A method for screening parameters of self-repairing microcapsules and preparation of anticorrosive coating

Abstract

The application discloses a kind of self-repairing microcapsule parameter screening and preparation method of anticorrosion coating, comprising, using integral geometry and geometric probability theory directional construction microcapsule-crack meeting probability model and combining Python algorithm realizes microcapsule repair efficiency modeling prediction, and microcapsule core parameter range is screened, and microcapsule parameter for self-repairing is screened by orthogonal test in combination with target performance. Microcapsule parameter is used with whole-process process collaborative control, and microcapsule synthesis, coating compounding and gradient curing process are optimized, coating density and the compatibility of microcapsule and matrix are improved, after 72h of neutral salt spray test, coating is free of blister, free of rust, impedance value is significantly improved, and corrosion resistance durability is improved by more than 30% compared with traditional process.

Description

Technical Field

[0001] This invention belongs to the field of anti-corrosion coating preparation technology, specifically involving a method for screening self-healing microcapsule parameters and preparing an anti-corrosion coating. Background Technology

[0002] Metal materials, when used long-term in complex environments such as marine, industrial, humid, and acidic / alkaline media, are highly susceptible to corrosion from oxygen, moisture, and chloride ions. This leads to surface material degradation, decreased mechanical properties, and even premature failure. Globally, corrosion causes trillions of dollars in economic losses annually, and also triggers indirect problems such as production interruptions, safety accidents, and soaring equipment maintenance costs. Anti-corrosion coatings, as one of the most efficient and cost-effective technologies for protecting metal structures, function primarily to form a barrier layer, inhibiting the corrosion process through passivation reactions or corrosion-inhibiting components.

[0003] Traditional anti-corrosion coatings generally suffer from structural fragility, susceptibility to damage, and difficulty in self-repair. Once localized damage or microcracks occur, corrosive media can rapidly penetrate, triggering pitting corrosion propagation and localized corrosion, severely shortening the coating's service life. To address this issue, self-healing anti-corrosion coatings have emerged. Their core principle involves introducing microcapsules carrying repair agents into the coating system. When cracks appear in the coating, the microcapsules rupture, releasing the repair agent to fill the cracks and form a dense protective layer, thus achieving self-repair.

[0004] Currently, the preparation process of self-healing anti-corrosion coatings still has many shortcomings: On the one hand, the parameters of microcapsules (such as particle size, wall thickness, core-to-wall ratio, dispersibility, etc.) lack systematic optimization, resulting in uneven dispersion and poor stability of microcapsules in the coating. They are either prone to premature rupture during the coating preparation process or cannot respond to rupture in time when cracks occur, which greatly reduces the self-healing efficiency. On the other hand, in the existing preparation process, the process parameters of microcapsule synthesis, coating composite and curing are independent of each other and have not formed a synergistic control system, resulting in insufficient coating density and poor compatibility between microcapsules and coating matrix, which in turn affects the anti-corrosion performance and self-healing durability of the coating.

[0005] In existing technologies, some studies attempt to optimize microcapsule parameters or single process steps, but these suffer from problems such as limited optimization dimensions, low process control precision, and failure to achieve synergistic matching between parameters and processes. For example, some schemes only optimize microcapsule particle size without considering the impact of wall thickness and core-to-wall ratio on the release rate of the repair agent; others only adjust the coating curing temperature without combining it with microcapsule thermal stability optimization parameters, leading to thermal damage to the microcapsules during curing. Furthermore, existing processes lack a robust parameter feedback and control mechanism, making it impossible to dynamically adjust parameters based on real-time preparation conditions, thus hindering the consistency and stability of coating performance.

[0006] Therefore, developing a preparation process based on microcapsule parameter system optimization to achieve coordinated control of the entire process of microcapsule synthesis, coating composite, curing and performance testing, and solving problems such as unreasonable microcapsule parameters, poor process coordination, low self-healing efficiency of coatings and insufficient anti-corrosion durability in existing processes, has become an urgent technical challenge in the field of self-healing anti-corrosion coatings. Summary of the Invention

[0007] The purpose of this section is to outline some aspects of embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0008] In view of the problems existing in the above and / or prior art, the present invention is proposed.

[0009] Therefore, the purpose of this invention is to overcome the shortcomings of the prior art and provide a method for screening self-healing microcapsule parameters and preparing anti-corrosion coatings.

[0010] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a method for screening parameters of self-healing microcapsules, comprising, A microcapsule-crack encounter probability model was constructed using integral geometry and geometric probability theory, and combined with Python algorithm to model and predict the microcapsule repair efficiency. The range of core parameters of the microcapsule was screened, and the parameters of self-healing microcapsules were obtained by orthogonal experiment combined with target performance screening. The core parameters of the microcapsule are microcapsule size, wall thickness, and core-to-wall ratio, and the target performance is dispersibility and thermal stability.

[0011] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for preparing a self-healing anti-corrosion coating, comprising: The parameters of the self-healing microcapsules obtained from the screening were used to synthesize microcapsules by Pickering emulsion polymerization, with the repair agent as the core material and urea-formaldehyde resin and graphene oxide as the wall material. The microcapsules were then obtained by vacuum freeze-drying. Using a resin matrix, curing agent, diluent, and additives as the coating matrix, microcapsules are added to the coating matrix at a ratio of 8% to 12% by weight. The microcapsules are then uniformly dispersed through a three-stage gradient stirring process to obtain a composite coating matrix. The composite coating substrate is coated onto the surface of the pretreated substrate and then subjected to a three-stage gradient curing process. Finally, the finished product is packaged and stored.

