(309d) Multiscale Modeling for Polymer Nano-Composite Coating Development

Polymer nano-composite coating (or simply called nano-coating) has been of great interest, as it may offer new or enhanced coating performances. Current nano-coating development approach has been exclusively experiment based. In laboratory, a small amount of organo-modified nano-particles is introduced into a conventional waterborne or solvent-borne resin. The resulting resin is then applied on a small substrate surface and a layer of thin film is formed through curing under a set of well-controlled curing conditions. A desired coating formulation is expected to be identified through repeated experiments. This approach does not support comprehensive and extensive experiments due to the concern of experimental cost and time limit. Furthermore, the experimental conditions are very different from the real coating manufacturing conditions. This could cause the nano-coating properties designed in lab to be not fully realizable in the final coating in real application.

In this work, a multiscale modeling approach is applied for effective nano-coating development in the automotive industry. By this approach, a set of multiscale models are developed to establish comprehensive correlations among material properties (at nano-to-macroscale), application conditions (usually at macroscale), and coating performances (at meso-to-macroscale). The macroscopic oven curing model set includes an air flow turbulence model, a radiation heating model and a panel heating model using CFD. This model can generate location specific coating temperature information. A lattice Monte Carlo with bond fluctuation model is utilized to construct the coating nano-to-mesoscale structure, i.e., the connectivity in the polymer network, spatial distribution of nanoparticles, and polymer chain conformation. A coating quality model correlates coating structure with the final coating property (e.g., stiffness). The information passed from the macroscopic curing condition model to the Monte Carlo code is generated through a macro-micro integration method.

The effects of material parameters and curing conditions on the final coating stiffness are thoroughly investigated. Simulation has revealed that when the nanoparticle and polymer have attractive interactions, the coating stiffness is steadily increased as increasing nanoparticle concentration. It is also suggested by simulation that the coating quality uniformity throughout the vehicle body can be improved through changing curing conditions (i.e., the direction of the air sprayed from the nozzles). These insights are especially valuable for identifying improved material formulation and application conditions, so that experiment based nano-coating development can be greatly assisted and product development cycle time can be significantly reduced.