Information processing system, information processing method and program

Abstract

To provide an information processing system.SOLUTION: A processor acquires, in an acquisition step, an imaging condition for imaging a specimen using a SEM, a plurality of SEM images picked up based on the imaging condition, and a feature amount of each of the plurality of SEM images. The imaging condition includes a plurality of variable conditions of conditions which are changed when picking up the plurality of SEM images. In a first display processing step, first visual information which is visual information capable of visually recognizing a relation between the feature amounts of the plurality of SEM images and a first variable condition which is one of the plurality of variable conditions is displayed. The first visual information is configured to visually recognize the relation between the feature amounts of the plurality of SEM images and the first visual information by disposing a first object at a corresponding position in the first visual information. A display mode of the first object is determined based on second variable condition with a smaller change in the feature amounts of the SEM images than the first variable condition in the plurality of variable conditions.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an information processing system, an information processing method, and a program. [Background technology]

[0002] Patent Document 1 discloses a defect inspection method and an apparatus therefor that allow recipes to be easily determined and optimum inspection conditions to be easily selected.

[0003] The method described in Patent Document 1 is a method for inspecting defects in a pattern formed on a substrate, and discloses a defect inspection method characterized by: imaging the substrate while changing image acquisition condition parameters and inspection condition parameters to obtain multiple images; displaying the multiple images of the substrate obtained while changing the image acquisition condition parameters and inspection condition parameters on a screen together with indices for evaluating each of the multiple images; setting inspection conditions on the screen displaying the multiple images and their respective evaluation indices; and sequentially inspecting defects in the pattern formed on the substrate based on the set inspection conditions. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2004-294358 Summary of the Invention [Problem to be solved by the invention]

[0005] However, there is still room for improvement in the technology for increasing the efficiency of searching for the optimal imaging conditions for observing samples using a scanning electron microscope (SEM). [Means for solving the problem]

[0006] According to one aspect of the present invention, there is provided an information processing system. The information processing system includes at least one processor configured to execute a program to perform the following steps: In the acquisition step, imaging conditions for imaging a sample using an SEM, multiple SEM images of the sample captured under the imaging conditions, and feature quantities for each of the multiple SEM images are acquired. The imaging conditions include multiple variable conditions that are conditions changed when capturing the multiple SEM images. In the first display processing step, first visual information is displayed, which is visual information that allows visual recognition of the relationship between the feature quantities of the multiple SEM images and a first variable condition, which is one of the multiple variable conditions. The first visual information is configured to allow visual recognition of the relationship between the feature quantities of the multiple SEM images and the first variable condition by placing a first object at a corresponding position within the first visual information. The display manner of the first object is determined based on a second variable condition, among the multiple variable conditions, that causes a smaller change in the feature quantities of the SEM images than the first variable condition.

[0007] According to this configuration, it is possible to improve the efficiency of searching for the optimum imaging conditions for observing a sample using a scanning electron microscope (SEM). [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a configuration diagram illustrating an information processing system 1. FIG. [Figure 2] FIG. 2 is a block diagram showing a hardware configuration of an information processing device 2. [Figure 3] FIG. 2 is a block diagram showing the hardware configuration of a user terminal 3. [Figure 4] FIG. 2 is a diagram illustrating an example of the configuration of an SEM 4. [Figure 5] 2 is a flowchart showing an outline of information processing executed in the information processing system 1. [Figure 6] 6 is a flowchart showing an example of a search range setting process shown in FIG. 5. [Figure 7] FIG. 10 is a diagram illustrating an example of a region setting screen. [Figure 8]FIG. 10 is a diagram illustrating an example of a search range setting screen. [Figure 9] 6 is a flowchart showing an example of the exploratory photography process shown in FIG. 5. [Figure 10] 6 is a flowchart showing an example of a shooting condition specification process shown in FIG. 5. [Figure 11] The correspondence between the photographing conditions, the SEM image, and the feature amount is shown as result data D1. [Figure 12] FIG. 10 is a diagram illustrating a conceptual diagram of a data structure DS. [Figure 13] FIG. 10 is a diagram illustrating an example of a condition specifying screen. [Figure 14] 14 is a diagram for explaining a change in the display content of the condition specifying screen 7 when a specifying operation is performed on the visual information 8 shown in FIG. 13. FIG. [Figure 15] FIG. 10 is a diagram showing an example of a region setting screen 5 in the case where multiple regions of interest R3 can be designated for one photographic region R2. DETAILED DESCRIPTION OF THE INVENTION

[0009] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described below with reference to the accompanying drawings. Various features shown in the following embodiments can be combined with each other.

[0010] Incidentally, the program for realizing the software appearing in one embodiment may be provided as a non-transitory computer-readable medium, or may be provided so that it can be downloaded from an external server, or may be provided so that the program is started on an external computer and its functions are realized on a client terminal (so-called cloud computing).

[0011] Furthermore, various information processing according to an embodiment may realize input and output corresponding to the input. Here, the form of information referenced in such information processing (hereinafter referred to as reference information) is not limited as long as an output is obtained as a result of the input. The reference information may be, for example, rule-based information such as a database, a lookup table, or a predetermined function (including a decision formula such as a regression formula constructed using a statistical method), a trained model that has previously trained the correlation between input and output, or a large-scale language model that can output a desired result by inputting a prompt.

[0012] In one embodiment, a "unit" may include, for example, a combination of hardware resources implemented by a circuit in the broad sense and software information processing that can be specifically realized by these hardware resources. In one embodiment, various information is handled, and this information is represented, for example, by physical values ​​of signal values ​​representing voltage and current, high and low signal values ​​as a binary bit set consisting of 0 or 1, or quantum superposition (so-called quantum bits), and communication and calculations can be performed on a circuit in the broad sense.

[0013] Furthermore, a circuit in the broad sense is a circuit realized by at least an appropriate combination of a circuit, circuitry, processor, memory, etc. The processor may be a general-purpose processor or a dedicated circuit. That is, it includes an application specific integrated circuit (ASIC), a programmable logic device (e.g., a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)), etc.

[0014] 1. Hardware Configuration This section explains the hardware configuration.

[0015] <Information Processing System 1> FIG. 1 is a configuration diagram showing an information processing system 1. The information processing system 1 includes an information processing device 2, a user terminal 3, and an electron microscope (Scanning Electron Microscopy: SEM) 4. The information processing device 2, the user terminal 3, and the SEM 4 are configured to be able to communicate with each other via a telecommunications line. In one embodiment, the information processing system 1 is made up of one or more devices or components. For example, if the information processing system 1 is made up of only the information processing device 2, the information processing system 1 can be the information processing device 2. These components will be described below.

[0016] <Information processing device 2> 2 is a block diagram showing the hardware configuration of the information processing device 2. The information processing device 2 includes a communication unit 21, a storage unit 22, and a processor 23, and these components are electrically connected via a communication bus 20 inside the information processing device 2. Each component will be further described.

[0017] The communication unit 21 is preferably a wired communication means such as USB, IEEE1394, Thunderbolt (registered trademark), wired LAN network communication, etc., but may also include wireless LAN network communication, mobile communication such as 3G / LTE / 5G, BLUETOOTH (registered trademark) communication, etc. as needed. In other words, it is more preferable to implement it as a collection of multiple communication means. In other words, the information processing device 2 may communicate various information from the outside via the communication unit 21 and the network.

[0018] The storage unit 22 stores various pieces of information defined above. This can be implemented, for example, as a storage device such as a solid state drive (SSD) that stores various programs and the like related to the information processing device 2 executed by the processor 23, or as a memory such as a random access memory (RAM) that stores temporarily required information (arguments, arrays, etc.) related to the program operations. The storage unit 22 stores various programs, variables, etc. related to the information processing device 2 executed by the processor 23.

