Preparation process of perforated organic silicon foam

Abstract

The invention discloses a preparation process of open-cell organic silicon foam, and aims to solve the problems of non-uniform pore structure, low aperture ratio and difficulty in performance balance in the prior art. The process comprises the following steps: optimizing parameters through bubble nucleation, pore connectivity and a mechanical property model; preparing a composite raw material containing polysiloxane, a fluorine-containing monomer, nano silicon dioxide and hollow microspheres; dynamic pressure circulation and ultrasonic-assisted pre-foaming are adopted; performing staged gradient foaming and curing; and carrying out vacuum post-treatment and plasma surface modification. According to the invention, accurate regulation and control of multi-scale pores are realized, air permeability, mechanical properties and hydrophilicity are significantly improved, heat insulation and high temperature resistance are accidentally improved, process efficiency is improved, by-product emission is reduced, and the method is suitable for the fields of aerospace, filtration and biomedicine.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of silicon foam, in particular to a preparation process of open-cell organic silicon foam. BACKGROUND

[0002] The open-cell organic silicon foam is widely used in the fields of aerospace, electronic industry, filtering material and biomedicine due to excellent high-temperature resistance, flexibility and chemical stability. In the prior art, the preparation process of the open-cell organic silicon foam usually adopts a physical or chemical foaming method, for example, a single foaming agent is decomposed and foamed at high temperature, or air bubbles are introduced through mechanical stirring, and then solidification forming is performed. However, these processes have significant technical problems: the pore structure is non-uniform, the distribution of micropores, mesopores and macropores is difficult to accurately control, and the open-cell rate is low and the pore uniformity is poor. This makes it difficult to achieve an ideal balance between air permeability, mechanical properties and functionality of the foam, limiting its use in high-performance application scenarios.

[0003] In addition, the existing process lacks theoretical guidance and relies on a large number of experimental trial and error to optimize the raw material ratio and process parameters, and has low process efficiency, poor batch consistency, long production cycle and high cost. At the same time, the emission of volatile by-products is high in the traditional foaming process, which does not meet the requirements of green manufacturing. Although some processes attempt to improve the pore structure by adding fillers or adjusting the foaming conditions, the effect is limited, and it is difficult to balance the multi-scale pore distribution, mechanical properties and functionality, resulting in unstable performance of the material under high load or complex environment. Therefore, there is an urgent need for a preparation method that can accurately control the multi-scale pore structure, improve performance, improve process efficiency and reduce environmental impact. SUMMARY

[0004] The application aims to provide a preparation method that can accurately control the multi-scale pore structure, improve performance, improve process efficiency and reduce environmental impact.

[0005] To achieve the above-mentioned purpose, the application provides the following technical scheme: a preparation process of open-cell organic silicon foam, comprising the following steps:

[0006] Step 1: model establishment and parameter optimization, by establishing bubble nucleation and growth model, pore connectivity model and mechanical property prediction model, predicting bubble nucleation rate, open-cell rate and compression strength, integrating to form a multi-scale pore collaborative optimization model, and optimizing raw material ratio, pressure and temperature parameters through numerical simulation;

[0007] Step 2: preparation of a composite raw material system, mixing high molecular weight polysiloxane and fluorosiloxane monomer as a base material, adding surface-modified nanosilica and hollow microspheres as a composite micropore control system, adding a composite foaming agent and a composite catalyst, and mixing in a high-shear mixing device to form a uniform mixture;

[0008] Step 3 dynamic pre-foaming and environmental regulation, in the intelligent pressure control reaction kettle, dynamic pressure cycle and low frequency ultrasonic auxiliary treatment are adopted to induce multi-scale bubble nucleation;

[0009] Step 4 gradient foaming and segmented curing, through the first stage micropore formation, the second stage mesopore expansion and connection, and the third stage structure curing, temperature and pressure gradient control is adopted to form multi-scale pore structure and complete the matrix curing;

[0010] Step 5 post-processing and functional modification, residual gas and by-products are removed in a vacuum environment, plasma surface treatment is adopted to introduce hydrophilic functional groups, and precise molding or numerical control cutting is adopted to form open-cell silicone foam.

[0011] Further, in the present application, the model establishment and parameter optimization in step 1 includes:

[0012] Step 1-1 establishes a bubble nucleation and growth model to predict the bubble nucleation rate per unit volume, which is optimized based on the relationship among surface tension, foaming agent decomposition pressure difference and micropore regulator wetting factor;

[0013] Step 1-2 establishes a pore connectivity model to predict the open-cell rate, which is controlled based on the relationship among dynamic pressure, foaming time and micropore regulator particle size;

[0014] Step 1-3 establishes a mechanical property prediction model to predict the compressive strength, which is optimized based on the relationship among the Young's modulus of the matrix material, the open-cell rate and the average pore diameter;

[0015] Step 1-4 integrates the above models to optimize the micropore regulator ratio, dynamic pressure, foaming time and temperature parameters through numerical simulation.

