In-SITU detector bandwidth measurement using images of a charged particle system

Abstract

A charged particle beam apparatus includes a charged particle beam source, a charged particle optical system, a charged particle detector, and a controller. The charged particle beam source generates a beam of primary charged particles. The charged particle optical system directs the beam of primary charged particles at a sample surface. The charged particle detector detects secondary charged particles associated with interaction of the primary charged particles with the sample surface. The controller determines an image of the sample surface based on the detected secondary charged particles. The image includes an array of pixels. The controller also determines an autocorrelation function between a signal represented by a line of the pixels and delayed copies of the signal. The controller also determines a bandwidth of the charged particle detector based on the autocorrelation function.

Description

IN-SITU DETECTOR BANDWIDTH MEASUREMENT USING IMAGES OF A CHARGED PARTICLE SYSTEMCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority of US application 63 / 665,991 which was filed on June 28, 2024 and which is incorporated herein in its entirety by reference.FIELD

[0002] The description herein relates to inspection systems, and more particularly, to detectors used for charged particle detection.BACKGROUND

[0003] In manufacturing processes of integrated circuits (ICs), unfinished or finished circuit components are inspected to ensure that they are manufactured according to design and are free of defects. Inspection can be performed using systems such as optical microscopes or charged particle beam microscopes (e.g., a scanning electron microscope (SEM). As the sizes of IC components continue to shrink, accuracy and speed of defect detection become more and more important for yield and throughput. However, imaging resolution and throughput of inspection tools struggle to keep pace with the ever-decreasing feature size of IC components.SUMMARY

[0004] Embodiments of the present disclosure provide a system and method for measuring detector bandwidth of a charged particle detector.

[0005] In some embodiments, a charged particle beam apparatus with in-situ detector bandwidth measurement capability is provided. The charged particle beam apparatus can comprise a charged particle beam source, a charged particle optical system, a charged particle detector, and a controller. The charged particle beam source can generate a beam of primary charged particles. The charged particle optical system can direct the beam of primary charged particles at a sample surface. The charged particle detector can detect secondary charged particles associated with interaction of the primary charged particles with the sample surface. The controller can determine an image of the sample surface based on the detected secondary charged particles. The image can comprise an array of pixels. The controller can also determine an autocorrelation function between a signal represented by a line of the pixels and delayed copies of the signal. The controller can also determine a bandwidth of the charged particle detector based on the autocorrelation function.

[0006] In some embodiments, a non-transitory computer-readable that stores a set of instructions for measuring a bandwidth of a charged particle detector is provided. The instructions are executable by at least one processor of an apparatus to cause the apparatus to perform operations. The operations cancomprise determining an image of a sample surface based on detection of secondary charged particles at a charged particle detector. The image can comprise an array of pixels. The secondary charged particles can be associated with interaction of primary charged particles with the sample surface. The primary charged particles can be associated with a beam of the primary charged particles directed to the sample. The operations can also comprise determining an autocorrelation function between a signal represented by a line of the pixels and delayed copies of the signal. The operations can also comprise determining a bandwidth of the charged particle detector based on the autocorrelation function.

[0007] In some embodiments, a method for measuring a bandwidth of a charged particle detector is provided. The method can comprise determining an image of a sample surface based on detection of secondary charged particles at a charged particle detector. The image can comprise an array of pixels. The secondary charged particles can be associated with interaction of primary charged particles with the sample surface. The primary charged particles can be associated with a beam of the primary charged particles directed to the sample. The method can also comprise determining autocorrelation function between a signal represented by a line of the pixels and delayed copies of the signal. The method can also comprise determining a bandwidth of the charged particle detector based on the autocorrelation function.

[0008] In some embodiments, a charged particle beam apparatus with in-situ detector bandwidth measurement capability is provided. The charged particle beam apparatus can comprise a charged particle beam source, a charged particle optical system, an charged particle detector, and a controller. The charged particle beam source can generate a beam of primary charged particles. The beam can be part of a plurality of beamlets. The charged particle optical system can direct the beam of primary charged particles at a sample surface. The charged particle detector can comprise a plurality of detector sections. A section of the plurality of sections can detect secondary charged particles associated with interaction of the primary charged particles with the sample surface. The controller can determine an image of the sample surface based on the detected secondary charged particles. The image can comprise an array of pixels. The controller can also determine an autocorrelation function between a signal represented by a line of the pixels and delayed copies of the signal. The controller can also determine a bandwidth of the section of the charged particle detector based on the autocorrelation function.

[0009] In some embodiments, a non-transitory computer-readable that stores a set of instructions for measuring a bandwidth of a charged particle detector is provided. The instructions are executable by at least one processor of an apparatus to cause the apparatus to perform operations. The operations can comprise determining an image of a sample surface based on detection of secondary charged particles at a section of a charged particle detector comprising a plurality of sections. The image can comprise an array of pixels. The secondary charged particles can be associated with interaction of primary charged particles with the sample surface. The primary charged particles can be associated with abeam of the primary charged particles directed to the sample. The beam can be part of a plurality of beamlets. The operations can also comprise determining an autocorrelation function between a signal represented by a line of the pixels and delayed copies of the signal. The operations can also comprise determining a bandwidth of the section of the charged particle detector based on the autocorrelation function.

[0010] In some embodiments, a method for measuring a bandwidth of a charged particle detector is provided. The method can comprise determining an image of a sample surface based on detection of secondary charged particles at a section of a charged particle detector comprising a plurality of sections. The image can comprise an array of pixels. The secondary charged particles can be associated with interaction of primary charged particles with the sample surface. The primary charged particles can be associated with a beam of the primary charged particles directed to the sample. The beam can be part of a plurality of beamlets The method can also comprise determining an autocorrelation function between a signal represented by a line of the pixels and delayed copies of the signal. The method can also comprise determining a bandwidth of the section of the charged particle detector based on the autocorrelation function.BRIEF DESCRIPTION OF FIGURES

[0011] The above and other aspects of the present disclosure will become more apparent from the description of exemplary embodiments, taken in conjunction with the accompanying drawings.

[0012] FIG. 1 is a schematic diagram illustrating an exemplary charged-particle beam inspection system, consistent with embodiments of the present disclosure.

[0013] FIG. 2 is a schematic diagram illustrating an exemplary multibeam inspection apparatus, consistent with embodiments of the present disclosure that can be a part of the exemplary charged- particle beam inspection system of FIG. 1.

[0014] FIG. 3A is a schematic diagram illustrating an exemplary structure of a detector, consistent with embodiments of the present disclosure.

[0015] FIG. 3B is a schematic diagram illustrating an exemplary surface of a detector array, consistent with embodiments of the present disclosure.

[0016] FIG. 4 is a schematic diagram illustrating an exemplary detector array with switching elements, consistent with embodiments of the present disclosure.

[0017] FIG. 5A is a graphical representation of exemplary SEM images, consistent with embodiments of the present disclosure.

[0018] FIG. 5B is a schematic representation of a device feature and corresponding detector response, consistent with embodiments of the present disclosure.

[0019] FIG. 6 is a graphical representation illustrating an exemplary featureless region of an SEM image, consistent with embodiments of the present disclosure.

[0020] FIG. 7 is an array representation illustrating an exemplary array of pixels of an SEM image, consistent with embodiments of the present disclosure.

[0021] FIG. 8 is an array representation illustrating an exemplary modified array of pixels of an SEM image, consistent with embodiments of the present disclosure.

[0022] FIG. 9 is an array representation illustrating an exemplary modified array of pixels of an SEM image, consistent with embodiments of the present disclosure.

[0023] FIG. 10 is a graph illustrating an exemplary plot of autocorrelation data with respect to time delay, consistent with embodiments of the present disclosure.

[0024] FIG. 11 is a flowchart of an exemplary method for measuring detector bandwidth of a charged particle detector, consistent with embodiments of the present disclosure.DETAILED DESCRIPTION

[0025] Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the drawings. The following description refers to the accompanying drawings in which the same numbers in different drawings represent the same or similar elements unless otherwise represented. The implementations set forth in the following description of exemplary embodiments do not represent all implementations consistent with the invention. Instead, they are merely examples of apparatuses, systems, and methods consistent with aspects related to subject matter that may be recited in the appended claims. For example, although some embodiments are described in the context of utilizing charged-particle beams (e.g., electron beams), the disclosure is not so limited. Other types of charged particle beams (e.g., proton beams) may be similarly applied. Furthermore, other imaging systems may be used, such as optical imaging, photodetection, x-ray detection, or the like.

[0026] Electronic devices are constructed of circuits formed on a piece of silicon called a substrate. Many circuits may be formed together on the same piece of silicon and are called integrated circuits or ICs. With advancements in technology, the size of these circuits has decreased dramatically so that many more of them can fit on the substrate. For example, an IC chip in a smart phone can be as small as a fingernail and yet may include over 2 billion transistors, the size of each transistor being less than 1 / 1, 000th the width of a human hair.

[0027] Making these ICs with extremely small structures or components is a complex, timeconsuming, and expensive process, often involving hundreds of individual steps. Errors in even one step have the potential to result in defects in the finished IC, rendering it useless. Thus, one goal of the manufacturing process is to avoid such defects to maximize the number of functional ICs made in the process, that is, to improve the overall yield of the process.

[0028] Yield is an important metric that characterizes failure rate in device fabrication, which relates to cost and efficiency. Yield can be defined as a ratio of all the wafers that are produced by a fab to the number of wafers that were introduced to the fab. Or yield can be the number of working chips that survive the device fabrication process performed on a wafer to the number of potential chips thatcan be fabricated from that wafer in the ideal case of zero failure. As some wafers or chips fail during fabrication, the overall yield is less than 100%. For example, to obtain a 75% yield for a 50-step process (where a step can be indicative of the number of layers formed on a wafer), each individual step should have a yield greater than 99.4%. In contrast, if individual steps have a yield of 95%, the compounding errors at each step result in an overall process yield as low as 7-8%. Every wafer or chip lost during fabrication is a sunk cost and lost time for the fab.

[0029] Integral to the making of these ICs with extremely small structures are highly accurate inspection processes, performed in between one or more fabrication steps, to ascertain whether fabrication steps are performing at expected tolerances. Errors in even one step have the potential to result in defects in the finished IC, rendering it useless. A goal of the manufacturing process is to avoid such defects to maximize the number / yield of functional ICs made in the process.

[0030] Inspection can be carried out using a scanning charged-particle microscope (e.g., a scanning electron microscope (SEM). A scanning charged-particle microscope can be used to image extremely small structures of ICs, by capturing an image of the structures on the wafer. The image can be used to determine if the structure was formed properly (e.g., having the expected dimensions and being properly located on the wafer). If the structure is defective, then the process can be adjusted, so the defect is less likely to recur.

[0031] The working principle of a SEM is analogous to that of a camera. A camera takes a picture by receiving and recording intensity of light reflected or emitted from people or objects. SEMs capture images by receiving and recording energies or quantities of electrons reflected or emitted from the structures of the wafer. Similar to how a camera uses a light source (e.g., ambient, sunlight, or a flash), SEMs use an electron source to send a beam(s) of electron to a surface of a wafer that has structures of interest for imaging. The electron beam(s) can be deflected and the wafer can be moved (on a movement stage) so that a plurality of regions of the wafer can be irradiated by the electrons. When the electrons are reflected or emitted (“exiting”) from the structures (e.g., from the wafer surface, from the structures underneath the wafer surface, or both), a detector of the SEM can receive and record the energies or quantities of those electrons to generate an inspection image of the regions of the wafer that were irradiated by electrons.

