Quantitative analysis method of trace elements in interface of superalloy by STEM-EDS

Abstract

The application discloses a kind of high-temperature alloy interface micro trace element STEM-EDS quantitative analysis method, belong to material microscopic analysis technical field.The method includes: the preparation thin area thickness less than 100nm transmission electron microscope sample;STEM imaging is carried out under 200-300kV using field emission or spherical aberration correction transmission electron microscope;First, under 2000x-3000x, the quantity proportion of different characteristic interface and its number ratio is counted, then under 200kx-300kx, a representative interface in each interface is selected to carry out 20-30 minutes EDS surface scanning, during enabling drift correction;Interface is divided into weak segregation interface and strong segregation interface according to EDS result;Data is divided into sample square, the average value of the element mass percentage of two types of interfaces and its 95% confidence level and number ratio are obtained by statistics;The final content of target element is calculated.The application solves the problem that existing technology cannot consider nanoscale spatial resolution and quantitative statistical representation, significantly improves the accuracy and repeatability of analysis result.

Description

Technical Field

[0001] This invention belongs to the field of materials micro-analysis technology, specifically relating to a quantitative analysis method for trace elements at the interface of high-temperature alloys using STEM-EDS. Background Technology

[0002] High-temperature alloys are widely used in critical hot-end components of aero-engines, such as turbine blades and turbine disks, due to their excellent high-temperature properties. Failure of these components could lead to serious accidents, making the safety and reliability of the materials crucial.

[0003] In addition to the main elements, high-temperature alloys typically contain various trace and minor elements (such as boron, carbon, phosphorus, and rare earth elements), with a total content usually less than 1 wt%. Although these elements are present in extremely low amounts in bulk materials, they tend to segregate at interfaces such as grain boundaries and phase boundaries. Beneficial elements (such as boron and zr) can strengthen grain boundaries, improving the creep life and fatigue performance of the alloy; while harmful elements (such as sulfur and phosphorus) weaken grain boundaries, leading to premature failure of the alloy during service. Therefore, accurately determining the true content, distribution, and occurrence form of these trace elements at interfaces is crucial for understanding their mechanisms of action, optimizing alloy composition design, and extending the service life of components.

[0004] Currently, the main techniques used for elemental analysis include classical chemical analysis, atomic absorption spectrometry, inductively coupled plasma optical emission spectrometry (ICP-OES), inductively coupled plasma mass spectrometry (ICP-MS), and electron probe microanalysis (EPMA). However, these techniques have significant limitations: classical chemical analysis requires complete dissolution of the sample and can only provide the bulk average content of elements, failing to reveal their segregation behavior in microscopic regions such as grain boundaries and phase boundaries (especially nanoscale interfaces); while EPMA is limited by micrometer-level spatial resolution (typically >1 μm) and relatively high element detection limits (approximately 0.01–0.1 wt%), making it difficult to effectively identify and accurately quantify trace element segregation at nanoscale interfaces.

[0005] Scanning transmission electron microscopy (STEM) combined with energy dispersive X-ray spectroscopy (EDS) provides a powerful tool for studying interfacial segregation, offering nanoscale and even atomic-level resolution. However, in practice, using STEM-EDS for quantitative analysis of interfaces (especially after trace elements in bulk are enriched at the interface) still faces a series of challenges: First, the lack of systematic and standardized sample preparation standards makes it difficult to ensure the representativeness of the analytical area and avoid artifacts introduced by sample preparation; second, the lack of standardized instrument parameter settings and data acquisition procedures makes it difficult to directly compare analytical results from different laboratories; finally, and most importantly, traditional point analysis or small-area analysis lacks statistical representativeness and cannot reflect the differences in segregation between different types of interfaces, resulting in highly random and poorly reproducible analytical results.

[0006] Therefore, there is an urgent need in this field to establish a quantitative analysis method for trace elements at the interface of high-temperature alloys that can be accurate, reliable and statistically significant while maintaining the original microstructure of the material, so as to make up for the shortcomings of the existing technology. Summary of the Invention

[0007] The purpose of this invention is to provide a quantitative analysis method for trace elements at the interface of high-temperature alloys using STEM-EDS.