[0012] In a preferred embodiment of the preparation method described in this invention, the repair agent is a compound system of tung oil, epoxy curing agent, and corrosion inhibitor, with a compound mass ratio of 5:3:2; the wall material is a composite wall material of urea-formaldehyde resin and graphene oxide, with a compound mass ratio of 9:1; the reaction parameters of the Pickering emulsion polymerization method are controlled as follows: reaction temperature 55-65℃, stirring speed 800-1200 r / min, reaction time 2-4 h, emulsifier addition amount 2%-5% of wall material mass, emulsification time 30-60 min; after microcapsule synthesis, it is treated by vacuum freeze-drying process, drying temperature -40 to -30℃, drying time 12-24 h, and the water content of the microcapsules is ≤0.5%.

[0013] In a preferred embodiment of the preparation method described in this invention, the coating matrix components, by mass parts, are: 40-60 parts resin matrix, 10-20 parts curing agent, 5-15 parts diluent, and 2-8 parts additives; the resin matrix is ​​an aqueous polyurethane resin, the curing agent is an isocyanate curing agent, the diluent is a mixture of anhydrous ethanol and ethyl acetate in a mass ratio of 3:1, and the additives include dispersants, defoamers, and leveling agents; during the component preparation process, the stirring speed is controlled at 500-800 r / min, the stirring time at 30-60 min, the preparation temperature at 25-35℃, and the viscosity of the coating matrix after preparation is 200-500 mPa·s.

[0014] In a preferred embodiment of the preparation method described in this invention, the microcapsules are added at an amount of 8% to 12% of the coating substrate mass; the gradient stirring process is divided into three stages: the first stage, with a stirring rate of 300 to 500 r / min and a stirring time of 10 to 15 min; the second stage, with a stirring rate of 800 to 1000 r / min and a stirring time of 20 to 30 min; and the third stage, with a stirring rate of 300 to 500 r / min and a stirring time of 5 to 10 min; and the temperature is controlled at 25 to 30°C during the dispersion process.

[0015] As a preferred embodiment of the preparation method described in this invention, the specific process of the substrate pretreatment is as follows: The substrate surface is sanded with sandpaper to control the surface roughness Ra to be 0.8–1.6 μm; it is then immersed in a 5%–10% alkaline degreasing agent at 50–60°C for 10–20 min; it is then immersed in a 10%–15% hydrochloric acid solution at room temperature for 5–10 min; it is then immersed in a 2%–5% passivating agent at 40–50°C for 3–5 min; after pretreatment, it is rinsed with deionized water and dried at 80–100°C for 10–15 min, resulting in a substrate surface cleanliness ≤5 mg / m². 2 .

[0016] As a preferred embodiment of the preparation method described in this invention, the following steps are taken: Spraying is used, with a spraying pressure of 0.3–0.5 MPa, a spraying distance of 20–30 cm, a spraying speed of 5–10 cm / s, a single coating thickness of 30–50 μm, and multiple coatings to a total thickness of 100–200 μm; or scraping is used, with a scraping speed of 2–5 cm / s and a total thickness of 100–200 μm; the coating environment parameters are: temperature 20–30℃, relative humidity 40%–60%, and no dust or airflow interference.

[0017] As a preferred embodiment of the preparation method described in this invention, the segmented gradient curing process is divided into three stages: the first stage, with a temperature of 80–100°C, a time of 30–60 min, and a heating rate of 5–10°C / min; the second stage, with a temperature of 120–140°C, a time of 60–90 min, and a heating rate of 3–5°C / min; and the third stage, with a temperature of 150–160°C, a time of 30–60 min, and a heating rate of 2–3°C / min; the ambient humidity is controlled to be ≤40% during the curing process, and the temperature is allowed to cool naturally after curing, with a cooling rate of ≤5°C / min.

[0018] As a preferred embodiment of the preparation method described in this invention, the performance testing includes: self-healing performance testing using the scratch method, with a self-healing efficiency ≥85% to be considered satisfactory; corrosion resistance testing using neutral salt spray test and electrochemical impedance spectroscopy, with no blistering or rust on the surface after 72 hours of salt spray test, and an impedance value increase of nearly two orders of magnitude to be considered satisfactory; mechanical performance testing including adhesion and impact resistance, with adhesion ≥1 and impact resistance ≥50 kg·cm to be considered satisfactory; if the tests fail to meet the standards, the corresponding parameters are adjusted according to the performance defects.

[0019] As a preferred embodiment of the preparation method described in this invention, the packaging adopts a sealed packaging bag containing a desiccant, the storage environment temperature is 10-25℃, the relative humidity is ≤50%, and the storage period does not exceed 12 months.

[0020] Beneficial effects of this invention: (1) This invention uses orthogonal experiments combined with Python modeling to systematically optimize core parameters such as microcapsule particle size, wall thickness, and core-to-wall ratio, which solves the problems of uneven microcapsule dispersion and untimely response in existing processes. It ensures that microcapsules accurately rupture and release repair agents when coating cracks occur, and the self-repair efficiency is stable at over 85%, which greatly extends the service life of the coating.

[0021] (2) The present invention adopts the coordinated control of microcapsule parameters and the whole process, optimizes the microcapsule synthesis, coating composite and gradient curing process, improves the coating density and the compatibility between microcapsules and the substrate. After 72 hours of neutral salt spray test, the coating has no blistering or rust, the impedance value is significantly improved, and the corrosion resistance and durability are improved by more than 30% compared with the traditional process.

