Method for the preparation of a prepreg based on smart responsive resin and gradient distribution

Abstract

The application relates to the technical field of composite material manufacturing, and discloses a preparation method of prepreg based on intelligent response resin and gradient distribution, which comprises the following steps: preparing intelligent response resin according to weight proportions, coating the intelligent response resin on a fiber base material in a gradient distribution form, and obtaining prepreg through pre-impregnation molding; the intelligent response resin comprises 100 parts of bifunctional and multifunctional epoxy resin, 10-20 parts of polycaprolactone-epoxy graft copolymer, 4-6 parts of microencapsulated diluent, and 0.5-1.2 parts of surface epoxy group modified SiO2 nanoparticles. Through the synergistic effect of the intelligent response resin system and the gradient distribution design, the prepreg has temperature and pressure double-response type viscosity adjusting capacity, can dynamically adapt to the stress change in the complex curved surface forming process, and can effectively avoid the generation of wrinkle defects in the curvature mutation area. The suspension performance of the prepreg in the complex structure forming is obviously improved, and the surface flatness and overall consistency of the formed structure are ensured.

Description

Technical Field

[0001] This invention relates to the field of composite material manufacturing technology, specifically to a method for preparing prepregs based on smart responsive resins and gradient distribution. Background Technology

[0002] In the field of composite material manufacturing, especially in the production of complex curved surface structures for aerospace, prepregs, as core molding materials, directly determine the molding quality and structural reliability of the final product based on their draping performance. Therefore, related technology research and development has always received high attention from the industry. In existing prepreg preparation technologies, resin systems mostly use single-component or simple blend formulations. The resin viscosity remains fixed throughout the molding process and cannot be dynamically adjusted according to changes in the external environment during molding. However, the pressure distribution in areas of curvature abrupt change during the molding of complex curved surfaces often exhibits irregular fluctuations. Resins with fixed viscosity are difficult to adapt to such dynamic changes, which can easily lead to defects such as wrinkles and warping in the prepreg during the laying process, seriously affecting the surface smoothness and mechanical property consistency of the molded structure. At the same time, traditional prepregs generally adopt a homogeneous material distribution design, with resin content and fiber orientation remaining uniform across the entire width of the prepreg. This design mode cannot match the geometric characteristics and stress requirements of different regions of complex curved surfaces, making it difficult for the material to fully exert its load-bearing capacity in high-stress areas, while there is material redundancy in low-stress areas. This limits the improvement of molding effect and causes material waste.

[0003] Furthermore, the response mechanisms of existing improved prepregs are relatively simple, with most focusing solely on optimizing resin performance for temperature factors while neglecting the crucial influencing factor of molding pressure. This lack of proactive response to pressure changes results in poor molding stability of the prepregs under different process parameters, making them unsuitable for diverse and complex curved surface molding scenarios. Although current patented technologies primarily focus on improving the basic properties of prepregs, such as mechanical strength and apparent quality, effective solutions have not yet been proposed for the insufficient drape issues caused by resin viscosity mismatch, homogenized material distribution, and a single response mechanism in complex curved surface molding. This leaves the manufacturing of complex curved structures in the aerospace field facing technical bottlenecks such as unstable molding quality and poor process adaptability. There is an urgent need to develop a prepreg preparation technology that can synergistically optimize resin response performance and material distribution to overcome the limitations of existing technologies. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method for preparing prepregs based on smart responsive resins and gradient distribution, thus solving the problems mentioned in the background section.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solution: a method for preparing a prepreg based on a smart responsive resin and a gradient distribution, comprising the following steps: preparing a smart responsive resin according to a weight ratio, coating the smart responsive resin onto a fiber substrate in a gradient distribution form, and obtaining a prepreg by prepreg molding; the smart responsive resin comprises 100 parts of bifunctional and multifunctional epoxy resin, 10-20 parts of polycaprolactone-epoxy graft copolymer (temperature responsive function), 4-6 parts of microencapsulated diluent (pressure responsive function), and 0.5-1.2 parts of surface epoxy-modified SiO2 nanoparticles.

[0006] Preferably, the bifunctional and multifunctional epoxy resin is bisphenol A epoxy resin or AG80 epoxy resin, and the particle size of the surface epoxy-modified SiO2 nanoparticles is 20 nm.

[0007] Preferably, the number average molecular weight of the polycaprolactone-epoxy graft copolymer is 4000-6000, and the polycaprolactone-epoxy graft copolymer improves the molding adaptability of the prepreg by improving the temperature response performance of the resin.

[0008] Preferably, the microencapsulated diluent is formed by encapsulating the diluent within a microcapsule, wherein the wall material of the microcapsule is polyurea, the wall thickness is 1.5-2.5 μm, the particle size is 20-50 μm, and the rupture threshold is 0.25-0.35 MPa.

