Method for simulating crystallinity and mechanical property of polytetrafluoroethylene based on molecular dynamics

Abstract

The invention discloses a method for simulating the crystallinity and mechanical properties of polytetrafluoroethylene based on molecular dynamics. Comprising the following steps: constructing an amorphous polytetrafluoroethylene full-atom model; performing sintering simulation on the amorphous polytetrafluoroethylene full-atomic model, and constructing a polytetrafluoroethylene coarse graining model according to key sequence information obtained by sintering simulation; performing cooling crystallization simulation on the polytetrafluoroethylene coarse graining model, and calculating the degree of crystallinity of polytetrafluoroethylene according to particle coordinate information obtained by cooling crystallization simulation; and performing uniaxial stretching simulation on the polytetrafluoroethylene coarse graining model subjected to cooling crystallization simulation, and evaluating the mechanical property of polytetrafluoroethylene according to a uniaxial stretching simulation result. According to the method, the crystallinity and the mechanical property of polytetrafluoroethylene with different molecular weights are obtained through simulation and are well matched with actual results, the test time and the money cost can be saved, and a certain guiding effect is provided for actual production.

Description

Technical Field

[0001] The invention relates to the technical field of polymer materials, and in particular to a method for simulating the crystallinity and mechanical properties of polytetrafluoroethylene based on molecular dynamics. Background Art

[0002] Polytetrafluoroethylene (PTFE) is a helical straight-chain polymer with excellent corrosion resistance, good chemical inertness and good machining performance. It is widely used in semiconductor manufacturing, biomedicine and chemical industry. The crystallinity of polytetrafluoroethylene powder is as high as 70-90%, and the melting temperature and melt viscosity are high. It is not easy to extrude or injection mold. It is often produced by a compression sintering method similar to "powder metallurgy", that is, cold compression molding under a certain pressure, and then heating to a temperature above the melting point of 325°C for free sintering, and finally forming a translucent solid after insulation and cooling. When heated, polytetrafluoroethylene changes from a crystal to an amorphous state, and the particles melt each other. As the temperature drops, the amorphous state changes to a new ribbon crystal, and the crystallinity drops to 25-40%. The mechanical properties of polytetrafluoroethylene products are affected by molecular weight and crystallinity. The molecular weight and crystallinity of polytetrafluoroethylene powders of different grades are different. With the change of sintering temperature, polytetrafluoroethylene has different degrees of thermal decomposition, and the macromolecular chain is decomposed into short chains. Therefore, there are differences in the molecular weight and crystallinity of polytetrafluoroethylene after sintering. Generally speaking, the lower the molecular weight, the stronger the crystallization dynamics of the molecular chain, the higher the degree of crystallinity, the greater the hardness and brittleness, but the poorer the deformation ability and flexibility, and the lower the tensile strength and elongation at break.

[0003] Molecular dynamics (MD) simulation is a deterministic computer simulation method based on Newtonian mechanics theory. This method constructs an atomic model at a microscopic scale to simulate the static structure of the system and its dynamic evolution over time. The force field is constructed by setting the interaction relationship between atoms; the initial state is determined by assigning the initial position and velocity of each basic unit in the system; the equilibrium system and its motion trajectory of each basic unit under a long-term state are obtained through time integration; and the macroscopic properties of the system such as physical quantities such as size, temperature and pressure are reflected through statistical physics methods.

[0004] At present, the sintered materials are usually characterized by a variety of methods: Scanning electron microscope (SEM) or transmission electron microscope (TEM) to observe the internal microstructure and crystal morphology; Differential scanning calorimeter (DSC) to measure the melting enthalpy and calculate the crystallinity; Gel chromatography to measure the molecular weight distribution; Uniaxial stretching to measure the elastic modulus and tensile strength of the material. The above experiments are cumbersome and take a long time. Summary of the invention

[0005] The present invention provides a method for simulating the crystallinity and mechanical properties of polytetrafluoroethylene based on molecular dynamics. The present invention is applicable to polytetrafluoroethylene of different molecular weights, and uses the molecular dynamics simulation calculation method to simulate the thermal decomposition and crystallization process of polytetrafluoroethylene during sintering from a microscopic perspective, characterize the crystallinity and mechanical properties of polytetrafluoroethylene of different molecular weights, establish the connection between microscopic characteristics and macroscopic properties, and achieve the purpose of quickly evaluating the performance of polytetrafluoroethylene without conducting a large number of experiments.

[0006] The technical solution adopted by the present invention is as follows:

[0007] 1. A method for simulating the crystallinity and mechanical properties of polytetrafluoroethylene based on molecular dynamics

[0008] The method of the present invention comprises the following steps:

[0009] 1) Use molecular modeling software to construct a full-atom model of amorphous polytetrafluoroethylene;

[0010] In the step 1), the amorphous polytetrafluoroethylene all-atom model is a visualized three-dimensional model. The amorphous polytetrafluoroethylene all-atom model is based on atoms and is mainly composed of a number of polytetrafluoroethylene molecular chains with the same or different molecular weights randomly stacked, and the polytetrafluoroethylene molecular chains are mainly polymerized from a number of tetrafluoroethylene monomers.

