Predicting the optical gap of conjugated systems
Botelho, André Leitão
MetadataShow full item record
The adapted Su-Schrieffer-Heeger model is developed in this work as a tool for in silico prediction of the optical gap of conjugated systems for photovoltaic applications. Full transferability of the model ensures reliable predictive power - excellent agreement with 180 independent experimental data points covering virtually all existing conjugated system types with an accuracy exceeding the time-dependent density functional theory, one of the most accurate first-principles methods. Insights on the structure-property relation of conjugated systems obtained from the model lead to guiding rules for optical gap design: 1) fusing aromatic rings parallel to the conjugated path does not significantly lower the optical gap, 2) fusing rings perpendicularly lowers the optical gap of the monomer, but has a reduced benefit from polymerization, and 3) copolymers take advantage of the lower optical gap of perpendicular fused rings and benefit from further optical gap reduction through added parallel fused rings as electronic communicators. A copolymer of parallel and perpendicular benzodithiophenes, differing only in sulfur atom locations, is proposed as a candidate to achieve the optimal 1.2 eV donor optical gap for organic photovoltaics. For small-molecule organic photovoltaics, substituting the end pairs of carbon atoms on pentacene with sulfur atoms is predicted to lower the optical gap from 1.8 eV to 1.1 eV. Furthermore, the model offers an improvement of orders of magnitude in the computational efficiency over commonly used first-principles tools.
Thesis (Ph.D.)--Boston UniversityPLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at email@example.com. Thank you.