Various SEM measurement methods for improved accuracy

Abstract

Charged particle beam inspection methods involve measuring a sample under multiple different signal acquisition modalities. Each modality may include a different set of inspection parameters that may be optimized for different purposes, such as high resolution or high acquisition speed. Measurements from the different signal acquisition modalities may be combined using deconvolution or other optimization tasks to form a composite image. The composite image may achieve superior resolution with higher throughput than can be achieved with a single high-resolution or high-speed scan.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to both U.S. patent application Ser. No. 63 / 443,832, filed February 7, 2023, and U.S. patent application Ser. No. 63 / 452,342, filed March 15, 2023, both of which are incorporated by reference in their entireties.

[0002] The description herein relates to metrology techniques that may be useful in the field of charged particle beam systems, and more particularly to systems and methods that may be applicable to charged particle inspection systems such as scanning electron microscope (SEM) tools. [Background technology]

[0003]

[0003] Inspection and metrology systems can be used to detect physically observable phenomena. For example, charged particle beam tools, such as electron microscopes, may be equipped with detectors that receive charged particles emitted from a sample and output a detection signal. The detection signal may be used to reconstruct an image of the sample structure under inspection, and may be used, for example, to reveal defects in the sample. Accurate imaging and detection of sample defects becomes increasingly important in the manufacture of semiconductor devices, which may include many densely packed miniature integrated circuit (IC) components. For this purpose, an inspection system may be provided.

[0004]

[0004] As semiconductor device miniaturization continues to advance, inspection systems continue to struggle with trade-offs between competing parameters such as speed and accuracy. For example, some inspections may use low beam currents to achieve high resolution at the expense of low throughput and a high signal-to-noise ratio (SNR). Other inspections may use higher beam currents to achieve higher throughput and better SNR at the expense of lower resolution. Summary of the Invention

[0005] Some embodiments of the present disclosure provide a charged particle beam inspection method, which includes measuring a first region of a sample using a charged particle beam inspection device under a first signal acquisition modality to obtain a first signal profile, measuring a second region of the sample using the charged particle beam inspection device under a second signal acquisition modality to obtain a second signal profile, the second signal acquisition modality being different from the first signal acquisition modality, and generating an inspection image based on a combination of the first signal profile and the second signal profile using an optimization task.

[0006]

[0006] Some embodiments may include a non-transitory computer-readable medium that may store a set of instructions that may be executable by at least one processor of the device to cause the device to perform the method.

[0007] Some embodiments of the present disclosure provide a charged particle beam device, which may include a charged particle beam source configured to generate a beam of primary charged particles, charged particle optics configured to direct the beam of primary charged particles toward a sample surface to inspect the sample surface, a charged particle detector configured to detect charged particles returned from the sample surface, and a controller including one or more processors and configured to operate the charged particle beam device.

[0008]

[0008] The above and other aspects of the present disclosure will become more apparent from a reading of the description of exemplary embodiments in conjunction with the accompanying drawings. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a diagrammatic representation of an exemplary electron beam inspection (EBI) system consistent with embodiments of the present disclosure. [Figure 2A]

[0010] FIG. 1 illustrates a charged particle beam device, which may be an example of an electron beam tool, consistent with embodiments of the present disclosure. [Figure 2B]

[0010] FIG. 1 illustrates a charged particle beam device that may be an example of an electron beam tool consistent with embodiments of the present disclosure. [Figure 3]

[0011] 1 is a diagrammatic representation of an exemplary signal acquisition module consistent with embodiments of the present disclosure. [Figure 4]

[0012] 1 is a diagrammatic representation of an example measurement acquisition scheme consistent with embodiments of the present disclosure. [Figure 5A]

[0013] 1 is a diagrammatic representation of an example measurement acquisition scheme consistent with embodiments of the present disclosure. [Figure 5B] 1 is a diagrammatic representation of an example measurement acquisition scheme consistent with embodiments of the present disclosure. [Figure 5C] 1 is a diagrammatic representation of an example measurement acquisition scheme consistent with embodiments of the present disclosure. [Figure 6]

[0014] 1 is a diagrammatic representation of an example measurement acquisition scheme consistent with embodiments of the present disclosure. [Figure 7]

[0015] 1 is a flowchart illustrating an example method that may be useful for generating a composite image from multiple signal acquisition modalities using an optimization task, consistent with embodiments of the present disclosure. [Figure 8]

[0016] 7 is a diagrammatic representation of an exemplary application of a method 700 that may be useful for generating a composite image from multiple signal acquisition modalities using an optimization task, consistent with embodiments of the present disclosure. [Figure 9]

[0017] 1 is a flowchart illustrating an example method that may be useful for generating a composite image from multiple signal acquisition modalities consistent with embodiments of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0010]

[0018] Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the drawings. The following description refers to the accompanying drawings, in which like numbers in different drawings represent the same or similar elements unless otherwise stated. The implementations described in the following description of exemplary embodiments do not represent all implementations consistent with the present invention. Instead, these implementations are merely examples of apparatus, systems, and methods consistent with aspects related to the subject matter that may be recited in the appended claims. For example, while some embodiments are described with reference to the use of charged particle beams (e.g., electron beams), the present disclosure is not so limited. Other types of charged particle beams (e.g., photon beams) may be similarly applied. Furthermore, other imaging systems, such as optical imaging, photodetection, and x-ray detection, may also be used.

[0011]

[0019] Electronic devices are built from circuits formed on a piece of silicon called a substrate. Many circuits may be formed together on the same piece of silicon, called an integrated circuit, or IC. Advances in technology have dramatically reduced the size of these circuits, allowing more circuits to fit on a substrate. For example, an IC chip in a smartphone can be about the size of a fingernail yet contain over 2 billion transistors, each less than 1 / 1000 the thickness of a human hair.

[0012]

[0020] Fabricating these ICs, which have multiple extremely small structures or components, is a complex, time-consuming, and expensive process that often involves hundreds of individual steps. An error in any one process can result in defects in the finished IC, rendering it unusable. Therefore, one of the goals of a manufacturing process is to avoid such defects and maximize the number of functional ICs produced by the process, i.e., improve the overall yield of the process.

[0013]

[0021] One element of improving yield is monitoring the chip manufacturing process to ensure that a sufficient number of functional integrated circuits are being produced. One way to monitor the process is to inspect the chip circuit structures at various stages of their formation. Inspection can be performed using a scanning charged particle microscope ("SCPM"). For example, an SCPM can be a scanning electron microscope (SEM). The SEM can be used to image these tiny structures, essentially taking a "picture" of them. This image can be used to determine whether the structures were formed properly and whether they were formed in the correct location. If the structures are defective, the process can be adjusted to reduce the likelihood of the defect recurring. To increase throughput (e.g., number of samples processed per hour), it is desirable to perform inspection as quickly as possible.

[0014]

[0022] The operating principle of an SEM is similar to that of a camera. A camera takes pictures by receiving and recording the intensity of light reflected or emitted from a person or object. An SEM takes "pictures" by receiving and recording the energy or quantity of electrons reflected or emitted from structures on a wafer. Before taking such a "picture," an electron beam may be projected onto the structure, and as electrons reflect or emit ("emit") from the structure (e.g., from the wafer surface, from structures below the wafer surface, or both), a detector in the SEM may receive and record the energy or quantity of those electrons to generate an inspection image. To take such a "picture," the electron beam may scan the wafer (e.g., line-by-line or in a zigzag fashion), and the detector may receive the incoming emitted electrons from the area under the electron beam projection (called the "beam spot"). The detector may receive and record the electrons emitted from each beam spot one at a time, and the recorded information for all beam spots may be combined to generate an inspection image. Some SEMs use a single electron beam (called a "single-beam SEM") to take one "picture" to generate an inspection image, while some SEMs use multiple electron beams (called a "multi-beam SEM") to take multiple "pictures" of the wafer in parallel, which can be used separately or chained together to generate an inspection image. By using multiple electron beams, the SEM can provide more electron beams onto the structure to obtain these multiple "pictures," resulting in more electrons being emitted from the structure. Thus, the detector can simultaneously receive more emitted electrons and generate images of the wafer's structures with greater efficiency and speed.

[0015]

[0023] Typically, the detection process involves measuring the magnitude of the electrical signal generated when an electron lands on a detector. Another approach may use electron counting, in which case the detector may count individual electron arrival events as they occur. In either approach, the intensity of the secondary beam may be determined based on the electrical signal generated at the detector, which changes proportionally to changes in the intensity of the secondary beam.

[0016]

[0024] Various inspection parameters, such as speed and resolution, can affect competing interests in the inspection process. For example, the landing energy and angle of incidence of the electron beam can have a significant effect on the sample's interaction volume (the region where incident electrons interact with the sample's material to generate, for example, secondary and backscattered electrons). Beam current can affect, for example, the probe's spot size and surface charging effects. These characteristics can be important factors in the scanning speed and effective resolution of an inspection tool. For example, the size of the interaction volume can relate to the minimum pixel size of the image generated during the inspection process and therefore the minimum level of detail that can be resolved.

[0017]

[0025] For example, a high-energy beam can generate a large interaction volume, which can result in a large number of electrons being emitted from the sample surface over a wide area. A large number of electrons can be sufficient to achieve a high SNR and faster acquisition of larger sample pixels, resulting in faster scan speeds. However, a large interaction volume also limits the achievable minimum resolution of the resulting image. On the other hand, a small interaction volume can reverse these costs and benefits. A small interaction volume can be achieved, for example, by using a low-energy or normal-incidence beam to generate images with finer resolution. However, a lower yield of emitted electrons can be more difficult to distinguish from noise, resulting in smaller pixels, slower scan times, and impaired throughput. Thus, conventional inspection systems suffer from an unavoidable trade-off between speed and resolution.

[0018]

[0026] Another trade-off that affects the speed of the inspection process is the risk of damage to features during inspection. High beam current inspection may not be suitable for all areas of the sample, especially areas containing sensitive components. Low beam current settings may be selected to avoid damage to such sensitive areas, but this may come at the expense of slowing down the scanning speed across the sample.

