A method for displaying isothermal softening microstructure of high nitrogen martensitic steel by reconstructing variants and applications thereof

Abstract

The application discloses a method and application for displaying isothermal softening structure of high-nitrogen martensitic steel by reconstructing variants, and relates to the field of material science and technology. The method comprises the following steps: data acquisition, obtaining electron backscatter diffraction data of the high-nitrogen martensitic steel after isothermal softening; data processing, performing calculation and smoothing processing on the electron backscatter diffraction data to obtain calculated and smoothed electron backscatter diffraction data; variant reconstruction, performing variant reconstruction on the calculated and smoothed electron backscatter diffraction data according to an orientation relationship; and quantifying the variants to realize image visual analysis and statistics of the martensitic variants. The application can quantitatively display the evolution of the martensitic variants in the isothermal softening process by reconstructing the variants to display the isothermal softening structure of the high-nitrogen martensitic steel, thereby revealing the isothermal softening mechanism of the high-nitrogen martensitic steel, opening up a new way for the research on the softening mechanism, and having important scientific significance and application value.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of material science, and particularly relates to a method for displaying isothermal softening structure of high-nitrogen martensitic steel by reconfiguring variants and application. BACKGROUND

[0002] With the rapid development of modern industrial technology, the performance requirements of metal materials are increasingly improved. Especially in extreme working environments such as high temperature, high pressure and high stress, the thermal stability of metal materials becomes a key factor restricting their application. Thermal stability is the ability of a metal material to maintain its performance stability under high temperature conditions. Under high temperature working conditions, metal materials often undergo changes in microstructure and degradation in performance, leading to premature failure of the materials. Therefore, in-depth research on the thermal stability mechanism of metal materials is expected to improve the performance stability of materials in high temperature environments.

[0003] The research content of traditional thermal stability mechanism mainly includes carbide precipitation and coarsening, and dislocation recovery. Among them, the Ostwald ripening theory and the Lifshitz-Slyozov-Wagner theory systematically reveal the evolution and coarsening mechanism of carbides. Dislocations will annihilate and rearrange during isothermal softening, and form subgrains. However, the evolution of martensite substructure remains to be explored. Martensite variant refers to the martensite substructure with different orientations formed during the martensitic transformation process, and its distribution and morphology have a significant impact on the performance of the material. By studying the martensite variant, the formation mechanism, transformation conditions and performance characteristics of martensite can be revealed, guiding the composition design of the material and optimizing the microstructure of the material, thereby improving the thermal stability of the material. CN 106546458A discloses a method for observing martensite variants of MnNiGe-based alloy, which can observe martensite variants through traditional sample preparation, heat treatment, polishing and etching. CN 116622962 A discloses a method for preparing hot-rolled high-strength and high-toughness engineering machinery steel by adjusting martensite variants, which adjusts the rolling temperature to adjust the selectivity of martensite variants, thereby increasing the number of high-angle grain boundaries and improving the toughness. However, in the above method, the martensite variants are directly observed by simple etching method, which cannot analyze the orientation relationship between the martensite variants, nor can it be quantitatively analyzed. SUMMARY

[0004] The present application aims to at least solve one of the problems in the prior art or related art.

[0005] To this end, the first aspect of the present application provides a method for displaying isothermal softening structure of high-nitrogen martensitic steel by reconfiguring variants, comprising:

[0006] Data acquisition to obtain electron backscatter diffraction data of high-nitrogen martensitic steel after isothermal softening;

[0007] Data processing, calculating and smoothing the electron backscatter diffraction data to obtain calculated and smoothed electron backscatter diffraction data;

[0008] variant reconstruction, performing variant reconstruction on the calculated and smoothed electron backscatter diffraction data according to different orientation relationships;

[0009] Quantification and analysis are carried out to determine the reasonable orientation relationship for displaying the isothermal softening structure of high nitrogen martensitic steel based on the variant reconstruction effect under different orientation relationships, thereby achieving quantitative display of the organizational evolution of martensitic variants during the isothermal softening process through variant reconstruction, and revealing the variant evolution mechanism of the high nitrogen martensitic steel after isothermal softening.

[0010] Furthermore, the data acquisition includes:

[0011] The electron backscatter diffraction data of the high nitrogen martensitic steel after isothermal softening are obtained by using a scanning electron microscope equipped with electron backscatter diffraction, with an acquisition step length of 0.05 μm to 0.1 μm and a resolution of 80% to 100%.

[0012] Preferably, the acquisition step is 0.05 μm to 0.08 μm, and the resolution is 90% to 100%.

[0013] Furthermore, before the data acquisition, the high nitrogen martensitic steel after isothermal softening is electrolytically polished; the electrolytic polishing: the electrolyte is a perchloric acid alcohol solution with a volume fraction of 8% to 15%, the voltage is 20V to 30V, the current is 0.5A to 1.0A, and the electrolysis time is 10s to 30s.

[0014] Preferably, the electrolyte is a perchloric acid alcohol solution with a volume fraction of 8% to 10%, the voltage is 25V to 30V, the current is 0.8A to 1.0A, and the electrolysis time is 20s to 25s.

[0015] Furthermore, the data processing includes:

[0016] The electron backscatter diffraction data is calculated with a threshold of 0° to 10°, and the grain smoothing range is 0° to 20°, to form calculated and smoothed electron backscatter diffraction data.

[0017] Preferably, the electron backscatter diffraction data is calculated with a threshold of 2° to 5°, and the grain smoothing range is 5° to 10°, to form calculated and smoothed electron backscatter diffraction data.

[0018] Further, the variant reconstruction comprises: reconstructing the calculated and smoothed electron backscattering diffraction data according to a Kurdjumov-Sachs orientation relationship, a Nishiyama-Wassermann orientation relationship, a Greninger-Troiano orientation relationship and a Pitsch orientation relationship.

