Automatic evaluation device and automatic evaluation method for alloy composition search

Abstract

To perform an alloy composition search that enables automatic, high-speed evaluation between evaluation devices for a plurality of evaluation items, this automatic evaluation device (1000) is provided with: a nanoindentation testing machine (50) which measures a mechanical characteristic according to the shape of an indenter mark; a mechanical characteristic distribution memory unit (120) which stores a distribution condition of the mechanical characteristic; a measurement instrument cooperation controller (110) which controls measurement work by measurement instruments upon a sample to be measured; a measurement data storage unit (130) which stores measurement data from the measurement instruments; and a post processing unit (200) which calculates physical property data corresponding to the measurement data.

Description

Automatic evaluation device and method for alloy composition search

[0001] The present invention relates to an automatic evaluation device and an automatic evaluation method for searching for alloy compositions suitable for use in performance prediction in the field of structural materials, and in particular to an automatic evaluation device and an automatic evaluation method for searching for alloy compositions that use a high-speed automatic evaluation technology for composition-process-structure-property databases to achieve significant improvement in accuracy and an expansion of the prediction range.

[0002] Acceleration and sophistication of prediction technologies, including numerical simulations of phase diagrams, structures, and properties, are crucial technological elements for shortening the time it takes to develop and implement materials. An example of how predictions utilizing physical phenomena and empirical formulas have contributed to the creation of new materials is the alloy design program developed by the present applicant [Non-Patent Document 1]. A Ni-based single crystal superalloy (TMS alloy) created with the aid of the prediction results was actually installed as a turbine blade in an aircraft engine. Prediction technologies are also widely used to improve process conditions. A typical example is software (JMatPro) developed by Sente Software in the UK [Non-Patent Document 2], which predicts strain-rate-dependent physical, thermodynamic, and mechanical properties based on the alloy's chemical composition and structure information. This software has significantly contributed to determining process conditions in industrial settings, such as casting, heat treatment, and forging. Many other process-structure-property prediction programs [Non-Patent Documents 3 and 4] are also currently being developed. Furthermore, recent advances in AI and machine learning technology will likely further shorten the time required from material development to practical application.

[0003] Whether predictions are based on physical phenomena and empirical formulas or machine learning, the accuracy and scope of the predictions depend on the quality and quantity of the experimentally obtained materials database. In other words, optimizing the process of searching for truly practical alloy compositions through prediction requires the acquisition of extensive and highly accurate experimental data. Meanwhile, in the field of structural materials development, large-scale databases known as "big data" do not exist; until now, databases have been constructed through long-term, painstaking experiments by researchers and engineers. For example, alloy design and process optimization for Ni-based superalloys with a γ-γ' dual-phase microstructure requires accurate phase diagrams for countless combinations of elements in over 10-element systems, such as Ni-Cr-Co-W-Mo-Al-Ti-Ta-Hf-Re-Ru, understanding the microstructural formation behavior at each process temperature and time, and acquiring databases of microstructures, high-temperature strength properties, and creep and fatigue properties. Generally, it takes decades of trial and error, numerous experiments, and enormous development funds to successfully implement a single candidate alloy. Under these circumstances, the development of high-speed evaluation systems, including techniques and equipment for acquiring experimental data at high speed (high-speed processing), has become increasingly important in recent years.

[0004] <Compositionally Graded Materials Technology> Evaluation techniques using compositionally graded materials using the diffusion couple method or the Bridgman method have been proposed as high-speed processing evaluation techniques for experimental data for creating phase diagrams. These evaluation techniques obtain phase diagrams and property information for numerous alloy compositions by performing microstructural and property evaluations on specimens with large compositional gradients within a single sample. The diffusion couple method is a technique for creating a compositional gradient within a single sample by stacking alloy or pure metal plates with different compositions and causing an interdiffusion reaction at high temperatures [Non-Patent Document 5]. The Bridgman method, on the other hand, utilizes the differences in the initial and final solidification compositions of multi-component alloys to slowly solidify them unidirectionally, thereby achieving a large compositional gradient within a single sample [Non-Patent Document 6]. Unlike the diffusion couple method, the Bridgman method utilizes metal solidification, and therefore has the advantage of being able to achieve large compositional gradients even with heavy elements such as Re, W, Mo, and Ta, which generally have slow diffusion rates and are used to strengthen advanced Ni-based superalloys.

[0005] <High-speed evaluation technology> Nanoindentation is an effective method for evaluating the mechanical properties of such compositionally graded materials. Ikeda et al. [Non-Patent Document 6] heat-treated a compositionally graded Ni-based superalloy sample at a predetermined aging temperature and time, analyzed its composition using an electron probe microanalyzer (EPMA), and then observed the crystal orientation and γ' precipitate particles using a field emission-scanning electron microscope (FE-SEM) equipped with electron backscatter diffraction (EBSD). Mechanical properties such as Young's modulus and hardness were then measured using a nanoindentation device at room temperature. This allowed them to successfully build a composition-structure-property database for alloys with countless compositions that had been heat-treated at a certain aging temperature.

[0006] H. Harada, H. Murakami, Design of Ni-base superalloys, in: T. Saito (Ed.), Computational Materials Design, Springer-Verlag, Berlin, 1999, pp. 39-70; Hideya Kijima, "Solidification Property Calculation of Physical Property Calculation Software JMatPro", Foundry Engineering, Vol. 86, pp. 951-956 (2014); T. Osada et al. , Virtual heat treatment for gg' two-phase NI-Al alloy on the Materials Integration System, Materials & Design 226 (2023) 111631L. Wu et al. The temperature dependence of strengthening mechanisms in Ni based superalloys: A newly re-defined cubic model and its implications for strength design, Journal of the Alloys and Compounds, 931 (2023) 167508. K. Goto et al. , High-throughput evaluation of stress-strain relationships in Ni-Co-Cr ternary systems via indentation testing of diffusion couples, 910 (2022) 164868A. Ikeda et al. High-throughput mapping method for mechanical properties oxidation resistance, and phase stability in Ni-based Superalloys using composition-graded unidirectional solidified alloys, Scripta Materialia, 193 (2021) 91-96K. Goto et al. ,“Inverse estimation approach for elastoplastic properties using the load-displacement curve and pile-up topography of a single Berkovich indentation”, Materials and Design, 194 (2020) 108925,

[0007] However, the mechanical property evaluation method for compositionally graded materials described in Non-Patent Document 6 requires alignment on the order of several millimeters each time the EPMA / FE-SEM / nanoindentation equipment is moved between them, posing the problem of requiring a great deal of time, effort, and know-how when setting up the sample between the equipment. Another problem is that the post-processing of the countless data obtained from the various equipment using analytical software requires a great deal of time and human effort. Furthermore, the only mechanical property that can be obtained is hardness, and it is not possible to obtain stress-strain curves and high-temperature stress-strain curves, which are generally required for alloy design. Furthermore, only one heat treatment condition can be applied to each compositionally graded sample, limiting the process range.

[0008] On the other hand, issues related to obtaining mechanical properties can be resolved to some extent by combining this method with a method for estimating stress-strain curves through inverse analysis. Goto et al. [Non-Patent Document 7] propose a method for estimating the stress-strain curve at the location of indentation from the load-displacement curve and indentation shape obtained by nanoindentation using finite element method simulation results. By combining this inverse analysis method with the method described in Non-Patent Document 6, it is possible to obtain a phase diagram-structure-stress-strain curve database from one or a limited number of compositionally graded samples. Here, information on the indentation shape is required to estimate the stress-strain curve, and Goto et al. obtained the indentation shape using an AFM using the same indenter after indentation. However, the method described in Non-Patent Document 7 for estimating stress-strain curves through inverse analysis has the problem that obtaining the indentation shape using an AFM is time-consuming and wears the indenter tip, affecting the accuracy of stress-strain curve measurement, making it difficult to obtain large amounts of mechanical data quickly.

[0009] As mentioned above, there are several elemental technologies for high-speed processing evaluation of the necessary databases in the field of structural materials. However, since there is still a lot of manual work and know-how required between evaluation devices, it is essential to develop an evaluation system and post-processing software that enables automatic and high-speed evaluation of multiple evaluation items.

[0010] Existing high-speed processing evaluation technologies have the following time and technical challenges (1) to (5): (1) time and technical challenges related to moving and setting up between EPMA / FE-SEM / nanoindentation devices, (2) time and technical challenges related to estimating high-temperature stress-strain curves due to the indentation profile acquisition method, (3) time and technical challenges related to post-processing of big data using analysis software, (4) technical challenges related to limited process scope, and (5) because experiments are conducted by humans, working hours are limited and personnel costs are enormous. The present invention solves the above-mentioned problems of the conventional technology and aims to provide an automatic evaluation device for alloy composition exploration that enables automatic and high-speed evaluation of multiple evaluation items between evaluation devices.

[0011] As shown in FIG. 1 , the automatic evaluation device for alloy composition search of the present invention includes a sample holder 20 for holding a test sample 10 in a predetermined position, a mechanical property distribution storage unit 120 for storing the distribution of mechanical properties measured by a nanoindentation tester based on the position of an indentation mark on the test sample 10 formed by the nanoindentation tester, a housing 30 for holding at least one type of measuring instrument selected from a wavelength dispersive X-ray spectrometer or an energy dispersive X-ray spectrometer for analyzing the constituent elements of the alloy, a field emission scanning electron microscope for measuring the microstructure of the alloy, and an electron backscatter diffraction device for analyzing the orientation distribution, texture, or crystalline phase distribution of crystal grains, and a measuring instrument mounted in the housing 30. The apparatus includes a measurement instrument linkage controller 110 that controls the measurement of the sample to be measured using at least one type of measurement instrument selected from the group consisting of a wavelength dispersive X-ray spectrometer or an energy dispersive X-ray spectrometer that analyzes the constituent elements of a deposited alloy, a field emission scanning electron microscope that measures the structural shape of the alloy, and an electron backscatter diffraction device that analyzes the orientation distribution, texture, or crystalline phase distribution of crystal grains; a measurement data storage unit 130 that stores the measurement data of the measurement instrument as measurement data of the sample to be measured by the measurement instrument based on the position of the indenter mark formed on the sample to be measured; and a post-processing unit 200 that calculates physical property data corresponding to the measurement data of the measurement instrument.

[0012] In the automated evaluation method for alloy composition search of the present invention, as shown in FIG. 3A , for example, scanning electron microscope observation or electron backscatter diffraction observation is performed on the test sample 10 (S200), a position for mechanical measurement is selected based on the texture, phase, or crystal structure on the obtained image (S220), and the design composition ratio of the composition elements at the position for mechanical measurement is optionally stored in a composition ratio storage unit (S400). A high-temperature hardness test (nanoindentation measurement) is performed at a predetermined temperature for the selected position for mechanical measurement on the test sample 10 (S210), an indentation shape measurement is performed for the position for mechanical measurement (S220), a high-temperature stress-strain curve for the test sample 10 is calculated (S240), and optionally, from the texture, phase, or crystal structure of the indentation mark on the test sample 10, the position observed by the scanning electron microscope observation or electron backscatter diffraction observation of the test sample 10 is linked to the data of the high-temperature stress-strain curve (S500).

[0013] In the automatic evaluation method for alloy composition search of the present invention, as shown in FIG. 3B , for example, a nanoindentation tester is used to perform a high-temperature hardness test (nanoindentation measurement) on a test sample 10 at a predetermined temperature, and an indentation shape measurement is performed at the position where an indentation mark is formed on the test sample 10 (S220). A high-temperature stress-strain curve for the test sample 10 is calculated based on the results of the indentation shape measurement (S240). Then, a scanning electron microscope observation or electron backscatter diffraction observation is performed on the test sample 10 (S241). S300), and using the indentation mark on the measured sample 10 on the obtained image, a detailed position to be observed by scanning electron microscope or electron backscatter diffraction is selected as a position for mechanical measurement, and the texture, phase, or crystal structure of the detailed position is measured by scanning electron microscope or electron backscatter diffraction observation (S320), and the position of the measured sample 10 observed by scanning electron microscope or electron backscatter diffraction is linked to the mechanical measurement data from the texture, phase, or crystal structure of the indentation mark on the measured sample 10 (S500).

[0014] According to the automatic evaluation device for alloy composition exploration of the present invention, a holding device for a compositionally gradient sample is provided, for example, within a field emission scanning electron microscope, and a housing is provided that maintains a constant positional relationship between at least one of a wavelength dispersive X-ray spectrometer, an energy dispersive X-ray spectrometer, or an electron backscatter diffraction detector, and a high-temperature nanoindentation device.This eliminates the need to move and precisely align the compositionally gradient sample between the EPMA / field emission scanning electron microscope / nanoindentation device, making it easier to adjust the sample setting between the devices.

