Double-phase multi-principal-element alloy component design method for laser melting deposition titanium steel connection transition layer

Abstract

The invention relates to a double-phase multi-principal-element alloy component design method for a laser melting deposition titanium steel connection transition layer, which aims at constructing a single-layer double-phase solid solution transition layer containing main alloy elements in titanium alloy and steel and combining experience criteria of phase stability of a multi-principal-element alloy system, high-flux phase diagram calculation and machine learning feature engineering. And efficient screening and quantitative design of the biphase transition layer alloy components are achieved. According to the method, the phase composition characteristics and the element proportion of the transition layer multi-principal element alloy system can be predicted in the design stage, it is guaranteed that when the transition layer components change, the forming stability of a solid solution structure is still kept, and forming of harmful intermetallic compounds is inhibited; and meanwhile, the problems of transition layer thickness, heterogeneous interface defects and preparation process complexity caused by introduction of a multi-layer composite transition layer are reduced, so that the metallurgical bonding performance of the titanium alloy and steel heterogeneous interface is improved, and a scientific basis and a calculation method support are provided for design and optimization of a heterogeneous metal connection transition layer alloy system.

Description

Technical Field

[0001] This invention relates to the field of heterogeneous metal additive manufacturing. Background Technology

[0002] Titanium alloy / steel heterostructures prepared by laser melting deposition possess both low density and high specific strength, meeting the requirements of hypersonic missile warhead shells for lightweight and high strength. However, due to the differences in the thermophysical properties of Ti and Fe, and the tendency for brittle intermetallic compounds to form at the heterostructure interface, defects such as interface cracks and voids occur, significantly reducing metallurgical bonding performance and structural stability.

[0003] The paper "Yuyan Wang, Yayun Lu, Yue Zhao, Jiguo Shan, Aiping Wu, Yueliang Lu, Identifying and suppressing Cr3Ni2 σ-phase via transition layer design for reliable titanium–steel bimetal fabrication in laser directed energy deposition. Materials&Design, 2025, 256, 114188" discloses a "multilayer composite transition layer design method based on suppressing the formation of brittle intermetallic compounds." This method, based on phase diagram thermodynamic analysis, aims to block elemental contacts that easily diffuse to form brittle intermetallic compounds. A composite transition layer is constructed by sequentially depositing a TC4 layer, a V layer, a Cr layer, and a Ni-Cr alloy layer on a TC4 substrate using laser melting deposition. Finally, an M50 steel layer is deposited. By adjusting the Cr content in the Ni-Cr alloy layer, the region in the phase diagram where the σ-Cr3Ni2 phase easily forms is avoided, thereby reducing the formation of brittle intermetallic compounds in Ti-Fe, Ti-Ni, Fe-V, and Cr-Ni systems.

[0004] However, to achieve effective element diffusion isolation, this method requires multiple optimizations of process parameters and increases in transition layer thickness, inevitably introducing multiple interfaces with significantly different physicochemical properties. This increases the complexity of the preparation process and leads to defects such as stress concentration, cracks, and voids. Furthermore, while this method, based on a binary phase diagram, can quickly obtain the alloy composition of the transition layer connecting pure titanium and pure iron, it does not consider the influence of alloying element diffusion from the titanium alloy to the steel on the phase composition of the transition layer. Therefore, it is difficult to effectively improve the structural stability and metallurgical bonding performance of the titanium-steel heterojunction interface. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a high-entropy effect based on a multi-principal alloy system. By establishing a quantitative relationship between the phase volume fraction and the proportion of transition layer alloy elements in the composition space of the two-phase solid solution, a transition layer alloy composition with a tendency to form a stable solid solution is obtained, thereby suppressing the formation of brittle intermetallic compounds at heterogeneous interfaces. This is achieved by designing a laser melting deposition titanium-steel connection transition layer two-phase multi-principal alloy composition.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: a method for designing the composition of a dual-phase multi-principal-element alloy for laser melting deposition of titanium-steel connection transition layers, comprising the following steps: Step 1: Based on the nominal composition of titanium alloys and steel, select elements that can form solid solutions with Ti and Fe elements without easily forming harmful intermetallic compounds as pre-selected alloying elements for the transition layer. Further select elements with different crystal structures from the pre-selected alloying elements, and which do not form harmful intermetallic compounds with Ti, Fe and the pre-selected alloying elements, as supplementary alloying elements for the transition layer; Meanwhile, elements with a mass fraction greater than 1 wt.% in the nominal composition of titanium alloy and steel, together with pre-selected alloying elements and supplementary alloying elements, are selected as components of the single-layer transition layer, thereby constructing a multi-principal alloy system for the transition layer to accommodate the main alloying elements in the titanium alloy and steel that diffuse into the transition layer, forming a single-layer transition layer with a body-centered cubic and face-centered cubic dual-phase solid solution structure. Step 2: Convert the mass fraction of each element in the multi-principal alloy system of the transition layer into atomic fraction. With the constraint that the multi-principal alloy system of the transition layer contains at least three elements and the total atomic fraction is 100 at.% with a step size of 1 at.%, generate the full composition space of the multi-principal alloy system of the transition layer. Then, with the goal of minimizing the total free energy of forming body-centered cubic and face-centered cubic two-phase solid solutions, the empirical criteria for phase stability of multi-principal alloy systems are used as screening conditions, and the boundary values ​​of the empirical criteria for phase stability are used as screening criteria to obtain the composition space of two-phase solid solutions with a single-layer transition layer. That is, the high entropy effect of multi-principal alloy systems is used to suppress the formation of harmful intermetallic compounds. Step 3: With the goal of ensuring that the range of alloy element values ​​in the multi-principal alloy system can uniformly cover the composition space of the first-screened two-phase solid solution, a stratified sampling method is used to select representative alloy components in the composition space of the first-screened two-phase solid solution and perform high-throughput phase diagram calculations accordingly to obtain the volume fraction of body-centered cubic and face-centered cubic phases in different multi-principal alloy systems under set temperature conditions. Next, the atomic fractions of elements and the corresponding volume fractions of body-centered cubic and face-centered cubic phases in different multi-principal alloy systems were used as characteristic variables. The Pearson correlation coefficient method was used to analyze the linear correlation between the characteristic variables, and the random forest regression model was used to calculate the characteristic importance of different alloying elements to the volume fractions of body-centered cubic and face-centered cubic phases. Furthermore, based on the linear correlation and feature importance results of the feature variables, alloying elements with high linear correlation and lowest feature importance are eliminated to obtain the composition space of the two-phase solid solution after secondary screening. Step 4: Perform high-throughput phase diagram calculations on all alloy compositions in the two-phase solid solution composition space after secondary screening to obtain the volume fractions of body-centered cubic and face-centered cubic phases corresponding to different alloy compositions under set temperature conditions. Next, the atomic fractions of the pre-selected alloying elements and supplementary alloying elements in the transition layer were normalized, and a mapping relationship between the alloying element ratio and the sum of the volume fractions of the body-centered cubic phase and the face-centered cubic phase was plotted. Based on the mapping results, the distribution trend between the alloying element ratio and the volume fractions of the body-centered cubic phase and the face-centered cubic phase was analyzed, and a quantitative relationship between the phase volume fraction and the alloying element ratio was established, thereby determining the boundary of the value range of the pre-selected alloying elements and supplementary alloying elements in the transition layer.

