Probe degradation determination method, probe degradation determination device, および, probe degradation determination prolog

Abstract

In the present invention, a computer performs: a step (S20) for acquiring a sample image which is generated on the basis of the measurement of a scanning probe microscope; a step (S30) for acquiring, by inputting the sample image to a discriminator, deterioration information indicating whether or not a probe of the scanning probe microscope has deteriorated; and a step (S50) for outputting the deterioration information. The discriminator has undergone a learning process by using teacher data so as to output, when receiving input of the image generated on the basis of the measurement of the scanning probe microscope, the deterioration information indicating whether or not the probe of the scanning probe microscope has deteriorated.

Description

[Technical Field]

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

[0002] A scanning probe microscope (SPM) observes irregularities of a sample surface with high resolution by bringing a sufficiently sharpened probe sufficiently close to a sample to be observed, and horizontally scanning the sample surface with the probe while vertically adjusting the height of the probe such that a physical quantity acting between the tip of the probe and the sample surface becomes constant.

[0003] Conventionally, various studies have been conducted on evaluation of probe deterioration in SPM. For example, Japanese Unexamined Patent Application Publication No. 2006-308312 (Patent Document 1) discloses a method for evaluating a probe tip using a dedicated sample (reference sample 11). Further, Japanese Unexamined Patent Application Publication No. 2006-250637 (Patent Document 2) discloses a mechanism (probe length measurement mechanism 62) that estimates the wear state of a probe using the difference between the length of the probe and the length of the probe when it is new. [Prior Art Literature] [Patent Literature]

[0004] [Patent Document 1] Japanese Unexamined Patent Application Publication No. 2006-308312 [Patent Document 2] Japanese Unexamined Patent Application Publication No. 2006-250637 [Summary of the Invention] [Problem to be Solved by the Invention]

[0005] As mentioned above, conventional techniques required special procedures using dedicated samples or mechanisms to evaluate probe degradation. Therefore, users could not recognize probe degradation unless they consciously evaluated it. In other words, even if a probe was degraded, if the user continued measurements without being aware of the degradation, there was a risk that observations using a degraded probe would continue in SPM.

[0006] This invention was conceived in view of the circumstances described herein, and its purpose is to provide a technology for reliably detecting probe deterioration in SPM without requiring the user to be aware of probe deterioration. [Means for solving the problem]

[0007] A probe degradation determination method according to a certain aspect of the present disclosure comprises the steps of: acquiring an image of a sample generated based on a measurement with a scanning probe microscope; inputting the image of the sample to a classifier and acquiring degradation information indicating whether or not the probe of the scanning probe microscope is degraded; and outputting the degradation information. The classifier is subjected to training processing 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 based on a measurement with a scanning probe microscope is input.

[0008] A probe degradation determination device according to a certain aspect of this disclosure comprises one or more processors and a storage device that stores a program executed by the one or more processors, wherein the program is executed by the one or more processors to cause the one or more processors to perform the probe degradation determination method described above.

[0009] A probe degradation determination program according to a certain aspect of this disclosure is executed by one or more processors, thereby causing one or more processors to perform the probe degradation determination method described above. [Effects of the Invention]

[0010] In accordance with certain aspects of this disclosure, a technology is provided for more reliably detecting probe degradation in SPM without requiring the user to be aware of probe degradation. [Brief explanation of the drawing]

