Probe determination determination method, probe determination determination device, and probe for determination

Abstract

A computer implements: a step (S20) for acquiring an image of a sample generated by measurement by a scanning probe microscope; a step (S30) in which an image of the sample is input to the recognizer and deterioration information indicating whether or not the probe of the scanning probe microscope has deteriorated is acquired; and a step (S50) for outputting the deterioration information. The recognizer is subjected to a learning process using training data so as to output degradation information indicating whether or not the probe of the scanning probe microscope is degraded when an image generated by measurement by the scanning probe microscope is input.

Description

Technical Field

[0001] The present invention relates to a method for determining deterioration of a probe of a scanning probe microscope. Background Art

[0002] A scanning probe microscope (SPM) brings a sufficiently sharpened probe close to the sample being observed, adjusts the probe's height so that the physical quantities acting on the probe's tip and the sample's surface remain constant, and uses the probe to scan the sample's surface horizontally, thereby observing the sample's surface irregularities with high resolution.

[0003] Various approaches have been explored in the past to evaluate probe degradation in SPM. For example, Japanese Patent Application Publication No. 2006-308312 (Patent Document 1) discloses a method for evaluating the tip of a probe using a dedicated sample (reference sample 11). Furthermore, Japanese Patent Application Publication No. 2006-250637 (Patent Document 2) discloses a mechanism (probe length measurement mechanism 62) that uses the difference between the probe's length and its original length to estimate the wear state of the probe.

[0004] Prior art literature

[0005] Patent Literature

[0006] Patent Document 1: Japanese Patent Application Laid-Open No. 2006-308312

[0007] Patent Document 2: Japanese Patent Application Laid-Open No. 2006-250637 Summary of the Invention

[0008] Problems to be solved by the invention

[0009] As mentioned above, conventional techniques require specialized procedures using dedicated samples or mechanisms to evaluate probe degradation. Consequently, unless the user consciously assesses probe degradation, probe degradation cannot be identified. In other words, if the user continues measurements without recognizing probe degradation, even though the probe is degraded, observations using the degraded probe may continue in SPM.

[0010] The present invention has been conceived in view of such actual circumstances, and an object of the present invention is to provide a technique for reliably detecting degradation of a probe in an SPM without requiring the user to be aware of the degradation of the probe.

[0011] Solutions for solving problems

[0012] According to an aspect of the present disclosure, a probe degradation determination method includes the following steps: acquiring an image of a sample generated based on measurement using a scanning probe microscope; inputting the image of the sample into an identifier to acquire degradation information indicating whether the probe of the scanning probe microscope has degraded; and outputting the degradation information, wherein the identifier is subjected to a learning process using training data so as to output degradation information indicating whether the probe of the scanning probe microscope has degraded when the image generated based on measurement using the scanning probe microscope is input.

[0013] A probe degradation determination device according to one aspect of the present disclosure includes: one or more processors; and a storage device storing a program executed by the one or more processors, wherein the program, when executed by the one or more processors, causes the one or more processors to implement the above-described probe degradation determination method.

[0014] The program for determining probe degradation according to one aspect of the present disclosure is executed by one or more processors to cause the one or more processors to implement the above-described method for determining probe degradation.

[0015] Effects of the Invention

[0016] According to a certain aspect of the present disclosure, there is provided a technique for reliably detecting degradation of a probe in an SPM without requiring a user to be aware of the degradation of the probe. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a schematic configuration diagram of one embodiment of a measurement system including a scanning probe microscope.

[0018] Figure 2 FIG. 1 is a diagram showing an example of a cantilever 113A for contact mode.

[0019] Figure 3 This is a diagram showing an example of the cantilever 113B for the dynamic mode.

[0020] Figure 4 This is a diagram showing an image of an example of the pyramid-shaped probe 114 .

[0021] Figure 5 This is a diagram showing an image of an example of the conical probe 114 .

[0022] Figure 6 FIG. 1 is a diagram showing an image of an example of the tetrahedral probe 114 .

