CN111816261A - Method for constructing molecular dynamics geometric model of amplitude modulation decomposition distribution - Google Patents

Method for constructing molecular dynamics geometric model of amplitude modulation decomposition distribution Download PDF

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CN111816261A
CN111816261A CN202010667817.XA CN202010667817A CN111816261A CN 111816261 A CN111816261 A CN 111816261A CN 202010667817 A CN202010667817 A CN 202010667817A CN 111816261 A CN111816261 A CN 111816261A
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姚尧
黄琦
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Xian University of Architecture and Technology
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Abstract

The invention belongs to the technical field of material molecular dynamics, and particularly relates to a method for constructing a molecular dynamics geometric model of amplitude-modulated decomposition distribution, which comprises the following steps: step one, constructing a phase field model of system amplitude modulation decomposition based on a Cahn-Hilliard model, utilizing MATLAB to iterate the phase field model, and finally outputting target concentration data of a block in vtk format; step two, calling an vtk format file of block target concentration data based on a Python environment, and storing the vtk format file in a built-in type of a sequence in the Python, namely a dictionary form; step three, creating a data file of a molecular dynamics geometric model, establishing a corresponding relation between an atomic coordinate and a coordinate of a block in a dictionary, and setting a concentration threshold of the block; arranging the molecular dynamics geometric model data file according to the concentration threshold value of the block, and outputting a new molecular dynamics model data file; and step four, inputting the new data file of the molecular dynamics model into LAMMPS for molecular dynamics simulation. The invention can be used for molecular dynamics simulation research on the porous nano metal material.

Description

Method for constructing molecular dynamics geometric model of amplitude modulation decomposition distribution
Technical Field
The invention belongs to the technical field of material molecular dynamics, and particularly relates to a method for constructing a molecular dynamics geometric model of amplitude-modulated decomposition distribution.
Background
Molecular dynamics simulation is to use a computer to simulate the structure and behavior of atoms or molecules with the atoms or molecules as basic units, so as to obtain various physical and chemical characteristics of the atom or molecule system. The molecular dynamics simulation can realize efficient simulation of the scale of 10000 atoms on a desktop computer so as to describe the mechanical property of the atoms, and the prediction accuracy is higher.
LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator), which is a Large-scale atom-molecule Parallel Simulator, is mainly used for some calculation and simulation works related to Molecular dynamics simulation. LAMMPS can support millions of atomic molecular systems in various ensembles, including gaseous, liquid, or solid phase morphologies, and can also provide support for a variety of potential functions.
Spinodal decomposition is one of the solid-state phase transitions, spinodal decomposition is a mechanism by which solid solutions decompose into different phases with different compositions and physical properties. Unlike nucleation driven mechanisms, spinodal decomposition occurs throughout the material, not just at discrete nucleation sites. Since the nucleation reaction does not present a thermodynamic barrier, the decomposition can only be driven by diffusion processes. Due to this simplicity, the model can be used in other areas besides a wide range of applications in material science, such as image repair, multiphase fluid flow, phase separation, flow visualization, formation of quantum dots, taylor flow in microchannels, pore movement in temperature gradients, tumor growth, etc.
The existing molecular dynamics simulation of the porous material only builds one or more spherical or cubic holes in a molecular dynamics model, only can simulate the influence of porosity on the material, is far different from the microstructure of the nano porous material observed under an electron microscope, and cannot reflect the influence of a real porous structure on the performance of the nano porous material.
The method is used for simulating the micro mechanisms such as damage and fracture of the nano porous materials (such as nano silver, nano gold, nano copper and the like) under various working conditions by establishing a molecular dynamics geometric model.
Disclosure of Invention
The invention aims to provide a construction method of a molecular dynamics geometric model of amplitude modulation decomposition distribution, which is used for simulating the micro mechanism of damage and fracture of a nano porous metal material.
