全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

The development of a high-throughput/ combinatorial workflow for the study of porous polymer networks

DOI: http://dx.doi.org/10.2147/IJHTS.S27359

Keywords: high-throughput, chemically induced phase separation, porous polymer, poragen

Full-Text   Cite this paper   Add to My Lib

Abstract:

evelopment of a high-throughput/ combinatorial workflow for the study of porous polymer networks Original Research (1659) Total Article Views Authors: Majumdar P, Bahr J, Crowley E, Kallam A, Gubbins N, Schiele K, Weisz M, Dirk SM, Lenhart JL, Chisholm BJ Published Date April 2012 Volume 2012:3 Pages 1 - 12 DOI: http://dx.doi.org/10.2147/IJHTS.S27359 Received: 15 October 2011 Accepted: 15 December 2011 Published: 11 April 2012 Partha Majumdar1, James Bahr1, Elizabeth Crowley1, Alekhya Kallam1, Nathan Gubbins1, Kris Schiele1, Michael Weisz1, Shawn M Dirk3, Joseph L Lenhart4, Bret J Chisholm1,2 1Center for Nanoscale Science and Engineering, 2Department of Coatings and Polymeric Materials, North Dakota State University, Fargo, North Dakota, 3Sandia National Laboratories, Albuquerque, New Mexico, 4US Army Research Laboratory, Aberdeen, Maryland, USA Abstract: A high-throughput workflow was developed for the study of porous polymers generated using the process of chemically induced phase separation. The workflow includes automated, parallel preparation of liquid blends containing reactive, polymer network-forming precursors and a poragen, as well as a high-throughput poragen extraction process using supercritical CO2. A structure–process–property relationship study was conducted using epoxy-amine cross-linked networks. The experimental design involved variations in polymer network cross-link density, poragen composition, poragen level, and cure temperature. A total of 216 unique compositions were prepared. Changes in opacity of the blends as they cured were monitored visually. Morphology was characterized using a scanning electron microscope on a subset of the 216 samples. The results obtained allowed for the identification of compositional variables and process variables that enabled the production of porous networks.

Full-Text

comments powered by Disqus

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133

WeChat 1538708413