Apparatus and method for evaluating noise in microscope devices

Abstract

This invention provides a noise evaluation apparatus and method for microscope devices. [Solution] A device for evaluating the effect of noise acting on a microscope device, the device comprising: a microscope device that detects a signal generated by a sample and forms a corresponding detection signal; a noise sensor unit that detects noise and forms a corresponding noise detection signal, and includes a mechanical noise sensor for detecting mechanical noise and a magnetic field sensor for detecting magnetic field noise; a control unit that generates a monitor signal corresponding to the drive signal of the microscope device; and a signal processing unit that receives one or more of the noise detection signal and the monitor signal and performs signal processing, the signal processing unit calculates the correlation between one or more of the noise detection signal and the monitor signal and the detection signal.

Description

Technical Field

[0001] The present disclosure generally relates to a noise evaluation apparatus and method for a charged particle beam apparatus.

Background Art

[0002] A scanning microscope places a probe at a specific position on a sample and detects a signal. The probe is two-dimensionally scanned in the X and Y directions on the sample, and the signal is measured at each coordinate. By two-dimensionally imaging the signal amount as a gray level for each coordinate, a microscope image can be obtained.

[0003] Among scanning microscopes, a microscope that uses an electron source as a light source, forms a probe by focusing an electron beam, and observes the sample surface using secondary electrons and reflected electrons generated in the sample as signals is called a scanning electron microscope (SEM). Also, a microscope that uses a thinned sample and observes the inside of the sample using transmitted electrons that have passed through the sample is called a scanning transmission electron microscope (STEM).

[0004] SEM and STEM that use an electron beam are widely used in the fields of materials science, nanoscience, and electronics engineering. An apparatus that uses charged particles such as an electron beam and an ion beam is called a charged particle beam apparatus. Since microscopic observation using a charged particle beam apparatus can obtain high spatial resolution, it can observe structures that are too small to be observed with a general optical microscope, such as thin films grown on a substrate, nanotubes, plasmon structures, and the atomic arrangement of a sample. In addition, a charged particle beam apparatus can also observe the fine structure of a biological sample such as a cell and the crystal structure of a sample through an electron diffraction image.

[0005] Scanning microscopes are instruments used to observe the fine structure of samples. With the advancement of materials science, nanoscience, and electronics, the demand for observing finer structures is increasing. However, when scanning microscopes are set to high magnification to observe samples at greater magnification, the resolution is often limited not only by the instrument's inherent resolution due to the probe size, but also by other factors. These limiting factors are called noise in the microscope image. Such noise problems can occur after the microscope has been installed as a product at a customer's site, or they can arise during the research and development process of new microscopes. [Overview of the project] [Problems that the invention aims to solve]

[0006] When acquiring a microscopic image of a sample at high magnification using a scanning microscope, disturbances caused by the environment where the microscope is installed may affect the microscope, or noise caused by the disturbances may be mixed into the signal detected by the microscope, or the microscope may be affected in a way that prevents the acquisition of a good microscopic image.

[0007] In scanning electron microscopes, multiple external disturbances such as vibrations from the floor, noise, and magnetic fields have an impact, making it difficult to pinpoint the cause. Furthermore, since the necessary countermeasures for the microscope differ depending on the type of noise, it is necessary to identify the cause. Therefore, if disturbance noise is introduced into the microscope image after the equipment has been installed, it is necessary to identify the cause early and implement countermeasures.

[0008] In addition to the disturbances and noises mentioned above, noise from the control system that supplies multiple electrical signals (voltage and current) to operate the microscope can also have adverse effects. Therefore, it is necessary to identify and address causes other than disturbance noise, including those from the control system. [Means for solving the problem]

[0009] This embodiment is a device for evaluating the effect of noise acting on a microscope device, the device comprising: a microscope device that detects a signal generated by a sample and forms a corresponding detection signal; a noise sensor unit that detects noise and forms a corresponding noise detection signal, and includes a mechanical noise sensor for detecting mechanical noise and a magnetic field sensor for detecting magnetic field noise; a control unit that generates a monitor signal corresponding to the drive signal of the microscope device; and a signal processing unit that receives one or more of the noise detection signal and the monitor signal and performs signal processing, the signal processing unit calculates the correlation between one or more of the noise detection signal and the monitor signal and the detection signal.

[0010] According to any aspect of this embodiment, the microscope device is one of the following: scanning electron microscope (SEM), scanning transmission electron microscope (STEM), scanning ion microscope (SIM), focused ion beam (FIB), scanning helium ion microscope (HIM), scanning probe microscope (SPM), atomic force microscope (AFM), and scanning tunneling microscope (STM).

[0011] According to any aspect of this embodiment, the mechanical noise sensor includes a vibration sensor for detecting floor vibrations, and one or more of the following: a vibration sensor for detecting vibrations of the microscope device and an acoustic sensor for detecting vibrations in the sound band. In this aspect, the vibration sensor and the magnetic field sensor are three-axis sensors.

[0012] According to any aspect of this embodiment, the microscope device includes one or more of the following: a scanning unit, a stigmeter, an alignment unit, a lens unit, an electron source, and a high-voltage source and a current source for driving; the drive signal of the microscope device is the drive signal of one or more of the scanning unit, stigmeter, alignment unit, lens unit, electron source, and high-voltage source and current source for driving; and the monitor signal is a signal corresponding to the drive signal.

[0013] According to any aspect of this embodiment, the microscope device further includes one or more of the following: a secondary electron detector (SED), a backscattered electron detector, a transmitted electron detector, a sample absorption current detector, an X-ray detector, and an electron energy loss spectrometer, and the detection signal further includes a signal formed when one or more of the secondary electron detector (SED), backscattered electron detector, transmitted electron detector, sample absorption current detector, X-ray detector, and electron energy loss spectrometer detect the sample.