[0011] [Figure 1] This is a schematic diagram of one embodiment of a measurement system including a scanning probe microscope. [Figure 2] This figure shows an example of a cantilever 113A for contact mode. [Figure 3] This figure shows an example of a cantilever 113B for dynamic mode. [Figure 4] This figure shows an example image of a pyramidal probe 114. [Figure 5] This figure shows an example image of a conical probe 114. [Figure 6] This figure shows an example image of a tetrahedral-type probe 114. [Figure 7] This figure shows examples of the probe's state at the start of use and after a certain period of use. [Figure 8] This is a diagram illustrating the wear pattern of the pyramidal probe 114. [Figure 9] This is a diagram illustrating the wear pattern of the tetrahedral-type probe 114. [Figure 10] This figure shows an example of an image acquired using the probe 114 in an undegraded state. [Figure 11] This figure shows another example of an image acquired using the probe 114 in an undegraded state. [Figure 12] This figure shows yet another example of an image acquired using the probe 114 in an undegraded state. [Figure 13] This figure shows an example of an image acquired using a deteriorated probe 114. [Figure 14] This figure shows an example of an image acquired using a deteriorated probe 114. [Figure 15]FIG. 1 is a diagram showing an example of an image acquired using a deteriorated probe 114. [Figure 16] FIG. 2 is a diagram showing an example of an image acquired using a deteriorated probe 114. [Figure 17] FIG. 3 is a diagram showing an example of an image acquired using a deteriorated probe 114. [Figure 18] FIG. 4 is a diagram showing an example of an image acquired using a deteriorated probe 114. [Figure 19] FIG. 5 is a diagram showing an example of an image acquired using a deteriorated probe 114. [Figure 20] FIG. 6 is a diagram showing an example of an image acquired using a deteriorated probe 114. [Figure 21] FIG. 7 is a flowchart illustrating processing executed for probe deterioration determination on an image generated by a scanning probe microscope 1. [Figure 22] FIG. 8 is a diagram showing an example of an output screen. [Figure 23] FIG. 9 is a diagram showing another example of an output screen. [Figure 24] FIG. 10 is a diagram showing still another example of an output screen. MODE FOR CARRYING OUT THE INVENTION

[0012] Embodiments of the present invention will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference symbols, and description thereof will not be repeated.

[0013] [Schematic Configuration of Measurement System] Figure 1 is a schematic diagram of one 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 the scanning probe microscope 1 is an atomic force microscope. The scanning probe microscope may be other types of scanning probe microscopes (e.g., a scanning tunneling microscope). The scanning probe microscope 1 is configured 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 inputs information to the computer 50 using the input device 91, and the computer 50 outputs the calculation results via the output device 92.

[0014] [Scanning probe microscope 1] As shown in Figure 1, the scanning probe microscope 1 includes a sample stage 112 on which a sample 110 is placed, a piezo scanner 111 that displaces the sample stage, a cantilever 113 with a probe 114 formed at its tip, a displacement detection mechanism 120 that detects the displacement of the cantilever 113, a controller 130, a feedback signal generation unit 131, and a scanning signal generation unit 133.

[0015] The piezo scanner 111 includes a Z scanner 111z that generates displacement in the Z direction based on a voltage value Vz, and an XY scanner 111xy that generates displacement in the XY direction based on voltage values ​​Vx and Vy.

[0016] 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, the laser light emitted from the laser diode 115 is reflected off the back surface of the cantilever 113, and the reflected light is received by the photodetector 119. As the probe 114 is brought closer to the surface of the sample 110, the cantilever 113 bends like a leaf spring, and the amount of bending is observed at the receiving position of the photodetector 119.

[0017] The feedback signal generator 131 receives a detection signal from the photodetector 119. Based on the detection signal, the feedback signal generator 131 calculates the amount of deflection of the cantilever 113. The feedback signal generator 131 controls the Z-direction position of the sample so that the interatomic force between the probe 114 and the surface of the sample 110 remains constant. Based on the amount of deflection of the cantilever 113, the feedback signal generator 131 calculates a voltage value Vz that displaces the piezo scanner 111 in the Z-axis direction and outputs it to the Z scanner 111z.

[0018] The scanning signal generation unit 133 calculates voltage values ​​Vx and Vy in the X and Y directions according to a predetermined scanning pattern so that the sample 110 moves relative to the probe 114 in the XY plane, and outputs them to the XY scanner 111xy.

[0019] A signal reflecting the Z-axis feedback amount (the voltage Vz applied to the scanner and the deviation signal Sd) is also sent to the controller 130. The signal is stored in a memory device within the controller 130 and also transmitted to the computer 50.

[0020] The controller 130 calculates the amount of surface displacement due to the unevenness of the sample 110 from the voltage Vz, based on correlation information showing the relationship between the voltage Vz stored in the memory device within the controller 130 and the corresponding amount of surface displacement due to the unevenness of the sample 110. The controller 130 reconstructs a three-dimensional image of the sample surface by calculating the amount of displacement at each position in the X-axis and Y-axis directions, and transmits this to the computer 50. This three-dimensional image data is also stored in the memory device within the controller 130. The controller 130 can perform height correction of the three-dimensional image data as needed.

