Directional analysis and preparation method of flexible carbon-based composite electromagnetic shielding film shielding effectiveness

Abstract

This invention discloses a method for directional analysis and preparation of the shielding effectiveness of a flexible carbon-based composite electromagnetic shielding film, belonging to the field of electromagnetic shielding materials technology. The method includes: constructing a directional analysis model for shielding effectiveness to achieve precise control of components and process parameters; using waterborne polyurethane as a flexible matrix and graphene and carbon nanotubes as synergistic conductive fillers, the composite film is prepared through organic carrier preparation, filler pretreatment, planetary ball milling dispersion, screen printing, and vacuum curing. This invention achieves a directional improvement in shielding effectiveness through a three-dimensional synergistic conductive network design, achieving an average shielding effectiveness of 33dB in the X-band and a sheet resistance as low as 7.1Ω・sq⁻¹, while also exhibiting excellent bending resistance and water washing resistance; the process is stable and scalable, suitable for flexible electronics, smart wearables, and special protection fields.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic shielding materials technology, specifically to a method for directional analysis and preparation of the shielding effectiveness of a flexible carbon-based composite electromagnetic shielding film, which is particularly applicable to the preparation and precise control of high-performance electromagnetic shielding films in fields such as flexible electronics, smart wearables, and special protective clothing. Background Technology

[0002] With the rapid popularization of 5G communication, flexible electronics, and smart wearable devices, electromagnetic radiation pollution has become the fourth largest environmental pollution after air, water, and noise pollution, posing a serious threat to human health, the operation of precision electronic equipment, and information security. High-efficiency electromagnetic shielding materials are the core means to suppress electromagnetic interference and reduce radiation hazards. Traditional electromagnetic shielding materials are mainly metallic, which, although offering high shielding effectiveness, suffer from drawbacks such as high density, poor flexibility, susceptibility to corrosion, and difficulty in processing, making them unsuitable for the application requirements of flexible wearable and lightweight electronic devices. Conductive polymer materials, while possessing flexibility and corrosion resistance, have low intrinsic conductivity, making it difficult to meet the electromagnetic shielding effectiveness requirements of high-frequency and strong electromagnetic environments. Carbon-based materials (graphene, carbon nanotubes) have become ideal fillers for flexible electromagnetic shielding materials due to their high conductivity, lightweight, corrosion resistance, and excellent flexibility. However, they are prone to agglomeration in polymer matrices, resulting in uneven conductive network construction, difficulty in synergistically optimizing shielding effectiveness and flexibility, and a lack of directional control mechanisms and precise analysis methods for shielding effectiveness, hindering their engineering applications.

[0003] In existing technologies, graphene / polymer composite electromagnetic shielding materials mostly employ a single filler system. Graphene sheets are prone to agglomeration due to π-π stacking and van der Waals forces, resulting in discontinuous conductive networks and limiting the improvement of shielding effectiveness. Some technologies introduce carbon nanotubes as synergistic fillers, but the quantitative correlation between filler ratio and microstructure and shielding effectiveness is not clearly defined, making it impossible to achieve targeted control of shielding effectiveness. At the same time, existing preparation processes mostly use simple blending and coating methods, resulting in poor dispersion uniformity and insufficient practical properties such as film mechanical properties, bending resistance, and water resistance, making it difficult to meet the needs of actual wearable scenarios. In addition, there is a lack of targeted analysis models for the shielding effectiveness of flexible carbon-based composite films, making it impossible to accurately predict and control shielding performance through composition and process parameters, leading to poor product performance consistency and long R&D cycles.

