corresponding circuits may be configured to operate independently. Figure 3A As shown in , circuits 321 , 322 , 323 , and 324 may be configured to be communicatively coupled to outputs of sensing elements 311 , 312 , 313 , and 314 , respectively, as indicated by four dashed lines between sensor layer 301 and signal processing layer 302 .

[0065] In some embodiments, the signal processing layer 302 can be configured as a single die on which a plurality of circuits are provided. The sensor layer 301 and the signal processing layer 302 can be in direct contact. In some embodiments, the components and functionality of different layers can be combined or omitted. For example, the signal processing layer 302 can be combined with the sensor layer 301 into a single layer. In addition, the charged particle counting circuit can be integrated at various points in the detector, such as in a separate readout layer of the detector or on a separate chip. More details of the electronic counting circuit system and alternative structures for the sensor layer 301 and the signal processing layer 302 can be found in the international publication WO2022 / 008518, the entire contents of which are incorporated herein by reference.

[0066] like Figure 3B As shown in FIG. 3 , a detector 344 b having an array of sensing elements 311 may be provided. The detector 344 b may be, for example, a pixelated electronic detector, such as a pixelated electronic counting detector. The detector 344 b may include a sensor layer 301 and a signal processing layer 302, such as Figure 3A . The detector circuit system may include an electron counting circuit provided separately for each sensing element. The detector 344b may include a plate 351 on which a plurality of sensing elements 311 are formed. The plate 351 may include an opening 345 for allowing the primary electron beam to pass through the plate 351.

[0067] Individual electron counting can be achieved when the individual sensing elements 311 of the detector are small compared to the geometric spread of the emitted electrons incident on the detector. For example, each sensing element can have its own counting unit, which includes a circuit system configured to measure the output signal from the sensing element. When the sensing element is made smaller, the rate of electrons reaching each sensing element is reduced, and thus the electron count at each sensing element can be achieved. In addition, the capacitance of the detector can be proportional to the area of ​​the detector surface. Some noise sources, such as noise sources caused by components (e.g., amplifiers) coupled to the detector, may be related to capacitance. The small area of ​​each individual element in the pixelated electron counting detector allows for a much lower capacitance than, for example, a large continuous sensing surface. For example, the individual sensing element can be a square or other shape with a size of, for example, 5, 10, 25, 50, 100, 200, or 300 μm on a side. The sensing element can be larger, such as at the millimeter level. A typical detector may include, for example, 100, 500, 1000, 5000, 10000, 50000, or 100000 or more sensing elements.

[0068] Some charged particle beam processes, such as high-resolution SEM, require very low primary beam currents (e.g., as low as 40 pA) and high operating speeds (e.g., 400 megapixels per second (Mpixel)). Such low primary beam currents may result in very small rates of emitted electrons reaching the detector, which in turn increases the dwell time required to reach a sufficient number of electrons to obtain an accurate reading. For example, the entire detector may only record a single electron event per clock cycle (2.5 ns = 1 / 400 MHz). Therefore, if a large number of emitted electrons are required, high operating speeds may not be achieved.

[0069] Furthermore, at such low primary beam currents, it becomes increasingly difficult to overcome shot noise and other noise sources. Shot noise can refer to the probabilistic nature of the spatial and temporal distribution of electron arrivals on the detector surface. Each electron landing event may occur on the detector surface with a certain probability. For example, in a simple case, the probability of an electron arrival occurring at the center portion of the detector may be high, with the probability decreasing as the distance from the center portion increases. Furthermore, the number of electrons detected in a given time period also varies according to a probability function. When enough electrons are collected over a sufficiently long 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 does not occur, and the probability of an electron arrival distribution reflecting the expected distribution is less likely.

[0070] Another source of noise can be dark current, which can cause false detections even when there is no incident radiation. Dark current can occur due to, for example, defects in the material forming the detector, such as defects in the crystal structure of the sensing diode. The term "dark" current can refer to the fact that current fluctuations are not related to incoming electrons but can still be interpreted as arrival events. Various noise sources, such as dark current, thermal energy, external radiation, etc., can cause unexpected current fluctuations in the detector output. Dark current and noise sources may produce signals at locations on the detector where the probability of registering an actual electron arrival event is low.

[0071] The shot noise problem may be particularly problematic when attempting to detect edge features in a low beam current arrangement. In a comparative embodiment, the presence of an edge feature may be at least partially inferred by observing an increase in emitted electrons as the primary beam scans the edge portion of a pattern feature. However, at low beam currents, this increase may not be as dramatic. Therefore, a large number of emitted electrons may need to be collected to distinguish between signal and noise. For example, for a sample pixel at an expected edge feature location, a conventional SEM tool may need to collect at least a range of, for example, 40-70, 70-100, 100-150 or more electrons. As discussed above, this higher collection rate can adversely affect operating speed.