[0021] [Computer 50] 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).

[0022] The memory device 20 stores various types of data non-volatilely (non-temporarily). In the example shown in Figure 1, the memory device 20 stores training data 21, measurement data 22, a learning program 23, a judgment program 24, an estimation model 25, and various other data 26.

[0023] The computer 50 functions as a probe degradation determination device that determines whether or not the probe 114 is degraded. In this case, the processor 10 inputs the 3D image generated by the scanning probe microscope 1 to the estimation model 25 to obtain an identification result of whether or not the probe 114 used to measure the 3D image is degraded. In one implementation example, the estimation model 25 obtains one or more types of features from the input image and derives an identification result for the input image based on the one or more types of features.

[0024] The training data 21 is a dataset used for machine learning of the estimation model 25. Each data point in the dataset is generated by labeling images produced based on measurements from a scanning probe microscope with a ground truth (information indicating whether or not the probe is degraded). In one implementation example, the labeling is performed by the user who views each image. More specifically, the user determines whether or not the image was acquired with a degraded probe and labels the image according to the result of that determination. The training data 21 may include only images generated by scanning probe microscope 1, or it may include images generated by other scanning probe microscopes.

[0025] Measurement data 22 is an image generated based on measurements from the scanning probe microscope 1, which is used to determine the degradation of the probe 114.

[0026] The training program 23 is a program for training the estimation model 25 using the training data 21. In one implementation example, the processor 10 executes the training program 23 to perform machine learning on the estimation model 25.

[0027] The determination program 24 is a program for determining the deterioration of the probe 114 using the measurement data 22. In one implementation example, the processor 10 inputs the measurement data 22 into the estimation model 25 by executing the determination program 24, thereby obtaining deterioration information indicating whether or not the probe 114 is deteriorated.

[0028] The estimation model 25 includes data for constructing a classifier (for example, model parameters). The classifier implemented by the estimation model 25 is not limited in type, as long as it is a model that can take an image generated based on measurements from the scanning probe microscope 1 as input and output degradation information indicating whether or not the probe 114 used to generate the image has degraded. It may be a classification model such as a support vector machine, or a model constructed using a neural network. The degradation information may represent the class to which the image is classified (degraded class or non-degraded class), or it may represent the degree of degradation (not degraded, slightly degraded, significantly degraded, etc.).

[0029] The various data 26 include data other than those described above, including data (settings, programs, etc.) that enable the computer 50 to perform the functions described herein.

[0030] As described above, the processor 10 trains the estimation model 25 using the training data 21 by executing the learning program 23. The training data 21 may also be labeled with the measurement mode of the scanning probe microscope when the image was generated. The measurement mode is, for example, the contact mode or the dynamic mode, as will be described later with reference to Figures 2 and 3. This allows the measurement mode to be used for outputting degradation information, and is expected to improve the accuracy of the output degradation information. In this case, it is preferable that the measurement mode of the scanning probe microscope 1 is also assigned to the measurement data 22.

[0031] 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, a pyramidal, conical, or tetrahedral type, as will be described later with reference to Figures 4 to 6. This allows the type of probe to be used in the output of degradation information, and is expected to improve the accuracy of the output degradation information. In this case, it is preferable that the measurement data 22 is also labeled with the type of probe 114 used in the scanning probe microscope 1.

[0032] The training data 21 may be labeled with both the measurement mode and the probe type as described above. In this case, it is preferable that the measurement data 22 also includes both the measurement mode in the scanning probe microscope 1 and the probe type 114.

[0033] [Measurement Mode] The measurement modes in the scanning probe microscope 1 will be described below.

[0034] One example of a measurement mode is the contact mode. The contact mode is a mode that detects static interatomic forces from the degree of curvature of the cantilever 113.

[0035] Figure 2 shows an example of a cantilever 113A for contact mode. The material of the cantilever 113A is, for example, silicon nitride. In the example in Figure 2, the cantilever 113A includes the probe 114A, has a thickness represented by D11 of approximately 1 μm, and a length represented by D12 of approximately 200 μm.

