Molecular modeling of directed self-assembly of block copolymers: Fundamental studies of processing conditions and evolutionary pattern design /

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Bibliographic Details
Author / Creator:Khaira, Gurdaman Singh, author.
Imprint:2016.
Ann Arbor : ProQuest Dissertations & Theses, 2016
Description:1 electronic resource (117 pages)
Language:English
Format: E-Resource Dissertations
Local Note:School code: 0330
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/10862862
Hidden Bibliographic Details
Other authors / contributors:University of Chicago. degree granting institution.
ISBN:9781339873442
Notes:Advisors: Juan J. de Pablo Committee members: Joseph Kline; Paul F. Nealey; Matthew Tirrell.
Dissertation Abstracts International, Volume: 77-10(E), Section: B.
English
Summary:Rapid progress in the semi-conductor industry has pushed for smaller feature sizes on integrated electronic circuits. Current photo-lithographic techniques for nanofabrication have reached their technical limit and are problematic when printing features small enough to meet future industrial requirements. "Bottom-up'' techniques, such as the directed self-assembly (DSA) of block copolymers (BCP), are the primary contenders to compliment current "top-down'' photo-lithography ones. For industrial requirements, the defect density from DSA needs to be less than 1 defect per 10 cm by 10 cm. Knowledge of both material synthesis and the thermodynamics of the self-assembly process are required before optimal operating conditions can be found to produce results adequate for industry. The work present in this thesis is divided into three chapters, each discussing various aspects of DSA as studied via a molecular model that contains the essential physics of BCP self-assembly. Though there are various types of guiding fields that can be used to direct BCPs over large wafer areas with minimum defects, this study focuses only on chemically patterned substrates.
The first chapter addresses optimal pattern design by describing a framework where molecular simulations of various complexities are coupled with an advanced optimization technique to find a pattern that directs a target morphology. It demonstrates the first ever study where BCP self-assembly on a patterned substrate is optimized using a three-dimensional description of the block-copolymers. For problems pertaining to DSA, the methodology is shown to converge much faster than the traditional random search approach.
The second chapter discusses the metrology of BCP thin films using TEM tomography and X-ray scattering techniques, such as CDSAXS and GISAXS. X-ray scattering has the advantage of being able to quickly probe the average structure of BCP morphologies over large wafer areas; however, deducing the BCP morphology from the information in inverse space is a challenging task. Using the optimization techniques and molecular simulations discussed in the first chapter, a methodology to reconstruct BCP morphology from X-ray scattering data is described. It is shown that only a handful of simulation parameters that come directly from experiment are able to describe the morphologies observed from real X-ray scattering experiments.
The last chapter focuses on the use of solvents to assist the self-assembly of BCPs. Additional functionality to capture the process of solvent annealing is also discussed. The bulk behavior of solvated mixtures of BCPs with solvents of various affinities is described, and the results are consistent with the experimentally observed behavior of BCPs in the presence of solvents.