Molecular dynamics simulation construction method of high-entropy alloy three-dimensional polycrystalline gradient model

Abstract

The invention discloses a molecular dynamics simulation construction method of a high-entropy alloy three-dimensional polycrystalline gradient model, and relates to a construction method of a three-dimensional polycrystalline gradient model. The method aims at solving the problems that an existing polycrystalline model construction method is complex in step and a constructed polycrystalline model is unreasonable in crystal structure and orientation. According to the molecular dynamics simulation construction method of the polycrystalline gradient model, the steps of the constructed polycrystalline gradient model are clearer and simpler than those of a traditional method, the constructed polycrystalline gradient model is visual in appearance and reasonable in crystal form structure and orientation, and by designing gradient distribution of different crystal grain sizes, shapes and orientations, the molecular dynamics simulation construction method of the polycrystalline gradient model can be used for constructing the polycrystalline gradient model. The material performance optimization is realized, the optimization design of the microstructure is realized, the material performance such as strength, toughness and fatigue life is comprehensively improved, and the method has important significance for developing novel high-performance materials.

Description

Technical Field

[0001] The invention relates to a method for constructing a three-dimensional polycrystalline gradient model. Background Art

[0002] Polycrystalline is a common form of crystal in nature. During the material forming process, due to different cooling rates, the phenomenon of grain gradient distribution will occur in the crystal. For the research methods of polycrystalline materials, not only experimental means, such as scanning, transmission, spherical aberration and other electron microscopy methods, but also high-energy synchrotron radiation, neutron diffraction and other means can be used to characterize its microstructure. The mechanical properties of polycrystalline materials can also be explored by nanoindentation, in-situ stretching or compression, micro-column compression and other methods. The grain size, grain orientation, gradient distribution of grains, grain boundary shape and size of polycrystalline materials will affect the mechanical properties of polycrystalline materials, mainly by affecting the nucleation and growth of dislocations inside the material, as well as the movement of dislocations, thereby affecting the macroscopic properties of the material. The polycrystalline gradient model can achieve a comprehensive improvement in material performance, such as strength, toughness, fatigue life, etc., through the optimization design of the microstructure, which is of great significance for the development of new high-performance materials.

[0003] The transition area of ​​the microstructure of the grain boundary is very small, often only at the level of a few atoms, and the above experimental methods have inevitable limitations. The computational simulation method is more microscopic than the experimental method, and the computational simulation process is more intuitive and clear. However, the construction method of the existing polycrystalline gradient model of metal and alloy materials is complicated and requires additional software plug-ins. In addition, there is the problem of unreasonable crystal structure and orientation of the constructed polycrystalline model. In the polycrystalline model, the orientation between the grains needs to be reasonably matched. If the angle difference between the orientations is too large, it will lead to unreasonable grain boundaries and unstable structures. If the size and distribution of the grains are unreasonable, it will affect the overall crystal structure and orientation. Summary of the invention

[0004] In order to solve the problems that the existing method for constructing a polycrystalline model has complicated steps and the crystal structure and orientation of the constructed polycrystalline model are unreasonable, the present invention proposes a molecular dynamics simulation construction method for a three-dimensional polycrystalline gradient model of a high entropy alloy.

[0005] The molecular dynamics simulation construction method of the high entropy alloy three-dimensional polycrystalline gradient model of the present invention is carried out according to the following steps:

[0006] 1. Generate single crystal unit cell: Use Atomsk plug-in to generate Fe atomic single crystal unit cell of fcc structure, and generate Fe atomic single crystal unit cell file as Fe.xsf file;

[0007] 2. Create a polycrystalline node file: Use python to generate a 3D_gradient.txt file, which is a polycrystalline node file;

[0008] 3. Generate polycrystalline file final.lmp: fill the Fe.xsf unit cell generated in step 1 into the 3D_gradient.txt grain to generate the final.lmp file that can be run by lammps;

[0009] 4. Modify the final.lmp file: modify the type of atoms and add the relative atomic mass of each atom;

[0010] 5. Replace atoms to generate alloy model: In lammps software, set the basic parameters of the alloy model, read the final.lmp file, and use the atomic replacement command settype / ratio to replace Fe with Cr, Ni, Co, and Cu in turn according to the atomic ratio of the high entropy alloy; obtain the multi-component polycrystalline alloy model of the target atomic component;

[0011] 6. Save the model file: Save the multi-element polycrystalline alloy model established in step 5 as a .data file;

[0012] 7. Display and coloring of polycrystalline model: Use Ovito software to read the data file in step 6 to display the multi-element polycrystalline alloy model, and finally color the grains with different grain properties in the multi-element polycrystalline alloy model.