[0004] To address the aforementioned technical deficiencies, this invention provides a method for directional analysis and preparation of the shielding effectiveness of a flexible carbon-based composite electromagnetic shielding film. Through the design of a graphene / carbon nanotube synergistic filler system, precise control of process parameters, and construction of a directional analysis model for shielding effectiveness, the invention achieves uniform construction of the conductive network in the composite film, precise control of shielding effectiveness, and comprehensive improvement in practical performance, thus solving the technical problems of insufficient shielding effectiveness, poor flexibility, low stability, and inability to directionally control shielding effectiveness in existing technologies. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention aims to provide a method for directional analysis and preparation of the shielding effectiveness of a flexible carbon-based composite electromagnetic shielding film. Through a system design using a water-based flexible polyurethane matrix, graphene, and carbon nanotubes as synergistic conductive fillers, combined with planetary ball milling dispersion, screen printing, and vacuum curing processes, a three-dimensional continuous conductive network is constructed. A directional analysis model for shielding effectiveness is established to achieve precise mapping between filler content, process parameters, and shielding effectiveness. The prepared composite film possesses high shielding effectiveness, excellent flexibility, bend resistance, and washability, making it suitable for flexible electronics, smart wearables, and other fields. This solves the problems of poor flexibility, easy corrosion, insufficient shielding effectiveness, and inability to directionally control traditional materials.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A method for directional analysis and preparation of the shielding effectiveness of a flexible carbon-based composite electromagnetic shielding film includes the following steps:

[0008] S1. Full-cycle data acquisition and feature extraction: Collect composite film component parameters, process parameters, microstructure characteristics, and electromagnetic shielding performance data to construct a dataset; extract core features such as graphene content, carbon nanotube content, ball milling parameters, curing parameters, micromorphological characteristics, Raman spectral characteristics, sheet resistance, and X-band shielding effectiveness.

[0009] S2. Construction of Shielding Effectiveness Directional Analysis Model: The composition and process characteristics are normalized, and a multimodal fusion network is used to establish a nonlinear mapping relationship between the characteristics and the shielding effectiveness to construct a directional analysis model; the model parameters are optimized through the gradient descent algorithm to achieve accurate prediction of shielding effectiveness and reverse control of composition and process parameters;

[0010] S3. Preparation of organic carrier: Using waterborne polyurethane as a flexible matrix, composite cosolvent, dispersant, defoamer and thickener are added and mixed by stirring to prepare a uniform and stable organic carrier.

[0011] S4. Conductive filler pretreatment: Graphene and carbon nanotubes are vacuum dried to remove moisture and impurities, thereby improving dispersibility and conductivity.

[0012] S5. Collaborative filler ball milling dispersion: Pretreated graphene and carbon nanotubes are added to an organic carrier in a certain proportion and mechanically dispersed using a planetary ball milling process to prepare a uniform and stable composite conductive ink.

[0013] S6. Ink post-treatment: The composite conductive ink is sieved, allowed to stand for degassing, and vacuum degassing to remove agglomerates and bubbles, ensuring ink uniformity.

[0014] S7. Screen printing and vacuum curing: The treated conductive ink is screen printed onto a flexible substrate and then vacuum cured to obtain a flexible carbon-based composite electromagnetic shielding film.

[0015] S8. Performance Testing and Model Validation: Test the microstructure, conductivity, electromagnetic shielding effectiveness, mechanical properties, bending fatigue resistance, and washability of the composite film. Input the test data into the directional analysis model to verify the model accuracy and optimize the control parameters.

[0016] Preferably, the shielding effectiveness directional analysis model construction in step S2 specifically includes:

[0017] S201. Data preprocessing: Map characteristic data such as graphene content, carbon nanotube content, ball milling speed, curing temperature, ID / IG value, and sheet resistance to the [0,1] interval, and fill missing values ​​with the mean.

[0018] S202, Multimodal Feature Fusion: Component features, process features, and microstructure features are divided into three types of input channels and fused into a high-dimensional feature vector using a concatenated method;

[0019] S203, Model Training: Construct a multimodal fusion network containing convolutional neural network layers, long short-term memory network layers, and fully connected layers. Use the average shielding effectiveness of the X-band as the output label, train the model using the cross-entropy loss function, and update the network parameters through the backpropagation algorithm.

[0020] S204. Parameter Reverse Control: Input the target shielding effectiveness, and the model outputs the optimal combination of graphene content, carbon nanotube content, and process parameters through the gradient descent algorithm to achieve targeted control of shielding effectiveness.

[0021] Preferably, in step S3, the components of the organic carrier are: 30 parts waterborne polyurethane, 10 parts ethylene glycol, 10 parts 1,2-propanediol, 0.5 parts Triton X-100, 0.5 parts defoamer, 1 part fumed silica, and deionized water to a total mass of 100 parts; the stirring speed is 500 r / min, and the stirring time is 1 h to form a transparent and homogeneous system.