[0022] (3) This invention ensures consistent preparation and reduces costs: It establishes a sound performance testing and parameter feedback mechanism, which can dynamically adjust microcapsule parameters or process parameters based on real-time testing results, avoid performance differences between batches, optimize raw material ratios and process steps, reduce microcapsule breakage and loss, reduce raw material waste and production costs during the preparation process, and facilitate industrial-scale production. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is a comparison diagram of the products before and after defoaming in Example 3 of the present invention; Detailed Implementation

[0024] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the examples in the specification.

[0025] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0026] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0027] Unless otherwise specified, all raw materials used in the embodiments of this invention are commercially available. See Table 1 for details.

[0028] Table 1

[0029] Example 1 This embodiment provides a microcapsule parameter optimization design, specifically as follows: In this embodiment, the core parameters of the microcapsules are optimized with the goal of "improving self-healing efficiency and anti-corrosion performance". The optimization range of each core parameter is determined as follows: particle size 2-6μm, wall thickness 0.1-0.5μm, core-to-wall ratio (mass ratio of repair agent to wall material) 3:1-8:1, dispersion ≤5%, and thermal decomposition temperature ≥180℃.

[0030] Orthogonal experimental design was used to optimize the microcapsule parameters. Three key factors were selected: particle size (A), wall thickness (B), and core-to-wall ratio (C). Three levels were set for each factor, as shown in Table 1 below. Table 2. Factors and Levels in the Orthogonal Experiment for Microcapsule Parameters

[0031] The orthogonal experiment used an L9 orthogonal array, with a total of 9 groups of experiments. Three parallel samples were prepared for each group. The encapsulation efficiency, dispersibility, and thermal stability of the microcapsules were used as evaluation indicators, and the optimal parameter combination was screened using range analysis. The encapsulation efficiency was determined by gravimetric method, dispersibility by laser particle size analyzer, and thermal stability by thermogravimetric analysis (TGA). The specific evaluation criteria were: encapsulation efficiency ≥90%, dispersibility ≤5%, and thermal decomposition temperature ≥180℃.

[0032] Meanwhile, a microcapsule-crack encounter probability model was constructed using integral geometry and geometric probability theory: with integral geometry and geometric probability theory as the core, combined with the microcapsule particle size distribution and crack surface geometric characteristics, the basic probability of microcapsule-crack encounter was derived; the influence of non-ideal spherical shape of microcapsules was corrected by introducing a shape factor, and the release rate of the repair agent was physically constrained by combining the wall thickness and core-wall ratio.

[0033] Let the microcapsule size be d, the number density be N, the average crack length be l, and the average crack width be w, then the probability of encountering the target is... Repair efficiency Where η is a shape factor derived based on integral geometry. The release rate of the repair agent after microcapsule rupture is used. Optimization is achieved using a Python algorithm: Step 1, input the particle size, wall thickness, core-to-wall ratio, and crack geometry parameters of the orthogonal experiment; Step 2, based on the wall thickness and core-to-wall ratio set to 0.7–0.9, calculate the E value for each group; Step 3, iteratively optimize by maximizing E; Step 4, output the optimal parameters and weight them with the orthogonal experiment results to determine the final parameter combination.

[0034] Specifically, by importing parameters such as microcapsule particle size and dispersion density through Python programming, the probability of encountering microcapsules with coating cracks is simulated. The model parameters are then adjusted based on experimental data, ultimately achieving precise optimization of microcapsule parameters. This ensures that the microcapsules can respond promptly, rupture, and release the repair agent when coating cracks occur.

[0035] The results of the orthogonal experiment are shown in Table 3 below: Table 3. Results of orthogonal experiments on microcapsule parameters

[0036] Range analysis revealed that the factors influencing the overall performance of the microcapsules, in descending order, were: core-to-wall ratio (C) > particle size (A) > wall thickness (B). Based on Python modeling and prediction results, the optimal combination of microcapsule parameters was selected as follows: particle size 4 μm, wall thickness 0.3 μm, and core-to-wall ratio 5:1. At this ratio, the microcapsule encapsulation rate was 92.3%, dispersibility was 3.5%, and thermal decomposition temperature was 190℃, all meeting the preset evaluation criteria. Furthermore, the probability of microcapsule-crack encounter was highest, and the predicted repair efficiency exceeded 88%.

[0037] Example 2 This embodiment provides a method for preparing microcapsules loaded with repair agents using Pickering emulsion polymerization, specifically as follows: (1) Raw material preparation: The repair agent adopts a compound system of tung oil, epoxy curing agent and corrosion inhibitor with a compound mass ratio of 5:3:2. Tung oil is used as the main repair agent, epoxy curing agent is used to improve the film-forming performance of the repair agent, and corrosion inhibitor is used to enhance the anti-corrosion effect. The wall material adopts a composite wall material of urea-formaldehyde resin and graphene oxide with a compound mass ratio of 9:1. Graphene oxide is used to enhance the stability and corrosion shielding effect of microcapsules, and improve the thermal stability and mechanical strength of microcapsules. The emulsifier is polysorbate-80, and the dispersion medium is deionized water.

[0038] Specifically, in this embodiment, the tung oil used is dehydrated and refined tung oil, the epoxy curing agent is polyamide 650 curing agent, the corrosion inhibitor is benzotriazole, the urea-formaldehyde resin is obtained by prepolymerization of urea and 37wt% formaldehyde solution under weak acid conditions, the graphene oxide is a powder with a sheet diameter of 0.5-5μm and a thickness of 1-5nm, and the emulsifier is specified as polysorbate-80.

