A method for modeling and optimizing thermal conductance of a polymer material series-parallel semi-crystalline model

Abstract

The application provides a modeling and thermal conductivity optimization method of a polymer material series-parallel half-crystal model. The method does not need to go through a complicated model conformation process, can better represent the related physical properties of the half-crystal polymer compared with a simple two-phase or three-phase series model, is simple to handle, has wide process applicability, and meets the model design requirements of various types of half-crystal polymers. Meanwhile, a processing method for further improving the thermal conductivity of the half-crystal polymer model by using an electric field is provided. Compared with directly applying an external force to cause the polymer to produce strain and then improve the thermal conductivity, the method can better obtain a polymer material with excellent thermal conductivity performance on the premise of ensuring the mechanical properties of the material. The application constructs a polymer model at a microscale, reduces experimental costs, fully utilizes the method of molecular dynamics to explore the influencing factors of the thermal conductivity of the polymer material, and improves the theoretical mechanism for preparing a high-performance heat spreader.

Description

Technical Field

[0001] The present invention belongs to the technical field of computer simulation of polymer materials, and in particular relates to a modeling method and a thermal conductivity optimization method of a series-parallel semi-crystalline model of polymer materials. Background Art

[0002] With the rapid development of aerospace technology, the electronic components of its equipment are becoming increasingly integrated and miniaturized. With the rapid increase in circuit density and load, and the reduction in geometric dimensions, heat dissipation within structures becomes increasingly difficult. This leads to significant heat accumulation, severely impacting the performance and stability of equipment. The electronics industry's "10°C Rule" states that for every 10°C increase in operating temperature, the failure rate of electronic devices increases by an order of magnitude. Statistics show that poor heat dissipation accounts for 55% of electronic product failures, placing even stricter demands on the thermal conductivity of thermal management materials. Heat generated by integrated circuits in electronic components is first transferred to the thermal interface material, then through the electronic packaging material, external thermal interface material, and high-thermal conductivity materials. Heat is then dissipated to the ambient environment through a heat sink via passive or active heat dissipation. The primary heat dissipation path can be understood as transfer within the well-insulated thermal interface material. Therefore, improving the thermal conductivity of thermal interface materials is crucial to addressing the significant challenges facing high-performance chip thermal management systems.

[0003] In today's field of materials science, polymer materials have attracted widespread attention due to their unique physical and chemical properties (insulation, high toughness, low density, low price, good corrosion resistance, etc.). Their thermal conductivity is a key material property and is of great significance for many applications, especially when a balance is required between thermal conductivity and insulation. However, due to the low inherent thermal conductivity of polymer materials, which is approximately 0.1 to 0.5 W / (m·K) at room temperature, the application of polymers in electronic equipment heat dissipation is severely limited. In addition, the low contact thermal conductivity between polymer-based thermal interface materials and metal heterogeneous interfaces further restricts their application. Therefore, it is necessary to explore the thermal conductivity mechanism of polymer-based thermal interface materials and provide a microscopic theoretical mechanism for the preparation of high thermal conductivity polymer thermal interface materials.

[0004] To fully explore the influencing mechanisms of thermal conductivity in polymer-based materials, Asegun Henry et al., in their paper "Anomalous heat conduction in polyethylene chains: Theory and molecular dynamics simulations" published in the journal Physical Review B, studied the thermal conductivity of a single polyethylene chain and found that the thermal conductivity of a single polyethylene chain along the chain direction was exceptionally high—300 W / (m·K), far exceeding the intrinsic thermal conductivity of the polymer bulk. However, the theoretical and simulation methods only explored ideal single polymer chains, and did not delve deeper into the factors affecting the thermal conductivity of the polymer bulk. In their paper "Tuning the thermal conductivity of polymers with mechanical strains" published in the journal Physical Review B, Jun Liu et al. studied the effect of strain on the thermal conductivity of bulk amorphous polyethylene and found that the thermal conductivity increased fivefold with the orderly arrangement of some molecular chains within the polymer bulk. However, directly applying strain would severely affect the mechanical properties of the polymer material. In addition, Jixiong He et al. published a paper titled "Molecular dynamics simulation of thermal transport in semicrystalline polyethylene: Roles of strain and the crystalline amorphous interphase region" in the Journal of Applied Physics. They used molecular dynamics simulation to explore the effect of interchain coupling between the crystalline and amorphous regions of an ideal series semicrystalline polyethylene model on thermal conductivity, and found that the topological structure of the interlayer chains determines the dependence of thermal conductivity on strain. These studies used molecular dynamics simulation to explore some of the mechanisms that influence the thermal conductivity of polymer materials at the microscale. In addition, there is a state of local crystallization in polymers, but the current research on semicrystalline polymer models is still limited to two-phase or three-phase series models. Polymer models that have both series and parallel characteristics still need to be further explored.

