Collaborative Research: Aggregation Mechanisms in Carbon Nanomaterials Based on Pi-conjugated Polycyclic Aromatic Hydrocarbons

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With support from the Macromolecular, Supramolecular, and Nanochemistry (MSN) Program of the Division of Chemistry, Professor Hans Lischka of Texas Tech University at Lubbock and Professor Miklos Kertesz of Georgetown University are studying the mechanisms of aggregation of individual polycyclic aromatic hydrocarbon molecules into assemblies. Polycyclic aromatic hydrocarbons are ubiquitous molecules that occur in practically all carbonaceous materials, including ones as familiar to the general public as soot. Facilitation as well as inhibition of aggregation requires understanding of the driving forces for this process at the molecular level. Such molecular level of understanding is central to the control of the formation of functional carbon nanomaterials and crucial for the rational development of organic semiconductors for application in electronic and optical technologies, such as organic solar cells, electronic sensors and quantum computing systems. During the course of conducting this collaborative project, graduate and undergraduate students from diverse backgrounds will be trained, and summer courses on the science of soft matter that are geared towards high school students will be conducted. The software protocols developed will be publicly shared with the scientific community and tutorials on quantum mechanical methods geared to the general public will be developed. The project addresses an urgently needed systematic study of the radical and biradical character of polycyclic aromatic hydrocarbon molecules and its role in their aggregation into nano-sized structures. Molecular level understanding of cluster formation is crucial for the rational development of organic nanocarbons for application in electronic and optical technologies. Computational modeling with highest-level quantum chemical methods (multireference theory) in combination with lower level, but computationally more efficient methods (ab initio single reference methods and density functional theory) will be employed. Descriptors will be used to construct and calculate promising dimer and trimer stacking combinations to evaluate the pancake interaction strength and compare them with experimental observations. These quantum chemical simulations will be extended by global modeling activities which will reflect in more detail the condensed phase structure based on the available interaction data of the quantum chemical calculations. This project includes collaboration with two experimental groups, providing structural and other characterization data. This project is expected to lead to a new and systematic approach to data collection based on computational work in the form of structural and energetic information with additional descriptors for biradical character. In the longer term, a better understanding of pancake bonding in the context of polycyclic aromatic hydrocarbons has the potential to provide important new insights into the mechanisms of radical and biradical aggregation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.