[0007] Furthermore, it also includes, Step 5: Use sandpaper of different grits to polish the titanium alloy substrate in sequence to remove the surface oxide layer. Then, use acetone and anhydrous ethanol for ultrasonic cleaning in sequence, and set it aside after drying. Weigh the elemental powder with a purity of not less than 99% according to the atomic fractions corresponding to the range of values ​​of the pre-selected alloying elements and supplementary alloying elements of the transition layer obtained in Step 4. After mixing evenly by ball milling, the transition layer alloy powder is prepared. Then, the designed transition layer and steel are deposited sequentially on the pretreated titanium alloy substrate using laser melting deposition technology, which realizes the high-entropy solid solution bonding between titanium alloy / steel heteromaterials.

[0008] Furthermore, the transition layer multi-principal element alloy system is an alloy used for high-entropy solid solution bonding of titanium alloys and steel. The alloying elements of the transition layer include the main alloying elements in titanium alloys and steel, and are within the range of commonly used elements in high-entropy alloys.

[0009] Furthermore, the empirical criteria for phase stability of the multi-principal element alloy system described in step two include: mixing entropy. Mixed enthalpy Solid solution formation parameters Average lattice distortion inside the alloy Local lattice distortion strain energy Valence electron concentration and poor electronegativity ; Then, the boundary values ​​of the empirical criteria for phase stability are as follows: ; ; ; ; ; ; ; .

[0010] Furthermore, the empirical criterion for phase stability of the multi-principal element alloy system described in step two is: , , , , , , , , In the formula, The mixing entropy of a multi-principal-element alloy system is expressed in units of . ; The gas constant is... ; for Atom fraction of an element, in units of ; The mixing enthalpy of a multi-principal alloy system, in units of ; for Elements and Binary enthalpy of mixing between elements; These are the solid solution formation parameters for multi-principal element alloy systems; for Melting point of an element, in units of ; is a lattice distortion parameter, representing the average lattice distortion in a multi-principal-element alloy system; and They are respectively Atomic radius of elements and average atomic radius of transition layer alloying elements, in units of ; is a normalized parameter for the geometric packing state, representing local lattice distortion in a multi-principal element alloy system; and These are the largest and smallest atomic radii among alloying elements, in units of 1 / 2 Å. ; These are parameters related to strain energy, in units of... ; and Transition layer alloy and The concentration of valence electrons in an atom; Because of poor electronegativity, and They are respectively Atoms and alloys average Pauling electronegativity.

[0011] Furthermore, in step three, the Pearson correlation coefficient between any two of the aforementioned feature variables is expressed by the formula: , , , In the formula, For characteristic variables and The Pearson correlation coefficient between them; Let X be the covariance of the characteristic variables X and Y. and These are the standard deviations of the characteristic variables X and Y, respectively; and The first and second are the characteristic variables X and Y, respectively. A number; and These are the average values ​​of the characteristic variables X and Y, respectively; This represents the total number of values ​​in the feature variables.

[0012] Furthermore, in step three, the random forest regression model constructed using multiple regression decision trees is used to calculate feature importance, where the feature variables... The importance of a feature is expressed by the formula: , , , , In the formula, For the first Index of each feature variable; The averaging of all decision trees yields the first... The global feature importance of each feature variable is such that the sum of the feature importance of all feature variables is 1. Indicates the first A decision tree; The number of decision trees; In the decision tree, the first... One node; For the first The set of nodes in a decision tree; Represents a node Using feature variables To split; For nodes Includes sample size; This represents the total number of samples used to train the random forest model; For nodes The lower the impurity, the smaller the prediction error of that node; For nodes The amount of impurity reduction caused by splitting; The total number of characteristic variables; This is the index of the feature variable, used when summing all feature variables; and These represent the number of samples for the left and right child nodes, respectively. and These represent the impurities of the left and right child nodes, respectively. For the first The true target value of each training sample; For nodes The average value of the target value in the sample.

