System and method for optimizing sample scanning in a testing system

Abstract

A system and method for optimizing sample scanning. The system and method may include providing a plurality of charged particle beams for scanning a first sample; identifying one or more defective charged particle beams from the plurality of charged particle beams; identifying one or more functional charged particle beams from the plurality of charged particle beams for scanning the first sample; generating a beam map based on the identified one or more defective charged particle beams and the identified one or more functional charged particle beams, wherein the generated beam map excludes the identified one or more defective charged particle beams; and creating a scanning strategy based on the generated beam map for scanning a first or second sample.

Description

Technical Field

[0001] Cross - Reference to Related Applications

[0001] This application claims priority to U.S. Patent Application No. 63 / 464,501, filed May 5, 2023, which is hereby incorporated by reference in its entirety.

[0002]

[0002] The description herein relates to the field of inspection and charged particle systems, and more particularly, to methods for optimizing the scanning of samples in inspection systems.

Background Art

[0003]

[0003] In the manufacturing process of integrated circuits (ICs), unfinished or completed circuit components are manufactured according to design and inspected to ensure no defects. Inspection systems using optical microscopes typically have a resolution up to several hundred nanometers, which is limited by the wavelength of light. As the physical size of IC components continues to shrink to sub - 100 nanometers or even further to sub - 10 nanometers, inspection systems with higher resolution than those using optical microscopes are needed.

[0004]

[0004] Charged particle (e.g., electron) beam microscopes with a resolution of less than 1 nanometer, such as a scanning electron microscope (SEM) or a transmission electron microscope (TEM), function as practical tools for inspecting IC components with feature sizes of sub - 100 nanometers. When using an SEM, electrons of a single primary electron beam or electrons of multiple primary electron beams can be focused on the target location of the wafer during inspection. The primary electrons can interact with the wafer and be backscattered or cause the wafer to emit secondary electrons. The intensity of the electron beam, including backscattered electrons and secondary electrons, can vary based on the characteristics of the internal and external structures of the wafer, thereby indicating whether there are defects in the wafer.

Summary of the Invention

[0005]

[0005] Embodiments of the present disclosure provide systems and methods for optimizing the scanning of samples in an inspection system. In some embodiments, the system, method and non-temporary computer-readable medium may include providing a plurality of charged particle beams for scanning a first sample; identifying one or more defective charged particle beams from the plurality of charged particle beams; identifying one or more functional charged particle beams from the plurality of charged particle beams for scanning the first sample; generating a beam map based on the identified one or more defective charged particle beams and the identified one or more functional charged particle beams, wherein the generated beam map excludes the identified one or more defective charged particle beams; and creating a scanning strategy based on the generated beam map for scanning a first or second sample.

[0006]

[0006] In some embodiments, the system, method and non-temporary computer-readable medium may include scanning a first sample, generating a beammap based on one or more uncharged particle beams of the scan and one or more functionally charged particle beams of the scan, creating a scan strategy based on the generated beammap, and scanning the first or second sample according to the scan strategy.

[0007]

[0007] In some embodiments, the system, method and non-temporary computer-readable medium may include determining that one or more beams of a multibeam system are faulty, determining that one or more beams of the multibeam system are functional, generating a beam map based on the determination that one or more beams are faulty and the determination that one or more beams are functional, and creating a sample scanning strategy based on the generated beam map. [Brief explanation of the drawing]

[0008] [Figure 1]

[0008] This is a schematic diagram showing an exemplary electron beam inspection (EBI) system consistent with embodiments of the present disclosure. [Figure 2A]

[0009] This is a schematic diagram showing an exemplary multibeam system, which is part of the exemplary charged particle beam inspection system shown in Figure 1, consistent with embodiments of the present disclosure. [Figure 2B]

[0010] This is a schematic diagram showing an exemplary single-beam system, which is part of the exemplary charged particle beam inspection system shown in Figure 1, consistent with embodiments of the present disclosure. [Figure 3]

[0011] An exemplary beammap corresponding to a multibeam system consistent with the embodiments of this disclosure is shown. [Figure 4]

[0012] An exemplary missing spot map corresponding to a multibeam system consistent with embodiments of this disclosure is shown. [Figure 5]

[0013] An exemplary structure of an optimized beammap corresponding to a multibeam system consistent with the embodiments of this disclosure is shown. [Figure 6A]

[0014] An exemplary array having position labels, consistent with embodiments of the present disclosure, is shown. [Figure 6B]

[0015] An exemplary optimized beammap consistent with embodiments of the present disclosure is shown. [Figure 6C]

[0016] An exemplary beammap is shown. [Figure 6D]

[0017] An exemplary graph consistent with embodiments of this disclosure is shown. [Figure 7]

[0018] An exemplary process for optimizing sample scanning, consistent with embodiments of this disclosure, is shown. [Modes for carrying out the invention]

[0009]

[0019] Herein, examples will be made in detail with reference to exemplary embodiments shown in the accompanying drawings. The following description will refer to the accompanying drawings, where, unless otherwise noted, the same numbers in different drawings represent the same or similar elements. The implementations described below in the description of exemplary embodiments do not represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with aspects relating to the subject matter enumerated in the accompanying claims. For example, some embodiments will be described in relation to the use of electron beams, but the present disclosure is not limited thereto. Other types of charged particle beams may be applied as well. Furthermore, other imaging systems such as optical imaging, photodetection, X-ray detection, extreme ultraviolet inspection, and deep ultraviolet inspection may be used, which will produce images of the corresponding type.

[0010]

[0020] Electronic devices are constructed from circuits formed on a piece of silicon called a substrate. Many circuits can be formed together on the same piece of silicon, and these are called integrated circuits or ICs. The size of these circuits has decreased dramatically, allowing more circuits to fit on a single substrate. For example, a smartphone IC chip can be as small as a thumbnail yet contain over 2 billion transistors, each transistor being less than 1 / 1000th the thickness of a human hair.

[0011]

[0021] Manufacturing these extremely small ICs is a complex, time-consuming, and expensive process that often involves hundreds of individual steps. An error in just one step can result in a defect in the finished IC, potentially rendering it unusable. Therefore, one of the goals of the manufacturing process is to avoid such defects and maximize the number of functional ICs produced by the process, thereby improving the overall yield of the process.

[0012]

[0022] One factor in improving yield is monitoring the chip fabrication process to ensure that a sufficient number of functional ICs are produced. One method of monitoring the process is to inspect the chip circuit structure at various stages of its formation. Inspection can be performed using a scanning electron microscope (SEM). The SEM can be used to actually "photograph" the wafer structure in order to image these extremely small structures. This image can be used to determine whether the structure was formed properly and also whether the structure was formed in the right place. If there are defects in the structure, the process can be adjusted to make it less likely that the defects will occur again. Defects can be generated at various stages of semiconductor processing. For the reasons mentioned above, it is important to find defects as early, accurately and efficiently as possible.

[0013]

[0023] The operating principle of a scanning electron microscope (SEM) is similar to that of a camera. A camera takes a photograph by receiving and recording the brightness and color of light reflected or emitted from a person or object. A SEM takes a "photograph" by receiving and recording the energy or quantity of electrons reflected or emitted from a structure. Before taking such a "photograph," an electron beam may be projected onto the structure, and when electrons are reflected or emitted ("emitted") from the structure, the SEM's detector can receive and record the energy or quantity of those electrons to generate an image. Some SEMs use a single electron beam to take such a "photograph" (called a "single-beam SEM"), while others use multiple electron beams to take multiple "photographs" of a wafer (called a "multi-beam SEM"). By using multiple electron beams, the SEM projects more electron beams onto the structure to obtain these multiple "photographs," and as a result, more electrons may be emitted from the structure. Therefore, the detector can receive more emitted electrons simultaneously and generate an image of the wafer structure with higher efficiency and at a faster rate.

[0014]

[0024] In a multi-beam inspection system, a certain percentage of the beams become defective during inspection. These inspection systems either generate defective images or no images at all due to the defective beams, resulting in image capture rate loss and missing defects in the sample. For example, beam defects can occur due to particles blocking one or more beams or due to discharge between a microelectromechanical system (MEMS) area and other ground planes in the inspection system, resulting in large spots on the generated image.

[0015]

[0025] However, typical inspection systems are constrained. A typical inspection system cannot re-acquire any image from the position on the sample scanned by the defective beam, resulting in the generation of defective images and remaining defects undetected by the inspection system, thereby reducing the throughput of the inspection system.

[0016]

[0026] The disclosed embodiments provide systems and methods for addressing some or all of these drawbacks by optimizing the scanning of the sample. The disclosed embodiments may include providing a plurality of charged particle beams to a first sample, identifying one or more defective charged particle beams among the plurality of charged particle beams, generating a beam map based on the identified one or more defective charged particle beams, creating a scan strategy based on the beam map, and providing one or more of the charged particle beams among the plurality of charged particle beams to a second sample according to the scan strategy. For example, by identifying one or more defective charged particle beams and generating a corresponding beam map, the inspection system can create a scan strategy such that the area of the sample corresponding to the defective charged particle beam can be scanned by functional charged particle beams.

[0017]

[0027] In some embodiments, the first sample can be a test sample having a predetermined pattern, and the second sample can be an inspection sample. By first scanning the test sample and identifying the defective charged particle beam, a robust scan strategy can be created such that a functional charged particle beam is provided to the inspection sample. Accordingly, the disclosed embodiments can reduce image capture rate loss and identify sample defects during inspection. As a result, the disclosed embodiments can generate higher quality images, detect sample defects, and improve the throughput of the inspection system.

[0018]

[0028] In some embodiments, the first sample can be the second sample. That is, the disclosed embodiments can only scan the sample during inspection. By scanning the sample during inspection and identifying the defective charged particle beam, a high throughput scan strategy can be created such that the area of the inspection sample scanned by the defective charged particle beam can be rescan by the functional charged particle beam. Accordingly, the disclosed embodiments can reduce image capture rate loss and identify sample defects during inspection. As a result, the disclosed embodiments can generate higher quality images, detect sample defects, and improve the throughput of the inspection system.

[0019]

[0029] The relative dimensions of components in the drawings may be exaggerated for clarity. In the following description of the drawings, like or similar reference numerals refer to like or similar components or entities, and only differences regarding individual embodiments are described.

[0020]

[0030] As used herein, unless otherwise specified, the term “or” encompasses all possible combinations, except where impossible. For example, if a component is specified to include A or B, then unless otherwise specified or impossible, the component may include A or B or A and B. As a second example, if a component is specified to include A, B, or C, then unless otherwise specified or impossible, the component may include A, or B, or C, or A and B, or A and C, or B and C, or A, and B, and C.

[0021]

[0031] Without limiting the scope of this disclosure, some embodiments may be described in connection with providing detectors and detection methods in systems utilizing electron beams. However, this disclosure is not limited in that way. Other types of charged particle beams may also be applied. Furthermore, the systems and methods for detection may also be used in other imaging systems such as optical imaging, photon detection, X-ray detection, and ion detection.

[0022]

[0032] Figure 1 shows an exemplary electron beam inspection (EBI) system 100 consistent with embodiments of the present disclosure. The EBI system 100 may be used for imaging. As shown in Figure 1, the EBI system 100 includes a main chamber 101, a loading / locking chamber 102, an electron beam tool 104, and an instrument front-end module (EFEM) 106. The electron beam tool 104 is located within the main chamber 101. The EFEM 106 includes a first loading port 106a and a second loading port 106b. The EFEM 106 may include additional loading ports. The first loading port 106a and the second loading port 106b receive wafer front-opening integrated pods (FOUPs) containing wafers (e.g., semiconductor wafers or wafers made of other materials) or samples to be inspected (wafers and samples may be used interchangeably). A “lot” is a group of wafers that may be loaded for processing as a batch.

