Method and system for overlay measurement using a charged particle inspection device

Abstract

The present application discloses a system including a charged particle beam inspection device configured to scan a sample including a target having multiple pattern layers, and a controller including circuitry, wherein the controller is configured to obtain detection data in response to the scanning of the target, and to determine one or more characteristics of the sample according to the obtained detection data and a model, wherein for each of the multiple pattern layers of the target, the model includes terms that depend on properties of the pattern layer.

Description

[Technical Field]

[0001]

[0001] This specification relates to the field of imaging inspection devices, and more particularly to measuring properties of a sample with a charged particle inspection device. The measured properties of the sample may include overlay. [Background technology]

[0002]

[0002] Imaging inspection devices (e.g., charged particle beam devices or optical beam devices) can generate two-dimensional (2D) images of wafer substrates by detecting particles (e.g., photons, secondary electrons, backscattered electrons, mirror electrons, or other types of electrons) from the surface of the wafer substrate upon impact with a beam (e.g., charged particle beam or optical beam) generated by a radiation source associated with the inspection device. In the semiconductor industry, various imaging inspection devices are used on semiconductor wafers for various purposes, such as wafer processing (e.g., e-beam direct write lithography systems), process monitoring (e.g., critical dimension scanning electron microscopes (CD-SEMs)), wafer inspection (e.g., e-beam inspection systems), or defect analysis (e.g., defect review SEMs, or e.g., DR-SEMs and focused ion beam systems, or e.g., FIBs).

[0003] In semiconductor manufacturing, integrated circuits can be fabricated on a wafer as one or more stacked layers of material (e.g., silicon, silicon dioxide, metal, or the like). Each layer of material can contain a designed pattern (referred to herein as a "pattern layer") for forming components of the integrated circuit (e.g., transistors, contacts, or the like). The fabrication of each layer involves transferring the pattern from a mask to the wafer surface through a lithography process. The relative position of each pattern layer with the previous pattern layer (referred to herein as "alignment") can affect the characteristics or quality of the manufactured integrated circuit.

[0004]

[0004] Overlay refers to the shift, displacement, or misalignment of a vector on a plane of a pattern layer relative to its neighboring pattern layer. For example, two pattern reference points (e.g., center points) can be selected for two patterns on two neighboring pattern layers, respectively, and the overlay between the two neighboring pattern layers can refer to the displacement of a vector on a plane between the two pattern reference points. If the overlay is large, it may cause problems or failures in the manufactured integrated circuit. Therefore, high-precision overlay measurement plays an important role in reducing the overlay. Summary of the Invention

[0005] Some embodiments of the present disclosure provide systems and methods for measuring properties of a sample under scanning performed by a charged particle beam inspection device. In some embodiments, a system is provided that includes a charged particle beam inspection device configured to scan a sample including a target having multiple pattern layers, and a controller including circuitry, wherein the controller is configured to obtain detection data in response to scanning the target and determine one or more properties of the sample according to the obtained detection data and a model, where for each of the multiple pattern layers of the target, the model includes a term that depends on a property of the pattern layer. In some embodiments, a non-transitory computer-readable medium is provided that stores a set of instructions executable by at least one processor of the device and causes the device to perform a method, the method including obtaining detection data in response to scanning the target with the charged particle beam inspection device and determining one or more properties of the sample according to the obtained detection data and a model, where the target includes multiple pattern layers, and where for each of the multiple pattern layers, the model includes a term that depends on a property of the pattern layer. In some embodiments, a computer-implemented method is provided for measuring properties of a sample under scanning performed by a charged particle beam inspection device, the method comprising: obtaining detection data in response to scanning of a target by the charged particle beam inspection device; and determining one or more properties of the sample according to the obtained detection data and a model, wherein the target comprises a plurality of pattern layers, and for each of the plurality of pattern layers, the model comprises terms that depend on properties of the pattern layer. [Brief explanation of the drawings]

[0006] [Figure 1] FIG. 1 is a schematic diagram illustrating an exemplary charged particle beam inspection (CPBI) system consistent with some embodiments of the present disclosure. [Figure 2]

[0007] 2 is a schematic diagram illustrating an example charged particle beam tool consistent with some embodiments of the present disclosure that may be part of the example charged particle beam inspection system of FIG. 1. [Figure 3]

[0008] FIG. 1 is a schematic diagram illustrating an exemplary target fabricated on a sample, consistent with certain embodiments of the present disclosure. [Figure 4A]

[0009] FIG. 1 illustrates a modeled signal and its components according to some embodiments, consistent with some embodiments of the present disclosure. [Figure 4B]

[0010] FIG. 2 illustrates a residual or error signal representing the difference between a measured signal and a modeled signal, according to some embodiments. [Figure 5]

[0011] FIG. 1 illustrates a modeled signal according to some embodiments when fitted to measured data. [Figure 6]

[0012] 1 is a flowchart illustrating an exemplary method of characteristic measurement, consistent with certain embodiments of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0007]

[0013] Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. The following description refers to the accompanying drawings, in which like numbers in different drawings represent the same or similar elements unless otherwise specified. The implementations described in the following description of example embodiments do not represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with aspects related to the subject matter recited in the appended claims. Without limiting the scope of the present disclosure, some embodiments may be described in the context of providing detection systems and methods in systems utilizing electron beams ("e-beams"). However, the present disclosure is not limited thereto. Other types of charged particle beams (e.g., including protons, ions, muons, or any other particles carrying an electric charge) may be similarly irradiated. Furthermore, the systems and methods for detection may be used in other imaging systems, such as optical imaging, light detection, x-ray detection, ion detection, etc.

[0008]

[0014] Electronic devices are composed of circuits formed on a piece of semiconductor material called a substrate. The semiconductor material can include, for example, silicon, gallium arsenide, indium phosphide, or silicon germanium. Many circuits can be formed together on the same piece of silicon and are called integrated circuits, or ICs. The dimensions of these circuits have been dramatically reduced so that many more circuits can fit on a substrate. For example, the IC chip in a smartphone can be as small as a thumbnail, yet contain over 2 billion transistors, each smaller than 1 / 1000 the size of a human hair.