[0013] Furthermore, the temperature under the set temperature conditions is from 20 degrees Celsius to the melting point temperature.

[0014] Furthermore, if the pre-selected alloying element is Cr or V, and the supplementary alloying element is Cu, then the alloying elements in the transition layer multi-principal element alloy system specifically include Ti, Fe, Cr, Cu, V, Al, Si, and Ni. In step three, 10,000 gold components are extracted from the composition space of the two-phase solid solution in one screening to ensure that the value range of each element in the sample data can cover the entire composition space, thereby obtaining the phase composition of 10,000 gold components at a temperature of 20 degrees Celsius, and extracting the volume fraction of the corresponding body-centered cubic phase and face-centered cubic phase. Furthermore, in step four, based on the trend between the volume fraction and elemental ratio of body-centered cubic and face-centered cubic phases under room temperature conditions in the image, five components with atomic ratios of Cr, Cu, and V of 1:0.6:0.6, 1:1:0.6, 1:1.4:0.6, 1:1:0.4, and 1:1:0.8, respectively, were selected from the pre-selected transition layer alloy composition range of V / Cr ratio between 0.4 and 0.8 and Cu / Cr ratio between 0.6 and 1.4 for experimental testing. This determined the CrCuV alloy composition. 0.6 Transition layer alloy.

[0015] The beneficial effects of this invention are: Based on the high entropy effect of the multi-principal alloy system, this invention introduces a single-layer multi-principal alloy transition layer at the interface between titanium alloy and steel, which accommodates Ti and Fe elements on both sides to form a stable solid solution structure, and significantly reduces the content of brittle intermetallic compounds in the transition layer.

[0016] The single-layer multi-principal element alloy transition layer design effectively simplifies the transition layer preparation process and reduces stress concentration, cracks, and porosity defects caused by the increased heterogeneous interfaces. Furthermore, based on the quantitative relationship between the volume fraction of the solid solution phase and the proportion of alloying elements in the transition layer, this invention obtains a multi-principal element alloy composition for the transition layer that exhibits a large solid solution range compared to the main alloying elements in titanium alloys and steel. This method ensures that the stability of the solid solution structure can be maintained even when the composition of the transition layer alloy varies within a certain range during laser melting deposition. It significantly improves the metallurgical bonding performance of titanium-steel heterojunction interfaces, providing a scientific basis and computational support for the design and optimization of heterojunction transition layer alloy systems. It avoids the process complexity caused by repeatedly optimizing process parameters to prepare multiple transition layers in order to achieve element diffusion isolation, and at the same time reduces the risk of stress concentration and defects such as cracks and pores caused by significant differences in the physicochemical properties between heterojunction interfaces. Attached Figure Description

[0017] Figure 1 To establish a full composition space diagram of the transition layer multi-principal element alloy system; Figure 2 This is a schematic diagram of the composition space of a first-stage two-phase solid solution obtained by full composition space screening of a multi-principal alloy system based on empirical criteria for phase stability of the multi-principal alloy system. Figure 3 The Pearson correlation coefficients between the alloying elements of the transition layer and the face-centered cubic and body-centered cubic phases in the transition layer at room temperature. Figure 4 The importance of the characteristics between transition layer alloying elements and phase composition; (a) represents the body-centered cubic phase in the transition layer under room temperature conditions; (b) represents the face-centered cubic phase in the transition layer under room temperature conditions. Figure 5 This is a schematic diagram of the composition space of a two-phase solid solution obtained after the first screening of the composition space of the two-phase solid solution by linear correlation and feature importance. Figure 6 This diagram illustrates the relationship between the proportions of pre-selected and supplementary alloying elements in the transition layer and the volume fraction of the phase in the compositional space of a two-phase solid solution undergoing secondary screening. Wherein, (a) represents the normalized Cr element; (b) represents the normalized Cu element; (c) represents the normalized V element; and (a1) is a magnified view of a portion of Figure a. Figure 7 TC4 / CrCuV 0.6 / G50 sample scanning electron microscopy image and electron backscatter diffraction analysis image; (a) shows the microstructure of the sample; (b) shows the microstructure of CrCuV. 0.6 Phase composition in the transition layer. Detailed Implementation

[0018] The principles and features of the present invention are described 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.

[0019] This invention is primarily a method for designing the composition of a single-layer transition layer in a body-centered cubic and face-centered cubic dual-phase multi-principal element alloy system for laser melting deposition of titanium alloys and steel. This method also allows those skilled in the art to study the composition design of transition layers for other commonly used alloying elements in high-entropy alloys.

[0020] This invention is based on the high-entropy effect of multi-principal element alloy systems. It introduces a single-layer multi-principal element alloy capable of forming a high-solubility solid solution with Ti and Fe elements into the transition layer, thereby suppressing the formation of brittle intermetallic compounds. This method avoids the process complexity caused by repeatedly optimizing process parameters to prepare multiple transition layers for element diffusion isolation. It also reduces the risk of stress concentration and defects such as cracks and voids due to significant differences in physicochemical properties between heterogeneous interfaces.

[0021] Furthermore, by establishing a quantitative relationship between the phase volume fraction and the proportions of pre-selected alloying elements and supplementary alloying elements in the transition layer within the composition space of the two-phase solid solution, this invention obtains a transition layer alloy composition with a tendency to form a stable solid solution.