[0011] 2) performing a sintering simulation on the amorphous polytetrafluoroethylene all-atom model, and constructing a coarse-grained model of polytetrafluoroethylene according to the bond order information obtained from the sintering simulation;

[0012] The step 2) specifically comprises the following steps:

[0013] 2.1) converting the amorphous polytetrafluoroethylene all-atom model into a text file and importing it into a molecular dynamics simulation software, and initializing the ReaxFF force field in the molecular dynamics simulation software;

[0014] The text file of the amorphous polytetrafluoroethylene full-atom model includes information such as atomic position coordinates, velocity information, chemical bonds, bond angles, and dihedral angles;

[0015] In the step 2.1), the ReaxFF force field is initialized as follows: Reaxff force field parameters and boundary conditions are set, the amorphous polytetrafluoroethylene all-atom model is optimized for energy minimization, particles are given initial velocity, and equilibrium relaxation is performed; the equilibrium relaxation adopts a canonical ensemble and a Nosé-Hoover temperature control method, and the relaxation temperature is 200K to avoid excessively high temperature causing chemical bonds to break;

[0016] 2.2) In the ReaxFF force field, the canonical ensemble and the Berendson temperature control method are used to perform a sintering simulation on the amorphous polytetrafluoroethylene all-atom model at a preset sintering simulation temperature to obtain bond order information; the sintering simulation temperature is higher than the melting point of polytetrafluoroethylene;

[0017] 2.3) by retrieving the bond sequence information, the broken chemical bonds, bond angles and dihedral angles are obtained, and the broken chemical bonds, bond angles and dihedral angles are deleted from the amorphous polytetrafluoroethylene full-atom model after sintering simulation to obtain a reconstructed amorphous polytetrafluoroethylene full-atom model;

[0018] 2.4) Using CF2 groups as basic units, the reconstructed amorphous polytetrafluoroethylene all-atom model is converted into a coarse-grained model of polytetrafluoroethylene.

[0019] 3) performing a cooling crystallization simulation on the polytetrafluoroethylene coarse-grained model, and calculating the crystallinity of the polytetrafluoroethylene according to the particle coordinate information obtained from the cooling crystallization simulation;

[0020] The step 3) specifically comprises the following steps:

[0021] 3.1) Initialize the Dreiding force field in the molecular dynamics software;

[0022] 3.2) In the Dreiding force field, a canonical ensemble, Nosé-Hoover temperature and pressure control method are used to simulate the cooling crystallization of the polytetrafluoroethylene coarse-grained model to obtain particle coordinate information;

[0023] The cooling crystallization simulation conditions are as follows: the pressure is 1 atm, the temperature is slowly reduced from the sintering simulation temperature to the crystallization relaxation temperature, and then the polytetrafluoroethylene coarse-grained model is relaxed at the crystallization relaxation temperature until the polytetrafluoroethylene reaches a steady state, so that the polytetrafluoroethylene is fully crystallized;

[0024] The crystallization relaxation temperature is preferably 300K;

[0025] 3.3) selecting intermediate particles of each molecular chain from all particles according to the particle coordinate information, calculating the local orientation factor of each intermediate particle, and judging whether the intermediate particle is in the crystallization region according to the local orientation factor of each intermediate particle;

[0026] In step 3.3), the specific process of calculating the local orientation factor of each intermediate particle is as follows:

[0027] 3.3.1) The intermediate particle is used as the target particle, and the localized particles are screened out from the remaining intermediate particles, and all the localized particles constitute a set P; the distance between the localized particles and the target particle is less than a preset cutoff radius R;

[0028] 3.3.2) Screening out heterochain particles from the set P, all heterochain particles constitute a set Q; there is no chemical bond between the heterochain particles and the target particles;

[0029] 3.3.3) Calculate the bond vectors of the target particle and each heterochain particle in the set Q respectively

[0030] The key vector Obtained by the following formula:

[0031]

[0032] Where n is the serial number of the particle whose bond vector is to be calculated, m and l are the serial numbers of the two particles connected to the particle whose bond vector is to be calculated by chemical bonds, x is the coordinate value of the particle on the x-axis, y is the coordinate value of the particle on the y-axis, and z is the coordinate value of the particle on the z-axis;

[0033] 3.3.4) Calculate the orientation factor of each heterochain particle and the target particle in the set Q;

[0034] The orientation factor of each heterochain particle and the target particle is obtained by the following formula:

[0035]

[0036] In the formula, i is the number of the target particle, j is the number of the heterochain particle, and f ij is the orientation factor of the target particle i and the heterochain particle j, f ij is the key vector With key vector The angle between

[0037] 3.3.5) Calculate the average value of the orientation factors of all heterochain particles and the target particle in the set Q, and use the average value as the local orientation factor of the intermediate particle.

[0038] In the step 3.3), the specific process of judging whether the intermediate particle is in the crystallization region according to the local orientation factor of the intermediate particle is as follows: if the local orientation factor of the intermediate particle is greater than or equal to a preset threshold, the intermediate particle is in the crystallization region; if the local orientation factor of the intermediate particle is less than the preset threshold, the intermediate particle is not in the crystallization region;

[0039] 3.4) Counting the total number of particles in the crystallization region and the total number of particles in the coarse-grained model of polytetrafluoroethylene, calculating the ratio between the total number of particles in the crystallization region and the total number of particles, and obtaining the crystallinity of the polytetrafluoroethylene.

[0040] 4) performing uniaxial stretching simulation on the coarse-grained model of polytetrafluoroethylene after the cooling crystallization simulation, and obtaining the mechanical properties of polytetrafluoroethylene according to the results of the uniaxial stretching simulation;

[0041] In the step 4), the uniaxial stretching simulation adopts a canonical ensemble, a Nosé-Hoover temperature and pressure control method, the uniaxial stretching simulation temperature is 300K, the pressure in the non-stretching direction is 1atm, and a constant strain rate is applied in the stretching direction; the result of the uniaxial stretching simulation is the strain and stress information of the polytetrafluoroethylene coarse-grained model in the stretching direction after the uniaxial stretching simulation;

[0042] In the step 4), the specific process of obtaining the mechanical properties of polytetrafluoroethylene according to the results of the uniaxial tensile simulation is: drawing a stress-strain curve according to the results of the uniaxial tensile simulation, and evaluating the elastic modulus and / or tensile strength of polytetrafluoroethylene according to the stress-strain curve.