[0039] (2) Emulsion preparation: Add deionized water to the reactor, heat to 55°C, add emulsifier polysorbate-80 (addition amount is 3% of the wall material weight), start stirring, stirring speed 800r / min, stir for 10min to completely dissolve the emulsifier; then, slowly add the compounded repair agent to the reactor, continue stirring for 30min to form a uniform water-in-oil emulsion, ensuring that the emulsion has no layering and no precipitation.

[0040] (3) Microcapsule synthesis: Urea-formaldehyde resin and graphene oxide were mixed evenly in a certain proportion and slowly added to the above emulsion. The stirring speed was adjusted to 1000 r / min, the temperature was raised to 60℃, and the reaction was carried out for 3 h. During the reaction, samples were taken every 30 min to observe the state of the emulsion to ensure that the microcapsules were formed uniformly and without agglomeration. After the reaction was completed, stirring was stopped, and the mixture was allowed to cool naturally to room temperature to obtain a microcapsule suspension.

[0041] (4) Microcapsule post-processing: The microcapsule suspension was centrifuged at a speed of 3000 r / min for 15 min to remove the supernatant; then, the microcapsules were washed three times with deionized water to remove residual emulsifier and unreacted raw materials on the surface; finally, the microcapsules were placed in a vacuum freeze dryer, and the drying temperature was set to -35℃ for 18 h to ensure that the water content of the microcapsules was ≤0.5%.

[0042] (5) Microcapsule parameter detection: The prepared microcapsules were tested for parameters. The particle size was measured by laser particle size analyzer, the wall thickness was measured by scanning electron microscope (SEM), the encapsulation rate was measured by gravimetric method, the dispersibility was measured by laser particle size analyzer, and the thermal decomposition temperature was measured by thermogravimetric analyzer (TGA).

[0043] The test results showed that the microcapsule particle size was 4.0±0.2μm, the wall thickness was 0.3±0.02μm, the encapsulation rate was 92.1%, the dispersibility was 3.4%, and the thermal decomposition temperature was 189.5℃, which met the optimal parameter standards and can be used for subsequent coating composites.

[0044] Example 3 This embodiment provides a coating matrix component formulation process aimed at achieving "good compatibility with microcapsules, improving coating density and mechanical properties," specifically as follows: (1) Raw material preparation: Prepare 50 parts of resin matrix, 15 parts of curing agent, 10 parts of diluent and 5 parts of additives by mass. Among them, the resin matrix is ​​water-based polyurethane resin, which has good film-forming properties, corrosion resistance and flexibility, and good compatibility with microcapsules. The curing agent is an isocyanate curing agent, which is used to promote the cross-linking and curing of the resin matrix and improve the mechanical strength of the coating. The diluent is a compound system of anhydrous ethanol and ethyl acetate with a compound mass ratio of 3:1, which is used to adjust the viscosity of the coating matrix to facilitate subsequent coating. The additives include dispersant, defoamer and leveling agent. The dispersant is a polycarboxylate dispersant (2 parts), which is used to improve the dispersibility of microcapsules in the coating matrix. The defoamer is an organosilicon defoamer (1 part), which is used to eliminate bubbles generated during component mixing. The leveling agent is an acrylate leveling agent (2 parts), which is used to improve the smoothness and flatness of the coating.

[0045] Specifically, the waterborne polyurethane resin uses anionic waterborne polyurethane emulsion with a solid content of 35% to 45%, and the curing agent uses hydrophilic modified hexamethylene diisocyanate trimer; the total amount of additives is 5 parts by mass, of which the mass ratio of dispersant, defoamer and leveling agent is 2:1:2, the dispersant is sodium polycarboxylate dispersant, the defoamer is polyether modified organosilicon defoamer, and the leveling agent is polyether modified polydimethylsiloxane leveling agent.

[0046] (2) Component preparation: Add waterborne polyurethane resin to a mixing tank, turn on the stirring at room temperature, stir at a stirring speed of 500 r / min for 10 min to disperse the resin evenly; then, slowly add isocyanate curing agent and continue stirring for 15 min to ensure that the curing agent and resin are fully mixed; next, add diluent, adjust the stirring speed to 600 r / min, stir for 10 min to adjust the viscosity of the coating substrate; finally, add dispersant, defoamer and leveling agent in sequence, adjust the stirring speed to 800 r / min, stir for 15 min to ensure that all components are mixed evenly, without lumps or bubbles.

[0047] (3) Post-mixing test: The performance of the mixed coating substrate is tested. The viscosity is measured by a rotational viscometer and the uniformity of mixing is observed by visual inspection.

[0048] Figure 1 The defoaming comparison diagram of the embodiment of the present invention shows that the viscosity of the coating substrate is 350 mPa·s, the mixture is uniform, there are no lumps or bubbles, which meets the requirements for subsequent composite.

[0049] Example 4 To achieve uniform dispersion of microcapsules in the coating matrix and avoid microcapsule aggregation or sedimentation, this embodiment employs a gradient stirring process for composite formation, specifically: (1) Composite preparation: Add the coating substrate prepared in Example 3 into the mixing tank, adjust the temperature of the mixing tank to 28°C, start the stirring, and maintain the stirring state at a stirring rate of 300r / min.

[0050] (2) Gradient stirring and compounding: The optimized microcapsules prepared in Example 2 were added to the stirring vessel at 10% of the mass of the coating substrate, and gradient stirring was started: In the first stage, the stirring speed was maintained at 300 r / min and stirred for 12 min to initially disperse the microcapsules in the coating substrate and avoid microcapsule agglomeration; In the second stage, the stirring speed was adjusted to 900 r / min and stirred for 25 min to uniformly disperse the microcapsules in the coating substrate and ensure that the distribution deviation of microcapsules in each gram of coating substrate was ≤5%; In the third stage, the stirring speed was adjusted to 400 r / min and stirred for 8 min to eliminate the bubbles generated during the stirring process and at the same time avoid microcapsule rupture caused by high-speed stirring.

