Macroscopic conductivity prediction method, system, medium and equipment

Abstract

The invention discloses a macroscopic conductivity prediction method, system, medium and equipment of a polymer composite material, and the method comprises the steps: calculating the volume fraction corresponding to each component according to the mass fraction and density of each component of the polymer composite material; analyzing the dispersion form of each component in the polymer composite material by adopting an optical microscope or a scanning electron microscope; after the volume fraction and the dispersion form are determined, a physical structure model of each component is generated in a composite material matrix, and on the basis of establishing a polymer composite material filling structure physical model, the macroscopic conductivity of the polymer composite material is calculated and predicted through finite element analysis in combination with the electric field and temperature dependency of the conductivity of each component of the composite material. According to the method, the comprehensive action of internal factors such as the geometric size of the filler and external factors such as temperature and electric field is considered, and the macroscopic conductivity of the polymer composite material can be effectively predicted.

Description

Technical Field

[0001] The present invention relates to the technical field of polymer electrical materials, and in particular to a method, system, medium and equipment for predicting the macroscopic conductivity of a polymer composite material. Background Art

[0002] Adding different materials as fillers to polymers can produce polymer-based composite materials. Due to their multi-component structural characteristics, polymer-based composite materials can obtain the required performance at a low cost and have been widely used in the field of electrical materials, such as electromagnetic shielding composite materials, energy storage polymer composite materials, etc. When applying polymer-based composite materials in the field of electrical materials, it is often necessary to consider the conductivity design of the material. For example, in electromagnetic shielding composite materials, it is usually hoped that the material has a higher conductivity so that the material can generate a larger induced current under the action of electromagnetic waves, weaken the penetration of electromagnetic waves, and achieve a better electromagnetic shielding effect. In energy storage polymer materials, it is usually desired that the material has a lower conductivity to reduce the loss of the material during use.

[0003] However, in the process of designing material conductivity, a large number of tests are mainly carried out through experimental methods, and the formula or component design that meets the requirements is screened based on the test results. This process is time-consuming and costly, and it is also difficult to obtain materials with ideal conductivity. In recent years, some studies have also proposed predicting material design based on a small number of test results combined with artificial intelligence. This method also has problems such as inaccurate predictions when the test volume is small.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the invention and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the invention

[0005] In view of the problems existing in the prior art, the present invention proposes a method, system, medium and equipment for predicting the macroscopic electrical conductivity of polymer composite materials, which can realize the conductivity prediction of multi-component polymer composite materials, reduce time and labor costs, and provide data reference for material design and development.

[0006] The present invention is achieved through the following technical solutions: A method for predicting the macroscopic conductivity of a polymer composite material includes: Step 1, calculating the volume fraction of each component according to the mass fraction and density of each component of the polymer composite material; Step 2, analyzing the dispersion morphology of each component in the polymer composite material using an optical microscope or a scanning electron microscope; In the third step, after determining the volume fraction and dispersion morphology, a physical structure model of each component is generated in the composite matrix; The fourth step is to test the data of the conductivity, electric field and temperature of each component of the composite material, and fit the dependence of the conductivity, electric field and temperature of the polymer composite material. In the fifth step, under steady-state conditions, the finite element method is used to solve the macroscopic equivalent conductivity of the physical structure model of the polymer composite material. The entire physical model is set as the solution field, and the corresponding field control equation is the current field, that is, ▽ is the Laplace operator, J is the overall current density, E is the electric field strength, s is the conductivity of the material, is the electric potential, When setting the material properties, the dependence of the conductivity of each component on the electric field strength and temperature is substituted into it, and the constitutive relationship is also satisfied: D is the electric displacement vector, e 0 is the dielectric constant of vacuum, e r is the relative dielectric constant of the medium, Then, the connection conditions are met on the interface: J 1n , J 2n is the normal component of the current density, D 1n , D 2n is the normal component of the electric displacement vector, s e is the free charge density on the interface, E 1t , E 2t is the tangential component of the electric field intensity, Again, when setting the grid division, the grid unit size should be at least 10 times smaller than the minimum size of the filling component. Calculate the current distribution state and the equivalent resistance R of the entire field, combined with the length of the field L and cross-sectional area S , the macroscopic conductivity of the polymer composite is calculated according to the following formula, , In the formula, L The length of the composite module body, S The cross-sectional area of ​​the composite module body is R is the block equivalent resistance calculated by the finite element method, c is the predicted value of the macroscopic conductivity of the composite material.