[0032] Some SEMs use a single electron beam (referred to as a “single-beam SEM”) to capture a single image. Some SEMs use multiple electron beams (referred to as a “multibeam SEM”) to capture multiple sub-images of the wafer in parallel. The multiple sub-images can be viewed separately or stitched together to generate a complete image. Multibeam parallelization is a technique that increases the number of electrons being received at a detector, thereby increasing efficiency and speed of measurement.

[0033] Speed, or throughput, is also an important metric alongside yield. Throughput is a measurable quantity that characterizes the manufacture speed of a fab (e.g., number of IC units produced per unit time). While throughput is a traditionally important metric, it has become even more regarded in viewof recent global chip shortages. As there are multiple steps in the fabrication of a chip device (e.g., for multiple layers), each step can have a characteristic throughput. For an inspection operation among the fabrication steps, throughput can characterize how quickly an inspection process can clear a wafer before moving on to the next wafer. Innovations in the design or functions of inspection tools can increase throughput, or at least resolve problems in another aspect while mitigating adverse impact to throughput.

[0034] To construct an image of a probed region of a wafer, electrons that exit the wafer are received at a detector. A detector can have several performance indicators. One indicator is the “pixel rate,” which is the rate at which pixels of the inspection image are generated. The pixel rate may indicate the digital data processing bandwidth in a digital system, and the maximum pixel rate of a detector may indicate its maximum digital data processing speed. Another indicator is the “analog signal bandwidth” (or “detector bandwidth”), which is the frequency range between the lowest and highest attainable frequency of analog signals. High-frequency analog signals are conducive for resolving details of the inspected structures and for higher throughput. The detector bandwidth indicates the detection capability of the detector and fineness of the inspection results, which is a different performance indicator from the pixel rate. For example, even if the pixel rate is high, the inspection image can still be blurred if the detector bandwidth is low, because some details of the structures can be lost due to the low detector bandwidth and may not be reflected in the SEM image.

[0035] The pixel rate and detector bandwidth can have significant impacts on other performance indicators of the detector, such as a signal-to-noise (“SNR”) ratio or performance capacity (e.g., maximum inspection speed or maximum inspection throughput) of the detector.

[0036] Detector bandwidth presents an additional complication in multibeam systems. A detector surface (or detector face) with an array of sensing elements can be used to detect multiple electron beams. However, depending on where each beam spot (or probe spot) lands on the detector surface, localized detection bandwidths can be different. In other words, different groups of sensing elements on a detector can have different localized detection bandwidths, thereby causing different electron beams distributed across the surface of the detector to illicit different detection performances. For accurate and consistent multibeam measurements, it is desirable that each electron beam be detected with consistent detector parameters. Therefore, it is desirable to have the different bandwidths across the detector be made uniform.

[0037] Localized detection bandwidth adjustments can be achieved by controlling circuitry (e.g., adjusting a tunable capacitor). However, ascertaining the results of bandwidth adjustment via measurement can be challenging.

[0038] Embodiments of the present disclosure provide a system and method to characterize localized detection bandwidth, in situ, without resorting to costly and complex modifications of a scanning charged-particle microscope or using less accurate methods, such as shining a laser on the detector. Inthis manner, sensing element groups can be rapidly and accurately adjusted to enhance detection consistency and accuracy.

[0039] Objects and advantages of the disclosure can be realized by the elements and combinations as set forth in embodiments described herein. However, embodiments of the present disclosure are not necessarily required to achieve such exemplary objects or advantages. Some embodiments can achieve a different feature or enhancement without necessarily achieving any expressly stated object or advantage.

[0040] As used herein, unless specifically stated otherwise, the term “or” encompasses all possible combinations, except where infeasible. For example, if it is stated that a component can comprise A or B, then, unless specifically stated otherwise or infeasible, the component can comprise A, or B, or A and B. As a second example, if it is stated that a component can comprise A, B, or C, then, unless specifically stated otherwise or infeasible, the component can comprise A, or B, or C, or A and B, or A and C, or B and C, or A and B and C.

[0041] Relative dimensions of components in drawings may be exaggerated for clarity. Within the following description of drawings, the same or like reference numbers refer to the same or like components or entities, and only the differences with respect to the individual embodiments are described.

[0042] FIG. 1 illustrates a schematic diagram of an exemplary electron beam inspection (EBI) system 100, consistent with embodiments of the present disclosure. EBI system 100 can be used for imaging. EBI system 100 can comprise a main chamber 101, a load / lock chamber 102, a beam tool 104, and an equipment front end module (EFEM) 106. Beam tool 104 can be located within main chamber 101. EFEM 106 can comprise a first loading port 106a and a second loading port 106b. EFEM 106 can comprise additional loading port(s). First loading port 106a and second loading port 106b can receive wafer front opening unified pods (FOUPs) that contain wafers (e.g., semiconductor wafers or wafers made of other material(s)) or samples to be inspected (wafers and samples may be used interchangeably). The term “lot” can refer to a plurality of wafers that can be loaded for processing as a batch.

[0043] One or more robotic arms (not shown) in EFEM 106 can transport the wafers to load / lock chamber 102. Load / lock chamber 102 can be connected to a load / lock vacuum pump system (not shown) that can evacuate gas molecules in load / lock chamber 102 to reach a first pressure below atmospheric pressure. After reaching the first pressure, one or more robotic arms (not shown) can transport the wafer from load / lock chamber 102 to main chamber 101. Main chamber 101 can be connected to a main chamber vacuum pump system (not shown) that can evacuate gas molecules in main chamber 101 to reach a second pressure below the first pressure. After reaching the second pressure, the wafer can be subject to inspection by beam tool 104. Beam tool 104 can be a singlebeam system or a multibeam system.

[0044] A controller 109 can be electronically connected to beam tool 104. Controller 109 can be a computer configured to execute various controls of EBI system 100. While controller 109 is shown in FIG. 1 as being outside of the structure that includes main chamber 101, load / lock chamber 102, and EFEM 106, in some embodiments, controller 109 can be part of the structure.

[0045] In some embodiments, controller 109 comprises one or more processors (not shown). A processor may be a generic or specific electronic device capable of manipulating or processing information. For example, the processor can comprise a central processing unit (or “CPU”), a graphics processing unit (or “GPU”), an optical processor, a programmable logic controllers, 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 Complex Programmable Logic Device (CPLD), a Field-Programmable Gate Array (FPGA), a System On Chip (SoC), an Application-Specific Integrated Circuit (ASIC), any type circuitry capable of data processing, or any combination of any number thereof. The processor can be a virtual processor. The virtual processor can include one or more processors distributed across multiple machines or devices coupled via a network.

[0046] In some embodiments, controller 109 further comprises one or more memories (not shown). A memory can be a generic or specific electronic device capable of storing instructions, code, or data accessible by the processor (e.g., via a bus). For example, the memory can comprise a random-access memory (RAM), a read-only memory (ROM), an optical disc, a magnetic disk, a hard drive, a solid- state drive, a flash drive, a security digital (SD) card, a memory stick, a compact flash (CF) card, any type of storage device, or any combination of any number thereof. The instructions, code, or data can include an operating system (OS) and one or more application programs (or “apps”) for specific tasks. The memory can be a virtual memory. The virtual memory can include one or more memories distributed across multiple machines or devices coupled via a network.

[0047] FIG. 2 illustrates a schematic diagram of an exemplary beam tool 104 and an image processing system 290 that can be configured for use in EBI system 100 (FIG. 1), consistent with embodiments of the present disclosure.

[0048] Beam tool 104 can be a multibeam device. Beam tool 104 can comprise a charged-particle source 202 configured to emit a primary charged-particle beam 210, a gun aperture 204, a condenser lens 206, a source conversion unit 212, a primary projection optical system 220, a motorized wafer stage 280, a wafer holder 282, a secondary optical system 242, and a charged-particle detection device 244. Primary charged-particle beam 210 can comprise a plurality of beamlets 214, 216, and 218 of primary charged-particle beam 210. Primary projection optical system 220 can comprise a beam separator 222, a deflection scanning unit 226, and an objective lens 228. Charged-particle detection device 244 can comprise detection sub-regions 246, 248, and 250.

[0049] Charged-particle source 202, gun aperture 204, condenser lens 206, source conversion unit 212, beam separator 222, deflection scanning unit 226, and objective lens 228 can be aligned with aprimary optical axis 260 of beam tool 104. Secondary optical system 242 and charged-particle detection device 244 can be aligned with a secondary optical axis 252 of beam tool 104.

[0050] Charged-particle source 202 can emit one or more charged particles, such as electrons, protons, ions, muons, or other particle carrying electric charges. In some embodiments, charged- particle source 202 can be an electron source. For example, charged-particle source 202 can comprise a cathode, an extractor, or an anode. Primary electrons can be emitted from the cathode and extracted or accelerated to form primary charged-particle beam 210 (in this case, a primary electron beam) with a crossover 208 (virtual or real crossover). For simplicity, some embodiments will be described in the context of electrons as the charged-particles. However, it is to be appreciated that any charged particle can be used in any embodiment of this disclosure, not limited to electrons. Primary charged-particle beam 210 can be visualized as being emitted from crossover 208. Gun aperture 204 can block off peripheral charged particles of primary charged-particle beam 210 to reduce Coulomb interactions (or Coulomb effect). The Coulomb effect can cause the size of a probe spot (or beam spot) of an electron beam to increase and blur, thereby reducing resolution.

[0051] Source conversion unit 212 can comprise an array of image-forming elements and an array of beam-limit apertures. The array of image-forming elements can comprise an array of micro-deflectors or micro-lenses. The array of image-forming elements can form a plurality of parallel images (virtual or real) of crossover 208 with a plurality of beamlets 214, 216, and 218 of primary charged-particle beam 210. The array of beam-limit apertures can limit the plurality of beamlets 214, 216, and 218. While three beamlets 214, 216, and 218 are shown in FIG. 2, embodiments of the present disclosure are not so limited. In some embodiments, beam tool 104 can be configured to generate a first number of beamlets. For example, the first number of beamlets can be in a range from 1 to 1000 or from 200- 500. The first number of beamlets can be, for example, 400 beamlets.

[0052] Condenser lens 206 can focus primary charged-particle beam 210. The electric currents of beamlets 214, 216, and 218 downstream of source conversion unit 212 can be varied by adjusting the focusing power of condenser lens 206 or by changing the radial sizes of the corresponding beam-limit apertures within the array of beam-limit apertures. Condenser lens 206 may be an adjustable condenser lens that may be configured so that the position of its first principle plane is movable. The adjustable condenser lens may be configured to be magnetic, which may result in off-axis beamlets 216 and 218 landing on the beamlet-limit apertures with rotation angles. The rotation angles change with the focusing power and the position of the first principal plane of the adjustable condenser lens. In some embodiments, the adjustable condenser lens may be an adjustable anti-rotation condenser lens, which involves an anti-rotation lens with a movable first principal plane. An example of an adjustable condenser lens is further described in U.S. Publication No. 2017 / 0025241, which is incorporated by reference in its entirety.

[0053] Objective lens 228 can focus beamlets 214, 216, and 218 onto a wafer 230 for imaging, and can form a plurality of probe spots 270, 272, and 274 on a surface of wafer 230.