[0051] (3) Composite system testing: The composite coating system was tested. The dispersibility of microcapsules was measured by laser particle size analyzer and the dispersion state of microcapsules was observed by SEM.

[0052] The test results showed that the microcapsules were 3.6% dispersible in the coating system, with no agglomeration, uniform dispersion, and no rupture of the microcapsules, meeting the requirements for subsequent coating.

[0053] Example 5 In this embodiment, the substrate to be coated is a Q235 carbon steel substrate (100mm×100mm×3mm). The purpose of substrate pretreatment is to remove surface oil, rust, and impurities, form a passivation film, and improve the adhesion between the coating and the substrate. Specifically: (1) Grinding treatment: Use 80-grit sandpaper to coarsely grind the surface of the substrate to remove the surface oxide scale and impurities; then use 200-grit sandpaper to finely grind the surface, controlling the surface roughness Ra of the substrate to be 1.2μm, to ensure that the surface of the substrate is flat and burr-free. After grinding, use compressed air to blow away the surface dust.

[0054] (2) Degreasing treatment: Prepare an 8% alkaline degreasing agent (a compound system of sodium hydroxide and sodium carbonate, with a compounding mass ratio of 2:1). Place the polished substrate into the degreasing agent, control the temperature at 55℃, and soak for 15 minutes to remove oil stains from the surface of the substrate. During the soaking process, stir once every 5 minutes to ensure uniform degreasing. After degreasing, rinse the surface of the substrate three times with deionized water to remove any residual degreasing agent.

[0055] (3) Rust removal treatment: Prepare a 12% hydrochloric acid solution, immerse the degreased substrate in the hydrochloric acid solution, and soak for 8 minutes at room temperature to remove the rust on the surface of the substrate; during the soaking process, observe the surface condition of the substrate to avoid excessive corrosion. After rust removal, rinse the surface of the substrate three times with deionized water to remove the residual hydrochloric acid solution on the surface.

[0056] (4) Passivation treatment: Prepare a 3% potassium dichromate aqueous solution as a chromate passivating agent. Immerse the derusted substrate in the passivating agent at a controlled temperature of 45°C for 4 minutes to form a dense passivation film on the substrate surface, thereby improving the corrosion resistance of the substrate and the adhesion of the coating. After passivation, rinse the substrate surface three times with deionized water to remove any residual passivating agent.

[0057] (5) Drying treatment: Place the pretreated substrate in an oven, set the drying temperature to 90℃ and the drying time to 12min to remove the moisture from the surface of the substrate. After drying, remove the substrate and cool it to room temperature for later use.

[0058] (6) Inspection after pretreatment: The pretreated substrate is inspected. The surface roughness is measured by a surface roughness meter and the surface cleanliness is measured by gravimetric method.

[0059] The test results showed that the surface roughness Ra of the substrate was 1.18 μm and the surface cleanliness was 4.2 mg / m². 2 It meets the preset requirements.

[0060] Example 6 This embodiment uses a spray coating method for coating application. During the coating process, coating parameters are strictly controlled to ensure uniform coating thickness, absence of bubbles, and absence of pinholes. The specific process is as follows: (1) Coating preparation: Pour the composite coating system prepared in Example 4 into the spray gun and check whether the spray gun is working properly; fix the pretreated substrate on the spraying worktable and adjust the angle between the substrate and the spray gun to 90° to ensure uniform spraying.

[0061] (2) Coating parameter control: The spraying pressure was set to 0.4 MPa, the spraying distance to 25 cm, and the spraying rate to 8 cm / s. Multiple coatings were used, with a single coating thickness of 40 μm and a total of 4 coatings for a total coating thickness of 160 μm. After each coating was completed, the coating was allowed to stand for 5 minutes to prevent it from dripping.

[0062] (3) Coating environment control: The temperature of the coating environment is controlled at 25℃ and the relative humidity is controlled at 50%. Doors and windows are closed to avoid dust and airflow interference, and to ensure that the coating surface is flat and free of impurities.

[0063] (4) Post-coating inspection: After coating, the surface condition of the coating is observed visually and the coating thickness is measured using a coating thickness gauge. The inspection results show that the coating surface is smooth, free of bubbles, pinholes, and flow, and the coating thickness is 158-162 μm, which is uniform and meets the preset requirements.

[0064] Example 7 This embodiment, taking into account the thermal stability parameters of the microcapsules (thermal decomposition temperature 189.5℃), employs a segmented gradient curing process to avoid thermal damage to the microcapsules due to excessively high temperatures during curing. Simultaneously, it ensures full cross-linking of the coating, improving its mechanical and corrosion-resistant properties. The specific process is as follows: (1) Curing preparation: Place the substrate coated in Example 6 above into the curing oven, adjust the humidity in the curing oven to ≤40%, turn on the heating system, and set the heating rate.

[0065] (2) Segmented gradient curing: The first stage (pre-curing): set the curing temperature to 90℃, the heating rate to 8℃ / min, and the curing time to 45min. The main purpose is to remove the thinner from the coating and avoid the thinner residue causing bubbles or pinholes in the coating.

[0066] Second stage (intermediate curing): After pre-curing, adjust the curing temperature to 130℃, the heating rate to 4℃ / min, and the curing time to 75min. This promotes the initial cross-linking of the coating matrix, enhances the initial strength of the coating, and avoids microcapsule damage caused by a sudden temperature rise.