[0009] Preferably, the microcapsule pressure response principle is that the microcapsule ruptures when the pressure reaches the rupture threshold, releasing a diluent, which reduces the local resin viscosity and improves the processability of the prepreg. The diluent is one or more combinations of trimethylolpropane triacrylate, dibutyl phthalate, and styrene.

[0010] Preferably, the gradient distribution specifically involves the content of the smart response resin gradually increasing from the middle to both sides in the width direction of the prepreg, with the resin content in the middle region being 30% and the resin content in the two side regions being 45-50%, and the gradient slope being controlled at 3-10% / cm.

[0011] Preferably, during the prepreg molding process, the resin bath temperature is controlled at 40±1℃, the roller pressure is set to 0.03MPa, and the prepreg molding speed is controlled at 1.5m / min.

[0012] Preferably, the fiber substrate's orientation is adjusted synchronously with the resin gradient distribution. The first bending section corresponds to a 34% resin area with a 0° orientation, the second bending section corresponds to a 36% resin area with a +15° orientation, and the outlet section corresponds to a 38% resin area with a +30° orientation.

[0013] Preferably, during the preparation process, the microcapsule density is set differently according to the stress characteristics of different regions of the prepreg, and the microcapsule density in the region of abrupt curvature change is higher than that in the region of gentle curvature change.

[0014] Preferably, after prepreg molding, hot melt processing is used, with the hot melt pressure controlled at less than 0.35 MPa. During laying, the molding pressure is monitored in real time and the microcapsule rupture trigger threshold is dynamically adjusted, and the resin viscosity change is controlled in conjunction with the process.

[0015] This invention provides a method for preparing prepreg based on smart responsive resin and gradient distribution. It has the following beneficial effects:

[0016] 1. Through the synergistic effect of intelligent responsive resin system and gradient distribution design, the prepreg has the ability to adjust viscosity in response to both temperature and pressure. It can dynamically adapt to the stress changes in the molding process of complex curved surfaces, effectively avoid wrinkle defects in areas of abrupt curvature change, significantly improve the draping performance of the prepreg in the molding of complex structures, and ensure the surface flatness and overall consistency of the molded structure.

[0017] 2. The components of the intelligent responsive resin work synergistically. The matrix resin provides stable mechanical properties and bonding effect, while functional additives optimize temperature response characteristics, mechanical strength and stability. Combined with the resin gradient distribution, it achieves precise matching of material properties, broadens the adaptability range of prepreg to different molding process parameters, and enhances the flexibility and adaptability of process applications.

[0018] 3. The gradient distribution design enables the rational allocation of resin in different regions of the prepreg. Combined with the precise response mechanism of the microencapsulated diluent, it reduces material waste and performance redundancy during the molding process, while improving the batch-to-batch performance stability of the prepreg. This provides reliable technical support for large-scale industrial production, taking into account both product quality consistency and economic efficiency in production applications. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating the preparation process of the present invention. Detailed Implementation

[0020] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Please see the appendix Figure 1 This invention provides a method for preparing a prepreg based on a smart responsive resin and a gradient distribution.

[0022] Example 1: Prepreg for satellite fairing (basic formulation + standard gradient)

[0023] Raw material ratio (parts by weight): 100 parts bisphenol A epoxy resin, 15 parts polycaprolactone-epoxy graft copolymer, 5 parts microencapsulation diluent (TMPTA as core material, polyurea wall material, particle size 40μm, rupture threshold 0.3MPa), and 0.8 parts surface epoxy modified SiO2 nanoparticles (particle size 20nm).

[0024] Gradient parameters: The resin content gradually increases from 31% in the middle to 45% on both sides, with a gradient slope of 5% / cm.

[0025] Preparation process: Resin tank temperature 40±1℃, roller pressure 0.03MPa, prepreg molding speed 1.5m / min; hot melt processing pressure 0.2MPa; laying temperature 40℃, molding pressure 0.3MPa, curing program 120℃ / 2h+180℃ / 3h.

[0026] Example 2: Prepreg for conical casing (high toughness formulation + high slope gradient)

[0027] Raw material ratio (parts by weight): 100 parts AG80 epoxy resin, 20 parts polycaprolactone-epoxy graft copolymer, 6 parts microencapsulation diluent (TMPTA+dibutyl phthalate composite core material, polyurea wall material, particle size 50μm, rupture threshold 0.35MPa), 1.2 parts surface epoxy modified SiO2 nanoparticles (particle size 20nm), 30 parts DDS curing agent, and 10 parts rubber toughening agent.

[0028] Gradient parameters: The resin content gradually increases from 30% in the middle to 50% on both sides, with a gradient slope of 10% / cm.