[0023] Figure 7 The diagram shows an example of each state of the probe at the beginning of use and after a certain period of use.

[0024] Figure 8It is a diagram for explaining how the pyramid-shaped probe 114 wears out.

[0025] Figure 9 This is a diagram for explaining how the tetrahedral probe 114 wears out.

[0026] Figure 10 FIG. 1 is a diagram showing an example of an image acquired using the probe 114 in a non-degraded state.

[0027] Figure 11 FIG. 1 is a diagram showing another example of an image acquired using the probe 114 in a non-degraded state.

[0028] Figure 12 This is a diagram showing another example of an image acquired using the probe 114 in a non-degraded state.

[0029] Figure 13 This is a diagram showing an example of an image acquired using the probe 114 in a degraded state.

[0030] Figure 14 This is a diagram showing an example of an image acquired using the probe 114 in a degraded state.

[0031] Figure 15 This is a diagram showing an example of an image acquired using the probe 114 in a degraded state.

[0032] Figure 16 This is a diagram showing an example of an image acquired using the probe 114 in a degraded state.

[0033] Figure 17 This is a diagram showing an example of an image acquired using the probe 114 in a degraded state.

[0034] Figure 18 This is a diagram showing an example of an image acquired using the probe 114 in a degraded state.

[0035] Figure 19 This is a diagram showing an example of an image acquired using the probe 114 in a degraded state.

[0036] Figure 20 This is a diagram showing an example of an image acquired using the probe 114 in a degraded state.

[0037] Figure 21 This is a flowchart of processing performed to determine probe degradation on an image generated by the scanning probe microscope 1 .

[0038] Figure 22 This is a diagram showing an example of an output screen.

[0039] Figure 23 This is a diagram showing another example of the output screen.

[0040] Figure 24 This is a diagram showing another example of the output screen. DETAILED DESCRIPTION

[0041] The embodiments of the present invention will be described in detail with reference to the accompanying drawings. The same or corresponding parts in the drawings are denoted by the same reference numerals and their description will not be repeated.

[0042] [General structure of the measurement system]

[0043] Figure 1 This is a schematic structural diagram of an embodiment of a measurement system including a scanning probe microscope. The measurement system includes a scanning probe microscope 1 and a computer 50. An example of a scanning probe microscope 1 is an atomic force microscope. In addition, the scanning probe microscope may also be another type of scanning probe microscope (for example, a scanning tunneling microscope). The scanning probe microscope 1 is configured to be able to communicate with the computer 50. The computer 50 includes an input device 91 (keyboard, mouse, etc.) and an output device 92 (display, speaker, etc.). The user uses the input device 91 to input information to the computer 50, and the computer 50 outputs the calculation results via the output device 92.

[0044] [Scanning probe microscope 1]

[0045] like Figure 1 As shown, the scanning probe microscope 1 includes: a sample stage 112, which is used to carry a sample 110; a piezoelectric scanner 111, which is used to displace the sample stage; a cantilever 113, which has a probe 114 formed at the front end; a displacement detection mechanism 120, which detects the displacement of the cantilever 113; a controller 130; a feedback signal generating unit 131; and a scanning signal generating unit 133.

[0046] The piezoelectric scanner 111 includes a Z scanner 111 z that generates displacement in the Z direction based on a voltage value Vz, and an XY scanner 111 xy that generates displacement in the XY directions based on voltage values Vx and Vy.

[0047] The displacement detection mechanism 120 includes a laser diode 115 and a photodetector 119. In the scanning probe microscope 1, when the tip of the probe 114 is brought close to the sample 110 for surface observation, laser light emitted from the laser diode 115 is reflected by the back surface of the cantilever 113, and the reflected light is received by the photodetector 119. When the probe 114 is brought close to the surface of the sample 110, the cantilever 113 deflects like a leaf spring, and the amount of deflection is observed at the light-receiving position of the photodetector 119.