[0014] According to any aspect of this embodiment, the signal processing unit calculates a correlation coefficient between one or more of the noise detection signal and the monitor signal and the detection signal. In this aspect, the correlation coefficient calculated by the signal processing unit is one or more of the Pearson correlation coefficient, Spearman correlation coefficient, and distance correlation coefficient.

[0015] According to any aspect of this embodiment, the signal processing unit displays the noise, the monitor signal, and the detection signal in one or more of the following domains: the time domain, the frequency domain to which Welch's method is applied, and the frequency domain.

[0016] According to any aspect of this embodiment, the microscope device positions a probe at any point on the sample and detects a signal with a detector, or positions and scans a probe along any edge of the sample and detects a signal, or positions and scans a region including at least one portion of the sample, senses and detects a signal to form a detection signal.

[0017] According to any aspect of this embodiment, the processing unit extracts one or more of the provided noise detection signals and monitor signals and signals within the frequency band set by the detection signal, and calculates the correlation between the extracted signals and the detection signal.

[0018] According to any one aspect of this embodiment, the processing unit includes a preprocessor unit that performs an FFT operation on one or more of the input noise detection signals and monitor signals and on the detection signal, a filter unit that extracts signals within a set bandwidth, and an IFFT operation unit that performs an IFFT (Inverse FFT) operation on the output signal of the filter unit. In this aspect, the filter unit extracts signals within the set bandwidth by applying one or more of the provided noise detection signals and monitor signals one or more of the low-pass filter (LPF), band-pass filter (BPF), and high-pass filter (HPF).

[0019] According to any aspect of this embodiment, the set bandwidth is a frequency bandwidth that includes the frequency band of noise affecting the microscope image.

[0020] This embodiment is a method for evaluating the influence of noise acting on a microscope device. The method includes: a step in which the microscope device detects secondary electrons formed by the sample to form a corresponding detection signal; a step in which a noise sensor including a mechanical noise sensor and a magnetic field sensor detects the noise acting on the microscope device to form a noise detection signal; a step in which a monitor signal corresponding to the drive signal of the microscope device is generated; and a step in which a signal processing unit calculates the correlation between any one or more of the noise detection signal and the monitor signal and the detection signal.

Advantages of the Invention

[0021] According to this technology, there is provided an advantage that it is possible to grasp what kind of noise affects the image formed by the charged particle beam device.

Brief Description of the Drawings

[0022] [Figure 1] It is a diagram showing an outline of an apparatus for evaluating the influence of noise acting on the microscope device of this embodiment. [Figure 2] It is a flowchart schematically showing a method for evaluating the influence of noise acting on the microscope device of this embodiment. [Figure 3] It is a diagram showing an example in which a microscope device provides a charged particle beam to a sample and detects secondary electrons formed by the sample in order to grasp the influence of noise. [Figure 4] It is a diagram showing an example in which a microscope device provides a charged particle beam to a sample and detects secondary electrons formed by the sample in order to grasp the influence of noise. [Figure 5] It is a block diagram exemplifying the outline of a preprocessing unit. [Figure 6] It is a flowchart exemplifying the outline of the preprocessing method of this embodiment. [Figure 7] It is a diagram showing the state in which the correlation coefficient is calculated and shown to the user. [Figure 8] It is a diagram showing the input signal in the time domain and the frequency domain.

Embodiments for Carrying Out the Invention

[0023] Hereinafter, this embodiment will be described with reference to the attached drawings. FIG. 1 is a diagram showing an overview of an apparatus for evaluating the influence of noise acting on the microscope apparatus of this embodiment. Referring to FIG. 1, the noise influence evaluation apparatus 10 for the microscope apparatus of this embodiment includes a microscope apparatus 100 that detects a signal generated by a sample and forms a corresponding detection signal, mechanical noise sensors 214, 216, 218 that detect noise and form corresponding noise detection signals, a noise sensor unit including a magnetic field sensor 212, a control unit 180 that generates a monitor signal mon corresponding to the drive signal of the microscope apparatus, and a signal processing unit 300 that performs signal processing when one or more of the noise detection signals n_mech1, n_mech2, n_mech3, n_mag, and the monitor signal mon are provided. The signal processing unit 300 calculates the correlation between one or more of the noise detection signals n_mech1, n_mech2, n_mech3, n_mag and the monitor signal mon and the detection signal det1.

[0024] In the illustrated embodiment, the microscope apparatus 100 is a scanning electron microscope. However, the microscope apparatus of this embodiment is not limited to this, and a scanning transmission electron microscope (STEM) that detects a signal transmitted through a sample and uses a thin film as a sample, a scanning ion microscope (SIM) that uses an ion source as a light source, focuses an ion beam to form a probe, and detects secondary electrons generated by the sample using secondary ions, a focused ion beam apparatus (FIB) that is a scanning ion microscope using a liquid metal ion source such as Ga as an ion source, or a scanning helium ion microscope (HIM) that is a scanning ion microscope using a gas ion source such as He as an ion source can be used.

[0025] Furthermore, the microscope device in this embodiment can be any one of the following: a scanning probe microscope (SPM), which uses a probe to detect the interaction between the probe and the sample, controls the distance between the probe and the sample to keep constant, and measures the displacement of the probe to obtain a microscope image; an atomic force microscope (AFM), which senses interatomic interactions and uses a cantilever; or a scanning tunneling microscope (STM), which senses tunneling current. To further clarify this embodiment, a scanning electron microscope (SEM) will be used as an example in the following explanation.