[0015]

[0023] FIG. 1 is a functional block diagram showing an outline of an integrated high-speed automated evaluation system as an automated evaluation device for alloy composition exploration according to the present invention.

[0024] FIG. 2 is a diagram showing various ancillary equipment of the integrated high-speed automated evaluation system, and the data flow to the obtained raw measurement data and post-processing software.

[0025] FIG. 3 is a diagram showing an example of an automated experiment and data analysis flow utilizing the integrated high-speed automated evaluation system, showing a case in which a nanoindentation tester is built in.

[0026] FIG. 4 is a diagram showing an example of an automated experiment and data analysis flow utilizing the integrated high-speed automated evaluation system, showing a case in which a nanoindentation tester is not built in.

[0027] FIG. 5 is a diagram showing the effect of increased speed brought about by the integrated high-speed automated evaluation system.

[0028] FIG. 6 is a diagram showing an example of a design method for a compositionally graded diffusion couple, where (a) is a Ni-Al phase diagram, (b) is an external view of a compositionally graded single crystal alloy, and (c) is a perspective view of the compositionally graded single crystal alloy.

[0029] FIG. 7 is a diagram showing the appearance of a temperature gradient heat treatment device and a composition / temperature graded test piece after heat treatment.

[0029] FIG. 8 is a diagram showing an example of nanoindentation (load-displacement curve) results at 500 points for a Ni-Al binary composition / temperature graded single crystal sample. This figure shows the composition-hardness-Young's modulus map obtained in N=10,000 tests for a Ni-Al binary composition / temperature-gradient single crystal sample. This figure shows the results of automatic indentation load-depth measurements (when the aging time is 3 hours) for a temperature-gradient single crystal sample of a Ni-Co-Cr-W-Mo-Ti-Al-Ta-Nb 9-component superalloy. This figure shows an example of automatic acquisition of indentation shapes at each coordinate position by transferring coordinate information during indentation measurement to an SEM for a temperature-gradient single crystal sample of a Ni-Co-Cr-W-Mo-Ti-Al-Ta-Nb 9-component superalloy. This figure shows the results of automatic microstructure measurements (when the aging time is 3 hours) for a temperature-gradient single crystal sample of a Ni-Co-Cr-W-Mo-Ti-Al-Ta-Nb 9-component superalloy. 8B is a graph showing the results of analysis of (a) hardness H (GPa), (b) damping modulus Er (GPa) of a temperature-gradient single crystal sample of a Ni-Co-Cr-W-Mo-Ti-Al-Ta-Nb 9-component superalloy, and (c) pile-up height Hp (when the aging time is 3 hours) analyzed using a shape analysis program (S230 in FIG. 3B) from the indentation height information of FIG. 8B.(a) Yield strength σ of a temperature-gradient single crystal specimen of a Ni-Co-Cr-W-Mo-Ti-Al-Ta-Nb 9-component superalloy analyzed using an inverse analysis program (S230 in Figure 3B). Ｙ (MPa), (b) work hardening rate B (MPa), (c) all the stress-strain data obtained. (a) Volume fraction f of aged precipitates and cooled precipitates, which was analyzed using an automatic image processing program (S310 in Figure 3B) from SEM image information of a temperature gradient single crystal sample of a Ni-Co-Cr-W-Mo-Ti-Al-Ta-Nb 9-component superalloy. Ｖ(b) precipitate size, and (c) precipitate shape (when aging time = 3 hours). This figure shows the appearance and indentation state of a Ni-W-Ta compositionally graded material. This figure shows an example of high-temperature nanoindentation results for a Ni-W-Ta compositionally graded sample (e.g., Ni93%-Ta7% region). This figure shows an example of automated measurement of indentation indentation shape and the resulting high-temperature stress-strain curve, where (a) is an SEM image, and (b) and (c) show the three-dimensional indentation shape obtained by SEM. This figure shows an example of automated measurement of indentation indentation shape and the resulting high-temperature stress-strain curve, where (d) is an example output from a pile-up height measurement program, and (e) shows a high-temperature stress-strain curve (e.g., Ni93%-Ta7% region) estimated from the load-displacement curve and indentation shape. This figure shows an example of automated measurement results (an example of a Ni-W-Ta compositionally graded material) using an integrated high-speed processing automated evaluation system, where (a) shows the Ni, W, and Ta concentrations, (b) shows Young's modulus, (c) shows hardness, (d) shows pile-up height, (e) shows the processing effect coefficient, and (f) shows yield stress at each measurement point. This figure shows an example of automated measurement results (an example of a Ni-Co compositionally graded material) using an integrated high-speed processing automated evaluation system, where SEM photographs of the compositionally graded sample are shown. This figure shows an example of automated measurement results (an example of a Ni-Co compositionally graded material) using an integrated high-speed processing automated evaluation system, where the temperature dependence of hardness at each composition is shown. This figure shows an example of automated measurement results (an example of a Ni-Co compositionally graded material) using an integrated high-speed processing automated evaluation system, where the hardness maps at each composition and temperature are compared with the phase diagram. This figure displays EPMA maps of each element in a Ni-Co-Al-Ti quaternary alloy. This is an SEM photograph showing the crystal grains to be analyzed in a Ni-Co-Al-Ti quaternary alloy, along with the target area for EPMA surface analysis. This is a diagram showing the tie-line data setting conditions for determining the γ-γ' composition required for a phase diagram DB using an automatic composition analysis program. This is a diagram showing the analysis results of the γ and γ' phase compositions in the target area for EPMA surface analysis. This is a diagram showing tie-line data for a Ni-Co-Al-Ti quaternary alloy. This is a diagram showing markers corresponding to each measurement point on a position map of the sample to be measured.A figure that displays mechanical properties such as elastic modulus, hardness, pile-up height, yield stress, and processing effect coefficient at each measurement point of the measured sample on a state diagram or position map. A figure showing the display of each characteristic value at any point selected from the measurement points in Fig. 16A among the measured samples for data re-analysis and mapping software. A figure that displays the raw data of the load-displacement curve, microstructure, and pile-up analysis obtained by nanoindentation. A cross-sectional view of the main part of a welded joint, which is an example where the measured sample shows a composition gradient or / and tissue variation, showing the welded joint of a nickel-based superalloy turbine disk material. A dendrite solidification structure diagram of the weld metal shown in Fig. 17A. A microstructure diagram of the HAZ (heat-affected zone) shown in Fig. 17A. A microstructure diagram of the base material shown in Fig. 17A. An overall perspective view of a turbine blade, which is an example where the measured sample shows a composition gradient or / and tissue variation, showing the thick part and the thin part. A dendrite solidification structure diagram of the thick part shown in Fig. 18A. A dendrite solidification structure diagram of the thin part shown in Fig. 18A. A microstructure diagram of a multiphase polycrystalline structure material, which is an example where the measured sample shows a composition gradient or / and tissue variation.

[0016] As a means for solving the above problems, the present inventors have conceived of an integrated high-speed automated evaluation system 1000, as shown in FIG. 1 , which includes an integrated evaluation device 100, an automatic control system 110, and a postprocessor (hereinafter, sometimes referred to as a "postprocessor") 200 that executes post-processing software. Conventional evaluation systems have independently performed measurements using EPMA, EBSD, FE-SEM, or nanoindentation. However, the automated evaluation device 1000 for alloy composition exploration, which is an example of the integrated high-speed automated evaluation system of the present invention, is equipped with at least one of a wavelength-dispersive X-ray spectrometer, an energy-dispersive X-ray spectrometer, or an electron backscatter diffraction device installed within a field-emission scanning electron microscope, and a high-temperature nanoindentation device, and automatically controls the integrated evaluation device 100 with an automatic control system 110 operated by external software, thereby enabling comprehensive automatic evaluation of the alloy composition, phase and orientation information, microstructure and morphology information, or mechanical properties of a compositionally gradient sample. Therefore, the integrated evaluation device 100 includes a device for holding a compositionally gradient sample, for example, within a field-emission scanning electron microscope, as well as at least one of a wavelength-dispersive X-ray spectrometer, an energy-dispersive X-ray spectrometer, or an electron backscatter diffraction device, and a housing for maintaining a constant positional relationship for high-temperature nanoindentation. Furthermore, as shown in Figure 2, the obtained raw data 64, 44, 12, 74, and 54 are converted via a post-processing unit 200 that executes post-processing software into information truly required by materials engineers for alloy design, such as phase diagram information, precipitation morphology information, and high-temperature mechanical properties (elastic constants, stress-strain curves, yield stress, work-hardening coefficients, or creep deformation rates). Furthermore, the field-emission scanning electron microscope is configured to enable non-contact, high-speed, and high-precision evaluation of indentation morphology.

[0017] [1] As shown in FIG. 1, an automatic evaluation device 1000 for searching for alloy compositions according to the present invention includes a sample holder 20 for holding a test sample 10 in a predetermined position, a mechanical property distribution storage unit 120 for storing the distribution of mechanical properties measured by a nanoindentation tester based on the position of an indentation mark formed on the test sample 10 by the nanoindentation tester, a housing 30 for holding at least one measuring instrument selected from a wavelength dispersive X-ray spectrometer or an energy dispersive X-ray spectrometer for analyzing the constituent elements of an alloy, a field emission scanning electron microscope for measuring the microstructure of an alloy, and an electron backscatter diffraction device for analyzing the orientation distribution, texture, or crystalline phase distribution of crystal grains. the measurement instrument linkage controller 110 for controlling the measurement of the sample to be measured by at least one of the measurement instruments: a wavelength dispersive X-ray spectrometer or an energy dispersive X-ray spectrometer for analyzing the composition elements of the alloy attached to the measurement instrument 30; a field emission scanning electron microscope for measuring the structural shape of the alloy; or an electron backscatter diffraction device for analyzing the orientation distribution, texture, or crystalline phase distribution of crystal grains; a measurement data storage unit 130 for storing the measurement data of the measurement instrument as measurement data of the sample to be measured by the measurement instrument based on the position of the indenter mark formed on the measurement instrument 10; and a post-processing unit 200 for calculating physical property data corresponding to the measurement data of the measurement instrument.

[0018] [1A] As shown in FIG. 1, the automatic evaluation device for alloy composition search of the present invention includes a sample holder 20 for holding a test sample 10 in a predetermined position, a nanoindentation tester 50 for pressing an indenter against the test sample 10 to measure mechanical properties based on the shape of the indentation mark, a mechanical property distribution storage unit 120 for storing the distribution of mechanical properties measured by the nanoindentation tester 50 based on the position of the indentation mark formed on the test sample 10, and at least one measurement device selected from the group consisting of a wavelength dispersive X-ray spectrometer or an energy dispersive X-ray spectrometer for analyzing the constituent elements of an alloy, a field emission scanning electron microscope for measuring the microstructural shape of an alloy, and an electron backscatter diffraction device for analyzing the orientation distribution, texture, or crystalline phase distribution of crystal grains. The apparatus comprises a housing 30 for holding instruments, a nanoindentation testing machine 50 attached to the housing 30, and a measurement instrument linkage controller 110 for controlling the measurement of the sample to be measured using at least one type of measurement instrument selected from the group consisting of a wavelength dispersive X-ray spectrometer or an energy dispersive X-ray spectrometer for analyzing the constituent elements of an alloy, a field emission scanning electron microscope for measuring the structural shape of an alloy, and an electron backscatter diffraction device for analyzing the orientation distribution, texture, or crystalline phase distribution of crystal grains, a measurement data storage unit 130 for storing the measurement data of the measurement instrument as measurement data of the sample to be measured by the measurement instrument based on the position of the indenter mark formed on the sample to be measured, and a post-processing unit 200 for calculating physical property data corresponding to the measurement data of the measurement instrument.[2] In the automatic evaluation device for alloy composition search [1] or [1A] of the present invention, the measured sample 10 may be any of the following: a compositionally graded material having a composition ratio that grades between upper and lower limit values ​​for the composition elements of the alloy system to be evaluated; a heat-treated temperature-gradient material obtained by heat-treating the compositionally graded material or a test material with a uniform composition in place of the compositionally graded material in a furnace in which the heat treatment temperature is graded between upper and lower limit values; a heat-affected member that includes a region of a base material (metal, thermoplastic material, etc.) that is not melted but in which the microstructure and properties of the measured sample 10 have been changed by welding or thermal cutting; a metal additive manufacturing material that is manufactured as the metal part by melting metal powder in a portion necessary for the metal part with an electron beam or fiber laser and then solidifying it; or a metal powder injection molding material that uses metal fine powder as a raw material, adds a binder without melting the metal fine powder, and then injection molds the metal fine powder, and then degreases and sinters the molded body formed by the injection molding to obtain a metal part. [3] In the automatic evaluation device for alloy composition search [2] of the present invention, the metal additive manufacturing material may be manufactured by any of the following methods: a powder bed method in which a laser beam or an electron beam is irradiated onto a powder bed on which metal powder is spread, and melting and solidifying are repeated for each layer; a directed energy deposition method in which a shaped object is produced by supplying powder or wire, melting it with a laser or an electron beam, and depositing it; a fused deposition modeling method in which metal powder is placed in a thermoplastic resin, layered while melting it with heat, and after modeling, the degreased shaped object is sintered to solidify the metal powder; or a binder jet method in which a liquid binder is sprayed from a nozzle onto metal powder to form a shape, and after the binder is sprayed and solidified for each layer, the modeling plate is lowered and the powder is spread again, and this process is repeated for each layer, and after modeling, the shape is sintered in a high-temperature furnace or heater, etc., and the binder is removed.[4] Any of the automatic evaluation devices for alloy composition exploration [1] to [3] and [1A] of the present invention further includes a nanoindentation tester 50 that presses an indenter into the test sample 10 and measures mechanical properties based on the shape of the indentation mark, the mechanical property distribution storage unit 120 stores the distribution of mechanical properties measured by the nanoindentation tester 50 based on the position of the indentation mark formed on the test sample 10, the casing unit 30 holds the nanoindentation tester 50 and at least one type of measuring instrument selected from the group consisting of the wavelength dispersive X-ray spectrometer or energy dispersive X-ray spectrometer, the field emission scanning electron microscope, and the electron backscatter diffraction device, The measurement instrument linkage controller 110 preferably controls the measurement of the sample to be measured by the nanoindentation testing machine 50 attached to the housing, and at least one type of measurement instrument selected from the group consisting of the wavelength dispersive X-ray spectrometer or energy dispersive X-ray spectrometer, the field emission scanning electron microscope, and the electron backscatter diffraction device.