Based on the purpose, the invention adopts the following technical scheme: a method for constructing a molecular dynamics geometric model of an amplitude modulation decomposition distribution comprises the following steps:
step one, constructing a phase field model of system amplitude modulation decomposition based on a Cahn-Hilliard model, then iterating the initial concentration field of the block by using the phase field model to obtain a target concentration field of the block, and outputting the target concentration field in vtk format;
secondly, calling a block target concentration field based on a Python environment, establishing a relation between block coordinates and corresponding block concentrations, and storing the relation in a built-in type of a sequence in the Python, namely a dictionary form, wherein keys in the dictionary are used for storing the coordinates of the block, and elements in the dictionary are used for storing the concentrations of the corresponding block;
step three, establishing a molecular dynamics geometric model data file by taking the lattice constant of atoms in the system as a unit, establishing a corresponding relation between an atom coordinate and a coordinate of a block in a dictionary, and setting a concentration threshold of the block; arranging the molecular dynamics geometric model data file according to the concentration threshold value of the block, and outputting a new molecular dynamics model data file;
and step four, inputting the new data file of the molecular dynamics model into LAMMPS for molecular dynamics simulation.
Further, in the step one, based on a Cahn-Hilliard equation model, a phase field model of system amplitude modulation decomposition is constructed, the initial concentration field of the block is iterated by using the phase field model to obtain a target concentration field of the block, and the specific process of outputting the target concentration field in vtk format is as follows:
1.1. based on a Cahn-Hilliard model and an explicit Euler time integration scheme, a model for evolution of a block concentration field along with time is obtained, and the method specifically comprises the following steps:
according to a diffusion model Cahn-Hilliard model of a phase change theory, the following equation can be obtained:
Figure BDA0002581065100000021
wherein c is the concentration of the patch; t is time; r is the location of the block; m is mobility; f is the total free energy of the system;
based on the Cahn-Hilliard model, using an explicit Euler time integration scheme, a time evolution model of the block concentration matrix can be obtained as follows:
Figure BDA0002581065100000022
wherein,
Figure BDA0002581065100000023
the concentration of the block coordinate (i, j, k) in the nth step is shown;
Figure BDA0002581065100000024
m is the n +1 step, and the block coordinate is the concentration at (i, j, k); i is the coordinate value of the x axis, j is the coordinate value of the y axis, and k is the coordinate value of the z axis; m is mobility; Δ t is the time step;
obtained by the formula (2)
Figure BDA0002581065100000025
And
Figure BDA0002581065100000026
the numerical relation between the blocks obtains an evolution model of the block concentration along with the time;
1.2. performing iterative operation on the block concentration evolution model along with time based on MATLAB to obtain an initial concentration field
Figure BDA0002581065100000027
Target concentration field with evolution time length of m deltat
Figure BDA0002581065100000028
And outputs the phase field model result file time m.vtk in vtk format.
Further, in a time evolution model
Figure BDA0002581065100000031
The calculation process is as follows:
f(c)＝Ac2(1-c)2.....(3)；
wherein c is the concentration of the patch; f, the chemical energy of the area c; a is a potential barrier for controlling two-phase balance in the system;
Figure BDA0002581065100000032
wherein,
Figure BDA0002581065100000033
is the derivative of the f-block c,
Figure BDA0002581065100000034
representing the block concentration with the block coordinate (i, j, k) in the nth step;
Figure BDA0002581065100000035
wherein the Las operator
Figure BDA0002581065100000036
Is calculated by a five-point finite difference method,
Figure BDA0002581065100000037
in the nth step, the block coordinate is the concentration at (i, j, k), i is the coordinate value of the x axis, j is the coordinate value of the y axis, and k is the coordinate value of the z axis;
Figure BDA0002581065100000038
the nth step is carried out, the coordinate of the block is the concentration at the (i +1, j, k), and the rest are analogized in sequence;
Figure BDA0002581065100000039
the formula (6) is obtained from the formulae (3) to (5).
Furthermore, the block is a square structure consisting of a plurality of crystal lattices in the system; the coordinate value of a horizontal axis (x axis) in the block coordinates is the number of lattices in the block along the direction of the horizontal axis; the coordinate value of a longitudinal axis (y axis) in the block coordinate is the number of crystal lattices in the block along the direction of the longitudinal axis; the vertical axis (z-axis) coordinate value in the block coordinate is the number of lattices of the block in the vertical axis direction.
Further, the method for sorting the geometric model data file of molecular dynamics according to the concentration threshold of the block in the fourth step comprises the following steps: retaining atoms in the data file of the molecular dynamics geometric model, which are higher than a concentration threshold value, and deleting atoms which are lower than the concentration threshold value; the block phase above the concentration threshold is a metal phase, and the block phase below the concentration threshold is a pore phase.
The existing simple spherical or cubic hole molecular dynamics model can only reflect the influence of porosity on the physical properties of the material, such as thermal property, electrical property and the like, and is far from the actual cavity of the material.
