Dynamic visualization device and method for temperature wave

Abstract

To provide a dynamic visualization device and method for temperature wave that is suitable for designing sample shapes to enable more accurate thermal conductivity analysis as an in-STEM thermal transport evaluation method.SOLUTION: A dynamic visualization device includes: a dynamic visualization processing unit 225 which performs dynamic visualization processing using image frame data of a temperature wave imaged by a scanning transmission electron microscope (STEM); and a dynamic visualization processing management data unit 232 including an image frame management unit 233 which manages the image frame data of the temperature wave, a starting point phase setting unit 234 which defines a starting point phase of the temperature wave, an inter-image frame phase propagation management unit 235 which defines phase propagation between image frames used for synchronization processing between the adjacent image frames, an equiphase interval management unit 236 which defines an equiphase interval used in dynamic visualization processing within the image frame, and a specific color management unit 237 which defines a specific color corresponding to the equiphase interval within the image frame.SELECTED DRAWING: Figure 11

Description

[Technical field]

[0001] The present invention relates to an apparatus and method for dynamic visualization of temperature waves on the nano- and micro-scale, and more specifically to an apparatus and method for dynamic visualization of temperature waves suitable for use in nano-scale heat transport evaluation within a transmission electron microscope using an electron beam pulse and a micro-thermocouple. [Background technology]

[0002] In recent years, there has been a demand for the development of a new nanoscale thermal transport evaluation method for controlling the thermal properties of thermoelectric materials and for developing materials and devices for precise thermal control. The present inventor has been developing a scanning transmission electron microscope (STEM)-based thermal analytical microscopy (STAM) method that combines a nanothermocouple produced by electrolytic polishing with a local heating method using electron beam irradiation (see Patent Document 1 and Non-Patent Document 1). Here, electrolytic polishing refers to a method in which a product is placed on the positive side, a direct current is passed through an electrolyte, and the metal surface is dissolved to obtain a polishing effect. The STAM method utilizes the temperature rise caused by plasmon excitation during electron beam irradiation, and has the advantage of being able to evaluate the heat passing through the sample based on Fourier's law by two-dimensionally recording the steady-state temperature (thermoelectromotive force) corresponding to each heating position during STEM scanning.

[0003] On the other hand, it is known that temperature wave thermal analysis is effective for measuring the thermal diffusivity of small amounts of thin materials, mainly thin polymeric materials (see Patent Document 2 and Non-Patent Documents 2 and 3). In temperature wave thermal analysis, a weak temperature wave with an amplitude of 1°C or less is applied to a sample, its propagation is analyzed, and the thermal conductivity λ is obtained from the temperature amplitude attenuation, and the thermal diffusivity α is obtained from the phase delay measurement. Known methods of applying thermal stimuli include pulse (flash method), step (hot wire method), alternating current (temperature wave method), constant temperature rise (DSC), etc. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 6164735 [Patent Document 2] Patent No. 5489789 [Non-patent literature]

[0005] [Non-Patent Document 1] N. Kawamoto et al., Nano Energy, 52 323-328 (2018). [Non-Patent Document 2] Junko Morikawa, Toshimasa Hashimoto, "Measurement of Thermal Diffusivity and Thermal Conductivity Using Temperature Waves," Network Polymer, Vol. 34, No. 2 (2013) [Non-Patent Document 3] Toshimasa Hashimoto and Junko Morikawa, "Fourier Transform Temperature Wave Thermal Analysis", Thermal Measurements Vol. 27 No. 3, 141-151 (2000) Summary of the Invention [Problem to be solved by the invention]

[0006] In the conventional microthermal conductivity measuring device as shown in Patent Document 1 and Non-Patent Document 1, the temperature at each heating point in a steady state where the temperature has risen to the maximum is recorded two-dimensionally at the nano thermocouple contact point (fixed). When performing thermal conductivity analysis based on Fourier's law using the conventional microthermal conductivity measuring device, it is necessary to prepare a sample in which a reference material with a known thermal conductivity and a measurement sample are arranged in series, and the sample is required to be rod-shaped and have a thickness as uniform as possible, which is a problem that it takes time to prepare the sample. That is, in the STAM method, the amount of heat input by electron beam irradiation depends on the difference in sample thickness and the plasmon mean free path of the irradiated material, so that there are problems such as the need to prepare a sample with a uniform thickness as much as possible and the need to consider the input heat amount during analysis for heat transport evaluation. In addition, because the conventional STAM method involves static image analysis in a steady state, more detailed image analysis is required to design the sample shape for more accurate analysis of thermal conductivity.

[0007] On the other hand, although temperature wave thermal analysis has been used to measure the thermal diffusivity of small amounts of thin materials, mainly polymer thin films, there are no known examples of its application to nanoscale heat transport evaluation in a transmission electron microscope, and no known examples of its application to dynamic visualization of temperature waves by extending temperature wave thermal analysis. The present invention is devised to solve the above-mentioned problems, and aims to provide an apparatus and method for dynamic visualization of temperature waves that is suitable for use in designing sample shapes to perform more accurate thermal conductivity analysis as a method for evaluating heat transport within a STEM, based on temperature wave phase measurement that is relatively unaffected by changes in the amount of heat absorption due to differences in sample thickness and type of material. [Means for solving the problem]

[0008] The inventors conceived the present invention based on the idea that if temperature wave thermal analysis could be expanded to enable the dynamic visualization of temperature waves, it would be possible to visually analyze the flow of temperature waves on a thermocouple, and also to visualize the temperature detection part of the thermocouple that converts temperature into thermoelectromotive force, which would enable the design of sample shapes for more accurate thermal conductivity analysis, and would also be useful for the optimal design of micro-thermal conductivity measuring devices using thermocouples.

[0009] [1] According to the dynamic visualization device of the present invention, as shown in FIG. 11, for example, the device is provided with a dynamic visualization processing unit 225 that performs dynamic visualization processing of the temperature wave using image frame data of the temperature wave photographed by a transmission electron microscope (TEM) or a scanning transmission electron microscope (STEM), an image frame management unit 233 that manages the image frame data of the temperature wave, and a dynamic visualization processing data management unit 232 including, as parameters used in the dynamic visualization processing unit 225, a starting phase setting unit 234 that defines the starting phase of the temperature wave, an inter-image frame phase propagation management unit 235 that defines phase propagation between image frames used for synchronization processing between adjacent image frames, an equal phase interval management unit 236 that defines an equal phase interval used in the dynamic visualization processing within the image frame, and a specific color management unit 237 that defines a specific color corresponding to an equal phase interval in an image frame that is determined to be within the equal phase interval by the equal phase interval management unit 236.

[0010] [2] In the dynamic temperature wave visualization device [1] of the present invention, the image frame data of the temperature waves is preferably time-series image frame data captured at equal time intervals. [3] In the dynamic visualization device of temperature waves [1] or [2] of the present invention, preferably, the dynamic visualization processing unit 225 is further connected to an image frame storage unit 293 that stores a start image frame, a second image frame, an nth image frame (n=3, 4, ..., N), and a terminal image frame, and the image frame data of the temperature wave is the start image frame, the second image frame, the nth image frame (n=3, 4, ..., N), and a terminal image frame stored in the image frame storage unit 293. Here, N is the number of the terminal image frame that is the nth image frame that is subjected to the dynamic visualization processing, when the start image frame is used as the starting point. [4] In the dynamic temperature wave visualization device [1] of the present invention, preferably, the image frame management unit 233 manages the image frames required for the dynamic visualization process by interpreting the start image frame, the second image frame, the nth image frame (n=3, 4, ..., N) and the end image frame stored in the image frame memory unit 293 as the start image frame, the second start image frame and the nth start image frame (n=3, 4, ..., N) depending on the progress stage of the dynamic visualization process. [5] In the dynamic temperature wave visualization device [1] of the present invention, the origin phase setting unit 234 preferably defines origin phases to be used in the start image frame, the second start image frame, and the nth start image frame (n=3, 4, ..., N). [6] In the dynamic temperature wave visualization device [1] of the present invention, it is preferable that the inter-image frame phase propagation management unit 235 performs reinterpretation management of the corresponding areas of phase resulting from phase propagation between image frames, which are used in the start image frame, the second start image frame, and the image frames subsequent to the nth start image frame (n = 3, 4, ..., N), depending on the progress stage of the dynamic visualization process. [7] In the dynamic temperature wave visualization device [1] of the present invention, it is preferable that the corresponding region of the phase due to phase propagation between the image frames is determined from the phase propagation between adjacent image frames due to the propagation of the temperature wave. [8] In the dynamic temperature wave visualization device [1] of the present invention, it is preferable that the equal phase interval management unit 236 defines an equal phase interval to be used in the dynamic visualization process for a corresponding region of the phase resulting from phase propagation between image frames. [9] In the dynamic temperature wave visualization device [1] of the present invention, preferably, the specific color management unit 237 defines specific colors for each equal phase interval so that the propagation of the temperature wave can be visually recognized as a dynamic visualization process, and performs coloring processing on the image frames subsequent to each starting image frame for each corresponding region of the phase resulting from the phase propagation between image frames.

