(717g) Lattice Monte Carlo Modeling and Analysis of Microstructure and Coating Quality Correlation for Optimal Paint Design

Paint is designed to offer various chemical and physical properties for surface protection, styling, and appearance. Nevertheless, the anticipated coating quality is frequently unsatisfactory, which is often attributed to paint formulation design. As new demands on coating performance continuously emerge, paint formulation design becomes even more sophisticated. This has triggered computational paint design as it can provide great freedom and control over the investigation of paint formulation through any number of in silico experiments under any application conditions.

In this paper, we introduce a comprehensive microscale modeling and analysis methodology for the design of paint formulation and the prediction of paint-based surface coating properties. By this methodology, which is resorted to lattice Monte Carlo (LMC) modeling and simulation, any paint formulation can be evaluated under any real industrial curing condition, and the coating performance in terms of solvent resistance and inter-coat adhesion can be thoroughly investigated. This can enable an establishment of various types of correlations among paint formulation, curing condition, coating microstructure and coating properties, which are critical for paint designers to optimally develop paint formulation. The introduced methodology is used to study the construction and analysis of polymer networks, where the distributions of polymer molecular weights and functional groups on polymer chains are all taken into account. Different from the known LMC simulation techniques, a unique approach is introduced to impose a curing condition on the network formation process, which enables the investigation of curing dynamics along both real curing time and MC steps. Furthermore, a new network analysis method is described for evaluating a key coating quality indicator, EECD (elastically effective crosslink density) by utilizing the information contained in a 3D polymer network structure. This can help greatly bridge the gap between the investigation of paint microstructures and the research on coating macroscopic quality. A comprehensive study on optimal design of acrylic-melamine-based resin will demonstrate the efficacy of the introduced methodology.