[0072] Embodiments of the present disclosure utilize additional information collected during the detection process to more effectively characterize pattern features. Specifically, spatial information on the electron arrival detector can be used to help detect edge features with fewer electron numbers than the number of electrons required for the comparative embodiment. In some embodiments of the present disclosure, the spatial information includes asymmetric information. Asymmetric information may include a measured offset of the distribution position of the emitted electron arrival, which can be used to determine the edge feature corresponding to the measured offset. Spatial information can be combined with other information to determine the presence of edge features. For example, spatial information can be combined with an emitted electron yield map.

[0073] Figure 4A-4B A charged particle detector (eg, Figure 2A-2D The detector 144 and Figure 3A-3B 344a and 344b). 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 on the right side of each distribution is a gray tone logarithmic scale of the probability of an electron arrival event at each detector pixel. White or light pixels indicate a high probability of an electron arrival, while darker pixels indicate a low or zero probability. Note that in the figure, the dark pixel in the center indicates a hole in the detector, similar to the primary beam hole 345 in FIG. 3, where an arrival event cannot occur and therefore has a probability of zero. Such a hole may not be present in all embodiments of the charged particle detector, but it may serve as a Figure 4A-4B A useful visual reference point for the offsets illustrated in .

[0074] Figure 4C A cross-sectional view of pattern features 432 / 433 on a portion of a sample 430 that is undergoing charged particle beam processing (such as a SEM scan) consistent with an embodiment of the present disclosure is illustrated. Sample 430 can be, for example, a semiconductor wafer having pattern features of an integrated circuit. The pattern features can include an alternating series of lines 431 and spaces 433 extending perpendicular to the plane of the page. An edge 432 can be located at the interface between each line 431 and space 433. Flat areas of the surface topography (such as the upper surface of a line 431 or space 433) can be scanned as flat sample pixels Pf. Transitional topography can be scanned as edge sample pixels Pe.

[0075] Figure 4A The diagram shows a device consistent with an embodiment of the present disclosure, for example Figure 4CThe arrival distribution of one of the flat sample pixels Pf of the detector 444. The distribution can have a substantially symmetrical shape and be centered on the surface of the detector 444. Such a property can be an indication that the sample pixel position has a substantially flat topography. The term "centered on..." can refer to, for example, the center of mass or geometric center of the distribution of arrival events (or arrival event probabilities). The center can, for example, be a weighted spatial average of the arrival events or it can exclude outliers. This spatial center of arrival can be likened to the center of mass (CoM) of a set of point objects, and therefore it can be referred to in this application as the CoM of the emitted electron arrival distribution. Figure 4A In , for a flat sample pixel Pf, the CoM of the emitted electron arrival distribution is centered on the detector.

[0076] Notice, Figure 4A The detector-centered properties of the CoM may be affected by other known parameters of the charged particle beam processing. For example, the primary electron beam during scanning can be deflected in two dimensions to scan the entire field of view (FoV) of the sample. The primary beam can be deflected so as to scan, for example, a rectangular FoV in a line-by-line, zigzag or serpentine manner. The scan may form a primary beam spot at each sample pixel location within the FoV. Due to the deflection, the primary beam does not always hit the sample surface at normal incidence. This may cause the arrival distribution of the emitted electrons on the detector surface to be shifted or deformed. Aberrations of the lens system may also cause shifts and deformations. Therefore, after accounting for typical known parameters such as scanning deflection, the CoM of the arrival distribution for a flat topography may be located at the expected location on the detector surface instead of at the center of the detector surface. Furthermore, considering these same known parameters, Figure 4A The symmetry shown in may be deformed in an expected manner. Therefore, as discussed further below, the shift or deformation of the emitted electron arrival distribution may be a shift or deformation from the expected position and expected shape, respectively. For example, if the sample pixel has a flat morphology, the CoM deviation of the edge sample pixel may be a deviation from the expected CoM. The shift, deformation or other spatial variation from the expected parameter can be referred to as an asymmetry parameter, and it may be attributed to the presence of edge features in the sample pixel.

[0077] There are also fixed parameters associated with the charged particle beam system that may affect the location and distribution of electron arrival events on the detector surface, such as, for example, electrodes, landing energy, and detector height. Deflection electrodes, focusing electrodes, or Wien filters may affect the location or shape of the electron distribution. The voltage on the deflection electrodes may affect the divergence of electrons as they move from the sample toward the detector. Individual detector branches (such as Figure 2AThe focusing electrodes in 242) may also affect the position or shape. The Wien filter can also be used to deflect the incident electrons away from the center of the detector, for example to minimize the loss of electrons through the primary beam hole. As discussed above, the geometric spread of electron arrivals may also increase with increasing landing energy. In addition, for a given divergence value, an increase in the detector height will result in a larger distribution of electrons.

[0078] Figure 4B The diagram is consistent with the embodiment of the present disclosure. Figure 4C The emission electrons of the edge sample pixel Pe on the right side of the image are distributed. Since there is an edge feature at the edge sample pixel Pe, an asymmetric parameter is introduced into the distribution. Figure 4B , the CoM of the distribution deviates from its expected position at the center of the detector, and the shape of the distribution is slightly shifted to the upper right corner. For example, the distribution shown might correspond to Figure 4C 431. The distribution corresponding to the left edge sample pixel Pe may exhibit similar asymmetric shifts in different directions on the detector surface, such as in the opposite direction to the left or diagonally. Such asymmetric parameters at the detector surface can be exploited in charged particle beam processing to determine that the sample pixels include edge features.