[0007] In the method for predicting the macroscopic conductivity of a polymer composite material, the dispersed morphology is in the form of flakes, strips, or spheres.

[0008] In the method for predicting the macroscopic conductivity of a polymer composite material, in step 4, the data of the conductivity, electric field and temperature of each component of the composite material are tested, and the dependence of the conductivity, electric field and temperature of the polymer material in the component is fitted by the following functional relationship: In the formula, s 0 is a material-related constant, G a is the product of activation energy and electron charge, k B is the Boltzmann constant, T is the temperature, c is the electric field coefficient, E is the electric field strength.

[0009] In the macroscopic conductivity prediction method of a polymer composite material, the upper surface of the field is set to a high potential, the potential magnitude is set according to the potential magnitude borne by composite materials of the same thickness under operating conditions, and the lower surface is set to 0 potential.

[0010] In the method for predicting the macroscopic conductivity of a polymer composite material, the polymer composite material comprises polyvinylidene fluoride and spherical conductive particles.

[0011] In the method for predicting the macroscopic conductivity of a polymer composite material, the spherical conductive particles are graphite.

[0012] A macroscopic conductivity prediction system for polymer composite materials includes: A volume fraction calculation unit, which is used to calculate the volume fraction corresponding to each component according to the mass fraction and density of each component of the polymer composite material; A dispersion morphology scanning unit, which is used to analyze the dispersion morphology of each component in the polymer composite material using an optical microscope or a scanning electron microscope; A physical structure model generation unit, which is used to generate a physical structure model of each component in the composite matrix after determining the volume fraction and the dispersion morphology; The fitting unit is used to test the conductivity, electric field and temperature data of each component of the composite material. The polymer matrix material adopts a functional relationship to fit the dependence of conductivity, electric field and temperature, where: In the formula, s 0 is a material-related constant, G a is the product of activation energy and electron charge, k B is the Boltzmann constant, T is the temperature, c is the electric field coefficient, E is the electric field strength, The finite element unit is used to solve the macro equivalent conductivity of the physical structure model using the finite element method. The entire physical model is set as the solution field, and the corresponding field control equation is the current field, that is, ▽ is the Laplace operator, J is the overall current density, E is the electric field strength, s is the conductivity of the material, is the electric potential, When setting the material properties, the functional relationship between the conductivity of each component and the electric field strength and temperature is substituted into it, and the constitutive relationship is also satisfied: D is the electric displacement vector, e 0 is the dielectric constant of vacuum, e r is the relative dielectric constant of the medium, Then, the connection conditions are met on the interface: J 1n , J 2n is the normal component of the current density, D 1n , D 2n is the normal component of the electric displacement vector, s e is the free charge density on the interface, E 1t ,E 2t is the tangential component of the electric field intensity, Again, when setting up the grid division, the grid unit size should be at least 10 times smaller than the minimum size of the filling component. The current distribution state and equivalent resistance of the entire field are calculated, combined with the length of the field. L and cross-sectional area S , the macroscopic conductivity of the polymer composite is calculated according to the following formula, , In the formula, L The length of the composite module body, S The cross-sectional area of ​​the composite module body is R is the block equivalent resistance calculated by the finite element method, c is the predicted value of the macroscopic conductivity of the composite material.

[0013] In the system, the fitting unit includes a processor.

[0014] A computer storage medium includes computer instructions, which, when executed on a computer, cause the computer to execute the method described.

[0015] An electronic device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method described is implemented.

