A micro-viscosity model of particle reinforced polymer composite and a method for establishing the same

Abstract

The application provides a particle reinforced polymer composite micro-viscosity model and a method for establishing the same. The relationship of the particle reinforced polymer composite micro-viscosity model is shown in formula (1). The model is obtained by respectively passing at least two particle reinforced polymer composites with different proportions through a capillary rheometer to obtain viscosity values of the particle reinforced polymer composites with different proportions at different shear rates at a set temperature, obtaining a relationship between the viscosity of the particle reinforced polymer composites with different proportions and the shear rate, and obtaining model parameters a2 and b2 related to a non-Newtonian index n through linear fitting and model parameters a1 and b1 and model constants a3 and b3 through fitting. According to the technical scheme, the influence of newly added particle materials on viscosity is considered, and the characteristic size factor of a micro part is combined, so that the accuracy of the prediction of the flow characteristics of the polymer composite melt is significantly improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of micro injection molding, and particularly relates to a micro-viscosity model of particle reinforced polymer composite material and a method for establishing the same. BACKGROUND

[0002] Micro injection molding technology is widely used in many manufacturing industries. The micro performance of polymer materials and their composites is increasingly concerned by scholars, in which viscosity is a specific form of polymer melt viscosity and an important physical quantity for characterizing fluid flow characteristics. The feature size of micro injection molding parts has reached microns, and the influence of micro-viscosity and other factors on filling behavior is correspondingly increased due to the influence of micro-size effect and the rheological properties of composite materials.

[0003] In the existing public literature, Zhuang Jian, Wang Minjie, etc. analyzed the influence of viscosity on the length-diameter ratio of flow channel at micro scale based on the macro Cross model, established a viscosity model for the flow characteristics of melt in micro channels, but did not discuss the actual factors generated in the injection molding process. Based on the macro Power-Law model, Xiong Jianjun, etc. analyzed the influence of ultrasonic vibration on the flow characteristics of polymer, and established a micro-viscosity model under ultrasonic vibration. However, this technology only explores the molding of microstructure of pure polymer in the injection molding process, and does not study the injection molding effect of composite materials. Yang Xiaodong, etc. rewrote the Cross model into Carreau form, used a segmented function to distinguish the Newtonian region and the non-Newtonian region of the viscosity curve, and used an Arrhenius type expression to modify the zero shear viscosity, and increased a control parameter τ0 to improve the model fitting ability. However, this viscosity model does not explore the micro-rheological properties and composite material properties. Ren Dongyun, etc. established a generalized viscosity model, which is suitable for composite flow of shear and tension according to the mutual independence of the second and third invariants of the strain rate tensor. The James flow channel containing shear and tension motion is selected to obtain the velocity distribution, and the modified viscosity model is obtained by assuming that the wall does not slip. However, this technology also does not involve the micro-rheological properties of composite materials. Gong Deng, etc. established a viscosity model according to the literature, simulated the pressure difference between the inflow surface and the outflow surface of the melt at different flow velocities to obtain the viscosity value. However, due to the lack of consideration of micro-rheological properties, the error is as high as 67.41%.

[0004] The above four viscosity models do not involve the change of micro-rheological properties of particle reinforced polymer composite materials. SUMMARY

[0005] In view of the above technical problems, the present application discloses a micro-viscosity model of particle reinforced polymer composite material and a method for establishing the same, which can be used for viscosity prediction of particle reinforced polymer composite materials for micro injection molding.

[0006] To this end, the technical scheme adopted by the present application is:

[0007] A particle reinforced polymer composite micro-viscosity model comprises:

[0008] The relational expression of the particle reinforced polymer composite micro-viscosity model is as formula (1):

[0009]

[0010] In formula (2), η micro : particle reinforced composite fluid micro-viscosity;

[0011] a1, b1: model parameters;

[0012] a2, b2: model parameters related to non-Newtonian index n;

[0013] a3, b3: model constants;

[0014] Shear rate;

[0015] l e : polymer matrix molecular chain segment length;

[0016] l p : particle material particle size;

[0017] d: micro part feature size;

[0018] Wherein, KL is the mass percentage content of the particle material in the particle reinforced polymer composite, which is calculated by formula (2):

[0019] KL = wt% * 100 (2),

[0020] In formula (3), wt% is the weight percentage of the particle material added in the polymer matrix.