[0019] The processor 23 processes and controls the overall operations related to the information processing device 2. The processor 23 is, for example, a central processing unit (CPU) not shown. The processor 23 realizes various functions related to the information processing device 2 by reading out predetermined programs stored in the storage unit 22. In other words, information processing by software stored in the storage unit 22 is specifically realized by the processor 23, which is an example of hardware, and can be executed as each functional unit included in the processor 23. These will be described in more detail in the next section. Note that the processor 23 is not limited to being single, and multiple processors 23 may be provided for each function. A combination of these may also be used.

[0020] The processor 23 is configured to be able to acquire information from the user terminal 3 or other devices. The processor 23 is configured to be able to acquire various pieces of information by reading out various pieces of information stored in a storage area that is at least a part of the memory unit 22 and writing the read out information in a working area that is at least a part of the memory unit 22. The storage area is, for example, an area of ​​the memory unit 22 that is implemented as a storage device such as an SSD. The working area is, for example, an area that is implemented as a memory such as a RAM. Note that acquisition by the processor 23 includes acquiring output results from each functional unit included in the processor 23.

[0021] The processor 23 is also configured to be able to display various types of information. The information can be presented to the user via the display unit 34 of the user terminal 3 or another device. In such a case, for example, the processor 23 controls the display unit 34 of the user terminal 3 to display visual information such as a screen, an image including a still image or a video, an icon, or a message. The processor 23 may generate only rendering information for displaying the visual information on the user terminal 3. Note that the processor 23 may present the output information to the user without going through the user terminal 3 or another device user.

[0022] <User terminal 3> 3 is a block diagram showing the hardware configuration of the user terminal 3. The user terminal 3 includes a communication unit 31, a storage unit 32, a processor 33, a display unit 34, and an HMI device 35, and these components are electrically connected via a communication bus 30 inside the user terminal 3. The description of the communication unit 31, the storage unit 32, and the processor 33 is omitted because they are the same as the description of each unit in the information processing device 2.

[0023] The display unit 34 may be included in the housing of the user terminal 3 or may be externally attached. The display unit 34 displays a graphical user interface (GUI) screen that can be operated by the user. This is preferably implemented by selectively using display devices such as a CRT display, a liquid crystal display, an organic EL display, or a plasma display depending on the type of user terminal 3.

[0024] The HMI device 35 is a human-machine interface device configured to receive input from a user. The HMI device 35 may be included in the housing of the user terminal 3 or may be externally attached. For example, the HMI device 35 may be integrated with the display unit 34 as a touch panel. The touch panel allows the user to input operations such as tapping and swiping. Of course, instead of a touch panel, switch buttons, a mouse, a QWERTY keyboard, a voice recognition device, a gesture detection device, a gaze detection device, a biosignal detection device, a photographing device, or the like may be used. In other words, the HMI device 35 receives an operation input from the user. In response, the HMI device 35 transfers a signal corresponding to the operation input to the processor 33 via the communication bus 30. The processor 33 may perform predetermined control or calculations as necessary.

[0025] <sem4> FIG. 4 is a diagram showing an example of the configuration of an SEM 4. The SEM 4 is configured to capture an SEM image showing the appearance or state of the sample S by irradiating incident electrons e1 onto the sample S and observing electrons e2 emitted from the sample S. There are various types of electrons e2, such as secondary electrons, backscattered electrons, and Auger electrons, and appropriate electrons e2 may be used depending on the purpose of observation. For convenience of explanation, the electrons e2 will be treated as backscattered electrons e2 here. As shown in FIG. 4, the SEM 4 includes a housing 41, an electron gun 42, a magnetic lens 43, a stage 44, and a detector 45.

[0026] The housing 41 is configured so that a vacuum state can be created by reducing the pressure inside the housing 41. The reduction in pressure is performed using, for example, an exhaust pump or the like provided outside the SEM 4.

[0027] The electron gun 42 is configured to output incident electrons e1. The electron gun 42 may be, for example, a tungsten filament type.

[0028] The magnetic lens 43 is configured to collect the incident electrons e1 output from the electron gun .

[0029] The stage 44 is configured so that a sample S can be placed thereon. Incident electrons e1 focused by a magnetic lens 43 are incident on the sample S placed on the stage 44. As a result, reflected electrons e2 are emitted from the sample S. An acceleration voltage is applied between the electron gun 42 and the stage 44. The incident electrons e1 are accelerated according to potential energy based on the acceleration voltage and reach the sample S. This makes it possible to adjust the energy of the incident electrons e1 that are incident on the sample S.

[0030] The detector 45 is configured to detect backscattered electrons e2 emitted from the sample S. The detector 45 is, for example, a semiconductor detector such as a photodiode for detecting electron beams.

[0031] The SEM 4 is configured to perform SEM-based measurements on the sample S under predetermined imaging conditions. The imaging conditions may include, for example, the accelerating voltage of the incident electrons e1, working distance, resolution, vacuum level, integration time, type of detector 45, scan mode, pixel time (pixel dwell time), and spot intensity (collection pattern of the incident electrons e1). These conditions can be changed when capturing each of the multiple SEM images. The conditions changed when capturing the multiple SEM images are called variable conditions. For example, if the multiple SEM images include SEM images with different accelerating voltages as a parameter of the imaging conditions, the accelerating voltage is a variable condition in the relationship between these SEM images. In other words, the imaging conditions may include multiple variable conditions that are changed when capturing the multiple SEM images.

[0032] 2. Information Processing In this section, the information processing executed in the information processing system 1 described above will be described with reference to the flowcharts of each information processing. The information processing described below may include any exception processing not shown. Exception processing includes the interruption of the information processing or the omission of each processing. The selection or input performed in the information processing may be based on a user operation or may be performed automatically without relying on a user operation.

[0033] 2.1. Overview of information processing 5 is a flowchart showing an outline of information processing executed in the information processing system 1. This information processing is performed, for example, to identify SEM imaging conditions suitable for analyzing the sample S.

[0034] 5, first, in step S1, the information processing system 1 executes a search range setting process to set a search range of SEM imaging conditions suitable for analyzing the sample S. Specifically, the processor 23 specifies multiple candidate imaging conditions by changing at least one of the parameters included in the imaging conditions as a variable condition.

[0035] Next, in step S2, the information processing system 1 executes a search photography process, photographs the sample S using an SEM under multiple candidate search conditions within the set search range, and obtains multiple SEM images corresponding to each photography condition.

[0036] Next, in step S3, the information processing system 1 executes an imaging condition specification process, and specifies SEM imaging conditions suitable for analyzing the sample S based on the multiple SEM images for each imaging condition obtained in step S2.

[0037] Next, in step S4, the information processing system 1 captures an SEM image for analysis under the imaging conditions specified in step S3. This allows the user to obtain an SEM image captured under imaging conditions suitable for analyzing the sample S.

[0038] 2.2. Search range setting process Next, an example of the search range setting process in step S1 in FIG. 5 will be described.

[0039] 2.2.1. Search range setting process flow FIG. 6 is a flowchart showing an example of the search range setting process shown in FIG. 5. As shown in FIG. 6, first, in step S11, the processor 23 acquires a designation of an observation region of the sample S. The designation may be input manually by a user or automatically by the information processing system 1. The processor 23 transmits the designation to the SEM 4. The SEM 4 performs measurements on the observation region of the sample S based on the designation. As a result, an SEM image including the observation region is obtained. Hereinafter, for convenience of explanation, an image including the observation region is referred to as an entire SEM image. In this embodiment, the entire SEM image coincides with an SEM image obtained by capturing the observation region. At this time, in order to calculate the position coordinates of the stage 44, the capturing conditions of the entire SEM image are stored in the storage unit 22 in a state associated with the entire SEM image. The capturing conditions of the entire SEM image may include, for example, information regarding the position of the stage 44 during capturing (e.g., the amount of movement of the stage 44, etc.), the capturing magnification, the size of the SEM image, the size of the pixels constituting the SEM image, etc.