[0023]

[0033] One or more robotic arms (not shown) of the EFEM 106 may transport a wafer to the loading / locking chamber 102. The loading / locking chamber 102 is connected to a loading / locking vacuum pump system (not shown) that removes gas molecules from within the loading / locking chamber 102 to a first pressure below atmospheric pressure. After reaching the first pressure, one or more robotic arms (not shown) may transport the wafer from the loading / locking chamber 102 to the main chamber 101. The main chamber 101 is connected to a main chamber vacuum pump system (not shown) that removes gas molecules from within the main chamber 101 to a second pressure below the first pressure. After reaching the second pressure, the wafer is inspected by an electron beam tool 104. The electron beam tool 104 may be a single-beam system or a multi-beam system.

[0024]

[0034] The controller 109 is electronically connected to the electron beam tool 104. The controller 109 may be a computer configured to perform various controls of the EBI system 100. In Figure 1, the controller 109 is shown as being outside the structure, which includes the main chamber 101, the loading / locking chamber 102, and the EFEM 106, but it is understood that the controller 109 may also be part of the structure.

[0025]

[0035] In some embodiments, the controller 109 may include one or more processors (not shown). A processor may be a general-purpose or dedicated electronic device capable of manipulating or processing information. For example, a processor may include any number or any combination of a central processing unit (or "CPU"), a graphics processing unit (or "GPU"), an optical processor, a programmable logic controller, a microcontroller, a microprocessor, a digital signal processor, an intellectual property (IP) core, a programmable logic array (PLA), a programmable array logic (PAL), a generic array logic (GAL), a composite programmable logic device (CPLD), a field-programmable gate array (FPGA), a system-on-a-chip (SoC), an application-specific integrated circuit (ASIC), and any type of circuitry capable of data processing. A processor may also be a virtual processor, comprising one or more processors distributed across multiple machines or devices connected via a network.

[0026]

[0036] In some embodiments, the controller 109 may further include one or more memories (not shown). The memories may be general-purpose or dedicated electronic devices capable of storing code and data accessible by the processor (e.g., via a bus). For example, the memories may include random access memory (RAM), read-only memory (ROM), optical disks, magnetic disks, hard drives, solid-state drives, flash drives, security digital (SD) cards, memory sticks, compact flash (CF) cards, or any number and any combination of any type of storage device. The code may include an operating system (OS) and one or more application programs (or "apps") for a particular task. The memories may also be virtual memory, including one or more memories distributed across multiple machines or devices connected via a network.

[0027]

[0037] Embodiments of the present disclosure may provide a single-charged particle beam imaging system ("single-beam system"). Compared to a single-beam system, a multi-charged particle beam imaging system ("multi-beam system") may be designed to optimize throughput for different scanning modes. Embodiments of the present disclosure provide a multi-beam system with the ability to optimize throughput for different scanning modes by using beam arrays having different geometries and adapted to different throughput and resolution requirements.

[0028]

[0038] Refer here to Figure 2A, a schematic diagram showing an exemplary electron beam tool 104, which includes a multibeam inspection tool that is part of the EBI system 100 of Figure 1, consistent with embodiments of the present disclosure. In some embodiments, the electron beam tool 104 may operate as a single-beam inspection tool that is part of the EBI system 100 of Figure 1. The multibeam electron beam tool 104 (also referred to herein as apparatus 104) includes an electron source 201, a Coulomb aperture plate (or "Gun aperture plate") 271, a focusing lens 210, a source conversion unit 220, a primary projection system 230, a motorized stage 209, and a sample holder 207 supported by the motorized stage 209 for holding a sample 208 to be inspected (e.g., a wafer or photomask). The multibeam electron beam tool 104 may further include a secondary projection system 250 and an electron detection device 240. The primary projection system 230 may include an objective lens 231. The electronic detection device 240 may include a plurality of detection elements 241, 242, and 243. The beam separator 233 and the deflection scanning unit 232 may be positioned inside the primary projection system 230.

[0029]

[0039] The electron source 201, Coulomb aperture plate 271, focusing lens 210, radiation source conversion unit 220, beam separator 233, deflection scanning unit 232, and primary projection system 230 can be aligned with the primary optical axis 204 of the device 104. The secondary projection system 250 and electron detection device 240 can be aligned with the secondary optical axis 251 of the device 104.

[0030]

[0040] The electron source 201 may include a cathode (not shown) and an extractor or anode (not shown). During operation, the electron source 201 is configured to emit primary electrons from the cathode, which are extracted or accelerated by the extractor and / or anode to form a primary electron beam 202 that forms a primary beam crossover (virtual or real) 203.

[0031]

[0041] The primary electron beam 202 can be visualized as being emitted from the primary beam crossover 203. The radiation source conversion unit 220 may include an image forming element array (not shown), an aberration compensator array (not shown), a beam limiting aperture array (not shown), and a pre-bending micro-deflector array (not shown). In some embodiments, the pre-bending micro-deflector array deflects multiple primary beamlets 211, 212, 213 of the primary electron beam 202 so that they are incident perpendicularly to the beam limiting aperture array, the image forming element array, and the aberration compensator array. In some embodiments, the device 104 may operate as a single-beam system so that a single primary beamlet is generated. In some embodiments, the focusing lens 210 is designed to focus the primary electron beam 202 so that it becomes a parallel beam and is incident perpendicularly to the radiation source conversion unit 220. The image forming element array may include one micro-deflector or microlens for each of the primary beamlets 211, 212, and 213 to influence a plurality of primary beamlets 211, 212, and 213 of the primary electron beam 202 and to form a plurality of parallel images (virtual or real images) of the primary beam crossover 203. In some embodiments, the aberration compensator array may include a field curvature compensator array (not shown) and an astigmatism compensator array (not shown). The field curvature compensator array may include a plurality of microlenses to compensate for the field curvature aberration of the primary beamlets 211, 212, and 213. The astigmatism compensator array may include a plurality of micro-astigmatism correctors to compensate for the astigmatism of the primary beamlets 211, 212, and 213. The beam limiting aperture array may be configured to limit the diameter of the individual primary beamlets 211, 212, and 213. Figure 2A shows three primary beamlets 211, 212, and 213 as an example, and it is understood that the source conversion unit 220 can be configured to form any number of primary beamlets. The controller 109 can be connected to various parts of the EBI system 100 in Figure 1, such as the source conversion unit 220, the electron detection device 240, the primary projection system 230, or the motorized stage 209.In some embodiments, the controller 109 may perform various image and signal processing functions, as will be described in more detail below. The controller 109 may also generate various control signals to control the operation of the charged particle beam inspection system.

[0032]

[0042] The focusing lens 210 is configured to focus the primary electron beam 202. The focusing lens 210 may be further configured to adjust the currents of the primary beamlets 211, 212, and 213 downstream of the radiation source conversion unit 220 by changing the focusing force of the focusing lens 210. Alternatively, the currents may be changed by changing the radial size of the beam limiting apertures in the beam limiting aperture array corresponding to the individual primary beamlets. The currents may also be changed by changing both the radial size of the beam limiting apertures and the focusing force of the focusing lens 210. The focusing lens 210 may be an adjustable focusing lens configured such that the position of the first principal plane is movable. The adjustable focusing lens may be configured to be magnetic, as a result, the off-axis beamlets 212 and 213 may irradiate the radiation source conversion unit 220 with a rotation angle. The rotation angle changes with the focusing force of the adjustable focusing lens or the position of the first principal plane. The focusing lens 210 may be a rotation-preventing focusing lens configured to maintain a constant rotation angle while the focusing force of the focusing lens 210 is changed. In some embodiments, the focusing lens 210 may be an adjustable rotation-preventing focusing lens in which the rotation angle does not change when the focusing force and the position of the first principal plane are changed.

[0033]

[0043] The objective lens 231 may be configured to focus beamlets 211, 212, and 213 onto the sample 208 for inspection, and in this embodiment, three probe spots 221, 222, and 223 may be formed on the surface of the sample 208. The Coulomb aperture plate 271 is configured to block peripheral electrons of the primary electron beam 202 during operation to reduce the Coulomb effect. The Coulomb effect can enlarge the size of each of the probe spots 221, 222, and 223 of the primary beamlets 211, 212, and 213, and thus degrade the inspection resolution.

[0034]

[0044] The beam separator 233 may be, for example, a Wien filter including an electrostatic deflector that generates an electrostatic dipole field and a magnetic dipole field (not shown in Figure 2A). When in operation, the beam separator 233 may be configured to exert an electrostatic force on the individual electrons of the primary beamlets 211, 212, and 213 by the electrostatic dipole field. This electrostatic force is equal in magnitude to the magnetic force exerted on the individual electrons by the magnetic dipole field of the beam separator 233, but in the opposite direction. Therefore, the primary beamlets 211, 212, and 213 can pass through the beam separator 233 in at least a substantially straight line at least a substantially zero deflection angle.

[0035]

[0045] The deflection scanning unit 232 is configured to deflect the primary beamlets 211, 212, and 213 to scan probe spots 221, 222, and 223 across individual scan areas in one section of the surface of sample 208 when in operation. In response to the primary beamlets 211, 212, and 213 or probe spots 221, 222, and 223 being incident on sample 208, electrons emerge from sample 208, generating three secondary electron beams 261, 262, and 263. Each of the secondary electron beams 261, 262, and 263 typically contains secondary electrons (with electron energy ≤ 50 eV) and backscattered electrons (with electron energy between 50 eV and the landing energy of the primary beamlets 211, 212, and 213). The beam separator 233 is configured to deflect the secondary electron beams 261, 262, and 263 toward the secondary projection system 250. Next, the secondary projection system 250 focuses the secondary electron beams 261, 262, and 263 onto the detection elements 241, 242, and 243 of the electron detection device 240. The detection elements 241, 242, and 243 are arranged to detect the corresponding secondary electron beams 261, 262, and 263 and generate corresponding signals, which are transmitted to the controller 109 or a signal processing system (not shown) to construct, for example, an image of the corresponding scan area of ​​the sample 208.

[0036]

[0046] In some embodiments, detection elements 241, 242, and 243 detect the corresponding secondary electron beams 261, 262, and 263, respectively, and generate corresponding intensity signal outputs (not shown) to an image processing system (e.g., controller 109). In some embodiments, each detection element 241, 242, and 243 may include one or more pixels. The intensity signal output of a detection element may be the sum of the signals generated by all pixels within the detection element.

[0037]

[0047] In some embodiments, the controller 109 may include an image processing system including an image acquirer (not shown) and storage (not shown). The image acquirer may include one or more processors. For example, the image acquirer may include a computer, server, mainframe host, terminal, personal computer, any kind of mobile computing device and the like, or a combination thereof. The image acquirer may be communicably coupled to the electronic detection device 240 of the apparatus 104 through a medium such as a conductor, optical fiber cable, portable storage medium, IR, Bluetooth, the Internet, a wireless network, wireless communication, or a combination thereof. In some embodiments, the image acquirer may receive signals from the electronic detection device 240 and construct an image. Thus, the image acquirer may acquire an image of sample 208. The image acquirer may also perform various post-processing functions such as contour generation and overlaying indicators onto the acquired image. The image acquirer may be configured to perform adjustments such as brightness and contrast of the acquired image. In some embodiments, the storage may be a storage medium such as a hard disk, flash drive, cloud storage, random access memory (RAM), or other types of computer-readable memory. Storage can be coupled to the image acquirer and used to store scanned raw image data as the original image and to store the processed image.