[0016] Compared with the prior art, the present invention has the following advantages: The prediction method of the present invention is convenient and easy to implement; it saves design time and reduces test costs; and it can achieve accurate prediction of the electrical conductivity of the composite material under different temperatures and electric field strengths. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] By reading the detailed description of the preferred specific embodiments below, various other advantages and benefits of the present invention will become clear to those of ordinary skill in the art. The drawings in the specification are only for the purpose of illustrating the preferred embodiments and are not considered to be limitations of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative work. Moreover, the same reference numerals are used to represent the same components throughout the drawings.

[0018] In the attached picture: Figure 1The present invention discloses a schematic flow chart of a method for predicting macroscopic conductivity of a polymer composite material provided by an implementation case; Figure 2 The figure is a schematic diagram of the corresponding relationship between the volume fraction and the mass fraction of graphite in a polyvinylidene fluoride based composite material, taking graphite and polyvinylidene fluoride as examples; Figure 3 Schematic diagram of graphite filling state in polyvinylidene fluoride based composite material; Figure 4 It is a schematic diagram of the particle size distribution of graphite fillers produced in the physical model of polyvinylidene fluoride based composite materials; Figure 5 This is a schematic diagram of the conductivity test results of polyvinylidene fluoride matrix material under different field strengths; Figure 6 is a schematic diagram of current density distribution in polyvinylidene fluoride based composite materials; Figure 7 This is a schematic diagram showing the relationship between the equivalent conductivity of polyvinylidene fluoride based composite materials and the filling amount; Figure 8 This is a schematic diagram comparing the calculated macroscopic conductivity and the measured conductivity of polyvinylidene fluoride based composite materials.

[0019] The present invention is further explained below in conjunction with the accompanying drawings and embodiments. DETAILED DESCRIPTION

[0020] The specific embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the specific embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0021] It should be noted that certain words are used in the specification and claims to refer to specific components. Those skilled in the art should understand that technicians may use different nouns to refer to the same component. This specification and claims do not use the difference in nouns as a way to distinguish components, but use the difference in the functions of the components as the criterion for distinction. As mentioned throughout the specification and claims, "including" or "comprising" is an open term, so it should be interpreted as "including but not limited to". The subsequent description of the specification is a preferred embodiment of the present invention, but the description is based on the general principles of the specification and is not intended to limit the scope of the present invention. The scope of protection of the present invention shall be determined by the attached claims.

[0022] To facilitate understanding of the embodiments of the present invention, further explanation will be given below by taking specific embodiments as examples in conjunction with the accompanying drawings, and each of the accompanying drawings does not constitute a limitation on the embodiments of the present invention.

[0023] like Figure 1 to Figure 8 As shown, the present invention discloses a method for predicting the macroscopic conductivity of a polymer composite material, comprising: Step 1, calculating the volume fraction of each component according to the mass fraction and density of each component of the polymer composite material; Step 2, analyzing the dispersion morphology of each component in the polymer composite material using an optical microscope or a scanning electron microscope; In the third step, after determining the volume fraction and dispersion morphology, a physical structure model of each component is generated in the composite matrix; In the fourth step, the conductivity, electric field and temperature data of each component of the composite material are tested, and the dependence of the conductivity, electric field and temperature is fitted by a functional relationship. The relationship between the change of polyvinylidene fluoride with the electric field and temperature is fitted as follows, and graphite is regarded as a constant as a conductive particle.

[0024] In the formula, s 0 is a material-related constant, G a is the product of activation energy and electron charge, k B is the Boltzmann constant, T is the temperature, c is the electric field coefficient, E is the electric field strength.

[0025] In the fifth step, the finite element method is used to solve the macroscopic equivalent conductivity of the physical structure model. The entire physical model is set as the solution field, and the corresponding field control equation is the current field, that is, ▽ is the Laplace operator, J is the overall current density, E is the electric field strength, s is the conductivity of the material, It is the electric potential.

[0026] When setting the material properties, the functional relationship between the conductivity of each component and the electric field strength and temperature is substituted into it, and the constitutive relationship is also satisfied: D is the electric displacement vector, e0 is the dielectric constant of vacuum, e r is the relative dielectric constant of the medium.