[0016] Further, in the present application, the specific conditions for preparing the composite raw material system in step 2 include:

[0017] The matrix material includes fluorine-containing siloxane monomer with a mass fraction of 58% and high molecular weight polysiloxane with a molecular weight of 150,000-600,000;

[0018] The composite micropore regulation system includes surface modified nano-silicon dioxide with a mass fraction of 35% and hollow microspheres with a mass fraction of 13%, the nano-silicon dioxide has a particle size of 20-40 nanometers, and the hollow microspheres have a particle size of 15 micrometers.

[0019] Further, in the present application, the specific conditions for preparing the composite raw material system in step 2 also include:

[0020] The composite foaming agent is 1.5-3% azobisdimethyl isobutyronitrile mixed with sodium bicarbonate at a mass ratio of 1:1, and the composite catalyst is 0.3-1.5% platinum-gold catalyst mixed with organic amine catalyst at a mass ratio of 2:1;

[0021] The mixing condition is that the mixing is carried out at 40-50 degrees Celsius for 20-30 minutes in a high-shear mixing device with a rotation speed of 1000-1500 revolutions per minute.

[0022] Further, in the present application, the specific conditions of the dynamic pre-foaming in step 3 and the environmental regulation are as follows:

[0023] In the intelligent pressure control reaction kettle, a dynamic pressure cycle of 0.1-0.6 megapascals is adopted, the cycle frequency is 0.5-1 hertz, nitrogen atmosphere is introduced, and preheating is carried out at 45-65 degrees Celsius for 40-60 minutes;

[0024] Synchronous application of low-frequency ultrasonic wave treatment with a frequency of 20-40 kilohertz and a power of 50-100 watts.

[0025] Further, in the present application, the specific conditions of the gradient foaming and segmented curing in step 4 are as follows:

[0026] First stage: heating at 80-100 degrees Celsius under a micro-pressure of 0.3-0.5 megapascals for 25-35 minutes to form a preliminary open-cell structure dominated by micropores;

[0027] Second stage: heating at 110-130 degrees Celsius under a pressure of 0.5-1.0 megapascals for 15-25 minutes to promote the formation of mesopores and pore connectivity;

[0028] Third stage: curing at 140-160 degrees Celsius under normal pressure for 10-20 minutes with a gradient cooling rate of 2-5 degrees Celsius per minute.

[0029] Further, in the present application, the specific conditions of the post-processing and functional modification in step 5 are as follows:

[0030] Vacuum treatment: treating in a vacuum environment of 0.01-0.03 megapascals for 15-20 minutes;

[0031] Plasma surface treatment: treating in an oxygen atmosphere with a power of 100-200 watts for 15-30 minutes to introduce hydrophilic functional groups;

[0032] Molding: adopting precision molding or numerical control cutting.

[0033] Further, in the present application, the pore structure of the open-cell organic silicone foam includes micropores, mesopores, and macropores.

[0034] Further, in the present application, the micropore aperture is less than 50 microns, accounting for 40-50%; the mesopore aperture is 50-200 microns, accounting for 30-40%; the macropore aperture is 200-500 microns, accounting for 10-20%; and the opening rate reaches 92-95%.

[0035] Further, in the present application, the opening organic silica foam has a compression strength of 1.6-2.2 MPa, a rebound rate of 87-92%, a permeability of 550-650 L / m2 / s, and a surface contact angle of 30-40 degrees.

[0036] Beneficial effects, the technical scheme of the present application has the following technical effects:

[0037] The present application provides a preparation process of an opening organic silica foam, which successfully solves the technical problems of uneven pore structure, low opening rate and difficult performance balance in the background art through model establishment, composite raw material system, dynamic pre-foaming, gradient foaming and segmented curing, and functional post-processing. By using bubble nucleation and growth model, pore connectivity model and mechanical property prediction model, the raw material ratio and process parameters are optimized through numerical simulation to realize the collaborative distribution of micropores, mesopores and macropores, and form a high-opening-rate and uniform pore structure. The composite micropore control system and dynamic pressure cycle, combined with ultrasonic assistance, ensure the uniformity of bubble nucleation and pore connectivity, significantly improve the air permeability, and make the foam suitable for filtration and biomedical fields.

[0038] Meanwhile, the present application enhances the matrix performance by using fluorosilicone monomers, optimizes the pore wall structure and crosslinking network by combining gradient foaming and segmented curing process, so that the foam still maintains excellent compression strength and rebound rate under high opening rate, meeting the needs of high load scenarios. The plasma surface treatment introduces hydrophilic functional groups, significantly improves the surface hydrophilicity and liquid absorption capacity, and expands the application scenarios of liquid filtration and tissue engineering scaffolds. In addition, it is accidentally found that the multi-scale pore structure and dynamic process refine the pore wall microstructure, significantly reduce the thermal conductivity and improve the high temperature resistance, making the foam suitable for high temperature industrial environment and prolonging the service life of the material.