[0021] By using this technical scheme, the particle reinforced polymer composite micro-viscosity model is improved based on the Power-Law macro-viscosity model, which takes into account the influence of particle material particle size, polymer matrix molecular chain segment length and micro part feature size, that is, the change of the micro rheological property of the particle reinforced polymer composite, so that the model is closer to the actual situation.

[0022] As a further improvement of the present application, the a1, b1, a3, b3 are the actual viscosity values of the rheological property of the particle reinforced polymer composite with different proportions measured by the capillary rheometer at different shear rates, which are obtained by fitting by using formula (3) and formula (4) as follows:

[0023]

[0024]

[0025] wherein, η is the viscosity value, A is the consistency coefficient corrected by the micro feature size and the particle content.

[0026] In this technical solution, formula (3) is a deformation based on the Power-Law macroscopic viscosity model, and the coefficient A is the consistency that is influenced by the particle material content and the micro feature size in the polymer matrix and the like, specifically, the higher the particle material content, the greater the consistency, therefore, the particle material content KL, the particle material particle size l p , the polymer matrix molecular chain segment length l e and the micro part feature size d are introduced to correct the consistency coefficient, and the parameter values a1, b1, a3 and b3 can be obtained through fitting.

[0027] As a further improvement of the present application, the a2 and b2 are the actual viscosity values of the rheological performance at different shear rates of the particle reinforced polymer composite with different proportions measured by the capillary rheometer by using formula (3) and formula (5), and the a2 and b2 are obtained through linear fitting:

[0028] n=a2+b2*KL (5);

[0029] wherein, n is the non-Newtonian index.

[0030] In this technical solution, the particle material content in the polymer matrix has an influence on the non-Newtonian index of the melt, the higher the particle material content, the worse the flow performance, and the smaller the non-Newtonian index n, and the composite material is more sensitive to shear, therefore, the particle material content KL is introduced to correct the non-Newtonian index n, and the a2 and b2 parameter values can be obtained through linear fitting by using the relationship between the particle material content and the non-Newtonian index n.

[0031] The present application also discloses a method for establishing the micro viscosity model of the particle reinforced polymer composite as described above, comprising:

[0032] Step S1, preparing at least two particle reinforced polymer composites with different proportions;

[0033] Step S2, obtaining the viscosity values of the particle reinforced polymer composites with different proportions at different shear rates at a set temperature by using the capillary rheometer.

[0034] Step S3, according to the viscosity values of the particle reinforced polymer composites with different ratios at different shear rates and different set temperatures, the viscosity-shear rate relationship of the particle reinforced polymer composites with different ratios is obtained by combining formula (3),

[0035]

[0036] wherein, η is the viscosity value, is the shear rate;

[0037] Step S4, by using formula (5) and combining the viscosity-shear rate relationship of the particle reinforced polymer composites with different ratios obtained in step S3, the model parameters a2 and b2 related to the non-Newtonian index n are obtained by linear fitting.

[0038] n=a2+b2×KL (5);

[0039] wherein, n is the non-Newtonian index, KL is the mass percentage content of the particle material in the particle reinforced polymer composite, which is calculated by formula (2):

[0040] KL=wt%×100 (2),

[0041] wt% is the weight percentage of the particle material added in the polymer matrix;

[0042] Step S5, by using formula (4) and combining the viscosity-shear rate relationship of the particle reinforced polymer composites with different ratios obtained in step S3, the model parameters a1 and b1 and the model constants a3 and b3 are obtained by fitting.

[0043]

[0044] wherein, l e is the polymer matrix molecular chain segment length, l p is the particle material particle size, and D is the feature size of the micro part.

[0045] Step S6, according to the model parameters a2 and b2 obtained in step S4, the model parameters a1 and b1 and the model constants a3 and b3 obtained in step S5, the relationship of the particle reinforced polymer composite micro-viscosity model is established:

[0046] In formula (1), η micro is the particle reinforced composite fluid micro-viscosity.

[0047] As a further improvement of the present application, it further comprises step S7: based on the established micro-viscosity model of particle reinforced polymer composite, finite element simulation calculation is carried out, under the conditions of different particle material contents and shear rates, according to the properties of polymer matrix material, the differences between the "micro-injection molding filling rate simulation value" and the "micro-injection molding filling rate experimental value" under different particle material contents and injection speeds are explored during the micro-injection molding finite element numerical simulation, and the corresponding rules are obtained and the accuracy of the model is verified.