[0009]

[0015] Fabricating ICs with these extremely small structures or components is a complex, time-consuming, and expensive process, often involving hundreds of individual steps. An error in just one step can result in a defect 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 in the process, i.e., to improve the overall yield of the process.

[0010]

[0016] One component of improving yield is monitoring the chip fabrication 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 in their formation. Inspection can be done using a scanning charged particle microscope ("SCPM"). For example, a scanning charged particle microscope can be a scanning electron microscope (SEM). A scanning charged particle microscope can actually take a "picture" of the structures on the wafer and can be used to image those tiny structures. This image can be used to determine if the structures were properly formed in the correct location. If the structures are defective, the process can be adjusted to make the defect less likely to recur.

[0011]

[0017] The operating principle of a scanning charged particle microscope (e.g., 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. A scanning charged particle microscope takes "pictures" by receiving and recording the energy or quantity of charged particles (e.g., electrons) reflected or emitted from structures on a wafer. Typically, the structures are fabricated on a substrate (e.g., a silicon substrate) that is placed on a platform called a stage for imaging. Before taking such a "picture," a charged particle beam can be projected onto the structure, and as charged particles 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 scanning charged particle microscope can receive and record the energy or quantity of those charged particles to generate an inspection image. To take such a "picture," the charged particle beam can scan the wafer (e.g., line-by-line or in a zigzag fashion), and a detector can receive the emitted charged particles from the area under the projection of the charged particle beam (called a "beam spot"). The detector can receive and record the emitted charged particles from each beam spot one by one, and combine the recorded information for all beam spots to generate an inspection image. Some scanning charged particle microscopes use a single charged particle beam to capture a single "image" to generate the inspection image (called "single-beam scanning charged particle microscopes," such as single-beam SEMs), while other scanning charged particle microscopes use multiple charged particle beams to capture multiple "subpictures" of the wafer in parallel and stitch them together to generate the inspection image (called "multibeam scanning charged particle microscopes," such as multi-beam SEMs). By using multiple charged particle beams, the SEM can expose more charged particle beams to the structure to obtain these multiple "subpictures," resulting in more emitted charged particles from the structure. Thus, the detector can simultaneously receive more exiting charged particles and produce inspection images of the wafer's structures with greater efficiency and speed.

[0012]

[0018] Various overlay measurement techniques can be used to control the quality of fabricated semiconductor structures. Typically, overlay can be measured using optical tools. For example, a broadband light beam can be directed onto the surface of a sample. The surface can include a specially designed and fabricated structure (also referred to herein as a "target"). The target can include a first layer (e.g., a top layer) and a second layer (e.g., a bottom layer) below the first patterned layer. Optical scatterometry tools can be used to measure the reflection or diffraction of the broadband light reflected by the target. The reflection or diffraction can have various properties, such as different wavelengths, polarizations, angles of incidence, phases, or other optical properties, from which unknown properties of the sample (e.g., overlay) can be determined.

[0013]

[0019] As an example, the overlay of a target can be determined based on the phase difference between the diffraction of a first layer (e.g., the top layer) and a second layer (e.g., the layer directly below the first layer), where each of the first and second layers includes a specific structure (e.g., a diffraction grating). Overlay determined using such a target is sometimes referred to as diffraction-based overlay (DBO). To measure diffraction-based overlay, the structures (e.g., diffraction gratings) of the first and second players can be fabricated with a programmed shift. A programmed shift between two layers herein may refer to the displacement of a vector on a designed (known) plane between the two layers. The programmed shift can be used to eliminate or reduce imperfections in optical scatterometry measurements.

[0014]

[0020] Optical-based overlay measurement techniques present several technical challenges. The first challenge is that the reflection or diffraction signal weakens as the target pitch (e.g., the pitch of a diffraction grating) decreases and as the separation between neighboring pattern layers increases. In this disclosure, "pitch" refers to the minimum center-to-center distance between interconnect lines in a fabricated integrated circuit and can be used as an indicator of the integration density of the integrated circuit. The second challenge is that selecting the wavelength of a broadband light beam for optical-based overlay measurement techniques can be complicated because different wavelengths can produce different measurement results. The third challenge is that the measurement results of optical-based overlay measurement techniques can be sensitive to subtle tilts in the area between target lines (e.g., diffraction grating lines). These challenges can increase uncertainty and inaccuracy in overlay measurements.

[0015]

[0021] Embodiments of the present disclosure may provide methods, apparatus, and systems for non-optical overlay measurement. In some disclosed embodiments, a scanning charged particle microscope (e.g., SEM) may be used for overlay measurement using one or more targets. The scanning charged particle microscope may inject a charged particle beam (e.g., an electron beam) into the surface of one or more targets, each of which includes a first layer (e.g., a top layer) and a second layer (e.g., below the first layer). Each of the first and second layers may include a similar pattern (e.g., a diffraction grating). The incident charged particle beam may interact with the pattern of the first layer and the pattern of the second layer to generate secondary electrons and backscattered electrons. The exiting secondary electrons and backscattered electrons are detected by a detector, and a signal is generated. Analysis of the signal may determine the overlay between the first layer and the second layer. Compared to optical-based overlay measurement techniques, non-optical overlay measurement may reduce or eliminate the above-mentioned challenges and significantly improve the accuracy of overlay measurement.

[0016]

[0022] The relative dimensions of components in the drawings may be exaggerated for clarity. In the following description of the drawings, the same or similar reference numerals refer to the same or similar components or entities, and only the differences with respect to the individual embodiments are described.

[0017]

[0023] As used herein, unless otherwise stated, the term "or" includes all possible combinations unless impractical. For example, if a component is described as being able to include A or B, the component can include A, or B, or A and B, unless otherwise stated or impractical. As a second example, if a component is described as being able to include A, B, or C, the component can include A, or B, or C, or A and B, or A and C, or B and C, or A, B, and C, unless otherwise stated or impractical.