[0079] In general, when scanning a first edge feature, an asymmetric parameter such as a first CoM deviation may be offset to one side of the detector surface. Next, when passing over an edge and scanning a flat region, the CoM deviation may return to a zero or center position. Next, when scanning a second (opposite) edge region, a second CoM deviation may appear on the detector that is offset in a direction opposite to the first CoM deviation. The direction of the CoM deviation on the detector surface can be used to further understand the sample topography, such as, for example, distinguishing between lines and spaces in the CoM map by determining whether an edge represents the beginning or end of such a line / space.

[0080] Figure 4A-4B The simulation depicted in indicates 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.

[0081] In addition, the sample pixel can be the sum of one or more short electron collection cycles or frames to produce enough information about the pixel. For example, a single frame can include, for example, between 0 and 100 detected electron arrival events. The sum can include, for example, between 2 and 200 frames. In some embodiments of the present disclosure, the sample pixel can include, for example, twenty-five to several hundred or more detected electron arrival events. However, at low beam currents, the collection rate may be at the lower end of these ranges.

[0082] Figure 5A-Figure 5B An example detector 544 (eg, Figure 2A-2D The detector 144 and Figure 3A-3B 344a and 344b) of the surface, and Figure 4A-4B The principle is similar to the principle shown in Figure 5A In the process, a small amount of emitted electrons reach 571a and are collected on a flat surface (such as Figure 4C The CoM of the distribution of emitted electrons arriving at 571a is located substantially at the center of the detector 544, which is indicated by the central primary beam aperture. As previously discussed, this aperture may not be present in some detectors. Figure 5B The edge sample pixels (such as Figure 4C Here, the CoM is offset from the center of the detector by a displacement d. In addition, the shape of the distribution of the emitted electrons arriving at 571b is relative to Figure 5A Finally, the number of emitted electrons arriving at 571b for the edge sample pixel Pe is higher than the number of emitted electrons arriving at 571a for the flat sample pixel Pf.

[0083] Asymmetry parameters such as CoM deviation (or shape deformation) at each sample pixel in the FoV can be compiled as Fig. 6A , where each point on the CoM map (i.e., map pixel) corresponds to a sample pixel in the FoV. Thus, each map pixel represents the distribution of emitted electrons for one sample pixel on the detector surface, such as, for example Figure 5A-Figure 5B Darker map pixels indicate that the emitted electron distribution has a larger CoM deviation from the detector center (such as Figure 5B ). Brighter map pixels indicate that the emitted electron distribution has a smaller CoM deviation from the detector center (such as Figure 5A ).

[0084] Fig. 6A The CoM diagram may come from examining Figure 6C Here, each line in the CoM diagram corresponds to a vertical edge 632 at the transition between a line 631 and a space 633.

[0085] The continuous background color of the CoM map gradually darkens with the distance from the center of the FoV. This low spatial frequency variation of the CoM map across the FoV may be attributed to the known parameters discussed above, such as lens aberrations and beam scanning deflection. However, the CoM map also reveals high spatial frequency components in the form of a series of vertical lines. This regular CoM deviation may be caused by the edge 632 in the line and space pattern (similar to Figure 4C Edge 632 may be caused by a controller such as Figure 1 and Figure 2B For example, the controller may identify pattern edges 632 by applying a contour fitting algorithm to the CoM map in combination with predetermined information, such as pattern layout data.

[0086] In addition to the CoM deviation, the CoM diagram can also represent another parameter, such as the shape of the emitted electron distribution or other asymmetry parameters. Fig. 6A A CoM diagram may convey only the magnitude of the deviation and not other information (such as, for example, the direction of the deviation), but such additional information may be encoded on the CoM diagram. As a visual example, a middle gray value may represent zero deviation, while pixels darker than the middle gray value indicate deviations in a first (e.g., negative) direction, and pixels brighter than the middle gray value indicate deviations in a second (e.g., positive) direction. For example, the diagram may be color-coded to indicate additional direction or shape information. Furthermore, the CoM diagram need not be embodied as a visual indicator at all. In general, a CoM diagram may be a representation of CoM parameters (such as CoM deviation and shape) for a set of sample pixels within an area (such as the FoV of a charged particle beam, a system, a single die of a wafer, an entire wafer, or other sample, etc.).

[0087] As Fig. 6A As an alternative to the CoM map illustrated in FIG. , an aberration-corrected CoM map can be derived. For example, a CoM map can be created where Fig. 6A The CoM value may represent not the deviation from the center of the detector, but the deviation from the expected position on the detector when such aberration factors are taken into account. In either case, the goal may be to determine the deviation due to edge features rather than other factors.

[0088] As discussed above, the spatial parameters of the electron arrival distribution are not the only indicators of edge features. As the primary beam spot scans edge features on the sample, the number of emitted electrons received on the detector surface may also increase. The number of emitted electron arrivals can be recorded at each sample pixel in the FoV to produce a graph such as Figure 6BHere, darker map pixels on the yield map correspond to sample pixels (such as Figure 5B ). Brighter map pixels on the yield map indicate that a smaller number of emitted electrons (such as Figure 5A ).