Compared with the existing spherical or cubic hole molecular dynamics model, the molecular dynamics model structure is simulated by constructing the molecular dynamics geometric model of the amplitude-modulated decomposition distribution. The molecular dynamics model structure established by the invention is similar to the microstructure of a real nano porous material observed under an electron microscope, and can better reflect the microstructure of the material, such as the size of ligaments, the distribution of the ligaments and the like. In addition, the physical properties (especially the mechanical properties) of the porous metal material can be simulated and analyzed through the model, the influence of the porosity and the microstructure of the pores of the porous material on the tensile strength of the porous material can be simulated through molecular dynamics, and a theoretical basis is provided for the application of the porous metal material.
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FIG. 1 is a schematic flow diagram of the process of the present invention;
FIG. 2 is a block information diagram of a phase field model result vtk file according to the present invention;
FIG. 3 is a block density information diagram of the phase field model result vtk file according to the present invention;
FIG. 4 is a data file of a geometric model of molecular dynamics according to the present invention;
FIG. 5 is a visual representation of a new molecular dynamics model for metallic silver with a porosity of 50%;
FIG. 6 is a true microscopic structure view under an electron microscope of metallic silver having a porosity of 50%;
FIG. 7 is a graph of a simulation of the molecular dynamics of metallic silver at different porosities;
FIG. 8 is a surface area analysis of a geometric model of molecular dynamics consistent with an AM decomposition profile.
Detailed Description
Example 1
A method for constructing a molecular dynamics geometric model of am decomposition distribution, as shown in fig. 1, comprising the following steps:
step one, constructing a system amplitude modulation decomposition phase field model based on a Cahn-Hilliard model, namely a block concentration evolution model along with time, and comprising the following steps of:
1.1 supposing to establish a phase field model with length, width and height of 60 lattice numbers, establishing a matrix of 60 x 60
Figure BDA0002581065100000041
Figure BDA0002581065100000042
Is an initial concentration field; each element in the matrix is the density of the block; the concentration range of the block is 0-1, and when the concentration of the block is 0 and 1, the block is two different phases.
The density of each block of the initial density field is as follows:
Figure BDA0002581065100000043
1.2 calculating Laplacian of current step and current block by using five-point finite difference method
Figure BDA0002581065100000044
The calculation formula is as follows:
Figure BDA0002581065100000045
wherein,
Figure BDA0002581065100000046
is the concentration at the n step and the block coordinate is (i, j, k), i is the coordinate value of x axis, j isy-axis coordinate value, and k is z-axis coordinate value.
1.3 the formula for the chemical energy f (c) of the phase field model is as follows:
f(c)＝Ac2(1-c)2.....(3)；
wherein c is the concentration of the patch; f, the chemical energy of the area c; a is the potential barrier for controlling the two-phase balance in the system.
Derivation of chemical energy of phase field model according to equation (3)
Figure BDA0002581065100000047
The formula is found as follows:
Figure BDA0002581065100000048
1.4 diffusion model of phase transition theory Cahn-Hilliard equation:
Figure BDA0002581065100000051
wherein, ciIs the concentration of the patch; t is time; r is the location of the block; m is mobility; f is the total free energy of the system;
the time evolution of the block concentration matrix can be obtained using an explicit Euler time integration scheme, and the time evolution formula of the concentration matrix is as follows:
Figure BDA0002581065100000052
wherein M is mobility, and M takes the value of 1; delta t is a time step length, and a delta t set value is 0.01;
in formula (2)
Figure BDA0002581065100000053
The following formula is used to solve the problem:
Figure BDA0002581065100000054
in formula (6)
Figure BDA0002581065100000055
The values are obtained by the equations (4) and (5), respectively.
Obtaining the concentration field of the current step according to the formula (6)
Figure BDA0002581065100000056
And the concentration field of the next step
Figure BDA0002581065100000057
The mathematical relationship between the concentration fields can update the concentration field of the next step, namely a model of the evolution of the block concentration along with the time through the concentration field of the current step.
And step two, iterating the phase field model by using MATLAB, and finally outputting target concentration data of the block in an vtk format, wherein the specific process is as follows: performing iterative operation on the block concentration evolution model along with time for 10000 times based on MATLAB to obtain an initial concentration field
Figure BDA0002581065100000058
Target concentration field with evolution time length of 100 (i.e. 10000 Δ t)
Figure BDA0002581065100000059
And outputs the phase field model result file time _10000.vtk in vtk format.