[0038]

[0048] In some embodiments, the image acquirer may acquire one or more images of a sample based on an imaging signal received from the electronic detection device 240. The imaging signal may correspond to a scanning operation for imaging charged particles. The acquired image may be a single image containing multiple imaging areas. The single image may be stored in storage. The single image may be a source image that can be divided into multiple regions. Each region may contain one imaging area containing features of the sample 208. The acquired image may contain multiple images of a single imaging area of ​​the sample 208, sampled multiple times in time series. The multiple images may be stored in storage. In some embodiments, the controller 109 may be configured to perform image processing steps using multiple images of the same location of the sample 208.

[0039]

[0049] In some embodiments, the controller 109 may include a measurement circuit (e.g., an analog-to-digital converter) to acquire the distribution of detected secondary electrons. The electron distribution data collected during the detection time window, in combination with the corresponding scan path data of each primary beamlet 211, 212, and 213 incident on the wafer surface, can be used to reconstruct an image of the wafer structure under inspection. The reconstructed image can be used to reveal various features of the internal or external structure of sample 208, thereby revealing any defects that may be present in the wafer.

[0040]

[0050] In some embodiments, the controller 109 may control the motorized stage 209 to move the sample 208 during inspection. In some embodiments, the controller 109 may enable the motorized stage 209 to move the sample 208 continuously in a certain direction at a constant speed. In other embodiments, the controller 109 may enable the motorized stage 209 to change the speed at which the sample 208 moves over time in accordance with the steps of the scanning process.

[0041]

[0051] Figure 2A shows that the apparatus 104 uses three primary electron beams, but it is understood that the apparatus 104 may use one, two, or more primary electron beams. This disclosure does not limit the number of primary electron beams used in the apparatus 104. In some embodiments, the apparatus 104 may be a SEM used for lithography. In some embodiments, the electron beam tool 104 may be a single-beam system or a multi-beam system.

[0042]

[0052] For example, as shown in Figure 2B, the electron beam tool 100B (also referred to herein as apparatus 100B) may be a single-beam inspection tool used in an EBI system 10, consistent with embodiments of the present disclosure. Apparatus 100B includes a wafer holder 136 supported by an electric stage 134 to hold a wafer 150 to be inspected. The electron beam tool 100B includes an electron emitter, which may include a cathode 103, an anode 121, and a gun aperture 122. The electron beam tool 100B further includes a beam limiting aperture 125, a focusing lens 126, a column aperture 135, an objective lens assembly 132, and a detector 144. In some embodiments, the objective lens assembly 132 may be a modified SORIL lens and includes a pole piece 132a, a control electrode 132b, a deflector 132c, and an excitation coil 132d. In the imaging process, the electron beam 161 emitted from the tip of the cathode 103 is accelerated by the anode 121 voltage, passes through the gun aperture 122, the beam limiting aperture 125, and the focusing lens 126, and is focused to a probe spot 170 by a modified SORIL lens, which can then collide with the surface of the wafer 150. The probe spot 170 can be scanned across the surface of the wafer 150 by a deflector such as a deflector 132c or another deflector of the SORIL lens. Secondary particles or scattered primary particles, such as secondary electrons or scattered primary electrons emitted from the wafer surface, can be collected by a detector 144 to determine the beam intensity, thereby allowing an image of the target area on the wafer 150 to be reconstructed.

[0043]

[0053] An image processing system 199 including an image acquirer 120, storage 130, and a controller 109 may also be provided. The image acquirer 120 may include one or more processors. For example, the image acquirer 120 may include a computer, server, mainframe host, terminal, personal computer, any kind of mobile computing device, or a combination thereof. The image acquirer 120 may be connected to the detector 144 of the electron beam tool 100B through a medium such as a conductor, fiber optic cable, portable storage medium, IR, Bluetooth, the internet, wireless network, wireless communication, or a combination thereof. The image acquirer 120 may receive signals from the detector 144 and construct an image. Thus, the image acquirer 120 may acquire an image of the wafer 150. The image acquirer 120 may also perform various post-processing functions such as contour generation and overlaying indicators onto the acquired image. The image acquirer 120 may be configured to perform adjustments such as brightness and contrast of the acquired image. The storage 130 may be a storage medium such as a hard disk, random access memory (RAM), cloud storage, or other types of computer-readable memory. The storage 130 may be coupled to the image acquirer 120 and used to store scanned raw image data as the original image and to store the processed image. The image acquirer 120 and the storage 130 may be connected to the controller 109. In some embodiments, the image acquirer 120, the storage 130, and the controller 109 may be integrated together as a single electronic control unit.

[0044]

[0054] In some embodiments, the image acquisition unit 120 may acquire one or more images of a sample based on an imaging signal received from the detector 144. The imaging signal may correspond to a scanning operation for imaging charged particles. The acquired image may be a single image containing multiple imaging areas that may include various features of the wafer 150. The single image may be stored in the storage 130. Imaging may be performed based on imaging frames.

[0045]

[0055] The focusing and illumination optics of an electron beam tool may include or be complemented by electromagnetic quadrupole electron lenses. For example, as shown in Figure 2B, the electron beam tool 100B may include a first quadrupole lens 148 and a second quadrupole lens 158. In some embodiments, the quadrupole lenses are 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.

[0046]

[0056] Figure 2B shows a charged particle beam apparatus in which the inspection system may use a single primary beam that can be configured to generate secondary electrons by interacting with the wafer 150. The detector 144 may be positioned along the optical axis 105, as in the embodiment shown in Figure 2B. The primary electron beam may be configured to move along the optical axis 105. Thus, the detector 144 may include a hole in its center so that the primary electron beam can pass through and reach the wafer 150.

[0047]

[0057] Herein, we refer to Figure 3, an exemplary beammap 300 corresponding to a multibeam system consistent with embodiments of the present disclosure (e.g., the EBI system 100 in Figure 1, the multibeam electron beam tool 104 in Figure 2A). In some embodiments, the multibeam system may generate the beammap 300 during a first scan of a sample, the first scan may include providing a plurality of charged particle beams to the sample. The beammap 300 may show an array 310 corresponding to a plurality of charged particle beams in the multibeam system (e.g., the primary electron beam 202 in Figure 2A). For example, the array 310 may show the layout of the plurality of charged particle beams provided to a sample in the multibeam system (e.g., sample 208 in Figure 2A). In some embodiments, the array 310 may include at least one functional charged particle beam 312 and at least one non-functional charged particle beam 314. In some embodiments, the system may not rescan the sample area if it indicates that the percentage of badly charged particle beams in the array is below a certain threshold (for example, if badly charged particle beams make up less than 5% of the array).

[0048]

[0058] For example, the working charged particle beam 312 may correspond to a charged particle beam that properly scans the sample area, while the defective charged particle beam 314 may correspond to a defective charged particle beam that does not properly scan the sample area (e.g., does not scan at all).

[0049]

[0059] In some embodiments, the system may scan a first sample by providing it with multiple charged particle beams. The first sample may be a test sample having a predetermined pattern, and the second sample may be an inspection sample. For example, the test sample may have a predetermined pattern so that the system can grasp the pattern, and each charged particle beam scans the same feature on the test sample. In some embodiments, the predetermined pattern may be a layout design that can be stored in a layout file for wafer design. The layout file may be in Graphic Database System (GDS) format, Graphic Database System II (GDS II) format, Open Artwork System Interchange Standard (OASIS) format, Caltech Intermediate Format (CIF), etc. The wafer design may include patterns or structures to be included on the wafer. The patterns or structures may be mask patterns used to transfer features from a photolithography mask or reticle to the wafer. In some embodiments, among other things, layouts in GDS or OASIS format may include feature information stored in a binary file format that represents planar geometric shapes, text, and other information relating to the wafer design. In some embodiments, the layout design may correspond to the field of view (FOV) of the inspection system (for example, the FOV of the inspection system may include one or more layout structures in the layout design).

[0050]

[0060] In some embodiments, the system may identify one or more faulty charged particle beams in an array of charged particle beams and generate a beammap 300 based on the one or more identified faulty charged particle beams.

[0051]

[0061] In some embodiments, the system can identify one or more defective charged particle beams by generating a concentration histogram for each charged particle beam in an array of charged particle beams. For example, each pixel in an image of a test sample produced as a result of a functional charged particle beam has a corresponding concentration. Since the pattern on the test sample is predetermined, based on the concentration histogram generated for each charged particle beam, the system can determine whether the image was produced as a result of a functional charged particle beam or whether one of the charged particle beams was defective.

[0052]

[0062] For example, a charged particle beam can be defective as a result of the beam becoming out of focus or being blocked. The beam may become out of focus due to misalignment of MEMS components, or it may be blocked due to one or more components blocking one or more beams. In some cases, a charged particle beam may be defective due to discharge between the MEMS component area and other grounding surfaces in the inspection system, which may result in large spots on the generated image.

[0053]

[0063] In some embodiments, the density across the entire generated image, which is dull, monotonous, or has a gentle (e.g., stepped) gradient, may indicate one or more poorly charged particle beams.

[0054]

[0064] In some embodiments, the system may identify one or more defective charged particle beams by determining the clarity or resolution of the image produced as a result of the array of charged particle beams. For example, an image of a test sample produced as a result of a functional charged particle beam has a corresponding clarity or resolution. Since the pattern on the test sample is predetermined, based on the clarity or resolution of the produced image, the system can determine whether the image was produced as a result of a functional charged particle beam or whether one of the charged particle beams was defective.

[0055]

[0065] In some embodiments, the generated image of a test sample, having a clarity or resolution different from the expected (e.g., known) clarity or resolution, may show one or more defective charged particle beams.

[0056]

[0066] In some embodiments, the system may create a scanning strategy based on a generated beammap 300, the generated beammap 300 corresponding to the beammap of the scanned test sample. In some embodiments, the system may scan a test sample (e.g., sample 208 in Figure 2A, wafer 150 in Figure 2B) by providing the test sample with one or more charged particle beams (e.g., a functional charged particle beam 312, the primary electron beam 202 in Figure 2A, the electron beam 161 in Figure 2B) excluding any defective charged particle beams 314, according to the scanning strategy. In some embodiments, the scanning strategy may include providing one or more charged particle beams to one or more areas of the test sample corresponding to identified defective charged particle beams (e.g., defective charged particle beam 314). That is, the one or more charged particle beams used to scan the test sample may be a subset of the charged particle beams used to scan the test sample, the subset excluding defective charged particle beams so that the test sample is scanned only by functional charged particle beams.

[0057]

[0067] A robust scanning strategy can be created to ensure that a functionally charged particle beam is delivered to the inspection sample by scanning the test sample and identifying the defective charged particle beam before scanning the inspection sample. Thus, embodiments of the disclosure can reduce image capture rate loss and identify sample defects during inspection. As a result, embodiments of the disclosure can produce higher quality images, detect sample defects, and improve the throughput of the inspection system.

[0058]

[0068] In some embodiments, the system may create a scanning strategy based on the generated beammap 300 and a design layout corresponding to a predetermined pattern. For example, based on the layout design, the system may identify high-priority and low-priority areas of the sample. For example, high-priority areas of the sample may be areas of the sample that need to be scanned or inspected more than low-priority areas of the sample. In some embodiments, the system may create a scanning strategy by arranging an array of charged particle beams (e.g., by positioning the array, shifting the array, rotating the array, rearranging the charged particle beams in the array, etc.) such that one or more identified faulty charged particle beams scan (e.g., are aligned with) low-priority areas of the sample during inspection, and one or more identified functional charged particle beams scan (e.g., are aligned with) high-priority areas of the sample during inspection.