[0089] The uniform background color of the yield map indicates that the average value of the emitted electron collection at the flat topography within the FoV is essentially constant. Fig. 6A This uniformity is for illustrative purposes only, compared to the continuously varying background of . In practice, the emitted electron yield may have a much greater degree of non-uniformity. Figure 1 Similarly, the yield graph reveals a series of vertical lines with a clear increase in the emitted electron yield. These lines can correspond to Fig. 6A The same edge of the line and space pattern 632. A controller (e.g., controller 109) can identify edge features by applying a contour fitting algorithm to the yield map in a manner similar to the CoM map discussed above.

[0090] In the comparative example, Figure 6B The yield map of can be the main indicator of edge characteristics. For example, in the comparative embodiment, Figure 5A-Figure 5B The difference in spatial distribution between the emitted electron arrivals 571a and 571b may not be recorded, and the information may be lost during signal readout. In this case, edge features may be determined primarily based on the difference in the number of electron arrivals acquired at each sample pixel. Due to this limited information, the minimum number of emitted electrons required to achieve suitable contrast may be higher than that required when the CoM map is also available.

[0091] 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 produce more information about edge features 632. For example, the two maps can be added, averaged, weighted or scaled, etc., to produce information about edge features 632. The two maps can be combined to form a combined map. Alternatively, the first map in the two maps can be used to reinforce the low confidence area in the second map in the two maps. The use of two maps can make it possible to detect edge features with a lower minimum number of emitted electrons. This lower minimum value may result in a shorter dwell time at each sample pixel, thereby improving the throughput of charged particle beam processing without sacrificing accuracy. For example, if the minimum number of electron arrivals required in a low beam current application can be reduced from, for example, 100 to 75, this will represent a 25% increase in throughput.

[0092] In some embodiments of the present disclosure, the detector can 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 can be configured to generate a signal proportional to the energy of the electron arrival. This information can also be used to assign weighting coefficients to individual arrival events to derive an energy-weighted CoM map.

[0093] The spatial information may also be utilized to determine aberrations or other system parameters, which may then be used to better analyze the results of the emission electron yield map. In this case, the CoM map may not be directly combined with the emission electron yield map, but rather used to determine system parameters to calculate corrections or adjustments to the emission electron yield map. The reverse may also be true, where the yield map may be used to determine corrections to the CoM map.

[0094] For example, a CoM map can be used to characterize low spatial frequency components of CoM deviations in order to monitor system drift. Low spatial frequency CoM variations will remain substantially consistent between multiple (similar) FoVs because it represents a property of the system rather than the sample. Therefore, system stability can be monitored by comparing low spatial frequency CoM variations across multiple scanned FoVs. Multiple FoVs can be scanned continuously. Alternatively, FoVs from different regions can be compared to each other based on their expected similarities (such as due to similar pattern data or other parameters). By comparing the CoM information of a first FoV acquired during a first time period with the CoM information of a second FoV acquired during a second time period, performance parameters of the system (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 the comparison.

[0095] Furthermore, the above disclosure is made with reference to a single emitted electron arrival distribution of a single emitted electron beam with a single CoM deviation. However, embodiments of the present disclosure may be applicable to multi-beam configurations, such as Figure 2A In this case, there may be multiple distributions of emitted electron arrivals on different detectors or different regions of a single detector, each with a different CoM bias. Furthermore, in this case, the detector "center" referred to above may refer to the center of the detector region on which one of the individual distributions of emitted electron arrivals is incident.

[0096] In addition to pixelated electronic detectors, segmented detectors can also be used to obtain spatial information. For example, the detector surface can be divided into two halves, four quadrants, etc. By detecting the difference in signal between one segment and another, the CoM deviation can be determined. Figure 7A-7B The present disclosure is consistent with the use of the segment detector 744. Figure 4A-4BThe 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 in that quadrant. Thus, even though the segmented detector may not be able to distinguish between individual arrival events, it is still configured to acquire sufficient spatial information about the electron arrivals to determine CoM deviations by taking the differences between the quadrants.

[0097] For example, the controller can take the difference between quadrants B and C (BC), or can measure the difference between the two halves (B+D) – (A+C). The difference between any or all segment pairs can be determined. Fig. 7A For flat sample pixels as seen in , the results of these subtractions will be low or zero due to the symmetry of the electron arrival. However, the distribution of edge sample pixels (such as Figure 7B The results for each sample pixel can be compiled into a CoM and yield map, as described above for Figure 6A-6C discussed.