[0005] Ferroelectric polymer - polyvinylidene fluoride (PVDF) is a thermoplastic polymer composed of -CH2CF2- repeating units. This simple chemical structure gives its molecular chain a high degree of flexibility. Under different conditions, PVDF can present different molecular chain conformations and crystal structures. In addition, due to the presence of CF2 groups, its molecular chain is sensitive to electric fields. When the applied electric field strength is greater than the coercive electric field, the molecular chain segments will change, such as Figure 1-2 As shown in the figure, it compresses in the direction of the electric field and expands in the direction perpendicular to the electric field, which has an electrostrictive effect. Based on this, we can obtain PVDF with stretched molecular chains by controlling the coupling effect of the electric field. Compared with other traditional polymers, PVDF has advantages such as high temperature resistance, aging resistance, good insulation, and high crystallinity. Therefore, it is an ideal thermal interface material matrix. Therefore, it is necessary to explore the influencing factors of thermal interface materials with PVDF as the polymer matrix to improve the theoretical mechanism for the preparation of high-performance heat sinks.

[0006] The research on high thermal conductivity polymer-based thermal interface materials and the factors affecting the thermal conductivity between them and metals is of great strategic significance for achieving global energy conservation and emission reduction, improving energy utilization efficiency and solving electronic thermal packaging problems. Summary of the Invention

[0007] The purpose of the present invention is to avoid the shortcomings of the prior art and provide a modeling and thermal conductivity optimization method for a series-parallel semi-crystalline model of a polymer material.

[0008] To achieve the above object, the technical solution adopted by the present invention is: a modeling and thermal conductivity optimization method for a series-parallel semi-crystalline model of a polymer material, characterized by comprising the following steps:

[0009] Step 1: First, establish a fully crystalline polymer model of corresponding size according to the type of polymer required;

[0010] Step 2: According to the simulation requirements, the central crystalline region is selected as the 'permanent crystalline region' and the rest of the region as the 'temporary crystalline region'. The covalent bonds between the atoms in the 'permanent crystalline region' and the 'temporary crystalline region' are then broken.

[0011] Step 3: Name the main chain atom at the end of the molecular chain in the 'permanent crystalline region' R1, and the main chain atom at the end of the molecular chain in the 'temporary crystalline region' R2. Then, randomly form covalent bonds between R1 and R2 atoms according to simulation requirements to obtain Model I with different interchain couplings.

[0012] Step 4: Using the open source software Lammps as the simulation software, molecular dynamics simulation is performed on Model I to obtain a semi-crystalline polymer model that conforms to the series morphology in the X, Y, and Z directions, which is called the series-parallel semi-crystalline polymer model IV;

[0013] Step 5: Using Model IV as the initial model, we investigated the effect of applying equal-strength electric fields in the X and Y directions on the morphology of the series-parallel semicrystalline polymers. We also used nonequilibrium molecular dynamics (NEMD) to perform heat transfer analysis, obtaining curves of temperature variation with position in each layer and heat flux variation with time.

[0014] Step 6: Use Python software to perform linear fitting on the temperature change curve of each layer position and the heat flow change curve over time to obtain the temperature gradient value and the rate of change of heat flow over time. Calculate the thermal conductivity of the material according to Fourier's law, and obtain the effect of changes in electric field intensity on the thermal conductivity of polymer materials.

[0015] Furthermore, the 'permanent crystalline region' in step 2 is completely surrounded by the 'temporary crystalline region' to ensure that amorphous polymer chains exist at the ends of the crystalline region in the interchain direction or along the chain direction during the subsequent simulation of local melting.