[10] In the dynamic temperature wave visualization device [1] of the present invention, preferably, the image frame memory unit 293 further has a dynamic visualization processed image frame memory unit that stores each image frame that has been subjected to dynamic visualization processing by the specific color management unit 237.

[11] In the dynamic visualization device of the present invention [1], it is preferable that the device further has a function of playing back each image frame that has been subjected to dynamic visualization processing and stored in the dynamic visualization processed image frame memory unit as a video of thermal diffusion using a temperature wave phase method.

[0011]

[12] According to the dynamic visualization method of the temperature wave of the present invention, for example, as shown in Figs. 13A, 13B, and 13C, image frame data of a temperature wave captured by a transmission electron microscope (TEM) or a scanning transmission electron microscope (STEM) is read (S422); The start image frame, the second image frame, the nth image frame (n=3, 4, ..., N), and the end image frame of the image frame data of the temperature wave are colored with a specific color corresponding to the start phase of the temperature wave, the phase propagation between the image frames, the equal phase intervals within the image frames, and the equal phase intervals (S424 to S432); For the image frame data group subsequent to the starting image of the image frame data of the temperature wave, a corresponding region of the phase caused by the phase propagation between the image frames is reinterpreted and managed, and the second starting image frame, the subsequent nth image frame (n=3, 4, ..., N), and the end image frame are colored with a specific color corresponding to the starting phase of the temperature wave, the phase propagation between the image frames, the equal phase interval within the image frame, and the equal phase interval (S434 to S444); For the image frame data group subsequent to the second start image of the image frame data of the temperature wave, the corresponding region of the phase resulting from the phase propagation between image frames is reinterpreted and managed, and the nth start image frame (n=3, 4, ..., N), the subsequent nth image frame (n=3, 4, ..., N), and the end image frame are colored with the start phase of the temperature wave, the phase propagation between image frames, the equal phase interval within the image frame, and a specific color corresponding to the equal phase interval (S446 to S456). Here, N is the number of the end image frame that is the target of the dynamic visualization process in the nth image frame for which the dynamic visualization process is performed, when the start image frame is used as the start point.

[0012]

[13] In the dynamic visualization method of temperature waves

[12] of the present invention, it is preferable to further store each image frame that has been subjected to dynamic visualization processing of the image frame data of the temperature waves colored by the specific color management unit 237.

[14] In the dynamic visualization method of temperature waves

[12] of the present invention, it is preferable that each image frame that has been subjected to the dynamic visualization process is reproduced as a video of thermal diffusion using a temperature wave phase method. Effect of the Invention

[0013] According to the dynamic visualization device and method of dynamic temperature waves of the present invention, by following the moving image (animation) of the present invention, it is possible to visually analyze the flow of temperature waves on a thermocouple, and also to visualize the temperature detection part of the thermocouple that converts temperature into thermoelectromotive force. [Brief description of the drawings]

[0014] [Figure 1] FIG. 1 is an overall configuration diagram of a dynamic temperature wave visualization device of the present invention and a micro thermal conductivity measurement device used in the prerequisites thereof. [Figure 2A] This is a photograph of a TEM holder with a nano thermocouple attached. [Figure 2B] This is a TEM image showing the nano thermocouple in contact with a sample. [Figure 2C]1 is a diagram for explaining the propagation of a temperature wave when a heating point of a sample is heated by an electron beam. [Figure 3A] FIG. 2 is an explanatory diagram of the principle of the temperature wave method used in the present invention, showing the frequency method. [Figure 3B] FIG. 1 is an explanatory diagram of the principle of the thermal wave method used in the present invention, showing the distance method of the heating position. [Figure 4] 1 is a flowchart illustrating a method for measuring micro-thermal conductivity used as a prerequisite of the present invention. [Diagram 5] FIG. 1 is a conceptual diagram illustrating a model of a configuration example that can determine the absolute value of the thermal conductivity of a conventional device. [Figure 6A] FIG. 1 is a conceptual diagram modeling an example of a configuration that can determine a relative value of thermal conductivity by a micro thermal conductivity measuring device used in the prerequisite of the present invention. [Figure 6B] This is an enlarged image of the thermocouple part taken with a STEM-HAADF (High-angle Annular Dark Field Scanning TEM). [Figure 6C] FIG. 2 is an explanatory diagram of heating by a pulsed electron beam of a predetermined frequency, showing an on-off waveform of the electron beam. [Figure 7] FIG. 2 is an explanatory diagram of heating by a pulsed electron beam of a predetermined frequency according to the frequency method, showing a temperature wave waveform measured by a thermocouple. [Figure 8] FIG. 1 is an explanatory diagram of heating by a pulsed electron beam of a predetermined frequency according to the frequency method, showing a phase image of a temperature wave measured by a thermocouple. [Figure 9] The relationship for evaluating thermal diffusivity is shown by the ratio of the phase delay θ of the temperature wave to the distance L from the heating position. [Figure 10] (A) is an explanatory diagram of heating by a pulsed electron beam of a specific frequency by the frequency method, showing the amplitude image of the temperature wave measured by a thermocouple. (B) shows the result of evaluating the amplitude of the temperature wave using the amplitude Q of the temperature wave and the distance L from the heating position. [Figure 11]2 is a functional block diagram of an information processing system that executes dynamic visualization processing using the analytical computer 60 shown in FIG. 1. FIG. [Figure 12] An exemplary computer program product 300 is illustrated in a functional block diagram of software for a computer shown in FIG. [Figure 13A] FIG. 12 is a flow chart of the software dynamic visualization process, which illustrates the processing of the starting image frame. [Figure 13B] The dynamic visualization process flow chart illustrates the processing of the second starting image frame. [Figure 13C] The flowchart of the dynamic visualization process illustrates the processing of the nth starting image frame (n=3, 4, . . . , N). [Figure 14A] This figure explains the dynamic observation state of temperature waves, and shows the case of 5 kHz. [Figure 14B] This figure explains the dynamic observation state of temperature waves, and shows the case of 10 kHz. [Figure 14C] This figure explains the dynamic observation state of temperature waves, and shows the case of 20 kHz. [Figure 15A] This figure explains the dynamic visualization process of temperature waves, and shows the area of ​​interest with the same phase in the initial state of the starting image frame of the video. [Figure 15B] This figure explains the dynamic visualization process of temperature waves, and shows an area in each image frame of the video that is in the same phase as the initial state of the starting image frame. [Figure 15C] This figure explains the dynamic visualization process of temperature waves, and shows an area of ​​phase that follows the same phase in the initial state in each image frame of the video. [Figure 15D] FIG. 13 is a diagram for explaining the dynamic visualization process of temperature waves, showing the completed state of the final image frame of the video. [Figure 16](A) is an explanatory diagram of heating of the entire sample by a pulsed electron beam of a specified frequency using the frequency method. (B) is an explanatory diagram of heating by enlarging the vicinity of the junction between the constantan and chromel of the thermocouple. (C) is an explanatory diagram of heating by enlarging the vicinity of the junction in Figure 16(B), with the brightness of the background region darkened. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] <<Definition of academic terms>> The following definitions are given for the academic terms used in this specification. Fourier's law describes the relationship between the amount of heat transferred in conductive heat transfer, and is expressed by the following equation.

number

[0016] Thermal conductivity is a coefficient that determines the speed at which thermal energy is transferred due to a temperature gradient. Specifically, when the amount of heat flowing per unit cross-sectional area per unit time (i.e., heat flux) is proportional to the temperature gradient, the thermal conductivity is the coefficient λ when the relationship between the heat flux J and the temperature (T) gradient is expressed by the following equation (2). J = -λgradT (2) If we express the relationship between temperature and heat in a material more generally using Gauss's divergence theorem, we can derive the following heat conduction equation. ∂q / ∂t=∇ 2 λT (3) Here, q is the amount of heat per unit volume, and it is assumed that there is no heat absorption or heat generation within the material. If the thermal conductivity λ is constant regardless of position or time, then equation (3) becomes ∂q / ∂t=λ∇ 2 T (4) It becomes.

[0017] Thermal diffusivity is a coefficient that determines the speed at which temperature travels through a temperature gradient; specifically, it is the proportionality coefficient α in the heat diffusion equation (equation (5)) derived by converting the heat quantity q to temperature T in equation (4). ∂T / ∂t=α∇ 2 T (5) The relationship between thermal conductivity λ and thermal diffusivity α is λ=α Cp ρ (6) These are related as follows, and together with ρ (density) and Cp (specific heat capacity at constant pressure), they are called the four thermal constants. When measuring, it is common to calculate either thermal conductivity or thermal diffusivity and convert it using equation (6). As with material diffusion, the longer the diffusion distance and the smaller the thermal diffusivity, the longer it takes to homogenize.