[0098] Figure 8 An experimental graph of the CoM deviation (in millimeters) of the arrival of emitted electrons on a detector consistent with an embodiment of the present disclosure is schematically illustrated. The diameter of the detector can be, for example, about 4 to 10 millimeters. The graph illustrates the CoM deviation of the electron arrival range up to 250 at the edge and flat areas of the sample. The deviation shown can represent a component of the total deviation, such as a horizontal or vertical component, or it can represent the total deviation. The deviation can be a deviation from the center of the detector. Alternatively, when system parameters other than the morphology are considered (such as beam deflection and lens aberrations), it can represent a deviation from the expected position. The zero mark on the ordinate axis indicates a reference point for the CoM deviation, such as the center of the detector. The ordinate axis extends from zero in the positive and negative directions. However, the positive or negative direction only indicates the amplitude of the distance from the zero mark.

[0099] Figure 8 The graph shows a consistent CoM difference between the edge and flat areas of the sample starting with the first data point of about 25 electron arrival events. At this level, the CoM of the emitted electron arrivals on the edge region is close to 0.3 mm from zero, while the CoM of the flat region is offset by about 0.1. The 50 arrival mark shows a significant difference in the CoM of the edge region, which is consistent with the uncertainty associated with low numbers of electron arrivals. However, even with this fluctuation, there is still a clear difference 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 the topography of the detector surface and the CoM deviation. But even at lower numbers, such as 25 or 50 arrivals, the CoM map can be used to distinguish between edge features and flat portions of the sample surface.

[0100] Fig. 9 A flow chart of an example method 900 for determining edge features in a sample surface using a charged particle detector consistent with embodiments of the present disclosure is illustrated. The charged particle detector can be part of a charged particle beam device. For example, the charged particle beam detector can be a pixelated electron counting detector in a SEM for scanning inspection samples (such as semiconductor wafers). The method can be performed by a processor and a memory of a controller configured to control the charged particle beam device to perform the method.

[0101] At step 910, a charged particle detector detects a plurality of charged particles on its surface. The detector may be, for example, Figure 2A Detector 244, Figure 2B-Figure 2D Detector 144, Figure 3A Detector 344a, Figure 3B Detector 344b or Figure 5A-Figure 5B Detector 544.

[0102] At step 920, the controller obtains spatial distribution information of the detected charged particle arrival positions on the surface of the charged particle detector for a plurality of sample pixels in the FoV of the sample surface. For example, the spatial distribution information may include the arrival 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 arrival, in which case the spatial distribution information may include an energy-weighted distribution.

[0103] At step 930, the spatial distribution information may be used to determine an asymmetry parameter. For example, the asymmetry parameter may be a deviation in the shape of the spatial distribution of emitted electron arrival events on the detector surface. The asymmetry parameter may be a deviation of the spatially distributed CoM from the center of the detector, or from the center of the beam spot area in a multi-beam detector. Alternatively, when taking into account, for example, beam deflection, lens aberrations, or other system parameters, the asymmetry parameter may be a deviation of the spatially distributed CoM from the expected position on the detector. The CoM may include the centroid or geometric center of the distribution of electron arrival events or a weighted spatial average of the arrival events. The CoM may include the centroid or geometric center of a subset of emitted electron arrivals after excluding outliers or potential false positives. The asymmetry parameter may include a CoM map of the asymmetry parameter over the FoV of the charged particle beam device. The CoM map may include, for example, Fig. 6A The CoM diagram shown in .

[0104] At step 940, edge features on the sample surface are determined based on the asymmetry parameters. For example, a profile fitting algorithm can be applied to the CoM map in combination with predetermined information (such as pattern layout data). The edge features can be used, for example, in a metrology process to determine metrology parameters. The metrology parameters can include, for example, critical dimension, critical dimension uniformity, line width, overlap, line edge roughness, line end shortening, bottom surface tilt, sidewall angle, and other dimensional parameters.

[0105] Fig.10 A flow chart of an example method 1000 for determining edge features in a sample surface using a charged particle detector consistent with an embodiment of the present disclosure is illustrated. The charged particle detector can be part of a charged particle beam device. For example, the charged particle beam detector can be a pixelated electron detector, such as a pixelated electron counting detector in a SEM used to scan and inspect samples (such as semiconductor wafers). The method can be performed by a processor and a memory of a controller configured to control the charged particle beam device to perform the method. Steps 1010-1030 can correspond to steps 910-930 of method 900 described above. Step 1040 can correspond to a modified version of step 940 of method 900 described above. Method 1000 also includes the following additional steps.

[0106] At step 1025 , after charged particles are detected at the detector surface at step 1010 , the controller obtains charged particle count information for a plurality of sample pixels in the FoV of the sample surface.

[0107] At 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, Figure 6B Production diagram.

[0108] At step 1040, edge features on the sample surface are determined based on the yield parameters obtained at step 1035 and the asymmetry parameters obtained at step 1030. For example, a profile fitting algorithm can be applied to the CoM map and the emitted electron yield map, respectively, in combination with predetermined information (such as pattern layout data). The edge features can be used, for example, in a metrology process to determine metrology parameters. The metrology parameters can include, for example, critical dimension, critical dimension uniformity, line width, overlap, line edge roughness, line end shortening, bottom surface tilt, sidewall angle, and other dimensional parameters.