[0026] The microscope apparatus 100 of this embodiment includes a stage 150 on which a sample is placed, a charged particle source 112, a first detector 610 that detects secondary electrons formed in the sample and provides them as corresponding det2, det2, and det1, and an objective lens 120 that provides the charged particle beam of charged particles generated by the charged particle source 112 to the sample. This embodiment may further include a control unit 180 that drives the microscope apparatus 100 by providing a drive voltage and / or current.

[0027] The sample is positioned on a stage 150 located inside a vacuum chamber V. In one embodiment, the stage 150 is a 5-axis stage, and the control unit 180 controls the stage 150 according to control commands provided by the user terminal to adjust the XYZ position, rotation, and tilt of the sample.

[0028] The microscope apparatus 100 includes a charged particle source 112. In one embodiment, the charged particle source 112 includes a filament that is heated to emit electrons, a suppressor electrode that prevents the emission of charged particles in any direction, an extractor electrode that draws charged particles in the desired direction and adjusts the emission current, and an electron source pump that creates a desired vacuum within the charged particle source.

[0029] In one embodiment, the microscope apparatus 100 includes one or more condenser lenses CL. The charged particle beam B is focused by one or more condenser lenses CL and an aperture, and the optical axis is aligned by multiple optical axis adjusters (not shown). Furthermore, the charged particle beam B is corrected for astigmatism by a stigmeter (not shown).

[0030] The charged particle beam B travels to the objective lens 120 and is focused onto the sample by the objective lens 120. In one embodiment, the objective lens 120 can be a magnetic field type, an electrostatic type, or a magnetic field / electric field combined type objective lens. In one embodiment, if the objective lens 120 is an electrostatic type, a high voltage is supplied to the upper electrode 122 and the lower electrode 124 by the control unit 180. As an example, the high voltage can be +1 to +30 kV.

[0031] In one embodiment, if the objective lens 120 is electrostatic, the objective lens 120 includes an upper electrode 122 and a lower electrode 124. In one embodiment, the microscope apparatus 100 may further include a first detector 610 and a scanning unit (810) together with the objective lens 120. In embodiments not shown, the microscope apparatus may include one or more of an alignment unit, a lens unit, an electron source, and a high voltage source and a current source for driving.

[0032] Figure 2 is a flowchart illustrating a method for evaluating the noise effect acting on the microscope apparatus of this embodiment. Referring to Figures 1 and 2, the method for evaluating the noise effect acting on the microscope apparatus of this embodiment includes the steps of: step S100, in which the microscope apparatus 100 detects secondary electrons formed in the sample and forms a corresponding detection signal; step S200, in which a noise sensor including a mechanical noise sensor and a magnetic field sensor detects noise and forms a noise detection signal, and the microscope apparatus forms a monitor signal corresponding to the drive signal; and step S300, in which the signal processing unit calculates the correlation between one or more of the noise detection signal and the monitor signal and the detection signal.

[0033] As one embodiment, the apparatus 10 of this embodiment can operate in a first operating mode for observing a sample using a microscope 100, and a second operating mode for evaluating the effect of noise interfering with the microscope 100. When operating the apparatus 10 of this embodiment, the user can select to operate it in either the first or second operating mode. The following description will use the case where the user operates the apparatus 10 of this embodiment in the second operating mode as an example.

[0034] When the microscope device 100 provides a charged particle beam to the sample, secondary electrons are formed in the sample. The first detector 610 detects the secondary electrons and generates a first detection signal det1 corresponding to the detected secondary electrons. Figure 3 shows an example in which the microscope device 100 provides a charged particle beam to the sample to understand the effects of noise and detects the secondary electrons formed in the sample. Referring to Figures 1 to 3(a), the microscope device 100 can provide a charged particle beam to the boundary of the sample and keep it stationary. The provided x-axis scan signal and y-axis scan signal can all be DC signals. As in the illustrated example, a static charged particle beam is provided to any one point on the boundary of the sample, and secondary electrons formed in the sample are detected and a corresponding detection signal is output.

[0035] Figure 3(b) illustrates an example of an SEM microscope image based on the detection signal when a charged particle beam is applied to a sample, with noise present. As shown, it can be confirmed that noise intervention causes tearing, where the outer edge of the sample is disturbed, or ripple, where ripples are formed around the outer edge of the sample.

[0036] Therefore, by fixing a charged particle beam to any one part of a static sample and irradiating it, and then detecting secondary electrons from it, it becomes easier to understand the effect of the noise provided to the microscope device 100 on the detection signal.

[0037] Referring to Figure 4(a), the microscope apparatus 100 can provide a charged particle beam along any one side of a sample on which multiple rectangular patterns are drawn, and keep it stationary. The scan signal in the x-axis direction can be a DC signal so that the charged particle beam is provided at the same coordinates along the x-axis. The scan signal in the y-axis direction can also be varied so that the charged particle beam provided along the y-axis moves.

[0038] As shown in the illustrated example, by providing a charged particle beam along the boundary of the sample and acquiring the detection signal, it becomes easier to understand the effect of the noise provided to the microscope device 100 on the detection signal.

[0039] Referring to Figure 4(b), the microscope apparatus 100 can acquire a detection signal by moving the charged particle beam to provide a charged particle beam along an area including the outer boundary of the sample on which multiple rectangular patterns are drawn. The scan signals in the x-axis and y-axis directions can be varied signals so that the charged particle beam is provided within the specified area.

[0040] In one embodiment, the first detector 610 that provides the first detection signal det1 may include a photomultiplier (PMT) that detects secondary electrons formed by the charged particle beam B provided by the charged particle beam apparatus 100 and forms the corresponding electrical signal, the first detection signal det1.

[0041] The microscope apparatus 100 may further include a second detector 620 that provides a second detection signal det2. For example, the second detector 620 may be one or more of the following: a secondary electron detector (SED) including a photomultiplier (PMT), a backscattered electron detector, a transmitted electron detector, a sample absorption current detector, an X-ray detector, and an electron energy loss spectrometer. The second detection signal det2 may be a signal formed by the second detector 620 detecting a sample or detecting a signal formed in the sample.