[0019]

[0027] Embodiments of the present disclosure may provide an inspection apparatus and method for generating high-resolution inspection images with high throughput. The inspection apparatus may include, for example, a charged particle beam apparatus such as an SEM tool or other electron beam tool. The apparatus may be configured to scan an area of ​​a sample surface under multiple signal acquisition modalities. Each signal acquisition modality may include a different set of inspection settings or other inspection parameters to obtain a different signal profile from the sample surface. Different signal acquisition modalities may be optimized for different purposes, such as achieving a high acquisition speed or high resolution. Optimization may include using different inspection settings to achieve different interaction volumes or other inspection parameters.

[0020]

[0028] Embodiments of the present disclosure may merge information acquired under different signal acquisition modalities to generate a high-resolution inspection image. For example, it is possible to merge acquired images by performing image synthesis or deconvolution using known information about the parameters of each signal acquisition modality. This may be achieved, for example, by solving an optimization task. Image synthesis / deconvolution may be used to combine images or features from different signal acquisition modalities or to identify and remove system noise from images. Embodiments of the present disclosure may enable the estimation of charged particle inspection images with greater accuracy than other systems can achieve at the same measurement speed, or at a higher measurement speed than other systems can achieve at the same resolution or accuracy.

[0021]

[0029] In some embodiments, the inspection device can scan an entire region of a sample under a first signal acquisition modality. Then, the inspection device can scan the entire region of the sample under a second signal acquisition modality that is different from the first signal acquisition modality. The region can include, for example, a single scan line or the entire field of view of the inspection device. By measuring the same location with multiple signal acquisition modalities, more information about the region can be obtained, producing a higher resolution image than would be obtained using a single signal acquisition modality.

[0022]

[0030] In some embodiments, the inspection device can switch between signal acquisition modalities while scanning an area. For example, the inspection device can change inspection settings on a pixel-by-pixel basis. In some embodiments, the inspection device can alternate between two or more signal acquisition modalities in a repeating sequence. In some embodiments, the inspection device can alternate between two or more signal acquisition modalities in an irregular or non-repeating sequence. In some embodiments, the inspection device can alternate between two or more signal acquisition modalities that are determined or updated in a feedforward or feedback manner based on, for example, real-time measurements or predetermined information such as a previous scan of pattern data or a reference sample.

[0023]

[0031] In some embodiments, pattern recognition sampling can be used to determine appropriate areas for switching between a first signal acquisition modality and a second signal acquisition modality. For example, an initial rough scan or pattern design file can be used to identify transition areas in a circuit pattern or other inspection sample. The transition areas can be, for example, edges of circuit pattern features where there is an abrupt change in wafer topography. Such edge features can require higher resolution imaging than is required in the relatively flat areas on either side of the edge feature, for example. Therefore, pattern recognition sampling can be used to switch between a first signal acquisition modality suitable for flat features and a second signal acquisition modality optimized for edge features.

[0024]

[0032] The objects and advantages of the present disclosure can be achieved by the elements and combinations described in the embodiments discussed herein. However, no embodiment of the present disclosure is necessarily required to achieve such exemplary objects or advantages, and some embodiments may not achieve any of the described objects or advantages.

[0025]

[0033] Without limiting the scope of the present disclosure, some embodiments may be described in connection with providing detection systems and methods in systems utilizing electron beams ("e-beams"). However, the disclosure is not so limited. Other types of charged particle beams (such as proton beams) may be similarly applicable. Furthermore, the detection systems and methods may be used in other imaging systems, such as optical imaging, photon detection, proton detection, x-ray detection, ion detection, etc. Photon detection may include infrared, visible light, UV, DUV, EUV, x-ray, or light in any other wavelength range. Thus, although detectors in the present disclosure may be disclosed with respect to electron detection, some embodiments of the present disclosure may be directed to the detection of other charged particles or photons.

[0026]

[0034] As used herein, unless specifically stated otherwise, the term "or" includes all possible combinations except where feasible. For example, if a component is stated to include A or B, the component may include A, or B, or A and B, unless specifically stated otherwise or feasible. As a second example, if a component is stated to include A, B, or C, the component may include A, or B, or C, or A and B, or A and C, or B and C, or A, B, and C, unless specifically stated otherwise or feasible.

[0027]

[0035] Referring now to FIG. 1 , FIG. 1 illustrates an exemplary electron beam inspection (EBI) system 10 that may be used for wafer inspection consistent with embodiments of the present disclosure. As shown in FIG. 1 , the EBI system 10 includes a main chamber 11, a load / lock chamber 20, an electron beam tool 100 (e.g., a scanning electron microscope (SEM)), and an equipment front-end module (EFEM) 30. The electron beam tool 100 is disposed within the main chamber 11 and may be used for imaging. The EFEM 30 includes a first load port 30 a and a second load port 30 b. The EFEM 30 may include additional load ports. The first load port 30 a and the second load port 30 b receive wafers (e.g., semiconductor wafers or wafers made of other materials) or wafer front-opening integrated pods (FOUPs) containing samples to be inspected (wafers and samples may collectively be referred to herein as “wafers”).

[0028]

[0036] One or more robot arms (not shown) of the EFEM 30 can transfer wafers to the load / lock chamber 20. The load / lock chamber 20 is connected to a load / lock vacuum pumping system (not shown) that removes gas molecules from the load / lock chamber 20 to reach a first pressure below atmospheric pressure. After the first pressure is reached, one or more robot arms (not shown) can transfer the wafers from the load / lock chamber 20 to the main chamber 11. The main chamber 11 is connected to a main chamber vacuum pumping system (not shown) that removes gas molecules from the main chamber 11 to reach a second pressure less than the first pressure. After the second pressure is reached, the wafers are inspected by the electron beam tool 100. The electron beam tool 100 can be a single-beam system or a multi-beam system. A controller 109 is electronically connected to the electron beam tool 100 and can be electronically connected to other components as well. The controller 109 can be a computer configured to perform various controls of the EBI system 10. In FIG. 1, the controller 109 is shown as being external to the structure including the main chamber 11, the load / lock chamber 20, and the EFEM 30, but it is understood that the controller 109 may also be part of the structure.

[0029]

[0037] In some embodiments, the controller 109 may include one or more processors (not shown). A processor may be a general-purpose or special-purpose electronic device capable of manipulating or processing information. For example, a processor may include any number or combination of a central processing unit (or "CPU"), a graphics processing unit (or "GPU"), an optical processor, a programmable logic controller, a microcontroller, a microprocessor, a digital signal processor, an intellectual property (IP) core, a programmable logic array (PLA), a programmable array logic (PAL), a generic array logic (GAL), a complex programmable logic device (CPLD), a field programmable gate array (FPGA), a system-on-chip (SoC), an application-specific integrated circuit (ASIC), and any other type of circuit capable of processing data. A processor may also be a virtual processor, including one or more processors distributed across multiple machines or devices coupled via a network.

[0030]

[0038] In some embodiments, the controller 109 may further include one or more memories (not shown). Memory may be a general-purpose or special-purpose electronic device capable of storing code and data accessible by the processor (e.g., via a bus). For example, memory may include any combination of any number of random access memory (RAM), read-only memory (ROM), optical disks, magnetic disks, hard drives, solid-state drives, flash drives, security digital (SD) cards, memory sticks, compact flash (CF) cards, or any type of storage device. Code may include an operating system (OS) and one or more application programs (or "apps") for specific tasks. Memory may also be virtual memory, which includes one or more memories distributed across multiple machines or devices coupled via a network.

[0031]

[0039] Charged particle beam microscopes, such as those formed by or that may be included in EBI system 10, may be capable of resolution down to the nanometer scale, for example, and may serve as practical tools for inspecting IC components on wafers. In e-beam systems, electrons from a primary electron beam may be focused onto a probe spot on the wafer being inspected. The interaction of the primary electrons with the wafer may form a secondary particle beam. The secondary particle beam may include backscattered electrons, secondary electrons, Auger electrons, or the like, resulting from the interaction of the primary electrons with the wafer. The characteristics (e.g., intensity) of the secondary particle beam may vary based on the properties of the internal or external structure or material of the wafer and may therefore indicate whether the wafer is defective.

[0032]

[0040] The intensity of the secondary particle beam can be determined using a detector. The secondary particle beam can form a beam spot on the surface of the detector. The detector can generate an electrical signal (e.g., current, charge, voltage, etc.) representing the intensity of the detected secondary particle beam. The electrical signal can be measured with a measurement circuit, which can include additional components (e.g., an analog-to-digital converter) for obtaining a distribution of the detected electrons. The electron distribution data collected during the detection time window can be used in combination with corresponding scan path data of the primary electron beam incident on the wafer surface to reconstruct an image of the wafer structure or material under inspection. The reconstructed image can be used to reveal various features of the internal or external structure of the wafer, as well as any defects that may be present in the wafer.

[0033]

[0041] 2A illustrates a charged particle beam device that may be one example of an electron beam tool 100 consistent with embodiments of the present disclosure. FIG. 2A illustrates an apparatus that uses multiple beamlets formed from a primary electron beam to simultaneously scan multiple locations on a wafer.

[0034]

[0042] As shown in FIG. 2A , the electron beam tool 100A may include an electron source 202, a gun aperture 204, a condenser lens 206, a primary electron beam 210 emitted from the electron source 202, a source conversion unit 212, multiple beamlets 214, 216, and 218 of the primary electron beam 210, a primary projection optics 220, a wafer stage (not shown in FIG. 2A ), multiple secondary electron beams 236, 238, and 240, a secondary optics 242, and an electron detection device 244. The electron source 202 may generate primary particles, such as electrons in the primary electron beam 210. A controller, an image processing system, and the like may be coupled to the electron detection device 244. The primary projection optics 220 may include a beam separator 222, a deflection scanning unit 226, and an objective lens 228. The electron detection device 244 may include detection subregions 246, 248, and 250.