[0048] The feedback signal generator 131 receives the detection signal from the photodetector 119. Based on the detection signal, the feedback signal generator 131 calculates the deflection of the cantilever 113. The feedback signal generator 131 controls the Z-direction position of the sample 110 so that the atomic force between the probe 114 and the surface of the sample 110 remains constant. Based on the deflection of the cantilever 113, the feedback signal generator 131 calculates a voltage value Vz for displacing the piezoelectric scanner 111 in the Z-axis direction and outputs this voltage value Vz to the Z scanner 111z.

[0049] The scanning signal generator 133 calculates the voltage value Vx in the X-axis direction and the voltage value Vy in the Y-axis direction so that the sample 110 moves relative to the probe 114 in the XY plane according to a predetermined scanning pattern, and outputs the voltage values Vx and Vy to the XY scanner 111xy.

[0050] A signal reflecting the feedback amount in the Z-axis direction (voltage Vz applied to the scanner and deviation signal Sd) is also sent to the controller 130. The signal is stored in a storage device within the controller 130 and is sent to the computer 50.

[0051] Based on information representing the relationship between voltage Vz and the corresponding surface displacement amount due to the unevenness of sample 110, stored in a storage device within controller 130, controller 130 calculates the surface displacement amount of sample 110 from voltage Vz. Controller 130 calculates the displacement amount for each position in the X-axis and Y-axis directions to reconstruct a three-dimensional image of the sample surface and transmits this three-dimensional image to computer 50. The data for this three-dimensional image is also stored in the storage device within controller 130. Controller 130 can perform height correction on the three-dimensional image data as needed.

[0052] [Computer 50]

[0053] The computer 50 includes a processor 10 and a storage device 20. The processor 10 may be composed of one or more central processing units (CPUs).

[0054] The storage device 20 stores various data in a non-volatile (non-temporary) manner. Figure 1 In the example of , the storage device 20 stores training data 21 , measurement data 22 , a learning program 23 , a determination program 24 , an estimation model 25 , and various data 26 .

[0055] The computer 50 functions as a probe degradation determination device that determines whether the probe 114 has degraded. In this case, the processor 10 inputs a three-dimensional image generated by the scanning probe microscope 1 to the estimation model 25 to obtain a result of determining whether the probe 114 used in the measurement of the three-dimensional image has degraded. In one implementation example, the estimation model 25 obtains one or more types of feature quantities from the input image and derives a recognition result for the input image based on the one or more types of feature quantities.

[0056] The training data 21 is a data set used in the machine learning of the estimation model 25. The data constituting the data set is generated by labeling the images generated by the scanning probe microscope with the correct results (information indicating whether the probe is degraded). In one implementation example, the labeling is performed by the user who observes each image. More specifically, the user determines whether the image was acquired with the probe degraded and labels the image according to the result of this determination. The training data 21 may include only images generated by the scanning probe microscope 1 or images generated by other scanning probe microscopes.

[0057] The measurement data 22 is an image generated based on the measurement of the scanning probe microscope 1 and is an object of determination of deterioration of the probe 114 .

[0058] The learning program 23 is a program for performing training of the estimation model 25 using the training data 21. In one implementation example, the processor 10 executes the learning program 23 to perform machine learning of the estimation model 25.

[0059] The determination program 24 is a program for determining degradation of the probe 114 using the measurement data 22. In one implementation example, the processor 10 executes the determination program 24 to input the measurement data 22 into the estimation model 25 to obtain degradation information indicating whether the probe 114 has degraded.

[0060] The estimation model 25 includes data (e.g., model parameters) used to construct the identifier. The identifier implemented by the estimation model 25 is not limited to any type, as long as it is a model that, when fed an image generated by a measurement using the scanning probe microscope 1, outputs degradation information indicating whether the probe 114 used to generate the image has degraded. It can be a classification model such as a support vector machine (SVM) or a model constructed using a neural network. The degradation information can be information indicating the class into which the image has been classified (degraded or non-degraded), or information indicating the degree of degradation (such as no degradation, slight degradation, or significant degradation).

[0061] The various data 26 are data other than those described above, and include data (settings, programs, etc.) for the computer 50 to realize the functions described in this specification.