[0054] Beam separator 222 can be a beam separator of Wien filter type, generating an electrostatic dipole field and a magnetic dipole field. The force exerted by the electrostatic dipole field on a charged particle (e.g., an electron) of beamlets 214, 216, and 218 can be substantially equal in magnitude and opposite in a direction to the force exerted on the charged particle by magnetic dipole field. Beamlets 214, 216, and 218 can, therefore, pass straight through beam separator 222 with zero or minimal deflection angle. However, the total dispersion of beamlets 214, 216, and 218 generated by beam separator 222 can also be non-zero. Beam separator 222 can separate secondary charged- particle beams 236, 238, and 240 from beamlets 214, 216, and 218 and direct secondary charged- particle beams 236, 238, and 240 towards secondary optical system 242.

[0055] Deflection scanning unit 226 can deflect beamlets 214, 216, and 218 to scan probe spots 270, 272, and 274 over a surface area of wafer 230. In response to the incidence of beamlets 214, 216, and 218 at probe spots 270, 272, and 274, secondary charged-particle beams 236, 238, and 240 can be emitted from wafer 230. Secondary charged-particle beams 236, 238, and 240 can comprise charged particles (e.g., electrons) with a distribution of energies. For example, secondary charged-particle beams 236, 238, and 240 can be secondary electron beams including secondary electrons (energies < 50 eV) and backscattered electrons (energies between 50 eV and landing energies of beamlets 214, 216, and 218). Secondary optical system 242 can focus secondary charged-particle beams 236, 238, and 240 onto detection sub-regions 246, 248, and 250 of charged-particle detection device 244. Detection sub-regions 246, 248, and 250 can be configured to detect corresponding secondary charged-particle beams 236, 238, and 240 and generate corresponding signals (e.g., voltage, current, or the like) used to reconstruct a scanning charged-particle microscope image (e.g., SEM image) of structures on or underneath the probed surface of wafer 230.

[0056] The generated signals can represent intensities of secondary charged-particle beams 236, 238, and 240 and can be provided to image processing system 290 that is in communication with charged- particle detection device 244, primary projection optical system 220, and motorized wafer stage 280. The movement speed of motorized wafer stage 280 can be synchronized and coordinated with the beam deflections controlled by deflection scanning unit 226, such that the movement of the scanning of probe spots (e.g., probe spots 270, 272, and 274) can orderly cover regions of interests on the wafer 230. The movement of the scanning can be, for example, a raster movement. The parameters of such synchronization and coordination can be adjusted to adapt to different materials of wafer 230. For example, different materials of wafer 230 can have different resistance-capacitance characteristics that can cause different signal sensitivities to the movement of the scanning of the probe spots.

[0057] The intensity of secondary charged-particle beams 236, 238, and 240 can vary according to the external or internal structure of wafer 230, and thus can indicate whether wafer 230 includes defects. Moreover, as discussed above, beamlets 214, 216, and 218 can be projected onto different locations of the top surface of wafer 230, or different sides of local structures of wafer 230, to generate secondary charged-particle beams 236, 238, and 240 that can have different intensities.Therefore, by mapping the intensity of secondary charged-particle beams 236, 238, and 240 with the areas of wafer 230, image processing system 290 can reconstruct an image that reflects the characteristics of internal or external structures of wafer 230.

[0058] In some embodiments, image processing system 290 can include an image acquirer 292, a storage 294, and a controller 296. Image acquirer 292 can comprise one or more processors. For example, image acquirer 292 can comprise a computer, server, mainframe host, terminals, personal computer, any kind of mobile computing devices, or the like, or a combination thereof. Image acquirer 292 can be communicatively coupled to charged-particle detection device 244 of beam tool 104 through a medium such as an electric conductor, optical fiber cable, portable storage media, IR, Bluetooth, internet, wireless network, wireless radio, or a combination thereof. Image acquirer 292 can receive a signal from charged-particle detection device 244. Image acquirer 292 can construct an image (e.g., as a digital representation, an image data file) based on one or more signals from charged- particle detection device 244. Image acquirer 292 can thus acquire scanning charged-particle microscope images of probed regions of wafer 230. Image acquirer 292 can perform various postprocessing functions, such as generating contours that are representative of structures in the image, superimposing indicators on an acquired image, or the like. Image acquirer 292 can perform adjustments of brightness and contrast of acquired images.

[0059] In some embodiments, storage 294 is a storage medium such as a hard disk, flash drive, cloud storage, random access memory (RAM), other types of computer-readable memory, or the like. Storage 294 can be coupled with image acquirer 292. Storage 294 can be used for saving scanned raw image data as original images, as well as post-processed images. Image acquirer 292 and storage 294 can be connected to controller 296. Image acquirer 292, storage 294, and controller 296 can be integrated together as one control unit.

[0060] In some embodiments, image acquirer 292 acquires one or more scanning charged-particle microscope images of a wafer based on one or more imaging signals received from charged-particle detection device 244. An imaging signal can correspond to a scanning operation for conducting charged-particle imaging. An acquired image can be a single image comprising a plurality of imaging areas or an image of an imaging area. The single image can be stored in storage 294. The single image can be an original image that is divided into a plurality of regions. Each of the regions can comprise one imaging area containing a feature of wafer 230. The acquired images can comprise multiple images of a single imaging area of wafer 230 sampled multiple times over a time sequence. The multiple images can be stored in storage 294. In some embodiments, image processing system 290 performs image processing steps with the multiple images of the same location of wafer 230.

[0061] In some embodiments, image processing system 290 comprises measurement circuits (e.g., analog-to-digital converters) to obtain a distribution of the detected secondary charged particles (e.g., secondary electrons). The charged-particle distribution data collected during a detection time window, in combination with corresponding scan path data of beamlets 214, 216, and 218 incident on the wafersurface, can be used to reconstruct images of the wafer structures under inspection. The reconstructed images can be used to reveal various features of the internal or external structures of wafer 230, and thereby can be used to reveal defects in the wafer.

[0062] In some embodiments, when electrons of primary charged-particle beam 210 are projected onto a surface of wafer 230 (e.g., probe spots 270, 272, and 274), the electrons of primary charged- particle beam 210 can penetrate the surface of wafer 230 for a certain depth to interact with deeper matter in wafer 230. Some electrons of primary charged-particle beam 210 can elastically interact with (e.g., in the form of elastic scattering or collision) the materials of wafer 230. Electrons can be reflected or recoiled out of the surface of wafer 230. An elastic interaction conserves the total kinetic energies of the bodies (e.g., electrons of primary charged-particle beam 210) of the interaction, in which the kinetic energy of the interacting bodies does not convert to other forms of energy (e.g., heat, electromagnetic energy, or the like). Such reflected electrons generated from elastic interaction may be referred to as backscattered electrons (BSEs).

[0063] In some embodiments, some electrons of primary charged-particle beam 210 inelastically interact with (e.g., in the form of inelastic scattering or collision) the materials of wafer 230. An inelastic interaction does not conserve the total kinetic energies of the bodies of the interaction, in which some or all of the kinetic energy of the interacting bodies convert to other forms of energy. For example, through the inelastic interaction, the kinetic energy of some electrons of primary charged- particle beam 210 can cause electron excitation and transition of atoms of the materials. Such inelastic interaction can also generate electrons that exit the surface of wafer 230, which may be referred to as secondary electrons (SEs). Yield or emission rates of BSEs and SEs can depend on, e.g., the material under inspection and the landing energy of the electrons of primary charged-particle beam 210 landing on the surface of the material, among others. The energy of the electrons of primary charged- particle beam 210 can be imparted in part by its acceleration voltage (e.g., the acceleration voltage between the anode and cathode of charged-particle source 202 in FIG. 2). The quantity of BSEs and SEs can be more or fewer (or even the same) than the injected electrons of primary charged-particle beam 210.

[0064] The images generated by SEM can be used for defect inspection. For example, a generated image of a test device region of a wafer can be compared with a reference image that corresponds to the same test device region. The reference image can be predetermined (e.g., by simulation) and include no known defect. If a difference between the generated image and the reference image exceeds a tolerance level, a potential defect can be identified. For another example, the SEM can scan multiple regions of the wafer, each region including a test device region designed as the same, and generate multiple images capturing those test device regions as manufactured. The multiple images can be compared with each other. If a difference between the multiple images exceeds a tolerance level, a potential defect can be identified.

[0065] In some embodiments, charged particle implementations described herein can be modified to use photons instead, for example, such as light in the visible, UV, DUV, EUV, x-ray, or any other wavelength range. For example, in a photon embodiment, a secondary beam spot can refer to reflected, refracted, diffracted or scattered light from a sample upon which a primary light beam is incident. Therefore, while detectors in the present disclosure may be described in the context of electron detection, some embodiments of the present disclosure can be directed to detecting other charged particles or photons.

[0066] FIG. 3A illustrates a schematic diagram of an exemplary structure of a detector 300A, consistent with embodiments of the present disclosure. Detector 300A can be provided as charged- particle detection device 244 (FIG. 2). Detector 300A can comprise a sensor layer 301, a section layer 302, and a readout layer 303. Sensor layer 301 can comprise a sensor die made up of multiple sensing elements, including sensing elements 311, 312, 313, and 314 (though four sensing elements are expressly numbered, it is to be appreciated that fewer or more sensing elements can be implemented).

[0067] In some embodiments, multiple sensing elements can be provided as an array of sensing elements. Sensing elements can have a uniform size, shape, and arrangement. The arrangement of components of detector 300 A can be described with respect to a coordinate axis reference frame (nonlimiting example coordinates). Sensor layer 301 can be arranged along an x-y plane. Sensing elements in sensor layer 301 can be arrayed in x-axis and y-axis directions. The x-axis direction can be referred to as a “horizontal” direction. The y-axis direction can be referred to as a “vertical” direction. Detector 300A can have a layer structure in which sensor layer 301, section layer 302, and section layer are stacked in a z-axis direction. The z-axis direction can also herein be referred to as a “thickness” direction. The z-axis direction can be aligned with a direction of incidence of charged particles that are directed toward detector 300A.

[0068] Section layer 302 can comprise multiple sections, for example, sections 321, 322, 323, and 324 (more or fewer sections can be implemented). The sections can comprise interconnections (e.g., wiring paths) configured to communicatively couple the multiple sensing elements. The sections can comprise switching elements for controlling the communicative couplings between the sensing elements. The sections can comprise connection mechanisms (e.g., wiring paths and switching elements) between the sensing elements and one or more common nodes in section layer 302. In the example of FIG. 3A, section 323 can be configured to communicatively couple to outputs of sensing elements 311, 312, 313, and 314, as shown by the four dashed lines between sensor layer 301 and section layer 302. In some embodiments, section 323 can be configured to output combined signals gathered from sensing elements 311, 312, 313, and 314 as a common output. A section can be communicatively coupled to sensing elements placed directly above the section (e.g., section 323 coupled to sensing elements 311, 312, 313, and 314 directly above). Section 323 can have a grid of terminals configured to connect with the outputs of sensing elements 311, 312, 313, and 314. Sections 321, 322, 323, and 324 can be provided as an array structure. Sections 321, 322, 323, and 324 canhave a uniform size, shape, and arrangement. Sections 321, 322, 323, and 324 can be square shaped, for instance.

[0069] In some embodiments, an isolation area is provided between adjacent sections to electrically insulate sections from one another. In some embodiments, sections can be arranged in an offset pattern, such as a tile layout.

[0070] In some embodiments, readout layer 303 comprises signal processing circuits for processing outputs of the sensing elements. Signal processing circuits can correspond with each of the sections of section layer 302. Multiple separate signal processing circuitry sections can be provided, for example, processing circuitry sections 331, 332, 333, and 334. The signal processing circuitry sections can be provided as an array of sections. The signal processing circuitry sections can have a uniform size, shape, and arrangement. The signal processing circuitry sections can be configured to connect with an output from corresponding sections of section layer 302. In the example of FIG. 3A, signal processing circuitry section 333 can be configured to communicatively couple to an output of section 323, as shown by the dashed line between section layer 302 and readout layer 303.

