Investigation of the fidelity of micro molded features using micro injection molding process

A.A. Rajhi, A. Almalki, J.P. Coulter
Lehigh University,
United States

Keywords: micro/nano injection molding, microfabrication, cooling time, micropillars stretching


The demand of micro molded features made of Thermoplastic polyurethane (TPU) is high for numerous biomedical applications. TPU offers distinct characteristics when it comes to compatibility and flexibility. However, there are some replication challenges that still need to be addressed to optimally mold micro features with high fidelity. In this work, a silicon-based mold insert (Si) with circular cavities of 5 µm diameter and 3 µm edge to edge spacing over dense area was replicated with an aspect ratio of 4. It was fabricated using photolithography followed by deep reactive ion etching (DRIE) to create the required depth. Prior to molding trails, numerical simulations were performed using Moldflow Insight to optimize the processing parameters and to determine a preliminary baseline for the experimental examinations. Once the optimal replication parameters such as cooling time, mold temperature, melt temperature were obtained, the features were examined to determine their influence on pillars stretching. This is done in order to find to what extent those features can be stretched while maintaining the required geometry with high fidelity. While feature stretching is expected to happen due to sidewall frictional forces during part ejection, cooling time could influence melt relaxation before part ejection and lead to a high extent of the feature's height. Thus, this could provide a proper understanding of features stretching as a function of cooling time to achieve final molded features' geometry. This stretching could facilitate the ability to improve the replication rate to a further point before the molded features start to collapse. Samples were characterized using Hitachi 4300 scanning electron microscopy (SEM) to measure features stretching and provide visualized understanding of parameters' effect on the replication.