Self-Assembly of Block Copolymers by Solvent Vapor Annealing, Mechanism and Lithographic Applications

Block copolymers (BCP) are a unique class of polymers, which can self-assemble into ordered microdomains with sizes from 3 nm to about 50 nm making BCPs an appealing meso-scale material. In thin films, arrays of BCP microdomains with longrange lateral order can serve as ideal templates or scaffolds for patterning nano-scale functional materials and synthesizing nanostructured materials with size scales that exceed the reach of photolithography. Among many annealing methods, solvent vapor annealing (SVA) is a low-cost, highly efficient way to annihilate defects in BCP thin films and facilitates the formation of highly ordered microdomains within minutes. Directing the self-assembly of BCPs could, in principle, lead to the formation of domains with near perfect lateral ordering. The mechanism of SVA of BCPs, however, is still illunderstood, albeit it has been widely adopted in research laboratories around the world for the past decade. In the first part of this thesis, the ordering process of BCP thin films during annealing in neutral solvents was investigated mainly by in situ synchrotron X-ray scattering. Briefly, the solvent molecules impart mobility to the BCP and enable a marked improvement in the lateral ordering of the BCP microdomains. Both, BCP concentration in the swollen film and the rate of solvent removal play a key role in obtaining films with well-ordered microdomains. The amount of swelling in a BCP thin film during SVA depends on the chemical nature of the blocks, the quality of the solvent, and the molecular weight of the BCP. A high degree of swelling - still low enough to prevent solvent-induced mixing (disordering) of BCP microdomains,- provides a high chain mobility, and thus results in the formation of arrays of ordered microdomains with large grain sizes after SVA in neutral solvents. The rate of solvent removal is another critical parameter for obtaining long-range lateral order in BCP thin films after SVA in neutral solvents. While in the swollen state ordered structures form with exceptional order, removal of the solvent results in a deterioration of order due to the confinement imposed to a BCP in a thin film by the rigid silicon substrate. It was found, however, that an instantaneous solvent removal can minimize disordering to preserve the order formed in the swollen state. Self-assembled BCP microdomains also serve as ideal template to pattern other materials with exceptional lateral resolution. In this thesis, two examples of BCP lithography was also demonstrated. A reconstruction process was used to enhance the etch contrast between two organic blocks. In one example, a BCP pattern was transferred to a silicon substrate to form high aspect ratio, 5:1, sub-10nm silicon lines or holes with high fidelity. While in a second example, I demonstrated the fabrication of silicon oxide dots with an areal density as high as 2 Tera dots per inch2 by BCP templates, which has the potential to serve as etch mask for bit pattern media applications

Joint return and volatility timing in exchange traded funds : evidence from Tokyo market

1 online resource (v, 43 p.)Includes abstract and appendix.Includes bibliographical references (p. 27-29).This paper tests the existence of volatility timing skills in the Tokyo ETFs market. The historical daily data on sixty-two ETFs are collected covering the period July 1st, 2003 to July 16 , 2013 from Bloomberg. Two methods are used in this paper, which are OLS- and PLS- regression methods. Regression results are then analyzed to finger out the existence of volatility timing skills of fund managers. The first regression results show that 90% funds confirm the existence of volatility timing skills in the Tokyo ETFs market. The second and third show the same results as the first one. In detail, the efficiency of volatility timing skills on ETFs improved in the Tokyo ETFs market after t[he] September 2008 financial crisis

The Meniscus-Guided Deposition of Semiconducting Polymers

The electronic devices that play a vital role in our daily life are primarily based on silicon and are thus rigid, opaque, and relatively heavy. However, new electronics relying on polymer semiconductors are opening up new application spaces like stretchable and self-healing sensors and devices, and these can facilitate the integration of such devices into our homes, our clothing, and even our bodies. While there has been tremendous interest in such technologies, the widespread adoption of these organic electronics requires low-cost manufacturing techniques. Fortunately, the realization of organic electronics can take inspiration from a technology developed since the beginning of the Common Era: printing. This review addresses the critical issues and considerations in the printing methods for organic electronics, outlines the fundamental fluid mechanics, polymer physics, and deposition parameters involved in the fabrication process, and provides future research directions for the next generation of printed polymer electronics

Machine Learning Prediction of Glass Transition Temperature of Conjugated Polymers From Chemical Structure

Predicting the glass transition temperature (Tg) is of critical importance as it governs the thermomechanical performance of conjugated polymers (CPs). Here, we report a predictive modeling framework to predict Tg of CPs through the integration of machine learning (ML), molecular dynamics (MD) simulations, and experiments. With 154 Tg data collected, an ML model is developed by taking simplified “geometry” of six chemical building blocks as molecular features, where side-chain fraction, isolated rings, fused rings, and bridged rings features are identified as the dominant ones for Tg. MD simulations further unravel the fundamental roles of those chemical building blocks in dynamical heterogeneity and local mobility of CPs at a molecular level. The developed ML model is demonstrated for its capability of predicting Tg of several new high-performance solar cell materials to a good approximation. The established predictive framework facilitates the design and prediction of Tg of complex CPs, paving the way for addressing device stability issues that have hampered the field from developing stable organic electronics