[0071] In some embodiments, readout layer 303 can comprise input and output terminals. Output(s) of readout layer 303 can be connected to a component for reading and interpreting the output of detector 300 A. For example, readout layer 303 can be directly connected to a digital multiplexer, digital logic block, controller, computer, or the like.

[0072] The sizes of sections and the number of sensing elements associated with a section can be adjusted to suit different applications. For example, while FIG. 3A illustrates a 2x2 array of four sensing elements in one section, embodiments of the disclosure are not so limited. In some embodiments, a section can comprise a 3x3, 4x4, 5x5, 6x6, 2x4, or 1x6 array, or any other suitable arrangement of arrayed elements.

[0073] While FIG. 3A illustrates sensor layer 301, section layer 302, and readout layer 303 as multiple discrete layers, it is noted that sensor layer 301, section layer 302, and readout layer 303 need not be provided as separate substrates. For example, a wiring path of section layer 302 can be provided in a sensor die including the multiple sensing elements or can be provided outside of the sensor die. Wiring paths can be patterned on sensor layer 301. Section layer 302 can be combined with readout layer 303. For example, a semiconductor die can comprise wiring paths of section layer302 and signal processing circuits of readout layer 303. Thus, structures and functionalities of the different layers can be combined or divided.

[0074] In some embodiments, a detector can be provided in a two-die configuration. However, embodiments of the present disclosure are not so limited. For example, functions of a sensor layer, section layer, and readout layer can be implemented in one die or in a package that contains one or more dies.

[0075] In some embodiments, arrangements of sensor layer 301, section layer 302, and readout layer303 can correspond with one another in a stacked relationship. For example, section layer 302 can bemounted directly on top of readout layer 303, and sensor layer 301 can be mounted directly on top of section layer 302. The layers can be stacked such that sections within section layer 302 are aligned with signal processing circuitry sections (e.g., sections 331, 332, 333, and 334) of readout layer 303. Furthermore, the layers may be stacked such that one or more sensing elements within sensor layer 301 are aligned with a section in section layer 302. Sensing elements to be associated with a section can be contained within the section. For example, in a plan view of detector 300A, sensing elements (e.g., sensing elements 311, 312, 313, and 314) of a section (e.g., section 323) can fit within a boundary defined by the corresponding section. Furthermore, individual sections of section layer 302 can overlap with signal processing circuitry sections of readout layer 303. In this manner, predefined areas can be established for associating sensing elements with sections and signal processing circuitry.

[0076] FIG. 3B illustrates a schematic diagram of an exemplary structure of a sensor surface 300B that can form a surface of charged-particle detection device 244 (FIG. 2), consistent with embodiments of the present disclosure. Sensor surface 300B can be provided with multiple sections of sensing elements, including sections 340, 350, 360, and 370, which are represented by the dashed lines. Sensor surface 300B can be the surface of sensor layer 301 in FIG. 3A. Each section can receive at least a part of a beam of charged particles emitted from a particular location from wafer 230, such as one of secondary charged-particle beams 236, 238, and 240 as shown in FIG. 2.

[0077] In some embodiments, sensor surface 300B comprises an array of sensing elements, for example, sensing elements 325, 326, and 327 (more or fewer sensing elements can be implemented). Each of sections 340, 350, 360, and 370 can contain one or more sensing elements. For example, section 340 can contain a first plurality of sensing elements, and section 350 can contain a second plurality of sensing elements, and so on. The first plurality of sensing elements and the second plurality of sensing elements can be mutually exclusive. In the example of FIG. 3B, each of sections 340, 350, 360, and 370 comprises a 6x6 array of sensing elements. In some embodiments, a sensing element can be a diode or any element similar to a diode that can convert incident energy into a measurable signal. For example, the sensing elements can include a PIN diode, an avalanche diode, an electron multiplier tube (EMT), or other components.

[0078] In some embodiments, an area 380 can be provided between adjacent sensing elements. Area 380 can be an isolation area to isolate the sides or comers of neighboring sensing elements from one another. Area 380 can comprise an insulating material that is different from that of the sensing elements of sensor surface 300B. Area 380 can be provided as a square. Some embodiments can omit implementation of area 380.

[0079] In some embodiments, a field programmable detector array can be provided with sensing elements having switching regions integrated between the sensing elements. For example, detectors can be provided such as some of those examples discussed in PCT Application No. PCT / EP2018 / 074833, filed on September 14, 2018, the content of which is incorporated herein by reference in its entirety. In some embodiments, a switching region can be provided between sensingelements so that some of the sensing elements are grouped when covered by the same charged-particle beam spot. Circuits for controlling the switching regions can be included in the signal processing circuits of the readout layer (e.g., readout layer 303 in FIG. 3A). As used throughout the present disclosure, the expression “group” of sensing elements can refer to sensing elements that are associated with one beam spot projected on a detector surface (e.g., within the boundary of the beam spot). A “switch matrix” can refer to all or part of a network of switching elements within a detector architecture configured to selectively connect the various elements and wiring paths in a detector and related control circuitry.

[0080] FIG. 4 illustrates a schematic diagram of an exemplary detector array 400 with switching elements, consistent with embodiments of the present disclosure. The architecture of FIG. 4 can be implemented with a multibeam inspection tool (e.g., beam tool 104 in FIG. 2), as well as with a single-beam inspection tool. Detector array 400 can be a more detailed implementation of detector 300A in FIG. 3A. Detector array 400 can comprise a sensor layer, a section layer, and a readout layer (e.g., sensor layer 301, section layer 302, and readout layer 303 in FIG. 3A). The sensor layer of detector array 400 can comprise multiple sensing elements, for example, sensing elements 311, 312, 313, and 314 (more or fewer sensing elements can be implemented). The sensing elements of detector array 400 can have a uniform size, shape, and arrangement. The sensing elements of detector array 400 can generate an electric current signal commensurate with the charged particles (e.g., electrons exiting from a wafer) received in the active areas of the sensing elements. The term “active areas” can refer to areas of the sensing elements having radiation sensitivity above a predetermined threshold value.

[0081] The section layer of detector array 400 can comprise a base substrate (e.g., a semiconductor substrate) comprising one or more wiring paths 402. Wiring paths 402 can be configured to communicatively couple the sensing elements of detector array 400. Detector array 400 can comprise a section 321 having sensing elements, for example, sensing elements 311, 312, 313, and 314. The sensing elements can have a 4x4 array arrangement. The section layer of detector array 400 can comprise inter-element switching elements 315 between any two adjacent sensing elements. The section layer of detector array 400 can comprise inter-element switching elements 315 communicatively coupled to edges of neighboring sensing elements. Wiring paths 402 can be configured to communicatively couple to outputs of sensing elements (e.g., sensing elements 311, 312, 313, and 314) in section 321. For example, wiring paths 402 can comprise a grid of terminals (shown as round black dots at the centers of the sensing elements) configured to connect with the outputs of sensing elements 311, 312, 313, and 314.

[0082] In some embodiments, wiring paths 402 are provided in the section layer of detector array 400. Wiring paths 402 can be communicatively coupled to the above sensing elements (e.g., sensing elements 311, 312, 313, and 314). Element-bus switching elements 316 can be provided between theoutputs of the sensing elements and wiring paths 402. Element-bus switching elements 316 can be provided in the section layer of detector array 400.

[0083] In some embodiments, wiring paths 402 can comprise lines of conductive material printed on the base substrate, flexible wires, bonding wires, or the like. Switching elements can be provided so that outputs of individual sensing elements can be connected or disconnected with the common output of section 321. The section layer of detector array 400 can comprise corresponding circuits for controlling the switching elements. Switching elements can be provided in a separate switch-element matrix that can itself comprise circuits for controlling the switching elements.

[0084] The readout layer of detector array 400 can comprise signal conditioning circuits for processing outputs of the sensing elements. The signal conditioning circuits can convert the generated current signal into a voltage that represents the intensity of received electrons associated with a beam spot. The signal conditioning circuits can have an amplification function to amplify the current signal. The signal conditioning circuit may include, for example, an amplifier 404 and one or more analog switching elements. The amplifier 404 can be a high speed transimpedance amplifier (TIA), a current amplifier, or the like. Amplifier 404 can be communicatively coupled to the common output of section 321 for amplifying the output signals of the sensing elements of section 321.

[0085] In some embodiments, amplifier 404 is a single-stage or a multi-stage amplifier. In an example of a multi-stage amplifier implementation, amplifier 404 can comprise a pre-amplifier and a post-amplifier, or comprise a front-end stage and a post stage, or the like.

[0086] In some embodiments, amplifier 404 can be a variable gain amplifier, such as a variable gain transimpedance amplifier (VGTIA), a variable gain charge transfer amplifier (VGCTA), or the like. The conditioning circuit can be coupled to a signal path that includes, for example, an analog-to- digital converter (ADC) 406. ADC 406 can be communicatively coupled to the output of the conditioning circuit (e.g., including amplifier 404) to convert the analog output signals of the sensing elements of section 321 to digital signals. The readout layer of detector array 400 can comprise other circuits for other functions. For example, the readout layer of detector array 400 can comprise switchelement actuating circuits to control the switching elements between the sensing elements. The signal path between the sensing elements and ADC 406 can be referred to as an “analog signal path.” For example, the analog signal path in the example of FIG. 4 includes the above-described signal conditioning circuit (e.g., including amplifier 404). The input of the analog signal path is communicatively coupled to the sensing elements, and the output of the analog signal path is communicatively coupled to ADC 406. The signal path between the sensing elements and a readout layer can be referred to as a “signal readout path.” The signal readout can be the same as, or different from, the analog signal path. For example, the signal readout path includes the analog signal path, or multiple analog signal paths, and can extend further into a readout layer of the detector 400, such as to digital multiplexer 409.

[0087] In some embodiments, ADC 406 comprises output terminals communicatively coupled to a component (e.g., a component inside or outside the readout layer of detector array 400) for reading and interpreting the digital signal converted by ADC 406. ADC 406 can be communicatively coupled to a digital multiplexer 409. Digital multiplexer 409 can be arranged in the readout layer of detector array 400. Digital multiplexer 409 can receive multiple signals as input to convert as an output signal (e.g., a combined output signal). The output signal of digital multiplexer 409 can be transmitted to a data processing stage (e.g., image processing system 290 in FIG. 2). The output signal of digital multiplexer 409 can be converted back to the multiple input signals (e.g., via digital demultiplexing).

[0088] In some embodiments, detector 400 comprises a further layer of switching elements, such as interconnection layer 416 that communicatively couples outputs of signal processing circuitry to each other. The signal processing circuitry can comprise analog signal paths. Interconnection layer 416 con comprise interconnection switching elements communicatively coupled to outputs of analog signal paths of detector array 400. Interconnection switching elements 420-423 can communicatively couple the outputs of adjacent analog signal paths. Detector array 400 can comprise an analog signal path 405 associated with section 321, which starts from the output of section 321 and ends at the input of an interconnection layer 416.

[0089] A switching element 408 can communicatively couple an output of section 321 to an input of analog signal path 405. Switching element 410 can communicatively couple an output of analog signal path 405 to an input (e.g., input / output point 426 or “I / O point” 426) of interconnection layer 416. Switching elements 408 and 410 can be configured to be communicatively disconnected if analog signal path 405 is not selected for use. For example, a charged-particle beam can impinge on some or all of the sensing elements of section 321, but the detection signals of section 321 can be redirected to another analog signal path corresponding to another section of detector array 400, as further discussed below. In such a case, analog signal path 405 can be disconnected as a result of not being selected.