[0067] The third stage (final curing): After intermediate curing, adjust the curing temperature to 155℃, the heating rate to 2.5℃ / min, and the curing time to 45min to achieve complete cross-linking of the coating and improve the mechanical properties, corrosion resistance and self-healing properties of the coating.

[0068] (3) Cooling treatment: After the final curing is completed, turn off the heating system and use natural cooling method. Control the cooling rate to 4℃ / min so that the coating can be slowly cooled to room temperature to avoid internal stress in the coating, which may cause the coating to crack or peel off from the substrate.

[0069] (4) Inspection after curing: After curing, remove the substrate, observe the surface condition of the coating by visual inspection, and measure the hardness of the coating by hardness tester.

[0070] The inspection results showed that the coating surface was smooth, without cracks or peeling, and the coating hardness was 2H, which met the preset requirements.

[0071] Example 8 This embodiment conducts comprehensive performance testing on the cured self-healing anti-corrosion coating, including self-healing performance, anti-corrosion performance, and mechanical properties. The testing methods and standards are as follows. If the test results do not meet the standards, feedback is provided to the corresponding steps to adjust the parameters.

[0072] (1) Self-healing performance test: The scratch method was used. According to GB / T 30786, a scratch with a length of 1 cm and a width of 380±10 μm was prepared on the coating surface using a utility knife. The scratch penetrated the coating to the substrate. Subsequently, the samples were placed in a natural environment (temperature 23±2℃, relative humidity 50±10%) and a salt spray environment (35±2℃, 5% sodium chloride solution, salt spray deposition rate 1~2 ml / 80cm). 2 Place the samples under the 24-hour light for 24 hours. Observe the healing of the scratches using an optical microscope, measure the width and depth of the scratches before and after healing, and calculate the self-healing efficiency (self-healing efficiency = (width before healing - width after healing) / width before healing × 100%).

[0073] The test results showed that under natural conditions, the width of the scratch after healing was 42μm, and the self-repair efficiency was 89.0%; under salt spray conditions, the width of the scratch after healing was 51μm, and the self-repair efficiency was 86.6%, both ≥85%, and the self-repair performance met the standards.

[0074] (2) Corrosion resistance test: including neutral salt spray test and electrochemical impedance spectroscopy (EIS) test.

[0075] The neutral salt spray test shall be conducted according to GB / T 1771. The sample shall be placed in a salt spray chamber, and the test parameters shall be set as follows: temperature 35±2℃, 5% sodium chloride solution, salt spray settling rate 1~2ml / 80cm. 2 • h, test time 72h; after the test, take out the sample, remove the surface salt residue with a soft sponge, observe the surface condition of the coating, and evaluate the corrosion of the coating in accordance with the provisions of GB / T 6461.

[0076] EIS testing was performed using an electrochemical workstation, with a testing frequency range of 10. -2 ~10 5 The test solution was 5% sodium chloride solution, and the test time was 72 hours. The change in the impedance value of the coating was recorded.

[0077] The test results showed that after 72 hours of salt spray testing, the coating surface showed no blistering, rust, or peeling, with a corrosion level of 0. After 72 hours of EIS testing, the coating's impedance value decreased from the initial 1.2 × 10⁻⁶. 6 Ω·cm 2 Increased to 1.1×10 8 Ω·cm 2 This represents an improvement of nearly two orders of magnitude, and the corrosion resistance meets the standards.

[0078] (3) Mechanical performance testing: including adhesion and impact resistance testing.

[0079] The adhesion test was conducted according to GB / T 9286, using the cross-cut test with a grid spacing of 1 mm. After the grid was drawn, adhesive tape was used to adhere the coating, and the coating peeling was observed. The adhesion grade was divided into 0 to 5, with grade 0 being the best and grade 5 being the worst.

[0080] The impact resistance test shall be conducted in accordance with GB / T 1732, using an impact testing machine with an impact energy of 50 kg·cm, and observing whether the coating shows cracking, peeling or other phenomena.

[0081] Test results showed that the coating adhesion was grade 1 with no obvious peeling; the impact resistance was 50 kg·cm, and the coating showed no cracking or peeling, meeting the mechanical performance standards.

[0082] In this embodiment, all performance test results met the standards, and no parameter adjustment was required before proceeding to the subsequent product packaging and storage steps.

[0083] Example 9 To prevent coating aging and microcapsule breakage and ensure the performance stability of the finished product, this embodiment adopts the following packaging and storage method, specifically: (1) Finished product packaging: The self-healing anti-corrosion coating finished products that have passed the test are packaged in sealed packaging bags. Each packaging bag contains one pack of desiccant (silica gel desiccant, with a mass of 5g). The sealed packaging bags are made of aluminum foil, which has good moisture-proof and anti-oxidation properties. After sealing, check whether the packaging bags leak air.

[0084] (2) Storage environment control: Place the packaged finished products in the storage warehouse and control the storage environment temperature to 18℃ and the relative humidity to 45%. Avoid direct sunlight, violent vibration and high temperature and high humidity environment in the storage warehouse, and keep away from corrosive gases and flammable and explosive materials.

[0085] (3) Storage period: The storage period of the finished product shall not exceed 12 months. During the storage period, the performance of the coating shall be sampled and tested once a month to ensure the stability of the coating performance. If the storage period is exceeded, the performance test shall be carried out again and the product can be used only after it meets the standards.