[0043] 2. A molecular dynamics simulation system applied to the above method

[0044] The molecular dynamics simulation system comprises:

[0045] A modeling module for constructing an all-atom model of amorphous polytetrafluoroethylene using molecular modeling software;

[0046] Molecular dynamics simulation module, used to use molecular dynamics software to perform sintering simulation, cooling crystallization simulation and uniaxial stretching simulation on the amorphous polytetrafluoroethylene all-atom model in sequence;

[0047] The simulation module is used to simulate the crystallinity of polytetrafluoroethylene according to the results of the cooling crystallization simulation, and to obtain the mechanical properties of polytetrafluoroethylene according to the results of the uniaxial tension simulation.

[0048] The molecular dynamics software is LAMMPS software.

[0049] The molecular modeling software is preferably Materials Studio software.

[0050] The beneficial effects of the present invention are as follows:

[0051] 1. The method of the present invention uses molecular dynamics method and computer simulation to simulate the thermal decomposition behavior and microscopic crystallization process of polytetrafluoroethylene during sintering, and reflects the crystallinity and mechanical properties of polytetrafluoroethylene with different molecular weights through calculation of local orientation factor and simulation of uniaxial stretching. The method of the present invention is based on molecular dynamics simulation, which can replace experiments to a certain extent, make reasonable predictions on the sintering quality and mechanical properties of materials, thereby saving experimental time and money costs, and providing certain guidance for actual production.

[0052] 2. The crystallinity obtained by the method of the present invention is in good agreement with the actual test results, and the trend of the mechanical properties obtained by the present invention is consistent with the actual results.

[0053] 3. In the crystallization simulation process, the method of the present invention is based on the coarse-grained (CG) model, that is, on the basis of all-atom molecular dynamics simulation, the CF2 group is regarded as a whole, and the interaction between atoms within the group is not considered, thereby reducing the system's degree of freedom and improving the calculation efficiency, while not affecting the simulation results of crystallinity and mechanical properties. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a schematic diagram of the process of determining whether a particle is in a crystallization region in the method of the present invention;

[0055] Figure 2 is a graph showing the change of crystallinity over time obtained in an embodiment of the present invention;

[0056] Figure 3 : is the stress-strain curve obtained in the embodiment of the present invention. DETAILED DESCRIPTION

[0057] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0058] The present invention provides a method for simulating the thermal decomposition of polytetrafluoroethylene with different molecular weights during sintering, as well as the crystallinity and mechanical properties after sintering. The process of the method of the present invention mainly comprises: establishing a full-atom model of polytetrafluoroethylene; simulating the thermal decomposition behavior of polytetrafluoroethylene during sintering under the ReaxFF force field, and reconstructing the coarse-grained model of polytetrafluoroethylene according to the chemical bond breaking information; simulating the crystallization process under the Dreiding force field, calculating the local orientation factor according to the atomic coordinates, judging whether the atom is in the crystallization region according to the local orientation factor, and calculating the crystallinity; simulating uniaxial stretching under the Dreiding force field, drawing the stress-strain curve, and analyzing the mechanical properties.

[0059] The "system" and "simulation system" mentioned in the present invention both refer to the simulation objects in the molecular dynamics software.

[0060] The method of the present invention comprises the following steps:

[0061] 1) A full-atom model of amorphous polytetrafluoroethylene is constructed using modeling software; wherein the full-atom model of amorphous polytetrafluoroethylene takes atoms as basic units and is mainly composed of a number of polytetrafluoroethylene molecular chains with the same or different molecular weights randomly stacked, and the polytetrafluoroethylene molecular chain is mainly composed of a number of tetrafluoroethylene monomers polymerized.

[0062] 2) Using molecular dynamics software to perform sintering simulation on the amorphous polytetrafluoroethylene all-atom model, and constructing a coarse-grained model of polytetrafluoroethylene based on the bond order information obtained from the sintering simulation. Specifically, the following steps are included:

[0063] 2.1) Import the amorphous polytetrafluoroethylene all-atom model into the molecular dynamics software and initialize the ReaxFF force field in the molecular dynamics software.

[0064] The specific steps of initializing the ReaxFF force field are: setting the Reaxff force field parameters and boundary conditions, optimizing the energy minimization of the amorphous polytetrafluoroethylene all-atom model, assigning the particles an initial velocity, and balancing the relaxation.

[0065] Among them, equilibrium relaxation adopts canonical ensemble and Nosé-Hoover temperature control method, and the relaxation temperature is 200K to avoid chemical bonds breaking due to excessively high temperature.

[0066] 2.2) In the initialized ReaxFF force field, the canonical ensemble (NVT ensemble) and Berendson temperature control method are used to perform sintering simulation on the amorphous polytetrafluoroethylene all-atom model at the preset sintering simulation temperature, and the bond order information during the sintering simulation is output through the fixreaxff / bonds command;

[0067] The sintering simulation temperature is higher than the melting point of polytetrafluoroethylene;

[0068] 2.3) Retrieving the bond order information obtained by the sintering simulation to obtain the broken chemical bonds, bond angles and dihedral angles, deleting the broken chemical bonds, bond angles and dihedral angles from the amorphous polytetrafluoroethylene full-atom model after the sintering simulation, and obtaining a reconstructed amorphous polytetrafluoroethylene full-atom model;

[0069] 2.4) Taking the CF2 group as the basic unit and ignoring the interaction between atoms within the group, the reconstructed amorphous polytetrafluoroethylene full-atom model is converted into a coarse-grained model of polytetrafluoroethylene.