[0059]

[0069] In some embodiments, the system may scan a test sample without scanning the test sample or generating a beam map in advance by providing the test sample with multiple charged particle beams. The pattern of the test sample may be unknown to the system. In some embodiments, during the inspection scan of the test sample, the system may identify one or more defective charged particle beams in the array of charged particle beams and generate a beam map 300 based on the one or more identified defective charged particle beams.

[0060]

[0070] In some embodiments, the system may identify one or more defective charged particle beams by generating a concentration histogram for multiple generated images associated with one or more charged particle beams in an array of charged particle beams used during an inspection scan. For example, the system may analyze one or more images from the same charged particle beam to determine whether the concentration histogram is changing across different locations in the inspection sample. Based on the system's analysis of one or more images from one or more charged particle beams, the system can distinguish between functional charged particle beams and any defective charged particle beams.

[0061]

[0071] In some embodiments, a concentration histogram that shows little or no change across different locations on the test sample relative to a charged particle beam may indicate one or more defective charged particle beams.

[0062]

[0072] In some embodiments, the system may identify one or more defective charged particle beams by determining the sharpness or resolution of one or more generated images associated with one or more charged particle beams in an array of charged particle beams used during the inspection scan. For example, an image of an inspection sample generated as a result of a functional charged particle beam has sharp edges (e.g., corresponding to the pattern scanned by the functional charged particle beam). Sharp edges may not be present in an image of an inspection sample generated as a result of a defective charged particle beam.

[0063]

[0073] In some embodiments, the system may create a scan strategy based on the generated beammap 300, the generated beammap 300 corresponding to the beammap of the scanned inspection sample. In some embodiments, the system may scan an inspection sample (e.g., sample 208 in Figure 2A, wafer 150 in Figure 2B) by providing the inspection sample with one or more charged particle beams (e.g., functional charged particle beam 312) excluding any defective charged particle beams 314, according to the scan strategy. In some embodiments, the scan strategy may include rescanning the inspection sample by providing one or more charged particle beams (e.g., primary electron beam 202 of the multi-beam tool 104 in Figure 2A, electron beam 161 of the single-beam tool 100B in Figure 2B) to one or more areas of the inspection sample corresponding to identified defective charged particle beams (e.g., defective charged particle beam 314). In other words, one or more charged particle beams used to rescan the inspection sample may be a subset of the charged particle beams used for the initial scan of the inspection sample, and this subset excludes defective charged particle beams so that the inspection sample is scanned only by functional charged particle beams.

[0064]

[0074] A high-throughput scanning strategy can be created such that by scanning the sample during inspection and identifying the faulty charged particle beam during inspection, areas of the inspection sample scanned with the faulty charged particle beam can be rescanned with the functionally charged particle beam. Thus, embodiments of the disclosure can reduce image capture rate loss and identify defects in the sample during inspection. As a result, embodiments of the disclosure can produce higher quality images, detect defects in the sample, and improve the throughput of the inspection system.

[0065]

[0075] Here, we refer to an exemplary missing spot map 400 corresponding to a multibeam system consistent with embodiments of the present disclosure (e.g., the EBI system 100 in Figure 1, the multibeam electron beam tool 104 in Figure 2A). In some embodiments, the multibeam system may generate the missing spot map 400 based on generated beam maps (e.g., beam map 300 in Figure 3). In some embodiments, the system may generate the missing spot map 400 by arranging multiple generated beam maps within the field of view (FOV). In some embodiments, the missing spot map 400 may include a care area 412 containing the area of ​​a sample (e.g., sample 208 in Figure 2A, wafer 150 in Figure 2B) scanned by a functional charged particle beam (e.g., functional charged particle beam 312 in Figure 3). In some embodiments, the missing spot map 400 may include missing spots 414 corresponding to the area of ​​a sample corresponding to a faulty charged particle beam (e.g., faulty charged particle beam 314 in Figure 3). In other words, the missing spot 414 may correspond to an area of ​​the sample that is not scanned by the charged particle beam due to a fault in the charged particle beam.

[0066]

[0076] In some embodiments, the system may scan a first sample by providing it with multiple charged particle beams. The first sample may be a test sample having a predetermined pattern, and the second sample may be an inspection sample. For example, the test sample may have a predetermined pattern so that the system can grasp the pattern, and each charged particle beam scans the same feature on the test sample. In some embodiments, the predetermined pattern may be a layout design that can be stored in a layout file for wafer design. The layout file may be in GDS format, GDS II format, OASIS format, CIF, etc. The wafer design may include patterns or structures to be included on the wafer. The patterns or structures may be mask patterns used to transfer features from a photolithography mask or reticle to the wafer. In some embodiments, among other things, layouts in GDS or OASIS format may include feature information stored in a binary file format that represents planar geometric shapes, text, and other information relating to the wafer design. In some embodiments, the layout design may correspond to the FOV of the inspection system (for example, the FOV of the inspection system may include one or more layout structures of the layout design).

[0067]

[0077] In some embodiments, the system may identify one or more faulty charged particle beams in an array of charged particle beams, generate a beam map based on the one or more identified faulty charged particle beams, and generate a missing spot map 400 based on the generated beam map.

[0068]

[0078] In some embodiments, the system can identify one or more defective charged particle beams by generating a concentration histogram for each charged particle beam in an array of charged particle beams. For example, each pixel in an image of a test sample produced as a result of a functional charged particle beam has a corresponding concentration. Since the pattern on the test sample is predetermined, based on the concentration histogram generated for each charged particle beam, the system can determine whether the image was produced as a result of a functional charged particle beam or whether one of the charged particle beams was defective.

[0069]

[0079] For example, a charged particle beam can be defective as a result of the beam becoming out of focus or being interrupted. The beam may become out of focus due to misalignment of the MEMS component, or it may be interrupted due to misalignment or one or more particles interrupting one or more beams. In some cases, a charged particle beam may be defective due to discharge between the MEMS component area and other grounding surfaces in the inspection system, which may result in large spots on the generated image.

[0070]

[0080] In some embodiments, the density across the entire generated image, which is dull, monotonous, or has a gentle (e.g., stepped) gradient, may indicate one or more poorly charged particle beams.

[0071]

[0081] In some embodiments, the system may identify one or more defective charged particle beams by determining the clarity or resolution of the image produced as a result of the array of charged particle beams. For example, an image of a test sample produced as a result of a functional charged particle beam has a corresponding clarity or resolution. Since the pattern on the test sample is predetermined, based on the clarity or resolution of the produced image, the system can determine whether the image was produced as a result of a functional charged particle beam or whether one of the charged particle beams was defective.

[0072]

[0082] In some embodiments, the generated image of a test sample, having a clarity or resolution different from the expected (e.g., known) clarity or resolution, may show one or more defective charged particle beams.

[0073]

[0083] In some embodiments, the system may create a scan strategy based on a generated missing spot map 400, the generated missing spot map 400 corresponding to the missing spot map of the scanned test sample. In some embodiments, the system may scan a test sample (e.g., sample 208 in Figure 2A, wafer 150 in Figure 2B) by providing the test sample with one or more charged particle beams (e.g., a functional charged particle beam 312, the primary electron beam 202 in Figure 2A, the electron beam 161 in Figure 2B) excluding any defective charged particle beams (e.g., corresponding to missing spots 414) according to the scan strategy. In some embodiments, the scan strategy may include providing one or more charged particle beams to missing spots 414 corresponding to one or more areas of the test sample corresponding to identified defective charged particle beams. That is, the one or more charged particle beams used to scan the test sample may be a subset of the charged particle beams used to scan the test sample, the subset excluding defective charged particle beams so that the test sample is scanned only by functional charged particle beams.

[0074]

[0084] A robust scanning strategy can be created to ensure that a functionally charged particle beam is delivered to the inspection sample by scanning the test sample and identifying the defective charged particle beam before scanning the inspection sample. Thus, embodiments of the disclosure can reduce image capture rate loss and identify sample defects during inspection. As a result, embodiments of the disclosure can produce higher quality images, detect sample defects, and improve the throughput of the inspection system.

[0075]

[0085] In some embodiments, the system may create a scanning strategy based on the generated missing spot map 400 and a layout design corresponding to a predetermined pattern. For example, based on the layout design, the system may identify high-priority and low-priority areas of the sample. For example, high-priority areas of the sample may be areas of the sample that need to be scanned or inspected more than low-priority areas of the sample. In some embodiments, the system may create a scanning strategy by arranging an array of charged particle beams (e.g., by positioning the array, shifting the array, rotating the array, rearranging the charged particle beams of the array, etc.) such that one or more identified defective charged particle beams scan (e.g., are aligned with) low-priority areas of the sample during inspection, and one or more identified functional charged particle beams scan (e.g., are aligned with) high-priority areas of the sample during inspection.

[0076]

[0086] In some embodiments, the system may scan a test sample without scanning the test sample or generating a beam map in advance by providing the test sample with multiple charged particle beams. The pattern of the test sample may be unknown to the system. In some embodiments, during the inspection scan of the test sample, the system may identify one or more defective charged particle beams in the array of charged particle beams, generate a beam map based on the one or more identified defective charged particle beams, and generate a missing spot map 400 based on the generated beam map.

[0077]

[0087] In some embodiments, the system may identify one or more defective charged particle beams by generating a concentration histogram for multiple generated images associated with one or more charged particle beams in an array of charged particle beams used during an inspection scan. For example, the system may analyze one or more images from the same charged particle beam to determine whether the concentration histogram is changing across different locations in the inspection sample. Based on the system's analysis of one or more images from one or more charged particle beams, the system can distinguish between functional charged particle beams and any defective charged particle beams.

[0078]

[0088] In some embodiments, a concentration histogram that shows little or no change across different locations on the test sample relative to a charged particle beam may indicate one or more defective charged particle beams.

[0079]

[0089] In some embodiments, the system may identify one or more defective charged particle beams by determining the sharpness or resolution of one or more generated images associated with one or more charged particle beams in an array of charged particle beams used during the inspection scan. For example, an image of an inspection sample generated as a result of a functional charged particle beam has sharp edges (e.g., corresponding to the pattern scanned by the functional charged particle beam). Sharp edges may not be present in an image of an inspection sample generated as a result of a defective charged particle beam.

[0080]

[0090] In some embodiments, the system may create a scan strategy based on a generated missing spot map 400, the generated missing spot map 400 corresponding to the missing spot map of the scanned inspection sample. In some embodiments, the system may scan an inspection sample (e.g., sample 208 in Figure 2A, wafer 150 in Figure 2B) by providing the inspection sample with one or more charged particle beams (e.g., functional charged particle beam 312) excluding any defective charged particle beams (e.g., corresponding to missing spots 414) according to the scan strategy. In some embodiments, the scan strategy may include rescanning the inspection sample by providing one or more charged particle beams (e.g., primary electron beam 202 in Figure 2A, electron beam 161 in Figure 2B) to missing spots 414 corresponding to one or more areas of the inspection sample corresponding to identified defective charged particle beams. That is, the one or more charged particle beams used to rescan the inspection sample may be a subset of the charged particle beams used for the initial scan of the inspection sample, the subset excluding defective charged particle beams so that the inspection sample is scanned only by functional charged particle beams.

[0081]

[0091] A high-throughput scanning strategy can be created such that by scanning the sample during inspection and identifying the faulty charged particle beam during inspection, areas of the inspection sample scanned with the faulty charged particle beam can be rescanned with the functionally charged particle beam. Thus, embodiments of the disclosure can reduce image capture rate loss and identify defects in the sample during inspection. As a result, embodiments of the disclosure can produce higher quality images, detect defects in the sample, and improve the throughput of the inspection system.