[0042] A noise sensor, including mechanical noise sensors 214, 216, and 218 and a magnetic field sensor 212, detects noise and forms noise detection signals n_mech1, n_mech2, n_mech3, and n_mag, and the microscope device forms a monitor signal mon corresponding to the drive signal (S200).

[0043] The apparatus 10 of this embodiment may include mechanical noise sensors 214, 216, and 218 and a magnetic field sensor 212. In one embodiment, the mechanical noise sensor 214 is a sensor that detects vibrations in the acoustic band. The mechanical noise sensor 214 detects vibrations in the acoustic band and outputs a noise detection signal n_mech1 corresponding to the detected vibrations. As an example, the mechanical noise sensor 214 can output a signal on a single channel.

[0044] The mechanical noise sensor 216 detects vibrations of the microscope apparatus 100 and outputs a noise detection signal n_mech2 corresponding to the detected vibrations. In one embodiment, the microscope apparatus 100 is placed on a damper to reduce vibrations transmitted from the floor S at the installation location. However, since the damper cannot completely reduce vibrations, vibrations may still be transmitted to the microscope apparatus 100 through the damper even when placed on it. In this embodiment, the mechanical noise sensor 216 detects vibrations in the x, y, and z axes transmitted through the damper and provides a noise detection signal n_mech2 corresponding to the detected vibrations through each channel.

[0045] The mechanical noise sensor 218 detects vibrations transmitted through the floor S at the location where the microscope device 100 is installed, and outputs a noise detection signal n_mech3 corresponding to the detected vibrations. The mechanical noise sensor 218 detects vibrations in the x, y, and z axes and provides a noise detection signal n_mech3 corresponding to the detected vibrations through each channel.

[0046] The magnetic field sensor 212 detects the magnetic field affecting the microscope device 100 and outputs a noise detection signal n_mag corresponding to the detected magnetic field in three channels: x, y, and z.

[0047] The microscope apparatus 100 in this embodiment operates by providing electrical signals to, or being provided with, a charged particle source 112, a condenser lens CL, a stigmeter (not shown) for correcting astigmatism, an objective lens 120, a scanning unit 810, and the objective lens 120, respectively.

[0048] Furthermore, the microscope device 100 includes a control unit 180, which provides voltage and current to the elements of the microscope device to drive the microscope device 100 and provides the necessary signals. Since the voltage and current provided through the control unit 180 may act as noise on the microscope device 100, the control unit 180 forms a monitor signal mon corresponding to the voltage, current, and other signals received from the microscope device 100 and provides it to the processing unit 300.

[0049] In one embodiment, the drive signal provided to the microscope apparatus 100 can be one or more of the scanning unit, stigmeter, alignment unit, lens unit, electron source, and high-voltage and current sources for driving, and the voltage is in the range of several volts to tens of kV. The control unit 180 forms a monitor signal mon corresponding to the electrical signal, but with an adjusted output range and normalized, and provides it to the processing unit 300. In one embodiment, the control unit 180 forms the monitor signal mon to have an amplitude corresponding to the input dynamic range of the ADC included in the processing unit 300 and provides it to the processing unit 300. In one embodiment, the monitor signal mon can be normalized as a signal with an amplitude of -10V to 10V, or a signal with an amplitude of -2.5V to 2.5V.

[0050] In the illustrated embodiment, the processing unit 300 may include a front end unit (FE, 322). In one embodiment, the front end unit 322 receives noise detection signals output by mechanical noise sensors 214, 216, and 218 and magnetic field sensor 212, as well as a monitor signal mon output by control unit 180, and processes them so that they can be processed by signal processing unit 320.

[0051] As one embodiment, the front-end unit 322 can perform analog signal preprocessing such as impedance matching, buffering, and amplification of the input analog signal, as well as output branching and output attenuation. Furthermore, the front-end unit 322 can perform signal sampling and analog-to-digital conversion using an ADC (analog-to-digital converter) on the preprocessed analog signal. As another embodiment, the sampling time (or frequency) of the front-end unit 322 can be varied according to the scan time (or frequency) required to acquire a scan microscope image where noise measurement is necessary. For example, in the case of a laboratory SEM, a sampling frequency of 500Hz to 1kHz is sufficient to acquire a single image in 1 to 3 minutes. As another example, in the case of a high-performance microscope, a faster sampling frequency of 1kHz or higher may be required.

[0052] In one embodiment, the front-end unit 322 may include a signal acquisition device that includes a general-purpose measuring instrument such as a data logger or oscilloscope, or a dedicated ADC may be used.

[0053] In the example illustrated in Figure 1, the front-end unit 322 is shown as being included in the signal processing unit 300. However, in embodiments not shown, the front-end unit 322 can be located separately from the signal processing unit 300 and provide the processed signal to the signal processing unit. The signal processing unit calculates the correlation between the detection signal and the noise and the drive signal from the noise and the drive signal.

[0054] In one embodiment, the signal processing unit 320 can be a digital signal processing unit (DSP) implemented using an FPGA. In another embodiment, the signal processing unit 320 can be implemented using software written in a programming language on a computer.

[0055] As described above, when operating the apparatus 10 of this embodiment, the user can select to operate it in either the first or second operating mode. In an embodiment in which the user operates the apparatus 10 of this embodiment in the first operating mode to observe a sample with the microscope apparatus 100, the first detector 610, which includes a photomultiplier (PMT), forms a detection signal det1, which is an electrical signal corresponding to the secondary electrons formed when the charged particle beam B is supplied to the sample. The sample can be observed in this manner.