[0036] Another example of a measurement mode is the dynamic mode. In dynamic mode, the cantilever 113 is excited in the longitudinal direction (the direction in which the cantilever 113 faces the sample 110). This excitation causes the cantilever 113 to vibrate near its resonant frequency. When the probe 114 approaches the sample in this state, the amplitude changes. In dynamic mode, this phenomenon is utilized to generate the surface observation result of the sample based on a control variable in the feedback control that keeps the amplitude of the cantilever 113's vibration constant.

[0037] Figure 3 shows an example of a cantilever 113B for dynamic mode. The material of the cantilever 113B is, for example, silicon. In the example in Figure 3, the cantilever 113B includes the probe 114A, has a thickness represented by D21 of approximately 5 μm, and a length represented by D22 of approximately 100 μm.

[0038] [Type of probe] The probes 114 used in the scanning probe microscope 1 can be classified according to their shape.

[0039] One example of the type of probe 114 is pyramidal. Figure 4 shows an image of an example of a pyramidal probe 114. In image IM11 of Figure 4, the tip of the probe 114 is positioned upwards. As shown in image IM11, one example of a probe 114 has a pyramidal shape.

[0040] Another example of the probe type 114 is the conical type. Figure 5 shows an image of an example of a conical probe 114. In image IM12 of Figure 5, the tip of the probe 114 is positioned upwards. As shown in image IM12, an example of the probe 114 has a conical shape.

[0041] Another example of the probe type 114 is the tetrahedral type. Figure 6 shows an image of an example of a tetrahedral probe 114. In image IM13 of Figure 6, the tip of the probe 114 is positioned upwards. As shown in image IM13, an example of the probe 114 has a tetrahedral shape.

[0042] [Probe deterioration] Figure 7 shows examples of the probe's state at the start of use and after a certain period of use. Image IM21 in Figure 7 shows an example of the state at the start of use, and Image IM22 shows an example of the state after 65 hours of measurement (scanning). In both Image IM21 and Image IM22, the tip of the probe 114 is positioned upwards. By comparing Image IM21 and Image IM22, it can be seen that the tip of the probe 114 wears down with use.

[0043] Figure 8 illustrates the wear pattern of the pyramidal probe 114. Figure 9 illustrates the wear pattern of the tetrahedral probe 114.

[0044] In both Figure 8 and Figure 9, the tip of the probe 114 is positioned downwards. As shown in Figure 8, the tip of the probe 114 changes from a point PT31 to a surface PL31 due to wear. Since the type of probe 114 in Figure 8 is pyramidal, the shape of surface PL31 is rectangular. Also, as shown in Figure 9, the tip of the probe 114 changes from a point PT32 to a surface PL32 due to wear. Since the type of probe 114 in Figure 9 is tetrahedral, the shape of surface PL32 is triangular. In other words, the shape of the tip after wear may differ depending on the type of probe 114.

[0045] Note that "wear and tear" is just one example of deterioration of the probe 114. Deterioration of the probe 114 can also occur in ways other than wear, such as cracks forming at the tip of the probe 114, which is sometimes referred to as a double tip.

[0046] [Specific examples of images acquired using a probe that has not deteriorated] Figure 10 shows an example of an image acquired using a probe 114 in an undegraded state. Image IM31 in Figure 10 shows the observation results of a 1.00 μm square area on the surface of the sapphire substrate. The height is 3.48 nm. As shown in image IM31, atomic steps on the surface of the sapphire substrate are clearly observed in the measurement results.

[0047] Figure 11 shows another example of an image acquired using a probe 114 in an undegraded state. Image IM32 in Figure 11 represents the observation result of a 5.00 μm square area on the surface of a lithium-ion battery (separator). The height is 678.4 nm. As shown in image IM32, the measurement results show pores on the surface of the lithium-ion battery.

[0048] Figure 12 shows yet another example of an image acquired using the probe 114 in an undegraded state. Image IM33 in Figure 12 shows the observation result of a 5.49 μm square Vibrio cholerae (unstained). The height is 232.39 nm. As shown in image IM33, the measurement result clearly shows the curved cell body characteristic of Vibrio cholerae and a single flagellum located at one end of the cell body.

[0049] [Specific examples of images obtained using a degraded probe] Figures 13 to 20 show examples of images acquired using a deteriorated probe 114.