[0039] The model optimization of the present application significantly reduces experimental trial and error, shortens the production cycle, improves batch consistency, enhances process efficiency and stability. Vacuum post-processing and optimized foaming agent dosage effectively reduce the emission of volatile by-products, meeting the requirements of green manufacturing. In summary, the present application breaks through the limitations of the prior art by multi-scale pore regulation, performance optimization and green process design, provides a preparation method of opening organic silica foam with excellent performance, efficient process and environmental friendliness, and provides a new scheme for high-performance material application.

[0040] It should be appreciated that all combinations of the foregoing concepts and additional concepts described in greater detail below (provided such concepts are not mutually inconsistent) are contemplated as being part of the inventive subject matter. For example, a specific embodiment of a particular concept can be combined with an embodiment of another concept to create another embodiment that can not be explicitly described or illustrated. It will be appreciated that various embodiments of the disclosing technology can include one or more of the described aspects.

[0041] The foregoing and other aspects, embodiments and features of the present teachings can be better understood from the following description of the present teachings when considered in connection with the accompanying drawings. The accompanying drawings, which are incorporated herein and illustrate several aspects of the present teachings, serve to explain by way of example, not limitation, various principles and aspects of the present teachings. BRIEF DESCRIPTION OF DRAWINGS

[0042] The drawings are not intended to be to scale. In the drawings, each identical, or nearly identical, component that is illustrated in various figures is represented with a like numeral for clarity. Not all components can be called out in each drawing. Embodiments of various aspects of the present teachings will now be described, by way of example only, with reference to the accompanying drawings in which:

[0043] Figure 1 Flowchart of the present teachings. DETAILED DESCRIPTION

[0044] For a more complete understanding of the present teachings, reference is now made to the following description taken in connection with the accompanying drawings in which:

[0045] Example 1: Preparation of open-cell silicone foam

[0046] Modeling and parameter optimization, bubble nucleation and growth model, pore connectivity model and mechanical property prediction model were established using MATLAB software, and integrated to form a multi-scale pore collaborative optimization model. The specific steps are as follows:

[0047] Bubble nucleation and growth model: based on the decomposition pressure difference of foaming agent, the wetting factor of surface modified nano-silica and the system temperature, the bubble nucleation rate was predicted, and the ratio of nano-silica and hollow microspheres was optimized to 4wt% and 2wt%.

[0048] Bubble nucleation rate model: J: bubble nucleation rate per unit volume, unit is m -3 ·s -1J0: nucleation frequency factor (m -3 ·s v1 ), which is related to the concentration of micropore regulators. Nucleation energy barrier, in J, is calculated by where σ is the surface tension, ΔP is the pressure difference generated by the decomposition of the blowing agent, and f(θ) is the wetting factor of the micropore regulator. B : Boltzmann constant, T is the absolute temperature. The model predicts the bubble nucleation density, optimizes the addition amount of nano-silica and hollow microspheres, and controls the ratio of micropores and mesopores. By adjusting ΔP and f(θ), the initial pore distribution can be accurately designed, and the non-uniformity caused by random pore formation can be reduced.

[0049] The model is based on classical nucleation theory and bubble dynamics, describing the nucleation rate of bubbles in the polysiloxane matrix during foaming. The nucleation rate is determined by the wetting characteristics of the micropore regulator, the pressure difference generated by the decomposition of the blowing agent, and the system temperature. The model predicts the generation rate of bubbles per unit volume by calculating the nucleation energy barrier, thereby optimizing the initial distribution of micropores and mesopores. It can accurately predict the pore distribution and quantitatively predict the nucleation density of micropores and mesopores, optimize the proportion of micropore regulators, and ensure that micropores account for 40-50% and mesopores account for 30-40%. It can reduce experimental trial and error, reduce the number of experiments for raw material ratio by simulating the nucleation process, and reduce optimization costs. It can improve pore uniformity, guide process parameters, and improve pore distribution uniformity.

[0050] The model is based on the regulation of nucleation energy barrier. Bubble nucleation needs to overcome the energy barrier formed by surface tension. Nano-silica reduces the energy barrier due to surface modification, promoting uniform nucleation. Hollow microspheres rupture under the pressure of blowing agent gas, inducing mesopore nucleation and forming multi-scale pores. The model accurately predicts the nucleation point density by quantifying the relationship between surface tension, pressure difference, and wetting factor, preventing pore non-uniformity caused by bubble coalescence. The model considers the effect of temperature on molecular thermal motion and the decomposition rate of the blowing agent, optimizes the pre-foaming temperature, ensures bubble nucleation when the matrix viscosity is moderate, and avoids pore collapse caused by high temperature. Dynamic pressure cycling regulates bubble growth rate through periodic compression, enhancing nucleation uniformity. The model optimizes the nucleation process from the perspectives of thermodynamics and kinetics, significantly improving the accuracy and uniformity of pore distribution, laying a foundation for subsequent connectivity and mechanical properties.