[0062] According to the above, the processor 10 executes the learning program 23, thereby implementing the training of the estimation model 25 using the training data 21. The training data 21 may also be labeled with the label of the measurement mode of the scanning probe microscope when the image was generated. The measurement mode is, for example, a reference Figure 2 and Figure 3 In the contact mode or dynamic mode described later, the accuracy of the output degradation information is expected to be improved by utilizing the measurement mode in the output of degradation information. In this case, it is preferable to also assign the measurement mode of the scanning probe microscope 1 to the measurement data 22.

[0063] The training data 21 may also be labeled with the type of probe used in the scanning probe microscope when the image was generated. The type of probe 114 is, for example, Figures 4 to 6 The pyramidal, conical, or tetrahedral types described below are used. By utilizing the probe type in outputting degradation information, it is expected that the accuracy of the output degradation information will be improved. In this case, it is preferable to also assign the type of probe 114 used in the scanning probe microscope 1 to the measurement data 22.

[0064] The training data 21 may be labeled with both the above-mentioned measurement mode and probe type. In this case, it is preferable to also assign both the measurement mode in the scanning probe microscope 1 and the type of the probe 114 to the measurement data 22.

[0065] [Measurement Mode]

[0066] The measurement mode in the scanning probe microscope 1 will be described.

[0067] An example of a measurement mode is a contact mode, which is a mode for detecting static atomic force based on the warping state of the cantilever 113 .

[0068] Figure 2 FIG. 1 is a diagram showing an example of a cantilever 113A for contact mode. The material of the cantilever 113A is, for example, silicon nitride. Figure 2 In the example shown in FIG. 1 , the cantilever 113A includes a probe 114A, the thickness indicated by D11 is approximately 1 μm, and the length indicated by D12 is approximately 200 μm.

[0069] Another example of a measurement mode is the dynamic mode. In the dynamic mode, excitation is applied to the cantilever 113 in the longitudinal direction (the direction in which the cantilever 113 and the sample 110 face each other). The excitation causes the cantilever 113 to vibrate near the resonant frequency. In this state, the amplitude changes as the probe 114 approaches the sample. In the dynamic mode, this phenomenon is exploited to generate surface observation results for the sample based on the control variable in the feedback control used to maintain a constant amplitude of the vibration of the cantilever 113.

[0070] Figure 3 1 is a diagram showing an example of a cantilever 113B for dynamic mode. The material of the cantilever 113B is, for example, silicon. Figure 3 In the example shown in FIG. 1 , the cantilever 113B includes a probe 114B, has a thickness indicated by D21 of approximately 5 μm, and has a length indicated by D22 of approximately 100 μm.

[0071] [Type of probe]

[0072] The probe 114 used in the scanning probe microscope 1 can be classified according to its shape.

[0073] An example of the type of the probe 114 is a pyramid type. Figure 4 1 is a diagram showing an example of an image of a pyramid-shaped probe 114. Figure 4 In the image IM11, the tip of the probe 114 is located at the top. As shown in the image IM11, an example of the probe 114 has a pyramid shape.

[0074] Another example of the type of probe 114 is a conical type. Figure 5 : is a diagram showing an image of an example of a conical probe 114. Figure 5 In the image IM12, the tip of the probe 114 is located upward. As shown in the image IM12, an example of the probe 114 has a conical shape.

[0075] Another example of the type of probe 114 is a tetrahedron type. Figure 6 : is a diagram showing an image of an example of a tetrahedral probe 114. Figure 6 In the image IM13, the tip of the probe 114 is located upward. As shown in the image IM13, an example of the probe 114 has a tetrahedral shape.

[0076] [Deterioration of the probe]

[0077] Figure 7 This is a diagram showing an example of the probe in each state at the beginning of use and after a certain period of use. Figure 7In the figure, image IM21 is shown as an example of the state at the beginning of use, and image IM22 is shown as an example of the state after 65 hours of measurement (scanning). In both images IM21 and IM22, the tip of probe 114 is positioned upward. By comparing images IM21 and IM22, it can be understood that the tip of probe 114 has worn due to use.