[0018]

[0024] FIG. 1 illustrates an exemplary charged particle beam inspection (CPBI) system 100 consistent with some embodiments of the present disclosure. The CPBI system 100 can be used for imaging. For example, the CPBI system 100 can use an electron beam for imaging. As shown in FIG. 1 , the CPBI system 100 includes a main chamber 101, a load / lock chamber 102, a beam tool 104, and a front-end equipment module (EFEM) 106. The beam tool 104 is disposed inside the main chamber 101. The EFEM 106 includes a first load port 106a and a second load port 106b. The EFEM 106 may include additional load ports. The first load port 106a and the second load port 106b receive wafer FOUPs (front opening unified pods) containing wafers (e.g., semiconductor wafers or wafers made of other materials) or samples (wafer and sample may be used interchangeably) to be inspected. A "lot" is a number of wafers that can be loaded for processing as a batch.

[0019]

[0025] One or more robot arms (not shown) in the EFEM 106 can transfer wafers to the load / lock chamber 102. The load / lock chamber 102 is connected to a load / lock vacuum pumping system (not shown), which removes gas molecules from the load / lock chamber 102 to reach a first pressure lower than atmospheric pressure. After the first pressure is reached, one or more robot arms (not shown) can transfer the wafers from the load / lock chamber 102 to the main chamber 101. The main chamber 101 is connected to a main chamber vacuum pumping system (not shown), which removes gas molecules from the main chamber 101 to reach a second pressure lower than the first pressure. After the second pressure is reached, the wafers are subjected to inspection by the beam tool 104. The beam tool 104 can be a single beam system or a multi-beam system.

[0020]

[0026] A controller 109 is electronically connected to the beam tool 104. The controller 109 may be a computer that may perform various controls of the CPBI system 100. While the controller 109 is illustrated in Figure 1 as being external to the structure including the main chamber 101, the load / lock chamber 102, and the EFEM 106, it will be understood that the controller 109 may be part of the structure.

[0021]

[0027] In some embodiments, the controller 109 can include one or more processors (not shown). A processor can be a general-purpose or specific electronic device capable of manipulating or processing information. For example, a processor can include any number and combination of central processing units (i.e., "CPUs"), graphics processing units (i.e., "GPUs"), optical processors, programmable logic controllers, microcontrollers, microprocessors, digital signal processors, intellectual property (IP) cores, programmable logic arrays (PLAs), programmable array logic (PALs), general array logic (GALs), complex programmable logic devices (CPLDs), field programmable gate arrays (FPGAs), systems-on-chips (SoCs), application-specific integrated circuits (ASICs), and any type of circuitry capable of processing data. A processor can also be a virtual processor, including one or more processors distributed across multiple machines or devices coupled via a network.

[0022]

[0028] In some embodiments, the controller 109 may further include one or more memories (not shown). Memory may be a general-purpose or specialized electronic device capable of storing code and data accessible to a processor (e.g., via a bus). For example, memory may include any combination of any number of random access memories (RAMs), read-only memories (ROMs), 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 (i.e., "apps") for specific tasks. Memory may also be virtual memory, including one or more memories distributed across multiple machines or devices coupled via a network.

[0023]

[0029] FIG. 2 illustrates an exemplary imaging system 200 consistent with embodiments of the present disclosure. The beam tool 104 of FIG. 2 can be configured for use in the CPBI system 100. The beam tool 104 can be a single-beam or multi-beam device. As shown in FIG. 2, the beam tool 104 includes a motorized sample stage 201 and a wafer holder 202 supported by the motorized sample stage 201 for holding a wafer 203 to be inspected. The beam tool 104 further includes an objective lens assembly 204, a charged particle detector 206 (including charged particle sensor surfaces 206 a and 206 b), an objective aperture 208, a condenser lens 210, a beam-limiting aperture 212, a gun aperture 214, an anode 216, and a cathode 218. In some embodiments, the objective lens assembly 204 may include a modified swing objective retarding immersion lens (SORIL) including a pole piece 204 a, a control electrode 204 b, a deflector 204 c, and an excitation coil 204 d. The beam tool 104 may further include an energy dispersive X-ray spectrometer (EDS) detector (not shown) for characterizing materials on the wafer 203.

[0024]

[0030] A primary charged particle beam 220 (or simply "primary beam 220"), such as an electron beam, is emitted from the cathode 218 by applying an accelerating voltage between the anode 216 and the cathode 218. The primary beam 220 passes through a gun aperture 214 and a beam-limiting aperture 212, both of which can determine the size of the charged particle beam entering the condenser lens 210 below the beam-limiting aperture 212. The condenser lens 210 focuses the primary beam 220 before it enters the objective aperture 208 to set the size of the charged particle beam before entering the objective lens assembly 204. A deflector 204c deflects the primary beam 220 to facilitate beam scanning over the wafer. For example, in a scanning process, the deflector 204c can be controlled to sequentially deflect the primary beam 220 to different positions on the top surface of the wafer 203 at different times to provide data for reconstructing images of different portions of the wafer 203. The deflector 204c may also be controlled to deflect the primary beam 220 onto different sides of the wafer 203 at specific locations at different times to provide data for reconstructing a three-dimensional image of the wafer structure at that location. Furthermore, in some embodiments, the anode 216 and cathode 218 may generate multiple primary beams 220, and the beam tool 104 may include multiple deflectors 204c for simultaneously projecting the multiple primary beams 220 onto different portions / sides of the wafer 203 to provide data for reconstructing an image of the different portions of the wafer 203.