[0051] Pore connectivity model: based on dynamic pressure and foaming time, predicts open cell rate, optimizes dynamic pressure to 0.4 MPa, cycle frequency to 0.8 Hz, and foaming time to 30 minutes (first stage) and 20 minutes (second stage).

[0052] Pore connectivity model: φ c : open cell rate.k c: Connectivity constant, related to micropore regulator particle size and blowing agent decomposition rate. P: Dynamic pressure, P0: Reference pressure. t: Foaming time, t0: Reference time. The model optimizes dynamic pressure cycles and foaming time to ensure 92-95% connectivity of the pores. By adjusting P and t, efficient connectivity of micropores and mesopores is achieved, enhancing air permeability and liquid permeability.

[0053] The model is based on percolation theory, describing the formation of interconnected channels between pores, predicting the open porosity, the proportion of connected pores to total pores. Open porosity is affected by dynamic pressure, foaming time and micropore regulator particle size. The model optimizes process parameters to achieve high open porosity by quantifying the effect of pressure and time on pore wall rupture and connectivity. The model can accurately optimize dynamic pressure and foaming time to keep open porosity at a high level, improving air permeability. By simulating connectivity changes, open porosity fluctuations between batches are reduced, with high batch consistency. High open porosity ensures excellent air permeability and liquid permeability, suitable for filtration and biomedical applications.

[0054] The physical mechanism of pore wall rupture is that during foaming, bubble growth thins the pore wall, and dynamic pressure cycles induce moderate pore wall rupture through periodic stress, forming interconnected channels. The model quantifies the effect of pressure on pore wall stress, optimizing the pressure range to avoid excessive pressure causing pore collapse or insufficient pressure for connectivity. Time-dependent connectivity, foaming time determines the extent of pore wall rupture, the model optimizes the foaming time of the first and second stages through the time parameter, ensuring gradual connectivity of micropores and mesopores. Ultrasonic assistance refines the pore wall structure through micro-vibration, reduces the critical pressure required for rupture, and improves connectivity efficiency. The role of micropore regulators, nano-silica and hollow microspheres, optimizes the formation probability of interconnected channels by regulating bubble spacing and pore wall thickness. The model parameterizes particle size and concentration to guide the ratio of regulators, enhancing connectivity. The model optimizes the pore connectivity process from the perspectives of fluid mechanics and materials mechanics, ensuring high open porosity and low resistance channel formation, improving air permeability and functionality.

[0055] Mechanical property prediction model: Based on the Young's modulus of the matrix, open porosity and average pore size, predict the compressive strength, optimize the temperature gradient to 90℃ (first stage), 120℃ (second stage), 150℃ (third stage).

[0056] Mechanical property prediction model: σ c : Compressive strength. E0: Young's modulus of the matrix material. φ c : Open porosity. n: Structure index, related to pore morphology. d p: average pore size, d0: reference pore size. The model predicts the influence of pore structure on mechanical properties, optimizing the balance between open-cell content and compressive strength. Guiding process parameters adjustment, ensuring compressive strength reaches 1.5-2.0 MPa while maintaining high open-cell content.

[0057] The model is based on the mechanics of porous materials, predicting the compressive strength and resilience of open-cell silicone foam. Compressive strength is related to the Young's modulus of the matrix material, open-cell content, and average pore size. The model optimizes process parameters to balance high open-cell content and high strength by quantifying the influence of pore structure on mechanical properties.

[0058] Guiding gradient foaming parameters, compressive strength reaches 1.6-2.2 MPa, and resilience is high. Achieving performance balance, maintaining excellent mechanical properties at 92-95% high open-cell content, breaking through the strength-porosity contradiction of traditional processes. Predictive results support material design for high-load scenarios. The mechanical contribution of the model's pore structure: micropores provide rigid support through high-density pore walls, enhancing compressive strength; mesopores and macropores absorb stress through flexible deformation of the pore walls, improving resilience. The model optimizes the proportion of micropores through parameterization of porosity and pore size, achieving a balance between strength and elasticity. The chemical mechanism of matrix enhancement: the introduction of fluorosilicone monomers with high-energy fluoralkyl chains enhances molecular chain flexibility and fatigue resistance, improving resilience. Gradient curing optimizes the Si-O-Si cross-linking network, increasing the Young's modulus of the matrix to support high strength. Mechanical optimization of process parameters: the model simulates the exponential decay effect of porosity on strength, guiding gradient foaming temperature and pressure to avoid strength loss due to high porosity. The model optimizes the interaction between pores and the matrix from the perspectives of material mechanics and molecular structure, ensuring significant improvement in mechanical properties at high open-cell content.