[0048] Wherein, the "micro-injection molding filling rate simulation value" is the percentage of the cross-sectional area of the polymer melt filling the rectangular micro groove to the total area of the rectangular micro groove; the "micro-injection molding filling rate experimental value" is the percentage of the cross-sectional area of the polymer melt forming to the actual micro groove cross-sectional area obtained by corresponding micro-injection molding experiment.

[0049] The present application also discloses a method for predicting the micro-viscosity of particle reinforced polymer composite, which uses the micro-viscosity model of particle reinforced polymer composite as described above to predict the micro-viscosity value of the target particle reinforced polymer composite in micro-injection molding.

[0050] Compared with the prior art, the present application has the following beneficial effects:

[0051] The micro-viscosity model obtained by the method for establishing the micro-viscosity model of particle reinforced polymer composite according to the technical scheme of the present application is used for corresponding viscosity prediction, the influence of the newly added particle material on the viscosity is considered, and the characteristic size factor of the micro part is combined, so that the accuracy of the prediction of the flow characteristics of the polymer composite melt is significantly improved. BRIEF DESCRIPTION OF DRAWINGS

[0052] Figure 1 is the macro-viscosity curve of the particle reinforced polymer composite with different kaolin contents set by the embodiment of the present application.

[0053] Figure 2 is the linear fitting graph of the non-Newtonian index n of the embodiment of the present application.

[0054] Figure 3 is the fitting graph of the consistency coefficient A after the micro feature size and particle content correction of the embodiment of the present application.

[0055] Figure 4 is the laser confocal detection graph of the microstructure of the mold core for micro-injection molding in the embodiment of the present application; wherein (a), (b) and (c) are detection graphs with aspect ratios of 3:1, 5:1 and 10:1 respectively.

[0056] Figure 5 is the micro groove filling result schematic diagram for microstructure molding in the embodiment of the present application.

[0057] Figure 6is a comparative schematic diagram of the filling rate of the micro-viscosity model of the particle reinforced polymer composite material when the aspect ratio is 3:1 in the embodiment of the present application.

[0058] Figure 7 is a comparative schematic diagram of the filling rate of the micro-viscosity model of the particle reinforced polymer composite material when the aspect ratio is 5:1 in the embodiment of the present application.

[0059] Figure 8 is a comparative schematic diagram of the filling rate of the micro-viscosity model of the particle reinforced polymer composite material when the aspect ratio is 10:1 in the embodiment of the present application. DETAILED DESCRIPTION

[0060] The present application will be described in detail below with reference to specific embodiments and to the accompanying drawings, but the present application is not limited thereto.

[0061] A micro-viscosity model of a particle reinforced polymer composite material for injection molding technology is established by the following steps, comprising:

[0062] Step S1, under the premise of ensuring the original toughness and excellent processing performance of the polymer material, in order to improve the comprehensive properties of the material, a particle material is added to the original polymer matrix to prepare a particle reinforced polymer composite material, and at least two particle reinforced polymer composite materials with different proportions are obtained.

[0063] The content of the particle material is related as follows:

[0064] KL = wt% x 100 (2)

[0065] In formula (2),

[0066] wt%: the weight percentage of the particle material added in the polymer matrix.

[0067] Step S2, the at least two particle reinforced polymer composite materials with different proportions obtained are respectively passed through a capillary rheometer to obtain the viscosity values of the particle reinforced polymer composite materials with different proportions at different shear rates at a set temperature;

[0068] Step S3, according to the viscosity values of the particle reinforced polymer composite materials with different proportions at different shear rates at a set temperature, and combining formula (3), the relationship between the viscosity of the particle reinforced polymer composite material with different proportions and the shear rate is obtained,

[0069]

[0070] wherein, η is the viscosity value, is the shear rate;

[0071] Step S4, using formula (5), combining the viscosity-shear rate relationship of the particle reinforced polymer composite with different proportions obtained in step S3, the model parameters a2 and b2 related to the non-Newtonian index n are obtained by linear fitting;

[0072] n = a2 + b2 x KL (5);

[0073] Wherein, n is the non-Newtonian index, KL is the mass percentage content of the particle material in the particle reinforced polymer composite, which is calculated by formula (2):

[0074] KL = wt% x 100 (2),

[0075] wt% is the weight percentage of the particle material added in the polymer matrix;

[0076] Step S5, using formula (4), combining the viscosity-shear rate relationship of the particle reinforced polymer composite with different proportions obtained in step S3, the model parameters a1, b1 and model constants a3, b3 are obtained by fitting;

[0077]

[0078] Wherein, l e is the polymer matrix molecular chain segment length, l p is the particle material particle size, and D is the feature size of the micro part;

[0079] Step S6, according to the model parameters a2 and b2 obtained in step S4, and the model parameters a1 and b1 and the model constants a3 and b3 obtained in step S5, the relationship formula of the particle reinforced polymer composite micro-viscosity model is established:

[0080] In formula (1), η micro is the micro-viscosity of the particle reinforced composite fluid.