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] 1. A quantitative analysis method for trace elements at the interface of high-temperature alloys using STEM-EDS, comprising the following steps:

[0010] a) Prepare transmission electron microscopy (TEM) samples and control the thickness of the thin region of the sample to be less than 100 nm;

[0011] b) Use a field emission transmission electron microscope or a transmission electron microscope equipped with a spherical aberration corrector to perform STEM imaging at an accelerating voltage of 200kV-300kV, adjust the beam spot size to 5-7, make the optical path aligned, and optimize the collection angle, energy resolution and detection efficiency of the EDS probe so that the EDS meets the detection accuracy requirements of micro-trace element analysis.

[0012] c) At low magnification 2000 -3000 Below, high-angle annular dark-field images were used to statistically analyze interfaces with different characteristic morphologies, and the proportion of each type of interface was recorded. Interfaces with a normal direction Δθ ≥ 10° along their length were labeled as curved interfaces; otherwise, they were labeled as straight interfaces. Subsequently, at high magnification (200k), [further details were provided]. -300k In each type of interface, a representative interface was selected for continuous EDS surface scanning data acquisition for 20-30 minutes. During the acquisition process, the electron beam drift correction function was enabled, and the probe current was controlled to be ≤0.0040nA and the count rate to be ≥1kcps.

[0013] d) Based on the EDS data obtained in step c), the interface with an element content between 0 and 0.1 wt% and excluding 0.1 wt% is defined as a weak segregation interface, and the interface with an element mass percentage content between 0.1% and 1% is defined as a strong segregation interface.

[0014] e) Divide the EDS data results of each type of interface collected in step c) into n×n quadrats, and select n quadrats containing interfaces to statistically obtain the elemental mass percentage content a1, a2…a of the weakly segregating interfaces. n The elemental mass percentages b1, b2…b at the strong segregation interface n And count the percentage of weakly clustered interfaces x and the percentage of strongly clustered interfaces y;

[0015] f) Average the obtained elemental content data to obtain the average mass percentage content of elements at strong and weak agglomeration interfaces:

[0016] ;

[0017] ;

[0018] in, The mass percentage of the element at the i-th weak segregation interface; is the mass percentage of the element at the i-th strong segregation interface; n is the number of quadrats. The average mass percentage of weakly segregating interface elements; The average mass percentage of strongly segregating interface elements;

[0019] Statistical analysis was performed on the obtained elemental content data, and the sample standard deviation was calculated to characterize the degree of dispersion.

[0020] ;

[0021] ;

[0022] in, This represents the sample standard deviation of the mass percentage of weakly segregating interface elements. The sample standard deviation of the mass percentage of strongly segregating interface elements;

[0023] The Type A standard uncertainty of element content at the interface is estimated using the mean standard error:

[0024] ;

[0025] ;

[0026] in, The standard error of the average mass percentage content of weakly segregating interface elements; The standard error of the average mass percentage content of elements at strong segregation interfaces;

[0027] Based on the selected 95% confidence level, the degrees of freedom are found to be: of Distribution critical value Calculate the expanded uncertainty of the average element content at strong and weak segregation interfaces:

[0028] ;

[0029] ;

[0030] in, and This represents the expanded uncertainty of the mean at a 95% confidence level, and this expanded uncertainty is the half-width of the confidence interval;

[0031] The average mass fraction of this element at the weakly segregating interface and its 95% confidence level are:

[0032] ;

[0033] The average mass fraction of this element at a strongly segregating interface and its 95% confidence level are:

[0034] ;

[0035] g) Using the formula Calculate the final mass percentage content of the target element. ;

[0036] Where x represents the proportion of weakly clustered interfaces; and y represents the proportion of strongly clustered interfaces.

[0037] Furthermore, in step a), a transmission electron microscope sample is prepared by electropolishing or focused ion beam method, and the thickness of the thin area of ​​the sample is controlled within the range of 50 nm to 100 nm.

[0038] Further, in step c), based on the interface feature shape, identify and mark it as a straight-line interface or a curved interface.