[0059] The bubble nucleation rate J above determines the initial pore density, directly affecting the pore connectivity φ c . By optimizing the f(θ) of the micropore regulator and the ΔP of the foaming agent, J can be improved, laying the foundation for high φ c . Pore connectivity φ c serves as a bridge, connecting the nucleation model and the mechanical model. Higher φ c improves air permeability but may reduce σ c . By adjusting P and t, mechanical properties can be maintained at high open-cell content. The mechanical property model optimizes nucleation and connectivity parameters through d p and φ c , ensuring the synergistic optimization of multi-scale pore structure and mechanical properties. The coupling between formulas achieves global optimization of pore distribution, open-cell content, and mechanical properties, significantly reducing pore heterogeneity, improving compressive strength, and improving air permeability, surpassing the random optimization effect of traditional trial-and-error methods.

[0060] Modeling step provides theoretical guidance for process design, and outputs optimized parameters such as micro-pore regulator proportion, pressure, and temperature, which can be directly applied to subsequent steps. The proportion of raw materials and process conditions are adjusted according to the model prediction results in the compounding and foaming step to ensure that the pore distribution and mechanical properties are consistent with the target. The post-processing step verifies the performance predicted by the model, and the closed-loop feedback further optimizes the process. Each step is linked together, and the model and experimental data are mutually verified to ensure the controllability and stability of the process.

[0061] Through numerical simulation, the process parameters are output: micro-pore regulator proportion, nano-silica 4wt%, hollow microspheres 2wt%, dynamic pressure 0.4MPa, temperature gradient 90-150℃.

[0062] Compound raw material system preparation: take 1000g of hydroxyl-terminated polydimethylsiloxane with a molecular weight of 300,000, and add 70g of fluorosilicone monomer with a mass fraction of 7%.

[0063] Compound micro-pore regulator system: add 40g of surface-modified nano-silica with a particle size of 30nm and a mass fraction of 4%, and 20g of hollow microspheres with a particle size of 3μm and a mass fraction of 2%.

[0064] Compound foaming agent: add 20g of azobisisobutyronitrile (AIBN) and sodium bicarbonate with a mass ratio of 1:1 and a mass fraction of 2%.

[0065] Compound catalyst: add 10g of platinum-gold catalyst and organic amine catalyst with a mass ratio of 2:1 and a mass fraction of 1%.

[0066] In a high-shear mixing device, the speed is 1200rpm, and the mixture is mixed at 45℃ for 25 minutes to obtain a uniform mixture.

[0067] Dynamic pre-foaming and environmental regulation: place the mixture in an intelligent pressure-controlled reaction kettle, and under a nitrogen atmosphere, use 0.4MPa dynamic pressure cycle with a frequency of 0.8Hz at 55℃ for 50 minutes. Simultaneously apply 30kHz, 80W low-frequency ultrasonic treatment to induce multi-scale bubble nucleation.

[0068] Gradient foaming and segmented curing: first stage: heat at 90℃, 0.4MPa micro-pressure for 30 minutes to form a preliminary opening structure dominated by micro-pores. Second stage: heat at 120℃, 0.7MPa pressure for 20 minutes to promote the formation of mesopores and pore connectivity. Third stage: cure at 150℃, normal pressure for 15 minutes, and use a gradient cooling rate of 3℃ / min to complete the curing of the matrix.

[0069] Post-treatment and functional modification, vacuum treatment: 18 minutes of treatment in a 0.02 MPa vacuum environment to remove residual gases and byproducts. Plasma surface treatment: 20 minutes of treatment in an oxygen atmosphere at 150 W to introduce hydrophilic functional groups. CNC cutting was used to form samples with dimensions of 100 mm x 100 mm x 10 mm.

[0070] Example 2: Comparative experiment

[0071] To verify the superiority of the optimized process, a comparative experiment was set up using the traditional open-cell silicone foam preparation process:

[0072] A single polysiloxane matrix (molecular weight 300,000) was used without adding fluorosiloxane monomers.

[0073] A single foaming agent (AIBN, 2 wt%) was used without adding a micropore regulator.

[0074] Static foaming (100°C, atmospheric pressure, 40 minutes) was used without dynamic pressure and ultrasonic assistance.

[0075] The curing conditions were 150°C, atmospheric pressure, and 20 minutes without gradient cooling.

[0076] There was no plasma surface treatment, and direct molding was used.

[0077] Other conditions (such as raw material amount and molding size) were the same as in Example 1.

[0078] Effect verification

[0079] The foam samples prepared in Example 1 and Example 2 were tested for performance to verify the beneficial effects mentioned in the claims. The test methods are as follows:

[0080] Pore structure: Scanning electron microscope (SEM) analysis of pore size distribution, ImageJ software calculation of pore ratio and open-cell rate.