[0078] Figure 8 It is a diagram for explaining how the pyramid-shaped probe 114 wears out. Figure 9 This is a diagram for explaining how the tetrahedral probe 114 wears out.

[0079] exist Figure 8 and Figure 9 In both cases, the front end of the probe 114 is located at the bottom. Figure 8 As shown, the tip of the probe 114 changes from point PT31 to plane PL31 due to wear. Figure 8 The type of the probe 114 is a pyramid type, so the shape of the surface PL31 is a quadrilateral. Figure 9 As shown, the tip of the probe 114 changes from point PT32 to plane PL32 due to wear. Figure 9 The probe 114 is a tetrahedron, so the shape of the surface PL32 is a triangle. That is, when the type of the probe 114 is different, the shape of the tip after the change due to wear may be different.

[0080] Furthermore, "wear" is an example of deterioration of the probe 114. The deterioration of the probe 114 may occur as a phenomenon other than wear, such as cracking at the tip of the probe 114, such as a so-called double tip.

[0081] [Specific example of an image acquired using a probe that has not degraded]

[0082] Figure 10 FIG. 1 is a diagram showing an example of an image acquired using the probe 114 in a non-degraded state. Figure 10 Image IM31 shows the observation results of a 1.00 μm square on the sapphire substrate surface. The height is 3.48 nm. As shown in image IM31, atomic steps on the sapphire substrate surface are clearly observed in the measurement results.

[0083] Figure 11 FIG. 1 is a diagram showing another example of an image acquired using the probe 114 in a non-degraded state. Figure 11Image IM32 shows the observation results of a 5.00 μm square on the surface of a lithium ion battery (separator). The height is 678.4 nm. As shown in image IM32, pores were observed on the surface of the lithium ion battery in the measurement results.

[0084] Figure 12 This is a diagram showing another example of an image acquired using the probe 114 in a non-degraded state. Figure 12 Image IM33 shows the observation results of a 5.49 μm square of Vibrio cholerae (unstained). The height is 232.39 nm. As shown in image IM33, the measurement results clearly show the curved cells unique to Vibrio cholerae and a flagellum at one end of the cell.

[0085] [Specific example of an image acquired using a degraded probe]

[0086] Figures 13 to 20 The figures in FIG. 1 are diagrams showing examples of images acquired using the probe 114 in a degraded state.

[0087] Figure 13 Image IM41 represents a 2.00 μm square area. Figure 14 Image IM42 represents a 1.00 μm square area. Figure 15 Image IM43 shows a 2.50 μm square area. Figure 16 Image IM44 shows a 3.00 μm square region. In each of images IM41 to IM44, objects representing the cross-sectional shape of the distal end of probe 114 appear entirely repeatedly. For example, in image IM41, quadrilateral objects appear entirely repeatedly, while in images IM42 and IM43, triangular objects appear entirely repeatedly.

[0088] Figure 17 Image IM45 represents a 3.00 μm square area. Figure 18 Image IM46 shows a 1.25 μm square area. Figure 19 Images of IM47 and Figure 20 Each image in the image IM48 represents a 2.00 μm square area. In each of the images IM45 to IM48, an object of a given shape appears repeatedly as a whole. For example, in Figure 17 In the image IM45, Figure 17 The objects shown enlarged in each of the images IM451, IM452, and IM453 are repeated as a whole. Figure 19 In the image IM47, Figure 19 The object shown enlarged in image IM471 is repeated in its entirety. Figure 20 In the image IM48, Figure 20 The objects shown enlarged in each of images IM481 and IM482 appear repeatedly as a whole.

[0089] According to the above, when the probe deteriorates, the same object reappears in the entire image. However, the shape of the recurring object is not constant, and the manner of repetition is also not constant. Therefore, although an experienced user may notice the recurrence of the object and think of the deterioration of the probe, an inexperienced user may ignore the recurrence of the object and not think of the deterioration of the probe. Due to various reasons, including the fact that the shape and / or manner of the recurring object is not constant, in the determination of probe degradation using the acquired image, it is preferable to use a determination using a recognizer that has been subjected to machine learning, rather than a determination using a rule determined in advance regarding degradation (rule-based determination).