[0039] Further, in step b), the accelerating voltage of the transmission electron microscope is set to 200kV.

[0040] Furthermore, in step c), the high magnification is 250kJ / L. .

[0041] Furthermore, in step c), the EDS surface scan data acquisition time is 25 to 30 minutes.

[0042] Furthermore, after step g), step h is also included: comparing the calculated target element mass percentage range wt% with the known chemical composition mass percentage wt0% of the element in the high-temperature alloy; when wt0% is within the uncertainty range of wt%, the reliability of the detection result wt% is confirmed.

[0043] Compared with existing technologies, the STEM-EDS-based quantitative analysis method for trace elements at high-temperature alloy interfaces provided by this invention has the following significant technical advantages:

[0044] 1. This invention achieves a balance between quantitative accuracy and statistical representativeness at the nanoscale: Through a systematic analysis process of "low-magnification statistical morphology - high-magnification classification acquisition - confidence interval calculation based on normal distribution," it extends traditional component analysis, limited to single points or small regions, to the statistical level of multiple interface types. Specifically, firstly, large-scale statistical analysis of interfaces with different morphological features is performed in low-magnification STEM images to determine the proportion of weakly and strongly clustered interfaces. Then, long-term, highly stable EDS signal acquisition is performed on two representative interfaces to improve the signal-to-noise ratio and accuracy of element quantification. Finally, based on the normal distribution assumption of multiple measurements, the confidence interval of element content and the reliability of the quantification results are calculated at a specified confidence level. This innovative workflow design effectively overcomes the randomness and limitations of single-region analysis. While maintaining the sub-nanometer high spatial resolution of STEM-EDS, it obtains quantitative results that reflect both local chemical states and high statistical representativeness, providing a new paradigm for the reliable characterization of nanoscale interface components.

[0045] 2. This invention establishes standardized operating procedures, significantly improving the repeatability and reliability of the method: Key operating steps and instrument parameters are precisely defined. Specifically, the sample thin-area thickness is strictly controlled within 50nm-100nm, effectively reducing multiple scattering of the electron beam and providing a fundamental guarantee for quantitative accuracy. The accelerating voltage, beam spot size, probe current, count rate, and acquisition time of 20-30 minutes are clearly specified, with drift correction enabled, ensuring high stability and a high signal-to-noise ratio in the data acquisition process, creating conditions for accurate detection of trace elements. These specific parameters and steps together constitute a clear and operable standardized scheme, greatly reducing result fluctuations caused by operational differences, and ensuring good comparability and repeatability of analytical results from different times, different operators, and even different laboratories.

[0046] 3. This invention introduces an objective result verification mechanism to ensure the accuracy of the final data: After calculating the elemental content, an additional step is added to compare and verify with the nominal chemical composition of the alloy (or the known overall composition). By determining whether the measured value falls within its 95% confidence interval, the reliability of the analytical results is assessed. This built-in quality control step provides an objective, quantitative, and criterionable standard for data validity, significantly improving the credibility of the method's output results, thereby providing more reliable basic data support for key applications such as high-temperature alloy composition design, interface control, and service life prediction. Attached Figure Description

[0047] Figure 1 The diagram shows the high-magnification grain boundary morphology and EDS surface distribution. In (a), the box represents the target sample plot used to calculate the average elemental content, and (b) represents the EDS surface distribution result of the P element. Detailed Implementation

[0048] The preparation method of the present invention will be described in detail below with reference to the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0049] Example 1

[0050] (1) Sample preparation

[0051] A certain type of nickel-based superalloy material was used, and transmission electron microscopy (TEM) samples were prepared by electrolytic polishing according to the requirements of GB / T18907-2013 standard. A 10% (v / v) perchloric acid-acetic acid solution was used as the electrolyte, and double-jet thinning was performed at -20℃ and 30V. Calibration with a thickness standard confirmed that the thickness of the thin region of the sample was controlled at 70 nm, which meets the 50 nm-100 nm range requirement of this invention.

[0052] (2) Instrument preparation

[0053] The tests were conducted using a FEIThemisZ field emission transmission electron microscope.