[0056] When a user drives the device 10 of this embodiment in the second operating mode, the signal processing unit 300 is provided with the first detection signal det1 provided by the first detector 610. The signal processing unit 300 is also provided with one or more of the following: noise detection signal n_mech1 provided by the mechanical noise sensor 214, noise detection signal n_mech2 provided by the mechanical noise sensor 216, noise detection signal n_mech3 provided by the mechanical noise sensor 218, noise detection signal n_mag provided by the magnetic field sensor 212, and monitor signal mon provided by the control unit 180. In one embodiment, a mechanical noise sensor and / or magnetic field sensor that outputs noise detection signals in multiple channels can provide the signal processing unit 300 with noise detection signals in at least one channel.

[0057] In one embodiment, when the apparatus 10 of this embodiment is driven in the second operating mode, the signal processing unit 300 may be further provided with the second detection signal det2 provided by the second detector 620.

[0058] The signal processing unit 300 calculates the correlation between one or more of the noise detection signals n_mech1, n_mech2, n_mech3, n_mag provided by the noise sensor unit and the monitor signal mon provided by the control unit 180 and the first detection signal det1. In one embodiment, the signal processing unit 300 further calculates the correlation between one or more of the noise detection signals n_mech1, n_mech2, n_mech3, n_mag provided by the noise sensor unit and the monitor signal mon provided by the control unit 180 and the second detection signal det2 provided by the second detector 620.

[0059] The correlation between one or more of the noise detection signals n_mech1, n_mech2, n_mech3, n_mag, and the monitor signal mon and the detection signal can be obtained by calculating the correlation coefficient. In one embodiment, the relationship between the detection signal and the noise and / or drive signal can be calculated by calculating the Pearson correlation coefficient. The Pearson correlation coefficient can be calculated as shown in Equation 1 below.

number

[0060] In another embodiment, the correlation calculation between the detection signal and the noise and / or drive signal can be performed by calculating the Spearman correlation coefficient. The Spearman correlation coefficient can be calculated as shown in Equation 2 below.

number

[0061] In another embodiment, the correlation calculation between the detection signal and the noise and / or drive signal can be performed by calculating the distance correlation coefficient. The distance correlation coefficient can be calculated as shown in Equation 3 below.

number

[0062] As described above, the correlation between the detection signal and the intervening noise and / or driving signal can be obtained by calculating the Pearson correlation coefficient, Spearman correlation coefficient, and distance correlation coefficient. Depending on the user's selection, the correlation between the detection signal and the intervening noise and / or driving signal can be calculated using one or more of the Pearson correlation coefficient, Spearman correlation coefficient, and distance correlation coefficient, and the calculated value can be shown to the user.

[0063] As another example, depending on the distribution of noise and / or drive signal values, one of the Pearson correlation coefficient, Spearman correlation coefficient, and distance correlation coefficient can be calculated and displayed to the user. In one embodiment, the Pearson correlation coefficient shows a relatively high correlation when the noise and / or drive signal intervening in the detection signal is linear. Therefore, the signal processing unit 320 calculates the Pearson correlation coefficient and informs the user when the intervening noise and / or drive signal is linear.

[0064] In another embodiment, the Spearman correlation coefficient shows a relatively high correlation when the noise and / or drive signal intervening in the detection signal are nonlinear. Therefore, the signal processing unit 320 calculates the Spearman correlation coefficient and informs the user when the intervening noise and / or drive signal are nonlinear.

[0065] In another embodiment, the distance correlation coefficient shows a relatively high correlation when the noise and / or drive signal intervening in the detection signal is periodic. Therefore, the signal processing unit 320 calculates the distance correlation coefficient and informs the user when the intervening noise and / or drive signal is periodic.

[0066] However, the system can calculate and display one of the following: the Pearson correlation coefficient, the Spearman correlation coefficient, and the distance correlation coefficient. In other embodiments, it is possible to calculate and display one or more of the following: the Pearson correlation coefficient, the Spearman correlation coefficient, and the distance correlation coefficient.

[0067] As one embodiment, the signal processing unit 320 can be provided with a pre-processed signal, calculate its correlation with the noise and / or drive signal mon, and display it to the user in a graph. As an example, the signal processing unit 320 can display the noise and / or drive signal for each channel measured in the time domain, according to the user's selection. As another example, the signal processing unit 320 can convert the signal measured in the time domain to the frequency domain, according to the user's selection, and display the noise and / or drive signal for each channel in the frequency domain. As yet another example, the signal processing unit 320 can convert the signal measured in the time domain to the frequency domain, according to the user's selection, and then convert and display the noise and / or drive signal for each channel in the frequency domain according to the Welch algorithm.

[0068] In the above-described embodiment, the correlation values ​​calculated according to the user's selection and / or the calculated graph can be shown. Therefore, the user can systematically understand which noise factor has the greatest impact, and at the same time, understand the impact of the noise by referring to the correlation with the noise and / or drive signal mon, which has been converted to the frequency domain along with the calculated correlation values ​​and converted by the Welch method.

[0069] The noise measured by device 10 can include both noise with frequency components that have a relatively large impact on image distortion and noise with low signal intensity that has a relatively small impact on image distortion. Therefore, when actually calculating the correlation coefficient, the correlation coefficient may be underestimated due to low-intensity frequency signals.

[0070] Such problems arise when low-intensity and high-intensity frequency signals coexist, and underestimating the correlation coefficient due to low-intensity frequency signals can make it difficult to identify the source of the noise that primarily affects the microscope device 100.

[0071] In one embodiment, the apparatus 10 may further include a pre-processing unit (310) that performs a noise pre-processing step. Figure 5 is a block diagram illustrating the outline of the pre-processing unit 310. Referring to Figure 5, the pre-processing unit 310 includes an FFT calculation unit 312 that receives the input signal and performs an FFT, a filter unit 314 that extracts signals within a set bandwidth, and an inverse FFT unit 316 that performs an inverse FFT operation on the signal output by the filter unit 314.