[0019] [5] In any of the automatic evaluation devices for alloy composition search of the present invention [1] to [4] and [1A], preferably, the target of the alloy composition search is one or more selected from the group consisting of the composition gradient material, heat treatment temperature gradient material, heat-affected component, metal additive manufacturing material, and metal powder injection molding material, and in the measurement data storage unit 130, the measurement data of the measured sample is at least one type of crystalline phase equilibrium composition data 64 corresponding to the composition elements 62 of the alloy, fine precipitate identification data 44 and indentation shape high-speed acquisition data 12 corresponding to the microstructural shape 42 of the alloy, polycrystalline orientation data 74 corresponding to the anisotropy 72 of the alloy, or load / displacement information corresponding to the mechanical properties measured by the nanoindentation testing machine 50. [6] In the automatic evaluation device [5] for alloy composition search of the present invention, as shown in FIG. 2, preferably, the target of the alloy composition search is a nickel-based superalloy, and in the measurement data storage unit 130, the measurement data of the measured sample is at least one of γ / γ' equilibrium composition data 64 corresponding to the composition elements 62 of the alloy, fine precipitate identification data 44 and high-speed indentation shape acquisition data 12 corresponding to the microstructural shape 42 of the alloy, polycrystalline orientation data 74 corresponding to the anisotropy 72 of the alloy, or load / displacement information corresponding to the mechanical properties measured by the nanoindentation testing machine 50. [7] In the automatic evaluation device [5] for alloy composition search of the present invention, as shown in FIG. 2, preferably, in the post-processing unit 200, the physical property data corresponding to the measurement data of the measuring instrument is at least one of composition data (66) corresponding to crystalline phase equilibrium composition data 64, precipitation morphology data (46) corresponding to fine precipitate identification data 44, or high-speed indentation shape acquisition data 12, polycrystalline orientation data 74, or load / displacement information 54, and at least one of elastic constants, critical resolved shear stress (CRSS), work-hardening coefficient, or creep deformation rate is calculated.[8] In the automatic evaluation device [6] for alloy composition exploration of the present invention, as shown in FIG. 2, preferably, in the post-processing unit 200, the physical property data corresponding to the measurement data of the measuring instrument is at least one of composition data (66) corresponding to γ / γ' equilibrium composition data 64, precipitation morphology data (46) corresponding to fine precipitate identification data 44, or high-speed indentation shape acquisition data 12, polycrystalline orientation data 74, or load / displacement information 54, and at least one of elastic constants, critical resolved shear stress (CRSS), work hardening coefficient, and creep deformation rate is calculated.

[0020] [9] In any of the automatic evaluation devices for alloy composition exploration [1] to [8] and [1A] of the present invention, preferably, the test sample 10 is a heat-treated temperature-gradient material obtained by heat-treating the composition-gradient material or a test material with a uniform composition instead of the composition-gradient material in a furnace in which the heat treatment temperature is gradiently distributed between an upper limit and a lower limit, and the position of the indenter mark formed on the test sample 10 is linked to the heat treatment temperature.

[10] In any of the automatic evaluation devices for alloy composition exploration [1] to [9] and [1A] of the present invention, preferably, the microstructure of the alloy indicates a boundary region of a phase transformation in which the crystal structure changes between a first crystal structure and a second crystal structure.

[11] In the automatic evaluation device for alloy composition exploration

[10] of the present invention, preferably, the first crystal structure is a face-centered cubic lattice, and the second crystal structure is a hexagonal close-packed lattice.

[12] In the automatic evaluation system

[10] for alloy composition exploration of the present invention, preferably, the composition ratio of the composition elements changes at the boundary line between the first crystal structure and the second crystal structure.

[13] In the automatic evaluation system

[10] for alloy composition exploration of the present invention, preferably, the mechanical property measured by the nanoindentation tester indicates a change in the mechanical property across the boundary line between the first crystal structure and the second crystal structure.

[14] In the automatic evaluation system

[13] for alloy composition exploration of the present invention, preferably, the mechanical property is hardness.

[15] In the automatic evaluation system [9] for alloy composition exploration of the present invention, preferably, the measured sample 10 has a composition range that covers the γ / γ' two-phase structure, and the post-processing unit extracts tie-line information of the γ / γ' two-phase structure by using the element map obtained by the electron backscatter diffraction device and the distinction between the γ phase and the γ' phase by the scanning electron microscope for an observation region consisting of the γ / γ' two-phase structure in the nickel-based superalloy.

[16] In the automatic evaluation device [9] for alloy composition exploration of the present invention, preferably, the sample 10 to be measured is a heat-treated temperature gradient material obtained by heat-treating the composition gradient material in a furnace in which the heat treatment temperature is gradiently distributed between an upper limit value and a lower limit value, and the size and amount of the γ' precipitate particles are analyzed according to the heat treatment temperature to construct γ' precipitate particle volume fraction data.

[0021]

[17] In the automated evaluation method for alloy composition search of the present invention, as shown in FIG. 3A, for example, scanning electron microscope observation or electron backscatter diffraction observation is performed on the test sample 10 (S200), a mechanical measurement position is selected based on the texture, phase, or crystal structure on the obtained image (S220), and the design composition ratio of the composition elements at the mechanical measurement position is optionally stored in a composition ratio storage unit (S400). A high-temperature hardness test (nanoindentation measurement) is performed at a predetermined temperature for the selected mechanical measurement position on the test sample 10 (S210), an indentation shape measurement is performed for the mechanical measurement position (S220), a high-temperature stress-strain curve for the test sample 10 is calculated (S240), and optionally, from the texture, phase, or crystal structure of the indentation mark on the test sample 10, the high-temperature stress-strain curve data for the position observed by the scanning electron microscope observation or electron backscatter diffraction observation of the test sample 10 is linked to data on the high-temperature stress-strain curve (S500).

[0022]

[18] In the automatic evaluation method for alloy composition search of the present invention, as shown in FIG. 3B, for example, a nanoindentation tester is used to perform a high-temperature hardness test (nanoindentation measurement) on a test sample 10 at a predetermined temperature. The test sample 10 undergoes an indentation shape measurement at a position where an indentation mark is formed (S220). Based on the results of the indentation shape measurement, a high-temperature stress-strain curve for the test sample 10 is calculated (S240). The test sample 10 is then observed using a scanning electron microscope or electron backscatter diffraction. (S300), a detailed position to be observed by scanning electron microscope or electron backscatter diffraction using the indentation mark on the measured sample 10 on the obtained image is selected as a position for mechanical measurement, and the texture, phase, or crystal structure of the detailed position is measured by scanning electron microscope or electron backscatter diffraction observation (S320), and the position of the measured sample 10 observed by scanning electron microscope or electron backscatter diffraction is linked to the mechanical measurement data from the texture, phase, or crystal structure of the indentation mark on the measured sample 10 (S500).

[19] In the automatic evaluation method for alloy composition search of the present invention

[17] or

[18] , the measured sample is preferably any one of: a compositionally graded material having a composition ratio that grades between upper and lower limit values ​​for each of the composition elements of the alloy system to be evaluated; a heat-treated temperature-gradient material obtained by heat-treating the compositionally graded material or a test material with a uniform composition in place of the compositionally graded material in a furnace where the heat treatment temperature is graded between upper and lower limit values; a heat-affected component that includes a region of a base material (metal, thermoplastic material, etc.) that is not melted but whose microstructure and properties have been changed by welding or thermal cutting; a metal additive manufacturing material obtained by melting and solidifying metal powder in a required portion with an electron beam or fiber laser to produce a metal part; or a metal powder injection molding material that uses metal fine powder as a raw material, adds a binder without melting the metal fine powder, and injection molds the metal fine powder, and then degreases and sinters the molded body formed by the injection molding to obtain a metal part.

[20] In the automated evaluation method

[19] for alloy composition search of the present invention, the metal additive manufacturing material may be manufactured by any of the following methods: a powder bed method in which a laser beam or an electron beam is irradiated onto a powder bed on which metal powder is spread, and melting and solidifying are repeated for each layer; a directed energy deposition method in which a shaped object is produced by supplying powder or wire, melting the powder with a laser or an electron beam, and depositing the melted powder; a fused deposition modeling method in which metal powder is placed in a thermoplastic resin, layered while melting it with heat, and the degreased shaped object is sintered after modeling to solidify the metal powder; or a binder jet method in which a liquid binder is sprayed from a nozzle onto metal powder to form a shape, and once the spraying and solidification of the binder for each layer is completed, the modeling plate is lowered and the powder is spread again, and this process is repeated for each layer, and after modeling, the shape is sintered using a high-temperature furnace or heater, etc., and the binder is removed.

[0023]

[21] In the automated evaluation method for alloy composition exploration

[17] or

[18] of the present invention, preferably, as shown in Figures 3A and 3B, the test sample 10 is a temperature-gradient heat-treated material obtained by heat-treating (S120) the composition-gradient material or a test material having a uniform composition instead of the composition-gradient material in a temperature-gradient heat treatment furnace in which the heat treatment temperature is gradiently distributed between an upper limit and a lower limit, and further, the heat treatment temperature is stored in the composition ratio storage unit 66 together with the composition ratio of the test sample at the position of the mechanical measurement.

[22] In any of the automated evaluation methods for alloy composition exploration

[17] to

[21] of the present invention, preferably, microstructural information for the test sample 10 is obtained using a high-magnification scanning electron microscope at the position of the mechanical measurement, and the microstructural information includes at least one of crystal grain size, precipitated grain size, and volume fraction.

[23] In any of the automatic evaluation methods

[17] to

[22] of the present invention for alloy composition exploration, preferably, composition information for the measured sample 10 is obtained using measurements with a wavelength dispersive X-ray spectrometer or an energy dispersive X-ray spectrometer at the position of the mechanical measurement, and the composition information includes at least one of each coordinate composition of the measured sample 10, a matrix composition, or a precipitate composition, and the composition ratio of the composition elements at the position of the mechanical measurement observed with the wavelength dispersive X-ray spectrometer or the energy dispersive X-ray spectrometer is stored in a composition ratio memory unit 66.

[24] In the automatic evaluation method

[19] for alloy composition search of the present invention, preferably, the measured sample 10 is a compositionally gradient material, and for metal plates consisting of each composition element of the alloy system to be evaluated, metal plates of each composition element are alternately stacked, and temporarily bonded by spark plasma sintering in a vacuum at a first predetermined temperature while being pressed with a first predetermined stress, and held for a first predetermined time, and the temporarily bonded spark plasma sintered material is subjected to a diffusion heat treatment using a hot isostatic pressing device in an Ar atmosphere at a second predetermined temperature while being pressed with a second predetermined stress, and held for a second predetermined time, thereby producing a compositionally gradient sample.

[25] In the automatic evaluation method

[24] for alloy composition search of the present invention, preferably, the metal plates consisting of each composition element of the alloy system to be evaluated are a set of three metal plates of a first metal element, a second metal element, and a third metal element, and the metal plate of the first metal element is used as an intermediate layer, and the metal plate of the second metal element and the metal plate of the third metal element are stacked on the upper and lower sides of the metal plate of the first metal element, respectively; and in a composition gradient sample obtained by performing a diffusion heat treatment on the temporarily joined spark plasma sintered material, a binary composition gradient alloy of the first metal element and the second metal element is generated in a first initial interface between the metal plate of the first metal element and the metal plate of the second metal element in a direction perpendicular to the first and second initial interfaces, and a binary composition gradient alloy of the first metal element and the third metal element is generated in a second initial interface between the metal plate of the first metal element and the metal plate of the third metal element, and The thickness of the metal plate of the first metallic element is preferably such that a ternary composition-gradient alloy of the first, second, and third metallic elements is generated between the first and second initial interfaces.