[0035]

[0043] Electron source 202, gun aperture 204, condenser lens 206, source conversion unit 212, beam separator 222, deflection scanning unit 226, and objective lens 228 may be aligned with primary optical axis 260 of apparatus 100A. Secondary optics 242 and electron detection device 244 may be aligned with secondary optical axis 215 of apparatus 100A.

[0036]

[0044] The electron source 202 may include a cathode, an extraction electrode, or an anode, and primary electrons may be emitted from the cathode and extracted or accelerated to form a primary electron beam 210 with a crossover (virtual or real) 208. The primary electron beam 210 may be visualized as being emitted from the crossover 208. The gun aperture 204 may block peripheral electrons of the primary electron beam 210 to reduce the size of the probe spots 270, 272, and 274.

[0037]

[0045] The source conversion unit 212 may include an image-forming element array (not shown in FIG. 2A ) and a beam-limiting aperture array (not shown in FIG. 2A ). Examples of the source conversion unit 212 can be found in U.S. Pat. No. 9,691,586, U.S. Patent Application Publication No. 2017 / 0021543, and International Application No. PCT / EP2017 / 084429, all of which are incorporated by reference in their entireties. The image-forming element array may include an array of micro-deflectors or micro-lenses. The image-forming element array can form multiple parallel images (virtual or real images) of the crossover 208 with the multiple beamlets 214, 216, and 218 of the primary electron beam 210. The beam-limiting aperture array can limit the multiple beamlets 214, 216, and 218.

[0038]

[0046] The condenser lens 206 can focus the primary electron beam 210. The currents of the beamlets 214, 216, and 218 downstream of the source conversion unit 212 can be varied by adjusting the focusing power of the condenser lens 206 or by changing the radial size of the corresponding beam-limiting apertures in the beam-limiting aperture array. The condenser lens 206 can be an adjustable condenser lens that can be configured to have a movable first principal plane position. The adjustable condenser lens can be configured to be magnetic, so that the off-axis beamlets 216 and 218 land on the beamlet-limiting apertures at a rotation angle. The rotation angle varies with the focusing power and the position of the first principal plane of the adjustable condenser lens. In some embodiments, the adjustable condenser lens can be an adjustable anti-rotation condenser lens that includes an anti-rotation lens with a movable first principal plane. An example of an adjustable focusing lens is further described in U.S. Patent Application Publication No. 2017 / 0021541, which is incorporated by reference herein in its entirety.

[0039]

[0047] The objective lens 228 can focus the beamlets 214, 216, and 218 onto the wafer 230 under inspection, forming multiple probe spots 270, 272, and 274 on the surface of the wafer 230. Secondary electron beams 236, 238, and 240 can be formed that emit from the wafer 230 and return toward the beam separator 222.

[0040]

[0048] Beam separator 222 may be a Wien filter-type beam separator that generates electrostatic and magnetic dipole fields. In some embodiments, when these fields are applied, the force exerted on electrons in beamlets 214, 216, and 218 by the electrostatic dipole field may be equal in magnitude and opposite in direction to the force exerted on electrons by the magnetic dipole field. Therefore, beamlets 214, 216, and 218 may pass through beam separator 222 in a straight line with zero deflection angle. However, the total dispersion of beamlets 214, 216, and 218 caused by beam separator 222 may be non-zero. Beam separator 222 may separate secondary electron beams 236, 238, and 240 from beamlets 214, 216, and 218 and direct secondary electron beams 236, 238, and 240 toward secondary optics 242.

[0041]

[0049] The deflection scanning unit 226 can deflect the beamlets 214, 216, and 218 to scan the probe spots 270, 272, and 274 across the surface area of ​​the wafer 230. In response to the beamlets 214, 216, and 218 impinging on the probe spots 270, 272, and 274, secondary electron beams 236, 238, and 240 can be emitted from the wafer 230. The secondary electron beams 236, 238, and 240 can include electrons having an energy distribution, including secondary electrons and backscattered electrons. The secondary optics 242 can focus the secondary electron beams 236, 238, and 240 onto detection subregions 246, 248, and 250 of the electron detection device 244. The detection subregions 246, 248, and 250 can be configured to detect the corresponding secondary electron beams 236, 238, and 240 and generate corresponding signals used to reconstruct an image of the surface area of ​​the wafer 230.

[0042]

[0050] The generated signals can represent the intensities of the secondary electron beams 236, 238, and 240 and can be provided to an image processing system (such as image processing system 199 provided in FIG. 2B below) in communication with the detection device 244, the primary projection optics 220, and the motorized wafer stage. The speed of movement of the motorized wafer stage can be synchronized and coordinated with the beam deflection controlled by the deflection scanning unit 226 so that movement of the scanning probe spots (e.g., scanning probe spots 270, 272, and 274) can sequentially cover the target area on the wafer 230. Such synchronization and coordination parameters can be adjusted to accommodate wafers 230 made of different materials. For example, wafers 230 made of different materials can have different resistance-capacitance characteristics that can cause different signal sensitivities to movement of the scanning probe spots.

[0043]

[0051] The intensities of the emitted secondary electron beams 236, 238, and 240 may vary depending on the external or internal structure of the wafer 230 and may therefore indicate whether the wafer 230 contains defects. Furthermore, as described above, the beamlets 214, 216, and 218 may be projected at different locations on the top surface of the wafer 230 or on different sides of local structures on the wafer 230 to generate secondary electron beams 236, 238, and 240 that may have different intensities. Thus, by mapping the intensities of the emitted secondary electron beams 236, 238, and 240 with areas of the wafer 230, an image processing system may reconstruct an image that reflects the characteristics of the internal or external structures of the wafer 230.

[0044]

[0052] Detection sub-regions 246, 248, and 250 may comprise separate detector packages, separate sensing elements, or separate regions of an array detector. In some embodiments, each detection sub-region may comprise a single sensing element.

[0045]

[0053] Another example of a charged particle beam device will now be discussed with reference to Figure 2B. Electron beam tool 100B (also referred to herein as device 100B) may be an example of an electron beam tool 100 and may be similar to electron beam tool 100A shown in Figure 2A. However, unlike device 100A, device 100B may be a single-beam tool that uses only one primary electron beam to scan locations on a wafer one at a time.

[0046]

[0054] 2B, apparatus 100B includes a wafer holder 136 supported by a motorized stage 134 for holding a wafer 150 to be inspected. Electron beam tool 100B includes an electron emitter, which may include a cathode 103, an anode 121, and a gun aperture 122. Electron beam tool 100B further includes a beam-limiting aperture 125, a condenser lens 126, a column aperture 135, an objective lens assembly 132, and a detector 144. Objective lens assembly 132 may be a modified SORIL lens in some embodiments and includes a pole piece 132a, a control electrode 132b, a deflector 132c, and an excitation coil 132d. In the detection or imaging process, an electron beam 161 emanating from the tip of the cathode 103 is accelerated by the voltage on the anode 121, passes through the gun aperture 122, the beam limiting aperture 125, the condenser lens 126, and is focused by a modified SORIL lens to a probe spot 170, which can then impinge on the surface of the wafer 150. A deflector, such as deflector 132c or another deflector in a SORIL lens, can cause the probe spot 170 to be scanned across the surface of the wafer 150. Secondary or scattered particles, such as secondary electrons or scattered primary electrons emanating from the wafer surface, are collected by a detector 144, allowing the intensity of the beam to be determined, so that an image of the area of ​​interest on the wafer 150 can be reconstructed.

[0047]

[0055] An image processing system 199 may also be provided, including the image acquirer 120, the storage 130, and the controller 109. The image acquirer 120 may include one or more processors. For example, the image acquirer 120 may include a computer, a server, a mainframe host, a terminal, a personal computer, any type of mobile computing device, and the like, or a combination thereof. The image acquirer 120 may be communicatively coupled to the detector 144 of the electron beam tool 100B through a medium such as an electrical conductor, a fiber optic cable, a portable storage medium, IR, Bluetooth, the Internet, a wireless network, wireless communication, or a combination thereof. The image acquirer 120 may receive signals from the detector 144 and construct an image. Thus, the image acquirer 120 may acquire an image of the wafer 150. The image acquirer 120 may also perform various post-processing functions, such as image averaging, contouring, overlaying indicators on the acquired image, and the like. The image acquirer 120 may be configured to perform adjustments, such as brightness and contrast, of the acquired image. The storage 130 may be a storage medium such as a hard disk, random access memory (RAM), cloud storage, other types of computer-readable memory, and the like. The storage 130 may be coupled to the image acquirer 120 and may be used to store scanned raw image data as original images and to store post-processed images. The image acquirer 120 and the storage 130 may be connected to the controller 109. In some embodiments, the image acquirer 120, the storage 130, and the controller 109 may be integrated together as one electronic control unit.

[0048]

[0056] In some embodiments, the image acquirer 120 can acquire one or more images of the sample based on imaging signals received from the detector 144. The imaging signals can correspond to a scanning motion for performing charged particle imaging. The acquired image can be a single image including multiple imaging areas that can include various features of the wafer 150. The single image can be stored in the storage 130. The imaging can be performed based on imaging frames.

[0049]

[0057] The collector and illumination optics of an electron beam tool can include or be supplemented by electromagnetic quadrupole electron lenses. For example, as shown in FIG. 2B , electron beam tool 100B can include a first quadrupole lens 148 and a second quadrupole lens 149. In some embodiments, the quadrupole lenses are used to control the electron beam. For example, first quadrupole lens 148 can be controlled to adjust the beam current, and second quadrupole lens 149 can be controlled to adjust the beam spot size and beam shape.

