By Topic

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

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Wornyo, E. ; Syst. & Technol. Group, IBM Microelectron., Hopewell Junction, NY, USA ; May, G.S. ; Gall, Ken

Shape memory polymers are of interest as high-capacity information storage media. This paper seeks to understand the effects of processing conditions on diethylene glycol dimethacrylate (DEGDMA) and bisphenol A ethoxylate dimethacrylate. Full factorial experiments are performed to characterize the impact of the following parameters: spin speed, spin time, and nitrogen flow rate. A total of ten experiments are conducted. The measured responses are film thickness, uniformity, hardness and modulus. Analysis of variance reveals the above input parameters are significant with respect to the output responses. The full factorial experiment is augmented by a central composite face centered (CCF) design to facilitate process modeling. Neural network models are developed to examine relationships. The average predictability of the models is better than 2% for training and less than 15% in testing. Genetic algorithms are used in optimizing recipes for the two materials.

Published in:

Semiconductor Manufacturing, IEEE Transactions on  (Volume:22 ,  Issue: 3 )