Design,Preparation And Performance Study Of Epoxy-based Self-healing And Self-warning Anticorrosion Coating

In recent years,smart anticorrosion coatings,which can respond to external stimuli and repair damage,have attracted great attention from academics at home and abroad.However,smart anticorrosion coatings often have low repair efficiency,difficulty in responding to changes in the corrosion microenvironment,weak longlasting anticorrosion properties,and difficulty in controlling the design of multicomponent formulations,which limit their further development and towards wider practical applications.To address the above questions,this paper uses Q235 steel as the metal substrate,and develops the design and preparation of epoxy-based selfhealing self-warning anticorrosion coating and its performance research,the main research ideas as follows:Firstly,in order to quickly and efficiently repair smallscale damage,the modified epoxy resin coating with intrinsic repair mechanism is prepared;for the damage that cannot be repaired by the intrinsic process,two types of externally self-healing self-warning coatings were prepared to enhance the corrosion warning capability and long-lasting corrosion protection performance of the epoxy coating.Finally,in order to further optimize the self-healing performance and corrosion resistance of the self-healing self-warning anticorrosion coatings,a machine learning optimization strategy for the design of multi-component material formulations in the background of small sample data was proposed,and a smart anticorrosion coating with multi-scale repair capability and corrosion detection capability was prepared by this strategy.The main contents are as follows:Firstly,to improve the self-healing efficiency of the coating,an anticorrosion coating that can be repaired efficiently at room temperature(25℃)was prepared by adjusting the quantity of the flexible units(polyetheramine)in the epoxy matrix and introducing the quadruple hydrogen bonding units(urea-pyrimidinone)in the epoxy matrix.By adjusting the content of polyetheramines a shape recovery capability of 99.7%at room temperature was endowed to the coating matrix.When damage occurs in the coating,the shape recovery ability helps to rapidly seal the damage and barrier the corrosive medium,which enables a rapid repair process through the self-association process of hydrogen bonding units at the closed interface.The results of the mechanical properties tests confirm that the material can achieve the repair of 73.3%tensile strength and the repair of 93.2%fracture strain at room temperature.When the coating was scratched in air or in a 3.5 wt.%NaCl solution,the damage of coating was effectively repaired within 5 min.At the same time,the good mechanical properties and the self-healing effect enable the damaged coating to reach a salt spray resistance class 10 after 20 days of salt spray exposure.For the case of severe damage that cannot be repaired by the intrinsic selfhealing coating and to realize the smart response of the coating to the corrosive environment,self-healing and corrosion detection,the second part of this study a smart protective coating possessing both damage warning and active corrosion protection abilities,enabled by pH-sensitive chitosan/alginate@CaCO3(CA@CaAPhen)microcontainers containing amino-o-phenanthroline(APhen)molecules.The permeability of the polyelectrolyte shell on the microcontainer surface could be changed under the corrosive environment-directed pH change conditions to achieve rapid release of APhen.Electrochemical results of the intact coating demonstrated that the presence of microcontainers enhanced the anticorrosive properties of the coating,with a 2 order of magnitude increase in low frequency impedance over the pure epoxy coating after 60 days of immersion in 3.5 wt.%NaCl solution.After 144 h of immersion in 3.5 wt.%NaCl solution,the lowfrequency impedance modulus of the epoxy coating containing CA@Ca-APhen microcontainers was enhanced by 2 orders of magnitude compared to the initial immersion stage,confirming the corrosion inhibition of the metal substrate at the coating scratch by the release of APhen.Salt spray tests demonstrated that the damaged coating could warn and inhibit corrosion within 2 min by the reaction of APhen with Fe2+generated by corrosion in the damaged area of the coating to form stable and bright red[Fe(APhen)3]2+complexes.Considering the limitations of inhibitor-based external self-healing coatings in terms of repair efficiency,in the third part,we report a development of a self-healing self-warning anticorrosion coating which incorporates CaCO3 microcontainers containing tung oil(TO)and APhen,using the ZIF-8 as nano-stoppers formed at the orifices of CaCO3 microcontainers.When the corrosive environment at the scratch is alkaline,the microcontainer can open the surface pores of the CaCO3 microcontainer through the dissolution process of the outer layer of Zif-8 nanoparticles to achieve the release of the core materials;when the corrosive environment at the scratch is acidic,both the Zif-8 nanoparticles and the CaCO3 microcontainer will dissolve at this time to cause the release of the core materials.The repair effect of the released TO on the coating damage was demonstrated by electrochemical results and FIB-SEM.After 50 days of immersion in 3.5 wt.%NaCl solution.the low frequency impedance of the coating reached 3.09 ×107 Ω·cm2,which was 2 orders of magnitude higher than that of the pure epoxy coating.The corrosion monitoring results showed that the coating corrosion current was still as low as 27.0 nA after 70 days of salt spray exposure,confirming the long-lasting corrosion protection capability of the damaged coating.When corrosion occurs at the coating/metal interface,the APhen at the scratch can report corrosion by complexing with Fe2+,while combining corrosion inhibition.The optimization of material performance is often achieved by involving the issue of how to select a multi-component formulation solution,and manual selection is often difficult to balance the relationship between the components to find the best formulation.In order to further optimize the self-healing performance and long-lasting anticorrosion performance of self-healing self-warning anticorrosion coatings.a machine learning optimization strategy for multicomponent material formulation design in the context of small sample data was proposed by combining orthogonal Latin square experimental design,active learning and Bayesian optimization,and the coating ratios with the best target performance are calculated and verified using this strategy.The machine-learningadjusted coating achieved a post-repair low-frequency impedance of 3.80 × 1011Ω·cm2.A self-healing self-warning anticorrosion coating was prepared by loading the coating formulation with microcontainers of TO and APhen.Salt spray tests for 60 days showed that the coating could repair light scratches(50 μm in width)and heavy scratches(500 μm in width)by an intrinsic hydrogen bonding self-healing mechanism and an external TO self-healing mechanism.After 80 days of salt spray exposure,optical images and Raman results demonstrated the coating’s ability to warn corrosion by the chromogenic effect of APhen and its long-lasting corrosion protection.