[0018] The thermal wave method is a method of measuring amplitude attenuation and phase delay by applying a weak AC stimulus to a sample using thermal energy. In order to popularize the measurement method, it was certified as standard in the field of thermal conductivity of plastics (TC-61) in 2008 as ISO22007-3 (phase analysis type for thin films), and further certified as amplitude analysis type as ISO-22007-6. In the case of an alternating temperature wave, the thermal diffusion length μ is defined as the following equation as a measure of the distance required for the temperature to be uniform. μ=√2α / ω (7)

[0019] <<Microthermal conductivity measuring device and method>> Next, the principle of micro thermal conductivity measurement, which is a prerequisite for use in the dynamic temperature wave visualization device and method of the present invention, will be described in detail. This micro thermal conductivity measuring device and method measures thermal diffusivity (α) using a temperature wave phase method, and is based on the following one-dimensional heat conduction equation.

number

number

[0020] In detecting the amplitude and phase of the temperature wave, the phase change Δθ occurring between the heating positions is given by the following equation:

number

[0021] FIG. 1 is a diagram showing the overall configuration of the dynamic temperature wave visualization device of the present invention and the micro thermal conductivity measurement device used in the preconditions thereof. In the figure, the dynamic temperature wave visualization device and micro-thermal conductivity measuring device comprises a transmission electron microscope 10, a temperature wave generating unit 20, a lock-in amplifier 30, a signal processing unit 40, an electron beam control and image processing system 50, and an analytical computer 60. The transmission electron microscope 10 includes an electrostatic shutter 12, a shutter driver 13, an electrostatic dose modulator (EDM) 14, a synchronization signal generator 15, an attenuation adjustment knob 16, and a control software unit 18. The temperature wave generating unit 20 is an enlarged view of the electron beam irradiated area of ​​the transmission electron microscope 10 shown in Fig. 1. The temperature wave generating unit 20 includes a sample 21, a pulsed electron beam 22, a constantan probe 23, and a chromel probe 24. Details will be described with reference to Figs. 2(A) and (B). In the lock-in amplifier 30, a constantan probe 23 and a chromel probe 24 of a thermocouple are connected to an input terminal, and a synchronization signal generating unit 15 is connected to a reference terminal.

[0022] The signal processing unit 40 includes an amplifier circuit, a filter circuit, and an attenuation circuit. The electron beam control and image processing system 50 may be, for example, a DigiScan (trademark) system provided by Gatan, Inc., a member company of the Electronic Instruments Business Group of AMETEK Corporation. An electron beam control signal and an image signal processed by a signal processing unit 40 are sent to an input terminal of the system, and an analysis computer 60 is connected to an output terminal. The electron beam control and image processing system 50 can measure the phase component of a temperature wave corresponding to the heating position of a heating point by a predetermined frequency using a STEM image obtained by the transmission electron microscope 10. The analytical computer 60 inputs the amplitude and phase of the temperature wave measured by the electron beam control and image processing system 50 and calculates the thermal conductivity of the sample 21. For such calculation, for example, a Gatan digital micrograph (trademark) may be used, in which a script for dividing the position information is actually written and converted into a thermal diffusivity image. Also, instead of using the analytical computer 60, a line profile of the phase image of the rod-shaped sample may be taken and the thermal diffusivity α may be calculated in Excel (trademark) according to the following formula: α=πf / (θ / L) 2 (16) The signal processing unit 40, the electron beam control and image processing system 50, and the analysis computer 60 are well known to those skilled in the art, or can be constructed by those skilled in the art without exerting any special inventive effort based on the descriptions in this specification and the drawings, and therefore detailed explanations and illustrations thereof will be omitted.

[0023] The Electrostatic Dose Modulator (EDM) 14 is a high-speed beam blanking system with electrostatic deflectors before the sample, including electronics and software control. With the EDM, the beam can be switched on or off in less than 50 ns, for example. This blanking speed is on the order of 10,000 to 100,000 times faster than the opening and closing speed of conventional electrostatic shutters 12, thus instantly improving the clarity of data acquired with fast exposure times. The EDM can also attenuate the electron irradiation without affecting the imaging conditions, thus giving TEM and STEM users great control over the dose to the sample. With the EDM, advanced applications such as time-dose structuring and STEM synchronization are available through state-of-the-art electronics and software add-ons.

[0024] The electron beam control and image processing system 50 can be connected to a STEM device, and a common user interface allows flexible setting of scan conditions and digitization tones to obtain an image suitable for an experiment. For example, the DigiScan (trademark) system allows up to four channels of synchronous input as standard, and is equipped with a function for setting the number of pixels in the X and Y directions up to a maximum of 32k x 32k pixels using analog or pulse input, but is not limited to this number of channels or pixels. The pixel dwell time can be set within the range of 50ns to 400ms per pixel. "Dwell time" refers to the time that the electron beam stays at one pixel when acquiring a STEM image by electron beam scanning. Dwell time is an index of the scanning speed of the electron beam. Multiplying the dwell time by the number of scan pixels in one horizontal line scan and adding the flyback time gives the scan time for one horizontal line scan, which is then multiplied by the number of vertical scans (horizontal scan lines) to calculate the acquisition time for one scanned image.

[0025] FIG. 2A is a photograph of a TEM holder with a nanothermocouple attached, and FIG. 2B is a TEM image showing the nanothermocouple in contact with a sample. As shown in paragraph numbers 0013 to 0019 of Patent Document 1, Cu was produced by an electrolytic polishing method using an H3PO4 aqueous solution 55 Ni 45 (mass%) (Constantan (trademark)) probe and Cr 10 Ni 90 (mass%) (Chromel (trademark)) probe, a Constantan - Chromel nanothermocouple was fabricated. As a result, the operating temperature range could be significantly expanded to -200°C < T < 800°C. Also, low thermal conductivity, large thermoelectric power, linear responsiveness, high resolution of the measured temperature reaching 10 -2 K, high responsiveness with a micro-sized junction realized, and since the thermocouple materials are a combination of non-magnetic materials, it became possible to introduce them into a strong magnetic field space such as inside a transmission electron microscope, and the performance could be improved in various aspects. Also, in this manufacturing method, depending on the application, a nanothermocouple can be fabricated using other thermocouple materials.

[0026] [Method for manufacturing a nanothermometer] By an electrolytic polishing method, Cu-Ni and Cr-Ni wire materials were each fabricated into microprobes with a tip diameter sharpened to 100 nm or less. Specifically, by precisely controlling the position of the microprobes using a piezo element inside a transmission electron microscope (TEM) and bringing the tip portions of these microprobes into contact with each other, and passing a current of about 10 μA between the probes, a junction with an extremely small contact resistance between the Constantan wire and the Chromel wire shown in Fig. 2(B) was formed, and a nanothermocouple, that is, a nanothermometer was fabricated. In the temperature wave dynamic visualization device configured in this way, by irradiating the converged electron beam onto the sample 21, heat is applied to the nanoscale region on the sample 21, and the heat input location and input amount can be controlled.

[0027] Figure 2(A) shows a photograph of the holder for mounting the nanothermocouple thus fabricated to measure the temperature of a minute region on a target sample in a TEM. Figure 2(A) also shows a schematic voltmeter for measuring the thermoelectromotive force generated in the nanothermocouple in this holder. What is important here is that since a large magnetic field (for example, 2 T in this embodiment) is applied to the sample position in the TEM, the holder material and the nanothermocouple must be made of a nonmagnetic material. This embodiment satisfies this condition by using chromel and constantan as the nano thermocouple material. Note that, although α-Al2O3 (hereinafter simply referred to as alumina), which can be used as a filler for composite materials, is used as the sample in this embodiment, it is of course possible to use various other materials as the sample to be measured.

[0028] [Heat application and temperature measurement at the nanoscale] The holder with the nanothermocouple attached as described above is placed inside the TEM, and the tip (junction) of the nanothermocouple is brought into contact with the sample as shown in FIG. 2(B). Here, an electron beam is irradiated near the tip of the thermocouple, and the thermoelectromotive force generated in the nanothermocouple changes depending on whether the electron beam is turned on or off. The electron gun used to irradiate the electron beam can be the same as that used in TEMs. In addition, the position where the nanothermocouple is brought into contact with the sample and the irradiation position of the focused electron beam can be accurately determined by observation using a TEM. In this way, the irradiation position can be determined by referring to the TEM image, allowing for a higher degree of freedom in measurements compared to methods in which the position where heat is applied is determined in advance and a specialized sample is prepared for that purpose.

[0029] An important point is that the location where heat is applied by the electron beam does not need to be spatially coincident with the location where the temperature is measured, and the electron beam may be irradiated to any point on the sample other than the contact point of the nano thermocouple, allowing the analysis of the thermal conduction in a desired section on the sample.