[0070] Among them, the Reaxff force field simulates the formation and breaking of chemical bonds through bond order, and the total energy of the system E system Bond energy E bond , supersaturated bond energy E over , bond angle energy E val , dihedral energy E tors , van der Waals interaction energy E vdWals , Coulomb interaction energy E coulomb , special bond energy E speciflc The sum of .

[0071] Among them, the boundary conditions are periodic boundary conditions, that is, the simulation system is replicated in all directions. When a particle moves out of the boundary, another particle enters the system from the opposite direction to ensure that the number and density of particles in the simulation system remain unchanged.

[0072] Among them, energy minimization optimization uses the conjugate gradient algorithm to calculate the interaction force between particles, so as to rearrange the overlapping or too close particles to reduce the energy of the system and obtain a more reasonable geometric configuration.

[0073] Among them, assigning the initial velocity to the particles means assigning a random velocity to each particle in the system at a specified temperature, and the velocity value distribution satisfies the Gaussian distribution.

[0074] Among them, equilibrium relaxation under the ReaxFF force field is to evolve the non-equilibrium system into an equilibrium state, so that the temperature, pressure and other physical quantities of the system are stable. According to the different complexity of the system, equilibrium relaxation can be divided into one step or multiple steps. The present invention adopts the canonical ensemble (NVT), Nosé-Hoover temperature control method, and the relaxation temperature is 200K to avoid excessive temperature causing chemical bonds to break.

[0075] The sintering simulation uses the NVT ensemble and the Berendson temperature control method. The sintering simulation temperature needs to be higher than the PTFE melting point of 325°C, and the bond order information is output through the fix reaxff / bonds command.

[0076] Preferably, in order to increase the reaction rate and break the chemical bonds within a limited simulation time, a sintering simulation temperature higher than the actual sintering temperature may be selected.

[0077] The process of reconstructing the polytetrafluoroethylene model according to the output bond order information and converting it into a coarse-grained model is as follows: according to the bond order information output at the end of the simulation, the existence of the corresponding chemical bonds before and after the simulation is retrieved, the polytetrafluoroethylene full-atom model is modified, the broken chemical bonds, bond angles and dihedral angles are deleted, the CF2 group is used as the basic unit, the interaction between atoms within the group is ignored, and the full-atom model is converted into a coarse-grained model for subsequent simulations.

[0078] 3) Use molecular dynamics software to simulate the cooling crystallization of the polytetrafluoroethylene coarse-grained model, and calculate the crystallinity of polytetrafluoroethylene based on the particle coordinate information obtained from the cooling crystallization simulation. Figure 1 As shown in the figure, the calculation of crystallinity requires calculating the order of arrangement of particles in a local range, that is, the local orientation factor. From a microscopic point of view, the particles in the crystal are arranged in an orderly manner and locally oriented. By comparing the local orientation factor with a threshold, when it is greater than or equal to the threshold, the particle is considered to be in the crystallization region. Finally, the ratio of the number of particles in the crystallization region to the total number of particles is calculated to obtain the crystallinity of the entire system.

[0079] The specific steps include:

[0080] 3.1) Initialize the Dreiding force field in the molecular dynamics software;

[0081] 3.2) In the initialized Dreiding force field, the NPT ensemble, Nosé-Hoover temperature and pressure control methods are used to simulate the cooling crystallization of the polytetrafluoroethylene coarse-grained model, and the particle coordinate information after the cooling crystallization simulation is obtained;

[0082] The cooling crystallization simulation conditions are as follows: the pressure is 1 atm, the temperature is slowly reduced from the sintering simulation temperature to 300 K, and then the polytetrafluoroethylene coarse-grained model is relaxed at 300 K until the polytetrafluoroethylene reaches a steady state, so that the polytetrafluoroethylene is fully crystallized;

[0083] 3.3) According to the particle coordinate information, the intermediate particles in each molecular chain are selected, the local orientation factor of each intermediate particle is calculated, and whether the intermediate particle is in the crystallization region is determined according to the local orientation factor of each intermediate particle.

[0084] The specific process of calculating the local orientation factor of each intermediate particle is:

[0085] 3.3.1) Taking the intermediate particle as the target particle, the localized particles are selected from the intermediate particles except the target particle, and all the localized particles constitute a set P; the distance between each localized particle and the target particle is smaller than the intermediate particle with a preset cutoff radius R;

[0086] 3.3.2) Screen out heterochain particles from the set P, and all heterochain particles constitute the set Q; there is no chemical bond between each heterochain particle and the target particle;

[0087] 3.3.3) Calculate the bond vectors of the target particle and each intermediate particle in the set Q

[0088] Key Vector Calculated by the following formula:

[0089]

[0090] Where n is the serial number of the particle whose bond vector is to be calculated, m and l are the serial numbers of the two particles connected to the particle whose bond vector is to be calculated by chemical bonds, x is the coordinate value of the x-axis, y is the coordinate value of the y-axis, and z is the coordinate value of the z-axis;

[0091] 3.3.4) Calculate the orientation factor of each heterochain particle and the target particle in the set Q;

[0092] The orientation factor of each heterochain particle and the target particle is obtained by the following formula:

[0093]

[0094] In the formula, i is the number of the target particle, j is the number of the heterochain particle, and f ijis the orientation factor of the target particle i and the heterochain particle j, f ij is the key vector With key vector The angle between is the bond vector of target particle i, is the bond vector of the heterochain particle with serial number j;

[0095] 3.3.5) Calculate the average value of the orientation factors of all heterochain particles and the target particle in the set Q, and use the average value as the local orientation factor of the target particle, i.e., the intermediate particle;

[0096] The local orientation factor of the target particle is obtained by the following formula:

[0097]

[0098] In the formula, k is the number of particles in set Q, j is the serial number of the intermediate particle in set Q, i is the serial number of the target particle, and f ij is the orientation factor of particles i and j, and F is the local orientation factor of the target particle with serial number i.