[0016] In step 3, a model I with different interchain couplings is obtained. The interchain coupling in model I is set according to the simulation requirements. Specifically, the interchain coupling is determined based on the bond length of the end atoms. Connections with distances exceeding the bond length are not made to prevent unreasonable structure of model I.

[0017] In step 4, the open source software Lammps is used as the simulation software to perform molecular dynamics simulation on Model I according to the following sub-steps:

[0018] (1) Based on the predicted size of the deformed polymer according to Model I, a simulation box is created and the corresponding size is set so that all the model atoms are located inside the box, thereby obtaining Model II;

[0019] (2) Visualize the model using ovito software, render model II in different colors according to the molecular chain number, and then observe whether the division of the polymer molecular chain is correct or not, and correct the molecular chain with incorrect division, so that the molecular number of the permanent crystalline region can be correctly extracted in the later stage, or the atomic number can be further determined by determining the z coordinate after the molecular number is determined;

[0020] (3) Record the molecular chain numbers of the ‘permanent crystalline region’ where there is no interchain coupling between the molecular chains of the ‘permanent crystalline region’ and the ‘temporary crystalline region’; further determine the atomic numbers of the ‘permanent crystalline region’ where there is interchain coupling between the molecular chains of the ‘permanent crystalline region’ and the ‘temporary crystalline region’ by coordinate position;

[0021] (4) Setting the potential function that describes the interaction between atoms in Model II and setting the initial simulation conditions and parameters, where the temperature must be higher than the melting point of the crystalline polymer;

[0022] (5) For the potential function, if the long-range Coulomb force interaction is considered, in order to avoid errors when obtaining the initial series-parallel semi-crystalline polymer model, the setting of the long-range Coulomb force interaction is first canceled, and initially only the spatial position distribution of the molecular chain is considered for model II;

[0023] (6) After setting the boundary conditions in the X, Y, and Z directions to non-periodic boundary (f) conditions, reflective walls are set on each side of the simulation box to prevent the polymer atoms from moving outside the simulation box during the local melting of Model II, causing simulation errors. The atoms in the 'permanent crystalline region' are divided into the same crystalline group according to the atomic number in sub-step (3) of step 4, and the force and velocity of the atoms in the crystalline group are set to 0, forming a fixed crystalline region.

[0024] (7) Model II was locally melted using the canonical ensemble (NVT). When the temporary crystalline region was melted at high temperature, the permanent crystalline region was fixed by simulation commands. After 1-2 ns, Model III was obtained. At this time, the permanent crystalline region still maintained the crystalline conformation, while the temporary crystalline region had transformed into an amorphous state.

[0025] (8) Use Model III as the model file, set the long-range Coulomb force interaction in the potential function, change the boundary conditions in the X, Y, and Z directions to periodic boundary (p) conditions, cancel the reflection wall set in sub-step (6) of step 4, cancel the fixed 'permanent crystalline zone' setting in sub-step (7) of step 4, and set the simulation temperature below the melting point of the crystalline polymer to avoid structural damage in the subsequent crystalline zone;

[0026] (9) Model III is relaxed under an isothermal and isobaric ensemble (NPT). After 1-2 ns, a semi-crystalline polymer model with a series morphology in the X, Y, and Z directions is obtained, which is called the series-parallel semi-crystalline polymer model IV.

[0027] In sub-step (1) of step 4, symmetrically distributed vacuum layers are added to the model box to prevent more amorphous chains from concentrating on one side.

[0028] In sub-step (2) of step 4, the polymer molecular chain is observed as follows: open the Model II file in text format, observe the second column of data under "Atoms", and judge whether the molecular number division is correct based on the total number of molecules that meet the model.

[0029] In sub-step (4) of step 4, the initial simulation conditions and parameters include model size, atom type, unit system, boundary conditions, neighbor list radius, time step, pressure, and temperature; the melting point of the crystalline polymer is determined according to literature or by using Lammps to simulate the polymer heating process.

[0030] Sub-step (8) of step 4 also includes: if the polymer chains are distributed in the simulation box, then proceed directly to the next simulation; if the polymer chain clusters in the simulation box are around the 'permanent crystalline region' and there is a large vacuum layer, then reduce the range of the vacuum layer in the model file to prevent errors due to exceeding the range of long-range Coulomb force interactions during relaxation under the isothermal and isobaric ensemble (NPT).