[0030] FIG. 2C is a diagram for explaining the propagation of a temperature wave when a heating point of a sample is heated by an electron beam. In a one-dimensional sample 21, the position where a thermocouple, a constantan probe 23 and a chromel probe 24, are connected to one end of the sample 21 is set as the origin, x=0, and the coordinates of the irradiation position of the pulsed electron beam 22 are x0, x1, and x2. i , t) (i=0, 1, 2), the amplitude attenuates with distance, but the following equation holds for the phase lag θ: θ1=k(x1-x0) (11) θ2=k(x2-x0) (12)

[0031] FIG. 3A is an explanatory diagram of the principle of the temperature wave method used in the present invention, showing the frequency control method, where (A) shows the heating position of the sample using a pulsed electron beam and the thermocouple attachment position, and (B) shows the phase delay θ, with the horizontal axis showing the square root of frequency (√f) and the vertical axis showing the phase. In Figure 3A, T M indicates the position where the thermocouple is attached to the sample, and the distance L indicates the distance between the heating position of the sample by the pulsed electron beam and the thermocouple attachment position. The phase lag θ increases at the rate of the square root of the frequency (√f) as the frequency f increases.

[0032] FIG. 3B is an explanatory diagram of the principle of the temperature wave method used in the present invention, showing the heating position distance method (Heating position control), in which (A) shows the heating position of the sample by the pulsed electron beam and the thermocouple attachment position, and (B) shows the phase delay θ, with the horizontal axis showing the square root of frequency (√f) and the vertical axis showing the distance L between the heating position of the sample by the pulsed electron beam and the thermocouple attachment position. In Fig. 3B(A), the heating position of the sample by the pulsed electron beam moves from a position close to the thermocouple attachment position to the other end of the sample. The phase lag θ increases in proportion to the increase in the distance L between the heating position of the sample by the pulsed electron beam and the thermocouple attachment position.

[0033] FIG. 4 is a flow chart for explaining the method for measuring the micro thermal conductivity used in the preconditions of the present invention. First, the sample 21 is placed in a TEM or STEM so that its TEM image or STEM image can be observed (S402). Next, the thermocouples (23, 24) are brought into contact with the sample 21 (S404). Next, at least one heating point on the sample 21 is heated using a pulsed electron beam of a predetermined frequency (f) (S406). The signal processing unit 40 detects multiple outputs of the thermocouples (23, 24) in response to the temperature rise at the contact point due to heating by the pulsed electron beam of a predetermined frequency (S408). If necessary, the positional and temporal relationship between the multiple output signals of the thermocouples (23, 24) by the signal processing unit 40 and the electron beam irradiated by the transmission electron microscope 10 is linked by the electron beam control and image processing system 50. The electron beam control and image processing system 50 measures the phase components of the temperature waves corresponding to the heating positions of the heating points at a predetermined frequency (S410). Using the phase component (θ) of the temperature wave generated by the pulsed electron beam, analytical computer 60 determines the thermal diffusivity (α) between the heated point and the contact point of the thermocouples (23, 24) on sample 21 from the distance (L) from the heated point to the contact point of the thermocouples (23, 24) on sample 21 using the following equation (S412). α=πf / (θ / L) 2

[0034] Preferably, the reliability of the dynamic temperature wave visualization method of the present invention can be improved by performing a calibration operation at regular intervals or when deemed necessary. In the calibration operation, a plurality of calibration outputs corresponding to the heating positions of a plurality of heating points from the thermocouples (23, 24) are detected in a state where the contact between the sample 21 and the thermocouples (23, 24) is released, and the influence of secondary electrons caused by the irradiation of the electron beam 22 on the plurality of heating points on the output of the thermocouples (23, 24) is cancelled by the plurality of calibration outputs.

[0035] A specific example of the device thus configured will be described. In Fig. 5, (A) is a conceptual diagram modeling an example of a configuration that can obtain the absolute value of thermal conductivity of a conventional device, and (B) is a line graph showing the relationship between the distance from the tip of the thermocouple to the electron beam irradiation position and the temperature rise at the tip of the thermocouple due to the irradiation. In Fig. 5(A), the sample 21 has a measured sample portion 212, a standard material portion 214, electron beam heat conversion portions 216a, 216b, and 216c, a thermal resistance portion 218, and a base portion 219. The measured sample portion 212 is a portion for measuring the thermal conductivity k of the sample. The standard material portion 214 is a standard material having a known thermal conductivity k. The electron beam heat conversion portions 216a, 216b, and 216c are "same sample" made of a heavy element (e.g., tungsten W) that has a high thermal conversion rate and a relatively large heat input when irradiated with an electron beam, and are provided in three separate locations to sandwich the standard sample portion 214 and the measured sample portion 212. The irradiation portions of the pulsed electron beam 22 are the electron beam heat conversion portions 216a, 216b, and 216c so that all the electron beam irradiation points are made of the same material so that the amount of heat absorbed when irradiated with an electron beam is the same at all irradiation points. The thermal resistance portion 218 is made of, for example, epoxy resin, and has a sufficiently large thermal resistance at the end opposite to the end that contacts the thermocouples 23 and 24. The base portion 219 supports the entire sample 21, and supports the electron beam heat conversion portions 216a, 216b, 216c, etc. and the thermocouples 23 and 24 via the thermal resistance portion 218.

[0036] In the apparatus thus configured, the electron beam is irradiated to points on the electron beam heat conversion parts 216a, 216b, and 216c on the sample placed in the TEM, whereby heat is applied to the points, causing the temperature to rise. A heat flow occurs due to the temperature gradient created by this. In FIG. 5(A), heat flow may occur to both the left and right sides of the electron beam irradiation point. However, the heat flow to the right side is almost blocked by the low thermal conductivity (i.e., high thermal resistance) of the thermal resistance part 218 (epoxy resin) for bonding the sample 21 to the pedestal part 219, and most of the heat flow flows to the left side of FIG. 5, and finally reaches the thermocouples 23 and 24 at the left end, causing a temperature change at this position. By providing the electron beam heat conversion parts 216a, 216b, and 216c, it is also possible to measure the thermal conductivity of a sample made of a light element that is difficult to convert into heat when irradiated with an electron beam, in which the measured sample part 212 is irradiated with an electron beam. Even if the measured sample part 212 is made of a light element such as carbon, which is a material that is more transparent to electron beams, such as carbon nanotubes, graphene, or epoxy resin, the sample is not directly irradiated with an electron beam, and therefore it is possible to overcome the problem of not being able to input a sufficient amount of heat due to poor heat absorption, which occurs when irradiating the sample directly with an electron beam.

[0037] In the configuration shown in FIG. 5(A), among the electron beam irradiation points (1) to (6), (2) and (3) are determined near the measurement sample on the upstream and downstream sides of the measurement sample portion 212 in terms of the direction of heat flow. Similarly, (4) and (5) are determined near the upstream and downstream sides of the standard material portion 214 in terms of the direction of heat flow. By irradiating this configuration with electron beams in the manner described above and measuring the temperature change at the left end portion with a thermocouple, the graph shown in FIG. 5(B) is obtained. Here, the electron beams are all irradiated to the portion made of tungsten, so the amount of heat absorbed by the sample by each irradiation is the same. In addition, the heat flow path length in the measurement sample and the standard material can be measured by observation with a TEM or the like. Therefore, it is possible to calculate ΔT sample / Δx sample, which is the slope of the line segment of the graph between (2) and (3), and ΔT standard material / Δx standard material, which is the slope of the line segment of the graph between (4) and (5) on this graph.

[0038] Now, using the known thermal conductivity k of the standard material, the thermal conductivity k of the sample can be expressed as k standard material = αk sample (13) Where: α = (ΔT sample / Δx sample) / (ΔT standard material / Δx standard material) (14) Since the numerator and denominator of the fractional expression representing α can be calculated as described above, the absolute value of the thermal conductivity k of the sample can also be calculated.

[0039] In this way, by estimating the heat energy generated during electron beam irradiation using a standard material with known thermal conductivity, it becomes possible to estimate the absolute value. That is, in order to make the heat flow pass through a material with known thermal conductivity (standard material part 214), the standard material part 214 sandwiched between electron beam heat conversion parts 216a, 216b, and 216c is provided in the passage of the heat flow.

[0040] In addition, in the above description, when the thermal conductivity of the electron beam thermal conversion parts 216a, 216b, and 216c sandwiching the measured sample part 212 in the relevant usage environment is known, the standard material part 214 can be made of the same material as the electron beam thermal conversion parts 216a, 216b, and 216c. In this way, when the standard material part 214 is also made of the same material as the electron beam thermal conversion parts 216a, 216b, and 216c, the structure on the left side of (3) in Figure 5(A) is simplified to an integrated structure made only of the same material as the electron beam thermal conversion parts 216a, 216b, and 216c. The above-mentioned formula for calculating the absolute value of the thermal conductivity can also be modified accordingly.