[0086] Example 10 The difference between this embodiment and Example 1 is that the microcapsule particle size, wall thickness, core-to-wall ratio, and addition amount in Example 1 are replaced with the minimum values ​​of the preferred range, namely, particle size 2 μm, wall thickness 0.1 μm, core-to-wall ratio 3:1, and addition amount 8%. The remaining steps are the same as in Example 1. The results are as follows: encapsulation rate 87.2%, dispersibility 4.9%, thermal decomposition temperature 182℃, self-healing efficiency 85.1% in natural environment and 82.3% in salt spray environment, no blistering or corrosion of the coating after 72 hours of salt spray test, adhesion grade 1, impact resistance 50 kg·cm. All indicators basically meet the standards, but the overall performance is lower than that of Example 1.

[0087] Example 11 The difference between this embodiment and Example 1 is that the microcapsule particle size, wall thickness, core-to-wall ratio, and addition amount in Example 1 are replaced with the maximum values ​​of the preferred range, namely, particle size 6 μm, wall thickness 0.5 μm, core-to-wall ratio 8:1, and addition amount 12%. The remaining steps are the same as in Example 1. The results are as follows: encapsulation rate 85.6%, dispersibility 5.2%, thermal decomposition temperature 186℃, self-healing efficiency 84.5% in natural environment and 80.8% in salt spray environment, very slight pitting corrosion on the coating after 72 hours of salt spray test, adhesion grade 1, impact resistance 45 kg·cm, still possessing self-healing and anti-corrosion function, but the performance is slightly lower than that of Example 1.

[0088] Comparative Example 1 The difference between this comparative example and Example 1 is that the microcapsule particle size in Example 1 was replaced with 1 μm, while the remaining steps were the same as in Example 1. The results were as follows: the encapsulation rate was 75.8%, the premature breakage rate of the microcapsules during the composite process reached 12.5%, the self-healing efficiency was 68.7% in natural environment and 62.3% in salt spray environment, and after 48 hours of salt spray testing, the coating showed obvious blistering and corrosion, the adhesion dropped to level 3, and the impact resistance dropped to 30 kg·cm.

[0089] Comparative Example 2 The difference between this comparative example and Example 1 is that the microcapsule wall thickness in Example 1 was replaced with 0.05 μm, while the other steps were the same as in Example 1. The results showed that the microcapsule rupture rate was as high as 18.6% and the encapsulation rate was 82.1% during the coating composite process. The self-healing efficiency was 65.4% in natural environment and 58.9% in salt spray environment. After 48 hours of salt spray testing, the coating showed extensive corrosion.

[0090] Comparative Example 3 The difference between this comparative example and Example 1 is that the core-to-wall ratio in Example 1 is replaced with 10:1, while the remaining steps are the same as in Example 1. The results are as follows: the encapsulation rate is 79.4%, the microcapsule wall thickness is insufficient, making it prone to premature rupture, the self-healing efficiency is 73.8% in natural environment and 69.2% in salt spray environment, and pitting corrosion appears on the coating after 72 hours of salt spray testing.

[0091] Comparative Example 4 The difference between this comparative example and Example 1 is that the amount of microcapsules added in Example 1 was replaced with 5%, while the rest of the steps were the same as in Example 1. The results were: self-healing efficiency of 72.6% in natural environment and 68.3% in salt spray environment. The total amount of repair agent was insufficient, the cracks could not be completely filled, and rust spots appeared after 72 hours of salt spray testing.

[0092] Comparative Example 5 The difference between this comparative example and Example 1 is that the amount of microcapsules added in Example 1 was replaced with 15%, while the remaining steps were the same as in Example 1. The results showed that the self-healing efficiency was 81.1%, but the coating density decreased, the adhesion dropped to level 3, and the impact resistance dropped to 35 kg·cm.

[0093] Comparative Example 6 The difference between this comparative example and Example 1 is that the repair agent (tung oil: epoxy curing agent: corrosion inhibitor = 5:3:2) in Example 1 was replaced with single tung oil (100% tung oil), while the other steps were the same as in Example 1. The results were: self-healing efficiency 78.5% in natural environment and 72.1% in salt spray environment; multiple rust spots appeared on the coating surface after 72 hours of salt spray testing; the electrochemical impedance value was only 4.2 × 10⁻⁶. 6 Ω·cm 2Although tung oil alone can oxidize and cross-link to form a film, it lacks the cross-linking enhancement effect of a curing agent and the active anti-corrosion effect of a corrosion inhibitor, resulting in poor film density.

[0094] Comparative Example 7 The difference between this comparative example and Example 1 is that the repair agent (tung oil: epoxy curing agent: corrosion inhibitor = 5:3:2) in Example 1 was replaced with a single polyamide 650 epoxy curing agent (100% curing agent), while the remaining steps were the same as in Example 1. The results were: self-healing efficiency 65.8% in natural environment and 58.4% in salt spray environment; the repair film was discontinuous, and crack filling was incomplete. When the epoxy curing agent is used alone as a repair agent, it needs to react with the epoxy resin components in the environment to form a film. In this system, the reactivity is insufficient in the waterborne polyurethane matrix, and an effective repair layer cannot be formed.

[0095] Comparative Example 8 The difference between this comparative example and Example 1 is that the wall material (urea-formaldehyde resin: graphene oxide = 9:1) in Example 1 was replaced with pure urea-formaldehyde resin (100% urea-formaldehyde), while the remaining steps were the same as in Example 1. The results showed that the thermal decomposition temperature of the microcapsules decreased to 172°C, and the premature breakage rate during coating composite process increased to 8.3%; the self-healing efficiency was 82.1% in natural environment and 78.6% in salt spray environment. The lack of reinforcement and barrier effect from graphene oxide led to a decrease in the thermal stability and mechanical strength of the microcapsules.