[0082]

[0092] Herein, we refer to Figure 5, i.e., an exemplary structure 500 of an optimized beammap 530 corresponding to a multibeam system consistent with embodiments of the present disclosure (e.g., the EBI system 100 in Figure 1, the multibeam electron beam tool 104 in Figure 2A). In some embodiments, the multibeam system may generate a beammap 510 during a first scan of a sample, the first scan may include providing a plurality of charged particle beams to the sample. The beammap 510 may show arrays corresponding to a plurality of charged particle beams in the multibeam system (e.g., the primary electron beam 202 in Figure 2A, the array 310 in Figure 3). For example, the beammap 510 may show the layout of a plurality of charged particle beams provided to a sample in the multibeam system (e.g., sample 208 in Figure 2A). In some embodiments, the beammap 510 may include at least one functional charged particle beam 512 (e.g., the functional charged particle beam 312 in Figure 3) and at least one non-functional charged particle beam 514 (e.g., the non-functional charged particle beam 314 in Figure 3).

[0083]

[0093] For example, the functional charged particle beam 512 may correspond to an active charged particle beam that properly scans the sample area, while the non-functional charged particle beam 514 may correspond to a non-functional charged particle beam that does not properly scan the sample area (e.g., does not scan at all).

[0084]

[0094] In some embodiments, the system may scan a first sample by providing it with multiple charged particle beams. The first sample may be a test sample having a predetermined pattern, and the second sample may be an inspection sample. For example, the test sample may have a predetermined pattern so that the system can grasp the pattern, and each charged particle beam scans the same feature on the test sample. In some embodiments, the system may identify one or more faulty charged particle beams in an array of charged particle beams and one or more functional charged particle beams in an array of charged particle beams scanning the test sample. In some embodiments, the system may generate a beammap 510 based on one or more identified faulty charged particle beams and one or more identified functional charged particle beams scanning the test sample.

[0085]

[0095] In some embodiments, the system can identify one or more defective charged particle beams by generating a concentration histogram for each charged particle beam in an array of charged particle beams. For example, each pixel in an image of a test sample produced as a result of a functional charged particle beam has a corresponding concentration. Since the pattern on the test sample is predetermined, based on the concentration histogram generated for each charged particle beam, the system can determine whether the image was produced as a result of a functional charged particle beam or whether one of the charged particle beams was defective.

[0086]

[0096] For example, a charged particle beam can be defective as a result of the beam becoming out of focus or being interrupted. The beam may become out of focus due to misalignment of the MEMS component, or it may be interrupted due to misalignment or one or more particles interrupting one or more beams. In some cases, a charged particle beam may be defective due to discharge between the MEMS component area and other grounding surfaces in the inspection system, which may result in large spots on the generated image.

[0087]

[0097] In some embodiments, the density across the entire generated image, which is dull, monotonous, or has a gentle (e.g., stepped) gradient, may indicate one or more poorly charged particle beams.

[0088]

[0098] In some embodiments, the system may identify one or more defective charged particle beams by determining the clarity or resolution of the image produced as a result of the array of charged particle beams. For example, an image of a test sample produced as a result of a functional charged particle beam has a corresponding clarity or resolution. Since the pattern on the test sample is predetermined, based on the clarity or resolution of the produced image, the system can determine whether the image was produced as a result of a functional charged particle beam or whether one of the charged particle beams was defective.

[0089]

[0099] In some embodiments, the generated image of a test sample, having a clarity or resolution different from the expected (e.g., known) clarity or resolution, may show one or more defective charged particle beams.

[0090]

[0100] In some embodiments, the system may create a scanning strategy based on the generated beammap 510, the generated beammap 510 corresponding to the beammap of the scanned test sample. In some embodiments, the system may scan a test sample (e.g., sample 208 in Figure 2A, wafer 150 in Figure 2B) by providing the test sample with one or more charged particle beams (e.g., a functional charged particle beam 312, the primary electron beam 202 of the multi-beam tool 104 in Figure 2A, the electron beam 161 of the single-beam tool 100B in Figure 2B) excluding any defective charged particle beams 514, according to the scanning strategy. In some embodiments, the scanning strategy may include providing one or more charged particle beams to one or more areas of the test sample corresponding to identified defective charged particle beams (e.g., defective charged particle beam 514). In other words, one or more charged particle beams used to scan the inspection sample may be a subset of charged particle beams used to scan the inspection sample, the subset excluding defective charged particle beams so that the inspection sample is scanned only by functional charged particle beams. In some embodiments, the subset of charged particle beams may exclude defective charged particle beams and some functional charged particle beams.

[0091]

[0101] For example, the system may generate a beammap 515 based on the generated beammap 510. In some embodiments, the beammap 515 may include a functionally charged particle beam 512 and an identified defective charged particle beam 514. In some embodiments, the beammap 515 may include an identified functionally charged particle beam 512a, which may correspond to functionally charged particle beams excluded from the optimized beammap 530. For example, an identified functionally charged particle beam 512a may be excluded from the beammap 520 and consequently from the optimized beammap 530 to minimize overlap of functionally charged particle beams during scanning of the inspection sample.

[0092]

[0102] In some embodiments, the system may generate a beammap 520 containing only functional charged particle beams 512. The system may generate an optimized beammap 530 by arranging multiple beammaps 520 within the FOV to optimize the FOV arrangement of the functional charged particle beams. For example, by excluding identified faulty charged particle beams 514 and excluding identified functional charged particle beams from beammap 520, the system may arrange beammap 520 within the FOV to generate an optimized beammap 530. In some embodiments, the optimized beammap 530 may be used to minimize overlap of functional charged particle beams during scanning of an inspection sample (e.g., when different functional charged particle beams scan the same area of ​​the inspection sample).

[0093]

[0103] A robust scanning strategy can be created to ensure that a functionally charged particle beam is delivered to the inspection sample with minimal overlap by scanning the test sample and identifying the defective charged particle beam before scanning the inspection sample. Thus, embodiments of the disclosure can reduce image capture rate loss and identify sample defects during inspection. As a result, embodiments of the disclosure can produce higher quality images, detect sample defects, and improve the throughput of the inspection system.

[0094]

[0104] Herein, we refer to Figure 6A, an exemplary beam array 610a having position labels, consistent with the embodiments of the present disclosure. The beam array 610a includes position labels 1 to M, where 1 corresponds to a charged particle beam in a first ring at the center of the beam array 610a, and M corresponds to a charged particle beam in a Mth ring on the outer periphery of the beam array 610a. The lower position labels correspond to rings of charged particle beams closer to the center of the beam array 610a. For example, position label 2 corresponds to a charged particle beam in a second ring from the center of the beam array 610a, and position label 3 corresponds to a charged particle beam in a third ring from the center of the beam array 610a.

[0095]

[0105] Beam array 610a may include any number of rings of charged particle beams (e.g., M rings), and it should be understood that the number of rings in the beam array is not limited to the number shown in Figure 6A.

[0096]

[0106] Here, we refer to Figure 6B, an exemplary optimized beammap 630b consistent with the embodiments of the present disclosure.

[0097]

[0107] In some embodiments, the system may generate an optimized beammap (e.g., optimized beammap 530 in Figure 5, optimized beammap 630b in Figure 6B) depending on the location of a faulty charged particle beam (e.g., faulty charged particle beam 314 in Figure 3, faulty charged particle beam 514 in Figure 5) in a multi-beam array (e.g., array 310 in Figure 3). If the faulty charged particle beam is located on the outer edge of the multi-beam array (e.g., location label M on beam array 610a), the system may optimize the scan during inspection by using the generated optimized beammap. The generated optimized beammap can optimize the scan, thereby minimizing the number of areas on the sample that are scanned more than once by the functionally charged particle beam, since in this case the multi-beam arrays may be positioned adjacent to each other within the FOV.

[0098]

[0108] For example, as shown in Figure 6B, the optimized beammap 630b may be generated to compensate for the faulty charged particle beam 614b by superimposing a set of functional beams 616b of a charged particle beam array, which includes the faulty charged particle beam 614b (e.g., if the faulty charged particle beam is on position label M, the M-1 beam will overlap in the generated optimized beammap) and the identified functional charged particle beam 612b (e.g., the identified functional charged particle beam 512a in Figure 5).

[0099]

[0109] In some embodiments, the optimized beammap may be generated according to the following formula.

number

[0100]

[0110] When a defective charged particle beam is on ring N of the beam array and 1 < N ≤ M, the number of functional charged particle beams to be superimposed within the generated optimized beam map can be calculated by the following formula (3). (M - 1)·(M - N + 1) (3)

[0101]

[0111] Here, refer to FIG. 6C, that is, exemplary beam map 630c. When a defective charged particle beam is close to or located at the center of the multi-beam array, the scan may not be optimized by generating a repositioned beam map. For example, when the defective charged particle beam 614c is located at the center of the beam array (e.g., position label 1 in FIG. 6A), the beam map 630c has M 2 for superimposing functional charged particle beams. As shown in FIG. 6C, when a new beam map 630c is generated based on the repositioned multi-beam array with the defective charged particle beam 614c located at the center of the multi-beam array, more areas of the sample are scanned two or more times by the functional charged particle beam 612c during inspection, thereby reducing the inspection throughput. The overlapping areas 640c and 650c correspond to the overlapping functional charged particle beams of the multi-beam array that scan the scan area of the sample two or more times.

[0102]

[0112] In an embodiment where the defective charged particle beam is at the center of the multi-beam array, the scan can be optimized by first scanning the inspection sample with the multi-beam array and then, in a second scan, scanning the area of the sample corresponding to the defective charged particle beam with a single functional charged particle beam (in contrast to the use of the multi-beam tool in the second scan).

[0103]

[0113] For example, returning to Figure 6A, if the faulty charged particle beam is located at position label 1, a multi-beam array may be used to scan the area of ​​the sample corresponding to the functionally charged particle beam within rings 2-M, while a single-beam tool may be used to scan the area of ​​the sample corresponding to position label 1. This method can minimize the number of areas on the sample that are scanned more than once by the functionally charged particle beam, thereby improving inspection throughput.

[0104]

[0114] Here, we refer to Figure 6D, an exemplary graph 600d that is consistent with the embodiments of the present disclosure.

[0105]

[0115] Graph 600d shows axis 610d corresponding to the ring position of the beam array where the faulty charged particle beams (e.g., faulty charged particle beam 314 in Figure 3, faulty charged particle beam 414 in Figure 4, faulty charged particle beam 514 in Figure 5, faulty charged particle beam 614b in Figure 6B, and faulty charged particle beam 614c in Figure 6C) reside (e.g., label positions 1-M in Figure 6A). Graph 600d also includes axis 620d corresponding to the effective scan area of ​​the sample (e.g., the area of ​​the sample scanned by the functionally charged particle beams) when a beam map is generated by positioning the beam array within the FOV.

[0106]

[0116] As shown by Graph 600d, consistent with Figures 6A, 6B, and 6C described above, when the beam array contains a faulty charged particle beam at or near the center of the beam array (e.g., at position label 1 on axis 620d), the effective scan area of ​​the sample is smaller compared to when the beam array has a faulty charged particle beam at or near the outer edge of the beam array (e.g., at position label 31 on axis 620d).

[0107]

[0117] For example, data point 630d may correspond to the effective scan area of ​​a sample when beammap 630c in Figure 6C is used to scan the sample, while data point 640d may correspond to the effective scan area of ​​a sample when beammap 630b in Figure 6B is used to scan the sample.

[0108]

[0118] In some embodiments, the system may generate a beammap by arranging the beam array within the FOV, as described above with respect to Figures 5 and 6B, by calculating the predicted effective scan area based on the identified badly charged particle beam and the identified functionally charged particle beam (e.g., the identified functionally charged particle beam 512a in Figure 5).