[0040] Next, in step S12, the processor 23 acquires an entire SEM image from the SEM 4.

[0041] Next, in step S13, the processor 23 displays a region setting screen on the display unit 34 based on the acquired overall SEM image. The region setting screen is configured so that multiple imaging regions can be set within the observation region of the overall SEM image. Specific examples of this screen will be described later.

[0042] Next, in step S14, the processor 23 acquires specifications regarding the imaging area and the area of ​​interest. The imaging area is a part of the observation area and is an area that will form an SEM image by executing the exploratory imaging process described below. Here, multiple imaging areas can be specified, and imaging is performed using an SEM for each of the specified multiple imaging areas under a certain imaging condition. The area of ​​interest is an area of ​​the imaging area that is used when calculating feature quantities corresponding to the SEM image. The feature quantity is, for example, a scalar quantity that represents features related to the shape of the sample S included in the imaging area. Specifically, for example, the feature quantity can be defined as a quantity corresponding to the average brightness value, standard deviation of brightness values, number of edges, texture contrast, surface smoothness, etc. in the area of ​​interest. The imaging of the imaging area is performed at a higher magnification than the imaging of the observation area.

[0043] Next, in step S15, the processor 23 displays a search range setting screen on the display unit 34. The search range setting screen is configured to allow input of specifications related to the search range of the imaging conditions of the SEM image to be executed for the imaging region specified in steps S13 and S14. An example of the search range setting screen will be described later.

[0044] Next, in step S16, the processor 23 acquires a specification regarding the search range of the imaging conditions based on the input results on the search range setting screen. The specification regarding the search range may include, for example, an upper limit value, a lower limit value, and a step width for each parameter included in the imaging conditions. The specification regarding the search range may also include a specification regarding an option to be used as a candidate imaging condition from among options regarding the parameters included in the imaging conditions. The specification regarding the search range may also include a specification regarding whether or not to treat a certain parameter as a variable condition. In other words, the processor 23, as a specification unit, accepts a specification of imaging conditions for capturing an SEM image of the sample S. The specification includes a specification regarding variable conditions.

[0045] Next, in step S17, the processor 23 identifies candidate imaging conditions based on the specification related to the search range acquired in step S16. The candidate imaging conditions can be used in capturing an SEM image in the search imaging process in step S2.

[0046] With the above, the information processing system 1 ends the search range setting process and proceeds to the search shooting process in step S2.

[0047] 2.2.2. Search range setting process flow Next, an example of the region setting screen displayed on the display unit 34 in step S13 will be described. Fig. 7 is a diagram showing an example of the region setting screen. The region setting screen 5 is configured to enable the user to specify various regions such as the photographing region R2 and the region of interest R3, as well as the manner in which the photographing region R2 is specified, while visually recognizing the observation region R1 as the entire SEM image IM1. As shown in Fig. 7, the region setting screen 5 includes a specified region 51, an SEM image region 52, and a button 53.

[0048] The designation area 51 is an area where a designation method for the photographing area R2 can be input. For example, the designation area 51 is configured to allow input of a designation regarding a setting method for the photographing area R2 ("photography pattern"), the number of photographing areas R2 that can be designated ("number of photographing areas"), the magnification when photographing the photographing area R2, etc. When the "photography pattern" is set to "random," the processor 23 initially arranges the photographing area R2 randomly within the observation area R1. Note that the arranged photographing area R2 can be configured to be arbitrarily changeable by the user.

[0049] The SEM image area 52 is an area configured to allow each of the areas R1, R2, and R3 in the overall SEM image IM1 to be viewed. In this embodiment, the range included in the overall SEM image IM1 constitutes the observation area R1. Furthermore, since the number of imaging areas is set to "10" in the specified area 51, ten imaging areas R2 are set in the overall SEM image IM1 displayed in the SEM image area 52. The shape of each imaging area R2 is rectangular, but this can be changed as appropriate depending on the imaging mode of the SEM image. In addition, in FIG. 7, at least some of the ten imaging areas R2 are arranged in a grid pattern with no gaps between them. However, this is not limited to this, and they can be arranged in any position. For example, the imaging area R2 can be manually changed by the user by dragging the frame indicating each imaging area R2. In this embodiment, one attention area R3 is set within each imaging area R2. For example, one attention area R3 can be randomly arranged within the corresponding imaging area R2. The user can arbitrarily change the position of the arranged attention area R3.

[0050] The button 53 is a UI for confirming the contents set by the specified region 51 and the SEM image region 52. When the button 53 is pressed, the processor 33 generates specifications regarding the settings of the photographing region R2, the region of interest R3, and the magnification of photographing these, and transmits them to the information processing device 2. As a result, the processor 23 acquires the specifications regarding the photographing region R2, etc. transmitted from the processor 33 in step S14. Thereafter, the processor 23 executes the process of step S15, and transitions the display content of the display unit 34 from the region setting screen 5 to the search range setting screen 6.

[0051] 2.2.3. Search range setting screen Next, an example of the search range setting screen displayed in step S15 will be described below. Fig. 8 is a diagram showing an example of the search range setting screen.

[0052] As shown in FIG. 8 , the search range setting screen 6 includes a search range setting area 61 and a button 62. The search range setting area 61 is configured to allow setting of a search range for each parameter that can be changed in the imaging conditions. The parameters may include, for example, acceleration voltage, resolution, working distance (WD), sensitivity (UD, MD) of the detector 45, scanning mode of the electron beam (scan mode), pixel dwell time (pixel time), integration time (number of integrated frames), and density of incident electrons e1 (spot intensity). The search range setting area 61 may include input fields configured to allow specification of upper and lower limits and step widths (Δ) for each parameter included in the imaging conditions, such as acceleration voltage and working distance. The search range setting area 61 may also include a UI (in this embodiment, a button-type UI allowing multiple selections) for specifying options to be used as imaging condition candidates from among options related to parameters included in the imaging conditions, such as resolution and sensitivity of the detector 45. The processor 23 causes the UI to display specified parameters and unspecified parameters in different ways.

[0053] Among the parameters specified in this way, if only one condition can be identified within the search range, the parameter is treated as a fixed condition when searching for candidate imaging conditions. Therefore, the specification of the search range may include a specification as to whether a certain parameter is treated as a variable condition. Examples of such specifications include a case where the upper and lower limits are the same and the step width is Δ0, such as in the case of spot intensity, or a case where only one of multiple options is specified, such as in the case of scan mode or number of integrated frames.

[0054] Button 62 is a button for confirming that the conditions specified in search range setting area 61 are to be the search range. When button 62 is pressed, processor 33 generates a specification regarding the search range and transmits it to information processing device 2. In step S16, processor 23 acquires the specification regarding the search range transmitted from processor 33.

[0055] For example, if the candidate imaging conditions generated include three acceleration voltage candidates (1 kV, 2 kV, and 3 kV), three resolution candidates (640 × 480, 1280 × 960, and 2560 × 3840), three working distance candidates (5.0, 5.5, and 6.0), and only one other parameter candidate, then 3 × 3 × 3 = 27 imaging conditions, representing all combinations of these three parameter candidates, are generated. In this case, each parameter with multiple options corresponds to a variable condition, which is a condition changed when capturing multiple SEM images. In other words, the imaging conditions may include multiple variable conditions, which are conditions changed when capturing multiple SEM images. The variable conditions may also include at least one of the electron beam acceleration voltage, working distance, resolution, vacuum level, and integration time.