[0025]

[0031] The excitation coil 204d and pole piece 204a generate a magnetic field that begins at one end of the pole piece 204a and ends at the other end of the pole piece 204a. A portion of the wafer 203 being scanned by the primary beam 220 can enter the magnetic field and become electrically charged, thus generating an electric field. The electric field reduces the energy of the impinging primary beam 220 near the surface of the wafer 203 before the primary beam 220 collides with the wafer 203. A control electrode 204b, electrically isolated from the pole piece 204a, controls the electric field on the wafer 203 to prevent micro-arching of the wafer 203 and to ensure proper beam focus.

[0026]

[0032] After receiving the primary beam 220, a secondary charged particle beam 222 (or "secondary beam 222"), such as a secondary electron beam, may be emitted from a portion of the wafer 203. The secondary beam 222 may form a beam spot on the sensor surfaces 206a and 206b of the charged particle detector 206. The charged particle detector 206 may generate a signal (e.g., voltage, current, etc.) representing the intensity of the beam spot and provide the signal to the image processing system 250. The intensity of the secondary beam 222 and the resulting beam spot may vary depending on the external or internal structure of the wafer 203. Furthermore, as discussed above, the primary beam 220 may be projected onto different locations on the top surface of the wafer or onto different sides of the wafer at a particular location to generate secondary beams 222 (and resulting beam spots) of different intensities. Thus, by mapping the position of the wafer 203 and the intensity of the beam spot, the processing system can reconstruct an image reflecting the internal or surface structure of the wafer 203.

[0027]

[0033] The imaging system 200 can be used to inspect a wafer 203 on a motorized sample stage 201 and includes the beam tool 104 as discussed above. The imaging system 200 can also include an image processing system 250, which includes an image acquirer 260, storage 270, and a controller 109. The image acquirer 260 can include one or more processors. For example, the image acquirer 260 can include a computer, a server, a mainframe host, a terminal, a personal computer, any type of mobile computing device, or the like, or a combination thereof. The image acquirer 260 can be connected to a detector 206 of the beam tool 104 via a medium such as electrical conductors, a fiber optic cable, a portable storage medium, IR, Bluetooth, the Internet, a wireless network, wireless radio, or a combination thereof. The image acquirer 260 can receive signals from the detector 206 and construct an image. In this manner, the image acquirer 260 can acquire an image of the wafer 203. The image acquirer 260 may also perform various post-processing functions, such as generating contours or overlaying indicators on the acquired image. The image acquirer 260 may adjust the brightness and contrast of the acquired image, etc. The storage 270 may be a storage medium, such as a hard disk, cloud storage, random access memory (RAM), or other type of computer-readable memory. The storage 270 may be coupled to the image acquirer 260 and may be used to save the scanned raw image data as an original image, a post-processed image, or other images to aid in processing. The image acquirer 260 and the storage 270 may be connected to the controller 109. In some embodiments, the image acquirer 260, the storage 270, and the controller 109 may be integrated into a single control unit.

[0028]

[0034] In some embodiments, the image acquirer 260 may acquire one or more images of the sample based on an imaging signal received from the detector 206. The imaging signal may correspond to a scanning motion for performing charged particle imaging. The acquired image may be a single image including multiple imaging areas. The single image may be stored in the storage 270. The single image may be an original image that may be divided into multiple regions. Each of these regions may include one imaging area that includes a feature of the wafer 203.

[0029]

[0035] In the process of measuring surface and subsurface structures using a charged particle beam tool (e.g., a scanning charged particle microscope), the scanning charged particle microscope ("SCPM") generates a primary charged particle beam for inspection (e.g., primary charged particle beam 220 of FIG. 2). For example, the primary charged particle beam may be a primary electron beam. Electrons of the primary electron beam are projected onto the surface of a sample. The sample may include features formed on a wafer 203. The wafer 203 may alternatively be referred to herein as a substrate 203 or a wafer substrate 203. The sample may be any material, such as a non-conductive resist, a silicon dioxide layer, a metal layer, or any layered combination of any dielectric or conductive material.

[0030]

[0036] Electrons in the primary electron beam may penetrate the surface of the sample to a certain depth (e.g., a few nanometers to a few micrometers) and interact with particles of the sample within the interaction volume. Some electrons in the primary electron beam may interact elastically with particles within the interaction volume (e.g., in the form of elastic scattering or collisions) and be reflected or recoiled from the surface of the sample. Elastic interactions conserve the total kinetic energy of the interaction bodies (e.g., electrons in the primary electron beam and particles of the sample), and the kinetic energy of the interaction bodies is not converted into other forms of energy (e.g., heat, electromagnetic energy, etc.). Such reflected electrons resulting from elastic interactions may be referred to as backscattered electrons (BSEs). Some electrons in the primary electron beam may interact inelastically with particles within the interaction volume (e.g., in the form of inelastically scattering or collisions). Inelastic interactions do not conserve the total kinetic energy of the interaction bodies, and some or all of the kinetic energy of the interaction bodies may be converted into other forms of energy. For example, through inelastic interactions, the kinetic energy of some electrons in the primary electron beam may cause electron excitation, generating electrons that exit the surface of the sample, which may be referred to as secondary electrons (SEs). Some of the SEs may have enough energy to eventually leave the sample surface and reach the detector, and some of the SEs may eventually leave the sample surface and re-enter, especially if the sample surface is positively charged. The yield or emission rate of BSEs and SEs may depend, for example, on the energy of the electrons in the primary electron beam and the material being inspected, among other factors. The energy of the electrons in the primary electron beam may be imparted in part by their acceleration voltage (e.g., the acceleration voltage between the anode 216 and the cathode 218 in FIG. 2). The number of BSEs and SEs may be greater than or less than (or may be the same as) the injected electrons in the primary electron beam.