[0022] The solid solution range of this alloy composition covers the compositional variation range of the main alloying elements in titanium alloys and steel, solving the problem that the diffusion of alloying elements in titanium alloys and steel during laser melting deposition causes changes in the composition of the transition layer, thereby damaging the stability of the transition layer structure and reducing the metallurgical bonding performance of the titanium-steel heterogeneous interface.

[0023] To achieve the above objectives, the present invention provides the following specific embodiments: Example 1: A method for designing the composition of a dual-phase multi-principal-element alloy for laser-melted deposition of titanium-steel bonding transition layers, comprising the following steps: Step 1: Based on the nominal composition of titanium alloys and steel, select elements that can form solid solutions with Ti and Fe elements without easily forming harmful intermetallic compounds as pre-selected alloying elements for the transition layer. Further select elements with different crystal structures from the pre-selected alloying elements, and which do not form harmful intermetallic compounds with Ti, Fe and the pre-selected alloying elements, as supplementary alloying elements for the transition layer; Meanwhile, elements with a mass fraction greater than 1 wt.% in the nominal composition of titanium alloy and steel, together with pre-selected alloying elements and supplementary alloying elements, are selected as components of the single-layer transition layer, thereby constructing a multi-principal alloy system for the transition layer to accommodate the main alloying elements in the titanium alloy and steel that diffuse into the transition layer, forming a single-layer transition layer with a body-centered cubic and face-centered cubic dual-phase solid solution structure. The transition layer multi-principal element alloy system is an alloy used for high-entropy solid solution bonding of titanium alloys and steel. The alloying elements of the transition layer include the main alloying elements in titanium alloys and steel, and are within the range of commonly used elements in high-entropy alloys.

[0024] Step 2: Convert the mass fraction of each element in the multi-principal alloy system of the transition layer into atomic fraction. With the constraint that the multi-principal alloy system of the transition layer contains at least three elements and the total atomic fraction is 100 at.% with a step size of 1 at.%, the goal is to minimize the total free energy of forming a body-centered cubic and face-centered cubic two-phase solid solution, and generate the full composition space of the multi-principal alloy system of the transition layer. Then, using the empirical criteria for phase stability of multi-principal alloy systems as screening conditions and the boundary values ​​of the empirical criteria as screening criteria, the composition space of the single-layer transition layer is obtained for the first screening of the two-phase solid solution. This means using the high entropy effect of multi-principal alloy systems to suppress the formation of harmful intermetallic compounds. Among them, empirical criteria for phase stability of multi-principal element alloy systems include, but are not limited to: mixing entropy. Mixed enthalpy Solid solution formation parameters Average lattice distortion inside the alloy Local lattice distortion strain energy Valence electron concentration and poor electronegativity ; The empirical criterion for phase stability in multi-principal element alloy systems is as follows: , , , , , , , , In the formula, The mixing entropy of a multi-principal-element alloy system is expressed in units of . ; The gas constant is... ; for Atom fraction of an element, in units of ; The mixing enthalpy of a multi-principal alloy system, in units of ; for Elements and Binary enthalpy of mixing between elements; These are the solid solution formation parameters for multi-principal element alloy systems; for Melting point of an element, in units of ; is a lattice distortion parameter, representing the average lattice distortion in a multi-principal-element alloy system; and They are respectively Atomic radius of elements and average atomic radius of transition layer alloying elements, in units of ; is a normalized parameter for the geometric packing state, representing local lattice distortion in a multi-principal element alloy system; and These are the largest and smallest atomic radii among alloying elements, in units of 1 / 2 Å. ; These are parameters related to strain energy, in units of... ; and Transition layer alloy and The concentration of valence electrons in an atom; Because of poor electronegativity, and They are respectively Atom and alloy average Pauling electronegativity; The boundary values ​​of the empirical criteria are as follows: ; ; ; ; ; ; ; .

[0025] Step 3: With the goal of ensuring that the range of alloy element values ​​in the multi-principal alloy system can uniformly cover the composition space of the first-screened two-phase solid solution, a stratified sampling method is used to select representative alloy components in the composition space of the first-screened two-phase solid solution and perform high-throughput phase diagram calculations accordingly to obtain the volume fraction of body-centered cubic and face-centered cubic phases in different multi-principal alloy systems under set temperature conditions. Next, the atomic fractions of elements and the corresponding volume fractions of body-centered cubic and face-centered cubic phases in different multi-principal alloy systems were used as characteristic variables. The Pearson correlation coefficient method was used to analyze the linear correlation between the characteristic variables, and the random forest regression model was used to calculate the characteristic importance of different alloying elements to the volume fractions of body-centered cubic and face-centered cubic phases. The Pearson correlation coefficient between any two feature variables is expressed by the formula: , , , In the formula, For characteristic variables and The Pearson correlation coefficient between them; Let X be the covariance of the characteristic variables X and Y. and These are the standard deviations of the characteristic variables X and Y, respectively; and The first and second are the characteristic variables X and Y, respectively. A number; and These are the average values ​​of the characteristic variables X and Y, respectively; The total number of values ​​in the feature variables; Feature importance is calculated using a random forest regression model composed of multiple regression decision trees, where the feature variables... The importance of a feature is expressed by the formula: , , , , In the formula, For the first Index of each feature variable; The averaging of all decision trees yields the first... The global feature importance of each feature variable is such that the sum of the feature importance of all feature variables is 1. Indicates the first A decision tree; The number of decision trees; In the decision tree, the first... One node; For the first The set of nodes in a decision tree; Represents a node Using feature variables To split; For nodes Includes sample size; This represents the total number of samples used to train the random forest model; For nodes The lower the impurity, the smaller the prediction error of that node; For nodes The amount of impurity reduction caused by splitting; The total number of characteristic variables; This is the index of the feature variable, used when summing all feature variables; and These represent the number of samples for the left and right child nodes, respectively. and These represent the impurities of the left and right child nodes, respectively. For the first The true target value of each training sample; For nodes The average of the target values ​​in the sample; Furthermore, based on the linear correlation and feature importance results of the feature variables, alloying elements with high linear correlation and low feature importance are eliminated to obtain the composition space of the two-phase solid solution after secondary screening.

