The main aim of work presented here is to understand photophysical processes of organic dyes and to design better organic molecules/systems which can be applied in many applications such as solar cells, photodynamic therapy, and fluorescence sensors. Developments of novel multichromophore organic materials for the above mentioned applications were made using computational tools. A brief description of the history of computational chemistry was given based on the photochemistry of organic dyes in the introductory chapters and also the importance of basis sets and functionals was discussed in order to produce accurate computational results. Density functional theory (DFT) and time-dependent DFT (TDDFT) calculations were performed to understand the photophysical processes in the porphyrin-perylene bisimide (HTPP-PDI) dyad that exhibited long-lived triplet states. The DFT results show that breaking the rigidity of PDI in HTPP-PDI was responsible for the generation of long-lived triplet states. Furthermore, six porphyrin derivatives were designed by introducing a 4,4’-dicarboxybutadienyl functional group to the porphyrin moiety and studied to investigate the substituent effects on the non-coplanarity, molecular orbitals, and excitation wavelength of the porphyrin donor. Five of the six proposed porphyrin derivatives are promising donors in the HTPP-PDI dyad to replace HTPP for its potential use in photodynamic therapy. Six donor- accepter(s) systems were designed for their potential application in solar cells. Four D-A1-A2 architectural triads, MTPA-TRC-AEAQ, MTPA-TRC-HTPP, MTPA-TRC-PDI, and MTPA-TRC-PBI were designed. The cascade electronic energy levels were obtained and experimentally observed, which lead to sequential electron transfers from 1MTPA* to TRC and then to AEAQ (HTPP/PDI/PBI) module as well as a hole transfer from 1AEAQ*(1HTPP*/1PDI*/1PBI*) to MTPA module. Therefore, all the D-A1-A2 systems we have designed are ambipolar. Interestingly, the lifetime of charge separated states of the newly designed MTPA*+-TRC-AEAQ*- was elongated to 650 ns, an eightfold of that of the donor-acceptor MTPA-TRC parent molecule (80 ns). However, different charge separated state lifetimes were obtained for MTPA*+-TRC-PDI*-(22ns) and MTPA*+-TRC-PBI*-(75ns). The photophysical results suggested that the charge separated state may decay to the triplet state when the charge separated state exhibits a higher energy level than the triplet state. Further, the photovoltaic tests indicated potential applications of MTPA-TRC-AEAQ in solar cells. DFT and TDDFT calculations were performed together with experimental studies to explore the nature of fluorescence enhancement in the anthracene-based sensor after the addition of Zn2+. A 23-fold fluorescence emission was quenched via non-radiative decay pathway in the absence of Zn2+. However, when the Zn2+ chelated to the sensor fluorescence intensity was increased remarkably. A 32-fold fluorescence increase was overserved and calculation results suggested this could be due to the inhibition of the electron-transfer pathway and enhanced rigidity of sensor-Zn2+ complex. The response selectivity of Zn2+ over Ca2+, Mg2+, Cu2+, and Hg2+ ions was also studied using DFT calculations and it was found that Zn2+ has a strong binding affinity to the sensor, which could be a potential application in the detection of Zn2+.

Investigating interactions between proteins and small molecules at an atomic scale is fundamental towards understanding biological processes and designing novel candidates during the pre-clinical stages of drug discovery. By optimizing the methods used to study these interactions in terms of accuracy and computational cost, we can accelerate this aspect of biological research and contribute more readily to therapeutic design. While biological assays and other experimental techniques are invaluable in quantitatively determining in vitro and in vivo inhibition activity, as well as validating computational predictions, there is an inherent benefit in the possible throughput provided by molecular dynamics (MD) simulations and related computational methods. These calculations provide researchers with unparalleled access to large amounts of all-atom sampling of biological systems, including non-physical pathways and other enhanced sampling methods. This dissertation presents research into advancing the application of expanded ensemble and other simulation-based methods of ligand design towards reliable and efficient absolute free energy of binding calculations on the scale of hundreds to thousands of small molecule ligands. This culminates in a combined workflow that allows for an automated approach to the force-field parameterization of custom systems, simulation preparation, optimization of the restraint and sampling protocols, production free energy simulations, and analysis that has facilitated the computation of absolute binding free energy predictions. Specifically highlighted is our ongoing effort to discover novel inhibitors of the main protease (Mpro) of SARS-CoV-2 as well as participation in the SAMPL9 Host-Guest Challenge. / Chemistry