[0054] The accelerating voltage is set to 200kV;

[0055] The condenser beam spot size was adjusted to 7;

[0056] Perform precise optical path alignment to ensure electron beam collimation;

[0057] Optimize the EDS probe collection angle to ensure that the detector solid angle is greater than 0.7 srad.

[0058] (3) Content detection

[0059] First in 2000 Under the conditions described, the thin area of ​​the sample was observed using a high-angle annular dark-field imaging system. Three interfaces with clear contrast were obtained, including one curved interface and two straight interfaces, with a ratio of 1:2.

[0060] Subsequently, a representative interface was selected from each type of interface and analyzed in 250k... The following 25 minutes of EDS surface scan data acquisition will be performed:

[0061] Enable real-time drift correction function and use image feature tracking algorithm to automatically correct beam spot position;

[0062] Control the probe current to 0.0040 nA;

[0063] The count rate remained stable at 2389 cps;

[0064] The acquisition area is 80nm×80nm in size.

[0065] Quantitative analysis of the collected EDS data (using the standard-free method) showed that the P element content of the linear interface was 0.12%, which was classified as a strong segregation interface.

[0066] One curved interface has a P element content of 0.08%, which is classified as a weak segregation interface.

[0067] (4) Data processing and error analysis

[0068] The EDS data from the two interfaces were divided into 10×10 quadrat grids, meaning each interface data point contained 100 pixels. Ten quadrats containing the interfaces were extracted as statistical samples (n=10), and the results were obtained using EDS analysis software.

[0069] Mass percentage (wt%) of phosphorus at weakly segregating interfaces: 0.07, 0.09, 0.05, 0.06, 0.09, 0.10, 0.07, 0.09, 0.09, 0.08;

[0071] Calculate the average elemental mass percentage (wt%): ;

[0072] Calculate the sample standard deviation (indicating the degree of data dispersion) (wt%): ;

[0073] The standard error (wt%) of the average mass percentage of elements at weakly segregating interfaces is calculated as follows: ;

[0074] Calculate the expanded uncertainty of the mean at a 95% confidence level (i.e., the half-width of the confidence interval): ;

[0075] The final average mass percentage of weakly segregating interface elements and its 95% confidence level: ;

[0076] P element content (wt%) at strong segregation interfaces: 0.13, 0.14, 0.17, 0.15, 0.18, 0.11, 0.10, 0.19, 0.09, 0.10;

[0077] Calculate the average elemental mass percentage (wt%): ;

[0078] Calculate the sample standard deviation (which represents the degree of dispersion of the data): ;

[0079] The standard error (wt%) of the average mass percentage of elements at strong segregation interfaces is calculated as follows: ;

[0080] Calculate the expanded uncertainty of the mean at the 95% level (i.e., the half-width of the confidence interval): ;

[0081] The final average mass percentage of elements at the strong segregation interface and its 95% confidence level: ;

[0082] The proportion of weakly segregating interfaces is x = 1 / 3 ≈ 33.3%;

[0083] The proportion of strongly segregating interfaces is approximately 66.7% (y = 2 / 3).

[0084] The final mass percentage (wt%) of element P is calculated using the formula of this invention: ;

[0085] The result was compared and verified with the overall P element content of 0.12 wt% in the alloy measured by inductively coupled plasma mass spectrometry (ICP-MS), and the result confirmed that it was consistent with the chemical composition of 0.12 wt%. Based on the judgment criteria of this invention, the reliability of the measured wt% result is confirmed. High-magnification grain boundary morphology and EDS surface distribution diagram are shown below. Figure 1 In (a), the box represents the target quadrat actually used to calculate the average element content, and (b) represents the EDS surface distribution result of element P.

[0086] Example 2

[0087] (1) Sample preparation

[0088] A certain type of nickel-based superalloy material was used, and transmission electron microscopy (TEM) samples were prepared by electrolytic polishing according to the requirements of GB / T18907-2013 standard. A 10% (v / v) perchloric acid-acetic acid solution was used as the electrolyte, and double-jet thinning was performed at -20℃ and 30V. Calibration with a thickness standard confirmed that the thickness of the thin region of the sample was controlled at 68 nm, which meets the 50 nm-100 nm range requirement of this invention.