[0026] Step 4: Perform high-throughput phase diagram calculations on all alloy compositions in the two-phase solid solution composition space after secondary screening to obtain the volume fractions of body-centered cubic and face-centered cubic phases corresponding to different alloy compositions under set temperature conditions. Next, the atomic fractions of the pre-selected alloying elements and supplementary alloying elements in the transition layer were normalized, and a mapping relationship between the alloying element ratio and the sum of the volume fractions of the body-centered cubic phase and the face-centered cubic phase was plotted. Based on the mapping results, the distribution trend between the alloying element ratio and the volume fractions of the body-centered cubic phase and the face-centered cubic phase was analyzed, and a quantitative relationship between the phase volume fraction and the alloying element ratio was established, thereby determining the boundary of the value range of the pre-selected alloying elements and supplementary alloying elements in the transition layer.

[0027] Step 5: Use sandpaper of different grits to polish the titanium alloy substrate in sequence to remove the surface oxide layer. Then, use acetone and anhydrous ethanol for ultrasonic cleaning in sequence, and set it aside after drying. Weigh the elemental powder with a purity of not less than 99% according to the atomic fractions corresponding to the range of values ​​of the pre-selected alloying elements and supplementary alloying elements of the transition layer obtained in Step 4. After mixing evenly by ball milling, the transition layer alloy powder is prepared. Then, the designed transition layer and steel are deposited sequentially on the pretreated titanium alloy substrate using laser melting deposition technology, which realizes the high-entropy solid solution bonding between titanium alloy / steel heteromaterials.

[0028] Example 2: Same as Example 1, except that the temperature in step four is set to 20 degrees Celsius to the melting point.

[0029] Example 3: Same as Example 1, except that: Step 1: Table 1 shows the nominal composition of TC4 titanium alloy, and Table 2 shows the nominal composition of G50 steel. Based on the nominal composition tables of TC4 titanium alloy and G50 steel in Tables 1 and 2, Cr and V elements, which tend to form solid solutions with Ti and Fe but do not form harmful intermetallic compounds, are selected as pre-selected transition layer alloying elements. Cu element, which has a face-centered cubic structure and, according to the binary alloy phase diagram, does not form harmful intermetallic compounds with Ti, Fe, or the pre-selected transition layer alloying elements, is selected as a supplementary transition layer alloying element. Table 1

[0030] Table 2

[0031] Step 2: Based on the nominal composition of TC4 titanium alloy and G50 steel, extract alloying elements with a content higher than 1 wt.% and the transition layer alloying elements from Step 1, namely the octagonal alloy composed of Ti, Fe, Cr, Cu, V, Al, Si, and Ni. The alloying elements in the multi-principal element alloy system at this point specifically include Ti, Fe, Cr, Cu, V, Al, Si, and Ni, and their possible value ranges in the transition layer are shown in Table 3. Table 3 is a table of spatial element value ranges (at.%) for octagonal alloy composition. Table 3

[0032] Step 3: Edit Python code, set the total content of the transition layer multi-principal alloy system to 100 at.%, and the step size to 1 at.%, with the constraint that at least 3 alloying elements exist simultaneously in the transition layer, and generate the full composition space of the transition layer multi-principal alloy system. The boundary values ​​of empirical criteria for phase stability in multi-principal element alloy systems, including mixing entropy, mixing enthalpy, solid solution formation parameters, average lattice distortion, local lattice distortion, strain energy, valence electron concentration, and electronegativity difference, are used as the initial screening criteria for solid solution formation space in the full composition space of transition layer multi-principal element alloy systems. This screening identifies the composition space for two-phase solid solutions and calculates it using the empirical criterion formula for phase stability in multi-principal element alloy systems. The empirical criterion formula for phase stability in multi-principal element alloy systems is as follows:

[0033]

[0034]

[0035]

[0036]

[0037]

[0038]

[0039]

[0040] in, The mixing entropy of a multi-principal-element alloy system is expressed in units of . Its boundary value is ; This is the gas constant, with units of . ; for Element concentration, in units of ; The mixing enthalpy of a multi-principal alloy system, in units of Its boundary value is ; for Elements and Binary enthalpy of mixing between elements; The solid solution formation parameters for multi-principal element alloy systems have boundary values. ; for Melting point of an element, in units of ; Let be the lattice distortion parameter, representing the average lattice distortion in a multi-principal element alloy system, with boundary values ​​of . ; and They are respectively Atomic radius of elements and average atomic radius of alloying elements, in units of ; The normalized parameter for the geometric packing state represents the local lattice distortion in a multi-principal element alloy system, with boundary values ​​of . ; and These are the largest and smallest atomic radii among alloying elements, in units of 1 / 2 Å. ; For strain energy related parameters, their boundary values ​​are ; and They are alloys and The valence electron concentration of an atom, its boundary value is ; For poor electronegativity, its boundary value is ; and They are respectively Atom and alloy average Pauling electronegativity; At this point, 10,000 gold compositions were selected from the composition space of the two-phase solid solution screened by stratified sampling to ensure that the range of values ​​of each element in the sample data could cover the entire composition space. The phase composition of the 10,000 gold compositions under room temperature conditions was obtained by high-throughput phase diagram calculation using Pandat software. The volume fractions of face-centered cubic and body-centered cubic phases in the transition layer under the corresponding room temperature conditions were extracted from the results. Next, the linear correlation between any two feature variables is calculated using the Pearson correlation coefficient from machine learning feature engineering, expressed by the formula:

