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

在化学系大分子、超分子和纳米化学（MSN）项目的支持下，德克萨斯理工大学拉伯克分校的Hans Lischka教授和乔治敦大学的Miklos Kertesz教授正在研究单个多环芳烃分子聚集成组装体的机制。 多环芳烃是普遍存在于几乎所有含碳材料中的分子，包括公众熟悉的烟灰。 促进以及抑制聚集需要理解的驱动力，这一进程在分子水平上。 这种分子水平的理解对于控制功能性碳纳米材料的形成至关重要，对于合理开发有机半导体在电子和光学技术中的应用至关重要，例如有机太阳能电池，电子传感器和量子计算系统。 在开展这一合作项目的过程中，将培训来自不同背景的研究生和本科生，并将举办面向高中生的软物质科学暑期课程。 开发的软件协议将与科学界公开分享，并将开发面向公众的量子力学方法教程。 该项目针对多环芳烃分子的自由基和双自由基特性及其在聚集成纳米尺寸结构中的作用进行迫切需要的系统研究。 在分子水平上理解团簇的形成对于合理开发有机纳米碳在电子和光学技术中的应用至关重要。 将采用最高水平量子化学方法（多参考理论）与较低水平但计算效率更高的方法（从头算单参考方法和密度泛函理论）相结合的计算建模。 描述符将用于构建和计算有前途的二聚体和三聚体堆叠组合，以评估煎饼相互作用强度，并将其与实验观察结果进行比较。这些量子化学模拟将通过全球建模活动进行扩展，这些活动将基于量子化学计算的可用相互作用数据更详细地反映凝聚相结构。该项目包括与两个实验组的合作，提供结构和其他表征数据。该项目预计将导致一个新的和系统的方法来收集数据的基础上计算工作的形式的结构和能量的信息与双基字符的额外描述符。从长远来看，在多环芳烃的背景下，更好地了解煎饼键有可能提供重要的新见解的自由基和双自由基aggregation.This奖项的机制反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

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.