[0019] Further, the quantitative variant analysis comprises:

[0020] According to the reconstructed austenite grain structure, image visualization analysis and statistics of martensite variants are performed, including calculation of the variant frequency of the electron backscattering diffraction pattern, the variant pair boundary density, so as to reveal the isothermal softening mechanism of high-nitrogen martensite steel.

[0021] In a second aspect, the application provides an application of a method for displaying the isothermal softening structure of high-nitrogen martensite steel by reconstructing variants, which is used to guide the composition design of metal materials and improve the thermal stability of metal materials.

[0022] Compared with the prior art, the application has at least the following beneficial effects:

[0023] The method for displaying the isothermal softening structure of high-nitrogen martensite steel by reconstructing variants can quantitatively display the evolution of the martensite variant in the isothermal softening process, thereby revealing the isothermal softening mechanism of the material, and can provide strong theoretical support and technical guidance for improving the thermal stability of metal materials, open up a new way for the study of the softening mechanism, and has important scientific significance and application value. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 a is a variant frequency distribution graph corresponding to the Kurdjumov-Sachs orientation relationship provided in embodiment 1 of the application;

[0025] Figure 1 b is a variant pair boundary density graph corresponding to the Kurdjumov-Sachs orientation relationship provided in embodiment 1 of the application;

[0026] Figure 2 a is a variant frequency distribution graph corresponding to the Nishiyama-Wassermann orientation relationship provided in embodiment 2 of the application;

[0027] Figure 2 b is a variant pair boundary density graph corresponding to the Nishiyama-Wassermann orientation relationship provided in embodiment 2 of the application;

[0028] Figure 3a is a variant frequency distribution map corresponding to the Kurdjumov-Sachs orientation relationship provided in Example 5 of the present invention;

[0029] Figure 3 b is a variant pair boundary density map corresponding to the Kurdjumov-Sachs orientation relationship provided in Example 5 of the present invention;

[0030] Figure 4 a is a variant frequency distribution map corresponding to the Nishiyama-Wassermann orientation relationship provided in Example 6 of the present invention;

[0031] Figure 4 b is a variant pair boundary density map corresponding to the Nishiyama-Wassermann orientation relationship provided in Example 6 of the present invention;

[0032] Figure 5 a is an un-reconstructed isothermal softening microstructure map provided in Comparative Example 1 of the present invention;

[0033] Figure 5 b is an isothermal softening microstructure map of variant reconstruction by Kurdjumov-Sachs orientation relationship provided in Example 1 of the present invention;

[0034] Figure 5 c is an isothermal softening microstructure map of variant reconstruction by Nishiyama-Wassermann orientation relationship provided in Example 2 of the present invention;

[0035] Figure 5 d is an isothermal softening microstructure map of variant reconstruction by Greninger-Troiano orientation relationship provided in Example 3 of the present invention;

[0036] Figure 5 e is an isothermal softening microstructure map of variant reconstruction by Pitsch orientation relationship provided in Example 4 of the present invention.

[0037] Figure 6 a is a variant frequency distribution map corresponding to the Kurdjumov-Sachs orientation relationship provided in Example 5 of the present invention;

[0038] Figure 6 b is a variant pair boundary density map corresponding to the Kurdjumov-Sachs orientation relationship provided in Example 5 of the present invention;

[0039] Figure 7 a is a variant frequency distribution map corresponding to the Nishiyama-Wassermann orientation relationship provided in Example 6 of the present invention;

[0040] Figure 7b is the variant pair boundary density map corresponding to the Nishiyama- Wassermann orientation relationship provided in Example 6 of the present application;

[0041] Figure 8 a is the variant frequency distribution map corresponding to the Greninger- Troiano orientation relationship provided in Example 7 of the present application;

[0042] Figure 8 b is the variant pair boundary density map corresponding to the Greninger- Troiano orientation relationship provided in Example 7 of the present application;

[0043] Figure 9 a is the variant frequency distribution map corresponding to the Pitsch orientation relationship provided in Example 8 of the present application;

[0044] Figure 9 b is the variant pair boundary density map corresponding to the Pitsch orientation relationship provided in Example 8 of the present application;

[0045] Figure 10 a is the isothermal softening texture map without reconstruction provided in Comparative Example 2 of the present application;

[0046] Figure 10 b is the isothermal softening texture map with variant reconstruction by Kurdjumov-Sachs orientation relationship provided in Example 5 of the present application;

[0047] Figure 10 c is the isothermal softening texture map with variant reconstruction by Nishiyama-Wassermann orientation relationship provided in Example 6 of the present application;

[0048] Figure 10 d is the isothermal softening texture map with variant reconstruction by Greninger-Troiano orientation relationship provided in Example 7 of the present application;

[0049] Figure 10 e is the isothermal softening texture map with variant reconstruction by Pitsch orientation relationship provided in Example 8 of the present application.

[0050] Figure 11 a is the variant frequency distribution map corresponding to the Kurdjumov- Sachs orientation relationship provided in Example 9 of the present application;

[0051] Figure 11 b is the variant pair boundary density map corresponding to the Kurdjumov- Sachs orientation relationship provided in Example 9 of the present application;

[0052] Figure 12a is a variant frequency distribution map corresponding to the Nishiyama-Wassermann orientation relationship provided in Example 10 of the present invention;

[0053] Figure 12 b is a variant pair boundary density map corresponding to the Nishiyama-Wassermann orientation relationship provided in Example 10 of the present invention;

[0054] Figure 13 a is a variant frequency distribution map corresponding to the Greninger-Troiano orientation relationship provided in Example 11 of the present invention;

[0055] Figure 13 b is a variant pair boundary density map corresponding to the Greninger-Troiano orientation relationship provided in Example 11 of the present invention;

[0056] Figure 14 a is a variant frequency distribution map corresponding to the Pitsch orientation relationship provided in Example 12 of the present invention;