[0031]

[0037] For example, a sample may include a first layer (e.g., a resist layer above the wafer surface) and a second layer (e.g., a patterned layer directly below the wafer surface). Each of the first and second layers may include designed patterns (e.g., targets) such as lines, slots, corners, edges, holes, etc. These features may have different heights. The primary electron beam may interact with particles in the first layer to generate SEs, and the SEs generated at different locations on the target in the first layer may be used to determine geometric information of the target in the first layer. The primary electron beam may also penetrate the first layer to reach the second layer and interact with particles in the second layer to generate BSEs, and the BSEs generated at different locations on the target in the second layer may be used to determine geometric information of the target in the second layer. The landing energy of electrons in the primary electron beam determines the depth at which SEs and bulk BSEs are generated within the sample. When the landing energy is low, a significant proportion of both SEs and BSEs may reach the detector. When the landing energy is high, more SEs fail to reach the detector, and therefore the proportion of detected electrons that are BSEs increases.

[0032]

[0038] Consistent with some embodiments of the present disclosure, a computer-implemented method for measuring overlay of a sample under scanning performed by a charged particle beam inspection apparatus may include obtaining a detector signal in response to scanning a target of the sample. In some embodiments, the charged particle beam inspection apparatus may include a scanning electron microscope. The sample may include a wafer.

[0033]

[0039] As an example, the charged particle beam inspection device can be an imaging system (e.g., imaging system 200 of FIG. 2). The sample can be a wafer (e.g., wafer 203 of FIG. 2) having structures (e.g., circuits) fabricated on its surface. In some embodiments, the target can be a specially designed and fabricated structure. For example, the target can be separate from and have no functional relationship to the fabricated circuits on the wafer. In some embodiments, the target can be fabricated in open space on the wafer that is not occupied by the fabricated circuits.

[0034]

[0040] The detector signal may be a signal output by a detector of a charged particle inspection apparatus (e.g., detector 206 in FIG. 2 ) in response to scanning. In some embodiments, a target may be scanned by a charged particle beam (e.g., in a single-beam inspection apparatus) or charged particle beamlets (e.g., in a multi-beam inspection apparatus). During scanning of the sample, after charged particles (e.g., electrons) of a primary beam (e.g., primary beam 220 in FIG. 2 ) hit the surface of the sample, secondary charged particles (e.g., SEs) and / or backscattered charged particles (e.g., BSEs) may be emitted from the surface of the sample and directed to a detector (e.g., detector 206 in FIG. 2 ). In some embodiments, secondary electrons and / or backscattered electrons may be emitted from the target and directed to a detector to generate a detector signal.

[0035]

[0041] In some embodiments, the detector signal may be a value representing the sum or count of electrons emitted from the target and detected. In some embodiments, the detector signal may be a value representing the sum of the charge of electrons emitted from the target and detected. In some embodiments, the detector signal may be visualized.

[0036]

[0042] In some embodiments, the target can include a first patterned layer and a second patterned layer below the first patterned layer. Each of the first patterned layer and the second patterned layer can include a diffraction grating. The pitch of the diffraction grating in each patterned layer can be the same or different.

[0037]

[0043] As an example, Figure 3 is a schematic diagram illustrating a sample including an exemplary target 300 fabricated on a substrate 305, consistent with some embodiments of the present disclosure. The substrate 305 may be a silicon wafer substrate 203. In some embodiments, the target 300 may be a diffraction-based overlay target. As shown in Figure 3, the target 300 includes a first patterned layer 301 and a second patterned layer 304 below the first patterned layer 301. The first patterned layer 301 and the second patterned layer 304 may each be a type of diffraction grating (e.g., a line grating).

[0038]

[0044] In some embodiments, the first pattern layer 301 may be a polymethyl methacrylate (PMMA) material. The first pattern layer 301 may be fabricated (e.g., by coating, lithography, and etching processes) on a support layer 302. The support layer 302 may also be formed from PMMA. The diffraction grating of the first pattern layer 301 may include a plurality of structures 306 (which may be lines 306) that define peaks and valleys above the support layer 302. The height of each structure 306 above the support layer 302 may be referred to as the height 311 of the diffraction grating in the first pattern layer 301. The first pattern layer 301 may have a pitch having a pitch value 309 that is the distance between the centers of two adjacent structures 306 of the diffraction grating.

[0039]

[0045] In some embodiments, the second pattern layer 304 may be a copper material. The second pattern layer 304 may be fabricated on the substrate 305 (e.g., by coating, lithography, and etching processes). The grating of the second pattern layer 304 may include a plurality of structures 307 (which may be lines 307) that define peaks and valleys above the surface of the substrate 305. The height of each structure 307 above the substrate 305 may be referred to as the height 312 of the grating in the second pattern layer 312. The second pattern layer 304 may have a pitch with a pitch value 310 that is the distance between the centers of two adjacent structures 307 of the grating. The pitch value 309 of the first pattern layer 301 may be different or the same as the pitch value 310 of the second pattern layer 304.

[0040]

[0046] In some embodiments, a silicon dioxide layer 303 may separate the support layer 302 and the second patterned layer 304. Gaps between structures 307 in the second patterned layer may be filled with silicon dioxide.

[0041]

[0047] The first patterned layer 301 and the second patterned layer 304 are separated by a separation distance 308 .

[0042]

[0048] Consistent with some embodiments of the present disclosure, a target, such as target 300 shown in FIG. 3, may be illuminated with an electron beam, such as primary electron beam 220. The electrons may be detected, thereby generating detection data, which may also be referred to as a detector signal. Determination of sample characteristics, such as overlay, may be performed in a computer-implemented manner based on the detection data.

[0043]

[0049] According to some embodiments, a model is constructed based on the known physical properties of the target 300 and the expected physical response of the target 300 to irradiation with electrons. The inventors have noticed that the detected response of a diffraction grating to irradiation resembles a waveform generated by the convolution of a block function with a kernel function, e.g., a Gaussian function. In particular, as the electron beam propagates through the structure, it widens. The convolution of a block function with a kernel function is an effective way to model this physical process. Some embodiments construct a model, and then the parameters of the model are adjusted so that the modeled detection data, i.e., the modeled detector signal, closely approximates the actual measured signal / data. Adjustable parameters of the model may include the position of the block function and the width of the kernel function. The adjusted values of the model parameters may be used to determine sample characteristics, such as overlay.