[0089] (2) Instrument preparation

[0090] The tests were conducted using a FEIThemisZ field emission transmission electron microscope: the accelerating voltage was set to 200 kV; the condenser beam spot size was adjusted to 7; fine optical path alignment was performed to ensure electron beam collimation; and the EDS probe collection angle was optimized to ensure that the detector solid angle was greater than 0.7 srad.

[0091] (3) Content detection

[0092] First in 2000 Under these conditions, a high-angle annular dark-field imaging system was used to observe the thin area of ​​the sample. Six interfaces with clear contrast were identified, including two curved interfaces and four straight interfaces, with a ratio of 1:2. Subsequently, a representative interface from each type was selected and observed at 250kΩ. A 25-minute EDS surface scan was performed to acquire data: real-time drift correction was enabled, and an image feature tracking algorithm was used to automatically correct the beam spot position; the probe current was controlled at 0.0040 nA; the count rate was stabilized at 2450 cps; and the acquisition area size was 80 nm × 80 nm. Quantitative analysis of the acquired EDS data (using the standard-free method) was performed. The results showed that: one linear interface had an Hf content of 0.14%, classified as a strong segregation interface; and one curved interface had an Hf content of 0.07%, classified as a weak segregation interface.

[0093] (4) Data processing and error analysis

[0094] The EDS data from the two interfaces were divided into 10×10 quadrat grids, meaning each interface data point contained 100 pixels. Ten quadrats containing the interfaces were extracted as statistical samples (n=10), and the results were obtained using EDS analysis software.

[0095] Mass percentage (wt%) of phosphorus at weakly segregating interfaces: 0.05, 0.08, 0.07, 0.06, 0.08, 0.07, 0.09, 0.06, 0.08, 0.07;

[0097] Calculate the average elemental mass percentage (wt%): ;

[0098] Calculate the sample standard deviation (indicating the degree of data dispersion) (wt%): ;

[0099] The standard error (wt%) of the average mass percentage of elements at weakly segregating interfaces is calculated as follows: ;

[0100] Calculate the expanded uncertainty of the mean at a 95% confidence level (i.e., the half-width of the confidence interval): ;

[0101] The final average mass percentage of weakly segregating interface elements and its 95% confidence level: ;

[0102] P element content (wt%) at strong segregation interfaces: 0.12, 0.13, 0.15, 0.14, 0.16, 0.17, 0.12, 0.18, 0.14, 0.15;

[0104] Calculate the average elemental mass percentage (wt%): ;

[0105] Calculate the sample standard deviation (which represents the degree of dispersion of the data): ;

[0106] The standard error (wt%) of the average mass percentage of elements at strong segregation interfaces is calculated as follows: ;

[0107] Calculate the expanded uncertainty of the mean at the 95% level (i.e., the half-width of the confidence interval): ;

[0108] The final average mass percentage of elements at the strong segregation interface and its 95% confidence level: ;

[0109] The proportion of interfaces with weak agglomeration is x = 4 / 6 ≈ 66.7%; the proportion of interfaces with strong agglomeration is y = 2 / 6 ≈ 33.3%.

[0110] The final mass percentage (wt%) of element P is calculated using the formula of this invention: ;

[0111] The result was compared with the overall Hf content of 0.10% wt% measured by inductively coupled plasma mass spectrometry (ICP-MS), and the result confirmed that it was consistent with the chemical composition of 0.10% wt%. Based on the judgment criteria of this invention, the reliability of the measured wt% result was confirmed.

[0112] Comparative Example 1

[0113] The same sample area as in Example 1 was used, but only one curved interface was randomly selected for 25 minutes of EDS surface scanning data acquisition.