[0050]

[0058] FIG. 2B illustrates a charged particle beam device that may use a single primary beam configured to generate secondary electrons by interacting with a wafer 150. The detector 144 may be positioned along the optical axis 105, as in the embodiment shown in FIG. 2B. The primary electron beam may be configured to travel along the optical axis 105. Accordingly, the detector 144 may include a hole in its center to allow the primary electron beam to pass through and reach the wafer 150. FIG. 2B illustrates an example of a detector 144 with an opening in its center. However, some embodiments may use a detector positioned off-axis with respect to the optical axis along which the primary electron beam travels. For example, as in the embodiment shown in FIG. 2A above, a beam separator 222 may be provided to direct the secondary electron beam toward the off-axis detector. The beam separator 222 may be configured to redirect the secondary electron beam by an angle α toward the electron detection device 244, as shown in FIG. 2A.

[0051]

[0059] A detector in a charged particle beam system can include one or more detector elements. The detector can include a single element detector or an array of multiple detector elements. The detector elements can be configured for charged particle counting. Detector detector elements that can be useful for charged particle counting are described in U.S. Patent Application Publication No. 2019 / 0379682, which is incorporated by reference in its entirety.

[0052]

[0060] The sensing element may include a diode or diode-like element capable of converting incident energy into a measurable signal. For example, the sensing element in a detector may include a PIN diode. Throughout this disclosure, the sensing element may be represented as a diode in figures, for example, although the sensing element or other component may deviate from the ideal circuit behavior of electrical elements such as diodes, resistors, capacitors, etc.

[0053]

[0061] FIG. 3 illustrates first and second exemplary signal acquisition modalities 353 and 354 consistent with embodiments of the present disclosure. The first and second signal acquisition modalities 353-354 may be used in an inspection apparatus, such as the electron beam tool 100 of FIG. 1 , the electron beam tool 100A of FIG. 2A , or the electron beam tool 100B of FIG. 2B . FIG. 3 illustrates a top view and a cross-sectional view of a region of a sample 350 under inspection. For example, the sample 350 may be a semiconductor wafer, and the region may be a field of view of an inspection apparatus. In FIG. 3 , as in further exemplary embodiments such as FIGS. 4-6 , the sample 350 (or sample 450 / 550 / 650) may include a vertical line / space pattern for illustrative purposes. The line / space pattern may include multiple substantially flat regions 351 separated by edge features 352. In practice, the signal acquisition modalities may be applied to the inspection of any sample, including integrated circuits, other semiconductor devices, photomasks, or other samples.

[0054]

[0062] Under the first signal acquisition modality 353, the sample 350 may be irradiated with a charged particle beam by scanning large pixel areas successively in a row along the fast scan direction FS. The charged particle beam and the sample may be relatively displaced by electrical or mechanical means in the slow scan direction SS to irradiate subsequent rows of large pixel areas until substantially the entire region has been examined under the first signal acquisition modality 353. The second signal acquisition modality 354 may be used in a manner similar to the first signal acquisition modality 353 but may correspond to smaller pixel areas, for example, as seen in FIG. 3 . The two signal acquisition modalities may be further distinguished as discussed below. Note that adjacent large pixel areas of the first signal acquisition modality 353 are shown as being in a spaced-apart relationship for clarity. In some embodiments, the large pixel areas may abut or overlap each other in the fast scan direction FS or the slow scan direction SS. Similarly, adjacent small pixel areas of the second signal acquisition modality 354 are shown as spaced apart for clarity, although in some embodiments the small pixel areas may abut or overlap one another in the fast scan direction FS or the slow scan direction SS. Furthermore, it should be understood that the illustrated pixel areas, along with their corresponding interaction volumes 355 / 356 and signal profiles 357 / 358, are highly schematic in nature and are provided for illustrative purposes.

[0055]

[0063] The size of the pixel area in the first or second signal acquisition modality 353 or 354 may depend on the size and other characteristics of the corresponding interaction volumes 355 and 356 resulting from the selected inspection parameters of the signal acquisition modality. The interaction volume can be considered the volume of surface and subsurface material of the sample 350 in which incident charged particles interact with the material of the sample 350 to generate secondary charged particles. In the case of an electron beam tool, the secondary charged particles may include, for example, secondary electrons, backscattered electrons, Auger electrons, etc. A larger interaction volume may generate a larger number of secondary electrons at the detector surface originating from a relatively large area of ​​the sample. Therefore, a larger interaction volume may correspond to higher signal intensity / higher SNR and faster signal acquisition time. However, a large interaction volume may also result in insufficient imaging resolution. Therefore, an inspection scan under the first signal acquisition modality 353 may result in a lower-noise, lower-resolution signal profile 357. On the other hand, a smaller interaction volume may generate fewer secondary electrons at the detector surface, which originate from a relatively small area of ​​the sample. Therefore, a smaller interaction volume may correspond to a higher imaging resolution. However, a smaller number of secondary electrons may be more difficult to distinguish from system noise, resulting in a lower SNR and longer signal acquisition times. Therefore, an inspection scan under the second signal acquisition modality 354 may result in a higher noise, higher resolution signal profile 358.

[0056]

[0064] Inspection tool parameters that can significantly affect the interaction volume include beam current, acceleration voltage, landing energy, and beam incidence angle. For example, the first signal acquisition modality 353 can use a relatively high beam current, a higher acceleration voltage or landing energy, or a lower or normal incidence angle to generate a larger interaction volume 355. The second signal acquisition modality 354 can use a relatively low beam current, a lower acceleration voltage or landing energy, or a higher incidence angle to generate a smaller interaction volume 356.

[0057]

[0065] In some embodiments, the first signal acquisition modality 353 and the second signal acquisition modality 354 may differ in ways other than interaction volume, resolution, SNR, pixel size, or acquisition speed. In general, scanning a sample under any number of different inspection tool settings may yield additional useful information about the sample in light of the different signal profiles each modality produces. When subjected to an image synthesis process, as described below, many signal acquisition modalities can be combined to produce enhanced, higher quality inspection images. Inspection tool settings may include, for example, beam current, landing energy, acceleration voltage, beam incidence angle, probe spot size, wafer orientation / beam scan angle, field of view size and shape, beam aperture setting, lens aberration values, focus, lens / deflector or other charged particle optics settings, or other charged particle inspection tool parameters.

[0058]

[0066] Additionally, some embodiments of the present disclosure are described with respect to only two signal acquisition modalities, such as the first signal acquisition modality 353 and the second signal acquisition modality 354 described above. However, embodiments of the present disclosure are not limited thereto. For example, some measurement schemes according to embodiments of the present disclosure are discussed with respect to only first and second signal acquisition modalities, but three or more may be utilized. For example, a measurement scheme may employ 2, 3, 4, ..., up to any number (N) of unique signal acquisition modalities.

[0059]

[0067] 4 illustrates an example measurement scheme 400 consistent with embodiments of the present disclosure. Measurement scheme 400 may be performed using an inspection apparatus such as, for example, electron beam tool 100 of FIG. 1, electron beam tool 100A of FIG. 2A, or electron beam tool 100B of FIG. 2B.

[0060]

[0068] Measurement scheme 400 may include a first measurement of a region of sample 450 under a first signal acquisition modality 453 and a second measurement of the region under a second signal acquisition modality 454. In other words, the same region of sample 450 may be scanned under multiple signal acquisition modalities. In some embodiments, the region may comprise a field of view of the inspection tool. In some embodiments, the region may comprise a portion of a field of view, such as a single scan line, multiple scan lines, or a portion of a scan line.

[0061]

[0069] For example, measurement scheme 400 may include performing a scan measurement of a first scan line under a first signal acquisition modality 453 and performing a scan measurement of the first scan line under a second signal acquisition modality 454. Some embodiments may include further scans up to an Nth scan measurement of the first scan line under an Nth signal acquisition modality. The sample 450 may then be displaced in the slow scan direction SS relative to the charged particle beam spot, and this process may be repeated on a second scan line, for example, until the entire field of view has been scanned under all signal acquisition modalities. In some embodiments, the entire field of view may be scanned under one signal acquisition modality, and then proceed to scan the entire field of view under the next signal acquisition modality.

[0062]

[0070] The first signal acquisition modality 453 may be configured, for example, for lower resolution, lower noise, and faster measurements (similar to the first signal acquisition modality 353 of FIG. 3), thereby generating a first signal profile 457. The second signal acquisition modality 454 may be configured, for example, for higher resolution, higher noise, and slower measurements (similar to the second signal acquisition modality 354 of FIG. 3), thereby generating a second signal profile 458.

[0063]

[0071] Image synthesis can be performed using the first and second signal profiles 457 and 458 to generate an enhanced composite image 459 of the surface of the sample 450. The composite image 459 can be used, for example, in a metrology process, an inspection process such as mask or wafer defect inspection, etc. Image synthesis can include solving a convex or non-convex optimization task (as discussed below with respect to FIGS. 7-8). In some embodiments, the optimization task can include a deconvolution task configured to reduce or eliminate system noise, aberrations, or other undesirable imaging effects.

[0064]

[0072] In the above discussion of FIG. 4 , it can be said that the “same” region can be scanned by the first and second image acquisition modalities. However, as discussed with respect to FIG. 3 and shown in FIG. 4 , the region illuminated by a single scan line under different signal acquisition modalities may not be identical if the interaction volumes and resulting pixel areas are substantially different. As described herein, in some embodiments, two signal acquisition modalities can be considered to illuminate the same region if, for example, the inspection beam spot or the resulting interaction volume is substantially centered on the same region in at least one planar direction. For example, FIG. 4 shows two linear scans with significantly different widths in the slow scan direction SS, but their center locations in the slow scan direction SS are substantially the same. Therefore, it can be said that the first signal acquisition modality 453 and the second signal acquisition modality 454 illuminate the same region.

[0065]

[0073] While the example of FIG. 4 can achieve excellent quality inspection image 459, in some embodiments it may be desirable to scan the sample with less redundancy. For example, while some embodiments of measurement scheme 400 may include scanning the same portion of sample 450 under multiple signal acquisition modalities, in some embodiments it may be desirable to scan different portions of the sample surface using different sets of signal acquisition modalities. The resulting partial signal profiles may then be combined to form a higher resolution image with higher throughput. Some examples of such embodiments are described below with respect to FIGS. 5A-5C.