[0072] Figure 6 is a flowchart illustrating an overview of the preprocessing method in this embodiment. Referring to Figure 6, the preprocessing method includes a step S1000 in which an FFT (Fast Fourier Transform) is performed on the image acquired by the microscope device 100 and the noise acquired by the sensor, a frequency band setting step S2000, and a filter application step S3000. In one embodiment, the preprocessing method may further include a step of inverse FFT transformation of the signal into the time domain.

[0073] The preprocessing process will be explained with reference to Figures 5 and 6. The FFT calculation unit 312 of the preprocessing unit 310 performs an FFT on the image acquired by the microscope device 100 and the noise acquired by the sensor (S1000). In one embodiment, the signal input to the preprocessing unit 310 can be one or more of the noise signals n_mag, n_mech1, n_mech2, n_mech3 and the monitor signal mon output by the noise sensor. In another embodiment, the signal input to the preprocessing unit 310 can be the signal output by the front-end unit 322 after processing the noise signals n_mag, n_mech1, n_mech2, n_mech3 and the monitor signal mon output by the noise sensor. The image acquired by the microscope device 100 can contain not only image components but also various noise components. An FFT is performed on the image acquired by the microscope device 100. Since the image is a two-dimensional image, it can be converted to spatial frequency units. In one embodiment, the spatial frequency can have the reciprocal of the length dimension. For example, spatial frequencies can have reciprocals of the length dimension, such as 1 / m, 1 / (μm), and 1 / (nm).

[0074] To convert the reciprocal of the length dimension to time frequency (Hz), the speed of the electron beam scanning signal used to acquire the image from the microscope device 100 is utilized. For example, if the scanning speed in the x-axis direction is 1 μs / Pixel and the scanning speed in the y-axis direction is 1 ms / Line, the time frequency range of the image acquired by the microscope device after performing the FFT is ±500 kHz and ±500 Hz, respectively. Therefore, by performing an FFT on the image acquired by the microscope device, the frequency of noise affecting the image can be compared with and understood from data measured by the sensor.

[0075] Furthermore, the noise components may include a noise detection signal n_mech1, which is a noise component corresponding to vibrations in the acoustic band; a noise detection signal n_mech2, which detects vibrations of the microscope device 100 transmitted through the damper; a noise detection signal n_mech3, which detects vibrations transmitted through the floor S at the location where the microscope device 100 is installed and corresponds to the detected vibrations; and a noise detection signal n_mag, which detects a magnetic field and corresponds to the detected magnetic field.

[0076] The FFT calculation unit 312 performs an FFT on each of the noise signals n_mech1, n_mech2, n_mech3, and n_mag detected by the sensor, which may include components measured along the x, y, and z axes. Therefore, by performing an FFT on each noise signal, the frequency bandwidth of each noise signal can be determined. Furthermore, the FFT calculation unit 312 can perform an FFT on the monitor signal mon provided by the control unit 180 (S1000).

[0077] The filter unit 314 sets the frequency band (S2000). The set frequency band can be the frequency band of noise that affects the image acquired by the microscope device 100. In one embodiment, the set frequency band can be set to the cutoff frequency, passband frequency, etc. of the filter unit 314. As an example, the set frequency band can be a band that includes multiple noise frequencies that greatly affect the image. As another example, the set frequency band can be a band of frequencies that include noise that affects the image.

[0078] As one embodiment, the filter can be a filter that selectively outputs noise within a set frequency band included in the filter unit 314. For example, if the noise spectrum includes noise at 20Hz and 40Hz, and the noise affecting the image acquired by the microscope device 100 is at 20Hz, and among the noise signals n_mag, n_mech1, n_mech2, and n_mech3 output by the noise sensor, the frequency band that does not affect the device or has little effect is at 40Hz, then the filter unit 314 will block the 40Hz noise and selectively output the 20Hz noise. This prevents the correlation coefficient of the 20Hz noise from being underestimated and ensures that noise in the frequency band with a greater effect is selectively output.

[0079] As another example, if we can determine from the noise spectrum that noise is distributed in the 30Hz, 60Hz, and 90Hz frequency bands, and the noise affecting the image acquired by the microscope device 100 is 60Hz, while the 30Hz and 90Hz noises do not affect the device or have little effect, then the band-pass filter (BPF) included in the filter unit 314 can be set to block 30Hz and 90Hz and selectively output signals within a certain range including 60Hz. This prevents the correlation coefficient of 60Hz noise from being underestimated and prevents the correlation coefficient from being incorrectly evaluated due to the 30Hz and 90Hz noises that have little effect on the device.

[0080] As another example, if the noise affecting the image acquired by the microscope device 100 is 100 Hz, but the noise signals n_mag, n_mech1, n_mech2, and n_mech3 output by the noise sensor contain signals with a frequency of 50 Hz, potentially leading to a low correlation coefficient with respect to the 100 Hz noise, then a high-pass filter (HPF) can be set to block 50 Hz and selectively output signals in the frequency range including 100 Hz. The filter can selectively output noise within the set frequency band.

[0081] As one embodiment, after performing the filter application step (S3000), an inverse FFT (316) can be performed on the acquired noise signal. Performing an inverse FFT allows the acquired noise signal to be converted into a time-domain signal, which offers the advantage of being able to more precisely and effectively measure and evaluate the correlation coefficient between the time-domain signal and the noise affecting the image.