[0050] Image IM41 in Figure 13 represents a 2.00 μm square area. Image IM42 in Figure 14 represents a 1.00 μm square area. Image IM43 in Figure 15 represents a 2.50 μm square area. Image IM44 in Figure 16 represents a 3.00 μm square area. In each of images IM41 to IM44, objects with shapes assumed to represent the cross-sectional shape of the tip of the probe 114 appear repeatedly throughout. For example, in image IM41, rectangular objects appear repeatedly throughout, and in images IM42 and IM43, triangular objects appear repeatedly throughout.

[0051] Image IM45 in Figure 17 represents a 3.00 μm square area. Image IM46 in Figure 18 represents a 1.25 μm square area. Image IM47 in Figure 19 and Image IM48 in Figure 20 each represent a 2.00 μm square area. In each of images IM45 to IM48, an object of a given shape appears repeatedly throughout. For example, in image IM45 in Figure 17, the object shown in enlarged form in images IM451, IM452, and IM453 in Figure 17 appears repeatedly throughout. In image IM47 in Figure 19, the object shown in enlarged form in image IM471 in Figure 19 appears repeatedly throughout. In image IM48 in Figure 20, the object shown in enlarged form in images IM481 and IM482 in Figure 20 appears repeatedly throughout.

[0052] From the above, if the probe is degraded, the same object will repeatedly appear throughout the image. However, the shape of the repeatedly appearing object is not constant, nor is the pattern of repetition constant. Therefore, while an experienced user may notice the repeated appearance of the object and realize that the probe is degraded, an inexperienced user may overlook the repeated appearance of the object and fail to realize that the probe is degraded. For various reasons, including the fact that the shape and / or pattern of the repeatedly appearing object are not constant, it is preferable to use a machine learning-based classifier for determining probe degradation using acquired images, rather than using a rule-based determination that relies on predetermined rules regarding degradation.

[0053] [Process Flow] Figure 21 is a flowchart of the process performed to determine probe degradation in an image generated by a scanning probe microscope 1. In one implementation, the processor 10 executes a determination program 24, which causes the computer 50 to perform the process shown in Figure 21. In one implementation, the computer 50 starts the process shown in Figure 21 in response to a measurement instruction being input to the input device 91.

[0054] As shown in Figure 21, 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.

[0055] In step S20, the computer 50 acquires (receives) the image generated as described above from the scanning probe microscope 1.

[0056] 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.

[0057] 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.

[0058] In step S50, the computer 50 displays the image generated in step S40 on the output device 92. After that, the computer 50 terminates the process shown in Figure 21.

[0059] Figure 22 shows an example of an output screen. The output screen 200 shown in Figure 22 includes frames 210 and 220. In the example in Figure 22, the measurement results are displayed in frame 210. Degradation information is displayed in frame 220. In the example in Figure 22, the degradation information indicates that the probe 114 has not deteriorated. As a result, the message "No problem" is displayed in frame 220 as probe information.

[0060] Figure 23 shows another example of an output screen. The output screen 201 shown in Figure 23 includes frames 210 and 220, similar to the output screen 200 in Figure 22. In the example in Figure 23, the degradation information indicates that the probe 114 is degraded. As a result, the message "Possible degradation - Please consider replacement" is displayed in frame 220 as probe information.

[0061] Figure 24 shows yet another example of an output screen. The output screen 202 shown in Figure 24 includes frames 210 and 220, similar to the output screen 200 in Figure 22. In the example in Figure 24, the degradation information indicates that the probe 114 is degraded. As a result, the message "Possible degradation_Please consider expanding the observation field of view" is displayed as probe information within frame 220.

[0062] In the embodiment described above, degradation information of the probe 114 used for measurement is generated using an image obtained as a result of measuring the sample 110 with the scanning probe microscope 1, and this degradation information is output. The mode of outputting the degradation information is not limited to the "display" described with reference to Figures 22 to 24. The mode of outputting the degradation information may be realized by lighting a given lamp, by outputting sound, or by a combination of these.

[0063] Degradation information can express not just whether or not something is degraded, but also the degree of degradation (e.g., not degraded, slightly degraded, significantly degraded).