[0057] Figure 14 b is a variant pair boundary density map corresponding to the Pitsch orientation relationship provided in Example 12 of the present invention;

[0058] Figure 15 a is an isothermal softening texture map without reconstruction provided in Comparative Example 3 of the present invention;

[0059] Figure 15 b is an isothermal softening texture map with variant reconstruction by Kurdjumov-Sachs orientation relationship provided in Example 9 of the present invention;

[0060] Figure 15 c is an isothermal softening texture map with variant reconstruction by Nishiyama-Wassermann orientation relationship provided in Example 10 of the present invention;

[0061] Figure 15 d is an isothermal softening texture map with variant reconstruction by Greninger-Troiano orientation relationship provided in Example 11 of the present invention;

[0062] Figure 15 e is an isothermal softening texture map with variant reconstruction by Pitsch orientation relationship provided in Example 12 of the present invention. DETAILED DESCRIPTION

[0063] In order to better understand the above technical solutions, the technical solutions of the embodiments of the present application will be described in detail below through the drawings and specific embodiments. It should be understood that the specific features in the embodiments of the present application and the embodiments are detailed descriptions of the technical solutions of the embodiments of the present application, and are not limitations of the technical solutions of the present application. In the case of no conflict, the technical features in the embodiments of the present application and the embodiments can be combined with each other.

[0064] In a first aspect of the embodiments of the present application, a method for displaying isothermal softening microstructure of high-nitrogen martensitic steel by reconstructing variants is provided, comprising:

[0065] Data acquisition, obtaining electron backscatter diffraction data of high-nitrogen martensitic steel after isothermal softening;

[0066] Data processing, calculating and smoothing the electron backscatter diffraction data to obtain calculated and smoothed electron backscatter diffraction data;

[0067] Variant reconstruction, reconstructing the calculated and smoothed electron backscatter diffraction data according to different orientation relationships;

[0068] Quantification and analysis, determining reasonable orientation relationships for displaying isothermal softening microstructure of high-nitrogen martensitic steel according to the variant reconstruction effect under different orientation relationships, and then realizing quantitative display of microstructure evolution of martensitic variants in the isothermal softening process by variant reconstruction, and revealing the variant evolution mechanism of the high-nitrogen martensitic steel after isothermal softening.

[0069] The method for displaying isothermal softening microstructure of high-nitrogen martensitic steel by reconstructing variants provided by the embodiments of the present application can quantitatively display the microstructure evolution of martensitic variants in the isothermal softening process, thereby revealing the isothermal softening mechanism of the material, and can provide strong theoretical support and technical guidance for improving the thermal stability of the metal material, open up a new way for the research of the softening mechanism, and has important scientific significance and application value.

[0070] It can be understood that the method for displaying isothermal softening structure of high-nitrogen martensitic steel through reconfiguring variants provided by the embodiment of the present application is applicable to all types of high-nitrogen martensitic steel, for example, the high-nitrogen martensitic steel has a chemical composition with a weight percentage of C 0.2% to 0.5%, Si 0.2% to 1.5%, Mn 0.1% to 2%, Cr 2% to 10%, Mo 0.2% to 3%, V 0.2% to 2%, N 0.08% to 0.2%, and the balance of Fe and other inevitable impurity elements; or, the high-nitrogen martensitic steel has a chemical composition with a weight percentage of C 0.2% to 0.6%, Si≤1.0%, Mn≤1.0%, Cr 10% to 18%, Mo 0.2% to 2%, Ni≤2%, N 0.2% to 0.6%, and the balance of Fe and other inevitable impurity elements; or, the high-nitrogen martensitic steel has a chemical composition with a weight percentage of C 0.5% to 2%, Si 0.05% to 2%, Mn 0.1% to 2%, Cr 2% to 6%, Mo 3% to 15%, Co 5% to 10%, N 0.1% to 0.4%, W 1% to 3%, V 1% to 3%, and the balance of Fe and other inevitable impurity elements; and the like. The method for displaying isothermal softening structure of high-nitrogen martensitic steel through reconfiguring variants provided by the embodiment of the present application first acquires electron backscatter diffraction data after isothermal softening through a scanning electron microscope with electron backscatter diffraction, then reconfigures martensitic variants based on the data collected by electron backscatter diffraction, displays isothermal softening structure of high-nitrogen martensitic steel, and thus reveals isothermal softening rules. Specifically, the following steps are included: (1) before data acquisition, preparing an isothermal softening sample and performing a thermal stability experiment, and the experimental method of thermal stability is as follows: after quenching and tempering treatment, the high-nitrogen martensitic steel is subjected to isothermal treatment at a temperature of 500°C to 700°C for 2h to 96h; as the isothermal softening temperature increases and the isothermal softening time prolongs, the structure will obviously recover. Under the premise of maintaining the morphology of lath martensite, the isothermal softening temperature is preferably 550°C to 650°C, and the isothermal time is preferably 2h to 72h. (2) collecting electron backscatter diffraction data by using a scanning electron microscope with electron backscatter diffraction; (3) importing the electron backscatter diffraction data into MATLAB for calculation and smoothing processing to obtain calculated and smoothed electron backscatter diffraction data; (4) reconfiguring variants according to the orientation relationship based on the calculated and smoothed electron backscatter diffraction data; (5) quantifying the variants and analyzing the variant evolution mechanism after isothermal softening.

[0071] In an available embodiment, the data acquisition comprises:

[0072] The electron backscatter diffraction data of the high-nitrogen martensitic steel after isothermal softening is obtained by using a scanning electron microscope with electron backscatter diffraction, and the collection step is set to 0.05 μm-0.1 μm, and the resolution is set to 80%-100%.