[0013] The grain properties are grain orientation, grain shape and grain size. Grains with different grain properties are grains with different grain properties. Grains with different grain properties in the multi-element polycrystalline alloy model are colored so that grains with different properties can be presented in different colors for subsequent differentiation of polycrystalline grains. Strengthening phases generated in the material research process can be found through the differences in grains.

[0014] When displaying the multi-element polycrystalline alloy model, after using Ovito to read the .data file exported in step six, the neighboring atomic structure analysis CNA in the structure characterization is used to distinguish the grains with different grain properties in the multi-element polycrystalline alloy model;

[0015] When coloring, use Ovito's structural characterization function, then select the colorcoding function, and then select the particleidentifier in the property to be characterized Inputproperty. At this time, the model is set to the same color, and select automatic identification of grain color range Adjustrange in the color range selection to make grains with different grain properties display different colors.

[0016] The beneficial effects of the present invention are:

[0017] The molecular dynamics simulation construction method of the FeCrNiCoCu polycrystalline gradient model in the present invention is more clear and simple in steps compared with the traditional method, and the constructed polycrystalline gradient model has an intuitive appearance, a reasonable crystal structure and orientation, and can also optimize material properties by designing gradient distributions of different grain sizes, shapes and orientations, and realize the optimization design of microstructures, comprehensively improve material properties such as strength, toughness, fatigue life, etc., which is of great significance for the development of new high-performance materials. Moreover, after later simulation and application verification, the model constructed by the present invention has a reasonable structure and stable properties, and can be used for a long time to study the subsequent multiple properties and performances of various polycrystalline material models. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a polycrystalline gradient model diagram established in Example 1;

[0019] Figure 2 For Figure 1 The corresponding nearest atomic structure analysis diagram (CNA);

[0020] Figure 3 For Figure 1 Corresponding grain coloring diagrams with different attributes;

[0021] Figure 4 This is a test diagram of the mechanical properties of the polycrystalline model (the structure of the polycrystalline phase change model during the stretching process);

[0022] Figure 5 This is a test diagram of the mechanical properties of the polycrystalline model (polycrystalline model structure after tensile fracture). DETAILED DESCRIPTION

[0023] The technical solution of the present invention is not limited to the specific implementation modes listed below, but also includes any reasonable combination of the specific implementation modes.

[0024] Specific implementation method 1: The molecular dynamics simulation construction method of the high entropy alloy three-dimensional polycrystalline gradient model in this implementation method is carried out according to the following steps:

[0025] 1. Generate single crystal unit cell: Use Atomsk plug-in to generate Fe atomic single crystal unit cell of fcc structure, and generate Fe atomic single crystal unit cell file as Fe.xsf file;

[0026] 2. Create a polycrystalline node file: Use python to generate a 3D_gradient.txt file, which is a polycrystalline node file;

[0027] 3. Generate polycrystalline file final.lmp: fill the Fe.xsf unit cell generated in step 1 into the 3D_gradient.txt grain to generate the final.lmp file that can be run by lammps;

[0028] 4. Modify the final.lmp file: modify the type of atoms and add the relative atomic mass of each atom;

[0029] 5. Replace atoms to generate alloy model: In lammps software, set the basic parameters of the alloy model, read the final.lmp file, and use the atomic replacement command settype / ratio to replace Fe with Cr, Ni, Co, and Cu in turn according to the atomic ratio of the high entropy alloy; obtain the multi-component polycrystalline alloy model of the target atomic component;

[0030] 6. Save the model file: Save the multi-element polycrystalline alloy model established in step 5 as a .data file;

[0031] 7. Display and coloring of polycrystalline model: Use Ovito software to read the data file in step 6 to display the multi-element polycrystalline alloy model, and finally color the grains with different grain properties in the multi-element polycrystalline alloy model.

[0032] The grain properties are grain orientation, grain shape and grain size. Grains with different grain properties are grains with different grain properties. Grains with different grain properties in the multi-element polycrystalline alloy model are colored so that grains with different properties can be presented in different colors for subsequent differentiation of polycrystalline grains. Strengthening phases generated in the material research process can be found through the differences in grains.