[0041] 6A is a conceptual diagram modeling an example of a configuration that can determine a relative value of thermal conductivity using a micro thermal conductivity measuring device used in the prerequisites of the present invention. The sample 21 is formed into a very fine or very thin shape (for example, as described above, it is processed to a thickness of 500 nm or less using a FIB (Focused Ion Beam)) and supported by a pedestal 219, so that there is no non-uniformity inside the sample. By configuring as shown in Fig. 6A, the one-dimensional heat flow model explained with reference to Fig. 5 is established. That is, not only is the end opposite to the end where the thermocouple is in contact thermally insulated by a means having a sufficiently large thermal resistance (for example, epoxy resin or vacuum, etc.), but in order to make the heat flow almost one-dimensional, it is necessary to surround the periphery with a material having a large thermal resistance, a vacuum, etc. so that there is practically no path of the heat flow in other directions (in Fig. 5(A) , the heat flow does not leak in the up and down directions in the middle of the path). Furthermore, the heat flow inside the sample also flows in a one-dimensional direction (that is, the inside of the sample has a one-dimensional structure in terms of thermal conductivity, and the heat flow does not meander or detour in an unpredictable manner inside the sample).

[0042] As another aspect in which the one-dimensional heat flow model is valid, even if there are regions with different thermal conductivities inside the sample, the last condition can be considered to be substantially satisfied if the distribution pattern of the regions is sufficiently uniform in comparison with the measurement resolution, or if, when focusing on a region through which most of the heat flow passes because the thermal conductivity is sufficiently greater than that of other regions, such a region provides a substantially uniform one-dimensional heat flow path.

[0043] 6B is an enlarged view of the thermocouple portion taken with a STEM-HAADF (High-angle Annular Dark Field Scanning TEM). A constantan probe 23 and a chromel probe 24, which are thermocouples, are connected to the ends of the sample 21. 6C is an explanatory diagram of heating by a pulsed electron beam of a predetermined frequency, showing the on-off waveform of the electron beam. Here, the frequency is 333 Hz, and the duty ratio of the on-off waveform is 1:1 (50%). Note that the predetermined frequency is not limited to 333 Hz, and an appropriate frequency f is selected and used depending on the material of the sample 21 and the length L of the measurement section, and may be, for example, a plurality of frequencies selected between 1 Hz and 500 kHz. Furthermore, the on-off duty ratio of the pulsed electron beam of a predetermined frequency (f) is not limited to 1:1, but may be selected, for example, between 1:9 and 9:1, and the pulse on-time width may be selected between 100 ns and 1 sec. The pulse on-time width is determined by the characteristics of the heating device, and for example, in the case of EDM, the minimum pulse on-time width is set to 100 ns.

[0044] Fig. 7 is an explanatory diagram of heating by a pulsed electron beam of a specific frequency by the frequency method, showing the temperature wave waveform measured by a thermocouple. Here, the cases of frequencies of 1 kHz, 5 kHz, 10 kHz, and 20 kHz are shown. As the frequency f increases, the phase delay θ increases. The signal-to-noise ratio decreased with increasing frequency f. Here, the phase delay θ is given by the following equation: θ=L√(πf / α) (15) Here, L is the distance from the heating position to the thermocouple, and α is the thermal diffusivity.

[0045] Figure 8 is an explanatory diagram of heating by a pulsed electron beam of a specific frequency by the frequency method, showing a phase image of a temperature wave measured by a thermocouple. Here, the cases of frequencies of 5 kHz, 10 kHz, and 20 kHz are shown, and for reference, a STEM image of a sample without heating by a pulsed electron beam is also shown. Here, the phase delay θ is represented by shading. Line profiles were acquired to quantitatively investigate the thermal diffusivity of the samples, as shown in Figure 8. The line profile provides information on the slope of the graph of phase delay θ versus distance L. That is, the ratio of θ to L was identified for each frequency of the irradiated pulsed electron beam. Here, in the case of 5 kHz, the phase lag θ at the heating point was 39°, and the phase lag θ at the sample end near the thermocouple was 18.5°. In the case of 10 kHz, the phase lag θ at the heating point was 54.5°, and the phase lag θ at the sample end near the thermocouple was 24°. In the case of 20 kHz, the phase lag θ at the heating point was 68°, and the phase lag θ at the sample end near the thermocouple was 25.5°.

[0046] Figure 9 shows the relationship for evaluating thermal diffusivity α based on the ratio of the temperature wave phase lag θ to the distance L from the heating position. Here, thermal diffusivity α is given by the following equation, which is a modification of equation (15). α=πf / (θ / L) 2 (16) In the case of 5 kHz, the regression equation is y = 0.0474x - 0.3666, θ / L = 0.0474, and the square of the correlation coefficient R is 2 The correlation coefficient R is 0.9975, which indicates a high correlation between the two variables x and y. In the case of 10 kHz, the regression equation is y = 0.0688x - 0.5183, θ / L = 0.0688, and the squared correlation coefficient R is 2 The correlation coefficient R is 0.9987, which shows a high correlation between the two variables x and y. In the case of 20 kHz, the regression equation is y = 0.0953x - 0.7280, θ / L = 0.0953, and the squared correlation coefficient R is 2 shows a high correlation between the two variables x and y, at 0.9977. As a result, the thermal diffusivity α(m 2 / s) is 6.99x10 at 5kHz -6 , 6.64x10 at 10kHz -6 , 6.92x10 at 20kHz -6 The values ​​are roughly equal to

[0047] FIG. 10(A) is an explanatory diagram of heating by a pulsed electron beam of a predetermined frequency by the frequency method, and shows the amplitude image of the temperature wave measured by a thermocouple. Here, the amplitude of the temperature wave in the case of 5 kHz was 8.0 μV when the heating point was at the thermocouple attachment position, 6.0 μV when the heating point was at the tip of the sample, and 6.7 μV when the heating point was at the midpoint between the thermocouple attachment position and the sample tip. The amplitude of the temperature wave in the case of 10 kHz was 6.1 μV when the heating point was at the thermocouple attachment position, 3.9 μV when the heating point was at the tip of the sample, and 4.6 μV when the heating point was at the midpoint between the thermocouple attachment position and the sample tip. The amplitude of the temperature wave in the case of 20 kHz was 4.0 μV when the heating point was at the thermocouple attachment position, 2.3 μV when the heating point was at the tip of the sample, and 3.1 μV when the heating point was at the midpoint between the thermocouple attachment position and the sample tip. Here, the amplitude T(x) of the temperature wave is given by the following equation:

number

[0048] Figure 10(B) shows the results of evaluating the amplitude of the temperature wave using the amplitude Q of the temperature wave and the distance L from the heating position. The theoretical values ​​and measured values ​​were compared for frequencies of 5 kHz, 10 kHz, and 20 kHz when the distance L from the thermocouple attachment position to the heating position ranged from 0 μm to 6 μm. When the frequency was 5 kHz and L was 0 μm, the amplitude of the temperature wave was maximum, with a theoretical value of 0.14 K and a measured value of 0.13 K. As the frequency decreased, the amplitude of the temperature wave became smaller, and when the frequency was 20 kHz and L was 8 μm, the amplitude of the temperature wave was minimum, with a theoretical value of 0.035 K and a measured value of 0.04 K.

[0049] <<Device and method for dynamic visualization of temperature waves>> Next, an example of the hardware configuration of the analysis computer 60 used in the dynamic temperature wave visualization device and method of the present invention will be described. Fig. 11 is a functional block diagram of an information processing system that executes dynamic visualization processing using analysis computer 60 shown in Fig. 1. The information processing system of Fig. 11 can be implemented using all or a part of computing device 200 as analysis computer 60. In a very basic configuration 201, a computing device 200 typically includes one or more processors 210 and a system memory 220. A memory bus 230 may be used for communication between the processor 210 and the system memory 220.

[0050] Depending on the desired configuration, the processor 210 may be of any type, including but not limited to a microprocessor (μP), a microcontroller (μC), a digital signal processor (DSP), or a combination thereof. The processor 210 may include another level of caching, such as a level 1 cache 211 and a level 2 cache 212, a processor core 213, and registers 214. An exemplary processor core 213 may include an arithmetic logic unit (ALU), a floating point unit (FPU), a digital signal processing core (DSP core), or any combination thereof, etc. An exemplary memory controller 215 may also be used with the processor 210, or in some implementations, the memory controller 215 may be an internal part of the processor 210.

[0051] Depending on the desired configuration, the system memory 220 can be of any type, including but not limited to, volatile memory (such as RAM), non-volatile memory (such as ROM, flash memory, etc.), or any combination thereof. The system memory 220 can include an operating system 221, one or more applications 222, and a dynamic visualization processing management data section 232. The applications 222 can include a TEM linking section 223, a microthermal conductivity measurement section 224, and a dynamic visualization processing section 225. The TEM link unit 223 has a program required for reading image data from the connected TEM 292, and may also manage management data required for imaging, such as specifying the magnification of an image captured by the TEM 292. The micro thermal conductivity measuring unit 224 is a program required to execute the micro thermal conductivity measurement of the sample placed inside the above-mentioned TEM 292. The micro thermal conductivity measuring unit 224 uses the phase component (θ) of the temperature wave generated by the pulsed electron beam to obtain the thermal diffusivity (α) between the heating point and the contact point of the thermocouples (23, 24) on the sample 21 from the following equation (S412), based on the distance (L) from the heating point to the contact point of the thermocouples (23, 24) on the sample 21. α=πf / (θ / L) 2 The dynamic visualization processing unit 225 is a program that performs dynamic visualization processing using image data captured by the above-mentioned TEM 292, and will be described in detail later.