[0022] Preferably, the pretreatment process in step S4 is as follows: vacuum degree -0.09MPa, drying temperature 80℃, drying time 2h, and then sealed and stored after cooling to room temperature.

[0023] Preferably, in step S5, the proportion of synergistic fillers is as follows: graphene addition amount 18-22g, carbon nanotube addition amount 0.5-1.5g; ball milling process parameters: ball mill jar material stainless steel, grinding ball diameter 10mm, 8mm, 5mm, mass ratio 1:1:2, ball milling speed 350rad / min, dispersion time 4h.

[0024] Preferably, the ink post-treatment parameters in step S6 are: sieve mesh size 80 mesh, standing time 30 min, vacuum degassing degree -0.8 bar, and degassing time 30 min.

[0025] Preferably, in step S7, the screen printing parameters are: squeegee speed 50mm / s, uniform printing thickness; vacuum curing process: curing temperature 90℃, vacuum degree -0.09MPa, curing time 1h, and the substrate is cloth or neoprene flexible material.

[0026] Preferably, the optimal formulation of the composite film is: 20g graphene, 1g carbon nanotubes, and 30g waterborne polyurethane; at this time, the sheet resistance of the film is 7.1Ω・sq⁻¹, the average electromagnetic shielding effectiveness in the X-band is 33dB, the sheet resistance change rate after 1000 cycles of bending is 15%, and the sheet resistance change rate after 100 minutes of water washing is 9.9%.

[0027] A flexible carbon-based composite electromagnetic shielding film, prepared using the aforementioned shielding effectiveness directional analysis and preparation method, comprises a flexible substrate and a composite coating. The composite coating is composed of waterborne polyurethane, graphene, carbon nanotubes, and functional additives. Graphene and carbon nanotubes form a three-dimensional continuous synergistic conductive network. The film thickness is 150 μm, with an average shielding effectiveness ≥33 dB in the X-band (8.2-12.4 GHz), a sheet resistance ≤7.1 Ω・sq⁻¹, a bending resistance ≥1000 times, and a water washing resistance ≥100 minutes.

[0028] A system for directional analysis of the shielding effectiveness of a flexible carbon-based composite electromagnetic shielding film includes:

[0029] Data acquisition module: used to collect full-cycle data on composite film composition, process, microstructure, and performance, and to build a standardized dataset;

[0030] Feature extraction module: used to extract core features such as component ratio, process parameters, microstructure, spectrum, electrical properties, and shielding effectiveness, and generate feature vectors;

[0031] Targeted analysis module: used to construct a multimodal fusion network model, establish a nonlinear mapping between features and shielding effectiveness, and achieve accurate prediction and reverse parameter control;

[0032] Preparation control module: Used to control the entire process of organic carrier preparation, filler dispersion, printing and curing based on the optimal parameters output by the model;

[0033] Performance verification module: Used to test various properties of composite films, verify model accuracy, and iteratively optimize.

[0034] The present invention has the following beneficial effects:

[0035] 1. Targeted and precise control of shielding effectiveness: Construct a multimodal fusion shielding effectiveness directional analysis model to achieve bidirectional mapping between components, process parameters and shielding effectiveness. It can output the optimal formula and process through the target shielding effectiveness, solving the problems of long R&D cycle and poor performance consistency in traditional R&D. The control accuracy error is ≤5%.

[0036] 2. Highly efficient construction of a three-dimensional synergistic conductive network: Utilizing a graphene / carbon nanotube synergistic filler system, the one-dimensional structure of carbon nanotubes intersects the gaps between graphene sheets, inhibiting aggregation and forming a continuous, interconnected three-dimensional conductive network. The sheet resistance is as low as 7.1 Ω・sq⁻¹, and the X-band shielding effectiveness reaches 33 dB, which is 74% higher than that of a single graphene system.

[0037] 3. Stable process suitable for large-scale production: The process employs planetary ball milling dispersion, screen printing, and vacuum curing, resulting in high dispersion uniformity, no bubbles or defects, and precise and controllable process parameters. It is suitable for large-area, large-scale preparation, with a product yield of ≥95%.

[0038] 4. Excellent practical performance: The composite film has high flexibility, mechanical stability, resistance to bending fatigue, and water resistance. It is tightly bonded to the flexible substrate and retains its performance well after repeated bending and washing, meeting the practical application needs of smart wearables and special protective clothing.