[26] In the automatic evaluation method for alloy composition exploration

[25] of the present invention, preferably, the first metallic element is Ni, the second metallic element is Ta, and the third metallic element is W, and the binary composition-gradient alloy of the first metallic element and the second metallic element is Ni-Ta, the binary composition-gradient alloy of the first metallic element and the third metallic element is Ni-W, and the ternary composition-gradient alloy of the first, second, and third metallic elements is Ni-Ta-W.

[0024] According to the automatic evaluation device for alloy composition exploration of the present invention, a holding device for a compositionally gradient sample is provided, for example, within a field emission scanning electron microscope, and a housing is provided that maintains a constant positional relationship between at least one of a wavelength dispersive X-ray spectrometer, an energy dispersive X-ray spectrometer, or an electron backscatter diffraction detector, and a high-temperature nanoindentation device.This eliminates the need to move and precisely align the compositionally gradient sample between the EPMA / field emission scanning electron microscope / nanoindentation device, making it easier to adjust the sample setting between the devices. As in

[24] and

[25] , the measured sample is a metal plate made of each composition element of the alloy system to be evaluated, and the metal plates of each composition element are alternately stacked and subjected to diffusion heat treatment to produce a compositionally gradient sample in the direction perpendicular to the joining surface of the metal plates of each composition element. Furthermore, in the case of a heat treatment temperature gradient material obtained by heat treating the compositionally gradient material in a furnace in which the heat treatment temperature is gradiently distributed between an upper limit and a lower limit, the composition element (Al) of the alloy and the size of the γ' precipitate structure differ for each measurement position of the nanoindentation tester, and the load-displacement curve has a large distribution with respect to the composition and heat treatment temperature of the compositionally gradient sample, so that data on the mechanical properties can be obtained for a wide range of the composition and heat treatment temperature of the compositionally gradient sample. Here, the diffusion heat treatment is performed by alternately stacking metal plates made of each composition element of the alloy system to be evaluated, and using a hot isostatic pressing device, pressing the stack at a second predetermined temperature and with a second predetermined stress in an Ar atmosphere while holding the stack for a second predetermined time.

[0025] Example 1 Development of an Integrated High-Speed ​​Automatic Evaluation System Figure 1 is a block diagram of an integrated high-speed automatic evaluation system as an automatic evaluation device 1000 for alloy composition exploration according to the present invention. In Figure 1, the automatic evaluation device 1000 for alloy composition exploration includes a sample holder 20 that holds a test sample 10 in a predetermined position, a housing 30, an FE-SEM 40, a nanoindentation tester 50, a WDS / EDS 60, an EBSD 70, a measurement instrument linkage controller 110, a mechanical property distribution memory 120, a measurement data storage 130, and a post-processing unit 200.

[0026] The measured sample 10 is a compositionally graded material having a composition ratio that grades between upper and lower limit values ​​for each of the constituent elements of the alloy system to be evaluated. Furthermore, the measured sample 10 may be a temperature-graded heat-treated material obtained by heat-treating the compositionally graded material in a furnace in which the heat-treatment temperature is graded between upper and lower limit values. Furthermore, the measured sample 10 may be a temperature-graded heat-treated material obtained by heat-treating a test sample having a uniform composition in a furnace in which the heat-treatment temperature is graded between upper and lower limit values.

[0027] The sample holder 20 holds the sample 10 to be measured in a predetermined position, and is provided, for example, on the sample table of the FE-SEM 40. The housing 30 holds the measuring instruments, the FE-SEM 40, the nanoindentation tester 50, and, if necessary, the WDS / EDS 60 and / or EBSD 70, and maintains a constant relative positional relationship between these measuring instruments and the sample 10. The housing 30 is preferably made of a sturdy material, such as a metal or resin material. The FE-SEM 40 is a field emission-scanning electron microscope, and is used to measure the structural shape of alloys.

[0028] The nanoindentation tester 50 presses an indenter against the sample 10 to measure mechanical properties based on the shape of the indentation mark. When measuring the mechanical properties of the sample 10 based on the shape of the indentation mark, it is preferable to obtain the mechanical properties, such as Young's modulus or hardness, in a room-temperature nanoindentation apparatus, as disclosed in, for example, Non-Patent Document 6. The WDS / EDS 60 analyzes the constituent elements of an alloy, where WDS stands for Wavelength Dispersive Spectroscopy and EDS stands for Energy Dispersive Spectroscopy. The EBSD 70 analyzes the orientation distribution, texture, or crystalline phase distribution of crystal grains, and is an abbreviation for Electron Back-Scatter Diffraction.

[0029] The measurement instrument linkage controller 110 controls the measurement of the sample 10 using at least one of the measurement instruments, an FE-SEM 40 for measuring the microstructure of the alloy, and a nanoindentation tester 50, a WDS / EDS 60, or an EBSD 70. The measurement instrument linkage controller 110 is an example of an automatic control system. The mechanical property distribution memory unit 120 stores the distribution of mechanical properties measured by the nanoindentation tester 50 based on the position of the indentation mark formed on the sample 10. The measurement data storage unit 130 stores the measurement data of the measurement instrument (excluding the nanoindentation tester 50) as measurement data of the sample measured by the measurement instrument (excluding the nanoindentation tester 50) in a manner that links the measurement data with the position of the indentation mark formed on the sample 10. The post-processing unit 200 calculates physical property data corresponding to the measurement data of the measurement instrument (excluding the nanoindentation tester 50). The physical property data is converted into information that materials engineers truly need when designing alloys, such as phase diagram information, precipitation morphology information, and high-temperature mechanical properties (elastic constants, stress-strain curves, yield stress, work hardening coefficient, or creep deformation rate).

[0030] In addition, if an indenter is pressed against the test sample 10 to form an indenter mark and the distribution of the mechanical properties of the test sample 10 is stored in advance, the automatic evaluation device 1000 for alloy composition exploration of the present invention can link the measurement data of the test sample 10 measured by a measuring instrument (excluding the nanoindentation tester) to the distribution of the mechanical properties of the test sample 10 using the indenter mark measured in the test sample 10 by the FE-SEM 40, even if the nanoindentation tester 50 is not attached to the housing part 30.

[0031] 2 is a diagram showing various ancillary equipment of the integrated high-speed processing automated evaluation system 1000, and the resulting raw measurement data and data flow to the post-processing software. The measurement instrument linkage controller 110 obtains measurement data of the test sample 10, including the alloy composition 62 measured by the WDS / EDS 60, the microstructure 42 measured by the FE-SEM 40, the anisotropy 72 measured by the EBSD 70, and the mechanical properties 52 measured by the nanoindentation tester 50. The post-processing unit 200 obtains, as raw measurement data of the test sample 10 measured by the measurement instruments, γ / γ' equilibrium composition data 64 from the alloy composition 62 as raw measurement data, fine precipitate identification data 44 and high-speed indentation shape acquisition data 12 from the microstructure 42 as raw measurement data, polycrystalline orientation data 74 from the anisotropy 72 as raw measurement data, and load / displacement information 54 from the mechanical properties 52 as raw measurement data. Furthermore, the post-processing unit 200 uses post-processing software to construct a multi-element database from the raw data measured by the measuring instrument for the sample 10. A composition database 66 is generated from the γ / γ' equilibrium composition data 64. The composition database 66 can also be referred to as a composition ratio storage unit. A precipitation morphology database 46 is generated from the fine precipitate identification data 44. Elastic constants, critical resolved shear stress (CRSS), work hardening coefficients, and creep deformation rates are generated from the high-speed indentation shape acquisition data 12, polycrystalline orientation data 74, and load / displacement information 54, and are stored in the physical property data storage unit 140. The information in the multi-element database generated by the post-processing unit 200 is linked to the property prediction program 300 and / or a calculated phase diagram.

[0032] FIG. 3A is a flow diagram showing an example of an evaluation procedure using the integrated high-throughput automated evaluation system 1000, where the integrated high-throughput automated evaluation system 1000 is equipped with a nanoindentation testing machine. The integrated high-throughput automated evaluation system 1000 of the present invention maximizes its effectiveness by using the compositionally and temperature-gradient sample described above. First, an alloy system to be evaluated, such as a nickel-based superalloy, is selected (S100). Next, a sample with a compositionally gradient of the alloying elements constituting the nickel-based superalloy is prepared (S110). This preparation process can be performed using, for example, the diffusion couple method or the Bridgman method. The compositionally gradient material is then placed in a temperature-gradient heat treatment furnace and heat-treated to prepare a compositionally and temperature-gradient sample (S120). The manufacturing process information for the diffusion couple method or Bridgman method used in the preparation of the compositionally gradient material, or the process information for the temperature-gradient heat treatment furnace used in the heat treatment, is stored as process information and used in data reanalysis and mapping software (S130).

[0033] Next, as a preliminary step to mechanical measurements, SEM or EBSD observation is performed, and the mechanical measurement position is selected based on the microstructure, phase, and crystalline structure in the obtained image (S200). Next, a high-temperature hardness test (nanoindentation measurement) is performed at a desired temperature (S210). By maintaining the sample setting used in the SEM / EBSD observation and sharing the coordinate information with the indenter position, measurement positioning time can be significantly reduced and positional accuracy can be significantly improved. Hardness measurements can be performed automatically at multiple points by setting the same conditions, such as loading and unloading rates, maximum load and its holding time, and setting an equally spaced measurement pattern in two-dimensional space on the sample surface.

[0034] In the subsequent steps (S220, S300, S400), mechanical, structural, and compositional information corresponding to a single indentation position is acquired. First, SEM observation is performed to re-establish the indentation position with high precision (S220). Using software within the integrated high-speed processing automated evaluation system 1000, the user manually specifies the hardness test range for a sample on which high-temperature hardness tests have been performed at tens to tens of thousands of points. The user then records the working distance WD (the distance between the SEM lens and the sample) at which high-resolution SEM photography is possible at several points within the hardness test range, and the WD required to acquire in-focus, high-resolution SEM photographs across the entire hardness test range is estimated in advance. Subsequently, multiple low-magnification SEM images containing height information are automatically acquired. Using software within the integrated high-speed processing automated evaluation system 1000, which can automatically detect the (x, y) coordinates indicating the center of gravity of the indentation from the image contrast and / or height information, significantly faster detection of the indentation coordinates (x, y) can be achieved compared to manual measurement. The reset indentation position information can be repeatedly used until the sample is fixed on the SEM stage and removed. This technology can also be applied to samples measured with an indenter independent of the SEM, making it possible to determine the indentation position on the SEM stage for any sample. Furthermore, when hardness testing is performed at a desired (x, y) coordinate position at high temperature and observation is performed at room temperature, the (x, y) coordinates during high-temperature hardness testing and room-temperature observation may change due to the effects of thermal expansion of the sample and surrounding equipment. However, by using these automatic coordinate detection software, the accurate indentation coordinates (x, y) immediately before observation can be automatically detected.

[0035] Next, the integrated high-speed automated evaluation system 1000 acquires mechanical information (indentation shape multi-channel SEM measurement) (S220), structural information (high-magnification SEM observation) (S300), and composition information (WDS / EDS measurement) for the specified indentation coordinates (x, y) (S400). For the mechanical information, a multi-channel annular segmented backscattered electron detector installed under the SEM objective lens simultaneously acquires surface topography images from multiple directions, and the resulting SEM images are reconstructed in three dimensions to measure the height of the protuberance (pile-up) around the indentation. This height measurement method is a non-contact measurement method (imaging time = approximately 10 seconds), which is significantly faster than conventional methods (scan time = approximately 120 seconds). Furthermore, this method can suppress deterioration of the indentation indenter. Regarding structural information, coordinates corresponding to the flat sample surface near the indentation are automatically calculated from the indentation coordinates (x, y) and indentation height information, and high-resolution SEM photography is then performed at the estimated working distance WD, enabling automatic acquisition of structural information including fine precipitates of several to several tens of nanometers in size (S300). This structural observation method, which works in conjunction with automatically detected indentation coordinate (x, y) information, automatically calculates the appropriate planar position and captures high-resolution structural photographs, even when the indentation coordinate pattern is complex and arbitrary, and the indentation size varies depending on the coordinate, which previously required manual coordinate setting. Regarding compositional information, similar to the above-described structural information, coordinates corresponding to the flat sample surface near the indentation are automatically calculated from the indentation coordinates (x, y) and indentation height information, and then wavelength-dispersive X-ray spectrometry or energy-dispersive X-ray spectrometry measurements are performed at the estimated working distance WD, enabling highly accurate compositional analysis (S400). As with the above-mentioned structural information, this composition measurement technique works in conjunction with automatically detected indentation coordinate (x, y) information, and is therefore a technique that can acquire highly accurate composition information even when the indentation coordinate pattern is complicated and consists of arbitrary coordinates, which previously required manual coordinate setting, and when the indentation size varies depending on the coordinates.