[0041]

[0042]

[0043] in, For characteristic variables and characteristic variables The Pearson correlation coefficient between them; Let X be the covariance of the characteristic variables X and Y. and These are the standard deviations of the characteristic variables X and Y, respectively; and The first and second are the characteristic variables X and Y, respectively. One value; and These are the average values ​​of the characteristic variables X and Y, respectively; This represents the total number of values ​​in the feature variables; feature importance is calculated using a random forest regression model, i.e., a random forest model is constructed using multiple regression decision trees, where the feature... The global feature importance is expressed by the formula:

[0044]

[0045]

[0046]

[0047] in, For the first Index of features; The averaging of all decision trees yields the first... The global feature importance of each feature is such that the sum of the feature importance of all features is 1. Indicates the first A decision tree; The number of decision trees; In the decision tree, the first... One node; For the first The set of nodes in a decision tree; Represents a node Use features To split; For nodes Includes sample size; This represents the total number of samples used to train the random forest model; For nodes The lower the impurity, the smaller the prediction error of that node; For nodes The amount of impurity reduction caused by splitting; The total number of features; The index of the feature is used when summing all features; and These represent the number of samples for the left and right child nodes, respectively. and These represent the impurities of the left and right child nodes, respectively. For the first The true target value of each training sample; For nodes The average of the target values ​​in the sample; Based on the linear correlation results between any characteristic variables, Al elements with high linear correlation and the least importance of volume fraction characteristics of face-centered cubic and body-centered cubic phases in the transition layer under room temperature conditions are removed. The composition space that does not contain Al elements is selected from the first screening of the two-phase solid solution composition space, thus obtaining the second screening of the two-phase solid solution composition space.

[0048] Step 4: Substitute all alloy compositions in the target composition space into Pandat software for high-throughput phase diagram calculations to obtain the volume fractions of face-centered cubic and body-centered cubic phases in the transition layer under corresponding room temperature conditions. Normalize the alloy elements in the transition layer to obtain a mapping image of the relationship between the alloy element ratio and phase composition. Based on the trend between the volume fractions and element ratios of face-centered cubic and body-centered cubic phases under room temperature conditions in the image, select five components with atomic ratios of Cr, Cu, and V of 1:0.6:0.6, 1:1:0.6, 1:1.4:0.6, 1:1:0.4, and 1:1:0.8, respectively, from the pre-selected range of transition layer alloy compositions with V / Cr ratios between 0.4 and 0.8 and Cu / Cr ratios between 0.6 and 1.4, for experimental research.

[0049] Step 5, after obtaining the target transition layer alloy composition, further includes: polishing the titanium alloy substrate with sandpaper of different grit sizes and removing the oxide layer and stains on the surface of the titanium alloy substrate using acetone and anhydrous ethanol; and sequentially depositing the transition layer and steel on the titanium alloy substrate using a laser melting deposition method.

[0050] To further illustrate the present invention, specific operational examples are also provided: such as Figures 1-7 As shown, S01: Establish a full composition space diagram of the transition layer multi-principal element alloy system, such as... Figure 1 As shown; S02: Using empirical criteria for phase stability, the full composition space of the transition layer multi-principal element alloy system is screened to obtain a schematic diagram of the composition space of a two-phase solid solution after a single screening, as shown below. Figure 2 As shown; S03: Using the Pearson correlation coefficient method in machine learning feature engineering, calculate the linear correlation between any two feature variables, including eight elements (Ti, Fe, Cr, Cu, V, Al, Si, and Ni) and the volume fractions of face-centered cubic and body-centered cubic phases in the transition layer at room temperature. The Pearson correlation coefficient ranges from [-1, 1]. Values ​​closer to 1 or -1 indicate a high positive or negative linear correlation between the two feature variables. Red represents positive correlation, and blue represents negative correlation; the closer the value is to 1 or -1, the darker the color. The results are as follows: Figure 3 As shown; S04: A random forest model is constructed using multiple regression decision trees. The feature importance of each feature to the body-centered cubic phase under room temperature conditions is calculated to obtain... Figure 4 (a) Results; Results obtained by the same method regarding the importance of alloying elements for the volume fraction characteristics of face-centered cubic phases at room temperature, such as... Figure 4 As shown in (b); S05: Based on the results of linear correlation and feature importance analysis, the composition space of two-phase solid solutions screened in the first screening was further screened to obtain the composition space of two-phase solid solutions screened in the second screening, as follows: Figure 5 As shown; S06: Perform a visual analysis of the target composition space. Alloy compositions where the sum of the volume fractions of face-centered cubic and body-centered cubic phases at room temperature is less than 50% are represented by a color map. The closer the sum of the volume fractions is to 50%, the closer the color is to red; the closer the sum of the volume fractions is to 0, the closer the color is to blue. Alloy compositions with a sum of volume fractions between 50% and 55% are represented by blue rhombuses, those between 55% and 60% by purple pentagons, and those greater than 60% by red hexagons. Normalize the Cr element in the target composition space, and plot the mapping diagram with the Cu / Cr ratio and V / Cr ratio as the horizontal and vertical axes, respectively, as shown below. Figure 6 As shown in (a); Figure 6 (b) and Figure 6 (c) are normalized Cu and V element mapping diagrams, respectively; Figure 6 (a1) is Figure 6 (a) A magnified view of a region where the V / Cr ratio is between 0.2 and 2.0 and the Cu / Cr ratio is between 0.4 and 2.0; the blue spherical marks indicate the boundaries of regions with high density of the sum of the volume fractions of body-centered cubic and face-centered cubic phases at room temperature, serving as the boundaries of the pre-selected transition layer alloy composition range; within this range, five representative alloy compositions are selected, as shown in the figure with black cross-shaped markings, with Cr, Cu, and V atomic ratios of 1:0.6:0.6, 1:1:0.6, 1:1.4:0.6, 1:1:0.4, and 1:1:0.8, respectively; S07: CrCuV 0.6 Using a transition layer alloy as a representative sample, CrCuV was sequentially deposited on a TC4 substrate using laser melting deposition technology. 0.6 The transition layer and the G50 steel layer were used to obtain scanning electron micrographs of the sample, such as... Figure 7 As shown in (a), where CrCuV 0.6 The average thickness of the transition layer is approximately 970 μm; Figure 7 (a) Electron backscattering diffraction analysis was performed on the transition layer region within the red box. The phase distribution results showed that the volume fractions of body-centered cubic and face-centered cubic phases were 68.5% and 17%, respectively. Figure 7 As shown in (b).