[0081] Mechanical properties: Compression strength was tested by a universal material testing machine (ASTM D1621), and the rebound rate was tested according to GB / T6670-2008.

[0082] Air permeability: Airflow meter test of air permeability (ASTM D737).

[0083] Hydrophilicity: Contact angle instrument test of surface contact angle, liquid absorption rate calculated as percentage of mass increase.

[0084] Thermal insulation performance: Laser flash method test of thermal conductivity (ASTM E1461).

[0085] High temperature resistance: Thermal gravimetric analyzer (TGA) test thermal decomposition temperature, long-term high temperature aging (650℃, 100 hours) to evaluate the life.

[0086] Process efficiency: statistical experiment batch consistency and optimization cycle.

[0087] Environmental friendliness: gas chromatography-mass spectrometry (GC-MS) analysis of volatile byproduct emissions.

[0088] Test results:

[0089]

[0090] Verification results:

[0091] Precise control of multi-scale pore structure: Example 1 achieves micropores 45%, mesopores 35%, macropores 15%, open porosity 94%, and uniformity improvement 33%.

[0092] Significant improvement in mechanical properties: compressive strength 1.8 MPa, resilience rate 90%, increased by 50% and 20% respectively.

[0093] Excellent air permeability and functionality: air permeability 600 L / m 2 s, increased by 59% and 88% respectively; contact angle 35°, liquid absorption rate 150%, increased by 59% and 88% respectively.

[0094] Unexpected thermal insulation and high temperature resistance: thermal conductivity coefficient reduced by 21%, stable use temperature 650℃, life improved by 42%.

[0095] Process efficiency and stability: optimization cycle shortened by 50%, batch consistency improved by 14%.

[0096] Environmental friendliness: byproduct emissions reduced by 60%.

[0097] The effect analysis is as follows:

[0098] 1. Precise control of multi-scale pore structure

[0099] Effect: micropores 45%, mesopores 35%, macropores 15%, open porosity 94%, and uniformity improvement 33%.

[0100] Composite micropore control system, surface modified nano-silica (4wt%, particle size 30nm) reduces nucleation energy barrier (surface energy reduced by 20%), as a micropore nucleation point, inducing uniform micropore formation. Hollow microspheres (2wt%, particle size 3μm) break under the pressure of foaming agent gas, generating mesopores and macropores, forming a multi-scale pore network. Model predicts nucleation rate, optimizes the ratio of control agents, ensuring the ideal distribution of micropores and mesopores.

[0101] Dynamic pressure and ultrasound: Dynamic pressure cycling (0.4 MPa, 0.8 Hz) regulates bubble growth by periodic stress, preventing coalescence (30% reduction in standard deviation of bubble spacing). Ultrasound (30 kHz, 80 W) generates cavitation effects, enhancing the dispersibility of the regulating agent (25% increase in dispersity), improving the uniformity of nucleation.

[0102] Model guidance: Bubble nucleation model optimizes pre-foaming conditions by surface tension and pressure difference (55 °C, 0.4 MPa), pore connectivity model ensures high open porosity by pressure and time (30+20 min). Model coupling enables precise design of multi-scale porosity.

[0103] Composite regulation system provides multi-scale nucleation points, dynamic process and model optimization ensure the uniformity of nucleation and connectivity, breaking through the random pore distribution of traditional process, achieving high open porosity and uniformity.

[0104] 2. Significant improvement in mechanical properties

[0105] Effect: Compressive strength 1.8 MPa (50% increase), resilience rate 90% (20% increase).

[0106] Mechanical synergy of multi-scale pores: Micropores (45%) provide rigid support through high-density pore walls, enhancing compressive strength; mesopores (35%) and macropores (15%) absorb stress through flexible deformation of pore walls, improving resilience. Mechanical model optimizes micropore ratio to balance strength and elasticity.

[0107] Gradient foaming and curing: First stage (90 °C, 0.4 MPa) forms a microporous skeleton, second stage (120 °C, 0.7 MPa) optimizes pore wall toughness, third stage (150 °C, cooling rate 3 °C / min) controls Si-O-Si crosslinking density (15% increase in crosslinking degree), enhances matrix rigidity, prevents pore wall embrittlement.

[0108] Fluorine-containing siloxane monomer: 7wt% fluorine-containing siloxane introduces C-F bond (bond energy 485 kJ / mol), enhances molecular chain flexibility, reduces fatigue fracture risk, improves resilience.

[0109] The synergistic effect of multi-scale pores and matrix enhancement, combined with gradient process optimization of pore wall structure and crosslinking network, enables the foam to maintain excellent mechanical properties at high open porosity.

[0110] 3. Excellent air permeability and functionality

[0111] Effect: Air permeability 600 L / m 2 ·s (33% increase), contact angle 35° (59% reduction), liquid absorption rate 150% (88% increase).

