Foam injection molding (FIM) is utilized in many industries. Despite its flourish, the understanding of the cell dynamics in FIM is still lacking. This work aims to improve the fundamental understanding of cell growth, dissolution, and elongation phenomena during FIM, to expedite the foam structure design for the industry via correlating the processing parameters with the final morphology.

A model that predicts the cell growth tailored to high-pressure FIM (HP-FIM) processes during the entire processing period is presented. The model captures the fluid flow and the transport phenomenon during cell growth facilitated by the Simha-Somcynsky equation of state and realistic material properties for the PS/CO₂ mixture. The proposed model predicted the cell growth profile for its entire lifespan under different HP-FIM conditions and was validated by comparison with the visualization experimental data.

Moreover, a study on the critical, but often overlooked, cell dissolution and its relation to the packing/holding stage is presented. The dissolution of cells in the packing stage decouples the foaming and filling steps in FIM and lays the foundation for the consistent production of uniform foam structures. Systematic experiments were conducted using a visualization mold to study the effect of various processing parameters on the packing efficiency to determine the time required to fully dissolve the gate-nucleated cells. A simulation attempt was made to predict the evolution of cell size during packing. Moreover, a sensitivity analysis showed the model’s response to the changes in various parameters, and echoed the experimental observations.

In the end, a study that attempted to correlate the mold opening (MO) parameters to the final foam structure is discussed. Visualized HP-FIM experiments demonstrated that the removal of the gate-nucleated cells could effectively prevent cell coalescence and collapse during MO. Besides the packing pressure, the packing time also dictated the structure by affecting the melt strength and gas diffusion coefficient. Moreover, employing the cell model, we were able to accurately predict the cell growth for a small MO distance and validated the results with experimentally measured growth data. For large MO distances, the simulated results demonstrated qualitative agreement with experimental observations.