[0064] Degradation information is generated using estimation model 25. This makes it possible to generate degradation information using images even if the factors (such as the type of features) that influence the degree of degradation of the probe 114 in the image are not clearly defined.

[0065] If the degradation information indicates that the probe 114 is degraded, the user may be prompted to replace the probe 114, as explained with reference to Figure 23, or to enlarge the field of view, as explained with reference to Figure 24. In the latter case, the user may perform the measurement again on the same sample 110 with the field of view enlarged using the scanning probe microscope 1.

[0066] In step S20, the image acquired from the scanning probe microscope 1 may have information indicating the measurement mode in the scanning probe microscope 1, information indicating the type of probe used in the scanning probe microscope 1, observation conditions (for example, information specifying the dimensions of two directions defining the field of view), or two or more types of information arbitrarily selected from these three types. If the estimation model 25 is trained using training data 21 to which such information is added, the degradation information generated using the output from the estimation model 25 will reflect the measurement mode and / or probe type added to the acquired image, and this is expected to improve the accuracy of the degree of degradation obtained as a judgment result.

[0067] The images used as training data 21 and measurement data 22 preferably have a relatively large number of pixels. In one implementation example, the number of pixels in both the first direction (e.g., horizontal) and the second direction (e.g., vertical) is preferably 64 dots or more, more preferably 128 dots or more, and even more preferably 256 dots or more.

[0068] As explained with reference to Figures 22 to 24, it is preferable that the degradation information be output on the same screen as the measurement results when the measurement results of the sample are output. This allows the user to obtain information about the degradation of the probe 114 even if they are not aware of the degradation of the probe 114 when performing a measurement of a sample using the scanning probe microscope 1.

[0069] In the embodiments described above, the computer 50 was described as an external device to the scanning probe microscope 1. However, the computer 50 may also be implemented as part of the scanning probe microscope 1. Furthermore, the computer 50 may be implemented as a single information processing unit, or as a group of interconnected information processing units.

[0070] [Aspect] Those skilled in the art will understand that the above-described exemplary embodiments are specific examples of the following embodiments.

[0071] (Section 1) A probe deterioration determination method according to one embodiment comprises the steps of: acquiring an image of a sample generated based on measurements using a scanning probe microscope; inputting the image of the sample to a classifier and acquiring deterioration information indicating whether or not the probe of the scanning probe microscope is deteriorated; and outputting the deterioration information, wherein the classifier may be subjected to training processing using training data to output deterioration information indicating whether or not the probe of the scanning probe microscope is deteriorated when an image generated based on measurements using a scanning probe microscope is input.

[0072] The probe degradation determination method described in paragraph 1 provides a technology for reliably detecting probe degradation in SPM without requiring the user to be aware of probe degradation.

[0073] (Clause 2) In the probe deterioration determination method described in paragraph 1, the step of outputting deterioration information may include outputting information suggesting the replacement of the probe and / or information suggesting the expansion of the observation field in the scanning probe microscope measurement when the deterioration information indicates that the probe is deteriorated.

[0074] According to the probe deterioration determination method described in paragraph 2, the user is provided with deterioration information, as well as information that can serve as a reference for specific actions corresponding to the deterioration information.

[0075] (Clause 3) In the probe deterioration determination method described in paragraph 1 or 2, the classifier is trained using training data to output deterioration information indicating whether or not the probe of the scanning probe microscope is deteriorated when an image generated based on the measurement of the scanning probe microscope is input in association with the measurement mode of the scanning probe microscope, and the step of acquiring an image of the sample may include acquiring the measurement mode of the scanning probe microscope associated with the image of the sample.

[0076] According to the probe deterioration determination method described in paragraph 3, the accuracy of deterioration information is improved. (Clause 4) In the probe deterioration determination method described in any one of paragraphs 1 to 3, the classifier is trained using training data to output deterioration information indicating whether or not the probe of the scanning probe microscope is deteriorated when an image generated based on the measurement of the scanning probe microscope is input in association with the type of probe of the scanning probe microscope, and the step of acquiring an image of the sample may include acquiring the type of probe of the scanning probe microscope associated with the image of the sample.