[0099] In step 3.3), the specific process of judging whether the intermediate particle is in the crystallization region according to the local orientation factor of the intermediate particle is as follows:

[0100] If the local orientation factor of the intermediate particle is greater than a preset threshold, the intermediate particle is in the crystallization region;

[0101] If the local orientation factor of the intermediate particle is less than a preset threshold, the intermediate particle is not in the crystallization region.

[0102] 3.4) Counting the total number of particles in the crystallization region and the total number of particles in the coarse-grained model of polytetrafluoroethylene, calculating the ratio between the total number of particles in the crystallization region and the total number of particles, and obtaining the crystallinity of polytetrafluoroethylene;

[0103] The calculation formula of PTFE crystallinity is as follows:

[0104]

[0105] In the formula, X is the crystallinity, N cr is the total number of particles in the crystallization region, and N is the total number of particles in the coarse-grained model of polytetrafluoroethylene.

[0106] Among them, the Dreiding force field is the non-bonded potential energy E non-bond , bond length potential energy E bond 、Bond angle potential energy E angle and dihedral potential energy E dihedral The sum of is as follows:

[0107] a) Non-bonded potential energy Enon-bond , describing the interaction force between particles that are not chemically bonded, the present invention uses the Lennard-Jones 12-6 potential:

[0108]

[0109] Where r is the distance between two coarse-grained particles, e is the LJ potential well depth, and r c is the cutoff radius.

[0110] b) Bond length potential energy E bond , describing the interaction force between particles connected by chemical bonds, the present invention adopts the harmonic potential:

[0111] E bond (r) = K b (r-r0) 2

[0112] In the formula, K b represents the tensile elastic constant of the chemical bond, and r0 is the length of the chemical bond in the equilibrium state.

[0113] c) Bond angle potential energy E angle , describing the bond angle bending potential between two chemical bonds formed by three consecutive atoms, the present invention adopts the harmonic potential:

[0114] E angle (q) = Kq(q-q0) 2

[0115] In the formula, K q is the bond angle distortion elastic constant, and q0 is the degree of the equilibrium bond angle.

[0116] d) Dihedral potential energy E dihedral , describes the torsion potential energy of the dihedral angle formed by four consecutive atoms. This method uses the CHARMN potential:

[0117] E dihedral (f) = K f [[1+cos(nf-d)]]

[0118] In the formula, K f is the dihedral angle torsion constant, n is the dihedral angle coefficient, and d is the angle adjustment coefficient.

[0119] 4) Using molecular dynamics software to perform uniaxial tensile simulation on the coarse-grained polytetrafluoroethylene model after cooling crystallization simulation, and evaluating the mechanical properties of polytetrafluoroethylene based on the results of the uniaxial tensile simulation;

[0120] Among them, the uniaxial stretching simulation adopts the NPT ensemble, Nosé-Hoover temperature and pressure control method, the uniaxial stretching simulation temperature is 300K, the pressure in the non-stretching direction is 1atm, and a constant strain rate is applied in the stretching direction;

[0121] Among them, the result of uniaxial tensile simulation is the strain and stress information of the polytetrafluoroethylene coarse-grained model in the tensile direction after uniaxial tensile simulation;

[0122] Among them, the mechanical properties include elastic modulus and / or tensile strength.

[0123] The specific embodiments of the present invention are as follows:

[0124] Example 1

[0125] The molecular modeling software Materials Studio used in this embodiment is a full-scale material simulation platform that can construct three-dimensional models of various crystalline, amorphous and polymer materials.

[0126] The molecular dynamics simulation software LAMMPS used in this embodiment is an open source classical molecular dynamics parallel simulator that can simulate a variety of atomic systems. It has a variety of built-in functions and can set force fields and boundary conditions according to its own needs to simulate the trajectory and mechanical characteristics of the system in the microscopic motion state. It is one of the commonly used tools in the current molecular dynamics method.

[0127] This embodiment specifically includes the following steps:

[0128] 1) Use the amorphous cell module of Materials Studio software to establish an amorphous polytetrafluoroethylene all-atom model; wherein the amorphous polytetrafluoroethylene all-atom model is based on atoms and is mainly composed of a number of polytetrafluoroethylene molecular chains with the same molecular weight randomly stacked, and the polytetrafluoroethylene molecular chain is mainly composed of a number of tetrafluoroethylene monomers polymerized. In this embodiment, the molecular weight of each polytetrafluoroethylene molecular chain is 20,000.

[0129] 2) Import the amorphous polytetrafluoroethylene all-atom model into the LAMMPS software, set the Reaxff force field parameters and boundary conditions in the LAMMPS software, perform energy minimization optimization on the amorphous polytetrafluoroethylene all-atom model, assign particles initial velocity, and balance relaxation; perform sintering simulation, and reconstruct the polytetrafluoroethylene model according to the output bond order information and convert it into a coarse-grained model.

