Thickness and Uniformity Modeling of the Deposition of Shape Memory Polymers for Information Storage Applications

Shape memory polymers are of interest as high-capacity information storage media. This research seeks to understand the effects of processing conditions on the following candidate polymers: diethylene glycol dimethacrylate (DEGDMA), tertbutyl acrylate (tBA), and bisphenol. Full factorial experiments were performed using three input factors: spin speed, spin time, and nitrogen flow rate. A total of ten experiments were conducted. The measured responses were film thickness, uniformity, hardness and modulus of the materials. Analysis of variance revealed that all input parameters were significant with respect to the film thickness. The full factorial experiments were augmented to a central composite face (CCF) design to enable response surface modeling. Neural network models were developed to examine relationships between the spin speed and thickness of spin coated films. The average predictability of the model was better than 2% for training and less than 15% in testing. This research is expected to aid in understanding the use of these materials in information storage.