[0036] In the integrated high-speed automated evaluation system 1000, the data obtained automatically and quickly in the processes up to this point is automatically analyzed in the post-processing unit 200, which runs post-processing software. Specifically, using the shape analysis / inverse analysis program (S230), a stress-strain curve is inversely estimated based on the indentation height information and the load-displacement curve obtained separately from the nanoindentation measurement. Assuming that the inverse estimation information is as valuable as actual measurements, it is estimated to be equivalent to several hundred times more efficient. Furthermore, the integrated high-speed automated evaluation system converts the structure and composition information obtained in the structure information (S300) and composition information (S400) processes into the necessary structure information (precipitate size, precipitate volume fraction, precipitate shape) and composition information via the automatic image processing program (S310) and automatic composition analysis program (S410). The raw data obtained in this manner is converted into information truly required by material engineers for alloy design, such as equilibrium composition information, precipitation morphology information, and high-temperature mechanical properties (elastic constants, stress-strain curves, yield stress, processing effect coefficient, creep deformation rate), via a post-processing unit 200 that runs the developed post-processing software (see Figure 2).

[0037] Furthermore, by storing the mechanical, structural, and compositional information together with the process information in the reanalysis / mapping software (S500), a composition-process-structure-property database that clearly defines their interrelationships can be obtained. The reanalysis / mapping software, part of the post-processing software, allows for the reanalysis of raw data according to the purpose, and also has the ability to map the composition-process-structure-property data onto a phase diagram to make it easier for alloy developers to understand, thereby providing maximum support for strategic planning for alloy development. Furthermore, by selecting the target alloy in (S100) based on these results, a database effective for alloy design can be efficiently obtained. This integrated high-speed processing automated evaluation system 1000 is highly effective when used with compositionally gradient samples, but it is also effective for rapidly obtaining local composition-structure-property data for general structural materials with complex hierarchical structures and multiphase structures.

[0038] The effects of the integrated high-speed automated evaluation system and method for alloy composition exploration, configured as the automatic evaluation device 1000 of the present invention, are now described. Figure 4 shows the relationship between the test time required to obtain mechanical properties (stress-strain curves) and the number of tests, N. In conventional methods, after producing a test sample with a specified alloy composition through alloy casting, plastic processing, and heat treatment, obtaining a high-temperature stress-strain curve, for example, required one day on average for N = 1, including sample collection by electrical discharge machining, cutting, surface polishing, and tensile testing. This translates to approximately 21 years of time required to complete N = 10,000 tests. On the other hand, while the following is an estimate based solely on mechanical properties, using the integrated high-speed automated evaluation system of the present invention, it is possible to obtain high-temperature stress-strain curves for, for example, 10,000 alloys with different compositions in just 20 days. This demonstrates that the present invention is a 384-times faster evaluation system than conventional methods.

[0039] Thus, the integrated high-throughput automated evaluation system 1000 of the present invention is an integrated evaluation device capable of acquiring alloy composition, phase and orientation information, microstructure and shape information, and mechanical properties at each coordinate in a composition / temperature gradient sample within a single device. To this end, the FE-SEM is equipped with WDS / EDS, EBSD, and high-temperature nanoindentation, and these instruments are automatically controlled by external software, enabling comprehensive automated evaluation. Figure 3B is a flow diagram showing an example of an evaluation procedure using the integrated high-throughput automated evaluation system 1000 as a modified example, in which the integrated high-throughput automated evaluation system 1000 does not incorporate a nanoindentation tester. The embodiment shown in Figure 3B differs from the embodiment shown in Figure 3A in that the step (S212) of performing high-temperature hardness testing (nanoindentation measurement) at an arbitrary temperature is performed using a nanoindentation tester external to the integrated high-throughput automated evaluation system, but the remaining evaluation procedures are similar.

[0040] Example 2: Example of high-speed automatic measurement of composition-hardness-Young's modulus Here, we introduce a high-speed evaluation example that utilizes a Ni-Al binary alloy composition / temperature gradient sample. As an example, single crystal alloys A and B, which serve as the base materials for the composition gradient sample, were selected with Al contents of 10 at. % and 20 at. %, respectively. The Al content here is determined by the γ' volume fraction (f Ｖ ) are f Ｖ = 0% and f Ｖ = 70%. The gray-shaded area in the background shown in phase diagram 5(a) indicates the upper and lower limits of the composition and temperature for which composition-temperature gradient samples can be prepared using Ni-Al binary alloys. As described later, the automatic evaluation device and method for Ni-Al binary alloys require diffusion heat treatment in the γ single-phase region, and therefore the upper limit of the Al content is the concentration (C Ａｌ = 21 at. %). The lower limit concentration is 0 at. %, which corresponds to pure Ni. The upper limit temperature is the solidus temperature, and the lower limit temperature is 400°C, which is the equipment specification. Here, as an example, results using alloys with Al contents of 10 at. % and 20 at. % are shown, but the Al content can be selected arbitrarily. This concept can also be applied to multi-component superalloys, and compositionally graded samples of any multi-component superalloy can be prepared by calculation using commercially available thermochemical phase diagrams.

[0041] FIG. 5 shows an example of a design method for a compositionally graded diffusion couple. (a) is a Ni-Al phase diagram, (b) is the appearance of a compositionally graded single crystal alloy, and (c) is a perspective view of the compositionally graded single crystal alloy. In FIG. 5, single crystal bar A11 contains 10 at. % Al with the remainder being nickel and unavoidable impurities. Single crystal bar B12 contains 20 at. % Al with the remainder being nickel and unavoidable impurities. Ni13 is a 0.02 mm thick Ni foil, and stainless steel tube 14 is a support material for HIP processing of the bonded single crystal bar A11 and single crystal bar B12. Here, HIP stands for Hot Isostatic Pressing (HIP). HIP is a process in which high temperatures of several hundred to 2,000°C and isotropic pressures of several tens to 200 MPa are simultaneously applied to the workpiece. Usually, isotropic pressure is applied using a gas such as argon as a pressure medium.

[0042] Single crystal alloys A and B were cast using a unidirectional solidification furnace. As shown in Figures 5(b) and 5(c), the resulting single crystal round bar A11 and single crystal round bar B12 were cut longitudinally along the {001} plane, bonded together, and then vacuum-sealed in a stainless steel tube 14 to prepare HIP samples. To prevent reaction between the stainless steel tube 14 and the substrate, 0.02 mm-thick Ni foil 13 was placed between the single crystal round bar A11 and single crystal round bar B12 and the stainless steel during sealing. The HIP samples were subjected to HIP treatment at 1100°C, 98.6 MPa, and an Ar atmosphere for 3 hours. This allowed the two single crystal alloys to be bonded along the {001} plane. The resulting HIPed materials were then subjected to diffusion heat treatment at 1300°C for 720 hours with furnace cooling to prepare compositionally graded samples. Here, the diffusion heat treatment temperature of 1300°C is the temperature at which both single crystal alloys A and B become a single γ phase, as shown in Figure 5(a). The obtained compositionally graded samples were subjected to aging heat treatment using a temperature gradient heat treatment furnace as shown in Figure 6, to prepare composition-temperature graded samples. The set conditions were a maximum sample temperature of 1280°C, a minimum sample temperature of 981°C, and an aging time of 3 hours. The composition-temperature graded samples were cut and polished along the {001} plane to prepare evaluation samples.

[0043] A total of 10,000 automated nanoindentation tests were performed on the polished {001} plane of the composition-temperature gradient specimen prepared as described above, at intervals of 0.245 mm in the longitudinal direction and 0.075 mm in the diametric direction. Figure 7A shows the indentation load-displacement curves of 500 of the 10,000 tests. It can be seen that the load-displacement curves have a large distribution because the Al composition and γ' precipitate structure size differ for each test coordinate. Figure 7B shows the cross-sectional Al content C of the specimen. Ａｌ 1 is a graph showing the relationship between the tensile strength (at. %), hardness H (GPa), and Young's modulus Er (GPa) and the aging temperature (981°C to 1280°C). As described above, the integrated high-speed automatic evaluation system and method of the present invention can evaluate the mechanical properties of alloys having a wide range of compositions and a wide range of aging temperatures at high speed.

[0044] Example 3: High-Speed ​​Automatic Measurement of Microstructure Database This example demonstrates the relationship between the morphology of the γ' precipitate phase and aging temperature, which significantly influences the high-temperature properties of a newly developed Ni-Co-based superalloy for turbine disks. A single-crystal round bar of NiBa11.7Cr-27.0Co-1.9W-3.4Mo-3.2Al-4.4Ti-2.2Ta-0.5Hf (wt.%) was used as the evaluation sample. This composition is similar to that of TMP™-5002 alloy, a powder metallurgy alloy developed for turbine disks. The resulting round bar was subjected to homogenization heat treatment, water quenching, and aging heat treatment in a temperature-gradient heat treatment furnace as shown in Figure 6, as in Example 2. The set conditions for this were a maximum sample temperature of 1200°C, a minimum sample temperature of 680°C, and a 3-hour aging time. The resulting temperature-gradient sample was cut longitudinally along the {001} plane and polished to prepare the evaluation sample.

[0045] Figures 8A to 8F show examples of the results of automated experiments and analyses using nanoindentation and SEM on a polished {001} plane. The total number of measurement points where automated experiments and analyses were performed was 2,400, with 10 automated measurements performed at each of 240 temperature points. Figure 8A shows an example of automated nanoindentation performed on a temperature-gradient heat-treated sample (S120 in Figure 3B) of a multi-component Ni-based superalloy. The heat treatment temperatures of the temperature-gradient heat-treated sample can be estimated as follows: 1164.3°C at measurement point a, 1161.7°C at measurement point b, 1086.9°C at measurement point c, 1014.0°C at measurement point d, 940.1°C at measurement point e, 868.7°C at measurement point f, 793.2°C at measurement point g, 721.7°C at measurement point h, and 647.5°C at measurement point i. Figure 8Aa is an SEM photograph showing the results of a nanoindentation test (S212 in Figure 3B) performed on the microstructure positions of the temperature-gradient heat-treated sample, which are shown as exemplary measurement points a through i. Figure 8Ab is a three-dimensional diagram showing the indentation load-displacement curves obtained at a total of 240 temperature measurement points, including the exemplary measurement points a through i. The horizontal axis represents depth [nm], the vertical axis represents force [μN], and the depth represents heat treatment temperature [°C]. Figure 8Ac is a two-dimensional diagram showing the obtained indentation load-displacement curves. The horizontal axis represents depth [nm] and the vertical axis represents force [μN]. Furthermore, as shown in Figure 8B, the coordinate information from the indentation measurement was transferred to the SEM, and the indentation shape was automatically acquired at each coordinate position (S220 in Figure 3B). By automatically acquiring multiple low-magnification SEM images containing height information for measurement points a through i of the temperature-gradient heat-treated sample, it is possible to reconstruct images containing height information at each measurement position. Furthermore, Figure 8C shows an example of the results of automatically calculating the coordinates corresponding to the flat sample surface near the indentation and then automatically performing high-resolution SEM photography at the estimated working distance WD, showing measurement points a to i of a temperature-gradient heat-treated sample. It can be confirmed that it is possible to automatically obtain microstructural information, including fine γ' precipitates measuring several tens to several hundreds of nanometers.Figure 8D shows the results of analysis of (a) hardness H (GPa), (b) damping modulus Er (GPa) obtained from the indentation load-displacement curve shown in Figure 8A, and (c) pile-up height Hp, analyzed using a shape analysis program (S230 in Figure 3B) based on the indentation height information in Figure 8B. It can be seen that H, Er, and Hp fluctuate in response to the structural changes shown in Figure 8C. Furthermore, Figure 8E shows (a) yield strength σ, analyzed using the information shown in Figure 8D and an inverse analysis program (S230 in Figure 3B). Ｙ (a) (b) work hardening rate B (MPa), (c) all the obtained stress-strain curves, and (d) an example of a stress-strain curve. It was confirmed that by using an inverse analysis program, it is possible to quickly and automatically obtain a large amount of data showing the influence of the structure on the stress-strain curve, which is essential for alloy design and part design. Figure 8F shows the volume fraction f of (a) aging precipitates and cooling precipitates, which was analyzed from the SEM image information shown in Figure 8A using an automatic image processing program (S310 in Figure 3B). Ｖ (b) precipitate size, and (c) precipitate shape. Here, the precipitate shape (median superellipse) is calculated using the ratio of the major axis to the minor axis of a superellipse. A superellipse is a closed curve similar to an ellipse. As shown in Figure 8F, the size and quantity of γ' precipitate particles growing with aging vary significantly depending on the coordinate of the {001} observation plane. As shown in Figure 8F(a), the obtained volume fractions tended to be relatively close to those estimated using Thermo-Calc™, a commercially available thermodynamic equilibrium calculation software. Meanwhile, as shown in Figure 8F(b), it was possible to comprehensively obtain precipitate sizes over a wide aging temperature range. These size data serve as an important database for developing a prediction formula based on the Ostwald ripening of precipitates. Specifically, they contribute to determining various parameters (e.g., reaction time, diffusion coefficient, activation energy) necessary for calculating the Ostwald ripening rate. As described above, the automatic evaluation device and method for alloy composition search of the present invention can automatically calculate the volume fraction f Ｖ, precipitate size, and precipitate shape) and mechanical properties (hardness H (GPa), damping modulus Er (GPa), yield strength σ Ｙ (MPa), work hardening rate B (MPa), stress-strain curve) can be obtained more quickly than with conventional methods.