[0073] It can be understood that electron backscatter diffraction (EBSD) is used to obtain crystallographic information such as crystal orientation and grain boundary misorientation. Considering the resolution and accuracy of data acquisition, and the data acquisition time, the collection step is set to 0.05 μm-0.1 μm, and the collection step is preferably 0.05 μm-0.08 μm; in order to ensure the accuracy and reliability of the data, the resolution is set to 80%-100%, and the resolution is preferably 90%-100%.

[0074] In a feasible embodiment, before the data acquisition, the high-nitrogen martensitic steel after isothermal softening is electrolytically polished; the electrolytic polishing: the electrolyte is 8%-15% by volume fraction of perchloric acid alcohol solution, the voltage is 20V-30V, the current is 0.5A-1.0A, and the electrolysis time is 10s-30s. The electrolytic polishing, preferably, the electrolyte is 8%-10% by volume fraction of perchloric acid alcohol solution, the voltage is 25V-30V, the current is 0.8A-1.0A, and the electrolysis time is 20s-25s.

[0075] Specifically, by electrolytic polishing, the surface stress layer generated after mechanical grinding of the high-nitrogen martensitic steel after isothermal softening is eliminated.

[0076] In a feasible embodiment, the data processing comprises:

[0077] The electron backscatter diffraction data is calculated with a threshold of 0°-10°, and the grain smoothing range is 0°-20°, to form the calculated and smoothed electron backscatter diffraction data. Preferably, the electron backscatter diffraction data is calculated with a threshold of 2°-5°, and the grain smoothing range is 5°-10°, to form the calculated and smoothed electron backscatter diffraction data.

[0078] Optionally, the electron backscatter diffraction data is imported into MATLAB software for data calculation and smoothing. The electron backscatter diffraction data is calculated with a threshold of 0°-10°, and the grain smoothing range is 0°-20°, to form the calculated and smoothed electron backscatter diffraction data. Preferably, the electron backscatter diffraction data is calculated with a threshold of 2°-5°, and the grain smoothing range is 5°-10°.

[0079] In an implementable embodiment, the variant reconstruction comprises: reconstructing the calculated and smoothed electron backscattering diffraction data according to a Kurdjumov-Sachs orientation relationship, a Nishiyama-Wassermann orientation relationship, a Greninger-Troiano orientation relationship and a Pitsch orientation relationship.

[0080] Specifically, we reconstruct the isothermal softening microstructure of high-nitrogen martensitic steel with different compositions according to the Kurdjumov-Sachs orientation relationship, the Nishiyama-Wassermann orientation relationship, the Greninger-Troiano orientation relationship and the Pitsch orientation relationship, and find that the reconstruction effect of the Kurdjumov-Sachs, Nishiyama-Wassermann and Greninger-Troiano orientation relationships is better, and the variant microstructure is completely reconstructed, while the reconstruction effect of the Pitsch orientation relationship is poor, and the variant microstructure is not completely displayed.

[0081] In an implementable embodiment, the quantitative variant analysis comprises:

[0082] According to the reconstructed austenite grain microstructure, image visualization analysis and statistics of martensite variants are performed, including calculation of the variant frequency, the variant boundary density of the electron backscattering diffraction pattern, so as to reveal the isothermal softening mechanism of high-nitrogen martensitic steel.

[0083] In a second aspect of the embodiment of the present application, the application of the method for displaying the isothermal softening microstructure of high-nitrogen martensitic steel by reconstructing variants is provided, and the method for displaying the isothermal softening microstructure of high-nitrogen martensitic steel by reconstructing variants is used to guide the composition design of metal materials, optimize the microstructure of metal materials, and improve the thermal stability of metal materials.

[0084] It can be understood that, in view of the increasing demand for high-performance metal materials in modern industry, the isothermal softening microstructure of high-nitrogen martensitic steel is displayed by reconstructing variants, and the softening mechanism of the material is revealed, which can provide strong theoretical support and technical guidance for improving the thermal stability of metal materials.

[0085] In the embodiment of the present application, the microstructure is observed by using a Zeiss Crossbeam 550 scanning electron microscope with electron backscattering diffraction, and the electron backscattering diffraction probe is an Oxford Instruments Symmetry S2.

[0086] The present application will be described in detail below in combination with specific embodiments, but they should not be understood as limiting the scope of protection of the present application.

[0087] Example 1

[0088] A method for displaying isothermal softening microstructure of high nitrogen martensitic steel by reconstructing variants, comprising the following steps:

[0089] (1) Prepare isothermal softening sample and conduct thermal stability experiment: the chemical composition of the experimental high nitrogen martensitic steel is detected as follows in percentage by weight: C 0.38%, Si 1.00%, Mn 0.40%, Cr 5.10%, Mo 1.40%, V 1.00%, N 0.10%, and the balance is Fe and other inevitable impurity elements. The high nitrogen martensitic steel after quenching and tempering is subjected to isothermal treatment at a temperature of 600 DEG C for 48 hours.

[0090] (2) Electrolytic polish the sample after isothermal softening treatment and collect electron backscatter diffraction data. The observation surface of the sample is electrolytically polished with 8% perchloric acid alcohol solution to eliminate the surface stress layer generated by mechanical grinding of the tempered sample. The electrolytic polishing parameters are voltage 28V and current 0.9A. Then, electron backscatter diffraction data with a step size of 0.07μm and a resolution of 95% are collected.

[0091] (3) Import the electron backscatter diffraction data into MATLAB software for data calculation and smoothing. The electron backscatter diffraction data is calculated with a threshold of 3° to form calculated and smoothed electron backscatter diffraction data, and the grain smoothing angle is 5°.

[0092] (4) Reconstruct the variants of the calculated and smoothed electron backscatter diffraction data by Kurdjumov-Sachs orientation relationship, see Table 1.