[0114] The EDS data of this single interface was also divided into 10×10 quadrats, and 10 quadrats containing the interface were extracted as statistical samples to obtain the P element content (wt%): 0.18, 0.17, 0.18, 0.19, 0.17, 0.18, 0.18, 0.17, 0.18, 0.19;

[0115] Calculate the average elemental mass percentage (wt%): ;

[0116] Calculate the sample standard deviation (indicating the degree of data dispersion) (wt%): ;

[0117] The standard error (wt%) of the average mass percentage of elements at strong segregation interfaces is calculated as follows: ;

[0118] Calculate the expanded uncertainty of the mean at a 95% confidence level (i.e., the half-width of the confidence interval): ;

[0119] The final average mass percentage of weakly segregating interface elements and its 95% confidence level: ;

[0120] This result deviates significantly from the average value of the P content (wt%) of strongly segregating interfaces calculated by statistically analyzing multiple interfaces in Example 1 (approximately 23.5%), and the uncertainty intervals overlap to a limited extent. This demonstrates that a lack of statistical representativeness of multiple interface types leads to inaccurate conclusions, highlighting the necessity of interface morphology statistics and classification collection in step c) of this invention.

[0121] Comparative Example 2

[0122] EDS surface scanning data was acquired in the same area as in Example 1 for only 5 minutes, with other parameters remaining unchanged. Due to the significantly shortened acquisition time, the count was severely insufficient and the signal-to-noise ratio was poor. Ten quadrats containing the interface were extracted from the same group of weakly segregating interfaces as statistical samples, and the P element content (wt%) was obtained as follows: 0.04, 0.11, 0.02, 0.08, 0.13, 0.06, 0.10, 0.01, 0.12, 0.05.

[0123] Although the average percentage content of elements (wt%) was calculated to be 0.072, the sample standard deviation (wt%) was as high as 0.038, and the expanded uncertainty of the mean (wt%) at the 95% confidence level reached 0.027. The final result was 0.072 ± 0.027 (wt%), with an uncertainty range as high as 37.5% of the average. This is in stark contrast to the stable result obtained after a long acquisition time of 25 minutes in Example 1 (0.079 ± 0.011, uncertainty range of 13.9%), proving that the 20-30 minute acquisition time specified in step c) of this invention is crucial for ensuring the statistical significance and low uncertainty of trace element analysis.

[0124] Comparative Example 3

[0125] Analysis was performed using a sample with a thickness of 180 nm, with other parameters identical to those in Example 1. Due to severe electron beam multiple scattering, the spatial resolution was significantly reduced. EDS analysis was performed on the same strongly segregating interface, and 10 quadrats containing the interface were extracted as statistical samples. The P element content (wt%) was obtained as follows: 0.19, 0.22, 0.25, 0.20, 0.24, 0.18, 0.17, 0.26, 0.16, 0.21. The calculated average element mass percentage (wt%) was 0.210, significantly higher than the result (0.136) for the corresponding interface of the 70 nm thin-area sample in Example 1. This result shows a systematically significant overestimation (biased by approximately 54%), and the sample standard deviation (wt%) is 0.033. The expanded uncertainty (wt%) of the mean at a 95% confidence level was calculated to be 0.023, with the uncertainty range reaching 109.5% of the mean. It is proven that a sample thickness of <100nm is a necessary condition to ensure quantitative accuracy and avoid systematic errors introduced by matrix effects.