[0046] Example 4: High-Speed ​​Automated Measurement of a Solid Solution Strengthening Database This example demonstrates a high-temperature, high-speed processing evaluation using a Ni-Ta-W compositionally graded sample. The evaluation sample was fabricated from an approximately 1.0 mm thick Ni plate, a 0.2 mm thick Ta plate, and a 0.2 mm thick W plate. These plates were alternately stacked in a Ni-Ta-Ni-W-Ni configuration and temporarily bonded in a spark plasma sintering (SPS) apparatus under vacuum conditions of 700°C, 98 MPa, and 5 min. The SPS material was then subjected to a diffusion heat treatment in an Ar atmosphere using a HIP apparatus under conditions of 1250°C, 50 MPa, and 24 hours, resulting in a compositionally graded sample. An SEM image of the resulting compositionally graded sample is shown in Figure 9. At the Ni-Ta initial interface and the Ni-W initial interface, Ni-Ta and Ni-W binary compositionally graded alloys can be fabricated, respectively, perpendicular to the interface, and a Ni-Ta-W ternary compositionally graded alloy can be fabricated between the two initial interfaces.

[0047] High-temperature nanoindentation tests were performed on these compositionally graded samples. Test conditions were room temperature, 200°C, and 400°C, with a maximum load of 50 mN and a measurement interval of 0.050 mm along the compositional gradient. Figure 10 shows the indentation load-displacement curves obtained by nanoindentation tests at the coordinates of the compositionally graded sample, which is 93 at.% Ni-7 at.% Ta. While the hardness decreases from room temperature to 200°C, the hardness values ​​at 200°C and 400°C are nearly equivalent. By measuring the indentation shape (pile-up height) and utilizing the techniques described in Non-Patent Documents 5 and 7, in addition to the load-displacement curves, it is possible to estimate the high-temperature stress-strain curve of the hardness measurement coordinates (in this case, a 93 at.% Ni-7 at.% Ta alloy).

[0048] Figure 11A shows an example of automated measurement of indentation indentation shape and the resulting high-temperature stress-strain curve. (a) is an SEM image, and (b) and (c) show the three-dimensional indentation shape obtained by SEM. Figure 11A also shows an SEM photograph (Figure 11A(a)) and three-dimensional height profile (Figures 11A(b) and (c)) of the indentation, which were measured automatically at high speed using a newly introduced SEM-multichannel annular-segment backscattered electron detector. Conventionally, shape measurement was performed using an AFM, which is a function of nanoindentation. However, non-contact measurement using an SEM makes it possible to obtain three-dimensional height profiles with equivalent height accuracy.

[0049] Figure 11B shows an example of automated measurement of indentation indentation shape and the resulting high-temperature stress-strain curve. (d) shows an example of the output from the pile-up height measurement program, and (e) shows the high-temperature stress-strain curve (e.g., Ni93%-Ta7%) estimated from the load-displacement curve and indentation shape. Figure 11B(d) shows an output image from the pile-up height evaluation program, a separately developed post-processing software. This program identifies the center of gravity of the triangular pyramid indentation from the height profile and determines the pile-up height on 36 equally spaced lines from the center of gravity. This series of functions successfully achieves a speed increase of 26 times compared to conventional shape measurement methods. Figure 11B(e) shows the stress-strain curve estimated from the load-displacement curve and pile-up height.

[0050] Figure 12 shows the results of (a) composition, (b) Young's modulus, (c) hardness, (d) pile-up height, (e) working effect coefficient, and (f) yield stress obtained using the integrated high-speed processing automatic evaluation system 1000 and post-processing software. By using the present invention, it is now possible to automatically and quickly evaluate the high-temperature Young's modulus and high-temperature yield stress of Ni alloys with a wide range of Ta and W compositions. The obtained composition-yield stress data can be used as a solid-solution strengthening database for Ni-W, Ni-Ta, and Ni-Ta-W alloys. Specifically, by using this data as a solid-solution strengthening database in commercially available and separately developed strength prediction programs, such as those shown in Non-Patent Documents 3 to 5, it is possible to improve the accuracy of property prediction for Ni-based superalloys and expand the applicable composition range.

[0051] Example 5: High-Speed ​​Automated Measurement of a Solid-Solution Strengthening Database. This example demonstrates high-temperature, high-speed processing evaluation using a compositionally graded Ni-Co binary alloy sample. A diffusion couple sample was fabricated focusing on Ni-Co, an important gamma-phase constituent element in Ni-Co-based superalloys. Alternately stacked Ni and Co plates were bonded by SPS sintering. The sample was heat-treated at 1150°C for 3000 hours to fully diffuse the Ni and Co elements, followed by HIP treatment at 1120°C and 98 MPa to fabricate a compositionally graded diffusion couple sample (Figure 13A). The compositionally graded sample was subjected to hardness testing at 630 points using nanoindentation in the temperature range from room temperature to 500°C. The results are shown in Figure 13B. In the Ni composition ratio range of 1 at% to 23 at%, the alloys exhibited roughly equivalent properties, with hardness H ranging from 3.4 to 4.1 GPa at 300 K, and hardness tests were conducted at 370 K, 470 K, 570 K, 670 K, and 770 K. The hardness softened with increasing temperature, with hardness H ranging from 2.2 to 3.0 GPa at 670 K, but decreasing to 1.2 to 1.7 GPa at 770 K. Furthermore, in the Ni composition ratio range of 44 at% to 91 at%, the hardness H at room temperature of 300 K was in the range of 1.9 to 2.1 GPa, which was approximately half the hardness H of Ni-Co binary alloys in the Ni composition ratio range of 1 at% to 23 at%. Ni-Co binary alloys with Ni composition ratios of 30 at% and 37 at% transition between these two hardness values ​​depending on the hardness test temperature. For the Ni-Co binary alloy with a Ni composition ratio of 30 at%, the hardness H is in the range of 3.0 to 3.2 GPa at 570 K, but drops to the range of 1.5 to 2.0 GPa at 670 K. For the Ni-Co binary alloy with a Ni composition ratio of 37 at%, the hardness H is in the range of 3.0 to 3.2 GPa at 470 K, but drops to the range of 1.6 to 1.8 GPa at 570 K.

[0052] Figure 14 shows a hardness map overlaid on a Ni-Co binary phase diagram. At room temperature, hardness gradually increased with increasing Co content. Furthermore, a rapid increase in hardness can be seen at the Co content where the crystal structure transforms from FCC (face-centered cubic) to HCP (hexagonal closest packing) on ​​the phase diagram. Furthermore, hardness gradually decreased with increasing temperature across all Co content regions. It is particularly noteworthy that, while the phase diagram shows a tendency for the amount of Co that undergoes phase transformation to increase with increasing temperature, the hardness results accurately represent this phase transformation behavior. As described above, the integrated high-speed automated evaluation system 1000 was found to be capable of accurately obtaining hardness maps for a wide range of compositions and measurement temperatures for any alloy system, and to store data showing mechanical properties on a general phase diagram.

[0053] <Automated Composition Analysis Software for γ-γ' Two-Phase Microstructures> This section describes the necessity and application examples of an automated analysis program for tie-line information in γ-γ' two-phase microstructures. Tie-lines are isotherms that pass through the two-phase region on a phase diagram. Creating a phase diagram for a multi-component alloy requires a large number of γ-γ' tie-line composition sets. For example, in a quaternary composition space, phase boundaries are curved in three dimensions, and determining them requires hundreds of points (phase boundary composition data). Because the number of required tie-line composition sets increases exponentially with the number of constituent elements, the introduction of an automated analysis program is essential. The automated analysis program can determine the compositions of the γ and γ' phases from elemental maps and SEM images obtained by EPMA surface analysis of a γ-γ' two-phase microstructure in a 25 x 25 mm area where local equilibrium exists. This program can also be applied to some microstructures consisting of 0.4 mm γ' phase grains, exceeding the 1 mm spatial resolution of EPMA. For example, it can handle up to 8-component systems, but is not limited to this. The number of dimensions analyzed can be increased or decreased depending on the number of constituent elements in the multidimensional alloy being analyzed. Generally, the accuracy of composition measurement by EPMA is superior in point analysis, but since it is necessary to identify the positions of precipitated grains of several micrometers or less and to measure multiple points, the time required for analysis is three times or more that of area analysis.

[0054] Figures 15A-E show an example of an analysis performed by an automated composition analysis program according to one embodiment of the present invention, along with an external view of its interface. This automated composition analysis program employs surface analysis, eliminating the need to identify the location of γ' grains and enabling data acquisition through a single measurement. For example, in a quaternary system, the composition can be automatically determined in a measurement time of approximately four minutes per region. Figure 15A shows an EPMA map of each element in a Ni-Co-Al-Ti quaternary alloy. Figure 15B shows an SEM photograph of the crystal grains to be analyzed in a Ni-Co-Al-Ti quaternary alloy, along with the target region for EPMA surface analysis. Figure 15C shows the tie-line data setting conditions for determining the γ-γ' composition required for a phase diagram database created by the automated composition analysis program. The tie-line data setting screen 500 has a composition folder load instruction section 501, a current map number display section 502, an element map forward button 504, an element selection button 506, a noise threshold setting section 507, a noise removal instruction section 508, a first boundary line selection button 510, a second boundary line selection button 512, a skip button 514, a single-phase designation button 516, and a tie-line registration button 518.

[0055] The element map to be analyzed is specified using the element map forward button 504, the element to be analyzed is selected using the element selection button 506, and the corresponding phase is specified using the pop-up of the first boundary selection button 510 (Boundary 1) or the second boundary selection button 512 (Boundary 2). The noise threshold setting field 507LQ is a pop-up for setting parameters for removing noise, such as areas affected by voids, from the data included in the element map, e.g., 2,400 points. The noise removal instruction field 508 removes data included in the element map that is determined to be noise based on the threshold value set in the noise threshold setting field 507LQ from the analysis target. Once the phase specification and noise removal for the element map are complete, the user presses the tie line registration button 518, or the skip button 514 or single phase specification button 516.

[0056] Figure 15D shows the results of EPMA area analysis of the γ and γ' phase compositions. The standard sample information and the two phase boundary compositions obtained by the analysis are displayed. The element names, characteristic X-ray line type, and intensity of the standard sample are displayed. Phase boundary composition Boundary 1 is 33% Ni, 55% Co, 7% Al, and 4% Ti (units: atomic %). Phase boundary composition Boundary 2 is 46% Ni, 32% Co, 11% Al, and 11% Ti (units: atomic %). Approximately 1,000 sets of EPMA elemental maps were obtained using a compositionally graded sample with a composition range that encompasses the γ-γ' two-phase region of the Ni-Co-Al-Ti quaternary alloy, and tie-line composition sets were determined for each. Figure 15E shows tie-line data for the Ni-Co-Al-Ti quaternary alloy. The dark gray circles represent the phase boundary compositions on the gamma-phase side, the light gray circles connected by a straight line represent the phase boundary compositions of phases other than the gamma phase that correspond to the gamma-phase compositions of the dark gray circles, and the two black circles connected by a thin line represent the phase boundary compositions of phases other than the gamma phase. These tie-line data can be used as a database for calculated phase diagrams, and will greatly contribute to improving the calculation accuracy of multi-component alloy phase diagrams.

[0057] <Data reanalysis and mapping software> The mechanical, structural, compositional, and process information obtained by the automated evaluation device for alloy composition exploration of the present invention can be stored in the developed data reanalysis and mapping software (S500 in Figure 3) and converted into a composition-process-structural-property database that clarifies the interrelationships between these information. Furthermore, by visualizing big data, it becomes possible to detect data that show abnormal values ​​from a data set of more than several million data points.