Calling an vtk format file of block target concentration data based on a Python environment, and storing the vtk format file in a dictionary form which is a built-in type of a sequence in the Python to obtain a molecular dynamics geometric model data file; the specific process is as follows:
3.1 building a Python environment, and importing the time _10000.vtk file in the step two by using Python, wherein the time _10000.vtk file is shown in FIG. 2. And defining the whole reading and integrating function by using a def function, thereby repeatedly calling the time _10000.vtk file.
3.2 deleting the model information of the 1 st to 6 th lines and the 216006(60 multiplied by 60+6) th to 216009(60 multiplied by 60+9) th lines in the time _10000.vtk file, artificially deleting part of the model information to simulate a cavity structure, establishing the relation between the block and the state value, and recording the block and the state value in a dictionary form which is a built-in type of the sequence in Python. The dictionary is a variable container model in Python, and is a collection of elements, each element has a field called a key, the keys of different elements are different, and the elements and the corresponding key-value pairs are bonded. Elements in the dictionary are used for storing block state values of the phase field model, keys in the dictionary are used for storing block coordinates of the phase field model, and the block coordinates correspond to the block state values.
3.3 after deleting the time _10000.vtk file part line, the obtained time _10000.vtk file has 432000(2 × 60 × 60 × 60) line in total, as shown in fig. 3, the last 216000(60 × 60 × 60) line in the time _10000.vtk file is recorded as an element of the dictionary, which represents the state value of each block of the phase field model. The front 216000 lines correspond to the rear 216000 lines one by one, and are keys of a dictionary, and the keys represent coordinates of each block of the phase field model; each row in the front 216000 is divided into three elements by a space, namely an x coordinate, a y coordinate and a z coordinate of the block, and the three values of the x coordinate, the y coordinate and the z coordinate are combined into a tuple and recorded by a dictionary, wherein the tuple is also a container model in Python.
Step four, setting a density threshold of the block; arranging the molecular dynamics geometric model data file according to the concentration threshold value of the block, and outputting a new molecular dynamics model data file; the specific process is as follows:
4.1 take silver metal with a porosity of 50% as an example, create a data file with no holes and a length, width and height of 60 lattices, since silver of one lattice has four silver atoms, 216000(60 × 60 × 60) lattices have a geometrical model of molecular dynamics of 864000 atoms, and silver metal with a porosity of 50% has about 432000 atoms. The first 9 rows of a typical data file are header information of the data file, and 432003 rows after the 10 th row are coordinate information of atoms, where one row of information, two empty rows, and 432000 atoms are each one row. Each row is partitioned by a space into an atom ID (1-432000), an atom type ID (1 if there is only one atom in the model, and so on), the x, y, and z coordinates of the atom.
The next 432003 rows are the speed information of the atoms, where one row of information, two empty rows, 432000 atoms one row per atom. Each line is divided into an atom ID (1-432000), an x-direction speed, a y-direction speed and a z-direction speed of the atom (the speed is the original data file speed, and is suggested to be zero) through a blank space.
A molecular dynamics geometric model data file obtained by using metallic silver with a porosity of 50% is shown in fig. 4, the data file is in a molecular dynamics model file format used by LAMMPS, and the created data file is read in by the LAMMPS to perform molecular dynamics simulation.
The atomic coordinates in the data file are represented by lattice numbers like the block coordinates, and are also separated into three elements through spaces, namely x coordinates, y coordinates and z coordinates of atoms. And (3) rounding the coordinates of the atoms with the lattice number as a unit to obtain three elements consisting of integers ranging from 0 to 60, wherein the x coordinate, the y coordinate and the z coordinate form an element ancestor, the type of the element ancestor is the same as that of the block coordinate information obtained in the step 3.3, and the corresponding relation between each atom in the data file and the block is established through indexing.
4.2 setting a block concentration threshold value, wherein the blocks with the block concentration exceeding the threshold value are defined as solid, the blocks with the block concentration lower than the threshold value are defined as holes, atoms in the hole blocks are deleted, the rest atoms are reserved, and the reserved atoms form an atomic structure conforming to the amplitude modulation decomposition distribution, namely a molecular dynamics geometric model. The size of the block concentration threshold is closely related to the porosity, and the higher the porosity is, the higher the set block concentration threshold is; the block concentration threshold is determined by the results of the phase field model, and repeated attempts are required to finalize the determination.