[0081] Step S7, based on the established particle reinforced polymer composite micro-viscosity model, the finite element simulation calculation is carried out, under the conditions of different particle material contents and shear rates, the difference between the "micro injection molding filling rate simulation value" and the "micro injection molding filling rate experimental value" is explored, the corresponding law is obtained and the accuracy of the model is verified;

[0082] Wherein, the "micro injection molding filling rate simulation value" is the percentage of the polymer melt filling rectangular micro groove cross-sectional area to the total area of the rectangular micro groove; the "micro injection molding filling rate experimental value" is the percentage of the polymer melt forming cross-sectional area to the actual micro groove cross-sectional area obtained by corresponding micro injection molding experiment.

[0083] The following is described in connection with specific examples.

[0084] Example 1

[0085] The micro-viscosity model of the kaolin particle reinforced polypropylene composite material and the verification are as follows:

[0086] Step one: preparation of experimental materials

[0087] The particle reinforced polymer composite material is a mixture of polypropylene particles (PP) and kaolin powder. The PP is a 9020M brand produced by Sinopec Maoming Branch; the kaolin is an industrial grade with a particle size of 10 μm produced by Tianjin Cheryou Chemical Reagent Co., Ltd.

[0088] First, sufficient PP raw particles and kaolin powder are taken out and placed in a vacuum drying box (model: DZ-6050B, manufacturer: Wohong Experimental Instrument Co., Ltd.) for vacuum drying at a constant temperature of 80℃ for 4 hours. After drying, PP and kaolin powder are weighed according to a certain weight ratio, and then the weighed PP and kaolin are placed in a horizontal planetary mixer (model: MSK-SFM-1, manufacturer: Hefei Jiesheng Material Technology Co., Ltd.) for stirring for 20 minutes at a stirring speed of 500 r / min, to prepare particle reinforced PP composite materials with different proportions of kaolin content of 5%, 7% and 9%.

[0089] Step two: viscosity measurement

[0090] The capillary rheological experiment scheme is determined. The test instrument of shear rheological viscosity is a RH7 type double barrel capillary rheometer of Anton Paar Company in Germany, the capillary port diameter is 1 mm, the length is 16 mm, and the diameter-length ratio is 1:16.

[0091] The molecular chain length of the polymer PP material is 2.18 nm; the particle size of kaolin is 10 μm; the feature size of the micro part is 1000 μm. The glass transition temperature of the PP material is -18℃, the specific pressure heat melting of the PP material is 1926 J / (kg·℃), the thermal conductivity coefficient is 0.138 W / (m·K), and the density is 910 kg / m 3 , and the initial temperature of micro injection molding is 200℃.

[0092] In the capillary rheological experiment, the melt temperature of the composite particle material is 200℃, and the shear rate value for viscosity test is 200 -1 , 500 -1 , 1000 -1 , 2000 -1 , 4000 -1 , 8000 -1The viscosity values of the 5%, 7%, and 9% different proportion of kaolin content of particle reinforced PP composites (5% KL / PP, 7% KL / PP, 9% KL / PP) at the corresponding shear rate are shown in Figure 1 .

[0093] Step three: parameter fitting

[0094] Using the data obtained in step two, the viscosity-shear rate curves of 5% KL / PP, 7% KL / PP, and 9% KL / PP particle composites are fitted by combining formula (3), and the quantity relationship of viscosity is as follows:

[0095] 5% KL / PP particle composite:

[0096] 7% KL / PP particle composite:

[0097] 9% KL / PP particle composite:

[0098] In formula (6)-(8):

[0099] η: viscosity, unit MPa·s;

[0100] Shear rate, unit s -1 .

[0101] (1) Non-Newtonian index n linear fitting:

[0102] a2, b2 are the actual viscosity values of the rheological properties of the particle reinforced polymer composites with different proportions measured by the capillary rheometer at different shear rates, the data of formula (6)-(8) are obtained, and then the linear fitting is obtained.