[0130] The specific process and parameters are as follows: Under the ReaxFF force field, perform energy minimization optimization, set the NVT ensemble, and relax for 500ps at 200K. Set the NVT ensemble, control the sintering simulation temperature at 700K, simulate sintering for 2ns, and output the bond order information of the process through the fix reaxff / bonds command. By searching and comparing the bond order changes before and after sintering, delete the broken chemical bonds and their corresponding bond angles and dihedral angles, reconstruct the polytetrafluoroethylene model, and convert the model into a coarse-grained model with CF2 groups as the basic unit.

[0131] 3) Set the Dreiding force field parameters and perform equilibrium relaxation on the system; cool down and crystallize, output the particle coordinate information of the process, calculate the local orientation factor of each particle based on the particle coordinate information, determine whether each particle is in the crystallization zone based on the local orientation factor of each particle, and calculate the crystallinity of the system.

[0132] The specific process and parameters are as follows: Under the Dreiding force field, set the NVT ensemble, relax at 700K for 10ns; then set the NPT ensemble, relax at 700K for 10ns under 1atm pressure. Set the NPT ensemble, drop the temperature from 700K to 300K, and simulate the cooling crystallization at 1atm pressure for 10ns; then set the NPT ensemble, relax at 300K for 10ns under 1atm pressure. According to the output particle coordinate information, the cutoff radius R is preset to 0.4nm, according to Figure 1 The process shown calculates the local orientation factor of each particle, with a preset threshold of 0.7. By comparing the local orientation factor of each particle with the preset threshold, it is determined whether each particle is located in the crystallization region, and finally the crystallinity of the system is calculated.

[0133] 4) Performing uniaxial stretching simulation on the coarse-grained model of polytetrafluoroethylene after cooling and crystallization at a constant strain rate, outputting pressure and size information of the coarse-grained model of polytetrafluoroethylene after cooling and crystallization during the uniaxial stretching simulation, drawing a stress-strain curve, and evaluating the elastic modulus and / or tensile strength of polytetrafluoroethylene based on the stress-strain curve.

[0134] The specific process and parameters are as follows: under the Dreiding force field, set the NPT ensemble, at a temperature of 300K and a pressure of 1atm, simulate uniaxial stretching at a strain rate of 0.00001, and output the stress-strain information of the system.

[0135] In the above step 3), the calculation process of crystallinity is as follows Figure 1 As shown, the specific steps are:

[0136] S1) Exclude the first and last particles in all molecular chains and only calculate the local orientation factor of the intermediate particles;

[0137] S2) taking the selected particle as the center and the area with a preset cutoff radius R as the local area, all local particles whose distance from the selected particle is less than the preset cutoff radius R and are not the head or tail of the molecular chain are screened to obtain a set P.

[0138] S3) By searching whether each localized particle in the set P has a chemical bond with the selected particle, the heterochain particles in the set P that are located in different molecular chains from the selected particle are further screened out to obtain the set Q.

[0139] S4) Calculate the bond vectors of the target particle and each intermediate particle in the set Q

[0140] Key Vector Calculated by the following formula:

[0141]

[0142] Where n is the serial number of the particle whose bond vector is to be calculated, m and l are the serial numbers of the two particles connected to the particle whose bond vector is to be calculated by chemical bonds, x is the coordinate value of the x-axis, y is the coordinate value of the y-axis, and z is the coordinate value of the z-axis;

[0143] S5) Calculate the orientation factor of each heterochain particle in the set Q and the target particle; the calculation formula of the orientation factor of any heterochain particle j in the set Q and the target particle i is as follows:

[0144]

[0145] In the formula, i is the number of the target particle, j is the number of the heterochain particle, and f ij is the orientation factor of the target particle i and the heterochain particle j, f ij is the key vector With key vector The angle between is the bond vector of the target particle, is the bond vector of the heterochain particle with serial number j;

[0146] S6) calculating the average value of the orientation factors of all heterochain particles and the target particle in the set Q, and taking the average value as the local orientation factor of the target particle, i.e., the intermediate particle;

[0147] The local orientation factor of the target particle, i.e. the intermediate particle, is obtained by the following formula:

[0148]

[0149] In the formula, k is the number of particles in the set Q, j is the serial number of the intermediate particle in the set Q, i is the serial number of the target particle, and f ijis the orientation factor of particles i and j, and F is the local orientation factor of the target particle with serial number i;

[0150] S7) comparing the local orientation factor F of the target particle with a preset threshold value, if the local orientation factor F of the target particle is greater than the threshold value, the target particle is in the crystallization region; otherwise, the target particle is not in the crystallization region;

[0151] S8) calculating the local orientation factor of each intermediate particle according to steps S2) to S7), and judging whether each intermediate particle is in a crystalline region according to the local orientation factor of each intermediate particle;

[0152] Count the number of particles N in the crystallization area cr And the number of all particles N in the system, the crystallinity is calculated according to the following formula:

[0153]

[0154] In the formula, X is the crystallinity, N cr is the total number of particles in the crystallization region, and N is the total number of particles in the coarse-grained model of polytetrafluoroethylene.

[0155] Example 2

[0156] In this example, a polytetrafluoroethylene all-atom model with a molecular weight of 60,000 was established according to step 1) in example 1. Then, according to steps 2) to 4) in example 1, the crystallinity and mechanical properties of polytetrafluoroethylene were obtained.

[0157] Example 3

[0158] In this example, a polytetrafluoroethylene all-atom model with a molecular weight of 120,000 was established according to step 1) in example 1. Then, according to steps 2) to 4) in example 1, the crystallinity and mechanical properties of polytetrafluoroethylene were obtained.