[0082] Figures 7(a), 7(b), and 7(c) show the state after calculating the correlation coefficient and displaying it to the user. In the illustrated experiment, the noise sensor includes a mechanical noise sensor that outputs noise detection signals (Accelerometer X, Accelerometer Y, Accelerometer Z) for the x, y, and z channels, a mechanical noise sensor that outputs a noise detection signal (Acoustic) that detects vibrations in the acoustic band, and a magnetic field sensor that outputs noise detection signals (Magnetic field X, Magnetic field Y, Magnetic field Z) that detect magnetic fields in the x, y, and z channels. The control unit of the microscope device also provides monitor signals (Scan X, ScanY) corresponding to the X / Y scanning drive signals.

[0083] The processing unit receives the output from the photomultiplier (PMT), which is the amplification mechanism of the secondary electron detector, as the first detection signal det1. Therefore, the processing unit receives a total of 10 channels of signals, including 7 channels of noise detection signals, 2 channels of monitor signals, and 1 channel of detection signal.

[0084] Figure 7(a) shows the user that the noise detected in the detection signal has the largest correlation coefficient with the mechanical vibration in the x-axis direction. The example illustrated in Figure 7(b) illustrates a state in which the noise detected in the detection signal is sorted in descending order of correlation coefficient. As shown in the figure, it can be seen that the mechanical vibration in the x-axis direction has the largest correlation coefficient, followed by the mechanical vibration in the z-axis direction and the mechanical vibration in the y-axis direction, which have successively large correlation coefficients.

[0085] Figure 7(c) shows the correlation coefficients calculated for each channel as horizontal lines, and the average value of the correlation coefficient as a dot. As shown in the figure, it can be seen that the x-axis mechanical vibration flowing into channel 8 has the largest correlation value compared to the noise flowing into channels 2 through 7 and channels 9 through 10. From this, the user can see that the x-axis mechanical vibration provides the noise that has the greatest impact on the image.

[0086] Figure 8(a) shows the input signal in the time domain, Figure 8(b) shows the input signal in the frequency domain, and Figure 8(c) shows the signal in the frequency domain to which the Welch method has been applied. Figure 8(a) shows the detection signal, which is the output of the photomultiplier (PMT) included in the first detector, and the signals input in the x, y, and z channels when the magnetic field sensor detects the magnetic field, in the time domain.

[0087] Figure 8(b) shows the signal in the frequency domain after preprocessing the input signals from all channels, and Figure 8(c) shows the signal in the frequency domain after preprocessing the input signals from all channels using the Welch method. In Figure 8(b), the signal diagrams are shown in thick lines, making them difficult to distinguish, but by applying the Welch method, they can be shown more simply and clearly.

[0088] Although the present invention has been described with reference to the embodiments illustrated in the drawings to aid in understanding the invention, these are merely illustrative examples for implementation, and a person with ordinary skill in the art will understand that various modifications and equivalent other embodiments are possible therefrom. Accordingly, the true scope of technical protection of the present invention should be defined by the appended claims. [Explanation of Symbols]

[0089] 10: Noise effect evaluation device for microscope equipment 100: Microscope equipment 112: Charged particle source 120: Objective lens 122: Upper electrode 124: Lower electrode 150: Stage 180: Control Unit 212: Magnetic field sensor 214: Mechanical noise sensor (acoustic vibration) 216: Mechanical noise sensor (vibration at the top of the damper) 218: Mechanical noise sensor (vibration on the floor) 300: Processing Unit 310: Pre-processing unit 320: Signal Processing Unit 322: Front end section 610: First detector: 620: Second detector B: Charged particle beam V: Vacuum Chamber det1: First detection signal det2: Second detection signal n_mag: Magnetic field noise detection signal n_mech1: Vibration noise detection signal (acoustic vibration) n_mech2: Vibration noise detection signal (vibration at the top of the damper) n_mech3: Vibration noise detection signal (vibration on the floor) mon: Monitor signal

Claims

1. This is a device for evaluating the effects of noise on a microscope, and the above device is A microscope device that detects signals generated in a sample and forms a corresponding detection signal, Detect noise and form a corresponding noise detection signal. A noise sensor unit including a mechanical noise sensor for detecting mechanical noise and a magnetic field sensor for detecting magnetic field noise, A control unit that generates a monitor signal corresponding to the drive signal of the above-mentioned microscope device, The system includes a signal processing unit that receives one or more of the above-mentioned noise detection signals and monitor signals and performs signal processing, The above signal processing unit is a device that calculates the correlation between one or more of the above noise detection signal and the above monitor signal and the above detection signal.

2. The above-mentioned microscope devices include scanning electron microscopes (SEM), scanning transmission electron microscopes (STEM), scanning ion microscopes (SIM), focused ion beams (FIB), scanning helium ion microscopes (HIM), scanning probe microscopes (SPM), atomic force microscopes (AFM), and scanning tunneling microscopes. The apparatus according to claim 1, wherein the apparatus is one of the following: Microscope, STM.

3. The apparatus according to claim 1, wherein the mechanical noise sensor includes one or more of the following: a vibration sensor for detecting floor vibrations, a vibration sensor for detecting vibrations of the microscope apparatus, and an acoustic sensor for detecting vibrations in the acoustic (sound) band.

4. The apparatus according to claim 3, wherein the vibration sensor and the magnetic field sensor are three-axis sensors.

5. The microscope apparatus according to claim 1, wherein the microscope apparatus includes one or more of a scanning unit, a stigmeter, an alignment unit, a lens unit, an electron source, and a high voltage source and a current source for driving, the drive signal of the microscope apparatus is a drive signal of one or more of the scanning unit, stigmeter, alignment unit, lens unit, electron source, and a high voltage source and a current source for driving, and the monitor signal is a signal corresponding to the drive signal.

