ITR: Development of Quantitative Coarse Grained Simulation Models for Polyolefin Blends

Rensselaer Polytechnic Institute, Troy NY

Investigators

Abstract

This award was made on a 'small' category proposal submitted in response to the ITR solicitation, NSF-02-168. It supports computational research and education to study polymer miscibility. The PI's propose to develop a suite of coarse-grained methodologies and computational algorithms to simulate the liquid state miscibility of polyolefins. Polyolefins, e.g., polyethyelene, polypropylene etc., are commercially important polymers which need to be cheaply synthesized with desired properties. Since minimizing cost is important, it has become popular to blend polyolefins of different chain microstructure to create materials with desired properties, rather than to synthesize new polymers. Unfortunately, many of these long chain polymers do not mix, so desired properties cannot be readily achieved. It is important to applications that a good a priori knowledge of the miscibility of a given polyolefin mixture be available. Available computer simulation tools cannot handle long enough chains to be useful from an experimental standpoint. The PIs aim to develop coarse-grained simulation methodologies, which can extend the range of chain lengths accessible to simulations by an order of magnitude or more. These tools will enable simulations in the range of experimentally relevant chain lengths and offer the possibility of developing a tool using information technology to predict polyolefin miscibility. Codes resulting from the research will be benchmarked against experiment, and made available to the broader materials research community. This award will increase the PIs' participation in various NSF supported education and outreach activities. %%% This award was made on a 'small' category proposal submitted in response to the ITR solicitation, NSF-02-168. It supports computational research and education to study polymer miscibility. The PI's propose to develop a suite of coarse-grained methodologies and computational algorithms to simulate the liquid state miscibility of polyolefins. Polyolefins, e.g., polyethyelene, polypropylene etc., are commercially important polymers which need to be cheaply synthesized with desired properties. Since minimizing cost is important, it has become popular to blend polyolefins of different chain microstructure to create materials with desired properties, rather than to synthesize new polymers. Unfortunately, many of these long chain polymers do not mix, so desired properties cannot be readily achieved. It is important to applications that a good a priori knowledge of the miscibility of a given polyolefin mixture be available. Available computer simulation tools cannot handle long enough chains to be useful from an experimental standpoint. The PIs aim to develop coarse-grained simulation methodologies, which can extend the range of chain lengths accessible to simulations by an order of magnitude or more. These tools will enable simulations in the range of experimentally relevant chain lengths and offer the possibility of developing a tool using information technology to predict polyolefin miscibility. Codes resulting from the research will be benchmarked against experiment, and made available to the broader materials research community. This award will increase the PIs' participation in various NSF supported education and outreach activities. ***