[0093] (5) Calculate the variant frequency of the entire electron backscatter diffraction pattern, as shown in Figure 1 (a). It can be seen that the variants are selectively distributed after softening, mainly with high frequency V7, V19, V21, V22 and V24 variants, accounting for 0.070, 0.075, 0.087, 0.081 and 0.078 respectively. The variant pairs V1 to V24 are classified and integrated to calculate the variant pair boundary density fraction of the entire electron backscatter diffraction pattern, as shown in Figure 1 (b). It can be seen that the V1-V2 boundary density is the highest in the isothermal softening microstructure with strong selectivity, being 1.16μm -1 .

[0094] Example 2

[0095] A method for displaying isothermal softening microstructure of high nitrogen martensitic steel by reconstructing variants, comprising the following steps:

[0096] (1) Prepare isothermal softening sample and conduct thermal stability experiment: the same as in Example 1.

[0097] (2) Electrolytic polishing and EBSD data collection of isothermally softened sample: same as Example 1.

[0098] (3) Data calculation and smoothing of EBSD data in MATLAB: same as Example 1.

[0099] (4) Variant reconstruction of calculated and smoothed EBSD data by Nishiyama-Wassermann orientation relationship, see Table 1.

[0100] (5) Variant frequency calculation of the whole EBSD map, as shown in Figure 2 (a). It can be seen that the variants are selectively distributed after softening, with high frequency of V10, V12 variants, accounting for 0.156 and 0.155 respectively. The variant pair group V1 to V12 is classified, and the V1 to V6 variant pair group is integrated, so as to calculate the variant pair boundary density fraction of the whole EBSD map, as shown in Figure 2 (b). It can be seen that the strong selective V1-V6 boundary density in the isothermally softened tissue is the highest, being 0.09 μm -1 .

[0101] Example 3

[0102] A method for displaying the isothermally softened tissue of high-nitrogen martensitic steel by reconstructing variants, comprising the following steps:

[0103] (1) Preparation of isothermally softened sample for thermal stability experiment: same as Example 1.

[0104] (2) Electrolytic polishing and EBSD data collection of isothermally softened sample: same as Example 1.

[0105] (3) Data calculation and smoothing of EBSD data in MATLAB: same as Example 1.

[0106] (4) Variant reconstruction of calculated and smoothed EBSD data by Greninger-Troiano orientation relationship, see Table 1.

[0107] (5) Variant frequency calculation of the whole EBSD map, as shown in Figure 3 (a). It can be seen that the variants are selectively distributed after softening, with high frequency of V10, V19, V21, V22, V24 variants, accounting for 0.064, 0.081, 0.077, 0.076, 0.088 respectively. The variant pair group V1 to V24 is classified, and the V1 to V6 variant pair group is integrated, and the variant pair boundary density distribution isFigure 3 (b) As shown in Figure 2, it can be seen that the density of the highly selective V1-V6 boundary in the isothermal softening structure is the highest, at 1.17 μm. -1 .

[0108] Example 4

[0109] A method for displaying the isothermal softening structure of high nitrogen martensitic steel by reconstructing variants comprises the following steps:

[0110] (1) Preparation of isothermal softening samples and thermal stability test: the same as in Example 1.

[0111] (2) The sample after isothermal softening treatment is electropolished and electron backscatter diffraction data is collected: the same as in Example 1.

[0112] (3) Importing the electron backscatter diffraction data into MATLAB software for data calculation and smoothing: the same as in Example 1.

[0113] (4) The calculated and smoothed electron backscatter diffraction data were reconstructed using the Pitsch orientation relationship, see Table 1.

[0114] (5) Calculate the variant frequency of the entire electron backscatter diffraction pattern, such as Figure 4 (a) shows that the variants are selectively distributed after softening, with the high-frequency V9, V10, and V11 variants being the main ones, accounting for 0.125, 0.120, and 0.114, respectively. The variant pair groups V1 to V12 are classified and the variant pair groups V1 to V6 are integrated. The density distribution of the variant pair boundaries is shown in Figure 4 (b) As shown in Figure 2, it can be seen that the density of the highly selective V1-V2 boundary in the isothermal softening structure is the highest, which is 0.36 μm. -1 .

[0115] Comparative Example 1

[0116] In this comparative example, an isothermal softening sample was prepared and a thermal stability test was conducted: the same as in Example 1, the isothermal softening tissue of Comparative Example 1 was not reconstructed. Figure 5 As shown in (a).

[0117] Example 5

[0118] A method for displaying the isothermal softening structure of high nitrogen martensitic steel by reconstructing variants comprises the following steps:

[0119] (1) Preparation of isothermal softening sample for thermal stability experiment: The chemical composition of the high-nitrogen martensitic steel used in the experiment was detected as follows: C 0.31%, Si 0.17%, Mn 0.39%, Cr 15.11%, Mo 0.98%, Ni 0.11%, N 0.39%, and the balance being Fe and other inevitable impurity elements. The high-nitrogen martensitic steel after quenching and tempering was subjected to isothermal treatment at a temperature of 600°C for 4h.

[0120] (2) Electrolytic polishing of the sample after isothermal softening treatment and collection of electron backscatter diffraction data: The observation surface of the sample was electrolytically polished with a 8% volume fraction of perchloric acid alcohol solution to eliminate the surface stress layer generated by mechanical grinding of the tempered sample. The electrolytic polishing parameters were voltage 28V and current 0.9A. Subsequently, electron backscatter diffraction data were collected with a step size of 0.07μm and an analysis rate of 96%.

[0121] (3) Importing the electron backscatter diffraction data into MATLAB software for data calculation and smoothing: The electron backscatter diffraction data were calculated with a threshold value of 3° to form calculated and smoothed electron backscatter diffraction data, and the grain smoothing angle was 5°.

[0122] (4) Variant reconstruction by Kurdjumov-Sachs orientation relationship of the calculated and smoothed electron backscatter diffraction data, see Table 1.