[0044]

[0050] The model may include multiple terms that combine to provide the modeled detection data. The model terms may include one or more of the following: a) Modeled offset, b) Modeled contribution from the first patterned layer 301; c) the contribution from the modeled second patterned layer 304, and d) Modeled interaction signals.

[0045]

[0051] The modeled offset may represent the average minimum signal level in the actual measured signal / data. The modeled offset may be in electron counts (in arbitrary units). The initial value of the modeled offset may be the average minimum value of the actual measured signal / data.

[0046]

[0052] The contribution from the modeled first patterned layer 301 may be referred to as the top signal. The top signal may be calculated as follows:

number

number

[0047]

[0053] The contribution from the modeled second patterned layer 304 may be referred to as the bottom signal. The bottom signal is calculated as follows:

number

number

[0048]

[0054] The interaction signal consists of a top signal and a bottom signal, as well as an additional term A interaction It depends on the point multiplication of interaction signal=A interaction × Top signal × Bottom signal

[0049]

[0055] A interaction The terms depend on the different expected physical interactions between the first patterned layer 301 and the second patterned layer 304. In particular, when the electron beam passes through the tops, or peaks, of the diffraction grating in the first patterned layer 301, the beam broadening and signal attenuation experienced are different than when the electron beam passes through the valleys of the diffraction grating. The interaction signal includes these different physical effects in the model.

[0050]

[0056] The model can be constructed by adding together all of the modeled offsets, top signals, bottom signals, and interaction signals described above.

[0051]

[0057] FIG. 4A illustrates a modeled signal and its components according to some embodiments. FIGS. 4B and 5 illustrate the accuracy of the modeled signal. In all of FIGS. 4A, 4B, and 5, the x-axis is pixel index, which relates to the location of the modeled and / or measured data / signal. In all of FIGS. 4A, 4B, and 5, the y-axis is gray level. The gray level may depend on the number of charged particles detected by a pixel of the detector over a period of time and / or the intensity of the signal detected by the pixel.

[0052]

[0058] Figure 4A shows all of the modeled top signal, bottom signal, and interaction components separately. The "Total Model" row in Figure 4A shows the sum of the model contributions, including the modeled offset.

[0053]

[0059] A process can be implemented to adjust the parameters of the model so that it better fits the actual measurements of electrons after irradiation of the target.

[0054]

[0060] The parameters in the model that can be adjusted to fit the model to the measured data are the offset, A top , A bottom , top shift, bottom shift, top-kernel width, bottom-kernel width, and A interaction Increasing the number of parameters adjusted can improve the accuracy of the model at the expense of increasing the complexity of fitting the model to the measured data. Reducing the number of parameters adjusted can decrease the accuracy of the model but can also reduce the complexity of fitting the model to the measured data.

[0055]

[0061] The tuning process may be performed using a cost function such as the L2 norm of the simulated modeled signal and, for example, a global minimizer, or using a combination of solving a set of linear equations and a global minimizer. Some embodiments also include other techniques for fitting the model to the measured data.

[0056]

[0062] 5 shows a modeled signal, or "total model" line, according to some embodiments when fitted to measured data. The modeled signal is a continuous line. The measured data includes measurements at different locations, as indicated by the discrete dots at different pixel indices.

[0057]

[0063] In FIG. 5, the parameter values that produced the modeled signals are as follows: -Offset=19.877 -Top-Kernel=(Gaussian kernel, width=5.84) -Bottom-Kernel=(Gaussian kernel, width=37.00) -A top =0.751 -A bottom =1.469 -A interaction =0.648 -Top shift = -0.135 -Bottom shift = -18.924

[0058]

[0064] Figure 4B shows the residual signal, or error signal, which represents the difference between the measured signal and the modeled signal. The value of the residual signal may be 0.782. The low absolute error value in Figure 4B indicates that the model fits the actual measurement data well.

[0059]

[0065] After the model is fitted to the measured data, the parameters of the model can be used to determine the characteristics of the target 300. In particular, overlay can be determined as a function of the top shift and bottom shift parameters of the model.

[0060]

[0066] The model according to some embodiments may be applied in several different situations. In particular, the model may be used to process received signals from a high-voltage scanning electron microscope (HV-SEM) to determine average overlay in an image of sample 300. Averaging the measurement data suppresses noise in the measurements. However, some embodiments also include not averaging the measurement data, and the model determines local overlay.

[0061]

[0067] Some embodiments include a top duty cycle and a bottom duty cycle in the model, which are also variable parameters that are adjusted when the model is fitted to the measured data, allowing the model to determine the average CD. Averaging the measured data suppresses noise in the measurements. However, some embodiments also include not averaging the measured data, and the model determines the local CD.

[0062]

[0068] Some embodiments are not limited to determining the properties of a diffraction grating. The lines of a diffraction grating are an example of a one-dimensional structure. A two-dimensional structure may, for example, have an L-shape in plan view. Some embodiments may be used to determine the properties of any feature formed on a substrate, including 2D structures, such as contact holes, bricks, and other patterns. The Block(..) function of the model may be modified to correspond to the shape of the structure being measured.

[0063]

[0069] FIG. 6 shows a flowchart of a computer-implemented method for measuring properties of a sample under a scan performed by a charged particle beam inspection device, according to one embodiment.

[0064]

[0070] In step 601 the method begins.

[0065]

[0071] In step 603, detection data is obtained in response to scanning a target across a sample with a charged particle beam inspection system, where the target includes multiple pattern layers.

[0066]

[0072] In step 605, one or more characteristics of the sample are determined in response to the obtained detection data and a model, where for each of a plurality of pattern layers of the target, the model includes terms that depend on properties of the pattern layer.

[0067]

[0073] In step 607, the method ends.

[0068]

[0074] Some embodiments also include some modifications and variations on the techniques described above.

[0069]

[0075] Some embodiments include models that use any of several different kernel functions to model the top and / or bottom signals. A preferred kernel function is a Gaussian kernel because it allows for accurate modeling. However, other types of kernel functions, such as a triangular kernel, can also be used, which reduces the complexity of the modeling process and thereby allows for faster modeling.