[0090] [Processing Flow]

[0091] Figure 21 This is a flowchart of a process performed to determine probe degradation based on an image generated by the scanning probe microscope 1. In one embodiment, the processor 10 executes the determination program 24, thereby performing a process in the computer 50. Figure 21 In one embodiment, the computer 50 starts to process the measurement in response to the input device 91 inputting the measurement instruction. Figure 21 processing.

[0092] like Figure 21 As shown, in step S10, the computer 50 instructs the scanning probe microscope 1 to start measuring the sample 110. In response, the scanning probe microscope 1 generates an image of the sample 110 and transmits the generated image (measurement data 22) to the computer 50.

[0093] In step S20 , the computer 50 acquires (receives) the image generated as described above from the scanning probe microscope 1 .

[0094] In step S30 , the computer 50 acquires degradation information based on the image acquired in step S20 . More specifically, the computer 50 inputs the image into the estimation model 25 , and generates degradation information using the output from the estimation model 25 .

[0095] In step S40 , the computer 50 generates an output screen using the image acquired in step S20 and the degradation information acquired in step S30 .

[0096] In step S50, the computer 50 displays the image generated in step S40 on the output device 92. After that, the computer 50 ends Figure 21 processing.

[0097] Figure 22 This is a diagram showing an example of an output screen. Figure 22 The output screen 200 shown includes frames 210 and 220. Figure 22 In the example of , the measurement result is displayed in frame 210. The degradation information is displayed in frame 220. Figure 22 In the example shown in FIG, the degradation information indicates that the probe 114 has not degraded. Therefore, a message “No problem” is displayed in the frame 220 as the probe information.

[0098] Figure 23 This is a diagram showing another example of the output screen. Figure 23 The output screen 201 shown is Figure 22 The output screen 200 also includes frames 210 and 220. Figure 23 In the example shown in FIG. 2 , the deterioration information indicates that the probe 114 has deteriorated. Therefore, a message “Possible deterioration - Please consider replacement” is displayed in the frame 220 as the probe information.

[0099] Figure 24 This is a diagram showing another example of the output screen. Figure 24 The output screen 202 shown is Figure 22 The output screen 200 also includes frames 210 and 220. Figure 24 In the example shown in FIG, the degradation information indicates that the probe 114 has degraded. Therefore, a message “Possibility of degradation exists—Please consider expanding the observation field” is displayed in the frame 220 as the probe information.

[0100] In the present embodiment described above, the image obtained as a result of the measurement of the sample 110 in the scanning probe microscope 1 is used to generate degradation information of the probe 114 used in the measurement and output the degradation information. The output method of the degradation information is not limited to the reference Figures 22 to 24 The deterioration information may be output by lighting a predetermined lamp, outputting a sound, or a combination thereof.

[0101] The degradation information may indicate not whether degradation has occurred but the degree of degradation (such as no degradation, slight degradation, or significant degradation).

[0102] Degradation information is generated using the estimation model 25. Thus, even if the factors (such as the type of feature amount) that affect the degree of degradation of the probe 114 are unclear in the image, degradation information can be generated using the image.

[0103] When the degradation information indicates that the probe 114 has degraded, the Figure 23 The replacement of the probe 114 may be prompted as described, or as described with reference to Figure 24 In the latter case, the user can measure the same sample 110 again in a state where the observation field is enlarged in the scanning probe microscope 1 .

[0104] The image acquired from the scanning probe microscope 1 in step S20 may be supplemented with information indicating the measurement mode used in the scanning probe microscope 1, information indicating the type of probe used in the scanning probe microscope 1, observation conditions (e.g., information specifying the dimensions of the observation field in two directions), or two or more types of information arbitrarily selected from these three types. When the estimation model 25 is trained using training data 21 supplemented with such information, the degradation information generated using the output of the estimation model 25 reflects the measurement mode and / or probe type applied to the acquired image, thereby improving the accuracy of the degradation degree obtained as a determination result.