[0031] In step 5, when investigating the effect of simultaneously applying equal-strength electric fields in the X and Y directions on the morphology of series-parallel semi-crystalline polymers, the applied electric field strength does not exceed the breakdown electric field strength value of the polymer; the simulation temperature is set above the melting temperature of the amorphous polymer and below the melting point of the crystalline polymer; after applying the electric field, the model is cooled to room temperature, and the effect of applying electric fields of different intensities on the thermal conductivity of the model is measured.

[0032] In step 5, the non-equilibrium molecular dynamics method is specifically as follows: the model is evenly divided into N layers along the heat conduction direction, the temperature gradient of each layer under stable heat flow is counted and output, and the thermal conductivity is calculated using Fourier's law, where N depends on the model length and N ≥ 8.

[0033] The beneficial effects of the present invention are:

[0034] 1. This invention, based on molecular dynamics simulation, proposes a new and more rational approach to modeling semicrystalline polymers, namely, a series-parallel semicrystalline polymer modeling method. This method eliminates the need for complex model conformation processing, simplifies the process, and offers broad applicability, meeting the design requirements for various semicrystalline polymer models.

[0035] 2. The series-parallel polymer simulation unit proposed for the first time in this invention can better characterize the relevant physical properties of semi-crystalline polymers compared with simple two-phase or three-phase series models, and provides a new idea for subsequent exploration of the influencing mechanism of the physical properties of polymers and their composites based on molecular dynamics methods at the microscale.

[0036] This invention proposes, for the first time, a method for enhancing the thermal conductivity of semicrystalline polymer models using electric fields. Compared to directly applying external forces to induce strain in the polymer and thereby enhance thermal conductivity, this method can better achieve polymer materials with excellent thermal conductivity while maintaining material mechanical properties. By constructing microscopic polymer models, this method reduces experimental costs and fully utilizes molecular dynamics methods to explore the factors influencing the thermal conductivity of polymer materials, providing theoretical insights into the mechanisms for the preparation of high-performance heat sinks. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a flow chart of the present invention;

[0038] Figure 2The model diagram of β-type pure crystalline PVDF in the embodiment of the invention, wherein (a) is the β-type unit cell of PVDF, and (b) is the model diagram after the cell is expanded;

[0039] Figure 3 This is a diagram of Model I in an embodiment of the invention. The green portion in the middle is the 'permanent crystalline region', and the remaining portion is the 'temporary crystalline region';

[0040] Figure 4 Rendering color images of Model II in an embodiment of the present invention, where (a) is a model image with an incorrect molecular number, (b) is a model image after the molecular number is corrected, and (c) is a cross-sectional view of the model after the molecular number is corrected;

[0041] Figure 5 The model diagrams of the "temporary crystalline region" after melting according to an embodiment of the present invention are shown, wherein (a) is the model diagram after direct melting, (b) is the cross-sectional diagram of the model after melting, and (c) is the model diagram after adjusting the size of the vacuum layer;

[0042] Figure 6 Graph showing the change of total energy of the system according to the embodiment of the present invention with relaxation time;

[0043] Figure 7 This is a schematic diagram of the morphological changes of the model after applying an electric field according to an embodiment of the present invention;

[0044] Figure 8 This is a cross-sectional view of the model after applying electric fields of different intensities for 2 ns according to an embodiment of the present invention;

[0045] Figure 9 This is a block diagram of the equilibrium molecular dynamics (NEMD) method according to a non-embodiment of the present invention;

[0046] Figure 10 The electric field strength of the embodiment of the present invention is Time-varying heat flow diagram of the series-parallel semi-crystalline PVDF polymer model cold and hot sources;

[0047] Figure 11 The electric field strength of the embodiment of the present invention is Axial temperature gradient diagram of series-parallel semi-crystalline PVDF polymer model;

[0048] Figure 12 This is a graph showing the variation of thermal conductivity of series-parallel semi-crystalline PVDF polymers with applied electric field strength according to an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The principles and features of the present invention are described below with reference to the accompanying drawings. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0050] Example 1:

[0051] Take the β-type crystalline polymer of polyvinylidene fluoride (PVDF) as an example.