The specific process of constructing an atomic structure conforming to an AM decomposition profile is as follows:
traversing each atom in the molecular dynamics geometric model data file obtained by the metal silver with the porosity of 50%, indexing coordinates of each atom after 4.1 processing in the dictionary created in the step 3.3, returning a state value of the atom, and comparing the state value with a threshold value. Atoms smaller than the threshold value are deleted, and the deleted atoms are not written into a new data file; and reserving atoms larger than the threshold value, and writing the atoms into a new data file. And recording the number of the reserved atoms in the traversal process.
And secondly, creating a new data file for writing the atomic information. First, header file information required by LAMMPS in the data file, i.e., description of the data file, the number of atoms (i.e., the number of atoms recorded in 4.3), the kind of atoms, and minimum and maximum values of x, y, and z coordinates in the phase-field model. Except that the number of atoms needs to be changed, other information is consistent with the data file before modification.
And fifthly, inputting the new data file of the molecular dynamics model into LAMMPS for molecular dynamics simulation.
The visual image of the new molecular dynamics model of the metallic silver with the porosity of 50 percent is shown in figure 5, the microstructure of the metallic silver with the porosity of 50 percent under an electron microscope is shown in figure 6, the structure of the molecular dynamics model established by the invention is similar to the microstructure of a real nano porous material observed under the electron microscope, and the molecular dynamics model established by the invention can more visually represent the microstructure of the metallic material.
Inputting a data file of a molecular dynamics model of metallic silver with the porosity of 50% into LAMMPS for molecular dynamics tensile simulation, and obtaining a strain stress diagram of the silver which conforms to amplitude modulation decomposition distribution, as shown in FIG. 7, wherein rho represents the porosity, as can be seen from FIG. 7, when the stress reaches a maximum value of 0.4GPa when the strain is 0.05, and the stress-strain curve presents obvious ductile fracture characteristics.
Example 2
Referring to the method for constructing the molecular dynamics geometric model of the spinodal decomposition distribution in example 1, the data files of the molecular dynamics geometric model conforming to the spinodal decomposition distribution are constructed for the metallic silver with the porosity of 10%, 20% and 40%, respectively, and are input into LAMMPS for molecular dynamics tensile simulation, and as a result, as shown in fig. 7, ρ in fig. 7 represents the porosity, and as the porosity increases, the tensile ultimate strength of the material decreases greatly. And it can be observed that the low porosity model exhibits brittle fracture characteristics, while the high porosity model exhibits ductile fracture. Further dislocation analysis of the model shows that the model with low porosity is broken directly after the appearance of the immobile dislocation (Hirth dislocation and ladder bar dislocation), while the model with high porosity enters a hardening stage after the appearance of the immobile dislocation, and the stress is gradually reduced after a large amount of dislocations are accumulated.
Surface area analysis is carried out on the molecular dynamics geometric model which accords with amplitude modulation decomposition distribution, and the result is shown in figure 8, and the surface area-volume ratio of the brittle fracture model is greatly lower than that of the ductile fracture model, so that the inference that high porosity brings more surfaces, so that dislocation has sufficient surface to slide, and the influence of immobile dislocation on dislocation accumulation is reduced; while the low porosity model, after the creation of the immobile dislocations, the dislocations accumulate rapidly leading to material fracture.
For the metal silver conforming to the molecular dynamics geometric model of the amplitude-modulated decomposition distribution, the influence of the porosity and the microstructure of the holes on the tensile strength of the porous silver material is simulated through molecular dynamics, the mechanism of brittle-tough conversion of the porous silver material caused by dislocation evolution is clarified, and a theoretical basis is laid for the application of the nano porous silver material.