[0027] Then, the connection conditions are met on the interface: J 1n , J 2n is the normal component of the current density, D 1n , D 2n is the normal component of the electric displacement vector, s e is the free charge density on the interface, E 1t , E 2t is the tangential component of the electric field strength.

[0028] Again, when setting up the grid division, the grid unit size should be at least 10 times smaller than the minimum size of the filling component. The current distribution state and equivalent resistance of the entire field are calculated, combined with the length of the field. L and cross-sectional area S , the macroscopic conductivity of the polymer composite is calculated according to the following formula, .

[0029] In the formula, L is the length of the composite building block, S is the cross-sectional area of ​​the composite building block, R is the block equivalent resistance calculated by the finite element method, and γ is the predicted value of the macroscopic conductivity of the composite material. The previous formula is only used to calculate the conductivity of each component. After the composite is formed, the overall conductivity needs to be determined based on the current size and voltage of the composite block as a whole. After the macroscopic resistance of the block is determined, the macroscopic resistivity of the block is further determined by the macroscopic resistance and size of the block, and the conductivity is determined by the resistivity.

[0030] In a preferred embodiment of the method for predicting the macroscopic conductivity of a polymer composite material, the dispersed morphology is in the form of flakes, strips, or spheres.

[0031] In a preferred embodiment of the method for predicting the macroscopic conductivity of a polymer composite material, the physical structure model is a three-dimensional model.

[0032] In a preferred embodiment of the method for predicting the macroscopic conductivity of a polymer composite material, the upper surface of the field is set to a high potential, the potential magnitude is set according to the potential magnitude borne by a composite material of the same thickness under operating conditions, and the lower surface is set to zero potential.

[0033] In a preferred embodiment of the method for predicting the macroscopic conductivity of a polymer composite material, the polymer composite material comprises polyvinylidene fluoride and spherical conductive particles.

[0034] In a preferred embodiment of the method for predicting the macroscopic conductivity of a polymer composite material, the spherical conductive particles are graphite.

[0035] A macroscopic conductivity prediction system for polymer composite materials includes: A volume fraction calculation unit, which is used to calculate the volume fraction corresponding to each component according to the mass fraction and density of each component of the polymer composite material; A dispersion morphology scanning unit, which is used to analyze the dispersion morphology of each component in the polymer composite material using an optical microscope or a scanning electron microscope; A physical structure model generation unit, which is used to generate a physical structure model of each component in the composite matrix after determining the volume fraction and the dispersion morphology; The fitting unit is used to test the conductivity, electric field and temperature data of each component of the composite material, and use a functional relationship to fit the dependence of the conductivity, electric field and temperature, where: In the formula, s 0 is a material-related constant, G a is the product of activation energy and electron charge, k B is the Boltzmann constant, T is the temperature, c is the electric field coefficient, E is the electric field strength.

[0036] The finite element unit is used to solve the macro equivalent conductivity of the physical structure model using the finite element method. The entire physical model is set as the solution field, and the corresponding field control equation is the current field, that is, ▽ is the Laplace operator, J is the overall current density, E is the electric field strength, s is the conductivity of the material, It is the electric potential.

[0037] When setting the material properties, the functional relationship between the conductivity of each component and the electric field strength and temperature is substituted into it, and the constitutive relationship is also satisfied: D is the electric displacement vector, e 0 is the dielectric constant of vacuum, e r is the relative dielectric constant of the medium.

[0038] Then, the connection conditions are met on the interface: J 1n , J 2n is the normal component of the current density, D 1n , D 2n is the normal component of the electric displacement vector, s e is the free charge density on the interface, E 1t , E 2t is the tangential component of the electric field strength.

[0039] Again, when setting up the grid division, the grid unit size should be at least 10 times smaller than the minimum size of the filling component. The current distribution state and equivalent resistance of the entire field are calculated, combined with the length of the field. L and cross-sectional area S , the macroscopic conductivity of the polymer composite is calculated according to the following formula, .