[0066]

[0074] 5A-5C illustrate exemplary measurement schemes 500A-C consistent with embodiments of the present disclosure. Measurement schemes 500A-C may be similar to measurement scheme 400, except as described below. In particular, some embodiments of measurement schemes 500A-C may include multi-modality measurements in which different regions of the surface of sample 550 may be measured under different signal acquisition modalities.

[0067]

[0075] The measurement scheme 500A of FIG. 5A may include performing a multi-modality measurement sequence. For example, the multi-modality measurement sequence may include first and second signal acquisition modalities 553 / 554, similar to modalities 353 / 354 of FIG. 3 or modalities 453 / 454 of FIG. 4. However, instead of scanning the entire region (e.g., all scan lines or the entire field of view) under a single modality, the multi-modality measurement sequence may switch between signal acquisition modalities in real time during the scan. The resulting signal profiles are shown on the right side of FIG. 5A as a set of partial signal profiles 557 and 558. Partial signal profile 557 may represent a segment of sample 550 scanned under first (e.g., lower resolution, lower noise, faster) signal acquisition modality 553. Partial signal profile 558 may represent a segment of sample 550 scanned under second (e.g., higher resolution, higher noise, slower) signal acquisition modality 554. Partial signal profiles 557 and 558 may be combined, for example, using an optimization task, to form composite image 559. Composite image 559 may have higher resolution than would be achievable, for example, by scanning the entire region under first signal acquisition modality 553. Furthermore, composite image 559 may have less noise and faster acquisition time than would be achievable, for example, by scanning the entire region under second signal acquisition modality 554. In some embodiments, combining two or more partial signal profiles may result in a composite image in which substantially all image characteristics are superior to any individual signal acquisition modality.

[0068]

[0076] In the measurement scheme 500B of FIG. 5B, the multi-modality measurement sequence may alternate between a slow scan direction SS rather than a fast scan direction FS. For example, a first line may be scanned under a first signal acquisition modality 553, and a second line may be scanned under a second signal acquisition modality 554. Signal profiles 557 and 558 may then be combined to form a higher-resolution, lower-noise composite image 559. Unlike the example of FIG. 4, in which the same region was scanned multiple times, measurement scheme 500B may sequentially scan adjacent or partially overlapping regions under different signal acquisition modalities. This may achieve an enhanced image 559 with greater throughput.

[0069]

[0077] Furthermore, as shown in FIG. 5C , the measurement scheme 500C may include multiple multi-modality measurement sequences alternating in both the fast scan FS direction and the slow scan SS direction. For example, the first signal acquisition modality 553 and the second signal acquisition modality 554 may alternate in multiple complementary sequences. For example, the inspection device may irradiate a first scan line of the sample 550 under a first multi-modality measurement sequence and scan a second scan line of the sample 550 under a second multi-modality measurement sequence. In some embodiments, the first and second multi-modality measurement sequences may be complementary to ensure that adjacent areas in the fast scan direction FS and the slow scan direction SS are measured under different signal acquisition modalities. For example, the sequences may be arranged to create a checkerboard or other 2D pattern.

[0070]

[0078] The first multi-modality measurement sequence can generate a plurality of first partial signal profiles 557 a / 558 a, and the second multi-modality measurement sequence can generate a plurality of second partial signal profiles 557 b / 558 b. Image synthesis can be used to merge all the partial signal profiles to generate a composite image 559.

[0071]

[0079] Although embodiments of the present disclosure generally illustrate an immediate transition between a first and second signal acquisition modality, in practice, this may not necessarily be the case. In some embodiments, the change may be more gradual, for example, due to a mismatch between the scan speed of the fast scan direction FS and the time required to transition between the inspection tool settings of the first and second signal acquisition modalities. In some embodiments, this gradual transition may include or be represented by one or more discrete signal acquisition modalities in which a parameter assumes a value between the values ​​of the signal acquisition modalities on either side of it. For example, the act of switching between a first (low-resolution, low-noise, high-speed) signal acquisition modality and a second (high-resolution, high-noise, low-speed) signal acquisition modality may include a period that may be represented by a third (medium-resolution, medium-noise, medium-speed) signal acquisition modality. Alternatively, the transition may include intentionally setting the inspection device to the third signal acquisition modality. Such transition modalities may allow measurement schemes to be performed with greater knowledge of the tool settings at each exposure pixel, thus allowing improved modeling and synthesis of the acquired signal profile.

[0072]

[0080] While the multi-modality sequences in Figures 5A-5C are shown as regularly repeating and binary, this is not necessarily the case. Some embodiments may include a sequence of 2, 3, 4, ..., up to any number (N) of signal acquisition modalities. The sequence may be simple and monotonic (e.g., 1-2-3-1-2-3, 1-1-2-2-2, etc.) or more complex and oscillatory (e.g., 1-2-1-3-1-4-1-3-1-2). In some embodiments, the multi-modality measurements may not have a repeating or identifiable sequence. For example, the inspection device may be configured to alternate between different signal acquisition modalities in a random or pseudo-random manner.

[0073]

[0081] Furthermore, in some embodiments, as shown in FIG. 5A , the multi-modality measurement sequence may not correspond to the sequence of pattern features on the sample. For example, the repeat period of the multi-modality measurement sequence may not align with the repeat period of the pattern feature under inspection. This can be advantageous because it allows different segments of the repeating pattern to be scanned under different signal acquisition modalities. However, in other embodiments, the multi-modality measurement sequence may be designed to match the pattern under inspection. For example, the multi-modality measurement sequence may be configured to illuminate a flat region 551 with a first signal acquisition modality 553 and an edge feature 552 with a second signal acquisition modality 554.

[0074]

[0082] In some embodiments, the multi-modality measurement sequence may be designed based on known information, such as a GDS file or other pattern design data. In some embodiments, pixel intensities measured at a first point may be used to infer information about the pattern characteristics under inspection (e.g., flat vs. edge regions, material properties, surface height, or other topography) at subsequent points. The dynamic multi-modality measurement sequence may be determined or adjusted in real time, or on a sample-by-sample or lot-by-lot basis. The dynamic determination may be based, for example, on feedforward or feedback information, machine learning training sets, or deep learning systems. In some embodiments, a reference region or reference sample may be scanned under a coarse signal acquisition modality (e.g., low-resolution, high-speed acquisition modality 553) to identify important feature areas for scanning under a fine signal acquisition modality (e.g., high-resolution, slow-speed acquisition modality 554).

[0075]

[0083] For example, FIG. 6 illustrates a further exemplary measurement scheme 600 consistent with embodiments of the present disclosure. The measurement scheme 600 may include feature-aware sampling under a second signal acquisition modality 654 based on information acquired under a first signal acquisition modality 653. For example, a first scan of an area of ​​a sample 650 may be performed under the first signal acquisition modality 653 to roughly distinguish important edge features 652 from flat areas 651. The first scan may include scanning the entire field of view or only a selected portion of the field of view. In some embodiments, the first scan may be performed under the second signal acquisition modality 654 on a different field of view or a different sample than the second scan. In some embodiments, a GDS file or other pattern design data may be used as an alternative to or in addition to the first scan.

[0076]

[0084] A second scan under the second signal acquisition modality 654 may then be applied only to regions where significant features 652 are expected to be found. In this manner, throughput may be improved by reserving the slower, higher resolution modality only for areas where it is deemed necessary. Noise components in the high resolution signal profile 658 may be mitigated by image blending with the low noise signal profile 657 to produce an enhanced blended image 659.

[0077]

[0085] In some embodiments, pattern recognition sampling or other multi-modality measurement sequences can be designed to accommodate sensitive structures on the sample surface. For example, some components of the sample may be susceptible to damage when irradiated under high beam current. Thus, using any of the measurement schemes described above, sensitive structures can be switched from a high-current signal acquisition modality to a low-current signal acquisition modality, for example. By reserving a slow signal acquisition modality only for areas requiring low beam current, throughput can be increased.

[0078]

[0086] In some embodiments of the present disclosure, knowledge of the flat region 651 can be used to identify noise components in the acquired signal profile. For example, by scanning the same or similar flat region 651 of the sample surface under multiple signal acquisition modalities or in multiple locations within the field of view, it may be possible to better separate aberration and system noise components from the measurements.

[0079]

[0087] 7 is a flowchart illustrating a method 700 that may be useful for generating a composite image from multiple signal acquisition modalities using an optimization task consistent with embodiments of the present disclosure. Method 700 may be performed using, for example, electron beam tool 100 of FIG. 1, electron beam tool 100A of FIG. 2A, or electron beam tool 100B of FIG. 2B. For example, some method steps may be performed using a controller, such as, for example, controller 109 of FIG. 1 or image acquisition unit 199 of FIG. 2B. In some embodiments, method 700 may be performed in conjunction with, for example, any of measurement schemes 400-600 of FIGS. 4-6, respectively.

[0080]

[0088] In step 701, N locations on the sample may be illuminated under m signal acquisition modalities, respectively, to obtain m*N signal profiles as images of regions on the sample surface. Each signal acquisition modality may correspond to a unique set of inspection tool settings described above. In some embodiments, different signal acquisition modalities may correspond to different regions within each of the N locations. For example, in some embodiments, the locations may correspond to a field of view of the sample, and each region may correspond to a portion of the field of view that is illuminated under a particular signal acquisition modality. Note that in some embodiments, not all locations are illuminated under the same number or type of signal acquisition modalities.

[0081]

[0089] In steps 702, 703, the m*N signal profiles acquired in step 701 may be used in combination with the signal acquisition modalities with which the m*N signal profiles were captured to determine the numerical value of the composite image. Specifically, in step 702, a loss function may be formed based on the numerical parameters of the composite image, the acquired signal profiles, and the signal acquisition modalities. In step 703, the numerical parameters of the composite image may be determined by minimizing the loss function with respect to the numerical parameters of the composite image (and optionally with respect to other parameters, as described below).