[0103] n=a2+b2*KL (5)

[0104] The specific data are: KL=[5 7 9]; n=[0.4 0.39 0.38];

[0105] Using the function f(KL)=n=a2+b2*KL to fit, we get:

[0106] a2=0.42; b2=-0.0044

[0107] R-square: 0.9962

[0108] The results are shown in Figure 2 , and a2=0.42; b2=-0.0044 is obtained.

[0109] (2) Fitting of consistency coefficient A after correction for microscopic feature size and particle content:

[0110] Establish a consistency relationship that takes into account the influence of microscopic feature size and particle content and corrects for it.

[0111] The molecular chain length of PP matrix material is l e The particle size of the added reinforcing material, kaolin, is 2.18 nm. p The micro-part feature size d is 1000μm. When calculating the consistency coefficient corrected for micro-feature size and particle content using formula (4), the molecular chain length of PP, which is 2.18nm, needs to be converted to 2.18×10. -3 μm.

[0112]

[0113] The specific data are: KL = [5 7 9]; A = [7356 7997 8894];

[0114] By fitting the function f(KL)=A=(a3*(10.00218 / 1000)*KL+b3)*(a1+b1*log(KL)), we obtain:

[0115] a1=44.34; b1=46.75; a3=9.11; b3=59.69

[0116] R-square: 0.9749

[0117] The results are as follows Figure 3 As shown, we obtain a1 = 44.34; b1 = 46.75; a3 = 9.11; b3 = 59.69.

[0118] Step 4: Model Building

[0119] The revised microviscosity relationship, i.e., the microviscosity model of particle-reinforced polymer composites, is as follows:

[0120]

[0121] Step 5: Finite Element Simulation of Micro-Injection Molding

[0122] The microviscosity model obtained in step four was substituted into the ANSYS-Fluent finite element analysis software, and then the microstructure filling was numerically solved. The following constraints were imposed on the solution conditions:

[0123] 1) Basic assumptions:

[0124] In the simulation of injection molding process, the granular composite melt is regarded as an incompressible fluid, i.e. ρ is constant. During the filling process, the melt temperature changes slightly, and the constant-pressure specific heat capacity CP and thermal conductivity λ of the melt are constant. The flow of the melt in the cavity is laminar, and the effects of gravity and inertial force on the melt flow are ignored. It is assumed that the velocity of the melt at the wall of the flow channel is zero, i.e. the no-slip boundary condition.

[0125] 2) Geometric model establishment and meshing:

[0126] To simulate the complete filling process of the granular composite melt into the microstructure, rectangular concave groove models with aspect ratios of 3:1 (feature size d = 161.1 μm), 5:1 (feature size d = 216.8 μm), and 10:1 (feature size d = 168.4 μm) were established. As shown in FIG. 1, the microstructure model was meshed and the boundary was defined using ANSYS-Meshing software. Figure 4

[0127] 3) Material properties:

[0128] The materials used in the model were 1% KL / PP and 7% KL / PP granular composites, and the melting temperature was 150°C.

[0129] 4) Boundary conditions:

[0130] Inlet: To study the effect of the injection speed of the KL / PP granular composite melt on the filling rate, the inlet speed was 40, 50, and 60 mm / s, respectively; the melt temperature T m was 200°C, and the injection pressure P was 8 MPa.

[0131] Wall: The mold temperature T M was 25°C, and the mold heat transfer coefficient was 25000 W / (m 2 ·K).

[0132] 5) Post-processing of simulation:

[0133] The simulation results were processed using CFD-Post software, the domain function was called to change the temperature display range, the area below the melting temperature (150°C) of the KL / PP granular composite was hidden, and the microstructure filling situation could be directly obtained, as shown in FIG. 2. Then the pixel point number of the microstructure filling area and the entire area of the simulation results was obtained using Photoshop software, and the simulation filling rate of the microstructure of the plastic part could be obtained by comparing the pixel area of the image. Figure 5

[0134] Step six: Micro-injection molding experiment

[0135] ​​The micro-injection molding machine was produced by Babyplast Company in Italy, model BABYPLAST-6-10P, mold temperature was 25℃, injection speed was 40, 50, 60 mm / s respectively, injection pressure was 8 MPa, injection time was 2 s, holding time was 4 s, and cooling time was 12 s. The materials were 1% KL / PP and 7% KL / PP particle composites, respectively. The first 10 samples of each particle composite were discarded after injection molding, and five samples were selected for laser confocal detection after the machine worked stably.