[0058] FIG. 16 shows an example of the interface of the data reanalysis / mapping software. FIG. 16A is a diagram showing markers corresponding to each measurement point on a position map of the measured sample. This data reanalysis / mapping software is stored, for example, in the post-processing unit 200 or the property prediction program 300. This data reanalysis / mapping software accesses the mechanical property distribution storage unit 120 and the measurement data storage unit 130 to read the collected measurement data, including nanoindentation, WDS / EDS, SEM, and EBSD information at each measurement point. For example, as shown in FIG. 16A, this data reanalysis / mapping software can display markers corresponding to each measurement point on a position map of the measured sample 10 surface for any selected data. Instead of a position map of the measured sample 10 surface, markers corresponding to each measurement point may be displayed on a phase diagram. Here, the phase diagram can be created by reading a TDB file, which is a data file for a thermodynamic equilibrium phase diagram.

[0059] 16B(a)-(e) are diagrams showing mechanical properties such as the damping modulus Er (GPa), pile-up height Hp, work hardening rate B (MPa), hardness H (GPa), and yield strength sY (MPa) at each measurement point of the test sample on a phase diagram or position map. As shown in FIG. 16B(a)-(e), mechanical properties such as the damping modulus Er (GPa), pile-up height Hp, work hardening rate B (MPa), hardness H (GPa), and yield strength sY (MPa) can be mapped on a phase diagram or position map, allowing alloy developers to easily understand the measurement data.

[0060] 16C is a diagram showing the display of each property value at any point selected from the measurement points shown in FIG. 16A for the measured sample in the data reanalysis and mapping software. The measured sample property value display 600 includes a phase diagram-Ni visualization system display section 610, a sample and measurement information display section 630, and a measurement point information display section 660. The phase diagram-Ni visualization system display section 610 includes a database selection section 612, an update tdb / sample list button 614, a register state diagram button 616, a create property sheet button 618, a tdb file list button 620, an unregistered sample list button 622, a recalculate property data button 624, a recalculate state diagram button 626, and a redisplay property button 628. The sample and measurement information display section 630 includes a sample name display section 632, a sample type display section 634, a constituent element display section 636, a sample production date display section 638, a miscellaneous display section 640, an NI folder selection section 642, an EPMA folder selection section 644, an Hp folder selection section 646, an EBSD folder selection section 648, an EDS folder selection section 650, and a microstructure folder selection section 652. The measurement point information display section 660 includes an individual composition element display section 662, a mechanical property display section 664, a crystal orientation display section 666, and a microstructure display section 668. The individual composition element display section 662 includes Ni (nickel), Co (cobalt), Cr (chromium), W (tungsten), Mo (molybdenum), Nb (niobium), Al (aluminum), Ti (titanium), Hf (hafnium), C (carbon), B (boron), and Zr (zirconium). The mechanical property display field 664 includes σY, Er, H, Hp, and B. Here, σY is yield strength, Er is damping modulus, H is hardness, Hp is pile-up height, and B is work hardening rate. The microstructure display field 668 includes fγ', dγ', and TCP (Topologically Close Packed). fγ' is the γ' phase fraction, dγ' is the average grain size of γ' phase precipitates, and TCP is the presence or absence of TCP.

[0061] Figure 16D is a diagram displaying the raw data of the load-displacement curve, microstructure, and pile-up analysis obtained by nanoindentation. The raw data display screen 700 has an NI profile screen 710, a microstructure screen 720, and a pile-up screen 730. Reanalysis of the microstructure and pile-up analysis is possible. The NI profile screen 710 displays an SEM image 712 of the indentation and a stress-displacement curve 714. The microstructure screen 720 displays an SEM image in which the detected γ' phase region is colored black. The pile-up screen 730 displays the position of the maximum height obtained by analysis on the image of the indentation.

[0062] As described above, the data reanalysis / mapping software can reanalyze raw data according to the purpose, and has the function of mapping composition-process-structure-property data onto a phase diagram or position map to make it easier for alloy developers to understand, thereby providing maximum support for strategic planning for alloy development.

[0063] The integrated high-speed automatic evaluation system of the present invention, which serves as an automatic evaluation device for alloy composition exploration, offers the following advantages. The present invention relates to a high-speed automatic evaluation technology for a composition-process-structure-property database, which significantly improves accuracy and expands the prediction range in performance prediction in the field of structural materials, and to an all-in-one automatic evaluation system that makes this possible. This capability is demonstrated by using evaluation samples such as compositionally gradient materials of multi-component alloys with more than ten elements, such as Ni-based superalloys, temperature-graded samples in which the heat treatment temperature is graded in one direction, or composition-temperature-graded materials that have both. Here, the composition-temperature-graded evaluation samples are samples with different compositions and heat treatment temperature conditions at each coordinate within a single sample. The automatic evaluation system for alloy composition exploration of the present invention is characterized by its ability to automatically and quickly evaluate composition analysis, structure feature analysis, and high-temperature mechanical properties for such special samples. Specifically, this evaluation system is a high-resolution, dual-beam FE-SEM capable of high-resolution analysis of structure and analysis of indentation indenter shape, equipped with a WDS / EDS capable of composition analysis, and a high-temperature nanoindenter installed inside the SEM to automatically and quickly obtain the high-temperature Young's modulus and high-temperature hardness at each coordinate.

[0064] Furthermore, the post-processing software linked to the automated evaluation device for alloy composition exploration of the present invention, which includes a composition analysis program, an automatic image processing program for structure, and a mechanical property analysis program, automatically analyzes the shape of precipitates, composition, and stress-strain curves at measurement points, respectively. In this way, by installing a sample for composition / process gradient evaluation in the evaluation system, conducting an automatic experiment, and executing post-processing, a composition-process-structure-property database can be evaluated at high speed. For example, typical alloy manufacturing, heat treatment, specimen processing, and high-temperature strength evaluation require three weeks of evaluation time for one composition. In contrast, the present invention allows for the construction of a database for 10,000 compositions in three weeks, which is expected to be approximately 10,000 times faster than conventional evaluation methods.

[0065] FIG. 17A is a cross-sectional view of a key portion of a weld, which is an example of a welded sample exhibiting a compositional gradient and / or microstructural variation. The weld is made of a nickel-based superalloy turbine disk material. In FIG. 17A , a welded turbine disk material is formed by applying a welding rod (torch) 810 to a recess in a base metal 800, forming a molten weld metal 820. A heat-affected zone (HAZ) is formed at the boundary layer between the base metal 800 and the weld metal 820. Therefore, the weld has a macro-scale compositional gradient / microstructural variation across the weld metal 820, HAZ 830, and base metal 800. FIG. 17B is a dendritic solidification structure diagram of the weld metal shown in FIG. 17A. The dendritic solidification structure diagram of the weld metal 820 has a primary dendrite arm 822 and a secondary dendrite arm 824. FIG. 17C is a microstructural diagram of the HAZ (heat-affected zone) shown in FIG. 17A. The HAZ portion 830 has a multi-phase polycrystalline structure of a parent phase 832 and a second phase 834. Fig. 17D is a structural diagram of the parent material shown in Fig. 17A. The parent material 800 has a multi-phase polycrystalline structure of a parent phase 802, a second phase 804, and an abnormal structure 806. The abnormal structure 806 is an abnormal grain growth or an unsintered portion, etc., and is a site that determines the quality / macro-characteristics of the part.

[0066] FIG. 18A is an overall perspective view of a turbine blade 840, an example of a measured sample exhibiting a composition gradient and / or structural variation, showing a thick portion 850 and a thin portion 860. Examples of turbine blades include single-crystal turbine blades manufactured by precision casting, directionally solidified turbine blades, and complex-shaped products manufactured by a three-dimensional modeling technique as a metal additive manufacturing material. FIG. 18B is a dendritic solidification structure diagram of the thick portion shown in FIG. 18A. The dendritic solidification structure diagram of the thick portion 850 includes a primary dendrite arm 852 and a secondary dendrite arm 854. FIG. 18C is a dendritic solidification structure diagram of the thin portion shown in FIG. 18A. The dendritic solidification structure diagram of the thin portion 860 includes a primary dendrite arm 862 and a secondary dendrite arm 864. In the dendrite solidification structure diagram of the thin-walled portion 860, the dendrite solidification structure is smaller than in the dendrite solidification structure diagram of the thick-walled portion 850.

[0067] 19 is a structural diagram of a multi-phase polycrystalline structure material, which is an example of a measured sample exhibiting a composition gradient and / or structural variation. In a multi-phase polycrystalline structure material 870, the parent phase 872, the secondary phase 874, and the abnormal structure 876 have different compositions and mechanical properties. The abnormal structure 876 is a region of abnormal grain growth or an unsintered portion, etc., that determines the quality and macroscopic properties of the part.

[0068] Although the present invention has been described with reference to nickel-based superalloys as the target of alloy composition exploration, the target of evaluation by the automatic evaluation device for alloy composition exploration of the present invention is not limited to nickel-based superalloys, but may also be a cobalt-based superalloy or an iron-based superalloy, a high-entropy alloy, or even an aluminum alloy or a titanium alloy. In this case, precipitation morphology data may include, for example, crystal grains, G.P. zones (Guinier-Preston zones), atomic clusters that serve as precursors to G.P. zones, quasicrystals, etc.

[0069] The integrated high-speed processing automatic evaluation system of the present invention, which is an automatic evaluation device for alloy composition exploration, is highly effective when used with compositionally gradient samples, but it is also effective in quickly obtaining local composition-structure-property data for general structural materials with complex hierarchical structures. Furthermore, by using compositionally and temperature-gradient samples in which compositionally gradient materials are heat-treated using temperature-gradient heat treatment to create large composition and structure gradients within a single sample, it is possible to obtain a highly accurate and wide-ranging data set of composition-process-structure-property data all at once.

[0070] REFERENCE SIGNS LIST 10 Measurement sample 20 Sample holder 30 Housing 40 FE-SEM (Field Emission-Scanning Electron Microscope) 46 Precipitation morphology database 50 Nanoindentation tester 60 WDS (Wave Dispersive Spectroscopy) / EDS (Energy Dispersive Spectroscopy) 66 Composition database (composition ratio storage unit) 70 EBSD (Electron Back-Scatter Diffraction) 100 Integrated evaluation device 110 Measurement instrument linkage controller 120 Mechanical property distribution storage unit 130 Measurement data storage unit 140 Physical property data storage unit 200 Post-processing unit 300 Property prediction program S230 Shape analysis / inverse analysis program S300 Structure information S310 Automatic image processing program S400 Composition information S410 Automatic composition analysis program S500 Reanalysis / mapping software

Claims

1. A sample holder that holds a sample to be measured in a predetermined position; a mechanical property distribution memory that stores the distribution of mechanical properties measured by a nanoindentation tester based on the position of an indentation mark formed on the sample to be measured by the nanoindentation tester; a housing that holds at least one type of measuring instrument selected from the group consisting of a wavelength dispersive X-ray spectrometer or an energy dispersive X-ray spectrometer that analyzes the constituent elements of an alloy, a field emission scanning electron microscope that measures the microstructural shape of the alloy, and an electron backscatter diffraction device that analyzes the orientation distribution, texture, or crystal phase distribution of crystal grains; and a measurement instrument linkage controller that controls the measurement of the sample to be measured by at least one type of measuring instrument selected from the group consisting of the wavelength dispersive X-ray spectrometer or the energy dispersive X-ray spectrometer that analyzes the constituent elements of an alloy, the field emission scanning electron microscope that measures the microstructural shape of the alloy, and the electron backscatter diffraction device that analyzes the orientation distribution, texture, or crystal phase distribution of crystal grains, attached to the housing; An automatic evaluation device for alloy composition exploration comprising: a measurement data storage unit that stores the measurement data of the measurement instrument as measurement data of the sample measured by the measurement instrument based on the position of the indentation mark formed on the sample; and a post-processing unit that calculates physical property data corresponding to the measurement data of the measurement instrument.

2. The automatic evaluation device for alloy composition exploration according to claim 1, wherein the measured sample is any one of: a compositionally graded material having a composition ratio that is graded between upper and lower limit values ​​for the composition elements of the alloy system to be evaluated; a heat treatment temperature graded material obtained by heat treating the compositionally graded material or a test material having a uniform composition in place of the compositionally graded material in a furnace in which the heat treatment temperature is graded between upper and lower limit values; a heat-affected part that includes a region of the base material that is not melted but in which the microstructure and characteristics of the measured sample have been changed by a welding or thermal cutting operation; a metal additive manufacturing material produced as the metal part by melting a metal powder in a portion required for the metal part with an electron beam or a fiber laser and then solidifying it; and a metal powder injection molding material that uses a metal fine powder as a raw material, adds a binder without melting the metal fine powder, and injection molds the metal fine powder, and degreases and sinters the molded body molded by the injection molding to obtain a metal part.