[0109]

[0119] For example, if the predicted effective scan area falls below a certain threshold (e.g., below a certain percentage of the effective scan area), the system may not generate a beammap by positioning the beam array within the FOV. For instance, the system might perform a first scan of the inspection sample with a multi-beam array, and then in a second scan, scan the area of ​​the sample corresponding to the faulty charged particle beam with a single functional charged particle beam (e.g., using a multi-beam tool, using a single-beam tool, etc.). Figure 6C, for example, may illustrate an example where the predicted effective scan area falls below a certain threshold.

[0110]

[0120] If the predicted effective scan area exceeds a certain threshold (e.g., a certain percentage of the effective scan area), the system may generate an optimized beammap by positioning the beam array within the FOV. For example, Figures 5 and 6B may illustrate an example where the predicted effective scan area exceeds a certain threshold.

[0111]

[0121] Herein, we refer to Figure 7, an exemplary process 700 for optimizing the scanning of a sample, consistent with the embodiments of the present disclosure.

[0112]

[0122] In a first variant of process 700, step 702 may scan a first sample (e.g., sample 208 in Figure 2A) by providing a plurality of charged particle beams (e.g., primary electron beam 202 in Figure 2A) for scanning the first sample. The first sample may be a test sample having a predetermined pattern, and the second sample may be an inspection sample. For example, the test sample may have a predetermined pattern so that the system can grasp the pattern, and each charged particle beam scans the same feature on the test sample.

[0113]

[0123] In step 704, the system may identify one or more faulty charged particle beams (e.g., faulty charged particle beam 314 in Figure 3, faulty charged particle beam 514 in Figure 5, and faulty charged particle beam 614b in Figure 6B) in the array of charged particle beams (e.g., array 310 in Figure 3).

[0114]

[0124] In step 706, the system may identify one or more functional charged particle beams (e.g., identified functional charged particle beam 512a in Figure 5, identified functional charged particle beam 612b in Figure 6B) of the array of charged particle beams scanning the test sample. In some embodiments, identified functional charged particle beams may correspond to functional charged particle beams excluded from the optimized beammap. For example, some identified functional charged particle beams may be excluded from the optimized beammap to minimize overlap of functional charged particle beams (e.g., the set of functional beams 616b in Figure 6B) during scanning of the test sample.

[0115]

[0125] In step 708, the system may generate a beam map (e.g., beam map 300 in Figure 3, beam map 510 in Figure 5) based on one or more identified faulty charged particle beams and one or more identified functionally charged particle beams, the generated beam map excluding the one or more identified faulty charged particle beams.

[0116]

[0126] In some embodiments, the system can identify one or more defective charged particle beams by generating a concentration histogram for each charged particle beam in an array of charged particle beams. For example, each pixel in an image of a test sample produced as a result of a functional charged particle beam has a corresponding concentration. Since the pattern on the test sample is predetermined, based on the concentration histogram generated for each charged particle beam, the system can determine whether the image was produced as a result of a functional charged particle beam or whether one of the charged particle beams was defective.

[0117]

[0127] For example, a charged particle beam can be defective as a result of the beam becoming out of focus or being interrupted. The beam may become out of focus due to misalignment of the MEMS component, or it may be interrupted due to one or more particles interrupting one or more beams. In some cases, a charged particle beam may be defective due to discharge between the MEMS component area and other grounding surfaces in the inspection system, which may result in large spots on the generated image.

[0118]

[0128] In some embodiments, the density across the entire generated image, which is dull, monotonous, or has a gentle (e.g., stepped) gradient, may indicate one or more poorly charged particle beams.

[0119]

[0129] In some embodiments, the system may identify one or more defective charged particle beams by determining the clarity or resolution of the image produced as a result of the array of charged particle beams. For example, an image of a test sample produced as a result of a functional charged particle beam has a corresponding clarity or resolution. Since the pattern on the test sample is predetermined, based on the clarity or resolution of the produced image, the system can determine whether the image was produced as a result of a functional charged particle beam or whether one of the charged particle beams was defective.

[0120]

[0130] In some embodiments, the generated image of a test sample, having a clarity or resolution different from the expected (e.g., known) clarity or resolution, may show one or more defective charged particle beams.

[0121]

[0131] In some embodiments, as described above in step 706, functionally charged particle beams may be excluded from the optimized beammap to minimize overlap of functionally charged particle beams during scanning of the inspection sample. By excluding identified defective particle beams and identified functionally charged particle beams from the beammap, the optimized beammap may be used to minimize overlap of functionally charged particle beams during scanning of the inspection sample.

[0122]

[0132] In step 710, the system may create a scan strategy based on the generated beammap to scan an inspection sample (e.g., sample 208 of the multi-beam tool 104 in Figure 2A, wafer 150 of the single-beam tool 100B in Figure 2B) by providing one or more charged particle beams (e.g., functional charged particle beam 312 in Figure 3, functional charged particle beam 512 in Figure 5, functional charged particle beam 612b in Figure 6B, primary electron beam 202 in Figure 2A, electron beam 161 in Figure 2B) to the inspection sample, excluding any defective charged particle beams and any identified functional charged particle beams, according to the scan strategy. In some embodiments, the scan strategy may include providing one or more charged particle beams to one or more areas of the inspection sample corresponding to identified defective charged particle beams. In other words, one or more charged particle beams used to scan the test sample may be a subset of charged particle beams used to scan the test sample, and this subset excludes defective charged particle beams so that the test sample is scanned only by functional charged particle beams.

[0123]

[0133] A robust scanning strategy can be created to ensure that a functionally charged particle beam is delivered to the inspection sample with minimal overlap by scanning the test sample and identifying the defective charged particle beam before scanning the inspection sample. Thus, embodiments of the disclosure can reduce image capture rate loss and identify sample defects during inspection. As a result, embodiments of the disclosure can produce higher quality images, detect sample defects, and improve the throughput of the inspection system.

[0124]

[0134] In a second variant of process 700, step 702 allows the system to scan the inspection sample (e.g., sample 208 in Figure 2A) without scanning the test sample or generating a beammap in advance, by providing multiple charged particle beams for scanning the inspection sample. The pattern of the inspection sample may be unknown to the system.

[0125]

[0135] In step 704, during the inspection scan of the inspection sample, the system may identify one or more defective charged particle beams (e.g., defective charged particle beam 314 in Figure 3) in the array of charged particle beams (e.g., array 310 in Figure 3).

[0126]

[0136] In step 706, the system may identify one or more functional charged particle beams in an array of charged particle beams scanning the test sample.

[0127]

[0137] In step 708, the system may generate a beam map (e.g., beam map 300 in Figure 3) based on one or more identified faulty charged particle beams and one or more identified functionally charged particle beams, the generated beam map excluding the one or more identified faulty charged particle beams.

[0128]

[0138] In some embodiments, the system may identify one or more defective charged particle beams by generating a concentration histogram for multiple generated images associated with one or more charged particle beams in an array of charged particle beams used during an inspection scan. For example, the system may analyze one or more images from the same charged particle beam to determine whether the concentration histogram is changing across different locations in the inspection sample. Based on the system's analysis of one or more images from one or more charged particle beams, the system can distinguish between functional charged particle beams and any defective charged particle beams.

[0129]

[0139] In some embodiments, a concentration histogram that shows little or no change across different locations on the test sample relative to a charged particle beam may indicate one or more defective charged particle beams.

[0130]

[0140] In some embodiments, the system may identify one or more defective charged particle beams by determining the sharpness or resolution of one or more generated images associated with one or more charged particle beams in an array of charged particle beams used during the inspection scan. For example, an image of an inspection sample generated as a result of a functional charged particle beam has sharp edges (e.g., corresponding to the pattern scanned by the functional charged particle beam). Sharp edges may not be present in an image of an inspection sample generated as a result of a defective charged particle beam.

[0131]

[0141] In step 710, the system may create a scan strategy based on the generated beammap to scan the inspection sample (e.g., sample 208 in Figure 2A, wafer 150 in Figure 2B) by providing the inspection sample with one or more charged particle beams (e.g., functional charged particle beam 312 in Figure 3) excluding any defective charged particle beams, according to the scan strategy. In some embodiments, the scan strategy may include rescanning the inspection sample by providing one or more charged particle beams (e.g., primary electron beam 202 of the multi-beam tool 104 in Figure 2A, electron beam 161 of the single-beam tool 100B in Figure 2B) to one or more areas of the inspection sample corresponding to identified defective charged particle beams. That is, the one or more charged particle beams used to rescan the inspection sample may be a subset of the charged particle beams used for the initial scan of the inspection sample, the subset excluding defective charged particle beams so that the inspection sample is scanned only by functional charged particle beams. In this variant of process 700, the second sample is the first sample.

[0132]

[0142] A high-throughput scanning strategy can be created such that by scanning the sample during inspection and identifying the faulty charged particle beam during inspection, areas of the inspection sample scanned with the faulty charged particle beam can be rescanned with the functionally charged particle beam. Thus, embodiments of the disclosure can reduce image capture rate loss and identify defects in the sample during inspection. As a result, embodiments of the disclosure can produce higher quality images, detect defects in the sample, and improve the throughput of the inspection system.

[0133]

[0143] Non-temporary computer-readable media may be provided for storing instructions to a processor of an electron beam tool or other system and other systems or components thereof for controlling a server (e.g., controller 109 in Figure 1), consistent with the embodiments of this disclosure. These instructions may enable one or more processors to perform actions such as image processing, data processing, beamlet scanning, graphing, operation of a charged particle beam apparatus or another imaging device to provide operations consistent with those described above with respect to Figures 3-5 and 7. In some embodiments, non-temporary computer-readable media may be provided for storing instructions for a processor to perform steps of process 700. Common forms of non-temporary media include, for example, floppy disks, flexible disks, hard disks, solid-state drives, magnetic tapes or any other magnetic data storage media, compact disk read-only memory (CD-ROM), any other optical data storage media, any physical media having a pattern of holes, random access memory (RAM), programmable read-only memory (PROM) and erasable programmable read-only memory (EPROM), flash EPROM or any other flash memory, non-volatile random access memory (NVRAM), caches, registers, any other memory chips or cartridges, and networked versions of the aforementioned.