[0159] The crystallinity of polytetrafluoroethylene obtained in Examples 1 to 3 of the present invention is shown in Figure 2 . Figure 2 The crystallinity calculation results of the polytetrafluoroethylene coarse-grained models with molecular weights of 20,000, 60,000 and 120,000 during the cooling crystallization process vary with time. It can be seen that as the cooling crystallization simulation time increases, the crystallinity increases first and then tends to stabilize, and the larger the molecular weight, the smaller the crystallinity. The final crystallinity of the models with molecular weights of 20,000 (Example 1), 60,000 (Example 2) and 120,000 (Example 3) are approximately 51%, 40% and 32%, respectively.

[0160] The trend of the crystallinity obtained by the method of the present invention changing with the molecular weight is consistent with the actual situation that the lower the molecular weight, the higher the crystallinity.

[0161] The stress-strain curves obtained in Examples 1 to 3 of the present invention are as follows: Figure 3 shown. Figure 3 It is the stress-strain curve of the coarse-grained model of polytetrafluoroethylene with molecular weights of 20,000, 60,000 and 120,000 during uniaxial stretching. It can be seen that when the strain is small, the material is in the elastic stage; after reaching the yield limit, the material enters the plastic stage. And the larger the molecular weight, the greater the elastic modulus and tensile strength of polytetrafluoroethylene. The trend of the mechanical properties obtained by the method of the present invention changing with the molecular weight is consistent with the actual trend that the lower the molecular weight, the greater the hardness and brittleness, and the lower the tensile strength and elongation at break.

[0162] Comparative Example

[0163] The actual measurement and calculation of this comparative example is to heat the polytetrafluoroethylene sintered products with molecular weights of 20,000, 60,000 and 120,000 from room temperature to 380°C at a rate of 10°C / min using a differential scanning calorimeter to obtain the melting enthalpy, and calculate the crystallinity according to the following formula:

[0164]

[0165] Where, X c is the crystallinity, ΔH f is the melting enthalpy of PTFE (J / g), ΔH f0 It is the melting enthalpy (J / g) of PTFE with 100% crystallinity. The specific value is 80 J / g.

[0166] The following table shows the comparison results of the simulated crystallinity obtained in Examples 1 to 3 and the actual measured and calculated crystallinity obtained in the comparative example:

[0167]

[0168] It can be seen that the simulation results of crystallinity are consistent with the experimental results.

[0169] The method of the present invention can simulate the thermal decomposition behavior of the molecular chain during the sintering process and the crystallinity after cooling for polytetrafluoroethylene with different molecular weights, and can also simulate its mechanical properties. Through simulation calculation, the purpose of quickly evaluating the performance of polytetrafluoroethylene is achieved without the need for complex experiments, and the conclusions are in good agreement with the actual results.

[0170] The above specific implementation modes are used to explain the present invention rather than to limit the present invention. Any modification and change made to the present invention within the spirit of the present invention and the protection scope of the claims shall fall within the protection scope of the present invention.

[0171] The above description is only a preferred embodiment of the present invention, so all equivalent changes or modifications made according to the structure, characteristics and principles described in the scope of the patent application of the present invention are included in the scope of the patent application of the present invention.

Claims

1. A method for simulating the crystallinity and mechanical properties of polytetrafluoroethylene based on molecular dynamics, characterized in that: The following steps are involved: 1) Using molecular modeling software to construct a full-atom model of amorphous polytetrafluoroethylene in a computer; 2) performing a sintering simulation on the amorphous polytetrafluoroethylene all-atom model, and constructing a coarse-grained model of polytetrafluoroethylene according to the bond order information obtained from the sintering simulation; 3) performing a cooling crystallization simulation on the polytetrafluoroethylene coarse-grained model, and calculating the crystallinity of the polytetrafluoroethylene according to the particle coordinate information obtained from the cooling crystallization simulation; 4) A uniaxial tensile simulation is performed on the coarse-grained model of polytetrafluoroethylene after the cooling crystallization simulation, and the mechanical properties of polytetrafluoroethylene are obtained according to the results of the uniaxial tensile simulation.

2. The method for simulating the crystallinity and mechanical properties of polytetrafluoroethylene based on molecular dynamics according to claim 1, characterized in that: The step 2) specifically comprises the following steps: 2.1) importing the amorphous polytetrafluoroethylene all-atom model into a molecular dynamics simulation software, and initializing the ReaxFF force field in the molecular dynamics simulation software; 2.2) In the ReaxFF force field, the canonical ensemble and the Berendson temperature control method are used to perform a sintering simulation on the amorphous polytetrafluoroethylene all-atom model at a preset sintering simulation temperature to obtain bond order information; 2.3) by retrieving the bond sequence information, the broken chemical bonds, bond angles and dihedral angles are obtained, and the broken chemical bonds, bond angles and dihedral angles are deleted from the amorphous polytetrafluoroethylene full-atom model after sintering simulation to obtain a reconstructed amorphous polytetrafluoroethylene full-atom model; 2.4) Using CF2 groups as basic units, the reconstructed amorphous polytetrafluoroethylene all-atom model is converted into a coarse-grained model of polytetrafluoroethylene.

3. The method for simulating the crystallinity and mechanical properties of polytetrafluoroethylene based on molecular dynamics according to claim 2, characterized in that: In the step 2.1), the ReaxFF force field is initialized as follows: Reaxff force field parameters and boundary conditions are set, the amorphous polytetrafluoroethylene all-atom model is optimized for energy minimization, particles are given initial velocity, and equilibrium relaxation is performed; the equilibrium relaxation adopts a canonical ensemble and a Nosé-Hoover temperature control method, and the relaxation temperature is 200K.