[0109] A non-transitory computer readable medium may be provided that stores information for use with a controller (e.g., Figure 1 Instructions of a processor of the controller 109 in the embodiment of the present disclosure for determining edge features (such as Figure 4A-Figure 9). For example, instructions stored in a non-transitory computer-readable medium may be executed by the circuit system of the controller to partially or fully perform the method 900 or 1000. Common forms of non-transitory media 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 with a pattern of holes, a random access memory (RAM), a programmable read-only memory (PROM) and an erasable programmable read-only memory (EPROM), a FLASH-EPROM or any other flash memory, a non-volatile random access memory (NVRAM), a cache, a register, any other memory chip or magnetic cartridge, and networked versions thereof.

[0110] The embodiments may also be described using the following terms:

[0111] 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:

[0112] Examining sample surfaces using a charged particle beam system;

[0113] Obtaining spatial distribution information of the arrival positions of the charged particles detected on the charged particle detector;

[0114] determining an asymmetry parameter of the spatially distributed information; and

[0115] The edge characteristics on the sample surface are determined based on the asymmetry parameter.

[0116] 2. The non-transitory computer-readable medium of clause 1, wherein the asymmetry parameter comprises a localization parameter of an arrival position of the detected charged particles on the charged particle detector.

[0117] 3. The non-transitory computer-readable medium of clause 2, wherein the localization parameter comprises a deviation of a center of mass (CoM) of a detected charged particle arrival position, the deviation being caused by an edge feature.

[0118] 4. The non-transitory computer-readable medium of clause 1, wherein the asymmetry parameter comprises a shape parameter of a detected charged particle arrival position on a charged particle detector.

[0119] 5. The non-transitory computer-readable medium of clause 4, wherein the shape parameter comprises a shape deviation of a detected charged particle arrival position at a charged particle detector, the deviation being caused by edge features.

[0120] 6. The non-transitory computer-readable medium of clause 1, wherein the set of instructions executable by at least one processor is configured to cause the device to further perform:

[0121] Determining a CoM map based on asymmetry parameters of detected charged particle arrival positions;

[0122] The edge features are determined based on the CoM graph.

[0123] 7. The non-transitory computer-readable medium of clause 1, wherein the set of instructions executable by at least one processor is configured to cause the device to further perform:

[0124] Obtaining the yield information of the detected charged particle arrivals;

[0125] determining a yield parameter of the detected charged particle arrival based on the yield information;

[0126] The edge characteristics are determined based on both the yield parameter and the asymmetry parameter.

[0127] 8. The non-transitory computer readable medium of clause 7, wherein the yield parameter comprises a charged particle yield map.

[0128] 9. The non-transitory computer-readable medium of clause 7, wherein the asymmetry parameter comprises a CoM map.

[0129] 10. The non-transitory computer-readable medium of clause 1, wherein the spatial distribution information comprises fewer than 120 detected charged particle arrival locations.

[0130] 11. The non-transitory computer-readable medium of clause 10, wherein the spatial distribution information comprises fewer than 50 detected charged particle arrival locations.

[0131] 12. The non-transitory computer readable medium of clause 1, wherein the charged particle detector is an electron detector.

[0132] 13. The non-transitory computer readable medium of clause 12, wherein the electron detector is one of a four-quadrant segmented detector, a two-half segmented detector, and a pixelated electron counting detector.

[0133] 14. The non-transitory computer readable medium of clause 1, wherein the charged particle beam device comprises a scanning electron microscope.

[0134] 15. A method for determining edge features on a sample surface, comprising:

[0135] Examining sample surfaces using a charged particle beam system;

[0136] Obtaining spatial distribution information of the arrival positions of the charged particles detected on the charged particle detector;

[0137] determining an asymmetry parameter of the spatially distributed information; and

[0138] The edge characteristics on the sample surface are determined based on the asymmetry parameter.

[0139] 16. The method according to clause 15, wherein the asymmetry parameter comprises a localization parameter of the detected charged particle arrival position on the charged particle detector.

[0140] 17. A method according to clause 16, wherein the localization parameter comprises a deviation in the CoM of the detected charged particle arrival position, the deviation being caused by the edge feature.

[0141] 18. The method of clause 15, wherein the asymmetry parameter comprises a shape parameter of a detected charged particle arrival position on the charged particle detector.

[0142] 19. The method of clause 18, wherein the shape parameter comprises a deviation in the shape of a detected charged particle arrival position at the charged particle detector, the deviation being caused by edge features.

[0143] 20. The method according to clause 15, further comprising:

[0144] Determining a CoM map based on asymmetry parameters of detected charged particle arrival positions;

[0145] The edge features are determined based on the CoM graph.

[0146] 21. The method according to clause 15, further comprising:

[0147] Obtaining the yield information of the detected charged particle arrivals;

[0148] determining yield parameters of detected charged particle arrivals;

[0149] The edge characteristics are determined based on both the yield parameter and the asymmetry parameter.

[0150] 22. The method of clause 21, wherein the yield parameter comprises a charged particle yield map.

[0151] 23. The method of clause 21, wherein the asymmetry parameter comprises a CoM map.

[0152] 24. The method of clause 15, wherein the spatial distribution information comprises fewer than 120 detected charged particle arrival locations.