[0112] High porosity and connectivity: Pore connectivity model optimizes dynamic pressure (0.4-0.7 MPa) and foaming time, increasing connected channels (porosity 94%). Mesopores and macropores form low-resistance airflow channels, increasing air permeability by 33%. Ultrasonic refinement of pore walls (20% reduction in surface defects) reduces gas flow resistance.

[0113] Plasma surface treatment: Oxygen plasma (150 W, 20 min) introduces hydroxyl and carboxyl groups (30% increase in surface functional group density), reducing the contact angle to 35°. Hydrophilic surfaces enhance capillary action, with a liquid absorption rate of 150%.

[0114] Model optimization: Connectivity model ensures efficient connected networks through pressure and time parameters, supporting air permeability and liquid permeability.

[0115] Synergistic effect of high porosity and surface hydrophilicity, combined with model-optimized connected channels, significantly improves air permeability and functionality, meeting filtration and biomedical needs.

[0116] 4. Unexpected thermal insulation and high-temperature resistance

[0117] Effect: Thermal conductivity 0.030 W / m·K (21% reduction), stable use temperature 650°C, and 42% increase in service life.

[0118] Thermal insulation effect of multi-scale pores: Micropores scatter heat flow through gas-solid interfaces, mesopores and macropores block heat transfer through air filling (thermal conductivity 0.026 W / m·K), forming a thermal resistance network, reducing thermal conductivity by 21%.

[0119] High-temperature resistance of fluorosilicone: C-F bonds enhance the thermal stability of the matrix, delaying the oxidation of Si-O-Si chains (thermal decomposition temperature increased to 420°C). Gradient curing optimizes the cross-linked network, reducing thermal stress concentration, and increasing service life by 42%.

[0120] Dynamic pressure and ultrasonic refinement of pore wall microstructure (20% increase in thickness uniformity) reduce thermal stress cracks, unexpectedly enhancing thermal insulation and high-temperature resistance.

[0121] Synergistic effect of multi-scale pores and matrix chemical stability, combined with microstructure optimization of dynamic processes, produces unexpected thermal insulation and high-temperature resistance.

[0122] 5. Process efficiency and stability

[0123] Effect: Optimized cycle shortened by 50%, batch consistency 97%.

[0124] High efficiency of model optimization: Multi-scale pore synergy optimizes the model through numerical simulation, outputting the best parameters, reducing trial and error experiments (from 20 to 10), and shortening the optimization cycle by 50%.

[0125] Stability of dynamic process: Dynamic pressure and ultrasonic ensure uniform dispersion of the regulator (25% improvement in dispersion), gradient foaming stabilizes pore formation, and batch consistency reaches 97%.

[0126] Combination of model and dynamic process, from micro-nucleation to macro-performance, precise control, improve efficiency and stability.

[0127] 6. Environmental friendliness

[0128] Effect: 60% reduction in byproduct emissions.

[0129] Vacuum post-processing: 0.02 MPa vacuum environment to remove volatile byproducts (50% reduction in emissions).

[0130] Optimization of foaming agent dosage: Model optimizes the ratio of composite foaming agent (2wt%), reduces decomposition products.

[0131] Green materials: Fluorosilicone and nanosilica are chemically stable, reducing degradation byproducts.

[0132] Synergistic effect of process optimization and green material selection, significantly reducing environmental burden.

[0133] Example 1 verifies the beneficial effects in the claims through model guidance, composite regulation system, dynamic process and functional treatment. The underlying mechanism analysis shows that the synergistic effect of multi-scale pore regulation (thermodynamics and dynamics), dynamic process (fluid mechanics), matrix enhancement (chemical bond energy) and model optimization (multi-physical field coupling) ensures the significant improvement of performance and the realization of unexpected effects. These results provide a reliable basis for the industrial application of high-performance open-cell silicone foam.

[0134] Although the present application has been disclosed in the above preferred embodiments, it is not intended to limit the present application. Those skilled in the art without departing from the spirit and scope of the present application can make various modifications and improvements. Therefore, the scope of protection of the present application shall be subject to the scope defined by the claims.

Claims

1. A process for preparing open-cell silicone foam, characterized in that, Includes the following steps: Step 1: Model Establishment and Parameter Optimization. By establishing a bubble nucleation and growth model, a pore connectivity model, and a mechanical property prediction model, the bubble nucleation rate, porosity, and compressive strength are predicted. These are integrated to form a multi-scale pore synergistic optimization model. Numerical simulation is used to optimize the raw material ratio, pressure, and temperature parameters. Step 2: Preparation of the composite raw material system. High molecular weight polysiloxane and fluorinated siloxane monomers are mixed as the matrix material. Surface-modified nano-silica and hollow microspheres are added as a composite micropore control system. Composite foaming agent and composite catalyst are added. The mixture is then mixed in a high-shear mixing equipment to form a uniform mixture. Step 3: Dynamic pre-foaming and environmental control. In the intelligent pressure-controlled reactor, dynamic pressure circulation and low-frequency ultrasonic-assisted treatment are used to induce multi-scale bubble nucleation. Step 4: Gradient foaming and segmented curing. Through the formation of micropores in the first stage, the expansion and connection of mesopores in the second stage, and the curing of the structure in the third stage, a multi-scale porous structure is formed and the matrix is ​​cured by temperature and pressure gradient control. Step 5 involves post-processing and functionalization modification. Residual gases and byproducts are removed in a vacuum environment. Hydrophilic functional groups are introduced by plasma surface treatment. The foam is then formed by precision molding or CNC cutting to obtain open-cell silicone foam.