[0052] A modeling method and thermal conductivity optimization method for a series-parallel semi-crystalline model of a polymer material, comprising the following steps:

[0053] Step 1: Establish a β-type crystalline polymer model of polyvinylidene fluoride (PVDF):

[0054] The lattice parameters of its unit cell are The space group is Cm2m, and one unit cell contains two PVDF monomers (-CH2-CF2-), each containing 4 C, H, and F atoms, such as Figure 2 (a); then expand the cell by 4, 5, and 50 in the X, Y, and Z directions respectively to obtain a crystalline polymer model, remove the periodicity, and add hydrogen atoms to the end C atoms of each main chain to obtain a pure crystalline polymer model, as shown in Figure 2 (b)

[0055] Step 2: Based on the crystalline mass fraction, some atoms in the center are selected as the 'permanent crystalline region'. Then, all the end atoms of the 'permanent crystalline region' and the 'temporary crystalline region' are broken. Twelve molecular chains in the center are selected as the 'permanent crystalline region', where each molecular chain contains 26 PVDF monomers.

[0056] Step 3: Name the main chain atom at the end of the molecular chain of the 'permanent crystalline region' R1, and name the main chain atom at the end of the molecular chain of the 'temporary crystalline region' R2. Then, according to the simulation requirements, all R1 and R2 atoms are connected to form a bridge link to obtain Model I, as shown in the following example: Figure 3 As shown;

[0057] Step 4: Use the open source software Lammps as the simulation software and perform molecular dynamics simulations on Model I according to the following sub-steps:

[0058] (1) If model I is initially periodic, in order to avoid the disorder of bond distribution caused by directly setting the vacuum layer, the 'Unwrap trajectories' function in the visualization software ovito can be used to display the unfolded coordinates of each atom and then re-export it as a Lammps model file. Then, the size of the polymer simulation box after deformation is predicted based on model I and the corresponding size of the simulation box is adjusted so that all the model atoms are located inside the box, thus obtaining model II.

[0059] (2) Visualize the model using Ovito software. Render the color of Model II according to the molecular chain serial number, then observe whether the division of polymer molecular chains is correct, and correct the wrongly divided molecular chains, so as to correctly extract the molecular serial numbers in the permanent crystalline region or determine the molecular serial numbers and further determine the atomic serial numbers by judging the z coordinate in the later stage; in this example, the initial molecular serial numbers are arranged wrongly, as shown in Figure 4 (a). In this figure, the color distribution of the same molecular chain is inconsistent. Therefore, the correct model is obtained after correction through relevant codes, as shown in Figure 4 (b);

[0060] (3) Draw the Figure 4 central sectional view of (b), as shown in Figure 4 (c). It can be seen that the 'permanent crystalline region' is distributed in the middle area of the molecular chains in the central blue part, which is marked with a black dotted line in the figure. However, in this model, since some atoms in the 'permanent crystalline region' and the 'temporary crystalline region' are on the same molecular chain, the 'permanent crystalline region' cannot be directly grouped by the molecular chain serial number (in this example, the molecular serial numbers where the atoms in the crystalline region are located are 11 - 14, 19 - 22, 27 - 30). Therefore, first extract all the atoms on the molecular chains where the 'permanent crystalline region' is located, and then determine and record the atomic serial numbers of the 'permanent crystalline region' according to the coordinate values of the atoms in the Z direction (37.5 < z < 90.19);

[0061] (4) Here, the PCFF potential function is selected to describe the interaction between atoms in Model II. Set the atomic type to the full form, the simulation unit to real, the neighbor list to 2.0 bin, the time step to 0.5 fs, the pressure to 0 atm, and then set the simulation temperature to 800 K. This value is obtained by directly heating and melting the model shown in Figure 2 using Lammps;

[0062] (5) The "pair_style" potential in the PCFF force field is "lj / class2 / coul / long", where 'long' represents considering the long-range Coulomb interaction. Therefore, it is necessary to set "kspace_style pppm 1.0e-6". However, to avoid the error of "exceeding the Coulomb interaction", initially only consider the spatial distribution of atoms in Model II, that is, change 'long' to 'cut' and cancel the setting of "kspace_style pppm 1.0e-6";