[0051] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method of designing a composition of a dual-phase multi-principal element alloy for a laser fusion deposition titanium steel joint transition layer, characterized in that, The method comprises the following steps: Step 1: According to the nominal composition of the titanium alloy and the steel, elements capable of forming a solid solution with Ti and Fe elements and not easily forming harmful intermetallic compounds are selected as pre-selected alloying elements of the transition layer; Further, elements different from the lattice structure of the pre-selected alloying elements and not forming harmful intermetallic compounds with Ti, Fe elements and the pre-selected alloying elements are selected as supplementary alloying elements of the transition layer; At the same time, elements with a mass fraction greater than 1wt.% in the nominal composition of the titanium alloy and the steel are selected together with the pre-selected alloying elements and the supplementary alloying elements as components of a single-layer transition layer, thereby constructing a multi-principal element alloy system of the transition layer to accommodate the main alloying elements of the titanium alloy and the steel diffused into the transition layer, and forming a single-layer transition layer with a body-centered cubic and face-centered cubic dual-phase solid solution structure; Step 2: The mass fraction of each element in the multi-principal element alloy system of the transition layer is converted into an atomic fraction, and a full composition space of the multi-principal element alloy system of the transition layer is generated under the constraint conditions that the multi-principal element alloy system of the transition layer contains at least three elements and the total atomic fraction is 100at.% with a step of 1at.%; Then, a first screening dual-phase solid solution composition space of the single-layer transition layer is obtained by taking the minimization of the total free energy of the body-centered cubic and face-centered cubic dual-phase solid solution as the target, taking the empirical criterion for phase stability as the screening condition, and taking the boundary value of the empirical criterion for phase stability as the screening basis, that is, the high-entropy effect of the multi-principal element alloy system is used to inhibit the formation of harmful intermetallic compounds; Step 3: A representative alloy composition is selected in the first screening dual-phase solid solution composition space by using the stratified sampling method, and a high-throughput phase diagram calculation is correspondingly performed to obtain the volume fraction of the body-centered cubic phase and the face-centered cubic phase corresponding to different multi-principal element alloy systems under a set temperature condition, with the aim of ensuring that the alloy element value range in the multi-principal element alloy system can uniformly cover the first screening dual-phase solid solution composition space; Next, the element atomic fraction in different multi-principal element alloy systems and the corresponding volume fraction of the body-centered cubic phase and the face-centered cubic phase are taken as characteristic variables, the linear correlation between the characteristic variables is analyzed by using the Pearson correlation coefficient method, and the characteristic importance of different alloy elements to the volume fraction of the body-centered cubic phase and the face-centered cubic phase is calculated by using the random forest regression model; Further, according to the linear correlation and the characteristic importance of the characteristic variables, the alloy element with high linear correlation and minimum characteristic importance is removed to obtain a second screening dual-phase solid solution composition space; Step 4: High-throughput phase diagram calculation is performed on all alloy compositions in the second screening dual-phase solid solution composition space to obtain the volume fraction of the body-centered cubic phase and the face-centered cubic phase corresponding to different alloy compositions under a set temperature condition. Then, the atomic fractions of the preselected alloying elements and the supplementary alloying elements of the transition layer are normalized respectively, and a mapping relationship diagram of the alloying element proportion and the sum of the volume fractions of the body-centered cubic phase and the face-centered cubic phase is drawn; according to the mapping result, the distribution trend between the alloying element proportion and the volume fractions of the body-centered cubic phase and the face-centered cubic phase is analyzed, and a quantitative relationship between the phase volume fraction and the alloying element proportion is established, so as to determine the value range boundary of the preselected alloying elements and the supplementary alloying elements of the transition layer.

2. The method of claim 1, wherein the composition of the dual-phase multi-principal element alloy is designed by laser melting deposition of a titanium steel joining transition layer having a composition of: Also includes, Step five, using sandpaper of different granularity to polish the titanium alloy substrate in turn to remove the surface oxidation layer, then using acetone and anhydrous ethanol in turn for ultrasonic cleaning, and after drying, standby; The purity of the elemental powder is not less than 99%, and the atomic fraction corresponding to the value range of the preselected alloying elements and the supplementary alloying elements of the transition layer obtained in step four is weighed, uniformly mixed by ball milling, and then a transition layer alloy powder is prepared, and a laser melting and deposition technology is used to deposit the designed transition layer and steel on the pretreated titanium alloy substrate, that is, to realize the high-entropy solid solution connection between titanium alloy / steel heterogeneous materials.