Isomerization is a synthetically useful technique to form the more stable internal alkene from terminal alkene feedstock. Unfortunately, these transformations form a variety of isomers without catalyst control. Z alkenes are thermodynamically challenging to form compared to their E counterparts but are useful in pharmaceutical, fragrance, and flavor industries, making them sought-after products. Therefore, catalysts targeting specific regio- and stereoisomers, particularly Z alkenes, will benefit many fields. This work analyzes several Mo(0) complexes as Z-2-alkene selective isomerization catalysts. Particular focus has been given to cis-Mo(CO)4(PCy3)(piperidine) due to easy purification and characterization. Substantial improvement to reported Z selectivities have been obtained with this complex, though disadvantages exist. To have a clearer understanding of the mechanism and source of Z selectivity, DFT analysis was completed, and a mechanism proposed. A rare rotation of hydride and carbonyl ligands was found, only reported in one prior Mo complex, that facilitates the isomerization. Key characteristics were discovered that will be applied to develop future iterations with the goal of reducing, or removing, the disadvantages of this system. / Chemistry

Stereodivergent and enantiodivergent pathways for the Friedel–Crafts reactions were computationally studied with DFT methods. This study aims to explain recently observed solvent-dependent regioselectivity, and enantioselectivity when cinchona catalyst is used. Deprotonation reaction, Frontier Kohn-Sham orbitals, dual descriptors, Mulliken charges, and Hirshfeld atomic charge for reactant were calculated and analyzed. The most probable position of electrophilic attack and nucleophilic attack in-silico predicted aligns with experimental observations. The calculation of the transition states on the anionic and neutral model in a vacuum show preference for the electrophilic attack in the para position. In comparison to the anionic system, the presence of potassium cation improves ortho/para selectivity and increases the energy barrier. For the key enantioselective step, 12 transition states were calculated which covers 4 representative product such: (R)-ortho, (S)-ortho, (R)-para, and (S)-para. The computational study suggests, that the presence of the cesium cation is essential for the arrangement of the reactant and catalyst in the transition state, which leads to observed selectivity.

Brief explanation and history of cinchona based Phase Transfer Catalysis (PTC). Studied aryl acetates in PTC, encompassing napthoyl, 6-methoxy napthoyl, phenyl and protected 4-hydroxy phenyl acetates. Investigated means of controlling the selectivity of the PTC reaction by changing the electrophile size, the ether side group size or by addition of inorganic salts. Found that either small or aromatic electophiles increased enantioselectivity more than aliphatic electrophiles, and that increasing the size of ether protecting group also increased selectivity. Positive effects of salt addition included either decreasing reaction time or increasing enantiomeric excess. Applied findings towards the synthesis of S-equol. Computational experiments working towards deducing the transition state between PTC and aryl acetate substrates.