[0096] Comparative Example 9 The difference between this comparative example and Example 1 is that the parameter optimization was not performed using orthogonal experiments, integral geometry, and Python modeling. Instead, the microcapsule parameters (particle size 3 μm, wall thickness 0.4 μm, core-to-wall ratio 6:1, and addition amount 10%) were selected by technicians based on experience, referencing publicly available process parameters. The remaining steps were the same as in Example 1. The results showed a self-healing efficiency of 78.4% in natural environment and 72.6% in salt spray environment. After 72 hours of salt spray testing, slight blistering appeared in the coating, and the impedance value decreased from 1.5 × 10⁻⁶. 6 Increased to 2.3×10 7 Ω·cm 2 The value of Example 1 was increased to 1.1 × 10⁻⁶. 8 Ω·cm 2 The results show that, without model optimization and relying solely on empirical parameter selection, both the self-healing efficiency and corrosion resistance are lower than those of Example 1.

[0097] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the present invention.

Claims

1. A method for screening parameters of self-healing microcapsules, characterized in that: include, A microcapsule-crack encounter probability model was constructed using integral geometry and geometric probability theory, and combined with Python algorithm to model and predict the microcapsule repair efficiency. The range of core parameters of the microcapsule was screened, and the parameters of self-healing microcapsules were obtained by orthogonal experiment combined with target performance screening. Among them, the core parameters of the microcapsule are microcapsule particle size, wall thickness and core-to-wall ratio, and the target performance is dispersion and thermal stability; the microcapsule-crack encounter probability model is based on integral geometry and geometric probability theory, combined with microcapsule particle size distribution and crack surface geometric characteristics, to derive the basic probability of microcapsule-crack encounter; by introducing a shape factor to correct the influence of non-ideal spherical shape of microcapsules, and by combining wall thickness and core-to-wall ratio to physically constrain the release rate of the repair agent, the microcapsule-crack encounter probability model shown in Equation (1) and the repair efficiency model shown in Equation (2) are obtained; Equation (1); Equation (2); Wherein, the microcapsule particle size is d, the number density is N, the average crack length is l, the average crack width is w, and η is a shape factor derived based on integral geometry. The release rate of the repair agent after the microcapsule ruptures.

2. A method for preparing a self-healing anti-corrosion coating, characterized in that: include, The self-healing microcapsule parameters obtained by screening according to claim 1 were used to synthesize microcapsules by Pickering emulsion polymerization with the repair agent as the core material and urea-formaldehyde resin and graphene oxide as the wall material. The microcapsules were then obtained by vacuum freeze-drying. Using a resin matrix, curing agent, diluent, and additives as the coating matrix, microcapsules are added to the coating matrix at a ratio of 8% to 12% by mass. The microcapsules are then uniformly dispersed through a three-stage gradient stirring process to obtain a composite coating matrix. The composite coating substrate is coated onto the surface of the pretreated substrate and subjected to a three-stage gradient curing process. Finally, the finished product is packaged and stored.

3. The preparation method according to claim 2, characterized in that: The self-healing microcapsules have a particle size of 3.8~4.2μm, a wall thickness of 0.1~0.5μm, a core-to-wall ratio of 3~8:1, a dispersion of ≤5%, a thermal decomposition temperature of ≥180℃, and a water content of ≤0.5%.

4. The preparation method according to claim 2, characterized in that: The repair agent is a compound system of tung oil, epoxy curing agent and corrosion inhibitor, with a compound mass ratio of 5:3:2; the mass ratio of urea-formaldehyde resin to graphene oxide is 9:1; the amount of emulsifier added is 2% to 5% of the wall material mass, the emulsification time is 30 to 60 min; the drying temperature is -40 to -30℃, and the drying time is 12 to 24 h.

5. The preparation method according to claim 2, characterized in that: The coating matrix components, by mass parts, are: 40-60 parts resin matrix, 10-20 parts curing agent, 5-15 parts diluent, and 2-8 parts additives; wherein the resin matrix is ​​waterborne polyurethane resin, the curing agent is an isocyanate curing agent, the diluent is a mixture of anhydrous ethanol and ethyl acetate in a mass ratio of 3:1, and the additives consist of dispersants, defoamers, and leveling agents; the viscosity of the coating matrix is ​​200-500 mPa·s.

6. The preparation method according to claim 2, characterized in that: The three-stage gradient mixing includes, In the first stage, the stirring rate is 300-500 r / min and the stirring time is 10-15 min; In the second stage, the stirring rate is 800-1000 r / min, and the stirring time is 20-30 min; In the third stage, the stirring rate is 300-500 r / min and the stirring time is 5-10 min; The temperature should be controlled at 25-30℃ during the dispersion process.

7. The preparation method according to claim 2, characterized in that: The coating includes spraying or scraping, with a total coating thickness of 100–200 μm, an ambient temperature of 20–30°C, and a relative humidity of 40%–60%.

8. The preparation method according to claim 2, characterized in that: The three-stage segmented gradient curing process includes, The first stage involves a temperature of 80–100℃, a time of 30–60 min, and a heating rate of 5–10℃ / min. The second stage involves a temperature of 120–140℃, a time of 60–90 min, and a heating rate of 3–5℃ / min. The third stage involves a temperature of 150–160℃, a time of 30–60 min, and a heating rate of 2–3℃ / min. During the curing process, the ambient humidity is controlled to be ≤40%. After curing, the temperature is allowed to drop naturally at a rate of ≤5℃ / min.

Images