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This dissertation research work focuses on the investigation of novel donor-acceptor systems elucidating their photochemical properties, anion binding, and their potential application in the development of artificial photosynthetic systems. The explored systems are based on oxoporphyrinogen (OxPs), porphyrins, fullerene, and boron dipyrromethene (BODIPY) based donor-acceptor systems. The photochemical properties of novel molecular systems were elucidated using UV-vis spectroscopy, fluorescence spectroscopy, electrochemical methods, computational calculations, and ultrafast transient absorption spectroscopy. A novel BODIPY-oxoporphyrinogen dyad which is able to bind with fluoride anion promoting the excited state ultrafast electron and energy transfer events mimicking the primary events in natural photosynthesis was introduced. Further, self-assembly of supramolecular complexes based on oxoporphyrinogens, fullerene, and different zinc porphyrin dimers was explored. The formed self-assembled complexes have shown photoinduced electron transfer. A novel push-pull supramolecular construct based on the spiro-locked N-heterocycle-fused zinc porphyrin was studied. The excited state charge separation and stabilization of this push-pull system was enhanced by the complexation with fluoride anion. Also, the effect of BODIPY functionalization and linkers on the electron transfer properties of a series of carbazole–BODIPY and phenothiazine-BODIPY dyads were investigated. These findings are important to develop advanced and efficient BODIPY-based donor-acceptor systems for efficient light harvesting applications. The entire study aims to expand our understanding of these systems and contribute towards the advancement of sustainable energy technologies.

Since their discovery, fullerenes and metallofullerenes have been investigated regarding their structures, synthesis, isolations, and applications. The highly symmetric structures of fullerenes and metallofullerenes lead to extraordinary physical properties, such as electron transfers, and attract major attention from the science community. It has been well established that the stabilities of fullerenes and metallofullerenes can be estimated by recognizing structural patterns. Recently, we developed a generalized spiral program and additional codes and believe they are useful for fullerene/metallofullerene researchers. The higher fullerenes, those with more than 90 carbon atoms, also follow certain structural patterns. In our studies, we have shown that the higher fullerenes with tubular structures are stable in thermodynamics and can survive the aminopropanol reaction, but other spherical fullerenes cannot. For the past three decades, great efforts have been devoted to applying fullerenes and metallofullerenes as electronic materials. In our studies, we find the ground state electron transfer properties endow metallofullerenes as an ideal material for perovskite solar cells to enhance the stabilities. It has been shown in our investigations that common metallofullerenes, such as Sc3N@C80, are capable to be as the electron transfer layers in perovskite solar cells, and the test demonstrates that our novel perovskite solar cells may achieve high stability and high efficiency. The electron transfer abilities of metallofullerenes are studied with the M2@C79N since electron densities located in between the two metal atoms convert between a single electron bond and a double electron bond. The huge spherical electron delocalized structures of fullerenes and metallofullerenes lead to strong interactions with other delocalized systems, such as graphene. Previous studies have shown that graphene has a unique ability in molecular adsorptions. However, the graphene surface is not always flat and the rippled areas have effects on the packing styles. Therefore, we examined the behavior of fullerenes on the rippled graphene surface and then compared with another flat molecule, PTCDA. The results show that the effect of rippled areas varies due to molecular structures. This study gives instructions for electronic device manufacturing using graphene and fullerenes. In our studies, polarizability is a key factor of fullerenes and metallofullerenes. It has been shown that the chromatographic retention behavior has a strong relationship with the average polarizability of a molecule. Based on the experimental data, we built a model for the prediction of chromatographic retention times using computational polarizabilities. After that, we validated the model by two series of chromatographic data. The characterization of carbon-based materials has been long investigated. In the last chapter, we introduce a dynamic nuclear polarization-based method to characterize the structures of chars and studied the adsorption of oxygen on the activated radical sites. Overall, the dissertation reports my Ph. D. studies in the areas including theoretical studies of fullerene geometries, chromatographic models, applications and also experimental studies of the applications of fullerenes/metallofullerenes and characterization. / Doctor of Philosophy / Fullerenes and metallofullerenes are important materials for engineering and science. In general, a fullerene cage contains only carbon atoms and has a closed spherical structure. Theoretically, for a given number of carbon atoms, there are thousands of different ways to assemble a fullerene structure, just like assembling Lego. However, just a limited number of fullerene molecules have been discovered. In the past four decades, several theories have been proposed to explain the fact. For example, an isolated pentagon rule shows that the fullerene structures should not have any conjugated pentagons, which will decrease the stabilities of fullerene molecules. In this dissertation, I would like to show our results, which demonstrate fullerenes that can be synthesized follow certain patterns. We apply experimental and theoretical methods to discover the patterns and explain the reason. The application of fullerenes/metallofullerenes is another hot topic. We consider the structures of fullerenes endow them extraordinary abilities of electron transfers. Therefore, we use metallofullerenes as electron transfer material in a solar cell, and we have a good solar cell with high efficiency. We also inspect the interactions between fullerenes and rippled graphene surface. The results are also extended to understand the chromatographic behavior of fullerenes. By considering the physical properties of fullerenes, we build up simple models to simulate the chromatographic retention behaviors of fullerene inside the chromatographic column. The characterization of carbon-based material is a big challenge and in this dissertation, we demonstrate our contributions of a novel method for characterization, which can detect activated carbons.