[0040] Where L is the length of the composite building block, S is the cross-sectional area of ​​the composite building block, R is the block equivalent resistance calculated by the finite element method, and γ is the predicted value of the macroscopic conductivity of the composite material.

[0041] In a preferred embodiment of the system, the fitting unit comprises a processor.

[0042] A computer storage medium includes computer instructions, which, when executed on a computer, cause the computer to execute the method described.

[0043] An electronic device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method described is implemented.

[0044] In one embodiment, consider filling polyvinylidene fluoride (PVDF) with spherical conductive particles represented by graphite to form a polymer-based composite material. The volume fraction corresponding to different mass fractions of graphite in the composite material is calculated, and the results are shown in the attached figure. Figure 2 shown.

[0045] If spherical particles are used, the average diameter of the spherical particles is about 18 μm. A random distribution model is established based on the volume fraction of fillers in the composite material, as shown in the attached figure. Figure 3 He Ru Figure 4 shown.

[0046] Test the conductivity of polyvinylidene fluoride material at 25℃ and different field strengths, as shown in the attached Figure 5 As shown, substituting the temperature, the relationship between polyvinylidene fluoride and electric field is fitted as follows: The finite element method is used to solve the model. Figure 3 The voltage applied to the upper surface of the cube is 50V, and the voltage applied to the lower surface is 0V. The current density distribution in the field is obtained as shown in the attached figure. Figure 6 shown.

[0047] For polyvinylidene fluoride based composite materials, the calculated relationship between the equivalent conductance of the entire field and the volume fraction of graphite filler is as follows: Figure 7 shown.

[0048] According to the formula Where L is the length of the composite building block, S is the cross-sectional area of ​​the composite building block, R is the block equivalent resistance calculated by the finite element method, and γ is the predicted value of the macroscopic conductivity of the composite material.

[0049] The calculated macroscopic conductivity of the material is compared with the actual measured conductivity. Figure 8 shown. Figure 8 The predicted value of the conductivity of the material falls within the conductivity error range obtained from actual measurements, and the prediction result is relatively accurate.

[0050] Although the embodiments of the present invention are described above in conjunction with the accompanying drawings, the present invention is not limited to the above specific embodiments and application fields, and the above specific embodiments are only illustrative and instructive, rather than restrictive. A person of ordinary skill in the art can also make many forms under the guidance of this specification and without departing from the scope of protection of the claims of the present invention, all of which belong to the protection of the present invention.

Claims

1. A method for predicting the macroscopic conductivity of a polymer composite material, characterized in that: It includes: Step 1, calculating the volume fraction of each component according to the mass fraction and density of each component of the polymer composite material; Step 2, analyzing the dispersion morphology of each component in the polymer composite material using an optical microscope or a scanning electron microscope; In the third step, after determining the volume fraction and dispersion morphology, a physical structure model of each component is generated in the composite matrix; The fourth step is to test the data of the conductivity, electric field and temperature of each component of the composite material, and fit the dependence of the conductivity, electric field and temperature of the polymer composite material. In the fifth step, under steady-state conditions, the finite element method is used to solve the macroscopic equivalent conductivity of the physical structure model of the polymer composite material. The entire physical model is set as the solution field, and the corresponding field control equation is the current field, that is, ▽ is the Laplace operator, J is the overall current density, E is the electric field strength, σ is the conductivity of the material, is the electric potential, When setting the material properties, the dependence of the conductivity of each component on the electric field strength and temperature is substituted into it, and the constitutive relationship is also satisfied: D is the electric displacement vector, ε 0 is the dielectric constant of vacuum, ε r is the relative dielectric constant of the medium, Then, the connection conditions are met on the interface: J 1n , J 2n is the normal component of the current density, D 1n , D 2n is the normal component of the electric displacement vector, σ e is the free charge density on the interface, E 1t , E 2t is the tangential component of the electric field intensity, Again, when setting the grid division, the grid unit size should be at least 10 times smaller than the minimum size of the filling component. Calculate the current distribution state and the equivalent resistance R of the entire field, combined with the length of the field L and cross-sectional area S , the macroscopic conductivity of the polymer composite is calculated according to the following formula, ， In the formula, L The length of the composite module body, S The cross-sectional area of ​​the composite module body is R is the block equivalent resistance calculated by the finite element method, γ is the predicted value of the macroscopic conductivity of the composite material.