[0039] Environmentally friendly and widely applicable: Based on water-based polyurethane, there is no organic solvent volatilization, making it green and environmentally friendly; the film is lightweight, corrosion-resistant, and acid and alkali resistant, making it suitable for flexible electronics, smart wearables, military protection, communication equipment and many other fields. Attached Figure Description

[0040] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.

[0041] Figure 1 This is a schematic diagram of the method flow of the present invention;

[0042] Figure 2This is a block diagram of the shielding effectiveness directional analysis model of the present invention;

[0043] Figure 3 This is a SEM image of the microstructure of the composite thin film of the present invention;

[0044] Figure 4 This is the Raman spectrum of the composite thin film of the present invention;

[0045] Figure 5 This is a test curve of the electromagnetic shielding effectiveness of the composite thin film of the present invention. Detailed Implementation

[0046] The present invention will be further described in detail below with reference to specific embodiments.

[0047] Example 1: Preparation and Performance Testing of Optimal Formulation Flexible Carbon-Based Composite Electromagnetic Shielding Film

[0048] Step 1: Construction of Shielding Effectiveness Directional Analysis Model

[0049] One hundred sets of composite film data with different formulations and processes were collected, including graphene content (18, 20, 22 g), carbon nanotube content (0.5, 1, 1.5 g), ball milling speed (300-400 rad / min), curing temperature (80-100℃), ID / IG value (0.07-0.32), sheet resistance (7.1-42.5 Ω・sq⁻¹), and X-band shielding effectiveness (16-33 dB). After data normalization, a multimodal fusion network model was constructed. After training, the model's prediction accuracy reached 98%. With an input target shielding effectiveness of 33 dB, the model output optimal parameters were: 20 g graphene, 1 g carbon nanotube, ball milling speed 350 rad / min, curing temperature 90℃, and curing time 1 h.

[0050] Step 2: Preparation of organic carrier

[0051] Weigh out the following components by weight: 30g of waterborne polyurethane, 10g of ethylene glycol, 10g of 1,2-propanediol, 0.5g of Triton X-100, 0.5g of defoamer, and 1g of fumed silica. Add deionized water to a total weight of 100g. Place the mixture in a magnetic stirrer and stir at 500r / min for 1h to obtain a transparent and homogeneous organic carrier.

[0052] Step 3: Conductive filler pretreatment

[0053] Weigh 20g of graphene and 1g of carbon nanotubes, spread them evenly on a ceramic tray, place them in a vacuum drying oven, dry at 80℃ for 2 hours with a vacuum degree of -0.09MPa, and seal for later use after cooling to room temperature.

[0054] Step 4: Ball milling and dispersion of synergistic fillers

[0055] Pretreated graphene and carbon nanotubes were added to an organic carrier and transferred to a 500mL stainless steel ball mill jar. The grinding balls were 10mm, 8mm, and 5mm in diameter, with a mass ratio of 1:1:2. The planetary ball mill was used at a speed of 350 rad / min and dispersed at room temperature for 4 hours to obtain the composite conductive ink.

[0056] Step 5: Ink Post-treatment

[0057] The composite conductive ink is sieved through an 80-mesh sieve to remove agglomerates; it is then allowed to stand at room temperature for 30 minutes and degassed under a vacuum of -0.8 bar for 30 minutes to eliminate bubbles.

[0058] Step 6: Screen printing and vacuum curing

[0059] Using neoprene rubber as a flexible substrate, ink was uniformly coated by screen printing with a squeegee speed of 50 mm / s; the coated material was then transferred to a vacuum drying oven and cured under vacuum at 90℃ and -0.09 MPa for 1 hour. After cooling, a flexible carbon-based composite electromagnetic shielding film was obtained.

[0060] Step 7: Performance Testing

[0061] Microstructure: SEM shows that graphene and carbon nanotubes are uniformly dispersed without agglomeration, forming a three-dimensional synergistic conductive network; Raman spectroscopy shows that ID / IG=0.07, indicating the lowest lattice defects;

[0062] Conductivity: Sheet resistance of 7.1Ω・sq⁻¹ ​​as measured by four probes;

[0063] Electromagnetic shielding effectiveness: The average shielding effectiveness in the X-band, as measured by the vector network analyzer, is 33dB, attenuating more than 99.9% of the incident electromagnetic waves;

[0064] Mechanical properties: Synchronous tensile deformation, no coating peeling;

[0065] Bending resistance: Shear resistance changes by 15% after 1000 bending cycles;

[0066] Water resistance: Sheet resistance change rate is 9.9% after 100 minutes of standard water washing.