The exploitation of the relationship between the chemical and physical properties of materials is the hallmark of advancing science throughout the world. The basic understanding of how and why molecules react and interact with each other in different environments allows for the discovery and implementation of new materials and devices that not only advance the state of human life but continually change the planet. The work described in this dissertation generally falls under three diverse categories: functionalization of fullerenes, investigation of host/guest interactions in solution, and the synthesis and characterization of ion containing polymers. The separation and functionalization of fullerenes is a recent and exciting area of research. The separation methods outlined are intended to increase the availability of endohedral metallofullerenes by decreasing their cost of production. Functionalized fullerene species were achieved through Bingel and Prato reactions to provide materials with novel functional groups. These materials may be further utilized in photovoltaic or other organic electronic devices. The characterization of noncovalent interactions between different molecules in solution is the focus of supramolecular chemistry. Isothermal Titration Calorimetry stands out as one of the best, among the many methods used to elucidate the characteristics of these systems. The binding of bis- imidazolium and paraquat guests with macrocyclic host molecules has been explored in this work. The measurements of the association constants for these systems will aid in the ongoing synthesis of new host/guest systems. Ion containing polymers were synthesized and characterized for their use in electroactive devices. Imidazolium containing polymers with bulky anions were synthesized on low glass transition polymer chains. These materials had enhanced ion conductivity and may eventually be used in electronic actuator materials. / Ph. D.

Despite its extremely low solubility in water, fullerite C₆₀ can form colloidally stable aqueous suspensions containing nanoscale C₆₀ particles (nC₆₀) when it is subject to contact with water. nC₆₀ is the primary fullerene form following its release to the environment. The aim of the present study was to provide fundamental insights into the properties and environmental impacts of nC₆₀. nC₆₀ suspensions containing negatively charged and heterogeneous nanoparticles were produced via extended mixing in the presence and absence of citrate and other carboxylates. These low-molecular weight acids were employed as simple surrogates of natural organic matter. The properties of nC₆₀ were characterized using dynamic light scattering (DLS), transmission electron microscopy (TEM), and UV-Vis spectroscopy. nC₆₀ produced in the presence of carboxylate differs from that produced in water alone (aq/nC₆₀) with respect to surface charge, average particle size, interfacial properties, and UV-Vis spectroscopic characteristics. Importantly, regularly shaped (spheres, triangles, squares, and nano-rods) nC₆₀ nanoparticles were observed in carboxylate solutions, but not in water alone. This observation indicates that a carboxylate-mediated 'bottom-up' process occurs in the presence of carboxylates. Changes in the UV-Vis spectra over time indicate that reactions between C₆₀ and water or other constituents in water never stop, potentially leading to significant morphologic changes during storage or as a result of simple dilution. These results suggest that studies examining the transport, fate, and environmental impacts of nC₆₀ should take the constituents of natural waters into consideration and that careful examination on the properties of the tested nC₆₀ should be conducted prior to and during each study. / Ph. D.

Machine learning methods are now extensively applied in various scientific research areas to make models. Unlike regular models, machine learning based models use a data-driven approach. Machine learning algorithms can learn knowledge that are hard to be recognized, from available data. The data-driven approaches enhance the role of algorithms and computers and then accelerate the computation using alternative views. In this thesis, we explore the possibility of applying machine learning models in the prediction of chromatographic retention behaviors. Chromatographic separation is a key technique for the discovery and analysis of fullerenes. In previous studies, differential equation models have achieved great success in predictions of chromatographic retentions. However, most of the differential equation models require experimental measurements or theoretical computations for many parameters, which are not easy to obtain. Fullerenes/metallofullerenes are rigid and spherical molecules with only carbon atoms, which makes the predictions of chromatographic retention behaviors as well as other properties much simpler than other flexible molecules that have more variations on conformations. In this thesis, I propose the polarizability of a fullerene molecule is able to be estimated directly from the structures. Structural motifs are used to simplify the model and the models with motifs provide satisfying predictions. The data set contains 31947 isomers and their polarizability data and is split into a training set with 90% data points and a complementary testing set. In addition, a second testing set of large fullerene isomers is also prepared and it is used to testing whether a model can be trained by small fullerenes and then gives ideal predictions on large fullerenes. / Machine learning models are capable to be applied in a wide range of areas, such as scientific research. In this thesis, machine learning models are applied to predict chromatography behaviors of fullerenes based on the molecular structures. Chromatography is a common technique for mixture separations, and the separation is because of the difference of interactions between molecules and a stationary phase. In real experiments, a mixture usually contains a large family of different compounds and it requires lots of work and resources to figure out the target compound. Therefore, models are extremely import for studies of chromatography. Traditional models are built based on physics rules, and involves several parameters. The physics parameters are measured by experiments or theoretically computed. However, both of them are time consuming and not easy to be conducted. For fullerenes, in my previous studies, it has been shown that the chromatography model can be simplified and only one parameter, polarizability, is required. A machine learning approach is introduced to enhance the model by predicting the molecular polarizabilities of fullerenes based on structures. The structure of a fullerene is represented by several local structures. Several types of machine learning models are built and tested on our data set and the result shows neural network gives the best predictions.