[0082]

[0090] In step 704, an inspection process, such as metrology or defect inspection, may be performed using the composite image. For example, it may be determined whether the product model meets anomaly criteria that indicate the presence of a defect. Optionally, the location of the defect on the area of ​​the sample may also be estimated. If a defect is detected, further metrology and / or defect inspection may be performed. Alternatively or additionally, step 704 may include metrology (measurement) on the product model.

[0083]

[0091] An example application of the method 700 of FIG. 7 is further described with reference to FIG. 8. In step 701, multiple signal profiles may be acquired under multiple signal acquisition modalities. Each signal profile may constitute an acquired image of an area on a location of a sample. FIG. 8 shows three acquired signal profile images 857. For example, the images may be acquired according to the measurement scheme 400 of FIG. 4 and may correspond to an area on a field of view of the sample. The signal acquisition modalities may include a first signal acquisition modality configured to generate a larger interaction volume and a second signal acquisition modality configured to generate a smaller interaction volume. The first signal acquisition modality may be configured with a higher acquisition rate, a higher SNR, and a lower resolution. The second signal acquisition modality may be configured with a lower acquisition rate, a lower SNR, and a higher resolution. Thus, the image 857 may be, for example, blurry and have poor spatial resolution, or may have higher resolution but poor SNR. The acquired images may be {P k} where k is an integer index, k=1, ...(m*N), N is the number of imaged locations, and m is the number of distinct signal acquisition modalities within each of the N images.

[0084]

[0092] Each acquired image 857 may include an n×n array of pixels, where n is an integer (for simplicity, a square array of pixels is considered, although in some embodiments the array need not be square), and each pixel may have a respective brightness value associated with it.

[0085]

[0093] The composite image in this example of method 700 may include, for example, a set of m*N images, shown as 859 in FIG. 8, that have a one-to-one correspondence with acquired image 857. Each image 859 may include a p×p array of pixels, where p is an integer, and each pixel has an associated intensity value. The intensity values ​​of all images 859 may collectively form the numerical value of the composite image. Image 859 may be referred to as a "reconstructed" image. The reconstructed image may be expressed as {X k}. Reconstructed image 859 may have a higher resolution or SNR than acquired image 857. Furthermore, p may be greater than n. Reconstructed image 859 may have a higher pixel resolution than acquired image 857 in that a given distance on the sample area may span a greater number of pixels in reconstructed image 859 than in acquired image 857.

[0086]

[0094] The imaging model in this case may include a set of convolutions 864 (or any physics-based model that can represent a model of the imaging system used to acquire the image 857) that are assumed to be known, since each convolution 864 may correspond to the settings of a particular signal acquisition modality. Alternatively, the set of convolutions 864 may be interpreted as unknowns that can be learned from available data. In such a case, the set of convolutions or other models 864 may be part of an optimization problem. Each of the convolutions 864 may have a point spread function B i , which may be a two-dimensional array (kernel) of values, followed by a pixel resolution reduction process 866 that reduces the pixel dimensions to n×n. In other words, the m*N reconstructed images 859 are generated by applying a different blur defined by the appropriate kernel B i When the image is convolved with m*N arrays 865 (which may also have size p×p) of convolved values, m*N arrays 865 of convolved values ​​are obtained, such that if the pixel dimensions of each of the arrays 865 were reduced to n×n (e.g., by being blurred, having a lower spatial resolution or SNR, etc.), they would produce m*N images 867 that resemble the corresponding images of the acquired images. Here, these m*N images 867 may be referred to as "corrupted images." Note that each of the corrupted images 867 may correspond to one of the acquired images 857, and may be images of the same region on the sample under inspection.

[0087]

[0095] In one simple form of pixel resolution reduction process 866, p may be a multiple of n (e.g., p=an, where a is an integer), so that each pixel of image 867 corresponds to a respective a×a patch of pixels in convolution array 865. Thus, to perform pixel resolution reduction process 866, the intensity value of each pixel of each corrupted image 867 may be obtained as the average of the intensities of the corresponding patch in convolution array 865.

[0088]

[0096] Reconstructed image 859 may be thought of as the intensity image that would be obtained if the sample region were imaged with a higher resolution, lower SNR imaging process than that which produced the corresponding image 857 .

[0089]

[0097] In principle, the set of many possible reconstructed images 859 will have the properties shown in FIG. 8 (e.g., the problem of forming reconstructed image 859 using acquired image 857 may be ill-posed). However, this application of method 700 assumes that some prior knowledge about reconstructed image 859 exists. First, reconstructed image 859 is known to be of limited complexity, with a relatively small number of top-to-bottom features visible on the patterned stack. Also, the expected device structure may have smooth local variations (e.g., patterned lines formed from a mass of material and not sharp features). Additionally, similarities may exist between reconstructed images 859 because their corresponding imaged regions may contain the same or similar structures. This prior knowledge may be used to define loss function terms as a function of reconstructed image 859 (and acquired image 857 and signal acquisition modality), such that minimizing the loss function with respect to reconstructed image 859 ensures that reconstructed image 859 conforms to this prior knowledge and is consistent with the measured data via the process illustrated in FIG. 8.

[0090]

[0098] Specifically, the loss function may be of the form:

number

number

[0091]

[0099]

number

number

[0092]

[0100] D is the matrix X k This shows the operation to convert ||·|| into a vector. * denotes the operation of the karyotype norm. The norm is calculated as the sum of the absolute singular values ​​of the concatenation of all vectorized images, e.g., [DX1,DX2,…,DX N ].

[0093]

[0101] α and β are hyperparameters that determine the relative importance of terms in the loss function.

[0094]

[0102] The minimization algorithm then becomes

number

[0095]

[0103] Specifically, the term

number

[0096]

[0104] regularization term

number

[0097]

[0105] term||[DX1,DX2,…,DXN ]|| * is image X k are images of respective areas containing similar structures (e.g., based on the same design data or design data meeting similarity criteria), so that image X k This requirement is encoded in equation (1) by ensuring that the concatenated reconstructed images produce a low-rank matrix. This property is realized by a convex relaxation of the low-rank property, i.e., the kernel norm ||[DX1,DX2,…,DX N ]|| * is encoded via

[0098]

[0106] The hyperparameters α and β may be selected by trial and error to produce a reconstructed image 859 with desired characteristics. For example, if a higher resolution image is available for a particular product, the hyperparameters α and β may be selected to ensure the best match with that image. Note that because setting the hyperparameters α and β only needs to be done once in a "setup" phase, it may be worth the cost of acquiring the higher resolution image, so that the resulting hyperparameter values ​​can then be used in the process of FIG. 8 to examine a larger number of other products.

[0099]

[0107] While the optimization problem described above can produce high-quality images, in some embodiments it may be desirable to reduce the time and computational load required to achieve such images. For example, in some embodiments, surrogate modeling, using, for example, a neural network, may be used to increase the efficiency of the modeling process. A faster neural network may be fed a set of selected image pairs 857 / 867 as training data generated from the slower optimization process described above. The training set may, for example, be sampled at predetermined values ​​across the parameter space of interest. Using the initial training set, the network may build a surrogate model 864. The surrogate model may then be analyzed to identify optima for generating additional training image pairs 857 / 867 via a slow optimization process based on the expected improvement of the training set. The additional image pairs 857 / 867 may then be used to strengthen the training set, and the process may be repeated.

[0100]

[0108] The surrogate modeling process can be used to build a significantly faster and computationally reduced set of models 864. Once trained, the surrogate models can be applied in the optimization process of FIG. 8 to more quickly generate enhanced synthetic images.

[0101]

[0109] Further details of the optimization task are discussed in European Patent Application No. EP22185297, which is incorporated by reference in its entirety.

[0102]

[0110] 9 is a flowchart illustrating a method 900 that may be useful for generating a composite image from multiple signal acquisition modalities consistent with embodiments of the present disclosure. Method 900 may be performed using, for example, electron beam tool 100 of FIG. 1, electron beam tool 100A of FIG. 2A, or electron beam tool 100B of FIG. 2B. For example, some method steps may be performed using a controller, such as, for example, controller 109 of FIG. 1 or image acquisition unit 199 of FIG. 2B. In some embodiments, method 900 may be performed in conjunction with, for example, any of measurement schemes 400-600 of FIGS. 4-6, respectively.

[0103]

[0111] In step 901, an inspection tool can measure a first region of a sample under a first signal acquisition modality. The first region of the sample can be, for example, the entire sample, a die region of the sample, the field of view of the inspection tool on the sample, a scan line on the sample, or a portion of a scan line. The first signal acquisition modality can be a set of inspection tool settings. The inspection tool settings can include, for example, beam current, landing energy, acceleration voltage, beam incidence angle, probe spot size, wafer orientation / beam scan angle, field size and shape, beam aperture settings, lens aberration values, focus, lens / deflector or other charged particle optical settings, or other charged particle inspection tool parameters. The first signal acquisition modality can be configured to produce a desired set of imaging parameters. For example, the first signal acquisition modality can be configured to produce a relatively large interaction volume, or can be configured to produce a signal profile with, for example, a higher acquisition speed, a higher SNR, or a lower resolution.

[0104]

[0112] In step 902, the inspection tool may measure a second region of the sample under a second signal acquisition modality that is different from the first signal acquisition modality in at least one inspection tool setting. For example, in some embodiments, the second signal acquisition modality may be configured to produce a relatively small interaction volume, or may be configured to produce a signal profile with, for example, a lower acquisition speed, a lower SNR, or a higher resolution.

[0105]

[0113] In some embodiments, the first and second regions may be the same. For example, the inspection tool may scan an entire line under each of the first and second signal acquisition modalities before proceeding to the next line, continuing until the entire field of view is exposed under both signal acquisition modalities. In such cases, individual lines, the entire field of view, etc. may be considered both the first and second regions. An example of the above-described embodiment may be seen in measurement acquisition scheme 400 of FIG. 4.