[0090] In some embodiments, if no sensing element of section 321 is impinged by any charged- particle and analog signal path 405 is not selected for use (e.g., to process signal from other sections), switching elements 408 and 410 function to disable amplifier 404 to reduce power consumption. When switching elements 408 and 410 are communicatively disconnected, analog signal path 405 (including amplifier 404) can be effectively deactivated from detector array 400.

[0091] The switch matrix comprising, e.g., inter-element switching elements 315, element-bus switching elements 316, and interconnection switching elements 420-423 can be configured to route signals from sensing elements to the readout layer of detector array 400 by a variety of signal readout paths. For example, when only one beam spot is incident on section 321, sensing elements can be coupled to the readout layer via element bus switching elements 316 and switching elements 408 and410. For instance, if a beam spot has been determined previously to be incident on all sensing elements in section 321, then the entire section can be coupled to the signal readout path via element-bus switching elements at each sensing element in section 321. Inter-element switching elements 315 between the sensing elements in section 321 can be left open to reduce parasitic parameters such as series resistance and parasitic capacitance. If, for example, sensing elements 311 and 312 are determined to be receiving a portion of a beam spot and the remaining sensing elements of section 321 are not, then only sensing elements 311 and 312 can be connected by closing their element-bus switching elements 316, while the remaining sensing elements are disconnected by leaving their own element-bus switching elements 316 open.

[0092] At the same time, sensing elements from neighboring sections can be coupled to a common signal readout path at interconnection layer 416 via interconnect switches 420-423. Alternatively, sensing elements from a neighboring section can be coupled to sensing elements within section 321 by closing the inter-element switching elements 315 between them.

[0093] If it is determined that two different beam spots are incident on two different portions of section 321, then signals from the two beam spots can be routed along different signal readout paths in order to differentiate the two beams (function can be scaled to more than two beams). In this case, it is avoided that both portions are coupled to analog signal path 405. For example, a first beam spot can be incident on sensing elements 311 and 312, as well as the neighboring section to the left of section 321 in FIG. 4 (not shown). A second beam spot can be incident on the entire row 317 containing sensing elements 313 and 314, as well as the neighboring section to the right of section 321 in FIG. 4 (not shown). If both sets of sensing elements are routed through analog signal path 405, their signals would not be differentiable. Therefore at least one of the portions can be connected to the adjacent section that shares a common beam spot.

[0094] For instance, sensing elements 311 and 312 can be connected to the neighboring section on the left side of section 321 by the inter-element switching elements on their left sides in FIG. 4. The neighboring section to the left can then be routed along an analog signal path other than analog signal path 405. Furthermore, interconnection switching element 423 can be open to disconnect the neighboring section from a signal readout path comprising analog signal path 405. At the same time, row 317 can be coupled to analog signal path 405 via their element-bus switching elements 316. Analog signal path 405 can be connected to an analog signal path of the neighboring section to the right by, e.g., closing interconnection switching element 421. Thus row 317 can be coupled to its adjacent section without closing the inter-element switching elements 315 between them.

[0095] The routing of the two portions in the manner described above can be determined based on, e.g., a desire to minimize the parasitic parameters in the system. For example, if parallel paths along element-bus switching elements 316 are preferred over series paths along inter-element switching elements 315, the routing can be determined such that fewer inter-element switching elements 315 are connected to the system. A total measure of parasitic parameters can be considered when determining optimal signal readout paths.

[0096] Further details and examples of detector arrays can be found in U.S. Provisional Patent Application No. 63 / 019,179, which is incorporated herein by reference in its entirety.

[0097] FIG. 5A illustrates an exemplary graphical representation of SEM images 500 and 502, consistent with embodiments of the present disclosure. While the term SEM is used in relation to the images, it is to be appreciated that other particle variants other than electrons (e.g., ions, photons, or the like) can be implemented according to embodiments described herein. In some embodiments, SEM images 500 and 502 are made up of image information, which can be represented in several forms. For example, SEM images 500 and 502 can be represented as digital data (e.g., saved in memory as ones and zeros). The graphical representation shown in FIG. 5A can be what is shown at a computer display based on an inspection measurement using the systems described in FIGS. 1-4 or based on opening a digital fde with image information. An analog representation or partially analog representation can be in the form of electrical signals from a detector (e.g., charged-particle detection device 244 (FIG. 2) along with positional information of the scanned electron beam.

[0098] In some embodiments, analyses and processing of image information will be described in the context of the graphical representation of FIG. 5A. However, it is appreciated that such analyses and processing are applicable to any form of representation of an image. For example, the generating of SEM images 500 and 502 from an inspection measurement can refer to one or more digital functions that calculate pixel intensities of SEM images 500 and 502 in digital form based on post-processing of detection signals.

[0099] SEM images 500 and 502 can correspond to one or more regions of a substrate (e.g., wafer 230 (FIG. 2) that were inspected using the systems described in FIGS. 1-4. SEM images 500 and 502 can comprise featureless regions (e.g., just the substrate or wafer), as well as device features or structures. For example, SEM images 500 and 502 comprise featureless regions 504a and 504b and a device feature 506. Device feature 506 can be a structure that has been added to the substrate via device fabrication processes (e.g., a transistor gate, a conductive trace, an isolation mesa, or the like). Featureless regions 504a and 504b can be bare regions of the substrate where no structures have been added during fabrication.

[0100] In some embodiments, SEM images 500 and 502 can be based on an inspection measurement performed by a multibeam inspection apparatus (e.g., as described in reference to FIG. 2). SEM image 500 can correspond to one of the multiple charged-particle beams. SEM image 502 can correspond to a different one of the multiple charged-particle beams. The example of FIG. 5A can correspond to an inspection of two side by side regions of the substrate. SEM images 500 and 502 are shown side by side as an example of how the two images can be stitched together to form a single combined image of the inspected regions of the substrate. It follows that featureless regions 504a and 504b and feature 506 can extend into both scanning charged-particle images 500 and 502 based on how the inspected regions are allocated.

[0101] Detector bandwidth can play an important role in the processes that generate SEM images 500 and 502. In the context of readout reset or zeroing, the detector bandwidth is a metric of the response speed of a detector. As explained above in reference to FIGS. 2-4, different regions of a detector can be discretized based on which of the multiple electron beams is incident in a given region. The discrete detector regions can be considered to have their own unique signal channel. The response of a given detector region can be different from that of another detector region. For example, overall detector bandwidth may not be uniform across the detector due to local differences in chip construction and circuit path of a given channel. In another example, a single-beam system can also have issues with difficulty in determining detector bandwidth due to design constraints. While localized detector bandwidths are properties of the detector, for simplicity, localized detector bandwidth can, by extension, be referenced as a function of beam identity (e.g., beam-to-beam detector bandwidth, n'1' beam detector bandwidth, or the like) since the different detector regions with different localized detector bandwidths happen to correspond to a different electron beam.

[0102] In some embodiments, a first beam detector bandwidth associated with SEM image 500 is different from a second beam detector bandwidth that is associated with SEM image 502. Even if the electron beam is scanned across the wafer at a uniform speed across both regions of SEM images 500 and 502, the difference in detector bandwidth can give different results. The first beam detector bandwidth can be higher (faster) and result in a sharper contrast of details. For example, an edge 508 of feature 506 in SEM image 500 is resolvable to a finite degree of sharpness. However, the second detector bandwidth (slower) associated with SEM image 502 can result in the same edge 508 being more blurred compared to SEM image 500. When generating SEM images, inconsistent detector bandwidth can affect accuracy of measurements.

[0103] FIG. 5B illustrates an exemplary graph 520 plotting a measurement of a feature structure 522 and the effects of a finite detector bandwidth, consistent with embodiments of the present disclosure. In some embodiments, a cross section of device feature 522 can have a height hl and a valley of height hO. A charged-particle beam inspection tool (e.g., the systems described in FIGS. 1-4) can be used to scan across a length of device feature 522, with the probe beam passing through the plateau regions of height hl and valley region of height hO. The primary vertical axis (to the left) can represent an actual height of device feature 522 (in arbitrary units of height). The secondary vertical axis can represent a detector response (arbitrary grayscale intensity of pixels). The horizontal direction of graph 520 is apportioned according to corresponding pixel widths of an image that results from the scanning of the probe beam.

[0104] For an ideal detector (e.g., infinite bandwidth), the line of pixels corresponding to such a scan would appear as shown in line of pixels 526. However, a detector with finite bandwidth can cause the detection signals to change slower than the changes of the topography of device feature 522. Hence, there can be a discrepancy between device features 522 and the detector response 528. The discrepancy can be better appreciated by comparing its corresponding pixel data (line of pixels 530) toline of pixels 526 of the ideal detector. It follows that, if detector bandwidth is inconsistent with respect to different sections of the detector, the results for line of pixels 530 can also be inconsistent with respect to which of the multiple beams of a charged-particle beam apparatus is used to perform the scan.

[0105] However, if the beam-to-beam detector bandwidths are determinable (e.g., via measurement), it is possible to adjust circuitry to equalize the beam-to-beam detector bandwidths (e.g., adjusting a time constant of an RC-circuit associated with amplifier 404 (FIG. 4), thereby restoring consistency in beam-to-beam inspection. However, measuring detector bandwidths can be challenging, particularly in vacuum-based charged-particle microscopes. Space is a valuable and limited resource in a vacuum-based inspection tool. Adding additional metrology tools for measuring bandwidth can undesirably increase complexity, cost, and space usage in the vacuum-based inspection tool. For example, a laser can be installed within the inspection tool to scan across the detector surface and measure the response of the different regions of the detector. The laser and accompanying peripherals can be difficult to implement in an already space -constrained environment. Furthermore, a measurement based on photons has the risk of not being able to provide a “true” characterization of the detector bandwidth. There is a fundamental difference in taking a measurement with photons (bosons, no Pauli exclusion, no electrical charge) as compared to using electrons (fermions, Pauli exclusion, electrically charged). The present disclosure addresses such issues by providing an in-situ technique to measure detector bandwidth by analyzing an image that was taken during regular operation of a scanning charged-particle microscope. This is particularly useful since the detector bandwidth determination (e.g., a calibration measurement) is performed without having to introduce additional measurement tools, as well as in-situ during regular operation, whereas conventional inspection tools are typically calibrated using an external metrology tool separately before being put into use.

[0106] In some embodiments, determination of a detector bandwidth can be performed by analyzing the shot noise signal present in an image. Shot noise is a fundamental limit of detectors as it is a quantum noise effect related to the discreteness of photons and electrons. In the interest extracting and isolating shot noise from other signals and disturbances in SEM image 500, a select featureless region 510 is identified and selected from among the expanse that is featureless region 504a. Select featureless region 510 can be identified manually by a person looking for a region in SEM image 500 that is substantially uniform (e.g., visual determination) or automatically by an algorithm. The algorithm can perform a search of SEM image 500 for an area that is void of features and is substantially uniform in terms of intensity (uniform “gray level” for a colorless image).

[0107] When digitized, SEM images 500 and 502 can be defined by arrays of pixels. Select featureless region 510 can comprise a subset of the pixels of SEM image 500. While pixels 514, 516, and 518 are expressly labeled for purposes of example, it is appreciated that the number of pixels in select featureless region 510 are determined based on region uniformity. Furthermore, an M*Nrectangular array of pixels is illustrated as a non-limiting example. Other suitable pixel array configurations can be implemented with embodiments described herein. The description of select featureless region 510 is also applicable to select featureless region 512 in SEM image 502.