[0056] 2.3. Exploratory photography processing Next, an example of the exploratory shooting process in step S2 in Fig. 5 will be described. Fig. 9 is a flowchart showing an example of the exploratory shooting process shown in Fig. 5. As shown in Fig. 9, first, in step S21, the processor 23 acquires candidates for the shooting conditions identified in step S1.

[0057] Next, in step S22, the processor 23 generates an imaging sequence based on the acquired imaging condition candidates. The imaging sequence specifies the order of imaging conditions when performing SEM imaging of the sample S. For example, the processor 23 determines the order of imaging conditions based on the time required to change each variable of the imaging conditions so as to minimize the total time required to change the imaging conditions, and generates the imaging sequence. Such optimization of imaging conditions may be performed based on a predetermined priority for each variable to be changed, or may be performed using an optimization method for a known model such as the traveling salesman problem. The imaging sequence may also include the order of imaging of the imaging region R2 under each imaging condition. Here, the imaging sequence is configured to image each imaging region R2 under a certain imaging condition, change the imaging condition, and then image each imaging region R2 again under the changed imaging condition. In other words, the imaging sequence may be specified so that after imaging multiple regions (imaging regions R2) of the sample S under a certain imaging condition, SEM images of the multiple regions of the sample S are captured after changing the variable condition included in the imaging condition.

[0058] Next, in step S23, the processor 23 transmits the generated imaging sequence to the SEM 4 and causes the SEM 4 to perform imaging of the sample S in accordance with the imaging sequence. As a result of executing the imaging sequence, the SEM 4 generates imaging conditions for imaging the sample S by the SEM and multiple SEM images of the sample imaged based on the imaging conditions. In other words, the processor 23 generates multiple SEM images by causing the SEM 4 to capture SEM images of multiple predetermined regions of the sample S in accordance with the imaging sequence including the imaging conditions. An example of the processing of step S23 will now be described. Note that the processing of steps S230 to S235 below is performed for each imaging condition in the order according to the imaging sequence. Furthermore, imaging under each imaging condition is performed for each imaging region R2 specified in step S14.

[0059] First, in step S230, the SEM 4 adjusts the optical system according to the imaging conditions for the next imaging. For example, the SEM 4 adjusts the air pressure inside the housing 41, the density of electrons output from the electron gun 42, the manner in which the magnetic field is applied by the magnetic lens 43, the potential difference between the electron gun 42 and the stage 44, the distance between the electron gun 42 and the stage 44 (corresponding to the so-called working distance), etc. In this way, the SEM 4 changes the desired variable condition among the imaging conditions.

[0060] Next, in step S231, the SEM 4 moves the stage 44 so that the incidence range of the incident electrons e1 coincides with the designated imaging region R2, thereby making it possible to image the imaging region R2.

[0061] Next, in step S232, the SEM 4 irradiates the imaging region R2 of the sample S with incident electrons e1 in accordance with imaging conditions, and captures an SEM image based on the detection result of the reflected electrons e2 by the detector 45. As a result, an SEM image of a certain imaging region R2 under certain imaging conditions is obtained.

[0062] Next, in step S233, the SEM 4 calculates the feature amount of the region of interest R3 based on the obtained SEM image. This process does not have to be performed by the SEM 4, but may be executed by the information processing device 2 or the like that acquired the SEM image.

[0063] Next, in step S234, the SEM 4 calculates an omission determination value based on the imaging history of the SEM images. For example, the SEM 4 compares the feature amounts of the latest SEM image with the feature amounts of SEM images acquired under the same imaging conditions as those of the latest SEM image, and calculates the change in the feature amounts in the latest SEM image as the omission determination value. As an example, the SEM 4 calculates the difference in the feature amounts between the latest SEM image and the immediately preceding SEM image as the change in the feature amounts. Furthermore, the SEM 4 calculates the difference in the feature amounts between the latest SEM image and multiple SEM images acquired immediately before, and calculates the omission determination value based on the change in each difference. This process does not have to be performed by the SEM 4, but may be performed by the information processing device 2 or the like that acquired the SEM image.

[0064] Next, in step S235, the SEM4 determines whether the omission determination value calculated in step S234 is equal to or less than a preset value. If it is determined that the omission determination value is equal to or less than the preset value, the SEM4 returns the process to step S231 and executes the process from step S231 for the next imaging region R2. Note that when imaging for all imaging regions R2 under a certain imaging condition is completed, the SEM4 returns the process to step S230 and executes the process from step S230 for the next candidate imaging condition. When the processes from step S230 onwards are completed for all candidate imaging conditions, the information processing system 1 ends the exploratory imaging process. As a result, multiple SEM images are generated for each imaging condition and imaging region R2 under which imaging was performed.

[0065] In another example, in step S234, the SEM 4 may calculate the omission determination value by comparing feature quantities of different regions of interest R3 under the same imaging conditions. A small omission determination value based on different regions of interest R3 under the same imaging conditions may indicate imaging conditions that make it difficult to obtain meaningful information from the SEM image. In this case, the SEM 4 may further shorten the imaging time by omitting imaging under such imaging conditions in step S235. Note that imaging conditions that make it difficult to obtain meaningful information include, for example, when halation occurs across the entire SEM image.

[0066] In yet another example, in step S234, the SEM 4 may calculate an omission determination value by comparing feature quantities of different regions of interest R3 under different imaging conditions. A small omission determination value based on different regions of interest R3 under different imaging conditions indicates that changing the imaging conditions has little effect on the SEM image, and therefore changing the imaging conditions is likely to be a low priority when searching for optimal imaging conditions. By omitting imaging under such imaging conditions in step S235, the SEM 4 can further shorten the imaging time.

[0067] On the other hand, if it is determined in step S235 that the change in the feature amount is greater than the default value, the SEM 4 skips steps S231 to S235 for the next and subsequent imaging regions R2 under the same imaging conditions, changes the imaging conditions, and returns to step S230. The default value can be set arbitrarily depending on the expected change in the feature amount. Similarly, the manner in which the change in the feature amount is compared with the default value is also arbitrary. In other words, based on a judgment value (e.g., an omission judgment value) calculated from the change in the feature amount between SEM images obtained according to the imaging sequence, the variable conditions included in the imaging conditions are changed regardless of whether imaging of multiple regions of the sample S under the previous imaging conditions has been completed. This configuration can shorten the time required to obtain SEM images for understanding the relationship between the feature amount and the variable conditions.

[0068] 2.4. Shooting condition specific processing 2.4.1. Flow of the imaging condition identification process Next, an example of the imaging condition specification process of step S3 in FIG. 5 will be described. FIG. 10 is a flowchart showing an example of the imaging condition specification process shown in FIG. 5. As shown in FIG. 10, first, in step S31, the processor 23 acquires imaging conditions for imaging the sample S using an SEM, multiple SEM images of the sample S captured under the imaging conditions, and feature amounts for each of the multiple SEM images, which are obtained as a result of the exploratory imaging process of step S2. The processor 23 may acquire the SEM images and their imaging conditions, set a region of interest R3 for each of the acquired SEM images, and calculate the feature amounts and their changes. Note that the processor 23 may use the feature amounts calculated in step S233 when performing the process of step S31. In this embodiment, the processor 23 acquires, as multiple SEM images, SEM images of the sample S captured under the imaging conditions specified in step S16.