[0106]

[0114] In some embodiments, the first and second regions may be different. For example, the first and second regions may be adjacent, spaced apart, or slightly overlapping. For example, the first and second regions may correspond to different portions of one or more scan lines. The inspection tool may illuminate a single scan line while alternating between a first signal acquisition modality and a second signal acquisition modality in a multi-modality measurement sequence in a scanning direction (e.g., a fast scan direction FS as seen in FIGS. 4-6). In such a case, the portion of the line illuminated under the first signal acquisition modality may correspond to the first region, and the portion of the line illuminated under the second signal acquisition modality may correspond to the second region. Alternatively, the inspection tool may scan multiple lines while alternating between the first and second signal acquisition modalities in a non-scanning direction (e.g., a slow scan direction SS as seen in FIGS. 4-6). In some embodiments, the inspection tool may employ multiple multi-modality sequences on different scan lines within the field of view. Examples of the embodiments discussed above can be seen in the measurement acquisition schemes 500A-C of Figures 5A-5C.

[0107]

[0115] In some embodiments, the second region can be contained within the first region. For example, the inspection tool can illuminate substantially the entire line or field of view under a first signal acquisition modality to obtain a coarse measurement (e.g., a high-speed, low-resolution measurement) of the first region. Using information about the critical features (e.g., information derived from the initial scan or known information such as previous scans, GDS files, or other pattern design data), the inspection tool can illuminate areas where the critical features are expected to be found.

[0108]

[0116] The measurements performed in steps 901 and 902 may result in a signal profile corresponding to an image of the measured area.

[0109]

[0117] In step 903, the signal profiles obtained in steps 901 and 902 may be combined to form an enhanced, high-quality image of a portion of the sample. For example, the combination may include performing an optimization task to find a solution for combining the signal profiles. In some embodiments, the combination may be described as a deconvolution task. Examples of optimization tasks may include those described above with respect to FIGS. 7 and 8. In some embodiments, deep learning or machine learning techniques may be used to combine the images.

[0110]

[0118] In step 904, the composite image may be used to perform an inspection process. For example, the composite image may be analyzed for defect detection, metrology operations, or other sample inspection processes.

[0111]

[0119] For example, a non-transitory computer-readable medium may be provided that stores instructions for a processor of a controller (e.g., controller 109 of FIG. 1 or image acquisition unit 199 of FIG. 2B) to detect charged particles according to measurement acquisition schemes 400-600 of FIGS. 4-6, exemplary flowchart 700 of FIG. 7, or exemplary flowchart 900 of FIG. 9 consistent with embodiments of the present disclosure. For example, the instructions stored on the non-transitory computer-readable medium may be executed by circuitry of the controller to partially or entirely implement measurement acquisition schemes 400-600 or methods 700 or 900. Common forms of non-transitory media include, for example, floppy disks, flexible disks, hard disks, solid state drives, magnetic tape or any other magnetic data storage medium, compact disk read-only memory (CD-ROM), any other optical data storage medium, any physical medium with a pattern of holes, random access memory (RAM), programmable read-only memory (PROM) and erasable programmable read-only memory (EPROM), flash EPROM or any other flash memory, non-volatile random access memory (NVRAM), cache, registers, any other memory chip or cartridge, and network-connected versions thereof.

[0112]

[0120] Embodiments of the present disclosure may be further described by the following clauses. 1. A non-transitory computer-readable medium storing a set of instructions executable by at least one processor of a device, the set of instructions causing the device to perform a method, the method comprising: measuring a first region of the sample with a charged particle beam inspection device under a first signal acquisition modality, thereby acquiring a first signal profile; measuring a second region of the sample using the charged particle beam inspection device under a second signal acquisition modality, thereby obtaining a second signal profile, the second signal acquisition modality being different from the first signal acquisition modality in measuring an inspection parameter of the charged particle beam device; generating an inspection image based on a combination of the first signal profile and the second signal profile using an optimization task; 1. A non-transitory computer-readable medium comprising: 2. The non-transitory computer-readable medium of clause 1, wherein the first region and the second region are the same region. 3. The non-transitory computer-readable medium of clause 1, wherein the first region is different from the second region. 4. The non-transitory computer-readable medium of clause 3, wherein the first region and the second region do not overlap. 5. The non-transitory computer-readable medium of clause 1, wherein the first region includes a field of view of a charged particle beam inspection device. 6. The first region includes a first scan line within a field of view of the charged particle beam inspection device; the second region includes a second scan line within a field of view of the charged particle beam inspection device, the second scan line being different from the first scan line; 1. The non-transitory computer-readable medium described in clause 1. 7. The first region includes a first portion of a first scan line within a field of view of the charged particle beam inspection device; the second region includes a second portion of the first scan line within a field of view of the charged particle beam inspection device, the second portion being different from the first portion; 1. The non-transitory computer-readable medium described in clause 1. 8. The non-transitory computer-readable medium of clause 7, wherein the first region and the second region of the first scan line correspond to a first multi-modality measurement sequence. 9. A set of instructions executable by at least one processor includes instructions for: measuring a third region of the sample under a first signal acquisition modality with a charged particle beam inspection device, thereby acquiring a third signal profile; measuring a fourth region of the sample under a second signal acquisition modality with the charged particle beam inspection device, thereby acquiring a fourth signal profile; Then run 9. The non-transitory computer-readable medium of clause 8, wherein generating the inspection image is further based on combining the third signal profile and the fourth signal profile. 10. The third region includes a third portion of the second scan line within a field of view of the charged particle beam inspection device, the second scan line being different from the first scan line; the fourth region includes a fourth portion of the second scan line within a field of view of the charged particle beam inspection device, the fourth portion being different from the third portion; 9. A non-transitory computer-readable medium as described in Clause 9. 11. The non-transitory computer-readable medium of clause 10, wherein the third and fourth regions of the second scan line correspond to a second multi-modality measurement sequence that is different from the first multi-modality measurement sequence. 12. The non-transitory computer-readable medium of clause 8, wherein the multi-modality measurement sequence does not correspond to a sequence of pattern features on the first region or the second region. 13. The non-transitory computer-readable medium of clause 8, wherein the multi-modality measurement sequence corresponds to a sequence of pattern features on the first region or the second region. 14. The non-transitory computer-readable medium of clause 13, wherein the multi-modality measurement sequence is based on prior knowledge of pattern features on the first region or the second region. 15. At least one processor in the device: The non-transitory computer-readable medium of clause 13, further comprising, during measurement of the first region or the second region, updating the multi-modality measurement sequence based on information obtained from the first region or the second region. 16. The non-transitory computer-readable medium of clause 1, wherein the second region corresponds to a sample feature in the first region. 17. The non-transitory computer-readable medium of clause 16, wherein the sample features include expected locations of pattern edge features. 18. The non-transitory computer-readable medium of clause 1, wherein the first signal acquisition modality is configured to generate a larger interaction volume in the sample than the second signal acquisition modality. 19. The non-transitory computer-readable medium of clause 1, wherein the first signal acquisition modality is configured to achieve one of a higher signal acquisition rate, a higher signal-to-noise ratio, or a lower resolution than the second signal acquisition modality. 20. The non-transitory computer-readable medium of clause 1, wherein the inspection parameters of the charged particle beam device include one of beam current, landing energy, acceleration voltage, beam incidence angle, probe spot size, wafer orientation, beam scan angle, field size, field shape, beam aperture setting, lens aberration value, focus value, and charged particle optics setting. 21. The non-transitory computer-readable medium of clause 1, wherein the optimization task includes a loss function. 22. The non-transitory computer-readable medium of clause 1, wherein the optimization task comprises an inverse problem. 23. The non-transitory computer-readable medium of clause 22, wherein the optimization task comprises a deconvolution task. 24. A charged particle beam inspection method comprising: measuring a first region of the sample with a charged particle beam inspection device under a first signal acquisition modality, thereby acquiring a first signal profile; measuring a second region of the sample using the charged particle beam inspection device under a second signal acquisition modality, thereby obtaining a second signal profile, the second signal acquisition modality being different from the first signal acquisition modality in measuring an inspection parameter of the charged particle beam device; generating an inspection image based on a combination of the first signal profile and the second signal profile using an optimization task; A method comprising: 25. The method of clause 24, wherein the first region and the second region are the same region. 26. The method of clause 24, wherein the first region is different from the second region. 27. The method of clause 26, wherein the first region and the second region do not overlap. 28. The method of clause 24, wherein the first region comprises a field of view of a charged particle beam inspection device. 29. the first region includes a first scan line within a field of view of the charged particle beam inspection device; 25. The method of claim 24, wherein the second region includes a second scan line within a field of view of the charged particle beam inspection device, the second scan line being different from the first scan line. 30. the first region includes a first portion of a first scan line within a field of view of the charged particle beam inspection device; 25. The method of clause 24, wherein the second region includes a second portion of the first scan line within a field of view of the charged particle beam inspection device, the second portion being different from the first portion. 31. The method of clause 30, wherein the first region and the second region of the first scan line correspond to a first multi-modality measurement sequence. 32. measuring a third region of the sample under a first signal acquisition modality with a charged particle beam inspection device, thereby acquiring a third signal profile; measuring a fourth region of the sample under a second signal acquisition modality with the charged particle beam inspection device, thereby acquiring a fourth signal profile; Further comprising: 32. The method of claim 31, wherein generating the inspection image is further based on combining the third signal profile and the fourth signal profile. 33. the third region includes a third portion of a second scan line within a field of view of the charged particle beam inspection device, the second scan line being different from the first scan line; 33. The method of claim 32, wherein the fourth region includes a fourth portion of the second scan line within a field of view of the charged particle beam inspection device, the fourth portion being different from the third portion. 34. The method of clause 33, wherein the third and fourth regions of the second scan line correspond to a second multi-modality measurement sequence that is different from the first multi-modality measurement sequence. 35. The method of clause 31, wherein the multi-modality measurement sequence does not correspond to a sequence of pattern features on the first region or the second region. 36. The method of clause 31, wherein the multi-modality measurement sequence corresponds to a sequence of pattern features on the first region or the second region. 37. The method of clause 36, wherein the multi-modality measurement sequence is based on prior knowledge of pattern features on the first region or the second region. 38. 37. The method of clause 36, further comprising, during measurement of the first region or the second region, updating the multi-modality measurement sequence based on information obtained from the first region or the second region. 39. The method of clause 24, wherein the second region corresponds to a sample feature within the first region. 40. The method of clause 39, wherein the sample features include expected locations of pattern edge features. 41. The method of clause 24, wherein the first signal acquisition modality is configured to generate a larger interaction volume at the sample than the second signal acquisition modality. 42. The method of clause 24, wherein the first signal acquisition modality is configured to achieve one of a higher signal acquisition rate, a higher signal-to-noise ratio, or a lower resolution than the second signal acquisition modality. 43. The method of clause 24, wherein the inspection parameters of the charged particle beam device include one of beam current, landing energy, acceleration voltage, beam incidence angle, probe spot size, wafer orientation, beam scan angle, field size, field shape, beam aperture setting, lens aberration value, focus value, and charged particle optics setting. 44. The method of clause 24, wherein the optimization task includes a loss function. 45. The method of clause 24, wherein the optimization task comprises an inverse problem. 46. ​​The method of clause 45, wherein the optimization task comprises a deconvolution task. 47. A charged particle beam device comprising: a charged particle beam source configured to generate a beam of primary charged particles; charged particle optics configured to direct a beam of primary charged particles onto a sample surface for inspecting the sample surface; a charged particle detector configured to detect charged particles returned from the sample surface; a controller including one or more processors, the controller including: measuring a first region of the sample with a charged particle beam inspection device under a first signal acquisition modality, thereby acquiring a first signal profile; measuring a second region of the sample using the charged particle beam inspection device under a second signal acquisition modality, thereby obtaining a second signal profile, the second signal acquisition modality being different from the first signal acquisition modality in measuring an inspection parameter of the charged particle beam device; and generating an inspection image based on a combination of the first signal profile and the second signal profile using an optimization task; a controller configured to execute 1. A charged particle beam device comprising: 48. A charged particle beam device according to clause 47, wherein the first region and the second region are the same region. 49. A charged particle beam device according to clause 47, wherein the first region is different from the second region. 50. A charged particle beam device according to clause 49, wherein the first region and the second region do not overlap. 51. A charged particle beam device according to clause 47, wherein the first region comprises a field of view of the charged particle beam inspection device. 52. the first region includes a first scan line within a field of view of the charged particle beam inspection device; 48. The charged particle beam device of clause 47, wherein the second region includes a second scan line within a field of view of the charged particle beam inspection device, the second scan line being different from the first scan line. 53. Charged particle beam device as defined in clause 47. the first region includes a first portion of a first scan line within a field of view of the charged particle beam inspection device; 48. The charged particle beam device of clause 47, wherein the second region includes a second portion of the first scan line within a field of view of the charged particle beam inspection device, the second portion being different from the first portion. 54. A charged particle beam device according to clause 53, wherein the first region and the second region of the first scan line correspond to a first multi-modality measurement sequence. 55. The controller controls the charged particle beam device to: measuring a third region of the sample under a first signal acquisition modality with a charged particle beam inspection device, thereby acquiring a third signal profile; measuring a fourth region of the sample under a second signal acquisition modality with the charged particle beam inspection device, thereby acquiring a fourth signal profile; and further configured to execute 55. The charged particle beam device of clause 54, wherein generating the inspection image is further based on combining the third signal profile and the fourth signal profile. 56. The third region includes a third portion of the second scan line within the field of view of the charged particle beam inspection device, the second scan line being different from the first scan line. 56. The charged particle beam device of clause 55, wherein the fourth region includes a fourth portion of the second scan line within a field of view of the charged particle beam inspection device, the fourth portion being different from the third portion. 57. A charged particle beam device as described in clause 56, wherein the third and fourth regions of the second scan line correspond to a second multi-modality measurement sequence that is different from the first multi-modality measurement sequence. 58. A charged particle beam device according to clause 54, wherein the multi-modality measurement sequence does not correspond to a sequence of pattern features on the first region or the second region. 59. A charged particle beam device according to clause 54, wherein the multi-modality measurement sequence corresponds to a sequence of pattern features on the first region or the second region. 60. A charged particle beam device according to clause 59, wherein the multi-modality measurement sequence is based on prior knowledge of pattern features on the first region or the second region. 61. The controller controls the charged particle beam device to: A charged particle beam device as described in clause 59, configured to further perform, during measurement of the first region or the second region, updating the multi-modality measurement sequence based on information obtained from the first region or the second region. 62. A charged particle beam device according to clause 47, wherein the second region corresponds to a sample feature within the first region. 63. A charged particle beam device according to clause 62, wherein the sample features include expected locations of pattern edge features. 64. A charged particle beam device according to clause 47, wherein the first signal acquisition modality is configured to generate a larger interaction volume in the sample than the second signal acquisition modality. 65. A charged particle beam device as described in clause 47, wherein the first signal acquisition modality is configured to achieve one of a higher signal acquisition speed, a higher signal-to-noise ratio, or a lower resolution than the second signal acquisition modality. 66. A charged particle beam device as described in Clause 47, wherein the inspection parameters of the charged particle beam device include one of beam current, landing energy, acceleration voltage, beam incidence angle, probe spot size, wafer orientation, beam scan angle, field size, field shape, beam aperture setting, lens aberration value, focus value, and charged particle optics setting. 67. A charged particle beam device as described in clause 47, wherein the optimization task includes a loss function. 68. A charged particle beam device as described in clause 47, wherein the optimization task comprises an inverse problem. 69. A charged particle beam device as described in clause 68, wherein the optimization task includes a deconvolution task.