[0108] FIG. 6 illustrates an exemplary graphical representation of a select featureless region 600 and disturbance correction results, consistent with embodiments of the present disclosure. In some embodiments, select featureless region 600 represents a gray level intensity map of a select featureless region (e.g., select featureless regions 510 or 512 (FIG. 5A). The horizontal axis can represent an X position with a length scale in arbitrary units. The vertical axis can represent a Y position with a length scale in arbitrary units. Intensity gray level can be represented from dark (lower intensity) to bright (higher intensity). At a glance, select featureless region 600 exhibits a periodic intensity variation. The periodicity of the intensity variation is uncharacteristic of shot noise. Signals other than shot noise can be detrimental to an analysis that relies on shot noise isolation. Hence, undesirable signals superimposed with the shot noise signal in the SEM image can be classified as nuisance disturbances that are to be corrected out.

[0109] Some examples of signals other than shot noise can include local charging of the wafer, device structures (e.g., feature 506 (FIG. 5A), non-uniformity of the wafer, electronic noise, and the like. Some disturbances, such as periodic disturbances, can have frequency characteristics that are identifiable via frequency domain analysis (e.g., Fourier domain analysis). Operations to isolate a disturbance can comprise converting the raw image information of select featureless region 600 into frequency domain. Anomalous intensities in the frequency domain information can inform the expected periodicities of the disturbances. The operations can comprise identifying, per pixel row, an N-fold disturbance (e.g., a 4-fold disturbance) across a line of pixels (e.g., along a pixel row) for which a feature repeats every N pixels. The operations can comprise determining, per row, a phase shift (e.g., pixel shift) of the identified N-fold disturbances that would align the disturbances to one another. The operations can comprise averaging the phase shifted disturbances. The operations can comprise generating an image representation of the N-fold disturbances using the averaged disturbance and phase shift periodicity. Disturbance image 602 can be generated in this manner. Disturbance image 602 can correspond to select featureless region 600 pixel for pixel.

[0110] The disturbance information in disturbance image 602 can be subtracted from the image information of select featureless regions 600 (raw image) to generate corrected image 604. As shown, the periodicity has been removed and what remains is shot noise. At this stage, or after multiple rounds of correction, corrected image 604 can comprise signal information that is predominantly shot noise. Having the shot noise information, autocorrelation calculations can be performed.

[0111] FIG. 7 illustrates an exemplary pixel array 700 based on an SEM image to be implemented with an array flattening scheme and autocorrelation calculations, consistent with embodiments of the present disclosure. To facilitate description, the example of FIG. 7 uses five rows of pixels with seven pixels per row. It is to be appreciated that images in some embodiments can have lines (rows orcolumns) that are hundreds, thousands, or more pixels across. In some embodiments, pixel array 700 can represent an image that is predominantly shot noise. Pixel positions are identified as 1 through 35. The top three rows with different fillings will be used for in the example that follows. Though not expressly shown, it is to be understood that each pixel contains gray level intensity information. And as the rows are manipulated and shifted, so too is the intensity information shifted by the corresponding amount. Pixel array 700 can represent a simplified view of corrected image 604 or select featureless regions 510 or 512 in the absence of corrections.

[0112] It is instructive to first consider how the intensity information for each pixel is generated. In some embodiments, an electron beam spot is scanned across a region of interest on a substrate. The scanning is to cover a two-dimensional area of the substrate. There are several two-dimensional movements that can be chosen from (e.g., zig-zag, raster, or the like). For the purposes of this example, a raster movement assumed. A raster movement can comprise moving the electron beam spot to scan horizontally for a finite length. The scan speed can be uniform (e.g., few nanoseconds per pixel). The horizontal scan can correspond to the top row of pixel array 700. At the end of the scan length, the electron beam can undergo a horizontal retrace. The horizontal retrace can comprise a fly back scan that brings the electron beam spot back to the beginning of a different row (e.g., one row down from the previously scanned row). From here, the electron beam can perform a second horizontal scan (at the same uniform speed for consistency). Then, the electron beam can perform yet another fly back scan to scan a new row. The process is repeated until the full images are generated, such as SEM images 500 and 502 in FIG. 5A.

[0113] In some embodiments, the dwell time of the beam per pixel is a parameter that is used at various calculation phases when determining a detector bandwidth. For example, if the electron beam is set to move pixel-to-pixel every 1 nanosecond, this information determines the time domain shift when a row of pixels is shifted by an integer number of pixel positions. Also, it is to be appreciated that the time difference from pixel 7 to pixel 8 may not conform to the speed setting. The left and right boundaries of pixel array 700 can represent select featureless regions 510 or 512, whereas the electron beam horizontal scan can cover the full width of SEM images 500 or 502 (FIG. 5A). In other words, while there is consistent time between adjacent horizontal pixels, there is an unaccounted time delay between pixels 7 and 8, pixels 14 and 15, pixels 21 and 22, and so on. However, operations provided herein can mitigate timing issues due to discontinuities of the scanning motion of the electron beam spot on the substrate.

[0114] Pixel array 700 can be flattened to generate flattened pixel arrays 706a and 706b. Flattened pixel arrays 706a and 706b are identical. Autocorrelation calculations as a function of time delay can result in a value between -1 to 1, with 1 being the maximum autocorrelation. For example, autocorrelation between a signal and a copy of itself (zero delay) can result in an autocorrelation value of 1. The scenario depicted by flattened pixel arrays 706a and 706b corresponds to an autocorrelation of 1. Shown at time position 708-1, the gray level intensity data of pixel 1 in flattened pixel array706a is aligned (e.g., aligned in time) with the gray level intensity of pixel 1 in flattened pixel array 706b. A similar pattern emerges for pixel 2 at time position 708-2 and pixel 3 at time position 708-3. The pattern can continue for as many time pixel / time positions 708- / there are in the flattened arrays.

[0115] FIG. 8 illustrates exemplary modified pixel arrays 800a and 800b to be implemented with an array flattening scheme and autocorrelation calculations, consistent with embodiments of the present disclosure. In some embodiments, the pixel positions of modified pixel arrays 800a and 800b, along with the gray level intensity data at each pixel, correspond to their numbered counterparts in pixel array 700 (FIG. 7). Modified pixel array 800a can be generated by removing (e.g., truncating) a line of pixels from an edge of pixel array 700 (FIG. 7). For example, the removed pixels 1, 8, 15, 22, and 29 at the left edge of modified pixel array 800a are represented as truncated portion 802. Similarly, modified pixel array 800b can be generated by removing pixels 7, 14, 21, 28, and 35 at the right edge of pixel array 700 (FIG. 7), the removed pixels being represented by truncated portion 804.

[0116] In some embodiments, modified pixel arrays 800a and 800b, which are shown as flattened pixel arrays 806a and 806b, respectively. The process of flattening an array can include reducing a dimension of the array while preserving the information content of the array. For example, the rows of modified pixel array 800a can be placed side by side along a single row so as to generate flattened pixel array 806a. The same process can be executed for modified pixel array 800b to generate flattened pixel array 806b. Flattened pixel arrays 806a and 806b and the gray level intensity data therein can then serve as input in autocorrelation calculations.

[0117] Autocorrelation can be represented as a mathematical relationship that calculates the correlation of a signal with a delayed copy of itself. In the present example, the truncation of the arrays, along with array flattening, results in flattened pixel array 806b being a delayed copy of flattened pixel array 806a — shifted by one pixel position. For a given array, if the data is graphed on an X-Y plot, the horizontal axis can represent pixel position, which can also be represented as time based on the speed setting used for the scanning of the electron beam spot (e.g., 1 nanosecond per pixel). The vertical axis of the X-Y plot can correspond to the gray level intensity for the corresponding pixel position (actual intensity values not shown, but can be values on the intensity scales shown in FIG. 6. Shown at time position 808-1, the gray level intensity data of pixel 2 in flattened pixel array 806a is aligned (e.g., aligned in time) with the gray level intensity of pixel 1 in flattened pixel array 806b. Shown at pixel / time position 808-1, the gray level intensity data of pixel 2 in flattened pixel array 806a is aligned with the gray level intensity of pixel 1 in flattened pixel array 806b. Shown at pixel / time position 808-2, the gray level intensity data of pixel 3 in flattened pixel array 806a is aligned with the gray level intensity of pixel 2 in flattened pixel array 806b. Shown at pixel / time position 808-3, the gray level intensity data of pixel 4 in flattened pixel array 806a is aligned with the gray level intensity of pixel 3 in flattened pixel array 806b. The pattern can continue for as many time pixel / time positions 808- there are in the flattened arrays.

[0118] In some embodiments, autocorrelation between a signal and a copy of itself (zero delay) can result in an autocorrelation value of 1. Autocorrelation between the signal represented by flattened pixel array 806a and a 1 -pixel-shifted copy of itself (or 1 -nanosecond-shifted) represented by flattened pixel array 806b, would likely result in an autocorrelation value of less than 1. With larger and larger increments of delays to the signal copies, the autocorrelation values can shift away from 1.

[0119] FIG. 9 illustrates exemplary modified pixel arrays 900a and 900b to be implemented with an array flattening scheme and autocorrelation calculations, consistent with embodiments of the present disclosure. In some embodiments, similar to the pixel removal process described with reference to FIG. 8, two columns of pixels are removed from pixel array 700 (FIG. 7) to generate modified pixel arrays 900a and 900b. The removed pixels 1, 2, 8, 9, 15, 16, 22, 23, 29, and 30 at the left edge of modified pixel array 900a are represented as truncated portion 902. Similarly, modified pixel array 900b can be generated by removing pixels 6, 7, 13, 14, 20, 21, 27, 28, 34, and 35 at the right edge of pixel array 700 (FIG. 7), the removed pixels being represented by truncated portion 904. The removal of more pixels as compared to FIG. 8 provides an even larger pixel shift (or time delay) of the signals used in autocorrelation calculations.

[0120] Modified pixel arrays 900a and 900b can be flattened to generate flattened pixel arrays 906a and 906b, respectively. When aligned, it is seen that signal represented by flattened pixel array 906b is a 2-increment shifted copy of the signal of flattened pixel array 906b. By comparison, the example in FIG. 8 would be a 1 -increment shift. Shown at pixel / time position 908-1, the gray level intensity data of pixel 3 in flattened pixel array 906a is aligned with the gray level intensity of pixel 1 in flattened pixel array 906b. Shown at pixel / time position 908-2, the gray level intensity data of pixel 4 in flattened pixel array 906a is aligned with the gray level intensity of pixel 2 in flattened pixel array 906b. Shown at pixel / time position 908-3, the gray level intensity data of pixel 5 in flattened pixel array 906a is aligned with the gray level intensity of pixel 3 in flattened pixel array 906b. The pattern can continue for as many time pixel / time positions 908- / there are in the flattened arrays.

[0121] Referring briefly back to FIG. 5A, select featureless regions 510 and 512 can be the basis for flattened arrays. Since select featureless regions 510 and 512 can produce flattened arrays that are thousands of pixels long (if not more), the incremental shifting of the signal copies can be performed many times over without significant loss of signal data as a result of array truncation. Furthermore, the method is not limited to flattened arrays. Image signals can be represented in any suitable configuration, array or otherwise.