[0070]

[0076] Some embodiments include models that use a variable kernel function to model the top and / or bottom signals. With a variable kernel, the width of the kernel depends on the position of the structure 307 below the first patterned layer 301. This provides a better representation of the physical process and can improve the accuracy of the model at the expense of increased computation time.

[0071]

[0077] Some embodiments also include models that use variable kernel functions to model the top and / or bottom signals. The width of each kernel may depend on the relative position of the structure 306 in the first patterned layer 301 and the structure 307 in the second patterned layer. This may improve the accuracy of the model at the expense of increased computation time, as it better represents the physical process.

[0072]

[0078] Some embodiments may provide improved determination of properties of the sample 300 over optical techniques.

[0073]

[0079] Some embodiments may also improve other charged particle-based measurement techniques that make decisions based on arbitrary thresholds rather than on models of the actual physical processes that occur.

[0074]

[0080] Some embodiments can determine properties based on measurements of a single target 300. This is an advantage over techniques that require measurements from multiple targets.

[0075]

[0081] Some embodiments have been described with reference to a target including a first patterned layer 301 and a second patterned layer 304. Some embodiments may also be used with other types of targets, such as targets including three or more patterned layers. Models according to some embodiments may be modified to include terms representing the detection of electrons from each of the three or more layers of the target and interactions between the layers.

[0076]

[0082] Some embodiments have been described in the context of a sample being irradiated by an electron beam, such as primary beam 220. The electron beam may be from a single beam charged particle device or a multi-beam charged particle device. Some embodiments more generally include irradiating a sample with any charged particle beam.

[0077]

[0083] Some embodiments include a sample that includes multiple targets and a local property of the sample that is determined at each target.

[0078]

[0084] A non-transitory computer-readable medium may be provided that stores instructions for a processor (e.g., a processor of controller 109 of FIG. 1 ) to perform overlay measurements, such as method 800 of FIG. 8 or method 900 of FIG. 9 , data processing, database management, graphical display, operation of an image inspection apparatus or another imaging device, detection of defects on a sample, etc. Common forms of non-transitory medium include, for example, floppy disks, flexible disks, hard disks, solid state drives, magnetic tape or any other magnetic data storage medium, CD-ROMs, any other optical data storage medium, any physical medium with perforation patterns, RAM, PROMs and EPROMs, FLASH-EPROMs or any other flash memory, NVRAM, cache, registers, any other memory chip or cartridge, and networked versions of any of the foregoing.

[0079]

[0085] Some embodiments include the following clauses: 1. A charged particle beam inspection device configured to scan a sample including a target having multiple patterned layers; a controller including a circuit; a controller comprising: obtaining detection data in response to scanning the target; determining one or more characteristics of the sample in response to the obtained detection data and the model; configured to: for each of a plurality of pattern layers of the target, the model includes a term that depends on properties of the pattern layer; system. 2. The controller: determining parameters of the model such that the modeled detection signal substantially fits the obtained detection data; determining one or more characteristics of the sample in response to the determined parameters; 2. The system of claim 1, configured to: 3. The system of clause 1 or 2, wherein the one or more characteristics of the sample include overlay and critical dimensions. 4. The target includes a first patterned layer and a second patterned layer; each patterned layer includes a diffraction grating; A system according to any one of clauses 1 to 3. 5. The diffraction grating formed by the first pattern layer has a first pitch; the diffraction grating formed by the second pattern layer has a second pitch; The first pitch is different from the second pitch, 4. The system described in clause 4. 6. The model terms are a top signal, which is the contribution from the first pattern layer modeled; a bottom signal, which is the contribution from the modeled second pattern layer; an interaction signal that models the interaction between the first pattern layer and the second pattern layer; 6. The system of clause 4 or 5, comprising: 7. The system of clause 6, wherein the model further includes an offset term to model the average of the minimum values of the obtained detection data. 8. The top signal is

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[0080]

[0086] The block diagrams in the figures 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 a flowchart or block diagram may represent a module, segment, or portion of code, including one or more executable instructions for implementing the specified logical function(s). It should be understood that in some alternative implementations, the functions shown in the blocks may occur in an order different from that shown in the figures. For example, depending on the functionality involved, two blocks shown in succession may be executed or implemented substantially simultaneously, or the two blocks may be executed in the reverse order. Some blocks may also be omitted. It should also be understood that each block and combination of blocks in the block diagrams may be implemented by a dedicated hardware-based system that performs the specified function or act, or by a combination of dedicated hardware and computer instructions.

[0081]

[0087] It will be understood that the embodiments of the present disclosure are not limited to the exact configurations described above and illustrated in the accompanying drawings, and that various modifications and changes can be made without departing from the scope of the present invention.

Claims

1. 1. A system comprising: a charged particle beam inspection device configured to scan a sample including a target having a plurality of patterned layers; and a controller including circuitry, The controller: obtaining detection data in response to scanning the target; determining one or more properties of the sample in response to the obtained detection data and a model; configured to: The system wherein, for each of the plurality of pattern layers of the target, the model includes terms that depend on properties of the pattern layer.

2. The controller: determining parameters of the model such that the modeled detection signal substantially matches the obtained detection data; determining one or more properties of the sample in response to the determined parameters; The system of claim 1 configured to:

3. The system of claim 1 , wherein the one or more characteristics of the sample include overlay and critical dimensions.

4. the target includes a first patterned layer and a second patterned layer; The system of claim 1 , wherein each patterned layer comprises a diffraction grating.

5. the target includes a first patterned layer and a second patterned layer; each patterned layer includes a diffraction grating; the diffraction grating formed by the first pattern layer has a first pitch; the diffraction grating formed by the second pattern layer has a second pitch; The system of claim 1 , wherein the first pitch is different from the second pitch.