3. The method for designing the composition of a dual-phase multi-principal-element alloy for laser melting deposition of titanium-steel connecting transition layers as described in claim 1, characterized in that, The transition layer multi-principal element alloy system is an alloy for titanium alloy and steel high-entropy solid solution connection, and the alloying elements of the transition layer include the main alloying elements in the titanium alloy and the steel, and are within the range of commonly used elements of high-entropy alloys.

4. The method of claim 1, wherein the composition of the dual-phase multi-principal element alloy of the laser melt-deposited titanium steel joint transition layer is designed by, The empirical criteria for phase stability of the multi-principal element alloy system described in Step two include: mixing entropy , mixing enthalpy , solid solubility parameter , average lattice distortion within the alloy , local lattice distortion , strain energy , valence electron concentration , and difference in electronegativity ; Therefore, the empirical criterion boundary value of phase stability is: ； ； ； ； ； ； 。 5. The method of claim 1, wherein the composition of the dual-phase multi-principal element alloy of the laser melt-deposited titanium steel joint transition layer is designed by, The empirical criterion of phase stability of the multi-principal element alloy system in step two is: ， ， ， ， ， ， ， ， where, is the mixing entropy of the multi-principal element alloy system, with unit of ; is the gas constant, ; is the element atomic fraction, with unit of ; is the mixing enthalpy of the multi-principal element alloy system, with unit of ; is the element and element binary mixing enthalpy; is the solid solubility parameter of the multi-principal element alloy system; is the element melting point, with unit of ; is the lattice distortion parameter, representing the average lattice distortion in the multi-principal element alloy system; and are the atomic radius of element and the average atomic radius of transition layer alloy elements, with unit of ; is the normalized parameter of geometric packing state, representing the local lattice distortion in the multi-principal element alloy system; and are the maximum atomic radius and the minimum atomic radius in the alloy elements, with unit of ; is the strain energy related parameter, with unit of ; and are the valence electron concentration of transition layer alloy and atom, respectively; is the electronegativity difference, and are the Pauling electronegativity of atom and the alloy average, respectively.

6. The method of claim 1, wherein the composition of the dual-phase multi-principal element alloy of the laser melt-deposited titanium steel joint transition layer is designed by, In step three, the Pearson correlation coefficient between any two characteristic variables is expressed by the formula: ， ， ， wherein is the Pearson correlation coefficient between the feature variables and ; is the covariance of the feature variables X and Y; and are the standard deviations of the feature variables X and Y, respectively; and are the i-th values of the feature variables X and Y, respectively; is the number of values of the feature variables X and Y; and are the mean values of the feature variables X and Y, respectively; is the total number of values of the feature variables.

7. The method of claim 1, wherein the composition of the dual-phase multi-principal element alloy of the laser melted deposition titanium steel joint transition layer is designed by, In step three, the random forest regression model composed of multiple regression decision trees is used to calculate the feature importance, where the feature variable The feature importance of is expressed by the formula: ， ， ， ， In the formula, is the index of the th feature variable; is the global feature importance of the th feature variable obtained after averaging all decision trees, and the sum of the feature importance of all feature variables is 1; represents the th decision tree; is the number of decision trees; represents the th node in the decision tree; is the node set of the th decision tree; represents that the node is split using the feature variable ; is the number of samples contained in the node ; is the total number of samples used to train the random forest model; is the impurity of the node , and the smaller the impurity, the smaller the prediction error of the node; is the reduction in impurity caused by splitting the node ; is the total number of feature variables; is the index of the feature variable, used when summing over all feature variables; and are the number of samples of the left and right child nodes, respectively; and are the impurities of the left and right child nodes, respectively; is the true target value of the th training sample; is the average of the target values of the samples in the node .

8. The method of claim 1-7, wherein the composition of the dual-phase multi-principal element alloy of the laser melted deposition titanium steel joint transition layer is designed by, The temperature under the temperature condition is 20 degrees Celsius to the melting point temperature.

9. The method of claim 1-7, wherein the composition of the dual-phase multi-principal element alloy of the laser melted deposition titanium steel joint transition layer is designed by, The preselected alloying element is Cr or V element; the supplementary alloying element is Cu element, and the alloying elements in the transition layer multi-principal element alloy system specifically include Ti, Fe, Cr, Cu, V, Al, Si and Ni elements; Therefore, in step three, 10,000 groups of alloy compositions are extracted from the dual-phase solid solution composition space to ensure that the value range of each element in the sample data can cover the entire composition space, so as to obtain the phase composition of 10,000 groups of alloy compositions under the temperature condition of 20 degrees Celsius, and the volume fractions of the body-centered cubic phase and the face-centered cubic phase are extracted; Further, in step four, according to the trend between the volume fraction of body-centered cubic phase and face-centered cubic phase and the element ratio in the image under room temperature, from the pre-selected transition layer alloy composition range of V / Cr ratio between 0.4 to 0.8 and Cu / Cr ratio between 0.6 to 1.4, five groups of compositions of Cr, Cu and V atomic ratio of 1:0.6:0.6, 1:1:0.6, 1:1.4:0.6, 1:1:0.4 and 1:1:0.8 are selected as representative alloy compositions for testing, and the CrCuV 0.6 transition layer alloy is determined.

Images