[0153] 25. The method of clause 24, wherein the spatial distribution information comprises fewer than 50 detected charged particle arrival locations.

[0154] 26. The method of clause 15, wherein the charged particle detector is one of an electron detector or a proton detector.

[0155] 27. The method of clause 26, wherein the electron detector is one of a four-quadrant segmented detector, a two-half segmented detector, and a pixelated electron counting detector.

[0156] 28. The method of clause 15, wherein the charged particle beam device comprises a scanning electron microscope.

[0157] 29. A charged particle beam device comprising:

[0158] a charged particle beam source configured to generate a primary charged particle beam;

[0159] an optical system configured to direct the primary charged particle beam to a sample surface to inspect the sample surface;

[0160] a charged particle detector configured to detect a spatial distribution of detected charged particles returning from a sample surface;

[0161] A controller comprising one or more processors and configured to cause the charged particle beam device to perform:

[0162] Obtaining spatial distribution information of the arrival positions of the charged particles detected on the charged particle detector;

[0163] determining an asymmetry parameter of the spatially distributed information; and

[0164] The edge characteristics on the sample surface are determined based on the asymmetry parameter.

[0165] 30. A charged particle beam apparatus according to clause 29, wherein the asymmetry parameter comprises a localization parameter of a detected charged particle arrival position on a charged particle detector.

[0166] 31. A charged particle beam apparatus according to clause 30, wherein the localization parameter comprises a deviation in the CoM of the detected charged particle arrival position, the deviation being caused by the edge feature.

[0167] 32. A charged particle beam apparatus according to clause 29, wherein the asymmetry parameter comprises a shape parameter of detected charged particle arrival positions on the charged particle detector.

[0168] 33. A charged particle beam apparatus according to clause 32, wherein the shape parameter comprises a shape deviation of detected charged particle arrival positions at the charged particle detector, the deviation being caused by edge features.

[0169] 34. A charged particle beam apparatus according to clause 29, wherein the controller is further configured to cause the charged particle beam apparatus to perform:

[0170] Determining a CoM map based on asymmetry parameters of detected charged particle arrival positions;

[0171] The edge features are determined based on the CoM graph.

[0172] 35. The charged particle beam apparatus according to clause 29, wherein the controller is further configured to cause the charged particle beam apparatus to perform:

[0173] Obtaining the yield information of the detected charged particle arrivals;

[0174] determining yield parameters of detected charged particle arrivals;

[0175] The edge characteristics are determined based on the yield parameter and the asymmetry parameter.

[0176] 36. A charged particle beam apparatus according to clause 35, wherein the yield parameter comprises a charged particle yield map.

[0177] 37. A charged particle beam apparatus according to clause 35, wherein the asymmetry parameter comprises a CoM diagram.

[0178] 38. A charged particle beam apparatus according to clause 29, wherein the spatial distribution information comprises fewer than 120 detected charged particle arrival locations.

[0179] 39. A charged particle beam apparatus according to clause 38, wherein the spatial distribution information comprises fewer than 50 detected charged particle arrival positions.

[0180] 40. The charged particle beam apparatus of clause 29, wherein the charged particle detector is one of an electron detector or a proton detector.

[0181] 41. A charged particle beam apparatus according to clause 40, wherein the electron detector is one of a four-quadrant segmented detector, a two-half segmented detector, and a pixelated electron counting detector.

[0182] 42. The charged particle beam apparatus of clause 29, wherein the charged particle beam apparatus comprises a scanning electron microscope.

[0183] 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:

[0184] Examining sample surfaces using a charged particle beam system;

[0185] Obtaining first spatial distribution information of the arrival positions of the charged particles detected on the charged particle detector within a first time period;

[0186] obtaining second spatial distribution information of the arrival positions of the detected charged particles on the charged particle detector in a second time period different from the first time period;

[0187] determining a performance parameter of the charged particle beam system based on the first spatial distribution information and the second spatial distribution information; and

[0188] Adjustments to the charged particle system are performed based on the determined performance parameters.

[0189] 44. A charged particle beam method comprising:

[0190] Examining sample surfaces using a charged particle beam system;

[0191] Obtaining first spatial distribution information of the arrival positions of the charged particles detected on the charged particle detector within a first time period;

[0192] obtaining second spatial distribution information of the arrival positions of the detected charged particles on the charged particle detector in a second time period different from the first time period;

[0193] determining a performance parameter of the charged particle beam system according to the first spatial distribution information and the second spatial distribution information;

[0194] Adjustments to the charged particle system are performed based on the determined performance parameters.

[0195] 45. A charged particle beam device comprising:

[0196] a charged particle beam source configured to generate a primary charged particle beam;

[0197] an optical system configured to direct the primary charged particle beam to a sample surface to inspect the sample surface;

[0198] a charged particle detector configured to detect a spatial distribution of charged particles returning from a sample surface;

[0199] A controller comprising one or more processors and configured to cause the charged particle beam device to perform:

[0200] Obtaining first spatial distribution information of the arrival positions of the charged particles detected on the charged particle detector within a first time period;

[0201] obtaining second spatial distribution information of the arrival positions of the detected charged particles on the charged particle detector in a second time period different from the first time period;

[0202] determining a performance parameter of the charged particle beam system based on the first spatial distribution information and the second spatial distribution information; and

[0203] Adjustments to the charged particle system are performed based on the determined performance parameters.