[0052] The dynamic visualization processing management data unit 232 may include an image frame management unit 233, a starting phase setting unit 234, an inter-image frame phase propagation management unit 235, an equal phase interval management unit 236, and a specific color management unit 237 as parameters used in the dynamic visualization processing unit 225. The image frame management unit 233 manages image frames required for dynamic visualization processing by interpreting the start image frame 294, the second image frame 295, the nth image frame 296 (n=3, 4, ..., N), and the end image frame 298 stored in the image frame storage unit 293 as a start image frame, a second start image frame, and an nth start image frame 296 (n=3, 4, ..., N) according to the progress stage of the dynamic visualization processing. The image frame management unit 233 also manages the storage of each image frame that has been subjected to dynamic visualization processing in the dynamic visualization processed image frame storage unit 299. Here, N is the image frame number of the end image frame 298 when the start image frame 294 is taken as the starting point, but in the dynamic visualization processing, it is not necessarily required to perform dynamic visualization processing up to the image frame of the end image frame 298 as the nth image frame 296, and it may be the number of the end image frame that is the target of dynamic visualization processing of the nth image frame that is subjected to dynamic visualization processing.

[0053] The starting point phase setting unit 234 defines starting point phases used in the starting point image frame, the second starting point image frame, and the nth starting point image frame 296 (n=3, 4, ..., N). The starting point phase may be, for example, 1°, but is not limited to this, and an appropriate value may be selected as long as it has an appropriate accuracy as the start of propagation of a temperature wave in dynamic visualization processing. The inter-image frame phase propagation management unit 235 performs management of the corresponding region of the phase caused by the phase propagation between image frames, which is used in the image frames subsequent to the start image frame, the second start image frame, and the n-th start image frame 296 (n=3, 4, ..., N) according to the progress stage of the dynamic visualization process. The corresponding region of the phase caused by the phase propagation between image frames is determined from the phase propagation between adjacent image frames caused by the propagation of the temperature wave.

[0054] The equal phase interval management unit 236 defines an equal phase interval used in dynamic visualization processing for a corresponding region of the phase caused by phase propagation between image frames. The equal phase interval may be, for example, 5°, but is not limited to this, and an appropriate value may be selected as long as the accuracy is such that the propagation of the temperature wave can be visually recognized in dynamic visualization processing. The specific color management unit 237 determines a specific color for each equal phase interval so that the propagation of the temperature wave can be visually recognized as a dynamic visualization process, and performs coloring process on the image frames subsequent to each starting image frame for each corresponding region of the phase resulting from the phase propagation between image frames. Preferably, each image frame that has been subjected to the dynamic visualization process by the specific color management unit 237 is stored in the dynamic visualization processed image frame storage unit 299 via the image frame management unit 233.

[0055] The computing device 200 may have additional features or functionality and additional interfaces to facilitate communication between the basic configuration 201 and any necessary devices and interfaces. For example, a bus / interface control 240 may be used to facilitate communication between the basic configuration 201 and one or more data storage devices 250 via a storage interface bus 241. The data storage device 250 may be a removable storage device 251, a non-removable storage device 252, or a combination thereof. Examples of removable and non-removable storage devices include magnetic disk drives such as floppy disk drives and hard disk drives (HDDs), optical disk drives such as compact disk (CD) drives or digital versatile disk (DVD) drives, solid state drives (SSDs), and tape drives. Exemplary computer storage media may include volatile and non-volatile, removable and fixed media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules, or other data.

[0056] System memory 220, removable storage 251, and non-removable storage 252 are all examples of computer storage media. Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVDs) or other optical storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices. Any such computer storage media that can be used to store desired information and that can be accessed by computing device 200 can be part of device 900.

[0057] The computing device 200 may also include an interface bus 242 to facilitate communication from various interface devices (eg, output interfaces, peripheral interfaces, and communications interfaces) to the basic configuration 201 via a bus / interface control unit 240 . In the output device 260, the image processing unit 261 and the audio processing unit 262 may be configured to communicate with various external devices, such as a display device 291 or speakers, via one or more AV ports 263.

[0058] The exemplary peripheral interface 270 includes a serial interface controller 271 or a parallel interface controller 272 that may be configured to communicate with external devices such as input devices (e.g., keyboard, mouse, pen, voice input device, touch input device, etc.) The peripheral interface 270 may be configured to communicate with an external database device containing a TEM 292 and an image frame store 293 via an I / O port 273. The exemplary communications device 280 includes a network controller 281, which may be configured to facilitate communications with one or more other computing devices 290 over a network communications link via one or more communications ports 282. The image frame storage unit 293 includes a starting image frame 294, a second image frame 295, an nth image frame 296 (n=3, 4, ..., N), an ending image frame 298, and a dynamic visualization processed image frame storage unit 299. The image frame data of temperature waves stored in the image frame storage unit 293 is time-series image frame data captured at equal time intervals.

[0059] A network communication link may be an example of a communication medium. A communication medium may typically be embodied by computer-readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and may include any information delivery media. A "modulated data signal" may be a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media may include wired media, such as a wired network or direct-wired connection, and wireless media, such as acoustic, radio frequency (RF), microwave, infrared (IR) and other wireless media. As used herein, the term computer-readable media may include both storage media and communication media.

[0060] Computing device 200 may be implemented as part of a small form factor portable (or mobile) electronic device such as a mobile telephone, a personal data assistant (PDA), a personal media player device, a wireless web watch device, a personal computer, a headset device including any of the above functionality, a special purpose device, or a hybrid device. Computing device 200 may also be implemented as a personal computer, including both laptop and non-laptop computer configurations.

[0061] Figure 12 is a functional block diagram of software for the computer shown in Figure 11, illustrating an exemplary computer program product 300. The program bearing medium 302, which may be implemented as a computer readable medium 306, a recordable medium 308, a communication medium 309, or a combination thereof, has program instruction storage 304 that may be configured to execute all or a portion of the processing of a processing unit.

[0062] The program commands stored in the program command storage unit 304 include, for example, a function (310) for reading observation condition settings such as the magnification of an image captured by a TEM, a microthermal conductivity measurement unit (320) for measuring the thermal diffusivity (α) of a sample using a temperature wave phase method, a function (330) for reading designated image frame data from the image frame storage unit 293 into the dynamic visualization processing unit 225 via the image frame management unit 233, a function (340) for reading a setting value of the starting phase, a setting value of phase propagation between image frames, a setting value of equal phase intervals, and a designation of a specific color from the dynamic visualization processing management data unit 232, and a processing unit 225 (350) for performing dynamic visualization processing of the read image frame data using various parameters for dynamic visualization processing read in the dynamic visualization processing management data unit 232. A function (360) for playing a video of thermal diffusion in a sample using the temperature wave phase method from the dynamic visualization processed image frame 299 on which dynamic visualization processing has been performed. The image frame data of temperature waves stored in the image frame memory unit 293 is time-series image frame data captured at equal time intervals. Therefore, by using the setting value of the starting phase and the setting value of the phase propagation between image frames, the time difference between different capture times can be used for phase propagation between image frames, making it possible to synchronize the time-series image frame data.

[0063] Fig. 13A is a flow chart of the dynamic visualization process of the software shown in Fig. 12, and explains the processing of the start image frame. Fig. 13B explains the processing of the second start image frame. Fig. 13C explains the processing of the n-th start image frame. First, Fig. 13A shows a dynamic visualization method of temperature waves (S420). The dynamic visualization processing unit 225 reads out a starting image frame of a moving image from the image frames stored in the image frame storage unit 293 (S422). The dynamic visualization processing unit 225 reads out a setting value of a starting phase, a setting value of phase propagation between image frames, a setting value of equal phase interval, and a designation of a specific color from the dynamic visualization processing management data unit 232, and colors an area indicating the starting phase in the phase distribution image of the starting image frame with the specific color (S424). The starting image frame that has been subjected to the dynamic visualization processing is recorded in the dynamic visualization processed image frame storage unit 299.

[0064] Next, the dynamic visualization processing unit 225, in accordance with the specifications of the image frame management unit 233, colors the area corresponding to the starting phase specified by the starting phase setting unit 234 for the image frame adjacent to the starting image frame with a specific color specified by the specific color management unit 237, and records it in the dynamic visualization processed image frame memory unit 299 as a subsequent frame of the video (S426). Next, the dynamic visualization processing unit 225 calculates, for the image frames sequentially adjacent to the adjacent image frame, an area equivalent to the start phase specified by the start phase setting unit 234, based on the equal phase interval specified by the equal phase interval management unit 236 and the sequential number m (m=1, 2, ...) of the sequentially adjacent image frames, in accordance with the specification by the image frame management unit 233 (S428). The dynamic visualization processing unit 225 colors the area equivalent to the start phase of the sequentially adjacent image frame with a specific color, in accordance with the specification by the specific color management unit 237, and records it in the dynamic visualization processed image frame storage unit 299 as a subsequent frame of the moving image (S430). In this way, the dynamic visualization processing unit 225 colors the area corresponding to the starting phase with a specific color up to the terminal image frame of the video, and records it in the dynamic visualization processed image frame memory unit 299 as the terminal image frame of the video (S432).