[0069] 11 shows the correspondence between the photographing conditions, SEM images, and feature amounts as result data D1. As shown in FIG. 11, the result data D1 may include image numbers associated with the respective SEM images, L photographing conditions C1 to CL, photographing area numbers 1 to M for identifying M photographing areas R2, and N feature amounts Y1 to YN calculated from the region of interest R3 of the photographing area R2 under each photographing condition. If the omission process in step S235 is not performed, N will be a maximum of L×M. Here, as an example, a case where L=2, M=3, and N=2×3=6 is shown.

[0070] Returning to FIG. 10 , next, in step S32, the processor 23 identifies variable conditions between a plurality of SEM images based on the acquired imaging conditions. In this embodiment, the processor 23 identifies a plurality of variable conditions based on the designation in step S16. Such a configuration can facilitate the identification of variable conditions. For example, the processor 23 identifies, as variable conditions, parameters for which a plurality of values ​​can be set as a result of input into the search range setting area 61 of the search range setting screen 6. Note that the manner in which variable conditions are identified is not limited to this and is arbitrary. For example, the processor 23 may find differences between the acquired imaging conditions and identify, as variable conditions, parameters for which there is a difference equal to or greater than a permissible value.

[0071] Next, in step S33, the processor 23 calculates a change in the feature quantity related to the variable condition by comparing the feature quantity of the SEM image captured under different imaging conditions based on the imaging results of step S2 with the feature quantity of the SEM image captured under different imaging conditions. The change may be appropriately normalized, for example, by the change in the variable condition. When an imaging sequence is generated in which each variable condition is changed one by one, the SEM 4 calculates the change in the feature quantity related to the variable condition by, for example, comparing the feature quantity of the SEM image captured under the immediately preceding imaging condition with the latest SEM image. Note that when multiple SEM images of the imaging region R2 are captured under the same imaging condition, a value based on the feature quantities of the multiple SEM images for one imaging condition, such as an average value, median value, maximum value, or minimum value, may be assigned as a representative value of the feature quantity for that imaging condition. Hereinafter, for convenience of explanation, the change in the feature quantity related to the variable condition calculated in step S33 may be simply referred to as the change in the feature quantity. Note that the change in the feature quantity may differ from the omission determination value calculated in step S234.

[0072] Then, the processor 23 hierarchically organizes the imaging conditions and the SEM images corresponding to those imaging conditions based on the magnitude of change in the feature amount related to the variable condition. This allows the processor 23 to generate a data structure DS structurally indicating the correspondence between the imaging conditions and the SEM images. For example, the processor 23 groups the imaging conditions so that the variable condition with the largest change in the feature amount as a result of imaging multiple imaging regions R2 is ranked higher. In this embodiment, the processor 23 groups the variable conditions so that the imaging conditions with the largest number of images are ranked higher, because imaging conditions with small changes in the feature amount may be omitted in step S235. One method for grouping the variable conditions is, for example, a method of performing sensitivity analysis using a model f (i.e., y = f(x, R)) that outputs a feature amount y by inputting a vector X corresponding to the imaging condition and a variable R corresponding to the imaging region. The vector X may include at least the variable condition as an element. The model f may be a function obtained by simulation or the like, a lookup table obtained experimentally or empirically, or a trained model trained by machine learning or the like. For example, a vector X can be expressed as X=(accelerating voltage value, WD value, resolution value).

[0073] An example of the data structure DS will now be described. FIG. 12 is a conceptual diagram of the data structure DS. For simplicity, a case will be described in which three variable conditions are specified: acceleration voltage, working distance (WD), and resolution. Each variable condition, acceleration voltage, working distance, and resolution, can take three values. Therefore, imaging of each imaging region R2 is performed under 3 × 3 × 3 = 27 imaging conditions. Among these, the changes in feature amounts are, in descending order, acceleration voltage, working distance, and resolution.

[0074] As shown in FIG. 12, the data structure DS first includes groups G1 to G3 for each acceleration voltage based on the possible values ​​of the acceleration voltage, which is the variable condition (an example of a first variable condition) that causes the greatest change in feature quantity among the three variable conditions. Each of the groups G1 to G3 is configured to include an imaging condition in which the acceleration voltage takes a corresponding value (1 kV, 2 kV, 3 kV), regardless of whether other variable conditions are the same. For ease of explanation, the groups G1 to G3 may be referred to as Gx below using a variable x. The variable x is a subscript corresponding to the value of the first variable condition. In this embodiment, x=1 corresponds to the acceleration voltage being 1 kV, x=2 corresponds to the acceleration voltage being 2 kV, and x=3 corresponds to the acceleration voltage being 3 kV.

[0075] Furthermore, the data structure DS is configured so that each group Gx includes three groups Gx1 to Gx3, one for each working distance, based on the possible values ​​of the working distance, which is the variable condition (an example of a second variable condition) with the second largest change in feature quantity after the acceleration voltage. Each of the groups Gx1 to Gx3 is configured to include imaging conditions for which the working distance takes a corresponding value (5.0 mm, 5.5 mm, 6.0 mm), regardless of differences in other variable conditions other than the higher-level variable condition (here, the acceleration voltage). Hereinafter, for ease of explanation, the groups Gx1 to Gx3 may be referred to as Gxy, using a variable y. The variable y is a subscript corresponding to the value of the second variable condition. In this embodiment, y=1 corresponds to the working distance = 5.0 mm, y=2 corresponds to the working distance = 5.5 mm, and y=3 corresponds to the working distance = 6.0 mm.

[0076] Furthermore, the data structure DS is configured so that each group Gxy includes three groups Gxy1 to Gxy3, each for a different resolution, based on the possible values ​​of resolution, which is the variable condition (an example of a third variable condition) with the second largest change in feature quantity after working distance. Each of the groups Gxy1 to Gxy3 is configured to include imaging conditions with corresponding resolution values ​​(640 × 480, 1280 × 960, 2560 × 3840), regardless of differences in other variable conditions other than the higher-level variable conditions (here, accelerating voltage and working distance). For ease of explanation, the groups Gxy1 to Gxy3 may be referred to as Gxyz, using a variable z. The variable z is a subscript corresponding to the value of the third variable condition. In this embodiment, z = 1 corresponds to a resolution of 640 × 480, z = 2 corresponds to a resolution of 1280 × 960, and z = 3 corresponds to a resolution of 2560 × 3840.

[0077] In this way, in this embodiment, the processor 23 classifies the imaging conditions into a hierarchical structure of groups Gx → Gxy → Gxyz so that the imaging conditions with the greatest change in feature amount for each of the three variable conditions, which take three values, are ranked higher. In this way, the processor 23 generates a data structure DS. Each of the groups Gx, Gxy, and Gxyz in each data structure DS is associated with an SEM image corresponding to the imaging condition belonging to the group Gx, Gxy, or Gxyz.

[0078] 10, next, in step S34, processor 23 executes processing for identifying variable conditions in analytical imaging based on the generated data structure DS. Thereafter, in step S35, processor 23 identifies imaging conditions to be used in analytical imaging in step S4 based on the variable conditions identified in step S34, and ends the imaging condition identification processing in step S3.

[0079] An example of the process of step S34 will now be described. Processor 23 executes the processes of steps S341 to S343 shown below for each variable condition, starting from the variable condition of the highest hierarchical level. Here, the highest group Gx will be used as an example, but the same applies to groups Gxy, Gxyz, etc. of the following hierarchical levels.