[0105] The images used as training data 21 and measurement data 22 preferably have a relatively large number of pixels. In one embodiment, the number of pixels in both the first direction (e.g., horizontal direction) and the second direction (e.g., vertical direction) is preferably 64 or more, more preferably 128 or more, and even more preferably 256 or more.

[0106] As reference Figures 22 to 24 As described above, when outputting the sample measurement results, the degradation information is preferably output on the same screen as the measurement results. This allows the user to obtain information on the degradation of the probe 114 even if the user is unaware of the degradation of the probe 114 while measuring the sample using the scanning probe microscope 1.

[0107] In the embodiment described above, the computer 50 is described as an external device relative to the scanning probe microscope 1. Alternatively, the computer 50 may be implemented as a part of the scanning probe microscope 1. Furthermore, the computer 50 may be implemented as a single information processing device or as a plurality of coordinated information processing devices.

[0108] [Way]

[0109] It will be understood by those skilled in the art that the above-described multiple exemplary embodiments are specific examples of the following aspects.

[0110] (Item 1) A method for determining probe degradation according to one embodiment may include the following steps: obtaining an image of a sample generated based on measurement using a scanning probe microscope; inputting the image of the sample into an identifier to obtain degradation information indicating whether the probe of the scanning probe microscope has degraded; and outputting the degradation information, wherein the identifier is subjected to a learning process using training data so as to output degradation information indicating whether the probe of the scanning probe microscope has degraded when the image generated based on measurement using the scanning probe microscope is input.

[0111] According to the probe deterioration determination method described in the first item, a technique for reliably detecting degradation of a probe in an SPM without requiring the user to be aware of the degradation of the probe is provided.

[0112] (Item 2) In the probe degradation determination method described in Item 1, the step of outputting the degradation information may include the following processing: when the degradation information indicates that the probe has deteriorated, outputting information recommending replacement of the probe and / or information recommending enlarging the observation field of view in the measurement of the scanning probe microscope.

[0113] According to the probe degradation determination method described in the second aspect, in addition to the degradation information, information corresponding to the degradation information and serving as a reference for specific measures is provided to the user.

[0114] (Item 3) In the probe degradation determination method described in Item 1 or Item 2, the identifier may be subjected to a learning process using training data so that when an image generated based on the measurement of the scanning probe microscope is input in association with a measurement pattern of the scanning probe microscope, degradation information indicating whether the probe of the scanning probe microscope is degraded is output, and the step of acquiring the image of the sample includes the following processing: acquiring the measurement pattern of the scanning probe microscope associated with the image of the sample.

[0115] According to the probe degradation determination method described in the third aspect, the accuracy of degradation information is improved.

[0116] (Item 4) In the probe degradation determination method described in any one of Items 1 to 3, the identifier may be subjected to a learning process using training data so that when an image generated based on a measurement of the scanning probe microscope is input in association with the type of the probe of the scanning probe microscope, degradation information indicating whether the probe of the scanning probe microscope is degraded is output, and the step of obtaining the image of the sample includes the following processing: obtaining the type of the probe of the scanning probe microscope associated with the image of the sample.

[0117] According to the probe degradation determination method described in the fourth aspect, the accuracy of degradation information is improved.

[0118] (Item 5) In the probe deterioration determination method described in any one of Items 1 to 4, the image acquired in the step of acquiring the image of the sample may have 64 or more pixels in each of the first direction and the second direction.

[0119] According to the probe degradation determination method described in the fifth aspect, the accuracy of degradation information is improved.

[0120] (Item 6) In the probe degradation determination method according to any one of Items 1 to 5, the step of outputting the degradation information may include a process of outputting a screen displaying the measurement result together with the degradation information.

[0121] According to the probe deterioration determination method described in the sixth aspect, information on probe deterioration is provided to a user who only wants to obtain the measurement result of the sample in addition to the measurement result, thereby enabling the user to reliably become aware of the probe deterioration.