[0136] The laser confocal detection results of the injection molded products were obtained, the cross-sectional area of each microstructure of the molded product under the same experimental conditions was measured, the average value was taken and the filling rate R was calculated. S The expression is as follows:

[0137]

[0138] In formula (9):

[0139] S m is the cross-sectional area of the molded micro-rib (mm 2 );

[0140] S i is the cross-sectional area of the mold micro-groove (mm 2 ).

[0141] Step seven: verification of micro-viscosity model

[0142] As shown in Figure 6-8 , the deviation between the filling rate simulated by the Micro-KL / PP micro-viscosity model and the experimental results is small. The average error between the micro-viscosity model simulation value and the experimental data of 1% KL / PP particle reinforced composite material is between 1.55% and 5.30%, and the average error between the micro-viscosity model simulation value and the experimental data of 7% KL / PP particle reinforced composite material is between 0.87% and 3.40%, which shows that the Micro-KL / PP micro-viscosity model can better characterize the rheological properties of micro-injection polymer melt. Secondly, the simulation accuracy of 7% KL / PP particle reinforced composite material micro-viscosity model is higher than that of 1% KL / PP particle reinforced composite material, which shows that the higher the particle content, the higher the simulation accuracy of the micro-viscosity model. Therefore, for the filling problem of micro-groove with different aspect ratios, the Micro-KL / PP micro-viscosity model can well reflect the flow of polymer melt during micro-injection molding.

[0143] The above is further detailed description of the present application in combination with specific preferred embodiments, and cannot be deemed as limitation of the specific implementation of the present application to these descriptions. For those skilled in the art to which the present application belongs, without departing from the concept of the present application, a number of simple deductions or substitutions can be made, and all should be deemed as falling within the protection scope of the present application.

Claims

1. A method for establishing a microviscosity model of a particulate-reinforced polymer composite, characterized by, The method comprises the following steps: Step S1, preparing at least two different particle reinforced polymer composites; Step S2, obtaining the viscosity values of the at least two different particle reinforced polymer composites at different shearing rates under a set temperature through a capillary rheometer; Step S3, obtaining the viscosity-shearing rate relationship of the at least two different particle reinforced polymer composites according to the viscosity values of the at least two different particle reinforced polymer composites at different shearing rates under a set temperature, and combining formula (3), wherein η is the viscosity value, is the shear rate; Step S4, obtaining the model parameters a2 and b2 related to the non-Newtonian index n through linear fitting by using formula (5) and the viscosity-shearing rate relationship of the at least two different particle reinforced polymer composites obtained in step S3; n = a2 + b2 x KL (5); wherein n is the non-Newtonian index, KL is the mass percentage content of the particle material in the particle reinforced polymer composite, and is calculated by using formula (2): KL = wt% x 100 (2), wt% is the weight percentage of the particle material added in the polymer matrix; Step S5, obtaining the model parameters a1 and b1 and the model constants a3 and b3 through fitting by using formula (4) and the viscosity-shearing rate relationship of the at least two different particle reinforced polymer composites obtained in step S3; wherein, l e is the length of the polymer matrix molecular segment, l p is the particle material grain size, d is the micro-part feature size; Step S6, according to the model parameters a2, b2 obtained in step S4, and the model parameters a1, b1 obtained in step S5, and the model constants a3, b3, the relationship of the micro-viscosity model of the particle reinforced polymer composite material is established: In formula (1), η micro is the microviscosity of the particle-reinforced composite fluid.

2. The method of claim 1, wherein the micro-viscosity model of the particulate- reinforced polymer composite is established by: The method further comprises step S7: performing finite element simulation calculation based on the established micro-viscosity model of the particle reinforced polymer composite, exploring the difference between the "micro-injection molding filling rate simulation value" and the "micro-injection molding filling rate experimental value" under different particle material contents and shearing rates during micro-injection molding finite element numerical simulation according to the properties of the polymer matrix, obtaining the corresponding rules and verifying the accuracy of the model; wherein the "micro-injection molding filling rate simulation value" is the percentage of the cross-sectional area of the polymer melt filled in the rectangular micro groove to the total area of the rectangular micro groove; and the "micro-injection molding filling rate experimental value" is the percentage of the cross-sectional area of the polymer melt formed to the actual micro groove cross-sectional area obtained by corresponding micro-injection molding experiment.

3. A method of predicting the microviscosity of a particulate reinforced polymer composite, characterized by: The micro-viscosity model of the particle reinforced polymer composite is used to predict the micro-viscosity value of the target particle reinforced polymer composite in micro-injection molding.

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