[0033] When displaying the multi-element polycrystalline alloy model, after using Ovito to read the .data file exported in step six, the neighboring atomic structure analysis CNA in the structure characterization is used to distinguish the grains with different grain properties in the multi-element polycrystalline alloy model;

[0034] When coloring, use Ovito's structural characterization function, then select the colorcoding function, and then select the particleidentifier in the property to be characterized Inputproperty. At this time, the model is set to the same color, and select automatic identification of grain color range Adjustrange in the color range selection to make grains with different grain properties display different colors.

[0035] This embodiment has the following beneficial effects:

[0036] The molecular dynamics simulation construction method of the FeCrNiCoCu polycrystalline gradient model in this embodiment is more clear and simple in steps than the traditional method, and the constructed polycrystalline gradient model has an intuitive appearance, a reasonable crystal structure and orientation, and can also optimize material properties by designing gradient distributions of different grain sizes, shapes and orientations, and achieve optimized design of microstructures, comprehensively improve material properties such as strength, toughness, fatigue life, etc., which is of great significance for the development of new high-performance materials. Moreover, after later simulations and application verifications, the model constructed by this embodiment has a reasonable structure and stable properties, and can be used for a long time to study the subsequent properties and performance of various polycrystalline material models.

[0037] Specific implementation method 2: This implementation method is different from the specific implementation method 1 in that: the lattice constant of the Fe atomic single crystal unit cell of the fcc structure in step 1 is

[0038] Specific implementation method three: The difference between this implementation method and specific implementation method one or two is that in step two, in the process of using python to generate the 3D_gradient.txt file, the size of the polycrystalline model is set to: X direction Y direction Z direction The sample is divided into 5 layers along the y direction. The number of grains in each layer is 200, 5, 1, 5, and 200, respectively, and the grain coordinate positions are randomly generated.

[0039] Specific implementation method 4: This implementation method is different from any one of specific implementation methods 1 to 3 in that: the atoms described in step 4 are Fe, Cr, Ni, Co and Cu.

[0040] Specific implementation mode 5: This implementation mode is different from any one of specific implementation modes 1 to 4 in that the atomic species in step 4 is 5.

[0041] Specific implementation method six: This implementation method is different from any one of specific implementation methods one to five in that the relative atomic masses of the atoms in step four are: 55.845 for Fe, 51.996 for Cr, 58.693 for Ni, 58.933 for Co, and 63.546 for Cu.

[0042] Specific implementation method seven: This implementation method is different from any one of specific implementation methods one to six in that: the atomic ratio of the high entropy alloy described in step five is Fe:Cr:Ni:Co:Cu=1:1:1:1:1.

[0043] Specific implementation eight: This implementation differs from any one of specific implementations one to seven in that: during the atomic replacement in step five, the atomic unit is set to metal unit, and periodic boundary conditions are used.

[0044] Specific implementation method 9: This implementation method is different from any one of specific implementation methods 1 to 8 in that the basic parameters of the alloy model described in step 5 are atom types, boundary conditions and atomic neighbor parameters.

[0045] Specific implementation method ten: This implementation method is different from any one of specific implementation methods one to nine in that: the atom type in step five is atomic, the boundary condition is psp, and the atomic neighbor parameter is 0.3bin.

[0046] Example 1

[0047] The molecular dynamics simulation method for constructing the high entropy alloy three-dimensional polycrystalline gradient model of this embodiment is carried out according to the following steps:

[0048] 1. Generate single crystal unit cell: Use Atomsk plug-in to generate Fe atomic single crystal unit cell of fcc structure, and generate Fe atomic single crystal unit cell file as Fe.xsf file;

[0049] The lattice constant of the Fe atom single crystal unit cell of the fcc structure is

[0050] 2. Create a polycrystalline node file: Use python to generate a 3D_gradient.txt file, which is a polycrystalline node file;

[0051] When using python to generate the 3D_gradient.txt file, set the size of the polycrystalline model to: X direction Y direction Z direction The sample was divided into 5 layers along the y direction, and the number of grains in each layer was 200, 5, 1, 5, and 200, respectively, and the grain coordinate positions were randomly generated;

[0052] 3. Generate polycrystalline file final.lmp: fill the Fe.xsf unit cell generated in step 1 into the 3D_gradient.txt grain to generate the final.lmp file that can be run by lammps;

[0053] The packaging and merging command is: atomsk--polycrystal Fe.xsf 3D_gradient.txt final.lmp--wrap.