[0063] (6) After the boundary conditions in the X, Y, and Z directions are all set to non-periodic boundary (f) conditions, in order to prevent the polymer atoms from moving outside the simulation box during the local melting of Model II and causing simulation errors, reflection walls are set on all sides of the simulation box. Then, the atoms in the 'permanent crystalline region' are divided into the same crystalline group according to the atomic number in step (3);

[0064] (7) Use the command “velocity crystal set 0 0 0, fix crystal setforce 0 0 0” to fix the “permanent crystalline region”, perform local melting simulation on model II under the canonical ensemble (NVT), and obtain model III after relaxation for 1 ns, as shown in Figure 5 (a) and draw a cross-sectional diagram, as shown in Figure 5 As shown in (b), at this time, the 'permanent crystalline region' in the model still maintains a crystalline conformation, while the 'temporary crystalline region' has transformed into an amorphous state;

[0065] (8) After resetting the long-range Coulomb force interaction in the potential function, change the boundary conditions in the X, Y, and Z directions to periodic boundary (p) conditions, cancel the reflection wall set in sub-step (6) of step (4), cancel the fixed setting of the 'permanent crystalline region' in sub-step (7) of step (4), set the simulation temperature to 300K; and observe Figure 5 (a) It is found that there is no vacuum layer in the X and Y directions, but there is a large vacuum layer in the Z direction. To avoid model errors when considering long-range Coulomb forces, manually adjust the size of the vacuum layer to an appropriate position, such as Figure 5 (c)

[0066] (9) After model III is relaxed for 1 ns under the isothermal and isobaric ensemble (NPT), model IV is obtained, in which the X, Y, and Z directions all conform to the series-connected semi-crystalline polymer model, which is called the series-parallel semi-crystalline polymer model. At this time, by observing the change of the total energy of the system with time during the relaxation process, it can be found that when the time reaches 1 ns, the total energy of the system has reached a dynamically stable state, such as Figure 6 As shown in the figure, the rationality of the obtained model is further proved. If other molecular dynamics simulation software is needed for subsequent simulation, the data file can be converted into an xyz file through ovito, or converted into a cif file using atomsk software, and then different types of model files can be converted into each other through visualization software such as Materials Studio or VMD.

[0067] Step 5: Investigate the changes in the morphology of Model IV after applying equal electric fields (Ex = Ey) in the X and Y directions:

[0068] First, the simulation temperature is set above the melting temperature of the amorphous polymer and below the melting point of the crystalline polymer. Then, the simulation is conducted by applying the The electric field of equal strength (E x =E y )2ns later, the morphology of the series-parallel semi-crystalline polymer changes. Figure 7 The figure shows the morphological changes of the model after applying an electric field. When an electric field of equal strength is applied to the model, the PVDF series-parallel semi-crystalline polymer will shrink in the X and Y directions and stretch in the Z direction. When electric fields of different strengths are applied and the electric field is removed after 2ns of electroinduced deformation, the cross-section of the model is shown in FIG. Figure 8 As shown, it can be seen that the "permanent crystalline region" still maintains a relatively stable structure. Then the temperature is cooled to room temperature 300K, and the NPT, NVT, and NVE ensembles are relaxed for 2ns to obtain a dynamic stable model at room temperature. The non-equilibrium molecular dynamics method is then used to perform heat transfer analysis, and the model is divided into multiple layers along the heat transfer direction (Z direction). The thickness of each layer is approximately Then fix the two outermost layers of atoms on both sides as fixed ends, and the two adjacent layers of atoms as heat source and heat sink respectively. The simulation box is set as follows Figure 9 As shown; then the Langevin method is used to control the temperature of the heat source and heat sink respectively to generate heat flow in the system until the heat flow basically maintains a stable growth and then the heat flow curve over time is statistically calculated, as shown Figure 10 As shown, finally the temperature of each layer is counted and the temperature variation curve of each layer position is drawn along the heat transfer direction, as shown in Figure 11 shown.