[0134]

[0144] Embodiments may be further described using the following clauses. 1. A method for optimizing sample scanning, To provide multiple charged particle beams for scanning the first sample, Identifying one or more defective charged particle beams among multiple charged particle beams, Identifying one or more functional charged particle beams from among multiple charged particle beams scanning the first sample, The method involves generating a beam map based on one or more identified faulty charged particle beams and one or more identified functionally charged particle beams, wherein the generated beam map excludes the one or more identified faulty charged particle beams. To scan the first or second sample, create a scanning strategy based on the generated beammap. A method that includes this. 2. The method according to Clause 1, wherein identifying one or more defective charged particle beams includes generating a concentration histogram for each of the multiple charged particle beams. 3. The method according to Clause 1 or 2, wherein identifying one or more defective charged particle beams includes determining either the clarity or resolution of an image produced as a result of multiple charged particle beams. 4. Identifying one or more defective charged particle beams is the method according to Clause 1, comprising generating a concentration histogram for multiple images associated with a first charged particle beam to determine whether the first charged particle beam is defective. 5. Identifying one or more defective charged particle beams is the method of Clause 1 or 4, comprising determining whether the first charged particle beam is defective by determining either the clarity or resolution of a plurality of images associated with the first charged particle beam. 6. The first sample is a method according to any one of the provisions 1 to 3, having a predetermined pattern. 7. Generating a beammap is the method described in any one of the clauses 1-3 or 6, which excludes a portion of one or more identified functionally charged particle beams. 8. The generated beammap is used to minimize the overlap of functionally charged particle beams during scanning of the second sample, as described in any one of clauses 1-3 or 6-7. 9. The scanning strategy is the method described in any one of the clauses 1-3 or 6-8, which includes scanning a second sample using the generated beammap. 10. The generated beammap is used to maximize the scan of the second sample, as described in any one of the provisions 1-3 or 6-9. 11. The method according to any one of the clauses 1-3 or 6-10, wherein the scanning strategy includes providing a charged particle beam to an area of ​​a second sample corresponding to one or more identified defective charged particle beams. 12. The method according to any one of clauses 1, 4, or 5, wherein the scanning strategy includes providing a charged particle beam to an area of ​​a first sample corresponding to one or more identified defective charged particle beams. 13. A method for optimizing sample scanning, Scanning the first sample, To generate a beammap based on one or more poorly charged particle beams in the scan and one or more functionally charged particle beams in the scan, Creating a scanning strategy based on the generated beammap, Scan the first or second sample according to the scanning strategy. A method that includes this. 14. The method according to clause 13, further comprising identifying one or more defective charged particle beams by generating a concentration histogram for each of the multiple charged particle beams associated with the scan of the first sample. 15. The method according to clause 13 or 14, further comprising identifying one or more defective charged particle beams by determining either the sharpness or resolution of an image produced as a result of multiple charged particle beams associated with scanning a first sample. 16. The method according to clause 13, further comprising identifying one or more defective charged particle beams by generating a concentration histogram for a plurality of images associated with a first charged particle beam to determine whether the first charged particle beam is defective. 17. The method according to clause 13 or 16, further comprising identifying one or more defective charged particle beams by determining whether the first charged particle beam is defective by determining either the sharpness or resolution of a plurality of images associated with the first charged particle beam. 18. The first sample is a method according to any one of the provisions 13 to 15, having a predetermined pattern. 19. Generating a beammap, which excludes one or more identified functionally charged particle beams, as described in any one of the provisions 13-15 or 18. 20. The generated beammap is used to minimize the overlap of functionally charged particle beams during scanning of the second sample, as described in any one of clauses 13-15 or 18-19. 21. The scanning strategy is the method described in any one of the clauses 13-15 or 18-20, which includes scanning a second sample using the generated beammap. 22. The generated beammap is used to maximize the scan of the second sample, as described in any one of clauses 13-15 or 18-21. 23. The method according to any one of clauses 13-15 or 18-22, wherein the scanning strategy includes providing a charged particle beam to an area of ​​a second sample corresponding to one or more identified defective charged particle beams. 24. The method according to any one of clauses 13, 16, or 17, wherein the scanning strategy includes providing a charged particle beam to an area of ​​a first sample corresponding to one or more identified defective charged particle beams. 25. A method for optimizing the scanning of a sample, Determining that one or more beams in a multi-beam system are faulty, Determining one or more beams in a multi-beam system to be functional, A beam map is generated based on the determination that one or more beams are defective and that one or more beams are functional. Creating a sample scanning strategy based on the generated beammap and A method that includes this. 26. Determining one or more beams of a multibeam system to be faulty is the method of Clause 25, which includes generating a concentration histogram for each of the multiple beams associated with the scan of a first sample. 27. Determining one or more beams of a multibeam system to be defective includes determining either the sharpness or resolution of the image produced as a result of the multiple beams associated with scanning a first sample, as described in Clause 25 or 26. 28. The method according to Clause 25, wherein determining one or more beams of a multibeam system is faulty includes generating density histograms for multiple images associated with a first beam to determine whether the first beam is faulty. 29. Determining that one or more beams of a multibeam system are faulty is the method of Clause 25 or 28, which includes determining whether the first beam is faulty by determining either the sharpness or resolution of a plurality of images associated with the first beam. 30. A sample having a predetermined pattern, as described in any one of the provisions 25 to 27. 31. Generating a beammap is the method described in any one of the clauses 25-27 or 30, which excludes one or more portions of a beam that are defective. 32. The generated beammap is used to minimize functional beam overlap during sample scanning, as described in any one of clauses 25-27 or 30-31. 33. A scanning strategy is the method described in any one of the clauses 25-27 or 30-32, which includes scanning a sample using the generated beammap. 34. The generated beammap is used to maximize the scan of the sample, as described in any one of the provisions 25-27 or 30-33. 35. The scanning strategy as described in any one of the clauses 25-27 or 30-33, comprising providing a beam to an area of ​​the sample corresponding to one or more beams determined to be defective. 36. The method of any one of the clauses 25, 28, or 29, wherein the scanning strategy includes providing a beam to an area of ​​the sample corresponding to one or more beams that have been determined to be defective. 37. A system for optimizing sample scanning, To provide multiple charged particle beams for scanning the first sample, Identifying one or more defective charged particle beams among multiple charged particle beams, Identifying one or more functional charged particle beams from among multiple charged particle beams scanning the first sample, The method involves generating a beam map based on one or more identified faulty charged particle beams and one or more identified functionally charged particle beams, wherein the generated beam map excludes the one or more identified faulty charged particle beams. To scan the first or second sample, create a scanning strategy based on the generated beammap. A system including a controller that includes a circuit configured to cause the system to perform a certain action. 38. The system described in Clause 37, wherein identifying one or more defective charged particle beams includes generating a concentration histogram for each of the multiple charged particle beams. 39. The system described in Clause 37 or 38, wherein identifying one or more defective charged particle beams includes determining either the clarity or resolution of an image produced as a result of multiple charged particle beams. 40. The system described in Clause 37, which identifies one or more defective charged particle beams, comprising generating a concentration histogram for multiple images associated with a first charged particle beam to determine whether the first charged particle beam is defective. 41. The system according to Clause 37 or 40, wherein identifying one or more defective charged particle beams includes determining whether the first charged particle beam is defective by determining either the clarity or resolution of a plurality of images associated with the first charged particle beam. 42. The first sample is a system having a predetermined pattern, as described in any one of clauses 37 to 39. 43. A system described in any one of clauses 37-39 or 42 that generates a beammap, which excludes a portion of one or more identified functionally charged particle beams. 44. The generated beammap is used to minimize the overlap of functionally charged particle beams during scanning of the second sample, in a system as described in any one of clauses 37-39 or 42-43. 45. The scanning strategy is one of the systems described in any one of the clauses 37-39 or 42-44, which includes scanning a second sample using the generated beammap. 46. ​​The generated beammap is used to maximize the scan of the second sample in the system described in either clause 37-39 or 42-45. 47. The system described in any one of clauses 37-39 or 42-46, wherein the scanning strategy includes providing a charged particle beam to an area of ​​a second sample corresponding to one or more identified defective charged particle beams. 48. The system according to any one of clauses 37, 40, or 41, wherein the scanning strategy includes providing a charged particle beam to an area of ​​a first sample corresponding to one or more identified defective charged particle beams. 49. A system for optimizing sample scanning, Scanning the first sample, To generate a beammap based on one or more poorly charged particle beams in the scan and one or more functionally charged particle beams in the scan, Creating a scanning strategy based on the generated beammap, Scan the first or second sample according to the scanning strategy. A system including a controller that includes a circuit configured to cause the system to perform a certain action. 50. The system according to Clause 49, further comprising identifying one or more defective charged particle beams by generating a concentration histogram for each of the multiple charged particle beams associated with the scan of the first sample. 51. The system according to Clause 49 or 50, further comprising identifying one or more defective charged particle beams by determining either the sharpness or resolution of an image produced as a result of multiple charged particle beams associated with scanning a first sample. 52. The system according to Clause 49, further comprising identifying one or more defective charged particle beams by generating concentration histograms for multiple images associated with a first charged particle beam to determine whether the first charged particle beam is defective. 53. The system according to Clause 49 or 52, further comprising identifying one or more defective charged particle beams by determining whether the first charged particle beam is defective by determining either the clarity or resolution of a plurality of images associated with the first charged particle beam. 54. The first sample is a system described in any one of clauses 49 to 51, having a predetermined pattern. 55. A system described in any one of clauses 49-51 or 54 that generates a beammap, excluding one or more identified functionally charged particle beams. 56. The generated beammap is used to minimize the overlap of functionally charged particle beams during scanning of the second sample, in a system as described in any one of clauses 49-51 or 54-55. 57. A system described in any one of clauses 49-51 or 54-56, wherein the scanning strategy includes scanning a second sample using the generated beammap. 58. The generated beammap is used to maximize the scan of a second sample in any one of the systems described in clauses 49-51 or 54-57. 59. The system described in any one of clauses 49-51 or 54-58, wherein the scanning strategy includes providing a charged particle beam to an area of ​​a second sample corresponding to one or more identified defective charged particle beams. 60. The system according to any one of clauses 49, 52, or 53, wherein the scanning strategy includes providing a charged particle beam to an area of ​​a first sample corresponding to one or more identified defective charged particle beams. 61. A system for optimizing sample scanning, Determining that one or more beams in a multi-beam system are faulty, Determining one or more beams in a multi-beam system to be functional, A beam map is generated based on the determination that one or more beams are defective and that one or more beams are functional. Creating a sample scanning strategy based on the generated beammap and A system including a controller that includes a circuit configured to cause the system to perform a certain action. 62. Determining one or more beams of a multibeam system as faulty includes generating a concentration histogram for each of the multiple beams associated with the scan of a first sample, as described in Clause 61. 63. The system described in Clause 61 or 62, wherein determining one or more beams of a multibeam system to be defective includes determining either the sharpness or resolution of the image produced as a result of the multiple beams associated with scanning a first sample. 64. Determining that one or more beams in a multibeam system are faulty includes generating density histograms for multiple images associated with a first beam to determine whether the first beam is faulty, as described in Clause 61. 65. Determining that one or more beams in a multibeam system are faulty includes determining whether the first beam is faulty by determining either the sharpness or resolution of a plurality of images associated with the first beam. 66. The sample is a system described in any one of clauses 61 to 63, having a predetermined pattern. 67. A system that generates a beammap, which excludes one or more portions of a beam that are defective, as described in any one of the clauses 61-63 or 66. 68. The generated beammap is used to minimize functional beam overlap during sample scanning, as described in any one of clauses 61-63 or 66-67. 69. The scanning strategy is a system described in any one of clauses 61-63 or 66-68, which includes scanning a sample using the generated beammap. 70. The generated beammap is used to maximize the scan of the sample in any one of the systems described in clauses 61-63 or 66-69. 71. The system described in any one of clauses 61-63 or 66-69, wherein the scanning strategy includes providing a beam to an area of ​​the sample corresponding to one or more beams determined to be defective. 72. The system described in any one of clauses 61, 64, or 65, wherein the scanning strategy includes providing beams to areas of a sample corresponding to one or more beams determined to be defective. 73. A non-temporary computer-readable medium for storing a set of instructions that can be executed by at least one processor of a computing device to cause the computing device to perform a method for optimizing the scanning of samples, wherein the method is: To provide multiple charged particle beams for scanning the first sample, Identifying one or more defective charged particle beams among multiple charged particle beams, Identifying one or more functional charged particle beams from among multiple charged particle beams scanning the first sample, The method involves generating a beam map based on one or more identified faulty charged particle beams and one or more identified functionally charged particle beams, wherein the generated beam map excludes the one or more identified faulty charged particle beams. To scan the first or second sample, create a scanning strategy based on the generated beammap. Non-temporary computer-readable media, including [specific examples of such media]. 74. Identifying one or more defective charged particle beams includes generating a concentration histogram for each of the multiple charged particle beams in a non-temporary computer-readable medium as described in Clause 73. 75. Identifying one or more faulty charged particle beams includes determining either the clarity or resolution of an image produced as a result of multiple charged particle beams, in a non-temporary computer-readable medium as described in Clause 73 or 74. 76. Identifying one or more defective charged particle beams includes generating a concentration histogram for a plurality of images associated with a first charged particle beam to determine whether the first charged particle beam is defective, as described in Clause 73, in a non-temporary computer-readable medium. 77. Identifying one or more defective charged particle beams includes determining whether the first charged particle beam is defective by determining either the clarity or resolution of a plurality of images associated with the first charged particle beam, in a non-temporary computer-readable medium as described in Clause 73 or 76. 78. The first sample is a non-temporary computer-readable medium having a predetermined pattern, as described in any one of clauses 73 to 75. 79. Generating a beammap excludes portions of one or more identified functionally charged particle beams in a non-temporary computer-readable medium as described in any one of clauses 73-75 or 78. 80. The generated beammap is used to minimize the overlap of functionally charged particle beams during scanning of the second sample in a non-temporary computer-readable medium as described in any one of clauses 73-75 or 78-79. 81. A non-temporary computer-readable medium as described in any one of clauses 73-75 or 78-80, wherein the scanning strategy includes scanning a second sample using the generated beammap. 82. The generated beammap shall be used to maximize the scan of the second sample in a non-temporary computer-readable medium as described in any one of clauses 73-75 or 78-81. 83. A non-temporary computer-readable medium as described in any one of clauses 73-75 or 78-82, comprising a scanning strategy that provides a charged particle beam to an area of ​​a second sample corresponding to one or more identified defective charged particle beams. 84. A non-transient computer-readable medium as described in any one of Clauses 73, 76, or 77, comprising a scanning strategy that provides a charged particle beam to an area of ​​a first sample corresponding to one or more identified defective charged particle beams. 85. A non-temporary computer-readable medium for storing a set of instructions that can be executed by at least one processor of a computing device to cause the computing device to perform a method for optimizing the scanning of samples, wherein the method is: Scanning the first sample, To generate a beammap based on one or more poorly charged particle beams in the scan and one or more functionally charged particle beams in the scan, Creating a scanning strategy based on the generated beammap, Scan the first or second sample according to the scanning strategy. Non-temporary computer-readable media, including [specific examples of such media]. 86. A non-temporary computer-readable medium as described in Clause 85, further comprising identifying one or more defective charged particle beams by generating a concentration histogram for each of the multiple charged particle beams associated with the scan of a first sample. 87. A non-temporary computer-readable medium as described in Clause 85 or 86, further comprising identifying one or more defective charged particle beams by determining either the sharpness or resolution of an image produced as a result of multiple charged particle beams associated with scanning a first sample. 88. A non-temporary computer-readable medium as described in Clause 85, further comprising identifying one or more defective charged particle beams by generating density histograms for multiple images associated with a first charged particle beam to determine whether the first charged particle beam is defective. 89. A non-temporary computer-readable medium as described in Clause 85 or 88, further comprising identifying one or more defective charged particle beams by determining whether the first charged particle beam is defective by determining either the clarity or resolution of a plurality of images associated with the first charged particle beam. 90. The first sample is a non-temporary computer-readable medium having a predetermined pattern, as described in any one of the clauses 85 to 87. 91. Generating a beammap excludes one or more identified functionally charged particle beams in a non-temporary computer-readable medium as described in any one of clauses 85-87 or 90. 92. The generated beammap is used to minimize the overlap of functionally charged particle beams during scanning of the second sample in a non-temporary computer-readable medium as described in any one of clauses 85-87 or 90-91. 93. A non-temporary computer-readable medium as described in any one of clauses 85-87 or 90-92, which includes scanning a second sample using the generated beammap. 94. The generated beammap shall be used to maximize the scan of the second sample in a non-temporary computer-readable medium as described in any one of clauses 85-87 or 90-93. 95. A non-transient computer-readable medium as described in any one of clauses 85-87 or 90-94, comprising a scanning strategy that provides a charged particle beam to an area of ​​a second sample corresponding to one or more identified defective charged particle beams. 96. A non-transient computer-readable medium as described in any one of clauses 85, 88, or 89, comprising a scanning strategy that provides a charged particle beam to an area of ​​a first sample corresponding to one or more identified defective charged particle beams. 97. A non-temporary computer-readable medium for storing a set of instructions that can be executed by at least one processor of a computing device to cause the computing device to perform a method for optimizing the scanning of samples, wherein the method is: Determining that one or more beams in a multi-beam system are faulty, Determining one or more beams in a multi-beam system to be functional, A beam map is generated based on the determination that one or more beams are defective and that one or more beams are functional. Creating a sample scanning strategy based on the generated beammap and Non-temporary computer-readable media, including [specific examples of such media]. 98. Determining one or more beams of a multibeam system as faulty includes generating a concentration histogram for each beam of multiple beams associated with a scan of a first sample, in a non-temporary computer-readable medium as described in Clause 97. 99. Determining one or more beams of a multibeam system as faulty includes determining either the sharpness or resolution of an image produced as a result of multiple beams associated with scanning a first sample, as described in a non-temporary computer-readable medium as described in Clause 97 or 98. 100. Determining that one or more beams in a multibeam system are faulty includes generating density histograms for multiple images associated with a first beam to determine whether the first beam is faulty, in a non-temporary computer-readable medium as described in Clause 97. 101. Determining that one or more beams of a multibeam system are faulty includes determining whether the first beam is faulty by determining either the sharpness or resolution of a plurality of images associated with the first beam, as described in the non-temporary computer-readable media of Clause 97 or 100. 102. The sample is a non-temporary computer-readable medium having a predetermined pattern as described in any one of clauses 97 to 99. 103. Generating a beammap excludes one or more defective portions of a beam in a non-temporary computer-readable medium as described in any one of clauses 97-99 or 102. 104. The generated beammap is used to minimize functional beam overlap during sample scanning in a non-temporary computer-readable medium as described in any one of sections 97-99 or 102-103. 105. A scanning strategy, including scanning a sample using a generated beammap, in a non-temporary computer-readable medium as described in any one of clauses 97-99 or 102-104. 106. The generated beammap shall be used to maximize the scan of the sample in a non-temporary computer-readable medium as described in any one of clauses 97-99 or 102-105. 107. A non-temporary computer-readable medium as described in any one of clauses 97-99 or 102-105, wherein the scanning strategy includes providing a beam to an area of ​​the sample corresponding to one or more beams determined to be defective. 108. A non-temporary computer-readable medium as described in any one of clauses 97, 100, or 101, comprising a scanning strategy that provides beams to areas of a sample corresponding to one or more beams determined to be defective. 109. The method according to clause 18, further comprising identifying high-priority areas and low-priority areas of the first sample based on a predetermined pattern. 110. The method according to Clause 109, wherein the scanning strategy includes adjusting the generated beammap such that one or more poorly charged particle beams scan low-priority areas of the second sample and one or more functionally charged particle beams scan high-priority areas of the second sample. 111. The method according to clause 30, further comprising identifying high-priority areas and low-priority areas of a sample based on a predetermined pattern. 112. The method according to Clause 111, wherein the scanning strategy includes adjusting the generated beammap such that one or more faulty beams scan low-priority areas of the sample and one or more functional beams scan high-priority areas of the sample. 113. The system as described in Clause 54, wherein the controller, including the circuit, is configured to cause the system to further identify high-priority areas and low-priority areas of the first sample based on a predetermined pattern. 114. The system as described in Clause 113, wherein the scanning strategy includes adjusting the generated beammap such that one or more poorly charged particle beams scan low-priority areas of the second sample and one or more functionally charged particle beams scan high-priority areas of the second sample. 115. The system as described in Clause 60, wherein the controller, including the circuit, is configured to cause the system to further identify high-priority areas and low-priority areas of a sample based on a predetermined pattern. 116. The scanning strategy of the system described in Clause 115 includes adjusting the generated beammap such that one or more faulty beams scan low-priority areas of the sample, and one or more functional beams scan high-priority areas of the sample. 117. A non-temporary computer-readable medium as described in Clause 90, wherein a set of instructions is executable by at least one processor of a computing device to cause the computing device to further identify high-priority areas and low-priority areas of a first sample based on a predetermined pattern. 118. The scanning strategy includes adjusting the generated beammap such that one or more poorly charged particle beams scan lower priority areas of the second sample, and one or more functionally charged particle beams scan higher priority areas of the second sample, as described in the non-temporary computer-readable media of Clause 117. 119. A non-temporary computer-readable medium as described in Clause 102, wherein the set of instructions is executable by at least one processor of a computing device to cause the computing device to further identify high-priority areas and low-priority areas of a sample based on a given pattern. 120. The scanning strategy includes adjusting the generated beammap so that one or more faulty beams scan lower priority areas of the sample, and one or more functional beams scan higher priority areas of the sample, as described in the non-temporary computer-readable media of Clause 119.