2. The method for predicting macroscopic conductivity of a polymer composite material according to claim 1, characterized in that: Preferably, the dispersed form is in the form of flakes, strips or spheres.

3. The method for predicting macroscopic conductivity of a polymer composite material according to claim 1, characterized in that: Step 4: Test the conductivity, electric field and temperature data of each component of the composite material, and use the following functional relationship to fit the dependence of the conductivity, electric field and temperature of the polymer material in the component. In the formula, σ 0 is a material-related constant, G a is the product of activation energy and electron charge, k B is the Boltzmann constant, T is the temperature, c is the electric field coefficient, E is the electric field strength.

4. The method for predicting macroscopic conductivity of a polymer composite material according to claim 1, characterized in that: The upper surface of the field is set to a high potential, the magnitude of the potential is set according to the magnitude of the potential that a composite material of the same thickness can withstand under operating conditions, and the lower surface is set to zero potential.

5. The method for predicting macroscopic conductivity of a polymer composite material according to claim 1, characterized in that: The combination of the polymer composite material includes polyvinylidene fluoride and spherical conductive particles.

6. The method for predicting macroscopic conductivity of a polymer composite material according to claim 5, characterized in that: The spherical conductive particles are graphite.

7. A macroscopic conductivity prediction system for polymer composite materials, characterized in that: These include, A volume fraction calculation unit, which is used to calculate the volume fraction corresponding to each component according to the mass fraction and density of each component of the polymer composite material; A dispersion morphology scanning unit, which is used to analyze the dispersion morphology of each component in the polymer composite material using an optical microscope or a scanning electron microscope; A physical structure model generation unit, which is used to generate a physical structure model of each component in the composite material matrix after determining the volume fraction and the dispersion morphology; The fitting unit is used to test the conductivity, electric field and temperature data of each component of the composite material. The polymer matrix material adopts a functional relationship to fit the dependence of conductivity, electric field and temperature, where: In the formula, σ 0 is a material-related constant, G a is the product of activation energy and electron charge, k B is the Boltzmann constant, T is the temperature, c is the electric field coefficient, E is the electric field strength, The finite element unit is used to solve the macro equivalent conductivity of the physical structure model using the finite element method. The entire physical model is set as the solution field, and the corresponding field control equation is the current field, that is, ▽ is the Laplace operator, J is the overall current density, E is the electric field strength, σ is the conductivity of the material, is the electric potential, When setting the material properties, the functional relationship between the conductivity of each component and the electric field strength and temperature is substituted into it, and the constitutive relationship is also satisfied: D is the electric displacement vector, ε 0 is the dielectric constant of vacuum, ε r is the relative dielectric constant of the medium, Then, the connection conditions are met on the interface: J 1n , J 2n is the normal component of the current density, D 1n , D 2n is the normal component of the electric displacement vector, σ e is the free charge density on the interface, E 1t , E 2t is the tangential component of the electric field intensity, Again, when setting up the grid division, the grid unit size should be at least 10 times smaller than the minimum size of the filling component. The current distribution state and equivalent resistance of the entire field are calculated, combined with the length of the field. L and cross-sectional area S , the macroscopic conductivity of the polymer composite is calculated according to the following formula, ， In the formula, L The length of the composite module body, S The cross-sectional area of ​​the composite module body is R is the block equivalent resistance calculated by the finite element method, γ is the predicted value of the macroscopic conductivity of the composite material.

8. The system according to claim 7, characterized in that The fitting unit comprises a processor.

9. A computer storage medium, characterized in that: The storage medium includes computer instructions, which, when executed on a computer, enable the computer to execute the method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: The electronic device comprises: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method according to any one of claims 1 to 7 is implemented.

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