[0069] Step 6: Calculate the effect of electric field strength on the thermal conductivity of PVDF series-parallel semi-crystalline polymers:

[0070] The temperature gradient value and the rate of change of heat flow over time are obtained by linear fitting the curve of temperature change with each layer position and the curve of heat flow change with time through Python software. Then the cross-sectional dimensions of the model are extracted and the thermal conductivity of the material is calculated according to Fourier's law. The effect of the change of electric field intensity on the thermal conductivity of the polymer material is obtained, such as Figure 12 As shown;

[0071] The above is only one embodiment of the present invention. Researchers in this technical field can make various modifications and use the present invention without departing from the research ideas and technical processes of the present invention. Therefore, simple modifications and equivalent changes of the present invention fall within the scope of the claims of the present invention and still fall within the scope of protection of the technical solution of the present invention.

[0072] 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 in the scope of protection of the present invention.

Claims

1. A modeling and thermal conductivity optimization method for a series-parallel semi-crystalline model of a polymer material, characterized in that: The following steps are involved: Step 1: First, establish a fully crystalline polymer model of corresponding size according to the type of polymer required; Step 2: According to the simulation requirements, the central crystalline region is selected as the 'permanent crystalline region' and the rest of the region as the 'temporary crystalline region'. The covalent bonds between the atoms in the 'permanent crystalline region' and the 'temporary crystalline region' are then broken. Step 3: Name the main chain atom at the end of the molecular chain in the 'permanent crystalline region' R1, and the main chain atom at the end of the molecular chain in the 'temporary crystalline region' R2. Then, randomly form covalent bonds between R1 and R2 atoms according to simulation requirements to obtain Model I with different interchain couplings. Step 4: Use the open source software Lammps as the simulation software to perform molecular dynamics simulation on Model I, and obtain a semi-crystalline polymer model that conforms to the series morphology in the X, Y, and Z directions, called the series-parallel semi-crystalline polymer model IV. The specific steps are as follows: (1) Based on the predicted size of the deformed polymer according to Model I, a simulation box is created and the corresponding size is set so that all the model atoms are located inside the box, thus obtaining Model II; (2) Visualize the model using ovito software, render model II according to the molecular chain number, and then observe whether the division of the polymer molecular chain is correct or not, and correct the molecular chain that is incorrectly divided, so that the molecular number of the permanent crystalline region can be correctly extracted in the later stage, or the atomic number can be further determined by determining the z coordinate after the molecular number is determined; (3) Record the molecular chain numbers of the ‘permanent crystalline region’ where there is no interchain coupling between the molecular chains of the ‘permanent crystalline region’ and the ‘temporary crystalline region’; further determine the atomic numbers of the ‘permanent crystalline region’ where there is interchain coupling between the molecular chains of the ‘permanent crystalline region’ and the ‘temporary crystalline region’ by coordinate position; (4) Set the potential function that describes the interaction between atoms in Model II, set the initial simulation conditions and parameters, and the temperature must be higher than the melting point of the crystalline polymer; (5) For the potential function, if the long-range Coulomb force interaction is considered, in order to avoid errors when obtaining the initial series-parallel semi-crystalline polymer model, the setting of the long-range Coulomb force interaction is first canceled, and initially only the spatial position distribution of the molecular chain is considered for model II; (6) After setting the boundary conditions in the X, Y, and Z directions to non-periodic boundary f conditions, reflective walls are set on each side of the simulation box to prevent the polymer atoms from moving outside the simulation box during the local melting of Model II, causing simulation errors. According to the atomic number in sub-step (3) of step 4, the atoms in the 'permanent crystalline region' are divided into the same crystalline group, and the force and velocity of the atoms in the crystalline group are set to 0, forming a fixed crystalline region. (7) Model II was locally melted using the canonical ensemble NVT. When the temporary crystalline region was melted at high temperature, the permanent crystalline region was fixed by simulation commands. After 1-2 ns, Model III was obtained. At this time, the permanent crystalline region still maintained the crystalline conformation, while the temporary crystalline region had transformed into an amorphous state. (8) Use Model III as the model file and set the long-range Coulomb force interaction in the potential function. Then, change the boundary conditions in the X, Y, and Z directions to periodic boundary p conditions. Cancel the reflection wall set in sub-step (6) of step 4. Cancel the fixed 'permanent crystalline zone' setting in sub-step (7) of step 4. Set the simulation temperature below the melting point of the crystalline polymer to avoid structural damage in the subsequent crystalline zone. (9) Model III is relaxed under the isothermal and isobaric NPT ensemble. After 1-2 ns, a semi-crystalline polymer model with a series morphology in the X, Y, and Z directions is obtained, which is called the series-parallel semi-crystalline polymer model IV. Step 5: Using Model IV as the initial model, we investigated the effect of applying equal-strength electric fields in the X and Y directions on the morphology of the series-parallel semicrystalline polymers. We also used the nonequilibrium molecular dynamics (NEMD) method to perform heat transfer analysis, obtaining curves of temperature variation with position in each layer and heat flux variation with time. Step 6: Use Python software to perform linear fitting on the temperature change curve of each layer position and the heat flow change curve over time to obtain the temperature gradient value and the rate of change of heat flow over time. Calculate the thermal conductivity of the material according to Fourier's law, and obtain the effect of changes in electric field intensity on the thermal conductivity of polymer materials.