<p>Automated reaction prediction has the potential to elucidate complex reaction networks for many applications in chemical engineering, including materials degradation, drug design, combustion chemistry and biomass conversion. Unlike traditional reaction mechanism elucidation methods that rely on manual setup of quantum chemistry calculations, automated reaction prediction avoids tedious trial-and-error learning processes and greatly reduces the risk of leaving out important reactions. Despite these promising advantages, the potential of automated reaction prediction as a general-purpose tool is still largely unrealized, due to high computational cost and inconsistent reaction coverage. Therefore, this dissertation develops methods to simultaneously reduce the computational cost and increase the reaction coverage. Specifically, the computational cost is reduced by the development of more efficient transition state (TS) localization workflows and fast molecular and reaction property prediction packages, while the reaction coverage is increased by a comprehensive reaction space exploration based on mathematically defined elementary reaction steps. These components are implemented in two open-source packages, one is TAFFI (Topology Automated Force-Field Interactions) component increment theory (TCIT) and the other is Yet Another Reaction Program (YARP).</p> <p><br></p> <p>The first package, TCIT, is the first component increment theory based molecular property prediction package. TCIT is based on the locality assumption, which decomposes molecular thermochemistry properties into the summation of the contributions of each subgraph. In contrast to the traditional "group" increment theory, TCIT treats each subgraph as the central atom plus its nearest and next-nearest neighboring atoms, and consistently parameterizes the contribution of each component according to purely quantum chemistry calculations. Although all parameterizations are based on quantum chemical calculations, when benchmarked against experimental data, TCIT provides more accurate predictions compared to traditional methods using the same experimental dataset for parameterization. With TCIT, the molecular properties (e.g., enthalpy of formation) and reaction properties (e.g., enthalpy of reaction) can be accurately predicted in an on-the-fly manner. The second package, YARP, is developed for automated reaction space exploration and deep reaction network prediction. By optimizing the reaction enumeration, geometry initialization, and transition state convergence algorithms that are common to many prediction methodologies, YARP (re)discovers both established and unreported reaction pathways and products while simultaneously reducing the cost of reaction characterization nearly 100-fold and increasing convergence of transition states, comparing with recent benchmarks. In addition, an updated version of YARP, YARP v2.0, further reduces the cost of reaction characterization from 100-fold to 300-fold, while increasing the reaction coverage beyond the scope of elementary reaction steps. This combination of ultra-low cost and high reaction-coverage creates opportunities to explore the reactivity of larger systems and more complex reaction networks for applications like chemical degradation, where computational cost is a bottleneck.</p> <p><br></p> <p>The power of TCIT and YARP has been demonstrated by a broad range of applications. In the first application, YARP was used to explore the reactivity of unimolecular and bimolecular reactants, comprising a total of 581 reactions involving 51 distinct reactants. The algorithm discovered all established reaction pathways, where such comparisons are possible, while also revealing a much richer reactivity landscape, including lower barrier reaction pathways and a strong dependence of reaction conformation in the apparent barriers of the reported reactions. Secondly, YARP was applied to the search for prebiotic chemical pathways, which is a long-standing puzzle that has generated a menagerie of competing hypotheses with limited experimental prospects for falsification. With YARP, the space of organic molecules that can be formed within four polar or pericyclic reactions from water and hydrogen cyanide (HCN) was comprehensively explored. A surprisingly diverse reactivity landscape was revealed within just a few steps of these simple molecules and reaction pathways to several biologically relevant molecules were discovered involving lower activation energies and fewer reaction steps compared with recently proposed alternatives. In the third application, predicting the reaction network of glucose pyrolysis, YARP generated by far the largest and most complex reaction network in the domain of biomass pyrolysis and discovered many unexpected reaction mechanisms. Further, motivated by the fact that existing reaction transition state (TS) databases are comparatively small and lack chemical diversity, YARP, together with the concept of a graphically defined model reaction, were utilized to address the data gap by comprehensively characterizing a reaction space associated with C, H, O, and N containing molecules with up to 10 heavy (non-hydrogen) atoms. The resulting dataset, namely Reaction Graph Depth 1 (RGD1) dataset, is composed of 176,992 organic reactions possessing at least one validated TS, activation energy, enthalpy of reaction, reactant and product geometries, frequencies, and atom-mapping. The RGD1 dataset represents the largest and most chemically diverse TS dataset published to date and should find immediate use in developing novel machine learning models for predicting reaction properties. In addition to exploring the molecular reaction space, YARP was also extended to explore and characterize reaction networks in heterogeneous catalysis systems. With ethylene oligomerization on silica-supported single site Ga catalysts as a model system, YARP illustrates how a comprehensive reaction network can be generated by using only graph-based rules for exploring the network and elementary constraints based on activation energy and system size for identifying network terminations. The automated reaction exploration (re)discovered the Ga-alkyl-centered Cossee-Arlman mechanism that is hypothesized to drive major product formation while also predicting several new pathways for producing alkanes and coke precursors. The diverse scope of these applications and milestone quality of many of the reaction networks produced by YARP  illustrate that automated reaction prediction is approaching a general-purpose capability.</p>

<p>Radical polymers bearing open-shell moieties at their pendant sites offer potential advantages in processing, stability, and optoelectronic properties compared to conventional doped conjugated polymers. The rapid development of radical-containing polymers has occurred across various applications in energy storage devices and electronic systems. However, significant gaps still exist in understanding the key structure-property-function relationships governing charge transport phenomena in these materials. Most reported radical conductors primarily rely on (2,2,6,6-tetramethylpiperidin-1-yl)oxyl (TEMPO) radicals, which raises fundamental questions about the ultimate limits of charge transport capabilities and the impact of radical chemistry choice on material deficiencies. Moreover, an understanding gap persists when it comes to connecting the computable electronic features of individual units and the charge transport behavior of these materials in condensed phases. This dissertation seeks to address these gaps by developing a molecular understanding of charge transport in radical-bearing materials through a combined computational and experimental approach.</p> <p><br></p> <p>The initial stage of this dissertation investigated the impact of dimeric orientations and interactions on charge transport by conducting a density functional theory (DFT) study on a diverse set of open-shell chemistries relevant to radical conductors. The results revealed the anomalously high reorganization energies of the TEMPO radical due to strong spin-localization, which may result in inefficient charge transfer. Additionally, a significant mismatch was identified between dimeric conformations favored by intermolecular interactions and those maximizing charge transfer. This study provided new insights into the impact of steric hindrance and spin delocalization on elementary charge transfer steps and suggests opportunities for exploiting directing interactions to enhance charge transport in these materials.</p> <p><br></p> <p>Building upon these findings, we established a direct relationship between the molecular architecture and intrinsic charge transport properties. To accomplish this, single-molecule characterization methods (i.e., break junction techniques) were implemented to study the nanoscale charge transport properties of radical-containing oligomeric nonconjugated molecules. Temperature-dependent measurements and molecular modeling revealed that the presence of radicals improves tunneling at the nanoscale. Integrating open-shell moieties into nonconjugated molecular structures significantly enhances charge transport, thereby characterizing charge transport through radicals at the individual level and opening new avenues for implementing molecular engineering in the field of nanoelectronics.</p> <p><br></p> <p>To further connect the electronic properties of repeat units with the condensed-phase charge transport behavior of radical polymers, a quantum chemical study was carried out to explicitly evaluate the interplay between polymer design, open-shell chemistries, and intramolecular charge transport. After comprehensive conformational sampling of the configurational space of radical polymers, we determined their anticipated intrachain charge transport values by utilizing graph-based transport metrics. We show that charge transport in radical polymers primarily hinges on the choice of radical chemistry, which in turn affects the optimal selection of backbone chemistry and spacer group to ensure proper radical alignment and prevent undesired trap states. These findings highlight the potential for a substantial synthetic exploration in radical polymers for radical conductors.</p> <p><br></p> <p>In summary, this dissertation provides compelling evidence of radical-mediated charge transport and suggests potential design guidelines to enhance the charge transfer behavior of radical-containing polymer materials. Furthermore, these findings inform future research directions in fine-tuning molecular engineering and modular design to enable the development of radical-based materials and their end-use applications in organic electronics.</p>