[0135]

[0145] It will be understood that the embodiments of this disclosure are not limited to the structures described above and shown in the attached drawings, and that various modifications and changes can be made without departing from their scope.

Claims

1. A system for optimizing sample scanning, To provide multiple charged particle beams for scanning a first sample, Identifying one or more defective charged particle beams among the plurality of charged particle beams, Identifying one or more functional charged particle beams from the plurality of charged particle beams scanning the first sample, The process involves generating a beam map based on the identified one or more defective charged particle beams and the identified one or more functionally charged particle beams, wherein the generated beam map excludes the identified one or more defective charged particle beams. To scan the first or second sample, a scanning strategy is created based on the generated beammap. A system including a controller that includes a circuit for causing the system to perform the above action.

2. The system according to claim 1, wherein identifying one or more defective charged particle beams includes generating a concentration histogram for each of the plurality of charged particle beams.

3. The system according to claim 1, wherein identifying one or more defective charged particle beams includes determining either the clarity or resolution of an image produced as a result of the plurality of charged particle beams.

4. The system according to claim 1, wherein identifying one or more defective charged particle beams includes generating a concentration histogram for a plurality of images associated with a first charged particle beam to determine whether the first charged particle beam is defective.

5. The system according to claim 1, wherein identifying one or more defective charged particle beams includes determining whether the first charged particle beam is defective by determining either the clarity or resolution of a plurality of images associated with the first charged particle beam.

6. The system according to claim 1, wherein the first sample has a predetermined pattern.

7. The system according to claim 1, wherein generating the beam map excludes a portion of one or more identified functionally charged particle beams.

8. The system according to claim 1, wherein the generated beammap is used to minimize overlap of functionally charged particle beams during scanning of the second sample.

9. The system according to claim 1, wherein the scanning strategy includes scanning the second sample using the generated beammap.

10. The system according to claim 1, wherein the generated beammap is used to maximize the scan of the second sample.

11. The system according to claim 1, wherein the scanning strategy includes providing a charged particle beam to an area of ​​the second sample corresponding to one or more identified defective charged particle beams.

12. The system according to claim 1, wherein the scanning strategy includes providing a charged particle beam to an area of ​​the first sample corresponding to one or more identified defective charged particle beams.

13. A system for optimizing sample scanning, Scanning the first sample, A beam map is generated based on one or more poorly charged particle beams from the scan and one or more functionally charged particle beams from the scan. Creating a scanning strategy based on the generated beammap, Scanning the first or second sample according to the aforementioned scanning strategy A system including a controller that includes a circuit for causing the system to perform the above action.

14. The system according to claim 13, further comprising identifying one or more defective charged particle beams by generating a concentration histogram for each of a plurality of charged particle beams associated with the scan of the first sample.

15. The system according to claim 13, further comprising identifying one or more defective charged particle beams by determining either the sharpness or resolution of an image produced as a result of a plurality of charged particle beams associated with the scan of the first sample.

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