[0054] 4. Modify the final.lmp file: modify the type of atoms and add the relative atomic mass of each atom;

[0055] The atoms are Fe, Cr, Ni, Co and Cu; the number of atomic species is 5, and the relative atomic mass of each atom is: 55.845 for Fe, 51.996 for Cr, 58.693 for Ni, 58.933 for Co, and 63.546 for Cu;

[0056] 5. Replace atoms to generate alloy model: In lammps software, set the basic parameters of the alloy model, read the final.lmp file, and use the atomic replacement command settype / ratio to replace Fe with Cr, Ni, Co, and Cu in turn according to the atomic ratio of the high entropy alloy; obtain the multi-component polycrystalline alloy model of the target atomic component;

[0057] The basic parameters of the alloy model are atomic type, boundary conditions and atomic neighbor parameters;

[0058] The atom type is atomic, the boundary condition is psp (the x and z directions are periodic boundary conditions, and the y direction is a contraction boundary condition), and the atomic neighbor parameter is 0.3bin;

[0059] During the atomic replacement, the atomic unit is set to metal unit, and periodic boundary conditions are used;

[0060] The atomic ratio of the high entropy alloy is Fe:Cr:Ni:Co:Cu=1:1:1:1:1;

[0061] Figure 1 The multi-component polycrystalline alloy model established in Example 1;

[0062] 6. Save the model file: Save the multi-element polycrystalline alloy model established in step 5 as a .data file;

[0063] 7. Display and coloring of polycrystalline model: Use Ovito software to read the data file in step 6 to display the multi-element polycrystalline alloy model. Finally, color the grains with different grain properties in the multi-element polycrystalline alloy model.

[0064] The grain properties include grain orientation, grain shape and grain size. Grains with different grain properties have different grain properties. Coloring grains with different grain properties in a multi-element polycrystalline alloy model can make grains with different properties appear in different colors for subsequent differentiation of polycrystalline grains. The strengthening phase generated in the material research process can be found through the difference in grains.

[0065] When displaying the multi-element polycrystalline alloy model, after using Ovito to read the .data file exported in step six, the neighboring atomic structure analysis CNA in the structure characterization is used to distinguish grains with different grain properties in the multi-element polycrystalline alloy model. Figure 2 For Figure 1 The corresponding neighbor atomic structure analysis diagram can be obtained from Figure 2 As can be seen, the crystal phase grains are green, and the amorphous phase between the grains is white; the polycrystalline model at this time is more intuitive, green represents the crystal phase grains, white represents the grain boundaries, and it can be seen that the grains have an obvious gradient distribution along the y direction.

[0066] When coloring, use the structure characterization function of Ovito, then select the colorcoding function, and then select the particle identifier in the property to be characterized Input property. At this time, the model is set to the same color. In the color range selection, select the automatic identification of the grain color range Adjustrange, so that grains with different grain properties display different colors. Figure 3 As shown, the model is colored with different colors to make the distribution of polycrystalline grains more vivid and intuitive;

[0067] In order to verify that this model can well demonstrate the interface behavior of grains and the interaction process between polycrystalline grains during mechanical tensile testing, the constructed polycrystalline gradient model was tested for mechanical tensile properties, such as Figures 4-5 As shown, as the stretching process of the polycrystalline gradient model proceeds, the grain boundaries between the polycrystalline will first expand, followed by a large number of phase changes in the grains, which often start and end at the grain boundaries. Finally, the model breaks, and cracks and fractures will first appear at the grain boundaries, indicating that the bonding strength of the model material here is relatively low. In the early stage of the tensile fracture of the material model, phase change phenomena also occur inside the model polycrystalline grains, and the phase change ends at the grain boundaries. The fracture of the model material starts at the grain boundaries, which reasonably reflects the phase change and fracture mechanism of the tensile process of the polycrystalline material. It can be seen that the polycrystalline gradient model constructed by the method of the present invention not only has simple steps and simple operation, but also has been verified through subsequent simulations and applications that the polycrystalline model constructed by the method of the present invention has a reasonable structure and stable properties, and can be used for a long time to study the subsequent properties and performance of various polycrystalline material models.