2. The method for modeling and optimizing thermal conductivity of a polymer material series-parallel semi-crystalline model according to claim 1, characterized in that: The 'permanent crystalline region' in step 2 is completely surrounded by the 'temporary crystalline region' to ensure that amorphous polymer chains exist at the ends of the crystalline region in the interchain direction or along the chain direction during the subsequent simulation of local melting.

3. The method for modeling and optimizing thermal conductivity of a polymer material series-parallel semi-crystalline model according to claim 1, characterized in that: In step 3, a model I with different interchain couplings is obtained. The interchain coupling in model I is set according to the simulation requirements. Specifically, the interchain coupling is determined based on the bond length of the end atoms. Connections with distances exceeding the bond length are not made to prevent unreasonable structure of model I.

4. The method for modeling and optimizing thermal conductivity of a polymer material series-parallel semi-crystalline model according to claim 1, wherein: In the step (1), symmetrically distributed vacuum layers are added to the model box to prevent more amorphous chains from concentrating on one side.

5. The method for modeling and optimizing thermal conductivity of a polymer material series-parallel semi-crystalline model according to claim 1, characterized in that: In step (2), the polymer molecular chain is observed as follows: open the Model II file in text format, observe the second column of data under "Atoms", and judge whether the molecular number division is correct or not based on the total number of molecules that meet the model.

6. The method for modeling and optimizing thermal conductivity of a polymer material series-parallel semi-crystalline model according to claim 1, characterized in that: In the step (4), the initial simulation conditions and parameters include model size, atom type, unit system, boundary conditions, neighbor list radius, time step, pressure, and temperature; the melting point of the crystalline polymer is determined according to the literature or by using Lammps to simulate the polymer heating process.

7. The method for modeling and optimizing thermal conductivity of a polymer material series-parallel semi-crystalline model according to claim 1, characterized in that: The step (8) further includes: if the polymer chains are distributed in the simulation box, then the next simulation is directly carried out; if the polymer chain clusters in the simulation box are around the 'permanent crystalline region' and there is a large vacuum layer, then the vacuum layer range is reduced in the model file to prevent an error from being reported due to exceeding the long-range Coulomb force interaction range during relaxation under the isothermal and isobaric ensemble NPT.

8. The method for modeling and optimizing thermal conductivity of a polymer material series-parallel semi-crystalline model according to any one of claims 1 to 7, characterized in that: In step 5, when investigating the effect of simultaneously applying equal-strength electric fields in the X and Y directions on the morphology of series-parallel semi-crystalline polymers, the applied electric field strength does not exceed the breakdown electric field strength value of the polymer; the simulation temperature is set above the melting temperature of the amorphous polymer and below the melting point of the crystalline polymer; after applying the electric field, the model is cooled to room temperature, and the effect of applying electric fields of different intensities on the thermal conductivity of the model is measured.

9. The method for modeling and optimizing thermal conductivity of a polymer material series-parallel semi-crystalline model according to claim 8, characterized in that: In step 5, the non-equilibrium molecular dynamics method is specifically as follows: the model is evenly divided into N layers along the heat conduction direction, the temperature gradient of each layer under stable heat flow is counted and output, and the thermal conductivity is calculated using Fourier's law, where N depends on the model length and N ≥ 8.

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