[0123] (5) Calculation of the variant frequency of the entire electron backscatter diffraction pattern, as shown in Figure 6 (a). It can be seen that the variants are selectively distributed after softening, with high frequency of V9 and V10 variants, accounting for 0.065 and 0.055 respectively. The variant pairs V1 to V24 were classified, and the V1 to V6 variant pairs were integrated to calculate the variant pair boundary density fraction of the entire electron backscatter diffraction pattern, as shown in Figure 6 (b). It can be seen that the strong selective V1-V3(V5) boundary density in the isothermal softening structure is the highest, being 1.03μm -1 .

[0124] Example 6

[0125] A method for displaying the isothermal softening structure of high-nitrogen martensitic steel by reconstructing variants, comprising the following steps:

[0126] (1) Preparation of isothermal softening sample for thermal stability experiment: The same as in Example 5.

[0127] (2) Electrolytic polishing of the sample after isothermal softening treatment and collection of electron backscatter diffraction data: The same as in Example 5.

[0128] (3) The EBSD data was imported into MATLAB software for data calculation and smoothing: same as Example 5.

[0129] (4) The calculated and smoothed EBSD data was reconstructed by Nishiyama-Wassermann orientation relationship, see Table 1.

[0130] (5) The variant frequency of the whole EBSD pattern was calculated, as shown in Figure 7 (a). It can be seen that the variants are selectively distributed after softening, mainly with high frequency V7 variants, accounting for 0.20. The variant pair groups V1 to V12 were classified, and the V1 to V6 variant pair groups were integrated, so as to calculate the variant pair boundary density fraction of the whole EBSD pattern, as shown in Figure 7 (b). It can be seen that the strong selective V1-V2 boundary density in the isothermal softening tissue is the highest, reaching 0.13 μm -1 .

[0131] Example 7

[0132] A method for displaying the isothermal softening tissue of high-nitrogen martensitic steel by reconstructing variants, comprising the following steps:

[0133] (1) Prepare the isothermal softening sample and perform the thermal stability experiment: same as Example 5.

[0134] (2) Electrolytic polishing the sample after isothermal softening treatment and collecting EBSD data: same as Example 5.

[0135] (3) The EBSD data was imported into MATLAB software for data calculation and smoothing: same as Example 5.

[0136] (4) The calculated and smoothed EBSD data was reconstructed by Greninger-Troiano orientation relationship, see Table 1.

[0137] (5) The variant frequency of the whole EBSD pattern was calculated, as shown in Figure 8 (a). It can be seen that the variants are selectively distributed after softening, mainly with high frequency V12 variants, accounting for 0.054. The variant pair groups V1 to V24 were classified, and the V1 to V6 variant pair groups were integrated, and the variant pair boundary density distribution is shown in Figure 8 (b). It can be seen that the strong selective V1-V3(V5) boundary density in the isothermal softening tissue is the highest, reaching 0.96 μm -1 .

[0138] Example 8

[0139] A method for displaying isothermal softening microstructure of high nitrogen martensitic steel by reconstructing variants, comprising the following steps:

[0140] (1) Preparation of isothermal softening sample, thermal stability experiment: same as example 5.

[0141] (2) Electrolytic polishing of the sample after isothermal softening treatment and collection of electron backscatter diffraction data: same as example 5.

[0142] (3) Importing electron backscatter diffraction data into MATLAB software for data calculation and smoothing: same as example 5.

[0143] (4) Reconstructing variants of the calculated and smoothed electron backscatter diffraction data by Pitsch orientation relationship, see table 1.

[0144] (5) Calculating the variant frequency of the whole electron backscatter diffraction pattern, as shown in Figure 9 (a). It can be seen that the variants are selectively distributed after softening, with high frequency of V2, V5 and V12 variants, accounting for 0.225, 0.276 and 0.248 respectively. The variant pairs V1 to V12 are classified, and the variant pair boundary density distribution is shown in Figure 9 (b). It can be seen that the V1-V2 boundary density is the highest in the isothermal softening microstructure, which is 0.11 μm -1 .

[0145] Comparative example 2

[0146] In this comparative example, the isothermal softening sample was prepared, and the thermal stability experiment was carried out: same as example 5. The isothermal softening microstructure of comparative example 1 without reconstruction is shown in Figure 10 (a).

[0147] Example 9

[0148] A method for displaying isothermal softening microstructure of high nitrogen martensitic steel by reconstructing variants, comprising the following steps:

[0149] (1) Preparation of isothermal softening sample, thermal stability experiment: the chemical composition of the high nitrogen martensitic steel used in the experiment was detected as follows: C 1.15%, Si 0.28%, Mn 0.29%, Cr 3.75%, Mo 9.47%, Co 8.01%, N 0.18%, W 1.49%, V 1.14%, and the balance was Fe and other inevitable impurity elements. The quenched high nitrogen martensitic steel was subjected to isothermal treatment at a temperature of 540℃ for 4h.

[0150] (2) Electrolytic polishing and collecting electron backscatter diffraction data of the sample after isothermal softening treatment. The observation surface of the sample was electrolytically polished with 8% perchloric acid alcohol solution to eliminate the surface stress layer generated by the tempering sample after mechanical grinding. The electrolytic polishing parameters were voltage 28V and current 0.9A. Then, the electron backscatter diffraction data were collected with a step size of 0.07pm and an analysis rate of 95%.

[0151] (3) Importing the electron backscatter diffraction data into MATLAB software for data calculation and smoothing. The electron backscatter diffraction data were calculated with a threshold of 3° to form the calculated and smoothed electron backscatter diffraction data, and the grain smoothing angle was 5°.

[0152] (4) Reconstructing the variants of the calculated and smoothed electron backscatter diffraction data by Kurdjumov-Sachs orientation relationship, see Table 1.