[0204] 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 a method comprising:

[0205] Examining sample surfaces using a charged particle beam system;

[0206] 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 comprises detecting a plurality of charged particles emitted from the sample pixel; and

[0207] A center of mass deviation map is determined for each of the plurality of charged particles emitted from each sample pixel of the plurality of sample pixels.

[0208] 47. A charged particle beam method comprising:

[0209] Examining sample surfaces using a charged particle beam system;

[0210] 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 comprises detecting a plurality of charged particles emitted from the sample pixel; and

[0211] A center of mass deviation map is determined for each of the plurality of charged particles emitted from each sample pixel of the plurality of sample pixels.

[0212] 48. A charged particle beam device comprising:

[0213] a charged particle beam source configured to generate a primary charged particle beam;

[0214] an optical system configured to direct the primary charged particle beam to a sample surface to inspect the sample surface;

[0215] a charged particle detector configured to detect charged particles returning from a sample surface;

[0216] A controller comprising one or more processors and configured to cause the charged particle beam device to perform:

[0217] Detecting a plurality of sample pixels within a field of view of the sample, wherein detecting each of the plurality of sample pixels comprises detecting a plurality of charged particles emitted from the sample pixel; and determining a center of mass deviation map for each of the charged particles emitted from each of the plurality of sample pixels.

[0218] Some embodiments of the present disclosure have been described for an electron beam system (such as a SEM) having an electron detector for detecting the arrival of electrons. However, the present disclosure is not limited thereto. It should be understood that the embodiments disclosed above can be applied to other systems, such as other non-SEM electron beam systems or non-electron-based charged particle beam systems. In addition, it should be understood that other charged particles or other types of electrons are also included within the scope of the present disclosure.

[0219] The block diagrams in the accompanying drawings may illustrate the architecture, functionality and operation of the possible implementation of the system, method and computer hardware or software product according to various exemplary embodiments of the present disclosure. In this regard, each block in the schematic diagram may represent certain arithmetic or logic operations that can be implemented using hardware such as electronic circuits. The block may also represent a module, segment or code portion including one or more executable instructions for implementing a specified logical function. It should be understood that in some alternative implementations, the functions indicated in the block may not occur in the order shown in the figure. For example, two blocks shown in succession may be executed or implemented substantially at the same time, or sometimes two blocks may be executed in reverse order, depending on the functionality involved. Some blocks may also be omitted. It should also be understood that each block in the block diagram and the combination of blocks may be implemented by a dedicated hardware system that performs a specified function or action, or by a combination of dedicated hardware and computer instructions.

[0220] It should be understood that the embodiments of the present disclosure are not limited to the exact configurations described above and illustrated in the accompanying drawings, and that various modifications and changes may be made without departing from the scope thereof. For example, a charged particle inspection system may be only one example of a charged particle beam system consistent with embodiments of the present disclosure.

Claims

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, the method comprising: Examining sample surfaces using a charged particle beam system; Obtaining spatial distribution information of positions reached by detected charged particles on a charged particle detector; determining an asymmetry parameter of the spatial distribution information; and An edge feature on the sample surface is determined based on the asymmetry parameter. 2 . The non-transitory computer readable medium of claim 1 , wherein the asymmetry parameter comprises a localization parameter of the location on the charged particle detector at which the detected charged particles arrive.

3. The non-transitory computer readable medium of claim 2, wherein the localization parameter comprises a deviation of a center of mass (CoM) of the location at which the detected charged particle arrives, the deviation being caused by the edge feature. 4 . The non-transitory computer readable medium of claim 1 , wherein the asymmetry parameter comprises a shape parameter of the location on the charged particle detector where the detected charged particles arrive. 5 . The non-transitory computer readable medium of claim 4 , wherein the shape parameter comprises a deviation in a shape of the location at which the detected charged particles arrive on the charged particle detector, the deviation being caused by the edge feature.

6. The non-transitory computer readable medium of claim 1 , wherein the set of instructions executable by the at least one processor is configured to cause the device to further perform: determining a CoM map based on the asymmetry parameters of the locations detected to be reached by the charged particles; The edge feature is determined based on the CoM map.

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

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

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

10. The non-transitory computer readable medium of claim 1, wherein the spatial distribution information includes fewer than 120 locations where the detected charged particles arrived.

11. The non-transitory computer readable medium of claim 10, wherein the spatial distribution information includes fewer than 50 locations where the detected charged particles arrived.

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

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

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

15. A method for determining edge features on a sample surface, comprising: examining the sample surface using a charged particle beam system; Obtaining spatial distribution information of positions reached by detected charged particles on a charged particle detector; determining an asymmetry parameter of the spatial distribution information; and An edge characteristic of the sample surface is determined based on the asymmetry parameter.

Images