[0113]

[0121] The block diagrams in the figures may illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer hardware or software products according to various exemplary embodiments of the present disclosure. In this regard, each block in the schematic diagrams may represent a specific arithmetic or logical operation that may be implemented using hardware, such as electronic circuits. The blocks may also represent modules, segments, or portions of code that include one or more executable instructions for performing the specified logical function(s). It should be understood that in some alternative implementations, the functions shown in the blocks may occur in a different order than that depicted in the figures. For example, depending on the functionality involved, two blocks shown in succession may be executed or performed substantially simultaneously, or the two blocks may sometimes be executed in the reverse order. Some blocks may also be omitted. It should also be understood that each block of the block diagrams, and combinations of blocks, may be implemented by a dedicated hardware-based system that performs the specified functions or operations, or by a combination of dedicated hardware and computer instructions.

[0114]

[0122] It will be understood that embodiments of the present disclosure are not limited to the exact configurations described above and illustrated in the accompanying drawings, and that various modifications and changes can be made without departing from the scope thereof. For example, a charged particle inspection system may be just one example of a charged particle beam system consistent with embodiments of the present disclosure.

Claims

1. 1. A non-transitory computer-readable medium storing a set of instructions executable by at least one processor of a device, the set of instructions causing the device to perform a method, the method comprising: measuring a first region of the sample with a charged particle beam inspection device under a first signal acquisition modality, thereby acquiring a first signal profile; measuring a second region of the sample using the charged particle beam inspection device under a second signal acquisition modality, thereby obtaining a second signal profile, the second signal acquisition modality being different from the first signal acquisition modality in measuring inspection parameters of the charged particle beam device; generating an inspection image based on a combination of the first signal profile and the second signal profile using an optimization task; 1. A non-transitory computer-readable medium comprising:

2. The non-transitory computer-readable medium of claim 1 , wherein the first region and the second region are the same region.

3. The non-transitory computer-readable medium of claim 1 , wherein the first region is different from the second region.

4. The non-transitory computer-readable medium of claim 3 , wherein the first region and the second region do not overlap.

5. The non-transitory computer-readable medium of claim 1 , wherein the first region comprises a field of view of the charged particle beam inspection device.

6. the first region includes a first scan line within a field of view of the charged particle beam inspection device; 2. The non-transitory computer-readable medium of claim 1, wherein the second region includes a second scan line in the field of view of the charged particle beam inspection device, the second scan line being different from the first scan line.

7. the first region includes a first portion of a first scan line within a field of view of the charged particle beam inspection device; 2. The non-transitory computer-readable medium of claim 1, wherein the second region includes a second portion of the first scan line within the field of view of the charged particle beam inspection device, the second portion being different from the first portion.

8. The non-transitory computer-readable medium of claim 7 , wherein the first region and the second region of the first scan line correspond to a first multi-modality measurement sequence.

9. The set of instructions executable by the at least one processor may include instructions for the device: measuring a third region of the sample under the first signal acquisition modality using the charged particle beam inspection device, thereby acquiring a third signal profile; measuring a fourth region of the sample under the second signal acquisition modality using the charged particle beam inspection device, thereby acquiring a fourth signal profile; Then run The non-transitory computer-readable medium of claim 8 , wherein generating the inspection image is further based on combining the third signal profile and the fourth signal profile.

10. the third region includes a third portion of a second scan line within a field of view of the charged particle beam inspection device, the second scan line being different from the first scan line; 10. The non-transitory computer-readable medium of claim 9, wherein the fourth region includes a fourth portion of the second scan line within the field of view of the charged particle beam inspection device, the fourth portion being different from the third portion.

11. 11. The non-transitory computer-readable medium of claim 10, wherein the third region and the fourth region of the second scan line correspond to a second multi-modality measurement sequence that is different from the first multi-modality measurement sequence.

12. The non-transitory computer-readable medium of claim 8 , wherein the multi-modality measurement sequence does not correspond to a sequence of pattern features on the first region or the second region.

13. The non-transitory computer-readable medium of claim 8 , wherein the multi-modality measurement sequence corresponds to a sequence of pattern features on the first region or the second region.

14. The non-transitory computer-readable medium of claim 13 , wherein the multi-modality measurement sequence is based on prior knowledge of the pattern features on the first region or the second region.

15. The at least one processor may cause the device to:

14. The non-transitory computer-readable medium of claim 13, further comprising: updating the multi-modality measurement sequence based on information obtained from the first region or the second region during the measurement of the first region or the second region.

Images