[0080] First, in step S341, the processor 23 identifies a thumbnail image for each group Gx corresponding to a variable condition based on a set of SEM images associated with the imaging conditions belonging to the group Gx. For example, the processor 23 identifies an SEM image having a median feature value among the set of SEM images included in the group Gx as the thumbnail image of the group Gx. At this time, the thumbnail images of all groups G1 to G3 may be identified as SEM images captured in the same imaging region R2. Identifying a thumbnail image from each group Gx in this way is equivalent to identifying a thumbnail image from a set of SEM images associated with groups Gx1 to Gx3 belonging to each group Gx. The thumbnail image is used as an object (here, a first object) corresponding to the group Gx in visual information (here, first visual information) described later. In other words, the display mode of the first object is determined based on a second variable condition among multiple variable conditions, which causes smaller change in the feature value of the SEM image than the first variable condition. Specifically, the first object is represented using an SEM image captured under imaging conditions including a first variable condition of a value corresponding to a corresponding position in the first visual information. With this configuration, it is possible to view at a glance the relationship between the feature amount and the variable condition for an SEM image that the user intuitively feels is appropriate.

[0081] Next, in step S342, the processor 23, based on the generated data structure DS, causes the display unit 34 to display a condition identification screen including first visual information indicating the relationship between the variable condition (here, acceleration voltage) used in grouping the group Gx and the feature quantity corresponding to the group Gx. In other words, the processor 23, as a display processing unit, causes the display unit 34 to display first visual information, which is visual information that allows the relationship between the feature quantities of the multiple SEM images and a first variable condition, which is one of the multiple variable conditions, to be visually recognized. The first visual information is configured so that the relationship between the feature quantities of the multiple SEM images and the first variable condition can be visually recognized by placing a first object at a corresponding position within the first visual information. For example, the above-mentioned thumbnail image is used as the first object. The processor 23 may also display the first object so that the visual aspect, such as its size, shape, or color, is changed depending on the magnitude of change in the feature quantity corresponding to the second variable condition (here, working distance). In other words, the display mode of the first object does not need to use a thumbnail image as long as it is determined based on a second variable condition, among multiple variable conditions, that has a smaller feature value of the SEM image than the first variable condition. With this configuration, for example, when identifying variable conditions included in the imaging conditions of a sample using an SEM, it is possible to preferentially identify variable conditions that have a larger feature value of the SEM image. This helps users intuitively understand the relationship between the feature value and the variable conditions based on the position of the object in the visual information. A specific example of the condition identification screen 7 will be described later. At this time, the processor 23 accepts an operation on an object (here, a thumbnail image) in the visual information 8 displayed on the display unit 34.

[0082] Note that a thumbnail image, which is an example of a first object, may be randomly determined based on an arbitrary second variable condition in which the change in the feature quantity is smaller than that of the first variable condition. Alternatively, the thumbnail image may be determined based on the change in the feature quantity related to the second variable condition from among variable conditions other than the first variable condition. In this case, for example, the processor 23 first calculates the average value of a set of feature quantities corresponding to imaging conditions in which the first variable condition and the second variable condition are identical among the imaging conditions belonging to the group Gx corresponding to the first variable condition. This allows obtaining a representative value of the feature quantities for each imaging condition having a specific first variable condition and a specific second variable condition among the imaging conditions belonging to the group Gx. Next, the processor 23 identifies a thumbnail image to be displayed as the first object based on the magnitude of the representative value. For example, the processor 23 identifies the imaging condition corresponding to the median of the representative values ​​of the feature quantities and identifies the SEM image corresponding to the imaging condition as the thumbnail image.

[0083] Next, in step S343, processor 23 specifies a variable condition for analytical imaging based on an operation on an object (here, the specified thumbnail image) in the visual information. For example, when an operation is performed to select a thumbnail image corresponding to group G1, processor 23 specifies a variable condition such that the acceleration voltage for analytical imaging is 1 kV.

[0084] Thereafter, processor 23 repeats the processes from step S341 to step S343 until all variable conditions are identified. For example, if processor 23 identifies an acceleration voltage of 1 kV as the first variable condition, processor 23 performs the same process, substituting Gx in the above description for group G1y and Gxy in the above description for group G1yz. In this manner, processor 23 identifies a variable condition corresponding to an object operated on based on an operation on the object displayed in the visual information, and then, in step S35, identifies a final imaging condition based on the result. In step S4, processor 23 causes SEM 4 to capture an SEM image of sample S under imaging conditions determined based on the identified variable conditions. This configuration allows for preferential identification of variable conditions that have a large contribution to the feature amount, and then imaging by SEM 4 can be performed. Therefore, imaging of sample S can be performed under more appropriate imaging conditions.

[0085] 2.4.1. Condition-specific screens containing visual information Next, an example of the above-mentioned condition identification screen will be described. FIG. 13 is a diagram illustrating an example of the condition identification screen. As illustrated in FIG. 13, the condition identification screen 7 includes visual information 8 corresponding to a first variable condition (in other words, first visual information). In this embodiment, the visual information 8 is configured such that thumbnail images 81 are displayed as objects (first objects) corresponding to the group Gx at positions based on the value and feature of the variable condition corresponding to each group Gx in a two-dimensional graph having the acceleration voltage as the first variable condition on the vertical axis and the feature corresponding to the group Gx on the horizontal axis. In FIG. 13, the thumbnail images 81 are arranged in the visual information 8 as thumbnail images 81a corresponding to the group G1, thumbnail image 81b corresponding to the group G2, and thumbnail image 81c corresponding to the group G3. The visual information 8 may also include a distribution line 82. The distribution line 82 is a line virtually representing the relationship between the acceleration voltage as a variable parameter and the feature as a continuous function. The thumbnail images 81a to 81c as the respective objects are arranged on the distribution line 82.

[0086] 13, when the user performs a predetermined confirmation operation on one of the thumbnail images 81a to 81c, for example, by hovering the mouse cursor MC over one of the thumbnail images 81a to 81c, the processor 23 may display an image group display area 83. The image group display area 83 is an area in which at least one (specifically, all) of the multiple SEM images belonging to the group Gx corresponding to the thumbnail image 81a to 81c for which the confirmation operation has been performed is displayed in a listable manner. With this configuration, it is possible to visually grasp the relationship between the feature amount and the variable condition while comprehensively considering the SEM images other than the thumbnail images.

[0087] Next, a change in the display content of the condition identification screen 7 when a specifying operation for specifying a variable condition in analytical imaging is performed on the visual information 8 will be described. FIG. 14 is a diagram for explaining a change in the display content of the condition identification screen 7 when a specifying operation is performed on the visual information 8 shown in FIG. 13. For convenience of explanation, in FIG. 14, the visual information 8 corresponding to the acceleration voltage shown in FIG. 13 is represented as visual information 8a. The specifying operation may be any operation as long as it can be distinguished from the above-mentioned confirmation operation, and is, for example, an operation of selecting one of the thumbnail images 81a to 81c by clicking with the mouse cursor MC. When a specifying operation is performed, the processor 23 proceeds to step S343 and specifies the variable condition corresponding to the thumbnail image 81 on which the operation was performed as the variable condition in analytical imaging. As a result, the processor 23 identifies thumbnail images corresponding to each of the working distance groups G11-G13, which are second variable conditions subordinate to the group G1 (step S341), and displays the condition identification screen 7 on the display unit 34, including visual information 8b indicating the relationship between the working distance and the feature amount (step S342). Thus, when the first object (e.g., thumbnail images 81a-81c in the visual information 8a) is operated, the display unit 34 displays the second visual information 8b, which is visual information that allows the relationship between the feature amounts of the multiple SEM images and the second variable conditions to be visually recognized. The second visual information is configured so that the relationship between the feature amounts of the multiple SEM images and the second variable conditions can be visually recognized by placing the second object at a corresponding position in the second visual information. With this configuration, after identifying the first variable condition, the user can intuitively grasp the relationship between the feature amount and the second variable condition, which contributes less to the feature amount than the first variable condition. The arrangement of the second object is similar to that of the objects (thumbnail images 81a to 81c) in the visual information 8a described above. The display mode of the second object is determined based on a third variable condition (here, resolution, which is a variable condition corresponding to group G1yz that belongs to group G1y) that is one of the multiple variable conditions. The resolution as the third variable condition is smaller than the working distance as the second variable condition.This configuration allows the user to intuitively grasp the relationship between the variable conditions and the feature quantities, arranging them in order from the first variable condition, the second variable condition, and the third variable condition, from the most significant to the least significant contribution to the feature quantities. In this embodiment, as described above, the second object is represented for each group G1y using thumbnail images 81a to 81c identified based on the SEM images corresponding to each group G1yz belonging to the group G1y. Also, as shown in FIG. 14 , in this embodiment, the display unit 34 updates the first visual information 8a to display the second visual information 8b. This configuration, for example, can prevent the amount of information on the screen from increasing unnecessarily compared to when the visual information 8b is displayed while the visual information 8a remains. This improves user convenience.

