Property of diblock copolymer having extremely narrow molecular weight distribution

Soojin Park, Du Yeol Ryu, Jin Kon Kim, Moonhor Ree, Taihyun Chang

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)

Abstract

Molecular weight distribution effect on the morphological behavior of polystyrene-block-polyisoprene (PS-b-PI) diblock copolymers was investigated. PS-b-PI samples were prepared by anionic polymerization and further fractionated by HPLC to obtain the fractions of similar average molecular weight and composition but of narrower distributions in both molecular weight and composition. The strategy is to use reversed-phase LC to fractionate the PI block and normal phase LC to fractionate the PS block with a minimal effect on the other blocks. The interfacial thickness, grain size and the phase transition behavior of the unfractionated and fractionated PS-b-PI were compared by X-ray reflectivity, small angle X-ray scattering, transmission electron microscopy and rheological measurements. The fractionated PS-b-PI with more homogeneous molecular weight and composition exhibits a narrower interface, larger grain size and a sharper morphological transition compared to the unfractionated PS-b-PI.

Original languageEnglish
Pages (from-to)2170-2175
Number of pages6
Journalpolymer
Volume49
Issue number8
DOIs
Publication statusPublished - 2008 Apr 15

Bibliographical note

Funding Information:
TC acknowledges the supports from KOSEF (National Research Laboratory and Center for Integrated Molecular Systems) and the BK21 program. JK acknowledges the support from KOSEF (National Creativity Research Initiative Center for Block Copolymer Self-Assembly). The XR and SAXS measurements at PAL were supported by the Ministry of Science and Technology and the POSCO.

All Science Journal Classification (ASJC) codes

  • Organic Chemistry
  • Polymers and Plastics
  • Materials Chemistry

Fingerprint

Dive into the research topics of 'Property of diblock copolymer having extremely narrow molecular weight distribution'. Together they form a unique fingerprint.

Cite this