Claims (5)

1. A method for constructing a molecular dynamics geometric model of an AM decomposition distribution is characterized by comprising the following steps:
step one, constructing a phase field model of system amplitude modulation decomposition based on a Cahn-Hilliard model, then iterating the initial concentration field of the block by using the phase field model to obtain a target concentration field of the block, and outputting the target concentration field in vtk format;
secondly, calling a block target concentration field based on a Python environment, establishing a relation between block coordinates and corresponding block concentrations, and storing the relation in a built-in type of a sequence in the Python, namely a dictionary form, wherein keys in the dictionary are used for storing the coordinates of the block, and elements in the dictionary are used for storing the concentrations of the corresponding block;
step three, establishing a molecular dynamics geometric model data file by taking the lattice constant of atoms in the system as a unit, establishing a corresponding relation between an atom coordinate and a coordinate of a block in a dictionary, and setting a concentration threshold of the block; arranging the molecular dynamics geometric model data file according to the concentration threshold value of the block, and outputting a new molecular dynamics model data file;
and step four, inputting the new data file of the molecular dynamics model into LAMMPS for molecular dynamics simulation.
2. The method for constructing an AM decomposition distributed molecular dynamics geometric model according to claim 1, wherein the first step is to construct a phase field model of the system AM decomposition based on a Cahn-Hilliard model, iterate the initial concentration field of the block by using the phase field model to obtain the target concentration field of the block, and output the target concentration field in vtk format by the specific process as follows:
1.1. based on a Cahn-Hilliard model and an explicit Euler time integration scheme, a model for evolution of a block concentration field along with time is obtained, and the method specifically comprises the following steps:
according to a diffusion model Cahn-Hilliard model of a phase change theory, the following equation can be obtained:
Figure FDA0002581065090000011
wherein c is the concentration of the patch; t is time; r is the location of the block; m is mobility; f is the total free energy of the system;
based on the Cahn-Hilliard model, using an explicit Euler time integration scheme, a time evolution model of the block concentration matrix can be obtained as follows:
Figure FDA0002581065090000012
wherein,
Figure FDA0002581065090000013
the concentration of the block coordinate (i, j, k) in the nth step is shown;
Figure FDA0002581065090000014
m is the n +1 step, and the block coordinate is the concentration at (i, j, k); i is the coordinate value of the x axis, j is the coordinate value of the y axis, and k is the coordinate value of the z axis; m is mobility; Δ t is the time step;
obtained by the formula (2)
Figure FDA0002581065090000015
And
Figure FDA0002581065090000016
the numerical relation between the blocks obtains an evolution model of the block concentration along with the time;
1.2. performing iterative operation on the block concentration evolution model along with time based on MATLAB to obtain an initial concentration field
Figure FDA0002581065090000017
Target concentration field with evolution time length of m deltat
Figure FDA0002581065090000021
And outputs the phase field model result file time m.vtk in vtk format.
3. The method of claim 2, wherein the time evolution model is a geometric model of the molecular dynamics of the AM decomposition profile
Figure FDA0002581065090000022
The calculation process is as follows:
f(c)＝Ac2(1-c)2.....(3)；
wherein c is the concentration of the patch; f (c) is chemical energy; a is a potential barrier for controlling two-phase balance in the system;
Figure FDA0002581065090000023
wherein,
Figure FDA0002581065090000024
is the derivative of (f) and (c),
Figure FDA0002581065090000025
representing the block concentration with the block coordinate (i, j, k) in the nth step;
Figure FDA0002581065090000026
wherein the Las operator
Figure FDA0002581065090000027
Is calculated by a five-point finite difference method,
Figure FDA0002581065090000028
in the nth step, the block coordinate is the concentration at (i, j, k), i is the coordinate value of the x axis, j is the coordinate value of the y axis, and k is the coordinate value of the z axis;
Figure FDA0002581065090000029
the nth step is carried out, the coordinate of the block is the concentration at the (i +1, j, k), and the rest are analogized in sequence;
Figure FDA00025810650900000210
determined by the formulae (3) to (5).
4. The method of claim 3, wherein the blocks are square structures composed of a plurality of lattices in a system; the coordinate value of a horizontal axis in the block coordinates is the number of lattices in the block along the direction of the horizontal axis; the coordinate value of a longitudinal axis in the block coordinate is the number of lattices in the block along the direction of the longitudinal axis; and the vertical axis coordinate value in the block coordinate is the number of the lattices of the block along the vertical axis direction.
5. The method for constructing the molecular dynamics geometric model of AM decomposition distribution according to claim 4, wherein the method for organizing the data file of the molecular dynamics geometric model according to the density threshold of the blocks in the third step is as follows: retaining atoms in the data file of the molecular dynamics geometric model, which are higher than a concentration threshold value, and deleting atoms which are lower than the concentration threshold value; the block phase above the concentration threshold is a metal phase, and the block phase below the concentration threshold is a pore phase.
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