[0153] (5) Calculating the variant frequency of the entire electron backscatter diffraction pattern, as shown in Figure 11 (a). It can be seen that the variants are selectively distributed after softening, with high frequency of V5 and V9 variants, accounting for 0.064 and 0.060, respectively. The variant pairs V1 to V24 were classified, and the V1 to V6 variant pairs were integrated to calculate the variant pair boundary density fraction of the entire electron backscatter diffraction pattern, as shown in Figure 11 (b). It can be seen that the V1-V3(V5) boundary density is the highest in the isothermal softening tissue with strong selectivity, being 1.23pm -1 .

[0154] Example 10

[0155] A method for displaying the isothermal softening structure of high-nitrogen martensitic steel by reconstructing variants, comprising the following steps:

[0156] (1) Preparing an isothermal softening sample for thermal stability experiment: the same as Example 9.

[0157] (2) Electrolytic polishing and collecting electron backscatter diffraction data of the sample after isothermal softening treatment: the same as Example 9.

[0158] (3) Importing the electron backscatter diffraction data into MATLAB software for data calculation and smoothing: the same as Example 9.

[0159] (4) Reconstructing the variants of the calculated and smoothed electron backscatter diffraction data by Nishiyama-Wassermann orientation relationship, see Table 1.

[0160] (5) Calculating the variant frequency of the entire electron backscatter diffraction pattern, as shown in Figure 12(a) shows. It can be seen that the variants are selectively distributed after softening, with high frequency of V10, V11 variants, accounting for 0.238, 0.208 respectively. The variant pair groups V1 to V12 are classified, and the V1 to V6 variant pair groups are integrated, so as to calculate the variant pair boundary density fraction of the whole electron backscattering diffraction map, as shown in Figure 12 (b) shows. It can be seen that the strong selective V1-V2 boundary density in the isothermal softening tissue is the highest, which is 0.104 μm -1 .

[0161] Example 11

[0162] A method for displaying the isothermal softening tissue of high-nitrogen martensitic steel by reconstructing variants, comprising the following steps:

[0163] (1) Prepare the isothermal softening sample and perform the thermal stability experiment: the same as example 9.

[0164] (2) Electrolytic polishing the sample after isothermal softening treatment and collecting electron backscattering diffraction data: the same as example 9.

[0165] (3) Import the electron backscattering diffraction data into MATLAB software for data calculation and smoothing: the same as example 9.

[0166] (4) The calculated and smoothed electron backscattering diffraction data is subjected to variant reconstruction by Greninger-Troiano orientation relationship, see table 1.

[0167] (5) Calculate the variant frequency of the whole electron backscattering diffraction map, as shown in Figure 13 (a) shows. It can be seen that the variants are selectively distributed after softening, with high frequency of V11, V17, V22 variants, accounting for 0.053, 0.053, 0.052 respectively. The variant pair groups V1 to V24 are classified, and the V1 to V6 variant pair groups are integrated, and the variant pair boundary density distribution is as shown in Figure 13 (b) shows. It can be seen that the strong selective V1-V3(V5) boundary density in the isothermal softening tissue is the highest, which is 1.25 μm -1 .

[0168] Example 12

[0169] A method for displaying the isothermal softening tissue of high-nitrogen martensitic steel by reconstructing variants, comprising the following steps:

[0170] (1) Prepare the isothermal softening sample and perform the thermal stability experiment: the same as example 9.

[0171] (2) Electrolytic polishing the sample after isothermal softening treatment and collecting electron backscattering diffraction data: the same as example 9.

[0172] (3) Import the EBSD data into MATLAB software for data calculation and smoothing: same as Example 5.

[0173] (4) Reconstruct the variants of the calculated and smoothed EBSD data by Pitsch orientation relationship, see Table 1.

[0174] (5) Calculate the variant frequency of the whole EBSD map, as shown in Figure 14 (a). It can be seen that the variants are selectively distributed after softening, mainly with V3 variant with a high frequency of 0.355. The variant pairs V1 to V12 are classified, and the V1 to V6 variant pairs are integrated, and the variant pair boundary density distribution is shown in Figure 14 (b). It can be seen that the V1-V2 boundary density is the highest in the isothermal softening tissue with strong selectivity, which is 0.19 μm -1 .

[0175] Comparative Example 3

[0176] In this comparative example, isothermal softening samples were prepared for thermal stability experiments: same as Example 9, the isothermal softening tissue of Comparative Example 1 without reconstruction is shown in Figure 14 (a).

[0177] Examples 1-12 were reconstructed according to different orientation relationships in Table 1.

[0178] Table 1. Information on the orientation relationship between variants

[0179]

[0180] Result Analysis

[0181] Comparative Examples 1, 2 and 3 cannot be analyzed for variants, and the martensite tissue after isothermal softening cannot be quantitatively counted. The variant tissue reconstructed according to different orientation relationships in Examples 1-4 is shown in Figure 5 b to Figure 5 e, which respectively correspond to Kurdjumov-Sachs, Nishiyama-Wassermann, Greninger-Troiano and Pitsch relationship. It can be seen that the variant tissue reconstructed according to different orientation relationships is color divided, representing the division of different martensite orientation relationships, among which Figure 5 b, Figure 5 c and Figure 5 d correspond to Kurdjumov-Sachs, Nishiyama-Wassermann, Greninger-Troiano orientation relationship, which shows better effect of isothermal softening tissue of high-nitrogen martensite steel, and the variant tissue is completely reconstructed,Figure 5 e corresponds to Pitsch orientation relationship, which shows poor effect on isothermal softening microstructure of high nitrogen martensite steel, and the variant organization is not completely displayed. Through quantitative statistics, the variant frequency distribution graph and the variant pair boundary density graph can be drawn.