[0122] FIG. 10 illustrates an exemplary plot 1000 of autocorrelation data with respect to delay shifts as described in reference to FIGS. 8 and 9, consistent with embodiments of the present disclosure. Dotted data points correspond to autocorrelation values determined based on time delays of original signal. An autocorrelation of 1 corresponds to the autocorrelation of a signal and a copy of itself with no delay. A curve fit can be performed on the data (shown as a dashed line). The signal that forms the SEM image can be a convolution of the shot noise with a low-pass filter of the detector. A low-passfilter can be modeled as an RC filter (resistor-capacitor filter) having a characteristic RC time constant r. The exponential decay fit can have the form exp(-t / r), where t is the time delay in FIG. 10. An exponential fit can yield information on the RC time of the low-pass filter.

[0123] The cutoff frequency (or detector bandwidth) can be extracted from the autocorrelation curve using the equation 1, with BW being bandwidth and r being the RC time constant from the exponential decay fit.

[0124] In this manner, localized detector bandwidth (on a per-beam basis) can be measured in-situ by analyzing the content of an SEM image.

[0125] More details about autocorrelation and detector noise can be found in Passmore et al., “Autocorrelation of electrical noise: an undergraduate experiment,” American Journal of Physics, 63(7), 592-594 (1995), the contents of which are incorporated by reference herein in its entirety.

[0126] With a method to measure different localized detector bandwidths, a number of capabilities can be implemented. For example, different amplifiers in detector array 400 (FIG. 4) can be tuned via capacitor to provide a uniform detector bandwidth across detector array 400. This can help to make sure each SEM image taken by different electron beams of a multibeam system provides consistent information. Without a fast and reliable method to measure detector bandwidth, it is inadvisable to adjust the detector bandwidth in view of the cumbersome calibration that can ensue. However, with a method to quickly and reliably measure detector bandwidth, a user of the detector can be given the choice to make a tradeoff between noise performance and bandwidth.

[0127] Embodiments described herein are not limited to multibeam systems. A multibeam example was used to better understand a scenario in which the operations described herein can be used to address issues with inconsistent detector performance. Embodiments of the present disclosure can be implemented with single-beam systems. Capabilities and performance of a single-beam system can also be enhanced by implementing the detector bandwidth measurement technique disclosed herein.

[0128] FIG. 11 illustrates an exemplary method 1100 for performing an in-situ measurement of detector bandwidth, according to embodiments of the present disclosure. The method can be executed using devices and functions described in reference to FIGS. 1-10, such as controller 109 of FIG. 1.

[0129] In some embodiments, at step 1102, an image of a sample surface (e.g., SEM images 500 or 502 of FIG. 5A) is determined based on detection of secondary charged particles associated with interaction of primary charged particles with the sample surface. The primary charged particles can be provided via a beam of charged particles generated by a charged particle source. The detection of the charged particles can be performed using a charged particle detector (e.g., beam tool 104 of FIGS. 1 and 2 can be used to acquire the image). The image can be a raw image or a post-processed correctedimage. Correction of an image can be performed as described in reference to FIG. 6. The image (e.g., the digital image information) can comprise an array of pixels. The pixels can encompass a featureless region of the sample surface.

[0130] At step 1104, an autocorrelation function can be determined. The autocorrelation function can be between a signal represented by a line of the pixels and delayed copies of the signal. The signal can be associated with the featureless region of the sample surface. The controller can select a featureless region of the sample surface based on region uniformity. The signal represented by a line of the pixels can be represented as a flattened pixel array as described in reference to FIGS. 8 and 9.

[0131] At step 1106, based on the autocorrelation function, a bandwidth of the charged particle detector can be determined. The determined bandwidth can be a localized detector bandwidth associated with one of multiple charged particle beams. The bandwidth can be extracted by calculating a cutoff frequency from a curve fit of the autocorrelation function as described in reference to FIG. 10.

[0132] A non-transitory computer-readable medium can store instructions for a processor of a controller (e.g., controller 109 in FIG. 1) for determining a detector bandwidth of a charged particle detector according to the exemplary flowcharts of FIG. 11 above, consistent with embodiments in the present disclosure. For example, the instructions stored in the non-transitory computer-readable medium are executable by the circuitry of the controller for performing method 1100 in part or entirely. Common forms of non-transitory media include, for example, a floppy disk, a flexible disk, hard disk, solid-state drive, magnetic tape, or any other magnetic data storage medium, a Compact Disc Read-Only Memory (CD-ROM), any other optical data storage medium, any physical medium with patterns of holes, a Random Access Memory (RAM), a Programmable Read-Only Memory (PROM), and Erasable Programmable Read-Only Memory (EPROM), a FLASH-EPROM or any other flash memory, Non-Volatile Random Access Memory (NVRAM), a cache, a register, any other memory chip or cartridge, and networked versions of the same.

