THE SCHOOL OF MATERIALS SCIENCE AND ENGINEERING
GEORGIA INSTITUTE OF TECHNOLOGY
Under the provisions of the regulations for the degree
DOCTOR OF PHILOSOPHY
on Monday, February 3, 2020
in MoSE 3201A
will be held the
DISSERTATION PROPOSAL DEFENSE
"Experimental and Theoretical Approaches for Elucidating Doped Organic Semiconductors: Towards a Materials Design Framework for High Conductivity"
Prof. Natalie Stingelin, Advisor, MSE/ChBE
Prof. Carlos Silva, MSE/CHEM/PHYS
Prof. Shannon Yee, ME
Prof. Rampi Ramprasad, MSE
Prof. Joshua Kretchmer, CHEM
The multibillion-dollar organic light-emitting diode (OLED) industry is based on the unique combination of properties that organic semiconductors can offer, including chemical versatility, processability, and tunable performance. Yet surprisingly, only a few reliable design guidelines exist to induce high conductivity in processable plastic conductors despite the substantial amount of work that exists in literature on the design of conducting organic materials. Factors impacting intermolecular interactions, transport properties, and other relevant parameters such as solubility/processability, are still not fully understood. This thesis proposal outlines experimental methods and theoretical approaches that will be combined to unravel the factors that determine charge transport properties in organic semiconductors, and to provide new paradigms for understanding these materials when used in devices.
The first objective of my PhD research is to establish the structure/property interrelationship of doped semiconductors, focusing on the model system of poly[2,5-bis(3-tetradecylthiophen-2-yl)thieno[3,2-b]thiophene] (PBTTT), where we can manipulate the self-assembly of the dopant and the semiconductor, and can target specific molecular assemblies. It is found that polymer:dopant miscibility, which can lead to vitrification, affects charge transport – a hypothesis that will be tested in my future work.
The second objective of my thesis is the screening of optoelectronic properties of semiconductor:dopant blends, examining the charge-relaxation dynamics in these multi-component systems via combined transient absorption and 2D coherent excitation spectroscopies, as well as (non-adiabatic) excited state molecular dynamic computations.
Finally, my third objective entails creating an extensive database that includes structural information, detailed spectroscopic data, charge-transport details and information on the thermal phase behavior of semiconductor:dopant blends, as well as essential parameters deduced from theory. This set of information will be fed into machine learning activities for property prediction and, potentially, expedited design of materials with anticipated properties, e.g., high-conductivity organic materials.
To summarize, my PhD research aims to build a platform to gain new insights into charge carrier properties in polymeric materials, by creating a feedback loop between experiment and computation. This platform will be further utilized for the development of quantitative design criteria towards materials with desired property sets. In addition, my research aims to incorporate machine learning and data-driven approaches to reform materials discovery from heuristic time- and labor-consuming studies towards more predictive pathways, creating a preliminary methodology of accelerated materials screening for the organic electronics community.