Claims

1. A molecular dynamics simulation method for constructing a three-dimensional polycrystalline gradient model of a high entropy alloy, characterized in that: The molecular dynamics simulation method for constructing a high entropy alloy three-dimensional polycrystalline gradient model is carried out in the following steps:

1. Generate single crystal unit cell: Use Atomsk plug-in to generate Fe atomic single crystal unit cell of fcc structure, and generate Fe atomic single crystal unit cell file as Fe.xsf file; 2. Create a polycrystalline node file: Use python to generate a 3D_gradient.txt file, which is a polycrystalline node file; 3. Generate polycrystalline file final.lmp: fill the Fe.xsf unit cell generated in step 1 into the 3D_gradient.txt grain to generate the final.lmp file that can be run by lammps; 4. Modify the final.lmp file: modify the type of atoms and add the relative atomic mass of each atom; 5. Replace atoms to generate alloy model: In lammps software, set the basic parameters of the alloy model, read the final.lmp file, and use the atomic replacement command settype / ratio to replace Fe with Cr, Ni, Co, and Cu in turn according to the atomic ratio of the high entropy alloy; obtain the multi-component polycrystalline alloy model of the target atomic component; 6. Save the model file: Save the multi-element polycrystalline alloy model established in step 5 as a .data file; 7. Display and coloring of polycrystalline model: Use Ovito software to read the data file in step 6 to display the multi-element polycrystalline alloy model, and finally color the grains with different grain properties in the multi-element polycrystalline alloy model. The grain properties are grain orientation, grain shape and grain size. Grains with different grain properties are grains with different grain properties. Grains with different grain properties in the multi-element polycrystalline alloy model are colored so that grains with different properties can be presented in different colors for subsequent differentiation of polycrystalline grains. Strengthening phases generated in the material research process can be found through the differences in grains. When displaying the multi-element polycrystalline alloy model, after using Ovito to read the .data file exported in step six, the neighboring atomic structure analysis CNA in the structure characterization is used to distinguish the grains with different grain properties in the multi-element polycrystalline alloy model; When coloring, use Ovito's structural characterization function, then select the colorcoding function, and then select the particleidentifier in the property to be characterized Inputproperty. At this time, the model is set to the same color, and select automatic identification of grain color range Adjustrange in the color range selection to make grains with different grain properties display different colors.

2. The molecular dynamics simulation method for constructing a high entropy alloy three-dimensional polycrystalline gradient model according to claim 1, characterized in that: The lattice constant of the Fe atom single crystal unit cell of the fcc structure in step 1 is 3. The molecular dynamics simulation method for constructing a three-dimensional polycrystalline gradient model of a high entropy alloy according to claim 1, characterized in that: Step 2: When using Python to generate the 3D_gradient.txt file, set the size of the polycrystalline model to: X direction Y direction Z direction The sample is divided into 5 layers along the y direction. The number of grains in each layer is 200, 5, 1, 5, and 200, respectively, and the grain coordinate positions are randomly generated.

4. The molecular dynamics simulation method for constructing a high entropy alloy three-dimensional polycrystalline gradient model according to claim 1, characterized in that: The atoms in step 4 are Fe, Cr, Ni, Co and Cu.

5. The molecular dynamics simulation method for constructing a high entropy alloy three-dimensional polycrystalline gradient model according to claim 1, characterized in that: The atomic species in step 4 is 5.

6. The molecular dynamics simulation method for constructing a high entropy alloy three-dimensional polycrystalline gradient model according to claim 1, characterized in that: The relative atomic masses of the atoms in step 4 are: Fe is 55.845, Cr is 51.996, Ni is 58.693, Co is 58.933, and Cu is 63.

546.

7. The molecular dynamics simulation method for constructing a high entropy alloy three-dimensional polycrystalline gradient model according to claim 1, characterized in that: In step 5, the atomic ratio of the high entropy alloy is Fe:Cr:Ni:Co:Cu=1:1:1:1:

1.

8. The molecular dynamics simulation method for constructing a high entropy alloy three-dimensional polycrystalline gradient model according to claim 1, characterized in that: During the atomic replacement described in step 5, the atomic unit is set to metal unit, and periodic boundary conditions are used.

9. The molecular dynamics simulation method for constructing a high entropy alloy three-dimensional polycrystalline gradient model according to claim 1, characterized in that: The basic parameters of the alloy model described in step 5 are atomic type, boundary conditions and atomic neighbor parameters.

10. The molecular dynamics simulation method for constructing a high entropy alloy three-dimensional polycrystalline gradient model according to claim 1, characterized in that: In step 5, the atom type is atomic, the boundary condition is psp, and the atomic neighbor parameter is 0.3bin.

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