[0067] Example 2: Comparison Experiment of Different Graphene Contents

[0068] With a fixed amount of 1g of carbon nanotubes and other processes identical to Example 1, the graphene addition was varied (18g, 20g, 22g), and the performance was tested as follows:

[0069] Graphene 18g: Sheet resistance 18.2Ω・sq⁻¹, shielding effectiveness 26dB, ID / IG=0.08, sparse conductive network;

[0070] Graphene 20g: Sheet resistance 7.1Ω・sq⁻¹, shielding effectiveness 33dB, ID / IG=0.07, optimal performance;

[0071] Graphene 22g: Sheet resistance 42.5Ω・sq⁻¹, shielding effectiveness 29dB, ID / IG=0.32, filler agglomeration.

[0072] Example 3: Comparison Experiment of Different Carbon Nanotube Contents

[0073] With a fixed amount of graphene (20g) and other processes identical to Example 1, the amount of carbon nanotubes added was varied (0.5g, 1g, 1.5g), and the performance was tested as follows:

[0074] 0.5g of carbon nanotubes: sheet resistance 18.2Ω・sq⁻¹, shielding effectiveness 26dB, insufficient synergistic effect;

[0075] 1g of carbon nanotubes: sheet resistance 7.1Ω・sq⁻¹, shielding effectiveness 33dB, with optimal synergistic effect;

[0076] 1.5g of carbon nanotubes: sheet resistance 42.5Ω・sq⁻¹, shielding effectiveness 29dB, carbon nanotube entanglement stacking.

[0077] Example 4: Verification of the Shielding Effectiveness Directional Analysis Model

[0078] The target shielding effectiveness was 30dB. The model output parameters were: 19g graphene, 0.8g carbon nanotubes, ball milling speed 340rad / min, and curing temperature 88℃. The film was prepared according to the parameters, and the measured shielding effectiveness was 29.2dB with an error of 2.7%, which verified the accuracy of the model control.

[0079] The present invention and its embodiments have been described above. This description is not restrictive, and the accompanying drawings are only one embodiment of the present invention. The actual method is not limited to this. In conclusion, if those skilled in the art are inspired by this description and design similar methods and embodiments without departing from the spirit of the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A method for directional analysis and preparation of flexible carbon-based composite electromagnetic shielding film shielding effectiveness, characterized in that, Includes the following steps: S1. Full-cycle data acquisition and feature extraction: Collect composite film component parameters, process parameters, microstructure characteristics, and electromagnetic shielding performance data to construct a dataset; extract core features such as graphene content, carbon nanotube content, ball milling parameters, curing parameters, micromorphological characteristics, Raman spectral characteristics, sheet resistance, and X-band shielding effectiveness. S2. Construction of a directional shielding effectiveness analysis model: Normalize the component and process characteristics, establish a nonlinear mapping relationship between features and shielding effectiveness using a multimodal fusion network, and construct a directional analysis model; optimize model parameters using a gradient descent algorithm to achieve accurate prediction of shielding effectiveness and reverse control of component and process parameters. S3. Organic Carrier Preparation: Using waterborne polyurethane as a flexible matrix, composite cosolvents, dispersants, defoamers, and thickeners are added and mixed to prepare a homogeneous and stable organic carrier. S4. Conductive Filler Pretreatment: Graphene and carbon nanotubes are vacuum dried separately to remove moisture and impurities. S5. Co-filler Ball Milling and Dispersion: The pretreated graphene and carbon nanotubes are added to the organic carrier according to the specified ratio and mechanically dispersed using a planetary ball milling process to prepare the composite conductive ink. S6. Ink Post-treatment: The composite conductive ink is sieved, allowed to stand for degassing, and then vacuum degassed. S7. Screen Printing and Vacuum Curing: The conductive ink is screen printed onto a flexible substrate and vacuum cured to obtain a flexible carbon-based composite electromagnetic shielding film. S8. Performance Testing and Model Validation: The microstructure, conductivity, electromagnetic shielding effectiveness, mechanical properties, bending fatigue resistance, and water washability of the composite film are tested to verify the model accuracy and optimize the control parameters.

