Massachusetts Institute of Technology
Self-assembly of silicon-containing triblock copolymer and terpolymers
Abstract
dc:description.abstractThe block copolymer (BCP) self-assembly has garnered significant interest due to its ability to generate periodic nanostructures with a variety of morphologies. Compared to diblock copolymers that have been extensively studied to form the conventional morphologies such as spheres, cylinders, and lamellae depending on the block volume fraction, more complex polymer architectures are expected to offer additional degrees of freedom and a wider range of structures. Solvent vapor annealing (SVA) using a continuous gas flow system allows a precise control over the annealing condition, which can capture intermediate morphologies including perforated lamellae and gyroids and can create unique nanostructures that have not been observed in diblock copolymers. Combining with self-consistent field theory (SCFT) modeling and in situ grazing-incidence small-angle X-ray scattering (GISAXS) measurement, the phase behavior of advanced polymer architectures can be revealed in details.
Degree
thesis:*- Name thesis:degree_name
- Master
- Department dc:contributor.department
- Massachusetts Institute of Technology. Department of Materials Science and Engineering
- Grantor dc:publisher
- Massachusetts Institute of Technology
- Year dc:date.issued
- 2019
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Lee, Sangho(Scientist in materials science and engineering)Massachusetts Institute of Technology.
- Advisor dc:contributor.advisor
-
- Caroline A. Ross.
Subjects
dc:subject × 1Rights
dc:rights- Statement dc:rights
-
- MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
- Licence dc:rights.uri
- Language dc:language.iso
- eng
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- https://hdl.handle.net/1721.1/121610
- OAI identifier oai:identifier
- oai:dspace.mit.edu:1721.1/121610