[0133] Some embodiments may further be described using the following clauses:1. A charged particle beam apparatus, comprising: a charged particle beam source configured to generate a beam of primary charged particles; a charged particle optical system configured to direct the beam of primary charged particles at a sample surface; a charged particle detector configured to detect secondary charged particles associated with interaction of the primary charged particles with the sample surface; and a controller comprising circuitry configured to: determine an image of the sample surface based on the detected secondary charged particles, wherein the image comprises an array of pixels; determine an autocorrelation function between a signal represented by a line of the pixels and delayed copies of the signal; anddetermine a bandwidth of the charged particle detector based on the autocorrelation function.2. The charged particle beam apparatus of clause 1, wherein: the controller comprises circuitry further configured to search, in the image, for a featureless region of the sample surface based on intensity uniformity; and the line of pixels used in computations of the autocorrelation function corresponds to a line of pixels of the featureless region.3. The charged particle beam apparatus of any one of clauses 1 or 2, wherein the controller comprises circuitry further configured to determine the bandwidth based on a determination of a cutoff frequency based on the autocorrelation function.4. The charged particle beam apparatus of clause 3, wherein the controller comprises circuitry further configured to determine the cutoff frequency based on an exponential fit of data from the autocorrelation function.5. The charged particle beam apparatus of any one of clauses 1 to 4, wherein the controller comprises circuitry further configured to: convert information of the image into frequency domain data; and determine a periodic disturbance in the image based on analysis of the frequency domain data.6. The charged particle beam apparatus of clause 5, wherein the controller comprises circuitry further configured to determine a corrected image based on removing the periodic disturbance from the image.7. The charged particle beam apparatus of clause 6, wherein signal information of the corrected image is predominantly shot noise.8. The charged particle beam apparatus of any one of clauses 1 to 7, wherein the controller comprises circuitry further configured to disregard pixels in the array that are associated with discontinuous scanning motion of the beam.9. The charged particle beam apparatus of any one of clauses 1 to 8, wherein the controller comprises circuitry further configured to flatten a portion of the array.10. The charged particle beam apparatus of any one of claims 1 to 9, wherein the beam comprises beamlets.11. The charged particle beam apparatus of clause 10, wherein: the bandwidth is one of a plurality of localized detector bandwidths associated with one of the beamlets; and the controller comprises circuitry further configured to determine another one of the localized detector bandwidths associated with another one of the beamlets.12. The charged particle beam apparatus of any one of clauses 1 to 11, wherein the controller comprises circuitry further configured to adjust the bandwidth of the charged particle detector based on a determination that the bandwidth is outside a compliance range.13. The charged particle beam apparatus of any one of clauses 1 to 12, wherein the controller comprises circuitry further configured to determine the bandwidth in-situ as the charged particle beam apparatus is used for inspecting the sample surface.14. A non-transitory computer-readable medium that stores a set of instructions that is executable by at least one processor of an apparatus to cause the apparatus to perform operations comprising: determining an image of a sample surface based on detection of secondary charged particles at a charged particle detector, wherein: the image comprises an array of pixels; the secondary charged particles are associated with interaction of primary charged particles with the sample surface; and the primary charged particles are associated with a beam of the primary charged particles directed to the sample; determining an autocorrelation function between a signal represented by a line of the pixels and delayed copies of the signal; and determining a bandwidth of the charged particle detector based on the autocorrelation function.15. The non-transitory computer-readable medium of clause 14, wherein: the operations further comprise searching, in the image, for a featureless region of the sample surface based on intensity uniformity; and the line of pixels used in computations of the autocorrelation function corresponds to a line of pixels of the featureless region.16. The non-transitory computer-readable medium of any one of clauses 14 or 15, wherein determining the bandwidth is further based on a determination of a cutoff frequency, the cutoff frequency being based on the autocorrelation function.17. The non-transitory computer-readable medium of clause 16, wherein the operations further comprise determining the cutoff frequency based on an exponential fit of data from the autocorrelation function.18. The non-transitory computer-readable medium of any one of clauses 14 to 16, wherein the operations further comprise: converting information of the image into frequency domain data; and determining a periodic disturbance in the image based on analysis of the frequency domain data.19. The non-transitory computer-readable medium of clause 18, wherein the operations further comprise determining a corrected image based on removing the periodic disturbances from the image.20. The non-transitory computer-readable medium of clause 19, wherein signal information of the corrected image is predominantly shot noise.21. The non-transitory computer-readable medium of any one of clauses 14 to 20, wherein the operations further comprise disregarding pixels in the array that are associated with discontinuous scanning motion of the beam.22. The non-transitory computer-readable medium of any one of clauses 14 to 21, the operations further comprise flattening a portion of the array.23. The non-transitory computer-readable medium of any one of clauses 14 to 22, wherein the beam comprises beamlets.24. The non-transitory computer-readable medium of clause 23, wherein: the bandwidth is one of a plurality of localized detector bandwidths associated with one of the beamlets; and the operations further comprise determining another one of the localized detector bandwidths associated with another one of the beamlets.25. The non-transitory computer-readable medium of any one of clauses 14 to 24, wherein the operations further comprise adjusting the bandwidth of the charged particle detector based on a determination that the bandwidth is outside a compliance range.26. The non-transitory computer-readable medium of any one of clauses 14 to 25, wherein the operations further comprise determining the bandwidth in-situ as the apparatus is used for inspecting the sample surface.27. A method for measuring a bandwidth of a charged particle detector, the method comprising: determining an image of a sample surface based on detection of secondary charged particles at a charged particle detector, wherein: the image comprises an array of pixels; the secondary charged particles are associated with interaction of primary charged particles with the sample surface; and the primary charged particles are associated with a beam of the primary charged particles directed to the sample; determining an autocorrelation function between a signal represented by a line of the pixels and delayed copies of the signal; and determining a bandwidth of the charged particle detector based on the autocorrelation function.28. The method of clause 27, further comprising searching, in the image, for a featureless region of the sample surface based on intensity uniformity, wherein the line of pixels used in computations of the autocorrelation function corresponds to a line of pixels of the featureless region.29. The method of any one of clauses 27 or 28, wherein determining the bandwidth is further based on a determination of a cutoff frequency, the cutoff frequency being based on the autocorrelation function.30. The method of clause 29, further comprising determining the cutoff frequency based on an exponential fit of data from the autocorrelation function.31. The method of any one of clauses 27 to 30, further comprising: converting information of the image into frequency domain data; and determining a periodic disturbance in the image based on analysis of the frequency domain data.32. The method of clause 31, further comprising determining a corrected image based on removing the periodic disturbances from the image.33. The method of clause 32, wherein signal information of the corrected image is predominantly shot noise.34. The method of any one of clauses 27 to 33, further comprising disregarding pixels in the array that are associated with discontinuous scanning motion of the beam.35. The method of any one of clauses 27 to 34, further comprising flattening a portion of the array.36. The method of any one of clauses 27 to 35, wherein the beam comprises beamlets.37. The method of clause 36, wherein: the bandwidth is one of a plurality of localized detector bandwidths associated with one of the beamlets; and the method further comprises determining another one of the localized detector bandwidths associated with another one of the beamlets.38. The method of any one of clauses 27 to 37, further comprising adjusting the bandwidth of the charged particle detector based on a determination that the bandwidth is outside a compliance range.39. The method of any one of clauses 27 to 38, further comprising determining the bandwidth in- situ as the charged particle detector is used for inspecting the sample surface.40. A charged particle beam apparatus, comprising: a charged particle beam source configmed to generate a beam of primary charged particles, wherein the beam is part of a plurality of beamlets; a charged particle optical system configmed to direct the beam of primary charged particles at a sample smface; a charged particle detector comprising a plurality of detector sections, wherein a section of the plurality of sections is configured to detect secondary charged particles associated with interaction of the primary charged particles with the sample surface; and a controller comprising circuitry configmed to: determine an image of the sample smface based on the detected secondary charged particles, wherein the image comprises an array of pixels; determine an autocorrelation function between a signal represented by a line of the pixels and delayed copies of the signal; anddetermine a bandwidth of the section of the charged particle detector based on the autocorrelation function.41. The charged particle beam apparatus of clause 40, wherein: the controller comprises circuitry further configured to search, in the image, for a featureless region of the sample surface based on intensity uniformity; and the line of pixels used in computations of the autocorrelation function corresponds to a line of pixels of the featureless region.42. The charged particle beam apparatus of any one of clauses 40 or 41, wherein the controller comprises circuitry further configured to determine the bandwidth based on a determination of a cutoff frequency based on the autocorrelation function.43. The charged particle beam apparatus of clause 42, wherein the controller comprises circuitry further configured to determine the cutoff frequency based on an exponential fit of data from the autocorrelation function.44. The charged particle beam apparatus of any one of clauses 40 to 43, wherein the controller comprises circuitry further configured to: convert information of the image into frequency domain data; and determine a periodic disturbance in the image based on analysis of the frequency domain data.45. The charged particle beam apparatus of clause 44, wherein the controller comprises circuitry further configured to determine a corrected image based on removing the periodic disturbance from the image.46. The charged particle beam apparatus of clause 45, wherein signal information of the corrected image is predominantly shot noise.47. The charged particle beam apparatus of any one of clauses 40 to 46, wherein the controller comprises circuitry further configured to disregard pixels in the array that are associated with discontinuous scanning motion of the beam.48. The charged particle beam apparatus of any one of clauses 40 to 47, wherein the controller comprises circuitry further configured to flatten a portion of the array.49. The charged particle beam apparatus of any one of clauses 40 to 48, wherein the beam of the plurality of beamlets is associated with the section.50. The charged particle beam apparatus of clause 49, wherein the controller comprises circuitry further configured to determine a bandwidth of another section of the plurality of sections, the other section being associated with another beam of the plurality of beamlets.51. The charged particle beam apparatus of any one of clauses 40 to 50, wherein the controller comprises circuitry further configured to adjust the bandwidth of the section of the charged particle detector based on a determination that the bandwidth is outside a compliance range.52. The charged particle beam apparatus of any one of clauses 40 to 51, wherein the controller comprises circuitry further configured to determine the bandwidth in-situ as the charged particle beam apparatus is used for inspecting the sample surface.53. A non-transitory computer-readable medium that stores a set of instructions that is executable by at least one processor of an apparatus to cause the apparatus to perform operations comprising: determining an image of a sample surface based on detection of secondary charged particles at a section of a charged particle detector comprising a plurality of sections, wherein: the image comprises an array of pixels; the secondary charged particles are associated with interaction of primary charged particles with the sample surface; and the primary charged particles are associated with a beam of the primary charged particles directed to the sample, wherein the beam is part of a plurality of beamlets; determining an autocorrelation function between a signal represented by a line of the pixels and delayed copies of the signal; and determining a bandwidth of the section of the charged particle detector based on the autocorrelation function.54. The non-transitory computer-readable medium of clause 53, wherein: the operations further comprise searching, in the image, for a featureless region of the sample surface based on intensity uniformity; and the line of pixels used in computations of the autocorrelation function corresponds to a line of pixels of the featureless region.55. The non-transitory computer-readable medium of any one of clauses 53 or 54, wherein determining the bandwidth is further based on a determination of a cutoff frequency, the cutoff frequency being based on the autocorrelation function.56. The non-transitory computer-readable medium of clause 55, wherein the operations further comprise determining the cutoff frequency based on an exponential fit of data from the autocorrelation function.57. The non-transitory computer-readable medium of any one of clauses 53 to 56, wherein the operations further comprise: converting information of the image into frequency domain data; and determining a periodic disturbance in the image based on analysis of the frequency domain data.58. The non-transitory computer-readable medium of clause 57, wherein the operations further comprise determining a corrected image based on removing the periodic disturbances from the image.59. The non-transitory computer-readable medium of clause 58, wherein signal information of the corrected image is predominantly shot noise.60. The non-transitory computer-readable medium of any one of clauses 53 to 59, wherein the operations further comprise disregarding pixels in the array that are associated with discontinuous scanning motion of the beam.61. The non-transitory computer-readable medium of any one of clauses 53 to 60, the operations further comprise flattening a portion of the array.62. The non-transitory computer-readable medium of any one of clauses 53 to 61, wherein the beam of the plurality of beamlets is associated with the section.63. The non-transitory computer-readable medium of clause 62, wherein the operations further comprise determining a bandwidth of another section of the plurality of sections, the other section being associated with another beam of the plurality of beamlets.64. The non-transitory computer-readable medium of any one of clauses 53 to 63, wherein the operations further comprise adjusting the bandwidth of the section based on a determination that the bandwidth is outside a compliance range.65. The non-transitory computer-readable medium of any one of clauses 53 to 64, wherein the operations further comprise determining the bandwidth in-situ as the apparatus is used for inspecting the sample surface.66. A method for measuring a bandwidth of a charged particle detector, the method comprising: determining an image of a sample surface based on detection of secondary charged particles at a section of a charged particle detector comprising a plurality of sections, wherein: the image comprises an array of pixels; the secondary charged particles are associated with interaction of primary charged particles with the sample surface; and the primary charged particles are associated with a beam of the primary charged particles directed to the sample, wherein the beam is part of a plurality of beamlets; determining an autocorrelation function between a signal represented by a line of the pixels and delayed copies of the signal; and determining a bandwidth of the section of the charged particle detector based on the autocorrelation function.67. The method of clause 66, further comprising searching, in the image, for a featureless region of the sample surface based on intensity uniformity, wherein the line of pixels used in computations of the autocorrelation function corresponds to a line of pixels of the featureless region.68. The method of any one of clauses 66 or 67, wherein determining the bandwidth is further based on a determination of a cutoff frequency, the cutoff frequency being based on the autocorrelation function.69. The method of clause 68, further comprising determining the cutoff frequency based on an exponential fit of data from the autocorrelation function.70. The method of any one of clauses 66 to 69, further comprising:converting information of the image into frequency domain data; and determining a periodic disturbance in the image based on analysis of the frequency domain data.71. The method of clause 70, further comprising determining a corrected image based on removing the periodic disturbances from the image.72. The method of clause 71, wherein signal information of the corrected image is predominantly shot noise.73. The method of any one of clauses 66 to 72, further comprising disregarding pixels in the array that are associated with discontinuous scanning motion of the beam.74. The method of any one of clauses 66 to 73, further comprising flattening a portion of the array.75. The method of any one of clauses 66 to 74, wherein the beam of the plurality of beamlets is associated with the section; and76. The method of clause 75, further comprising determining a bandwidth of another section of the plurality of sections, the other section being associated with another beam of the plurality of beamlets.77. The method of any one of clauses 66 to 76, further comprising adjusting the bandwidth of the charged particle detector based on a determination that the bandwidth is outside a compliance range.78. The method of any one of clauses 66 to 77, further comprising determining the bandwidth in- situ as the charged particle detector is used for inspecting the sample surface.

[0134] It will be appreciated that the embodiments of the present disclosure are not limited to the exact construction that has been described above and illustrated in the accompanying drawings and that various modifications and changes may be made without departing from the scope thereof.

Claims

CLAIMS1. A charged particle beam apparatus, comprising: a charged particle beam source configured to generate a beam of primary charged particles; a charged particle optical system configured to direct the beam of primary charged particles at a sample surface; a charged particle detector configured to detect secondary charged particles associated with interaction of the primary charged particles with the sample surface; and a controller comprising circuitry configured to: determine an image of the sample surface based on the detected secondary charged particles, wherein the image comprises an array of pixels; determine an autocorrelation function between a signal represented by a line of the pixels and delayed copies of the signal; and determine a bandwidth of the charged particle detector based on the autocorrelation function.

2. The charged particle beam apparatus of claim 1, wherein: the controller comprises circuitry further configured to search, in the image, for a featureless region of the sample surface based on intensity uniformity; and the line of pixels used in computations of the autocorrelation function corresponds to a line of pixels of the featureless region.

3. The charged particle beam apparatus of claim 1, wherein the controller comprises circuitry further configured to determine the bandwidth based on a determination of a cutoff frequency based on the autocorrelation function.

4. The charged particle beam apparatus of claim 3, wherein the controller comprises circuitry further configured to determine the cutoff frequency based on an exponential fit of data from the autocorrelation function.

5. The charged particle beam apparatus of claim 1, wherein the controller comprises circuitry further configured to: convert information of the image into frequency domain data; and determine a periodic disturbance in the image based on analysis of the frequency domain data.

6. The charged particle beam apparatus of claim 5, wherein the controller comprises circuitry further configured to determine a corrected image based on removing the periodic disturbance from the image.

7. The charged particle beam apparatus of claim 6, wherein signal information of the corrected image is predominantly shot noise.

8. The charged particle beam apparatus of claim 1, wherein the controller comprises circuitry further configured to disregard pixels in the array that are associated with discontinuous scanning motion of the beam.

9. The charged particle beam apparatus of claim 1, wherein the controller comprises circuitry further configured to flatten a portion of the array.

10. The charged particle beam apparatus of claim 1, wherein the beam comprises beamlets.

11. The charged particle beam apparatus of claim 10, wherein: the bandwidth is one of a plurality of localized detector bandwidths associated with one of the beamlets; and the controller comprises circuitry further configured to determine another one of the localized detector bandwidths associated with another one of the beamlets.

12. The charged particle beam apparatus of claim 1, wherein the controller comprises circuitry further configured to adjust the bandwidth of the charged particle detector based on a determination that the bandwidth is outside a compliance range.

13. The charged particle beam apparatus of claim 1, wherein the controller comprises circuitry further configured to determine the bandwidth in-situ as the charged particle beam apparatus is used for inspecting the sample surface.

14. A non-transitory computer-readable medium that stores a set of instructions that is executable by at least one processor of an apparatus to cause the apparatus to perform operations comprising: determining an image of a sample surface based on detection of secondary charged particles at a charged particle detector, wherein: the image comprises an array of pixels; the secondary charged particles are associated with interaction of primary charged particles with the sample surface; andthe primary charged particles are associated with a beam of the primary charged particles directed to the sample; determining an autocorrelation function between a signal represented by a line of the pixels and delayed copies of the signal; and determining a bandwidth of the charged particle detector based on the autocorrelation function.

15. A method for measuring a bandwidth of a charged particle detector, the method comprising: determining an image of a sample surface based on detection of secondary charged particles at a charged particle detector, wherein: the image comprises an array of pixels; the secondary charged particles are associated with interaction of primary charged particles with the sample surface; and the primary charged particles are associated with a beam of the primary charged particles directed to the sample; determining an autocorrelation function between a signal represented by a line of the pixels and delayed copies of the signal; and determining a bandwidth of the charged particle detector based on the autocorrelation function.

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