[0065] 13B, the dynamic visualization processing unit 225, in accordance with the designation by the image frame management unit 233, designates a subsequent phase to the area indicating the origin phase designated by the origin phase setting unit 234 for the phase distribution image of the second start image frame (S434). The dynamic visualization processing unit 225 reads the setting value of the origin phase, the setting value of phase propagation between image frames, the setting value of equal phase interval, and the designation of the specific color from the dynamic visualization processing management data unit 232, and colors the area indicating the subsequent phase in the phase distribution image of the second start image frame with the second specific color (S436). Next, in accordance with the specifications of the image frame management unit 233, the dynamic visualization processing unit 225 colors the area corresponding to the subsequent phase determined from the starting phase specified by the starting phase setting unit 234 and the equal phase interval specified by the equal phase interval management unit 236 for the image frame adjacent to the second starting image frame with a second specific color in accordance with the specifications of the specific color management unit 237, and records it as a subsequent frame of the video (S438).

[0066] Next, the dynamic visualization processing unit 225 calculates, for the image frames sequentially adjacent to the adjacent image frame, an area corresponding to a subsequent phase determined from the start phase specified by the start phase setting unit 234 and the equal phase interval specified by the equal phase interval management unit 236, based on the equal phase interval and the sequential number m (m=1, 2, ...) of the sequentially adjacent image frames, in accordance with the specification by the image frame management unit 233. The dynamic visualization processing unit 225 colors the area corresponding to the subsequent phase of the sequentially adjacent image frames with a second specific color, and records it in the dynamic visualization processed image frame storage unit 299 as a subsequent frame of the moving image (S442). In this way, the dynamic visualization processing unit 225 colors the area corresponding to the subsequent phase up to the terminal image frame of the video in a second specific color, and records it in the dynamic visualization processed image frame memory unit 299 as the terminal image frame of the video (S444).

[0067] 13C, the dynamic visualization processing unit 225 specifies a phase subsequent to the region indicating the origin phase in the phase distribution image of the nth start image frame as the target phase region of the phase distribution image to be processed next (S446) in accordance with the specification of the image frame management unit 233. The dynamic visualization processing unit 225 reads the setting value of the origin phase, the setting value of phase propagation between image frames, the setting value of equal phase interval, and the specification of a specific color from the dynamic visualization processing management data unit 232, and colors the region indicating the subsequent phase in the phase distribution image of the nth (n=3, 4, ..., N) start image frame with the nth specific color (S448). Next, in accordance with the specifications of the image frame management unit 233, the dynamic visualization processing unit 225 colors the area corresponding to the subsequent phase determined from the starting phase specified by the starting phase setting unit 234 and the equal phase interval specified by the equal phase interval management unit 236 for the image frames adjacent to the nth starting image frame with the nth specific color, and records it in the dynamic visualization processed image frame memory unit 299 as a subsequent frame of the video (S450).

[0068] Next, the dynamic visualization processing unit 225 calculates, for the image frames sequentially adjacent to the adjacent image frame, an area corresponding to a subsequent phase determined from the start phase specified by the start phase setting unit 234 and the equal phase interval specified by the equal phase interval management unit 236, based on the equal phase interval and the sequential number m (m=1, 2, ...) of the sequentially adjacent image frames, in accordance with the specification by the image frame management unit 233 (S452). The area corresponding to the subsequent phase of the sequentially adjacent image frame is colored with an nth specific color, and recorded as a subsequent frame of the video (S454). In this way, the dynamic visualization processing unit 225 colors the area corresponding to the subsequent phase up to the terminal image frame of the video with the nth specific color, and records it in the dynamic visualization processed image frame memory unit 299 as the terminal image frame of the video (S456).

[0069] Next, a process of performing dynamic visualization processing on a diagram showing a dynamic observation state of a specific temperature wave will be described according to the flowchart of the dynamic visualization processing shown in FIG. 13A to FIG. 13C. 14A to 14C are diagrams for explaining the dynamic observation state of temperature waves, where (A) shows the case of 5 kHz, (B) shows 10 kHz, and (C) shows the case of 20 kHz. In Fig. 14A to 14C, the phase image in which the arrival time from the heating position to the temperature measurement position (thermocouple junction) is recorded is colored with the same phase bands, and the temperature waves can be dynamically observed by frame-by-frame advancement at equal time intervals. The number of image frames in Fig. 14A is 36, the number of image frames in Fig. 14B is 49, and the number of image frames in Fig. 14C is 63. In each image frame, areas with similar colors have similar phase delays. The phase delays increased quantitatively with increasing frequency. Thus, the width of the color bands decreases with increasing frequency. At the interface between the sample and the thermocouple, the delay in heat transfer is reflected in the thermal resistance. Therefore, the junction position of the thermocouple (including the thermoelectric material) can be directly observed by dynamic observation based on the phase image.

[0070] Next, a processing procedure of the dynamic visualization method of temperature waves according to the present invention will be described. Fig. 15 is a diagram for explaining the dynamic visualization process of temperature waves, where (A) shows the area of ​​the same phase to be noted in the initial state of the starting image frame of the video, (B) shows the area of ​​the same phase as the initial state of the starting image frame in each frame of the video, (C) shows the area of ​​the phase following the initial state in each frame of the video, and (D) shows the completed state of the processing of the final frame of the video. Here, the creation of a temperature wave phase image for dynamic observation will be explained using 5 kHz as shown in Fig. 14A.

[0071] The dynamic observation of the temperature wave is stored frame by frame in an image frame store 293 (eg, Gatan Digital Micrograph) of the analysis computer 60. First, as shown in Fig. 15A, for a phase distribution image, which is time information of an image frame that is the starting image frame of a moving image, here frame 8 (abbreviated as F8), an area showing the same phase (around 18°) on the image frame stored in the image frame storage unit is colored in a specific color, for example, yellow. For example, the colored area is a 5° phase band (area from 18 to 23°) on the sample of F8 colored in yellow gradation. Next, as shown in Figure 15B, the area to be colored a specific color, for example yellow, is shifted at equal phase intervals (1° in this case) from F9 (19-23° area) to F10 (20-24° area) to F11 (21-25° area) ... in the image frames adjacent to the starting image frame, and recorded as one frame of a video. In this manner, the video is colored in a specific color, for example, yellow, up to the final image frame F39.

[0072] As shown in FIG. 15C, the target phase region of the phase distribution image to be processed next is the subsequent phase adjacent to the same phase (near 18°) of the image frame that is the starting image frame of the above-mentioned moving image. Here, for the image frame F9 adjacent to the starting image frame, the region showing the same starting phase (near 18°) as the starting image frame F8 is colored with a second specific color different from the above specific color, for example, red. For example, the colored region is a 5° phase band (18 to 23° region) on the sample of F9 colored with a red gradation. Here, the image frame F9 adjacent to the starting image frame is called the second starting image frame. Next, the area to be colored a second specific color, for example red, is shifted at equal phase intervals (1° in this case) from F10 (19-23° area) → F11 (20-24° area) → F12 (21-25° area) ... in the image frames adjacent to the second starting image frame, and recorded as one frame of a video. Therefore, when looking at the color distribution of the image frame at this processing stage, for example, for image frame F12, the area from 22 to 26° is colored in a first specific color, yellow, and the area with a phase of 19 to 23° is colored in a second specific color, red. In this manner, the video is colored in the second specific color, for example, red, up to the final image frame F39.

[0073] The target phase region of the phase distribution image to be processed next is the subsequent phase adjacent to the same phase (near 18°) of the image frame that is the second start image frame of the above-mentioned video. Here, the image frame F10 adjacent to the second start image frame is called the third start image frame. For the image frame F10 adjacent to the second start image frame, the region showing the same start phase (near 18°) as the second start image frame F9 is colored with a second specific color different from the above specific color, for example, green. For example, the colored region is a 5° phase band (18 to 23° region) on the sample of F10 colored with a green gradation. Next, the area to be colored a third specific color, for example green, is shifted at equal phase intervals (1° in this case) from F11 (19-23° area) to F12 (20-24° area) to F13 (21-25° area) ... in the image frames adjacent to the third starting image frame, and recorded as one frame of a video. In this manner, the video is colored in a third specific color, for example, green, up to the final image frame F39.