6. The microscope apparatus according to claim 1, further comprising one or more of a secondary electron detector (SED), a backscattered electron detector, a transmitted electron detector, a sample absorption current detector, an X-ray detector, and an electron energy loss spectrometer, wherein the detection signal further comprises a signal formed when one or more of the secondary electron detector (SED), backscattered electron detector, transmitted electron detector, sample absorption current detector, X-ray detector, and electron energy loss spectrometer detect the sample.

7. The apparatus according to claim 1, wherein the signal processing unit calculates a correlation coefficient between one or more of the noise detection signal and the monitor signal and the detection signal.

8. The apparatus according to claim 7, wherein the correlation coefficient calculated by the signal processing unit is one or more of the Pearson correlation coefficient, Spearman correlation coefficient, and distance correlation coefficient.

9. The apparatus according to claim 1, wherein the signal processing unit displays the noise, the monitor signal, and the detection signal in one or more of the time domain, the frequency domain to which Welch's method is applied, and the frequency domain.

10. The microscope apparatus according to claim 1, wherein the microscope apparatus positions a probe at any one point of the sample and detects a signal with a detector, or positions and scans a probe along any one edge of the sample and detects a signal, or positions and scans a region including at least one part of the sample, senses and detects a signal to form a detected signal.

11. The apparatus according to claim 1, wherein the processing unit extracts a signal within the frequency band set by the noise detection signal and the monitor signal, and calculates the correlation between the extracted signal and the detection signal.

12. The apparatus according to claim 11, wherein the processing unit includes a preprocessor that performs an FFT calculation on one or more of the input noise detection signals and monitor signals and on the detection signal, a filter unit that extracts signals within a set bandwidth, and an IFFT calculation unit that performs an IFFT (Inverse FFT) calculation on the output signal of the filter unit.

13. The apparatus according to claim 12, wherein the filter unit applies one or more of the low-pass filter (LPF), band-pass filter (BPF), and high-pass filter (HPF) to one or more of the provided noise detection signal and monitor signal to extract a signal within the set bandwidth.

14. The apparatus according to claim 11, wherein the set bandwidth is a frequency bandwidth that includes the frequency band of noise affecting the microscope image.

15. This is a method for evaluating the noise effect on a microscope device, and the above method is The above-mentioned microscope device detects secondary electrons formed in the above-mentioned sample and forms a corresponding detection signal. A noise sensor including a mechanical noise sensor and a magnetic field sensor detects noise acting on the microscope device and forms a noise detection signal; The steps include generating a monitor signal corresponding to the drive signal of the above-mentioned microscope device, A method comprising the step of a signal processing unit calculating the correlation between one or more of the noise detection signal and the monitor signal and the detection signal.

16. The above-mentioned microscope devices include scanning electron microscopes (SEM), scanning transmission electron microscopes (STEM), scanning ion microscopes (SIM), focused ion beams (FIB), scanning helium ion microscopes (HIM), scanning probe microscopes (SPM), atomic force microscopes (AFM), and scanning tunneling microscopes. The method according to claim 15, wherein the method is one of Microscope, STM, etc.

17. The method according to claim 15, wherein the mechanical noise sensor includes a vibration sensor for detecting floor vibrations, a vibration sensor for detecting vibrations of the microscope device, and an acoustic sensor for detecting vibrations in the acoustic (sound) band.

18. The method according to claim 17, wherein the vibration sensor and the magnetic field sensor are three-axis sensors.

19. The microscope apparatus described above includes one or more of a scanning unit, an astigmatism correction unit, an alignment unit, a lens unit, an electron source, and a high voltage source and a current source for driving, the drive signal of the microscope apparatus is the drive signal of one or more of the scanning unit, astigmatism correction unit, alignment unit, lens unit, electron source, and a high voltage source and a current source for driving, and the monitor signal is a signal corresponding to the drive signal, according to claim 15.

20. The method according to claim 15, wherein the microscope apparatus further includes one or more of a secondary electron detector (SED), a backscattered electron detector, a transmitted electron detector, a sample absorption current detector, an X-ray detector, and an electron energy loss spectrometer, and the detection signal further includes a signal formed when one or more of the secondary electron detector (SED), backscattered electron detector, transmitted electron detector, sample absorption current detector, X-ray detector, and electron energy loss spectrometer detect the sample.

21. The method according to claim 15, wherein the signal processing unit calculates a correlation coefficient between one or more of the noise detection signal and the monitor signal and the detection signal.

22. The method according to claim 21, wherein the correlation coefficient calculated by the signal processing unit is one or more of the Pearson correlation coefficient, Spearman correlation coefficient, and distance correlation coefficient.

23. The method according to claim 15, wherein the signal processing unit displays the noise, the monitor signal, and the detection signal in the time domain, the frequency domain using the Welch method, and one or more of the frequency domains.

24. The method according to claim 15, wherein the microscope apparatus positions a probe at any one point of the sample and detects a signal with a detector, or positions and scans a probe along any one edge of the sample and detects a signal, or positions and scans a region including at least one portion of the sample, senses and detects a signal to form a detected signal.

25. The method according to claim 15, further comprising a preprocessing step of extracting one or more of the provided noise detection signals and monitor signals and signals within the frequency band set by the detection signals.

26. The method according to claim 25, wherein the above preprocessing step includes an FFT calculation step in which one or more of the above noise detection signal and the above monitor signal are input and an FFT calculation is performed; a filter step in which signals within a set bandwidth are extracted; and an IFFT calculation step in which an IFFT (Inverse FFT) calculation is performed on the output signal of the filter unit.

27. The method according to claim 26, wherein the filtering step is performed by applying one or more of the provided noise detection signal and monitor signal to extract a signal within the set bandwidth by applying one or more of the low-pass filter (LPF), band-pass filter (BPF), and high-pass filter (HPF).

28. The method according to claim 25, wherein the set bandwidth is a frequency bandwidth that includes the frequency band of noise affecting the microscope image.

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