[0088] In this way, processor 23 displays visual information 8a corresponding to a higher-level variable condition on display unit 34, and when a specific operation is performed on an object corresponding to a group included in visual information 8, processor 23 identifies a variable condition corresponding to the object on which the specific operation is performed, and displays visual information 8b corresponding to a variable condition at the next level, repeating this process. According to this aspect, the user can gradually narrow down the shooting conditions while utilizing the visual feedback of visual information 8a and 8b, and efficiently identify the final shooting conditions.

[0089] 3. Variations The above embodiment can be implemented by appropriately combining the following aspects, for example.

[0090] For example, the number of attention regions R3 shown in FIG. 7 is not limited to one per imaging region R2, and may be multiple. FIG. 15 is a diagram showing an example of the region setting screen 5 in a case where multiple attention regions R3 can be specified per imaging region R2. As shown in FIG. 15, the specified region 51 in this case may include an item ("Number of attention regions") that allows specification of the number of attention regions R3 for one imaging region R2. For example, if the number of magnetic lenses 43 is set to two, the attention regions R3 displayed in the SEM image region 52 are specified as two different regions for each imaging region R2. When multiple attention regions R3 are specified, the processor 23 may calculate a feature quantity corresponding to the imaging region R2 based on the feature quantities of each of the multiple attention regions R3. For example, the processor 23 may calculate the average value of the feature quantities of each of the multiple attention regions R3 as the feature quantity corresponding to the imaging region R2. In this case, the processor 23 may use the "average value of feature quantities" instead of the feature quantity on the horizontal axis of the visual information 8 shown in FIG. 13, etc.

[0091] The process of skipping imaging for calculating feature quantities in the imaging region R2, included in step S23, is not limited to skipping imaging in the imaging region R2, but may be implemented to skip certain imaging conditions. For example, the processor 23 samples some of the variable conditions among the candidate imaging conditions identified in step S1 at intervals and performs the process of step S23 for the sampled imaging conditions. The processor 23 then calculates feature quantities of the SEM image corresponding to each sampled imaging condition and calculates the change in feature quantities between the sampled variable conditions. If the calculated feature quantities are greater than the default value, the processor 23 then performs further imaging using the SEM for candidate imaging conditions with variable conditions between the two variable conditions. This configuration allows for further reduction in imaging time by skipping imaging conditions.

[0092] Specifically, when candidate imaging conditions are specified such that the variable condition, accelerating voltage, takes five values ​​of 1, 2, 3, 4, and 5 kV, processor 23 samples three of these, accelerating voltages of 1, 3, and 5 kV. Next, processor 23 captures SEM images for each of the accelerating voltages of 1, 3, and 5 kV, and calculates the feature quantities of each SEM image. Thereafter, processor 23 calculates the change in the feature quantities of the SEM images when the accelerating voltage is 1 kV and 3 kV, and when the accelerating voltage is 3 kV and 5 kV, and compares the results with default values. For example, if the former is greater than a predetermined value and the latter is equal to or less than the predetermined value, the processor 23 determines that the change in the feature is large at 2 kV, and takes an additional SEM image for the imaging conditions when the acceleration voltage is 2 kV, but determines that the change in the feature is small at 4 kV and is not significantly different from the cases of 3 kV and 5 kV, and omits taking an SEM image at 4 kV.

[0093] 5 may be executed by different user terminals 3. For example, steps S1 and S2 may be executed by a dedicated terminal for operating the SEM 4, and the data obtained there may be imported into another user terminal 3, thereby executing step S3 on that user terminal 3. Thereafter, the user may import the execution results of the process of step S3 into a dedicated terminal for operating the SEM 4 again, and perform imaging using the SEM 4 in step S4 by operating that dedicated terminal.

[0094] In the above-described embodiment, the information processing device 2, the user terminal 3, and the SEM 4 are identified as separate operating entities, but at least two of them may be integrated into one device. For example, the information processing device 2 and the user terminal 3 may be one device.

[0095] The information processing device 2 may be an on-premise type or a cloud type. As the information processing device 2 in the cloud type, the above-mentioned functions and processes may be provided in the form of, for example, SaaS (Software as a Service) or cloud computing.

[0096] In the above embodiment, the information processing device 2 performs various storage and control operations, but multiple external devices may be used instead of the information processing device 2. That is, various information and programs may be distributed and stored in multiple external devices using block chain technology or the like.

[0097] The above embodiment is not limited to the information processing system 1, and may be an information processing method or an information processing program. The information processing method includes each step of the information processing system 1. The information processing program causes at least one computer to execute each step of the information processing system 1.

[0098] The information processing system 1 and the like may be provided in the following aspects.

[0099] (1) An information processing system comprising at least one processor, the processor configured to execute a program to perform the following steps: an acquisition step acquires imaging conditions for photographing a sample using an SEM, multiple SEM images of the sample photographed based on the imaging conditions, and feature quantities for each of the multiple SEM images, the imaging conditions including multiple variable conditions that are conditions changed when photographing the multiple SEM images; a first display processing step displays first visual information that is visual information that enables visual recognition of the relationship between the feature quantities of the multiple SEM images and a first variable condition that is one of the multiple variable conditions; the first visual information is configured to make the relationship between the feature quantities of the multiple SEM images and the first variable condition visible by placing a first object at a corresponding position within the first visual information; and the display manner of the first object is determined based on a second variable condition among the multiple variable conditions that causes a smaller change in the feature quantities of the SEM images than the first variable condition.

[0100] With this configuration, for example, when identifying variable conditions included in the imaging conditions of a sample using an SEM, it is possible to preferentially identify variable conditions that cause large changes in the feature quantities of the SEM image, and to assist in intuitively grasping the relationship between the feature quantities and the variable conditions based on the position of an object in the visual information.

[0101] (2) In the information processing system described in (1) above, the first object is represented using the SEM image taken under the shooting conditions including the first variable condition of a value corresponding to a corresponding position within the first visual information.

[0102] With this configuration, it is possible to view at a glance the relationships between the feature amounts and the variable conditions relating to SEM images that the user intuitively feels are appropriate.

[0103] (3) In the information processing system described in (1) or (2) above, in the second display processing step, when the first object is operated, second visual information is displayed, which is visual information that makes it possible to visually recognize the relationship between the feature amounts of the multiple SEM images and the second variable condition, and the second visual information is configured so that the relationship between the feature amounts of the multiple SEM images and the second variable condition can be visually recognized by placing a second object at a corresponding position within the second visual information.

[0104] With this configuration, after identifying a first variable condition, it is possible to intuitively grasp the relationship between the first variable condition and the feature amount and a second variable condition that contributes less to the feature amount than the first variable condition.

