Polymeric surface coating has numerous applications in the automotive, aerospace, electronics, steel, chemical and paper-making industries. It is widely recognized that the coating quality in terms of corrosion prevention and scratch resistance is directly determined by the coating microstructure (i.e., the 3D polymer network structure) that is formed during the curing process. Thus microstructure-based real-time quality control is the key to achieving superior coating performance, for which characterizing the 3D polymer network formation during the curing process becomes a crucial basis. Numerous efforts have been devoted to either microscopic modeling of the polymer network formation^1-3 or macroscopic modeling of the curing process.⁴ The monoscale modeling efforts can be hardly applied for realizing microstructure-based product quality control.

In this work, we will introduce a unified multiscale modeling method for characterizing polymeric coating curing. The macroscopic dynamic curing condition is modeled using the computational fluid dynamics (CFD), where different heating mechanisms (e.g., convection and radiation) can be readily applied. The microscopic crosslinked network structure is created through a Lattice Monte Carlo (LMC) simulation, which has unique capability for dealing with polymeric materials with any distributions of molecular weight and functional groups on the polymer chains. The macroscopic and microscopic models are seamlessly coupled by a special bi-directional coupling method. The curing temperature at a specific time instant obtained from the CFD model is sent to the LMC model for evolving the coating microstructure. On the other hand, the crosslinking conversion derived from the microstructure is sent back to the CFD model, which determines the next time instant for sending a temperature to the LMC model. Consequently, the microstructure evolution throughout a complete curing process under any curing condition can be revealed. Furthermore, a microstructure analysis method is introduced to correlate the micostructure (at a length scale of 10¹-10² nm) with the macroscopic coating quality (at a length scale of 10^-2-10¹ m). The introduced methodology is applied to an automotive coating curing case study. The attractiveness of revealing on-line all-time information about the coating microstructure and performance evolution will be fully demonstrated.

References:

1. Gina N, Cohen C, Panagiotopoulos AZ. A Monte Carlo study of the structural properties of end-linked polymer networks. Journal of Chemical Physics. 2000; 112: 6910-6916.

2. Balabanyan AG, Kramarenko EY, Ronova IA, Khokhlov AR. Monte Carlo study of structure and kinetics of formation of end-linked polymer networks. Polymer. 2005; 46, 4248-4257.

3. Hagn C, Wittkop M, Kreitmeier S, Trautenberg HL, Holzl T, Goritz D. The creation and spatial structure of end-linked bimodal polymer networks: a Monte Carlo study. Polymer Gels and Networks. 1995; 5: 327-337.

4. Lou HH, Huang YL. Integrated modeling and simulation for improved reactive drying of clearcoat. Ind. Eng. Chem. Res. 2000; 39: 500-507.