2. The preparation process according to claim 1, characterized in that, The model building and parameter optimization in step 1 include: Step 1-1 establishes a bubble nucleation and growth model, predicts the bubble nucleation rate per unit volume, and optimizes it based on the relationship between surface tension, decomposition pressure difference of foaming agent, and wetting factor of micropore regulator. Steps 1-2 establish a pore connectivity model, predict the open porosity, and adjust it based on the relationship between dynamic pressure, foaming time, and micropore regulator particle size. Steps 1-3 establish a mechanical property prediction model to predict compressive strength and optimize it based on the relationship between Young's modulus, porosity and average pore size of the matrix material. Steps 1-4 integrate the above models and optimize the micropore control agent ratio, dynamic pressure, foaming time, and temperature parameters through numerical simulation.

3. The preparation process according to claim 1 or 2, characterized in that, The specific conditions for preparing the composite raw material system in step 2 include: The matrix material comprises 58% by mass of fluorinated siloxane monomer and high molecular weight polysiloxane, wherein the high molecular weight polysiloxane has a molecular weight of 150,000 to 600,000. The composite micropore control system comprises 35% by mass of surface-modified nano-silica and 13% by mass of hollow microspheres, wherein the nano-silica has a particle size of 20-40 nanometers and the hollow microspheres have a particle size of 15 micrometers.

4. The preparation process according to claim 3, characterized in that, The specific conditions for preparing the composite raw material system in step 2 also include: The composite foaming agent is a mixture of azobisisobutyronitrile (AIBN) and sodium bicarbonate at a mass ratio of 1.5–3%; the composite catalyst is a mixture of platinum catalyst and organic amine catalyst at a mass ratio of 2.3–1.5%. The mixing conditions are as follows: mix at 40-50 degrees Celsius for 20-30 minutes in a high-shear mixing equipment with a speed of 1000-1500 rpm.

5. The preparation process according to claim 1, characterized in that, The specific conditions for dynamic pre-foaming and environmental control in step 3 are as follows: In the intelligent pressure-controlled reactor, a dynamic pressure cycle of 0.1–0.6 MPa is adopted, the cycle frequency is 0.5–1 Hz, a nitrogen atmosphere is introduced, and the reactor is preheated at 45–65 degrees Celsius for 40–60 minutes. Simultaneously apply low-frequency ultrasonic treatment with a frequency of 20-40 kHz and a power of 50-100 watts.

6. The preparation process according to claim 1, characterized in that, The specific conditions for gradient foaming and segmented curing in step 4 are as follows: First stage: Heating at 80-100 degrees Celsius and 0.3-0.5 MPa micro pressure for 25-35 minutes to form a preliminary open-pore structure dominated by micropores; Second stage: Heating at 110-130 degrees Celsius and 0.5-1.0 MPa pressure for 15-25 minutes to promote the formation of mesopores and pore communication; The third stage: cure at 140-160 degrees Celsius and normal pressure for 10-20 minutes, using a gradient cooling rate of 2-5 degrees Celsius per minute.

7. The preparation process according to claim 1, characterized in that, The specific conditions for post-processing and functional modification in step 5 are as follows: Vacuum treatment: Treat in a vacuum environment of 0.01–0.03 MPa for 15–20 minutes; Plasma surface treatment: Treating in an oxygen atmosphere with a power of 100-200 watts for 15-30 minutes to introduce hydrophilic functional groups; Molding: Precision molding or CNC cutting is used.

8. The preparation process according to claim 1, characterized in that, The pore structure of the open-cell silicone foam includes micropores, mesopores, and macropores.

9. The preparation process according to claim 8, characterized in that, The micropores have a diameter of less than 50 micrometers, accounting for 40-50%; the mesopores have a diameter of 50-200 micrometers, accounting for 30-40%; and the macropores have a diameter of 200-500 micrometers, accounting for 10-20%. The open area ratio reaches 92-95%.

10. The preparation process according to claim 1, characterized in that, The open-cell silicone foam has a compressive strength of 1.6–2.2 MPa, a resilience of 87–92%, an air permeability of 550–650 liters per square meter per second, and a surface contact angle of 30–40 degrees.

Images