Phase behavior of gradient copolymer solutions: A Monte Carlo simulation study

Gunja Pandav, Victor Pryamitsyn, Keith C. Gallow, Yueh Lin Loo, Jan Genzer, Venkat Ganesan

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

We use computer simulations to study the phase separation behavior of amphiphilic linear gradient copolymer solution under poor solvent conditions. Using the bond fluctuation model and parallel tempering algorithm, we explore the influence of the gradient strength (the largest difference in the instantaneous composition along the copolymer) upon the phase separation characteristics. Under poor solvent conditions, the chains collapse to form micelle-like aggregates. We find that the critical temperature for this transition exhibits a linear dependence on the gradient strength of the copolymers. A systematic quantification of the cluster characteristics formed during the phase separation also reveals a strong dependence of aggregation numbers and the bridging statistics upon the gradient strength of the copolymers. Analysis of our results reveals that the critical parameter determining the thermodynamic behavior of gradient copolymers is in fact the average length of the hydrophobic sequences in the gradient copolymers. We demonstrate that the latter provides a useful measure to quantitatively predict the critical transition temperature of the gradient copolymer solution. We also present a few results from the framework of an annealed representation of the sequences of the gradient copolymer to demonstrate the limitations arising from such a model representation.

Original languageEnglish (US)
Pages (from-to)6471-6482
Number of pages12
JournalSoft matter
Volume8
Issue number24
DOIs
StatePublished - Jun 28 2012

All Science Journal Classification (ASJC) codes

  • General Chemistry
  • Condensed Matter Physics

Fingerprint

Dive into the research topics of 'Phase behavior of gradient copolymer solutions: A Monte Carlo simulation study'. Together they form a unique fingerprint.

Cite this