[0126] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. All equivalent changes or modifications made in accordance with the spirit and essence of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for quantitative analysis of interfacial micro- trace elements of superalloys by STEM-EDS, characterized in that, The method comprises the following steps: a) preparing a transmission electron microscope sample and controlling the thin area thickness of the sample to be less than 100 nm; b) using a field emission transmission electron microscope or a transmission electron microscope equipped with a spherical aberration corrector to perform STEM imaging at an acceleration voltage of 200 kV-300 kV, adjusting the beam spot size to 5-7, aligning the optical path, and optimizing the collection angle, energy resolution and detection efficiency of the EDS probe to meet the detection accuracy requirements of micro trace element analysis; c) at low magnification 2000 - 3000 Next, the interfaces with different characteristic morphologies were counted by high-angle annular dark-field imaging, and the proportion of each type of interface was recorded. When the normal direction of the interface along the length direction Δθ ≥ 10°, it was marked as a curved interface; otherwise, it was marked as a straight interface. Subsequently, at high magnification 200k - 300k Next, a representative interface was selected from each type of interface for EDS area scan data collection for 20-30 minutes. During the collection process, the electron beam drift correction function was enabled, and the probe current was controlled to be ≤ 0.0040 nA, and the count rate was ≥ 1 kcps. d) defining the interface with an element content of 0-0.1 wt% and not containing 0.1 wt% as a weak segregation interface, and defining the interface with an element mass content of 0.1%-1% as a strong segregation interface according to the EDS data obtained in step c); e) The EDS data results of each type of interface collected in step c) are respectively divided into n x n quadrats, and the element mass percentage a1, a2…a of weakly segregated interfaces and the element mass percentage b1, b2…b of strongly segregated interfaces are respectively obtained by selecting n quadrats containing interfaces n and n The number of weakly segregated interfaces accounts for x, and the number of strongly segregated interfaces accounts for y. f) performing average processing on the obtained element content data to obtain the average mass percentage of the elements in the strong segregation interface and the weak segregation interface, respectively: ; ; wherein, is the average mass percent content of the element at the weakly segregated interfaces; is the average mass percent content of the element at the weakly segregated interfaces; is the average mass percent content of the element at the weakly segregated interfaces; is the average mass percent content of the element at the weakly segregated interfaces; Statistical analysis is performed on the obtained element content data, and the sample standard deviation is calculated to represent the dispersion degree: ； ; wherein Ss is the sample standard deviation of the mass percent of weakly segregated interfacial element, Ss is the sample standard deviation of the mass percent of strongly segregated interfacial element; The A-class standard uncertainty of the element content at the interface is estimated by the mean standard error: ; ; wherein is the standard deviation of the average value of the mass percentage of weakly segregated interfacial elements; is the standard deviation of the average value of the mass percentage of strongly segregated interfacial elements; According to the selected 95% confidence level, the degrees of freedom are found to be of distribution critical values , the expanded uncertainty of the average of the strongly and weakly segregated interface element content is calculated: ; ; wherein, and represents the expanded uncertainty of the mean at the 95% confidence level, which is half the width of the confidence interval; The average value of the element mass fraction at the weak segregation interface and its 95% confidence level are: ; The average value of the element mass fraction at the strong segregation interface and its 95% confidence level are: ; g) using the formula to calculate the final mass percent content of the target element ; Wherein, x is the proportion of the number of weak segregation interfaces; y is the proportion of the number of strong segregation interfaces.

2. The method for quantitative analysis of trace elements in the interface of superalloy by STEM-EDS according to claim 1, characterized in that, In step a), the transmission electron microscope sample is prepared by electrolytic polishing or focused ion beam method, and the thin area thickness of the sample is controlled in the range of 50 nm to 100 nm.

3. The method for quantitative analysis of trace elements in the interface of superalloy by STEM-EDS according to claim 1, characterized in that, In step c), the interfaces with different characteristic morphologies include straight line interfaces and curved line interfaces, wherein when the normal direction Δθ of the interface along the length direction is ≥10°, it can be marked as a curved line interface; otherwise, it is marked as a straight line interface.

4. The method of claim 1, wherein the micro-amount of element of the interface of the superalloy is quantitatively analyzed by STEM-EDS. In step b), the acceleration voltage of the transmission electron microscope is set to 200 kV.

5. The method for quantitative analysis of trace elements in the interface of superalloy by STEM-EDS according to claim 1, characterized in that, In step c), the high magnification is 250k .

6. The method of claim 1, wherein the micro-amount of element of the interface of the superalloy is quantitatively analyzed by STEM-EDS. In step c), the EDS face scanning data acquisition time is 25 minutes to 30 minutes.

7. The method of claim 1, wherein the micro-amount of element of the interface of the superalloy is quantitatively analyzed by STEM-EDS. After step g), step h) is further included: comparing the calculated target element mass percentage content interval wt% with the known chemical composition mass percentage wt0% of the element in the high-temperature alloy, when wt0% is located in the uncertainty interval of wt%, it is confirmed that the detection result wt% has reliability.

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