[0182] The variant organization reconstructed according to different orientation relationships in Examples 5-8 is shown in Figure 10 b- Figure 10 e, which respectively correspond to Kurdjumov-Sachs, Nishiyama-Wassermann, Greninger-Troiano and Pitsch relationship. It can be seen that the variant organization reconstructed according to different orientation relationships is color divided, representing the division of different martensite orientation relationships, in which Figure 10 b, Figure 10 c and Figure 10 d correspond to Kurdjumov-Sachs, Nishiyama-Wassermann, Greninger-Troiano orientation relationship, which shows good effect on isothermal softening microstructure of high nitrogen martensite steel, and the variant organization is completely reconstructed, Figure 10 e corresponds to Pitsch orientation relationship, which shows poor effect on isothermal softening microstructure of high nitrogen martensite steel, and the variant organization is not completely displayed. Through quantitative statistics, the variant frequency distribution graph and the variant pair boundary density graph can be drawn.

[0183] The variant organization reconstructed according to different orientation relationships in Examples 9-12 is shown in Figure 15 b- Figure 15 e, which respectively correspond to Kurdjumov-Sachs, Nishiyama-Wassermann, Greninger-Troiano and Pitsch relationship. It can be seen that the variant organization reconstructed according to different orientation relationships is color divided, representing the division of different martensite orientation relationships, in which Figure 15 b, Figure 15 c and Figure 15 d correspond to Kurdjumov-Sachs, Nishiyama-Wassermann, Greninger-Troiano orientation relationship, which shows good effect on isothermal softening microstructure of high nitrogen martensite steel, and the variant organization is completely reconstructed, ​ e corresponds to Pitsch orientation relationship, which shows poor effect on isothermal softening microstructure of high nitrogen martensite steel, and the variant organization is not completely displayed. Through quantitative statistics, the variant frequency distribution graph and the variant pair boundary density graph can be drawn.

[0184] In summary, all the examples, according to Kurdjumov-Sachs, Nishiyama-Wassermann, Greninger-Troiano, the effect of the reconstruction of the variants is better, and the Pitsch relationship shows that the variants are not complete, and the reconstruction effect is poor.

[0185] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "a specific embodiment", and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily mean the same embodiment or example. Furthermore, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0186] The above is only the preferred embodiment of the present application, and is not used to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for displaying the isothermal softening structure of high nitrogen martensitic steel by reconstructing variants, characterized in that: include: Data acquisition, obtaining electron backscatter diffraction data of high nitrogen martensitic steel after isothermal softening; Data processing, calculating and smoothing the electron backscatter diffraction data to obtain calculated and smoothed electron backscatter diffraction data; variant reconstruction, performing variant reconstruction on the calculated and smoothed electron backscatter diffraction data according to different orientation relationships; Quantify the variants and analyze them. Based on the variant reconstruction effects under different orientation relationships, determine the reasonable orientation relationship for displaying the isothermal softening structure of high nitrogen martensitic steel. Then, quantitatively display the microstructural evolution of martensitic variants during isothermal softening through variant reconstruction, and reveal the variant evolution mechanism of high nitrogen martensitic steel after isothermal softening. The variant reconstruction includes: performing variant reconstruction on the calculated and smoothed electron backscatter diffraction data according to the Kurdjumov-Sachs orientation relationship, the Nishiyama-Wassermann orientation relationship, the Greninger-Troiano orientation relationship and the Pitsch orientation relationship; The quantitative variants and analysis include: Based on the reconstructed parent phase austenite grain structure, image visualization analysis and statistics of martensite variants are performed, including calculation of the variant frequency and variant boundary density of the electron backscattered diffraction pattern, thereby revealing the isothermal softening mechanism of high nitrogen martensitic steel.

2. The method for displaying the isothermal softening structure of high nitrogen martensitic steel by reconstructing variants according to claim 1, characterized in that: The data acquisition includes: Electron backscatter diffraction data of the high nitrogen martensitic steel after isothermal softening were obtained using a scanning electron microscope equipped with electron backscatter diffraction, with an acquisition step size of 0.05 μm to 0.1 μm and a resolution of 80% to 100%.

3. The method for displaying the isothermal softening structure of high nitrogen martensitic steel by reconstructing variants according to claim 2, characterized in that: The acquisition step size is 0.05 μm to 0.08 μm, and the resolution is 90% to 100%.

4. The method for displaying the isothermal softening structure of high nitrogen martensitic steel by reconstructing variants according to claim 2 or 3, characterized in that: Before the data acquisition, the high nitrogen martensitic steel after isothermal softening was electropolished; the electropolishing: the electrolyte was a perchloric acid alcohol solution with a volume fraction of 8% to 15%, the voltage was 20 V to 30 V, the current was 0.5 A to 1.0 A, and the electrolysis time was 10 s to 30 s.

5. The method for displaying the isothermal softening structure of high nitrogen martensitic steel by reconstructing variants according to claim 4, characterized in that: The electrolyte is a perchloric acid alcohol solution with a volume fraction of 8%~10%, the voltage is 25 V~30 V, the current is 0.8 A~1.0 A, and the electrolysis time is 20 s~25 s.

6. The method for displaying the isothermal softening structure of high nitrogen martensitic steel by reconstructing variants according to claim 1, characterized in that: The data processing includes: The electron backscatter diffraction data is calculated with a threshold of 0° to 10°, and the grain smoothing range is 0° to 20° to form calculated and smoothed electron backscatter diffraction data.

7. The method for displaying the isothermal softening structure of high nitrogen martensitic steel by reconstructing variants according to claim 6, characterized in that: The electron backscatter diffraction data is calculated with a threshold of 2° to 5°, and the grain smoothing range is 5° to 10° to form calculated and smoothed electron backscatter diffraction data.

8. Application of a method for displaying the isothermal softening structure of high nitrogen martensitic steel by reconstructing variants, characterized in that: The method of displaying the isothermal softening structure of high nitrogen martensitic steel by reconstructing variants as described in any one of claims 1 to 7 is used to guide the composition design of metal materials and improve the thermal stability of metal materials.

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