4. The method for simulating the crystallinity and mechanical properties of polytetrafluoroethylene based on molecular dynamics according to claim 1, characterized in that: The step 3) specifically comprises the following steps: 3.1) Initialize the Dreiding force field in the molecular dynamics software; 3.2) In the Dreiding force field, a canonical ensemble, Nosé-Hoover temperature and pressure control method are used to simulate the cooling crystallization of the polytetrafluoroethylene coarse-grained model to obtain particle coordinate information; The cooling crystallization simulation conditions are: the pressure is 1 atm, the temperature is slowly reduced from the sintering simulation temperature to the crystallization relaxation temperature, and then relaxed at the crystallization relaxation temperature until the polytetrafluoroethylene coarse-grained model reaches a steady state; 3.3) selecting intermediate particles of each molecular chain from all particles according to the particle coordinate information, calculating the local orientation factor of each intermediate particle, and judging whether the intermediate particle is in the crystallization region according to the local orientation factor of each intermediate particle; 3.4) Counting the total number of particles in the crystallization region and the total number of particles in the coarse-grained model of polytetrafluoroethylene, calculating the ratio between the total number of particles in the crystallization region and the total number of particles, and obtaining the crystallinity of the polytetrafluoroethylene.

5. The method for simulating the crystallinity and mechanical properties of polytetrafluoroethylene based on molecular dynamics according to claim 4, characterized in that: In step 3.3), the specific process of calculating the local orientation factor of each intermediate particle is as follows: 3.3.1) The intermediate particle is used as the target particle, and the localized particles are screened out from the remaining intermediate particles, and all the localized particles constitute a set P; the distance between the localized particles and the target particle is less than a preset cutoff radius R; 3.3.2) Screening out heterochain particles from the set P, all heterochain particles constitute a set Q; there is no chemical bond between the heterochain particles and the target particles; 3.3.3) Calculate the bond vectors of the target particle and each heterochain particle in the set Q respectively The key vector Obtained by the following formula: Where n is the serial number of the particle whose bond vector is to be calculated, m and l are the serial numbers of the two particles connected to the particle whose bond vector is to be calculated by chemical bonds, x is the coordinate value of the x-axis, y is the coordinate value of the y-axis, and z is the coordinate value of the z-axis; 3.3.4) Calculate the orientation factor of each heterochain particle in the set Q and the target particle; The orientation factor of each heterochain particle and the target particle is obtained by the following formula: In the formula, i is the number of the target particle, j is the number of the heterochain particle, and f ij is the orientation factor of the target particle i and the heterochain particle j, f ij is the key vector With key vector The angle between 3.3.5) Calculate the average value of the orientation factors of all heterochain particles and the target particle in the set Q, and use the average value as the local orientation factor of the intermediate particle.

6. The method for simulating the crystallinity and mechanical properties of polytetrafluoroethylene based on molecular dynamics according to claim 1, characterized in that: In the step 3.3), the specific process of judging whether the intermediate particle is in the crystallization region according to the local orientation factor of the intermediate particle is as follows: if the local orientation factor of the intermediate particle is greater than or equal to a preset threshold value, the intermediate particle is in the crystallization region; if the local orientation factor of the intermediate particle is less than the preset threshold value, the intermediate particle is not in the crystallization region.

7. The method for simulating the crystallinity and mechanical properties of polytetrafluoroethylene based on molecular dynamics according to claim 1, characterized in that: In the step 4), the uniaxial stretching simulation adopts a canonical ensemble and Nosé-Hoover temperature and pressure control method, the uniaxial stretching simulation temperature is 300K, the pressure in the non-stretching direction is 1atm, and a constant strain rate is applied in the stretching direction; the result of the uniaxial stretching simulation is the strain and stress information of the coarse-grained polytetrafluoroethylene model in the stretching direction after the uniaxial stretching simulation.

8. The method for simulating the crystallinity and mechanical properties of polytetrafluoroethylene based on molecular dynamics according to claim 7, characterized in that: The specific process of obtaining the mechanical properties of polytetrafluoroethylene according to the results of uniaxial tensile simulation is: drawing a stress-strain curve according to the results of uniaxial tensile simulation, and evaluating the elastic modulus and / or tensile strength of polytetrafluoroethylene according to the stress-strain curve.

9. The method for simulating the crystallinity and mechanical properties of polytetrafluoroethylene based on molecular dynamics according to claim 1, characterized in that: In the step 1), the amorphous polytetrafluoroethylene all-atom model is based on atoms and is mainly composed of a number of polytetrafluoroethylene molecular chains with the same or different molecular weights randomly stacked, and the polytetrafluoroethylene molecular chains are mainly polymerized from a number of tetrafluoroethylene monomers.

10. A molecular dynamics simulation system applied to the method according to any one of claims 1 to 9, characterized in that: The molecular dynamics simulation system comprises: A modeling module for constructing an all-atom model of amorphous polytetrafluoroethylene using molecular modeling software; Molecular dynamics simulation module, used to perform sintering simulation, cooling crystallization simulation and uniaxial stretching simulation on the amorphous polytetrafluoroethylene all-atom model using molecular dynamics software; The simulation module is used to simulate the crystallinity of polytetrafluoroethylene according to the results of the cooling crystallization simulation, and to obtain the mechanical properties of polytetrafluoroethylene according to the results of the uniaxial tension simulation.

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