[0077] According to the probe deterioration determination method described in Section 4, the accuracy of deterioration information is improved. (Clause 5) In the probe deterioration determination method described in any one of paragraphs 1 to 4, the image acquired in the step of acquiring an image of the sample may have 64 or more pixels in each of the first and second directions.

[0078] According to the probe deterioration determination method described in Section 5, the accuracy of deterioration information is improved. (Clause 6) In the probe deterioration determination method described in any one of paragraphs 1 to 5, the step of outputting the deterioration information may include outputting a screen that displays the measurement results along with the deterioration information.

[0079] According to the probe degradation determination method described in Section 6, users who are only seeking measurement results for a sample are provided with information about probe degradation in addition to the measurement results, ensuring that users are aware of probe degradation.

[0080] (Clause 7) A probe deterioration determination device according to one embodiment comprises one or more processors and a storage device that stores a program executed by the one or more processors, wherein the program is executed by the one or more processors, causing the one or more processors to perform the probe deterioration determination method described in any one of paragraphs 1 to 6.

[0081] The probe degradation determination device described in Section 7 provides a technology for reliably detecting probe degradation in SPM without requiring the user to be aware of probe degradation.

[0082] (Clause 8) A probe deterioration determination program according to one embodiment may be executed by one or more processors, thereby causing the one or more processors to perform the probe deterioration determination method described in any one of paragraphs 1 to 6.

[0083] The probe degradation detection program described in Section 8 provides a technology for reliably detecting probe degradation in SPM without requiring the user to be aware of the probe degradation.

[0084] The embodiments disclosed herein should be considered in all respects to be illustrative and not restrictive. The scope of this disclosure is indicated by the claims rather than by the description of the embodiments above, and all modifications within the meaning and scope of the claims are intended to be included. Furthermore, each technique in the embodiments is intended to be practiced individually or, as far as possible, in combination with other techniques in the embodiments. [Explanation of Symbols]

[0085] 1 Scanning probe microscope, 10 Processor, 20 Memory device, 25 Estimation model, 50 Computer, 91 Input device, 92 Output device, 110 Sample, 111 Piezo scanner, 111xy XY scanner, 111z Z scanner, 112 Sample stage, 113 Cantilever, 114 Needle, 115 Laser diode, 119 Photodetector, 120 Displacement detection mechanism, 130 Controller, 131 Feedback signal generator, 133 Scanning signal generator.

Claims

1. The steps include: acquiring an image of the sample generated based on measurements using a scanning probe microscope; The steps include inputting an image of the sample to the classifier and obtaining degradation information indicating whether or not the probe of the scanning probe microscope is degraded, The system includes a step of outputting the aforementioned degradation information, A probe degradation determination method, wherein the classifier 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 based on measurements of the scanning probe microscope is input.

2. The probe deterioration determination method according to claim 1, wherein the step of outputting the deterioration information includes outputting information suggesting the replacement of the probe and / or information suggesting the expansion of the field of view in the scanning probe microscope measurement when the deterioration information indicates that the probe is deteriorated.

3. The classifier has been trained using training data to output degradation information indicating whether or not the probe of the scanning probe microscope is degraded when an image generated based on the measurement of the scanning probe microscope is input in association with the measurement mode of the scanning probe microscope. The probe degradation determination method according to claim 1 or 2, wherein the step of acquiring an image of the sample includes acquiring the measurement mode of the scanning probe microscope associated with the image of the sample.

4. The classifier has been trained using training data to output degradation information indicating whether or not the probe of the scanning probe microscope is degraded, when an image generated based on measurements of the scanning probe microscope is input in relation to the type of probe of the scanning probe microscope. The probe degradation determination method according to claim 1 or 2, wherein the step of acquiring an image of the sample includes acquiring the type of probe of the scanning probe microscope associated with the image of the sample.

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

6. The probe deterioration determination method according to claim 1 or claim 2, wherein the step of outputting the deterioration information includes outputting a screen that displays the measurement results together with the deterioration information.

7. One or more processors, The system includes a storage device for storing programs executed by one or more processors, The program is executed by the one or more processors, causing the one or more processors to perform the probe deterioration determination method described in claim 1 or claim 2, in a probe deterioration determination device.

8. A probe deterioration determination program that, when executed by one or more processors, causes the one or more processors to perform the probe deterioration determination method described in claim 1 or claim 2.

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