[0029] Preparation process: Resin tank temperature 40±1℃, roller pressure 0.03MPa, prepreg molding speed 1.2m / min; hot melt processing pressure 0.3MPa; laying temperature 40℃, molding pressure 0.5MPa, curing program 120℃ / 2h+180℃ / 3h.

[0030] Example 3: Prepreg for leading edge of aircraft wings (low-temperature adapted formula + low slope gradient)

[0031] Raw material ratio (parts by weight): 100 parts bisphenol A epoxy resin, 10 parts polycaprolactone-epoxy graft copolymer, 4 parts microencapsulation diluent (styrene core material, polyurea wall material, particle size 20μm, rupture threshold 0.25MPa), and 0.5 parts surface epoxy modified SiO2 nanoparticles (particle size 20nm).

[0032] Gradient parameters: The resin content gradually increases from 30% in the middle to 42% on both sides, with a gradient slope of 3% / cm.

[0033] Preparation process: Resin tank temperature 38±1℃, roller pressure 0.02MPa, prepreg molding speed 1.8m / min; hot melt processing pressure 0.15MPa; laying temperature 35℃, molding pressure 0.25MPa, curing program 110℃ / 3h+170℃ / 4h.

[0034] Example 4: Prepreg for aerospace engine nozzles (composite diluent + differentiated microcapsule density)

[0035] Raw material ratio (parts by weight): 100 parts of bisphenol A+AG80 composite epoxy resin (mass ratio 1:1), 18 parts of polycaprolactone-epoxy graft copolymer, 5 parts of microencapsulation diluent (TMPTA+styrene composite core material, polyurea wall material, particle size 30μm, rupture threshold 0.28MPa), and 1.0 part of surface epoxy-modified SiO2 nanoparticles (particle size 20nm).

[0036] Gradient parameters: The resin content gradually increases from 32% in the middle to 48% on both sides, with a gradient slope of 7% / cm; the microcapsule density in the curvature abrupt region is 30% higher than that in the gentler region.

[0037] Preparation process: Resin tank temperature 41±1℃, roller pressure 0.04MPa, prepreg molding speed 1.4m / min; hot melt processing pressure 0.25MPa; laying temperature 42℃, molding pressure 0.4MPa, curing program 125℃ / 2.5h+185℃ / 2.5h.

[0038] II. Comparative Examples (4 examples)

[0039] Comparative Example 1: Traditional homogeneous resin prepreg (no gradient + no smart response)

[0040] Raw material ratio (parts by weight): 100 parts bisphenol A epoxy resin, 5 parts common diluent (TMPTA), and 0.8 parts SiO2 nanoparticles.

[0041] Key parameters: uniform resin content of 38% (no gradient), no polycaprolactone-epoxy graft copolymer, and no microencapsulation design.

[0042] Preparation process: conventional hot melt method, hot melt pressure 0.3MPa, laying temperature 40℃, molding pressure 0.3MPa, curing program 120℃ / 2h + 180℃ / 3h.

[0043] Comparative Example 2: Gradient-distributed prepreg only (without smart-response resin)

[0044] Raw material ratio (parts by weight): 100 parts bisphenol A epoxy resin, 5 parts common diluent (TMPTA), and 0.8 parts surface epoxy modified SiO2 nanoparticles.

[0045] Key parameters: Gradient parameters are the same as in Example 1 (31% in the middle → 45% on both sides, slope 5% / cm), without polycaprolactone-epoxy graft copolymer, and without microencapsulation design.

[0046] Preparation process: Same as in Example 1.

[0047] Comparative Example 3: Smart Response Resin Prepreg Only (No Gradient Distribution)

[0048] Raw material ratio (parts by weight): Same as Example 1 (including smart response resin system).

[0049] Key parameter: Uniform resin content 38% (no gradient).

[0050] Preparation process: Same as in Example 1.

[0051] Comparative Example 4: Inferior microcapsules + incorrect gradient prepreg (parameters deviate from the scope of the invention)

[0052] Raw material ratio (parts by weight): 100 parts bisphenol A epoxy resin, 8 parts polycaprolactone-epoxy graft copolymer (below the scope of the invention), 3 parts microencapsulation diluent (wall material is gelatin, particle size 60μm, rupture threshold 0.4MPa) (below the scope of the invention), and 0.4 parts surface epoxy modified SiO2 nanoparticles (below the scope of the invention).

[0053] Key parameters: The resin content decreases from 40% in the middle to 30% on both sides (reverse gradient), with a gradient slope of 12% / cm (outside the scope of the invention).

[0054] Preparation process: Same as in Example 1.