[0122] (Item 7) A probe degradation determination device according to one embodiment may be a probe degradation determination device comprising: one or more processors; and a storage device storing a program executed by the one or more processors, wherein the program is executed by the one or more processors to enable the one or more processors to implement the probe degradation determination method according to any one of items 1 to 6.

[0123] According to the probe degradation determination device described in the seventh aspect, a technique for reliably detecting degradation of the probe in the SPM without requiring the user to be aware of the degradation of the probe is provided.

[0124] (Item 8) The program for determining probe degradation according to one aspect may be executed by one or more processors to cause the one or more processors to implement the probe degradation determination method according to any one of Items 1 to 6.

[0125] According to the program for determining probe degradation according to the eighth aspect, a technique for reliably detecting degradation of a probe in an SPM without requiring the user to be aware of the degradation of the probe is provided.

[0126] The embodiments disclosed herein should be considered in all respects to be illustrative and non-restrictive. The scope of this disclosure is not indicated by the description of the embodiments described above, but rather by the claims, and is intended to encompass all modifications within the meaning and scope equivalent to the claims. Furthermore, it is intended that each technique in the embodiments be capable of being implemented independently or, as needed, in combination with other techniques in the embodiments to the greatest extent possible.

[0127] Description of Reference Numerals

[0128] 1: scanning probe microscope; 10: processor; 20: storage device; 25: estimation model; 50: computer; 91: input device; 92: output device; 110: sample; 111: piezoelectric scanner; 111xy: XY scanner; 111z: Z scanner; 112: sample stage; 113: cantilever; 114: probe; 115: laser diode; 119: photodetector; 120: displacement detection mechanism; 130: controller; 131: feedback signal generating unit; 133: scanning signal generating unit.

Claims

1. A method for determining probe degradation, comprising the following steps: Acquiring an image of a sample generated based on measurement using a scanning probe microscope; inputting the image of the sample into an identifier to obtain degradation information indicating whether a probe of the scanning probe microscope has deteriorated; as well as outputting the degradation information, The identifier is subjected to a learning process using training data so as to output degradation information indicating whether the probe of the scanning probe microscope has degraded when an image generated based on measurement by the scanning probe microscope is input.

2. The probe degradation determination method according to claim 1, wherein: The step of outputting the degradation information includes the following processing: When the degradation information indicates that the probe has deteriorated, information recommending replacement of the probe and / or information recommending enlargement of the observation field during measurement using the scanning probe microscope is output.

3. The probe degradation determination method according to claim 1 or 2, wherein: The identifier is subjected to a learning process using training data so that, when an image generated based on measurement by the scanning probe microscope is input in association with a measurement mode of the scanning probe microscope, the identifier outputs degradation information indicating whether the probe of the scanning probe microscope has deteriorated. The step of acquiring the image of the sample includes a process of acquiring a measurement mode of the scanning probe microscope associated with the image of the sample.

4. The probe degradation determination method according to claim 1 or 2, wherein: The identifier is subjected to a learning process using training data so that, when an image generated based on measurement of the scanning probe microscope is input in association with the type of the probe of the scanning probe microscope, the identifier outputs degradation information indicating whether the probe of the scanning probe microscope has deteriorated. The step of acquiring the image of the sample includes a process of acquiring the type of the probe of the scanning probe microscope associated with the image of the sample.

5. The probe degradation determination method according to claim 1 or 2, wherein: The image acquired in the step of acquiring the image of the sample has 64 or more pixels in each of the first direction and the second direction.

6. The probe degradation determination method according to claim 1 or 2, wherein: The step of outputting the degradation information includes a process of outputting a screen displaying the measurement result together with the degradation information.

7. A probe degradation determination device comprising: More than one processor; and a storage device storing a program executed by the one or more processors, in, The program, when executed by the one or more processors, causes the one or more processors to implement the probe deterioration determination method according to claim 1 or 2. 8 . A program for determining probe degradation, which, when executed by one or more processors, causes the one or more processors to implement the probe degradation determination method according to claim 1 or 2 .

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