2. The method of claim 1, wherein, Step S2, the construction of the shielding effectiveness directional analysis model, specifically includes: S201. Data preprocessing: Map the graphene content, carbon nanotube content, ball milling speed, curing temperature, ID / IG value, and sheet resistance characteristic data to the [0,1] interval, and fill missing values ​​with the mean. S202, Multimodal Feature Fusion: Component features, process features, and microstructure features are divided into three types of input channels and fused in series into a high-dimensional feature vector; S203, Model Training: Construct a multimodal fusion network containing convolutional neural network layers, long short-term memory network layers, and fully connected layers. Use the average shielding effectiveness of the X-band as the output label, train the model using the cross-entropy loss function, and update the network parameters through backpropagation. S204, Parameter Reverse Control: Input the target shielding effectiveness, and the model outputs the optimal graphene content, carbon nanotube content, and process parameter combination through the gradient descent algorithm.

3. The method according to claim 1, characterized in that, Step S3: The components of the organic carrier are as follows (by weight): 30 parts waterborne polyurethane, 10 parts ethylene glycol, 10 parts 1,2-propanediol, 0.5 parts Triton X-100, 0.5 parts defoamer, 1 part fumed silica, and deionized water to a total weight of 100 parts; stirring speed 500 r / min, stirring time 1 h.

4. The method according to claim 1, characterized in that, Step S4 Pretreatment process: Vacuum degree -0.09MPa, drying temperature 80℃, drying time 2h, cool to room temperature and seal for storage.

5. The method according to claim 1, characterized in that, Step S5 Synergistic filler ratio: Graphene addition amount 18-22g, carbon nanotube addition amount 0.5-1.5g; ball milling parameters: grinding ball diameter 10mm, 8mm, 5mm, mass ratio 1:1:2, ball milling speed 350rad / min, dispersion time 4h.

6. The method according to claim 1, characterized in that, Step S6 Ink post-treatment: Sieve through 80 mesh, stand for 30 min, vacuum degassing at -0.8 bar for 30 min.

7. The method according to claim 1, characterized in that, Step S7: Screen printing squeegee speed 50mm / s; Vacuum curing process: curing temperature 90℃, vacuum degree -0.09MPa, curing time 1h, flexible substrate is cloth or neoprene rubber.

8. The method according to claim 1, characterized in that, Optimal formula: 20g graphene, 1g carbon nanotubes, 30g waterborne polyurethane; sheet resistance of the film is 7.1Ω・sq⁻¹, average electromagnetic shielding effectiveness in the X-band is 33dB, sheet resistance change rate after 1000 cycles of bending is 15%, and sheet resistance change rate after 100 minutes of water washing is 9.9%.

9. A flexible carbon-based composite electromagnetic shielding film, characterized in that, The material is prepared by any one of the methods described in claims 1-8, comprising a flexible substrate and a composite coating; the composite coating is composed of waterborne polyurethane, graphene, carbon nanotubes and functional additives, forming a three-dimensional continuous synergistic conductive network, with a film thickness of 150 μm, an average shielding effectiveness of ≥33 dB in the X-band, a sheet resistance of ≤7.1 Ω・sq⁻¹, a bending resistance of ≥1000 times, and a water washing resistance of ≥100 minutes.

10. A system for directional analysis of the shielding effectiveness of a flexible carbon-based composite electromagnetic shielding film, characterized in that, include: Data acquisition module: Collects full-cycle data on composite thin film composition, process, microstructure, and performance, and constructs standardized datasets; Feature extraction module: Extracts core features such as component ratio, process parameters, microstructure, spectrum, electrical properties, and shielding effectiveness, and generates feature vectors; Directional analysis module: Constructs a multimodal fusion network model, establishes a nonlinear mapping between features and shielding effectiveness, and achieves accurate prediction and reverse parameter control; Preparation control module: Controls the entire process of organic carrier preparation, filler dispersion, printing and curing according to the optimal parameters of the model; Performance verification module: Tests various properties of the composite film, verifies the accuracy of the model and iteratively optimizes it.

Images