[0105] (4) In the information processing system described in (3) above, the display mode of the second object is determined based on a third variable condition, which is one of the plurality of variable conditions, and the third variable condition causes a smaller change in the feature quantity of the SEM image than the second variable condition.

[0106] With this configuration, the relationship between the variable conditions and the feature quantity can be intuitively grasped in order from the first variable condition, the second variable condition, and the third variable condition, which contributes most to the feature quantity to the third variable condition.

[0107] (5) In the information processing system described in (3) or (4) above, the second display processing step displays the second visual information by updating the first visual information.

[0108] Such a configuration can improve convenience for the user.

[0109] (6) In the information processing system described in any one of (3) to (5) above, in the identification step, a variable condition corresponding to the operated object displayed in the visual information is identified based on the operation on the object, and in the SEM execution step, an SEM image of the sample is taken under the shooting conditions determined based on the identified variable conditions.

[0110] With this configuration, it is possible to perform SEM imaging after preferentially identifying variable conditions that have a large contribution to the feature amount, thereby enabling the sample to be imaged under more appropriate imaging conditions.

[0111] (7) In the information processing system described in any one of (1) to (6) above, the variable conditions include at least one of the acceleration voltage of the electron beam, the working distance, the resolution, the degree of vacuum, and the integration time.

[0112] (8) In the information processing system described in any one of (1) to (7) above, further, in the SEM image generation step, the plurality of SEM images acquired in the acquisition step are generated by performing SEM image capture for a plurality of predetermined regions of the sample in accordance with an imaging sequence including the imaging conditions, and the imaging sequence is specified so that, after the plurality of regions of the sample are photographed under certain imaging conditions, variable conditions included in the imaging conditions are changed and then SEM images of the plurality of regions of the sample are captured, and in the change step, the variable conditions included in the imaging conditions are changed based on a judgment value calculated from changes in feature amounts between the SEM images obtained according to the imaging sequence, regardless of whether or not the photographing of the plurality of regions of the sample under the immediately preceding imaging conditions has been completed.

[0113] According to this configuration, it is possible to reduce the time required to obtain an SEM image for grasping the relationship between the feature amount and the variable condition.

[0114] (9) In the information processing system described in any one of (1) to (8) above, the system further includes: a specification step of accepting a specification of the shooting conditions for taking an SEM image of the sample, wherein the specification includes a specification regarding the variable conditions; a acquiring step of acquiring SEM images of the sample taken under the shooting conditions based on the specification as the plurality of SEM images; and a condition identifying step of identifying the plurality of variable conditions based on the specification.

[0115] With this configuration, it is possible to easily identify the variable conditions.

[0116] (10) An information processing method, comprising the steps of the information processing system according to any one of (1) to (9) above.

[0117] (11) A program that causes at least one computer to execute each step of the information processing system according to any one of (1) to (9) above. Of course, this is not the case.

[0118] Finally, while various embodiments of the present disclosure have been described, they are presented as examples and are not intended to limit the scope of the invention. The novel embodiments may be embodied in various other forms, and various omissions, substitutions, and modifications may be made without departing from the spirit of the invention. Such embodiments and modifications are intended to be included within the scope and spirit of the invention, as well as within the scope of the inventions and their equivalents as defined in the claims. [Explanation of symbols]

[0119] 1: Information processing system 1: Shooting area number 2: Information processing equipment 3: User terminal 4:SEM 5: Area setting screen 6: Search range setting screen 7: Condition specific screen 8: Visual information 8a: Visual information 8b: Visual information 20: Communication bus 21: Communications Department 22: Storage section 23: Processor 30: Communication bus 31: Communications Department 32: Storage section 33: Processor 34:Display section 35: HMI device 41: Housing 42: Electron gun 43: Magnetic lens 44: Stage 45: Detector 51 :Specified area 52: SEM image area 53: Button 61: Search range setting area 62: Button 81: Thumbnail image 81a: Thumbnail image 81b: Thumbnail image 81c: Thumbnail image 82: Distribution line 83: Image group display area D1: Result data DS: Data Structure IM1: Overall SEM image MC: Mouse cursor R1: Observation area R2: Shooting area R3: Area of ​​interest S: Sample SEM: Overall e1: incident electron e2: Backscattered electron

Claims

1. An information processing system, At least one processor is provided, the processor being configured to execute a program to perform the following steps: In the acquisition step, imaging conditions for photographing a sample using an SEM, a plurality of SEM images of the sample photographed based on the imaging conditions, and feature amounts of each of the plurality of SEM images are acquired; the imaging conditions include a plurality of variable conditions that are conditions that are changed when the plurality of SEM images are captured, In the first display processing step, first visual information is displayed, which is visual information that allows visual recognition of a relationship between feature amounts of the plurality of SEM images and a first variable condition that is one of the plurality of variable conditions; the first visual information is configured so that a relationship between the feature amounts of the plurality of SEM images and the first variable condition can be visually recognized by arranging a first object at a corresponding position in the first visual information; A system in which the display mode of the first object is determined based on a second variable condition among the plurality of variable conditions, the second variable condition causing a smaller change in the feature amount of the SEM image than the first variable condition.

2. 2. The information processing system according to claim 1, The system, wherein the first object is represented using the SEM image taken under the shooting conditions including the first variable condition of a value corresponding to a corresponding position within the first visual information.

3. 2. The information processing system according to claim 1, In the second display processing step, when the first object is operated, second visual information is displayed, the second visual information being visual information that allows a relationship between the feature amounts of the plurality of SEM images and the second variable condition to be visually recognized; The system is configured such that the relationship between the features of the multiple SEM images and the second variable condition is visible by placing a second object at a corresponding position within the second visual information.

4. 4. The information processing system according to claim 3, a display mode of the second object is determined based on a third variable condition that is one of the plurality of variable conditions; The third variable condition causes a smaller change in the feature amount of the SEM image than the second variable condition.

5. 4. The information processing system according to claim 3, In the second display processing step, the second visual information is displayed by updating the first visual information.

6. 4. The information processing system according to claim 3, In the identification step, a variable condition corresponding to an object that has been operated is identified based on an operation on the object displayed in the visual information; In the SEM execution step, the system causes the capture of an SEM image of the sample to be performed under the imaging conditions determined based on the specified variable conditions.

7. 2. The information processing system according to claim 1, The variable conditions include at least one of an accelerating voltage of the electron beam, a working distance, a resolution, a degree of vacuum, and an integration time.

8. 2. The information processing system according to claim 1, Furthermore, in the SEM image generating step, SEM images are captured for a plurality of predetermined regions of the sample in accordance with an imaging sequence including the imaging conditions, thereby generating the plurality of SEM images acquired in the acquiring step; the imaging sequence is defined so that, after imaging a plurality of regions of the sample under certain imaging conditions, a variable condition included in the imaging conditions is changed and then SEM images of the plurality of regions of the sample are acquired; In the change step, the system changes the variable conditions included in the shooting conditions based on a judgment value calculated from the change in feature amounts between the SEM images obtained according to the shooting sequence, regardless of whether or not shooting of multiple areas of the sample under the immediately previous shooting conditions has been completed.

9. 2. The information processing system according to claim 1, Furthermore, in the designation step, designation of the imaging conditions for performing imaging of the SEM image of the sample is accepted, where the designation includes designation regarding the variable conditions; In the acquisition step, SEM images of the sample photographed under the photographing conditions based on the designation are acquired as the plurality of SEM images; In the condition specifying step, the system specifies the plurality of variable conditions based on the specification.

10. An information processing method, comprising: A method comprising the steps of the information processing system according to any one of claims 1 to 9.

11. A program, A program that causes at least one computer to execute each step of the information processing system according to any one of claims 1 to 9.

Images