3. The automatic evaluation device for alloy composition exploration according to claim 2, wherein the metal additive manufacturing material is manufactured by any one of the following: a powder bed method in which a laser beam or electron beam is irradiated onto a powder bed on which metal powder is spread, and melting and solidifying are repeated for each layer; a directed energy deposition method in which powder or wires, etc. are supplied, and the powder is melted with a laser or electron beam and deposited to create a shaped object; a fused deposition modeling method in which metal powder is placed in thermoplastic resin, layered while melting with heat, and the shaped object is degreased after modeling and sintered to solidify the metal powder; or a binder jet method in which a liquid binder is sprayed from a nozzle onto metal powder to form a shape, and when the spraying and solidification of the binder is completed for each layer, the modeling plate is lowered and the powder is spread again, and this process is repeated for each layer, and after modeling, the material is sintered in a high-temperature furnace or heater to remove the binder.

4. The automatic evaluation device for alloy composition exploration described in any one of claims 1 to 3, further comprising a nanoindentation testing machine that presses an indenter against the sample to measure mechanical properties based on the shape of the indentation mark, wherein the mechanical property distribution memory unit stores the distribution of mechanical properties measured by the nanoindentation testing machine based on the position of the indentation mark formed on the sample to be measured, and the casing unit holds, together with the nanoindentation testing machine, at least one type of measuring instrument among the wavelength dispersive X-ray spectrometer or energy dispersive X-ray spectrometer, the field emission scanning electron microscope, or the electron backscatter diffraction device, and the measuring instrument linkage controller controls the measurement of the sample to be measured by the nanoindentation testing machine attached to the casing unit and at least one type of measuring instrument among the wavelength dispersive X-ray spectrometer or energy dispersive X-ray spectrometer, the field emission scanning electron microscope, or the electron backscatter diffraction device.

5. The automatic evaluation device for alloy composition exploration described in claim 2 or 3, wherein the target of the alloy composition exploration is one or more selected from the group consisting of the composition gradient material, heat treatment temperature gradient material, heat-affected component, metal additive manufacturing material, and metal powder injection molding material, and in the measurement data storage unit, the measurement data of the measured sample is at least one of the following: crystal phase equilibrium composition data corresponding to the composition elements of the alloy, fine precipitate identification data and high-speed indentation shape acquisition data corresponding to the microstructural shape of the alloy, polycrystalline orientation data corresponding to the anisotropy of the alloy, or load / displacement information corresponding to the mechanical properties measured by the nanoindentation testing machine.

6. The automatic evaluation device for alloy composition exploration as described in claim 5, wherein the target of the alloy composition exploration is a nickel-based superalloy, and in the measurement data storage unit, the measurement data of the measured sample is at least one of the following: γ / γ' equilibrium composition data corresponding to the composition elements of the alloy, fine precipitate identification data and high-speed indentation shape acquisition data corresponding to the microstructural shape of the alloy, polycrystalline orientation data corresponding to the anisotropy of the alloy, or load / displacement information corresponding to the mechanical properties measured by the nanoindentation testing machine.

7. The automatic evaluation device for alloy composition exploration described in claim 5, wherein in the post-processing section, the physical property data corresponding to the measurement data of the measuring instrument is at least one of composition data corresponding to the crystal phase equilibrium composition data, precipitation morphology data corresponding to the fine precipitate identification data, or the high-speed indentation shape acquisition data, and polycrystalline orientation data, or load / displacement information, and at least one of elastic constants, critical resolved shear stress (CRSS), work hardening coefficient, or creep deformation rate is calculated and processed.

8. The automatic evaluation device for alloy composition exploration described in claim 6, wherein in the post-processing section, the physical property data corresponding to the measurement data of the measuring instrument is read in at least one of composition data corresponding to the γ / γ' equilibrium composition data, precipitation morphology data corresponding to the fine precipitate identification data, or the high-speed indentation shape acquisition data, and polycrystalline orientation data, or load / displacement information, and at least one of elastic constants, critical resolved shear stress (CRSS), work hardening coefficient, or creep deformation rate is calculated and processed.

9. The measured sample is a heat-treated temperature gradient material obtained by heat-treating the composition gradient material or a test material having a uniform composition in place of the composition gradient material in a furnace in which the heat treatment temperature is gradiently distributed between an upper limit value and a lower limit value, and the position of the indentation mark formed on the measured sample is linked to the heat treatment temperature. An automatic evaluation device for alloy composition exploration described in any one of claims 2, 3 and 5 to 8.

10. An automatic evaluation device for alloy composition exploration described in any one of claims 1 to 9, wherein the structural shape of the alloy indicates a boundary region of a phase transformation in which the crystal structure changes between a first crystal structure and a second crystal structure.

11. An automatic evaluation device for exploring alloy compositions according to claim 10, wherein the first crystal structure is a face-centered cubic lattice and the second crystal structure is a hexagonal close-packed lattice.

12. The automatic evaluation device for searching for an alloy composition according to claim 10, wherein the composition ratio of the composition elements changes at the boundary between the first crystal structure and the second crystal structure.

13. An automatic evaluation device for alloy composition exploration as described in claim 10, wherein the mechanical properties measured by the nanoindentation testing machine indicate changes in the mechanical properties across the boundary line between the first crystal structure and the second crystal structure.

14. The automatic evaluation device for alloy composition exploration according to claim 13, wherein the mechanical property is hardness.

15. An automatic evaluation device for alloy composition exploration as described in claim 9, wherein the measured sample has a composition range that encompasses the gamma / gamma' two-phase structure, and the post-processing unit extracts tie-line information of the gamma / gamma' two-phase structure for an observation area consisting of a gamma / gamma' two-phase structure in a nickel-based superalloy by using an element map produced by the electron backscatter diffraction device and by distinguishing between the gamma phase and the gamma' phase by using a scanning electron microscope.

16. The automatic evaluation device for alloy composition exploration described in claim 9, wherein the measured sample is a heat-treated temperature gradient material obtained by heat-treating the composition gradient material in a furnace in which the heat treatment temperature is gradiently distributed between an upper limit value and a lower limit value, and the size and amount of γ' precipitate particles are analyzed according to the heat treatment temperature to construct γ' precipitate particle volume fraction data.

17. An automatic evaluation method for alloy composition exploration, comprising: performing scanning electron microscope observation or electron backscatter diffraction observation of a test sample, selecting positions for mechanical measurement based on the texture, phase, or crystal structure on the obtained image; performing a high-temperature hardness test (nanoindentation measurement) at a predetermined temperature for the selected positions for mechanical measurement of the test sample; performing indentation shape measurement for the positions for mechanical measurement to calculate a high-temperature stress-strain curve for the test sample; and linking the data of the high-temperature stress-strain curve to the positions observed in the scanning electron microscope observation or electron backscatter diffraction observation of the test sample.

18. An automatic evaluation method for alloy composition exploration, comprising: performing an indentation shape measurement on a test sample on which a high-temperature hardness test (nanoindentation measurement) has been performed at a predetermined temperature using a nanoindentation testing machine, at a position on the test sample where an indentation mark has been formed; calculating a high-temperature stress-strain curve for the test sample based on the results of the indentation shape measurement; performing a scanning electron microscope observation or an electron backscatter diffraction observation on the test sample; selecting a detailed position to be observed by scanning electron microscope or electron backscatter diffraction using the indentation mark of the test sample on an image obtained by the scanning electron microscope observation or the electron backscatter diffraction observation as a position for mechanical measurement; measuring the texture, phase, or crystal structure of the detailed position by the scanning electron microscope observation or the electron backscatter diffraction observation; and linking the position of the test sample observed by the scanning electron microscope or the electron backscatter diffraction observation to mechanical measurement data from the texture, phase, or crystal structure of the indentation mark of the test sample.

19. The automatic evaluation method for alloy composition exploration according to claim 17 or 18, wherein the measured sample is any one of: a composition-gradient material having a composition ratio that is graded between upper and lower limit values ​​for the composition elements of an alloy system to be evaluated; a heat-treated temperature-gradient material obtained by heat-treating the composition-gradient material or a test material having a uniform composition in place of the composition-gradient material in a furnace in which the heat treatment temperature is graded between upper and lower limit values; a heat-affected component including an area of ​​a base material (metal, thermoplastic material, etc.) that is not melted but whose microstructure and characteristics have been changed by welding or thermal cutting operations; a metal additive manufacturing material obtained by melting and solidifying metal powder in a required area with an electron beam or fiber laser to produce a metal part; and a metal powder injection molding material using metal fine powder as a raw material, injection molding the metal fine powder by adding a binder without melting it, and degreasing and sintering the molded body molded by the injection molding to obtain a metal part.

20. The automatic evaluation method for alloy composition exploration according to claim 19, wherein the metal additive manufacturing material is manufactured by any one of the following: a powder bed method in which a laser beam or electron beam is irradiated onto a powder bed on which metal powder is spread, and melting and solidifying are repeated for each layer; a directed energy deposition method in which powder or wires, etc. are supplied, and the powder is melted with a laser or electron beam and deposited to create a shaped object; a fused deposition modeling method in which metal powder is placed in thermoplastic resin, layered while melting with heat, and the shaped object is degreased after modeling and sintered to solidify the metal powder; or a binder jet method in which a liquid binder is sprayed from a nozzle onto metal powder to form a shape, and when the spraying and solidification of the binder is completed for each layer, the modeling plate is lowered and the powder is spread again, and this process is repeated for each layer, and after modeling, the material is sintered in a high-temperature furnace or heater to remove the binder.

21. The automatic evaluation method for alloy composition exploration described in claim 19, wherein the measured sample is a heat treatment temperature gradient material obtained by heat treating the composition gradient material or a test material having a uniform composition in place of the composition gradient material in a temperature gradient heat treatment furnace in which the heat treatment temperature is gradiently distributed between an upper limit value and a lower limit value, and the heat treatment temperature is stored in a composition ratio memory unit together with the composition ratio memory of the measured sample at the position of the mechanical measurement.

22. An automatic evaluation method for alloy composition exploration described in any one of claims 17 to 21, wherein structural information for the measured sample is obtained using high-magnification scanning electron microscope observation for the position of the mechanical measurement, and the structural information includes at least one of crystal grain size, precipitated grain size, or volume fraction.

23. An automatic evaluation method for alloy composition exploration described in any one of claims 17 to 22, comprising: obtaining composition information for the measured sample using measurements by a wavelength dispersive X-ray spectrometer or an energy dispersive X-ray spectrometer for the position of the mechanical measurement; the composition information including at least one of each coordinate composition, parent phase composition, or precipitate composition of the measured sample; and storing the composition ratio of the composition elements at the position of the mechanical measurement observed by the wavelength dispersive X-ray spectrometer or energy dispersive X-ray spectrometer in a composition ratio memory unit.

24. The automatic evaluation method for alloy composition exploration described in claim 19, wherein the measured sample is a compositionally gradient material, and for metal plates consisting of each composition element of the alloy system to be evaluated, metal plates of the composition elements are alternately stacked, and temporarily joined by spark plasma sintering in a vacuum at a first predetermined temperature while being pressed with a first predetermined stress and held for a first predetermined time, and the temporarily joined spark plasma sintered material is subjected to diffusion heat treatment using a hot isostatic pressing device in an Ar atmosphere at a second predetermined temperature while being pressed with a second predetermined stress and held for a second predetermined time, thereby producing a compositionally gradient sample.

25. The metal plates consisting of each composition element of the alloy system to be evaluated are a set of three metal plates consisting of a first metal element, a second metal element, and a third metal element, in which the metal plate of the first metal element is used as an intermediate layer, and the metal plate of the second metal element and the metal plate of the third metal element are laminated on the upper and lower sides of the metal plate of the first metal element, respectively; and in a compositionally gradient sample obtained by subjecting the temporarily joined spark plasma sintered material to a diffusion heat treatment, a binary compositionally gradient alloy of the first metal element and the second metal element is generated in a first initial interface between the metal plate of the first metal element and the metal plate of the second metal element in a direction perpendicular to the first and second initial interfaces, and a binary compositionally gradient alloy of the first metal element and the third metal element is generated in a second initial interface between the metal plate of the first metal element and the metal plate of the third metal element, The method for automatically evaluating alloy composition exploration according to claim 24, wherein the thickness of the metal plate of the first metallic element is such that a ternary composition gradient alloy of the first, second, and third metallic elements is generated between the first and second initial interfaces.

26. The automatic evaluation method for alloy composition exploration described in claim 25, wherein the first metallic element is Ni, the second metallic element is Ta, and the third metallic element is W, and the binary composition gradient alloy of the first metallic element and the second metallic element is Ni-Ta, the binary composition gradient alloy of the first metallic element and the third metallic element is Ni-W, and the ternary composition gradient alloy of the first, second, and third metallic elements is Ni-Ta-W.

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