[0055] III. Performance Test Results and Comparison Tables

[0056] Test item description:

[0057] Pleat height: measured using a 150mm diameter hemispherical mold, unit: mm;

[0058] Surface Adhesion Rate: The ratio of the adhesion area to the theoretical area after complex curved surface molding, expressed in % (%).

[0059] Droop coefficient: Characterizes the ability of prepreg to adapt to curved surfaces; the closer the value is to 1, the better.

[0060] Inter-batch sagging coefficient variation: coefficient of variation of test results from 10 batches of samples, in %

[0061] Installation efficiency: The percentage reduction in time compared to the traditional method (Comparative Example 1), in units.

[0062] The test results are shown in Table 1 below:

[0063]

[0064] Table 1 (Comparison of performance test results of prepreg based on smart response resin and gradient distribution with control samples)

[0065] As shown in Table 1:

[0066] Wrinkle height: The wrinkle height of Examples 1-4 is ≤0.10mm, which is much lower than that of Comparative Example 1 (1.35mm) and Comparative Example 4 (0.88mm), and better than that of Comparative Example 2 (0.62mm) with only gradient distribution and Comparative Example 3 (0.45mm) with only smart responsive resin. This proves that the synergistic effect of smart responsive resin and gradient distribution can effectively suppress wrinkle formation.

[0067] Surface fit rate: The fit rate of the examples is ≥98.8%, and that of the comparative examples is ≤94.7%, which shows that the formulation and gradient design of the present invention can better adapt the prepreg to complex curved surfaces.

[0068] Droop coefficient and stability: The drape coefficient of the example is ≥0.97 and the batch-to-batch fluctuation is ≤1.5%, which is significantly better than the comparative example (drape coefficient ≤0.89 and fluctuation ≥2.8%), reflecting the product quality stability.

[0069] Installation efficiency: The efficiency of the example is improved by 40%-58%, while that of the comparative example is improved by ≤30%, which proves that the process of the present invention has stronger adaptability and can improve production efficiency.

[0070] In summary, the data in the table fully demonstrates that the present invention, through the synergistic design of the intelligent responsive resin system and gradient distribution, is significantly superior to existing technologies and solutions that deviate from the scope of the invention in terms of drape, surface adaptability, quality stability, and production efficiency.

[0071] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for preparing a prepreg based on a smart-response resin and a gradient distribution, characterized in that, Includes the following steps: The smart responsive resin is prepared according to the specified weight ratio, coated onto a fiber substrate in a gradient distribution, and prepreg is obtained by prepreg molding. The smart responsive resin comprises 100 parts of bifunctional and multifunctional epoxy resin, 10-20 parts of polycaprolactone-epoxy graft copolymer, 4-6 parts of microencapsulation diluent, and 0.5-1.2 parts of surface epoxy-modified SiO2 nanoparticles. The bifunctional and multifunctional epoxy resin is bisphenol A epoxy resin or AG80 epoxy resin. The microencapsulated diluent is formed by encapsulating the diluent within microcapsules. The wall material of the microcapsules is polyurea, with a wall thickness of 1.5-2.5 μm, a particle size of 20-50 μm, and a rupture threshold of 0.25-0.35 MPa. The gradient distribution specifically refers to the gradual increase in the content of smart responsive resin from the middle to both sides in the width direction of the prepreg, with the resin content in the middle region being 30% and the resin content in the two side regions being 45-50%, and the gradient slope being controlled at 3-10% / cm.

2. The preparation method according to claim 1, characterized in that, The particle size of the surface epoxy-modified SiO2 nanoparticles is 20 nm.

3. The preparation method according to claim 1, characterized in that, The number-average molecular weight of the polycaprolactone-epoxy graft copolymer is 4000-6000.

4. The preparation method according to claim 1, wherein the diluent is one or more combinations of trimethylolpropane triacrylate, dibutyl phthalate, and styrene.

5. The preparation method according to claim 1, characterized in that, During the prepreg molding process, the resin bath temperature is controlled at 40±1℃, the pressure in the roller pressing zone is set to 0.03MPa, and the prepreg molding speed is controlled at 1.5m / min.

6. The preparation method according to claim 1, characterized in that, The fiber substrate's orientation is adjusted synchronously with the resin gradient distribution. The first bending section corresponds to a 34% resin area with a 0° orientation, the second bending section corresponds to a 36% resin area with a +15° orientation, and the outlet section corresponds to a 38% resin area with a +30° orientation.

7. The preparation method according to claim 1, characterized in that, During the preparation process, the microcapsule density was set according to the stress characteristics of different regions of the prepreg, and the microcapsule density in the region of abrupt curvature change was higher than that in the region of gentle curvature change.

8. The preparation method according to claim 1, characterized in that, After prepreg molding, the product is processed by hot melt method, with the hot melt pressure controlled at less than 0.35MPa.

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