[0074] In this way, the target phase region of the phase distribution image to be processed is repeated for the subsequent phases adjacent to the same phase (near 18°) of the image frame that will be the subsequent starting image frame, and the image frames that will be the subsequent starting image frames are colored with different specific colors in sequence. Then, as shown in FIG. 15D, the image frames are colored with the specific colors in the same phase band of phase band width Δq (for example, 5°) on the sample in sequence up to the end image frame F39 of the video, similarly to the first specific color and the second specific color, and each processed image frame is saved.

[0075] Thereafter, frames are recorded in which the colored parts of the same phase band are shifted, for example, every 1°, until finally successive image frames with equal phase intervals, as shown in FIG. 14A, are prepared. By animating the prepared successive image frames using animation software, such as gif animation, it is possible to dynamically observe how the same phase band of the temperature wave moves. By observing this animation, it is possible to visually evaluate how the temperature wave propagates even in a non-uniform sample. Furthermore, the temperature gradient can be visually determined based on the spatial width of the same phase band, and therefore regions with high and low thermal diffusivity can be visually determined. Furthermore, in the dynamic observation processing unit, the range of the same phase band and the number of frames can be freely changed as necessary. In general, the higher the measurement frequency of the phase distribution image, the higher the phase resolution contained in the phase distribution image, so that the number of frames can be increased.

[0076] In addition, the phase distribution image records the time it takes for the temperature wave to reach the electron beam irradiation position, with the thermocouple at the center of the temperature detection section. On the other hand, by tracking the temperature wave video using the dynamic visualization method of temperature waves of the present invention, not only can the flow of the temperature wave on the thermocouple as shown in Figure 1 be visually analyzed, but the temperature detection section of the thermocouple that converts temperature into thermoelectromotive force can also be visualized as shown in Figure 3. Figure 16(A) is an explanatory diagram of heating of the entire sample by a pulsed electron beam of a specified frequency using the frequency method, Figure 16(B) is an explanatory diagram of heating by enlarging the vicinity of the junction between the constantan and chromel of the thermocouple, and Figure 16(C) is an explanatory diagram of heating by enlarging the vicinity of the junction in Figure 16(B), with the brightness of the background area darkened.

[0077] As described above, in the dynamic temperature wave visualization device and method of the present invention, a thermocouple is used for temperature detection, but the present invention is not limited to this and can also be applied to the analysis of the junction interface of a thermoelectric material that generates a thermoelectromotive force due to a temperature difference. In addition, the dynamic temperature wave visualization device and method of the present invention can be applied to phase distribution images of temperature waves measured in each frequency band from 100 Hz to 500 kHz, and can also visualize the joint interface (power generation part) that cannot be identified in a normal TEM image. [Industrial Applicability]

[0078] The dynamic temperature wave visualization device and method of the present invention are suitable for use in designing the shape of a sample to perform a more accurate analysis of the thermal conductivity of a sample used in a STEM heat transport evaluation method, based on temperature wave phase measurement, which is relatively unaffected by changes in the amount of heat absorption due to differences in sample thickness or type of material. Furthermore, the dynamic temperature wave visualization device and method of the present invention can be applied to the evaluation of thermal resistance at voids, grain boundaries, and contact interfaces within materials, and can be used to analyze the heat transport state and temperature wave propagation path of insulators, semiconductors, metals, nanowires, nanotubes, particles, thermally conductive fillers, composite heat dissipation materials, etc. [Explanation of symbols]

[0079] 10 Transmission Electron Microscopy (STEM) 12 Electrostatic Shutter 14 Electrostatic Dose Modulator (EDM) 20 Temperature wave generator 21 Sample 22 Pulsed electron beam 23 Constantan probe (thermocouple) 24 Chromel probe (thermocouple) 30 Lock-in amplifier 40 Signal Processing Section 50 Electron beam control and image processing system (DigiScan) 60 Analysis Computer

Claims

1. A dynamic visualization processing unit that performs dynamic visualization processing on temperature waves using image frame data of temperature waves captured by a transmission electron microscope (TEM) or scanning transmission electron microscope (STEM), An image frame management unit that manages the image frame data of the temperature wave, The parameters used in the dynamic visualization processing unit are: A starting phase setting unit that defines the starting phase of the temperature wave, An image frame phase propagation management unit that defines the phase propagation between image frames used for synchronization processing between adjacent image frames, An equiphase interval management unit that defines equiphase intervals used in dynamic visualization processing within an image frame, and The above-mentioned equal-phase-interval management unit includes a specific color management unit that defines specific colors corresponding to equal-phase intervals within image frames that are deemed to be within equal-phase intervals, Management data unit for dynamic visualization processing, A dynamic visualization device for temperature waves, equipped with [specific features / features].

2. The aforementioned temperature wave image frame data is a time-series image frame data taken at equal time intervals. The dynamic visualization device for temperature waves according to claim 1.

3. Furthermore, the dynamic visualization processing unit is connected to an image frame storage unit that stores the starting image frame, the second image frame, the nth image frame (n = 3, 4, ..., N), and the ending image frame. The image frame data of the temperature wave is stored in the image frame storage unit and consists of a start image frame, a second image frame, an nth image frame (n = 3, 4, ..., N), and an end image frame. N is the number of the nth image frame that undergoes dynamic visualization processing, starting from the initial image frame, and is the last image frame that is the target of dynamic visualization processing. A dynamic visualization device for temperature waves according to claim 1 or 2.

4. The image frame management unit manages the image frames necessary for dynamic visualization processing by interpreting the initial image frame, second image frame, nth image frame (n=3, 4, ..., N), and final image frame stored in the image frame storage unit as the initial image frame, second initial image frame, and nth initial image frame (n=3, 4, ..., N) according to the progress of the dynamic visualization processing. The dynamic visualization device for temperature waves according to claim 3.

5. The starting phase setting unit defines the starting phase used in the starting image frame, the second starting image frame, and the nth starting image frame (n = 3, 4, ..., N). The dynamic visualization device for temperature waves according to claim 3.

6. The aforementioned inter-image frame phase propagation management unit manages the reinterpretation of the corresponding region of phase caused by inter-image frame phase propagation, used in the initial image frame, the second initial image frame, and subsequent image frames following the nth initial image frame (n = 3, 4, ..., N), according to the progress of the dynamic visualization process. The dynamic visualization device for temperature waves according to claim 3.

7. The dynamic visualization apparatus for temperature waves according to claim 5, wherein the corresponding region of phase resulting from phase propagation between image frames is determined from the phase propagation between adjacent image frames resulting from the propagation of the temperature wave.

8. The aforementioned equiphase spacing management unit defines equiphase spacings used for dynamic visualization processing for the corresponding region of phase caused by phase propagation between image frames. The dynamic visualization device for temperature waves according to claim 3.

9. The aforementioned specific color management unit, as a dynamic visualization process, determines specific colors at equal phase intervals so that the propagation of the temperature wave can be visually observed, and performs color processing on each image frame following the starting image frame for each corresponding region of phase caused by phase propagation between image frames. The dynamic visualization device for temperature waves according to claim 3.

10. The image frame storage unit further includes a dynamically visualized image frame storage unit that stores each image frame that has been dynamically visualized by the specific color management unit. The dynamic visualization device for temperature waves according to claim 3.

11. Furthermore, it has a function to play back each dynamically visualized image frame stored in the dynamically visualized image frame storage unit as a video of thermal diffusion using the temperature wave phase method. The dynamic visualization device for temperature waves according to claim 10.

12. The image frame data of temperature waves captured by a transmission electron microscope (TEM) or scanning transmission electron microscope (STEM) is read. The starting image frame, second image frame, nth image frame (n = 3, 4, ..., N), and ending image frame of the temperature wave image frame data are colored with the starting phase of the temperature wave, the phase propagation between image frames, the equiphase intervals within the image frames, and specific colors corresponding to said equiphase intervals. For the image frame data set following the starting image of the temperature wave image frame data, a corresponding region of phase reinterpretation due to phase propagation between image frames is performed, and the second starting image frame, the nth image frame following it (n=3, 4, ..., N), and the ending image frame are colored with the starting phase of the temperature wave, the phase propagation between image frames, the equiphase intervals within the image frames, and specific colors corresponding to said equiphase intervals. For the group of image frame data following the second starting image of the temperature wave image frame data, a corresponding region of phase reinterpretation due to phase propagation between image frames is performed, and the nth starting image frame (n=3, 4, ..., N), the nth image frame that follows it (n=3, 4, ..., N), and the ending image frame are colored with the starting phase of the temperature wave, the phase propagation between image frames, the equiphase intervals within the image frames, and specific colors corresponding to said equiphase intervals. Here, N is the number of the nth image frame that is the target of the dynamic visualization process, starting from the initial image frame. A method for dynamically visualizing temperature waves.

13. Furthermore, the system stores each image frame that has undergone dynamic visualization processing of the colored image frame data of the temperature wave. The method for dynamically visualizing temperature waves according to claim 12.

14. Furthermore, each image frame that has undergone dynamic visualization processing is played back as a video of thermal diffusion using the temperature wave phase method. A method for dynamically visualizing temperature waves according to claim 12 or 13.

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