6. The term in the model is: a top signal, which is the contribution from the modeled first pattern layer; a bottom signal, which is the contribution from the modeled second pattern layer; an interaction signal that models the interaction between the first patterned layer and the second patterned layer; The system of claim 1 , comprising:

7. The term in the model is: a top signal, which is the contribution from the modeled first pattern layer; a bottom signal, which is the contribution from the modeled second pattern layer; an interaction signal that models the interaction between the first patterned layer and the second patterned layer; an offset term for modeling the average of the minimum values of the obtained detection data; The system of claim 1 , comprising:

8. The term in the model is: a top signal, which is the contribution from the modeled first pattern layer; a bottom signal, which is the contribution from the modeled second pattern layer; an interaction signal that models the interaction between the first patterned layer and the second patterned layer; an offset term for modeling an average of the minimum values of the obtained detection data; The top signal is [Equation 1] is calculated as, where: "A ｔｏｐ " represents the amplitude of the detected signal from the diffraction grating in the first patterned layer; "Block(..)" is a function that models the shape of the diffraction grating, "Top Pitch" is the pitch value of the first pattern layer; "Top duty cycle" relates to the width and spacing of the grating in the first patterned layer; "Top shift" is relative to the position reference point, 「 [Equation 2] " indicates a convolution operation, The system of claim 1 , wherein the “Top-Kernel” is a kernel function.

9. The term in the model is: a top signal, which is the contribution from the modeled first pattern layer; a bottom signal, which is the contribution from the modeled second pattern layer; an interaction signal that models the interaction between the first patterned layer and the second patterned layer; an offset term for modeling an average of the minimum values of the obtained detection data; Here, the bottom signal is [Equation 3] is calculated as, where: "A ｂｏｔｔｏｍ " represents the amplitude of the detected signal from the diffraction grating in the second patterned layer; "Block(..)" is a function that models the shape of the diffraction grating, "bottom pitch" is the pitch value of the second pattern layer; "bottom duty cycle" relates to the width and spacing of the grating in the second patterned layer; "Bottom shift" is relative to the position reference point, 「 [Equation 4] " indicates a convolution operation, The system of claim 1 , wherein the “Bottom-Kernel” is a kernel function.

10. The term in the model is: a top signal, which is the contribution from the modeled first pattern layer; a bottom signal, which is the contribution from the modeled second pattern layer; an interaction signal that models the interaction between the first patterned layer and the second patterned layer; an offset term for modeling an average of the minimum values of the obtained detection data; The top signal is [Equation 5] is calculated as, where: "A ｔｏｐ " represents the amplitude of the detected signal from the diffraction grating in the first patterned layer; "Block(..)" is a function that models the shape of the diffraction grating, "Top Pitch" is the pitch value of the first pattern layer; "Top duty cycle" relates to the width and spacing of the grating in the first patterned layer; "Top shift" is relative to the position reference point, 「 [Equation 6] " indicates a convolution operation, "Top-Kernel" is the kernel function, The bottom signal is [Equation 7] is calculated as, where: "A ｂｏｔｔｏｍ " represents the amplitude of the detected signal from the diffraction grating in the second patterned layer; "Block(..)" is a function that models the shape of the diffraction grating, "bottom pitch" is the pitch value of the second pattern layer; "bottom duty cycle" relates to the width and spacing of the grating in the second patterned layer; "Bottom shift" is relative to the position reference point, 「 [Equation 8] " indicates a convolution operation, "Bottom-Kernel" is the kernel function, The determined parameters of the model are the offset term, A ｔｏｐ , A ｂｏｔｔｏｍ , a top shift, a bottom shift, a top-kernel width, a bottom-kernel width, and one or more of the interaction signal.

11. The term in the model is: a top signal, which is the contribution from the modeled first pattern layer; a bottom signal, which is the contribution from the modeled second pattern layer; an interaction signal that models the interaction between the first patterned layer and the second patterned layer; an offset term for modeling an average of the minimum values of the obtained detection data; The top signal is [Equation 9] is calculated as, where: "A ｔｏｐ " represents the amplitude of the detected signal from the diffraction grating in the first patterned layer; "Block(..)" is a function that models the shape of the diffraction grating, "Top Pitch" is the pitch value of the first pattern layer; "Top duty cycle" relates to the width and spacing of the grating in the first patterned layer; "Top shift" is relative to the position reference point, 「 [Equation 10] " indicates a convolution operation, "Top-Kernel" is the kernel function, The bottom signal is [0011] is calculated as, where: "A ｂｏｔｔｏｍ " represents the amplitude of the detected signal from the diffraction grating in the second patterned layer; "Block(..)" is a function that models the shape of the diffraction grating, "bottom pitch" is the pitch value of the second pattern layer; "bottom duty cycle" relates to the width and spacing of the grating in the second patterned layer; "Bottom shift" is relative to the position reference point, 「 [0012] " indicates a convolution operation, "Bottom-Kernel" is the kernel function, The system of claim 1 , wherein the controller is configured to determine the overlay of the samples in response to the determined top shift and the determined bottom shift.

12. the charged particle beam inspection device includes a scanning electron microscope; The system of claim 1 , wherein the sample comprises a target formed on a substrate.

13. A non-transitory computer-readable medium storing a set of instructions executable by at least one processor of a device to cause the device to perform a method, the instructions comprising: The method comprises: obtaining detection data in response to scanning the target with the charged particle beam inspection device; determining one or more properties of the sample in response to the obtained detection data and the model; The non-transitory computer-readable medium, wherein the target includes a plurality of pattern layers, and for each of the plurality of pattern layers, the model includes a term that depends on the property of the pattern layer.

14. The method comprises: determining parameters of the model such that the modeled detection signal substantially matches the obtained detection data; determining one or more properties of the sample in response to the determined parameters; 14. The non-transitory computer-readable medium of claim 13, further comprising:

15. 14. The non-transitory computer-readable medium of claim 13, wherein the one or more characteristics of the sample include overlay and critical dimensions.

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