Redox reactions are crucial to biological processes that protect organisms against oxidative stress. Metalloenzymes, such as cytochrome c peroxidases which reduce excess hydrogen peroxide into water in the periplasm of multiple bacterial organisms, play a key role in detoxification mechanisms. While accurate computational tools can be used to simulate ground state redox potentials in biomolecules, adapting such approaches to properly describe redox reactions in transition metal complexes, particularly in hemes in heterogeneous protein environments, remains a significant challenge. Here we present the results of polarizable hybrid QM/MM studies of the reduction potentials of two heme sites in the cytochrome c peroxidase of Nitrosomonas europaea. The simulated redox potential of the catalytic site Low Potential (LP) is in good agreement with the experiment, while for the High Potential (HP) heme the computational estimate significantly overestimate the experimental value. We have found that environment polarization shifts the computed value of the redox potential of the catalytic LP heme by 1.3 V, while it does not affect that of the non-catalytic High Potential (HP) heme. We demonstrate that it is necessary to account for mutual polarization of heme site and the protein environment when describing redox processes, particularly those that involve more charged heme sites. We have explored the role of various factors such as heme geometries, axial ligands, propionate side chains, and electrostatic field of the protein in tuning the redox potentials of hemes in NeCcP. The fluctuations in computed vertical ionization and electron attachment energies are predominantly affected by fluctuations in the electrostatic field of the environment but not by fluctuations in heme geometries. We attribute the difference in computed LP and HP heme reduction potentials of 0.05 V and 1.15 V, respectively, to different axial ligands and electrostatic interactions of the hemes with the protein environment. / 2023-06-30T00:00:00Z

Computational chemistry is a branch of modern chemistry that utilizes the computers to solve chemical problems. The fundamental of computational chemistry is Schrödinger equation. To solve the equation, researchers developed many methods based on BornOppenheimer Approximation, such as Hartree-Fock method and DFT method, etc. Computational chemistry is now widely used on reaction mechanism study and new chemical designing. In the first project described in Chapter 3, we designed phosphine oxide modified Ag3, Au3 and Cu3 nanocluster catalysts with DFT method. We found that these catalysts were able to catalyze the activation of H2 by cleaving the H-H bond asymmetrically. The activated catalyst-2H complex can be further used as reducing agent to hydrogenate CO molecule to afford HCHO. The mechanism study of these catalysts showed that the electron transfer from electron-rich metal clusters to O atom on the phosphine oxide ligand is the major driving force for H2 activation. In addition, different substituent groups on phosphine oxide ligand were tested. Both H affinity of metal and the substituent groups on ligand can both affect the activation energy. Another project described in Chapter 4 is the modelling of catalyst with DFT. We chose borane/NHC frustrated Lewis pair (FLP) catalyzed methane activation reaction as example to establish a relationship between activation energy and catalysts’ physical properties. After performing simulation, we further proved the well-accepted theory that the electron transfer is the main driving force of catalysis. Furthermore, we were able to establish a linear relationship for each borane between activation energy and the geometrical mean value of HOMO/LUMO energy gap (ΔEMO). Based on that, we introduced the formation energy of borane/NHC complex (ΔEF) and successfully established a generalized relationship between Ea and geometrical mean value of ΔEMO and ΔEF. This model can be used to predict reactivity of catalysts.

Low energy electron (LEE) driven chemistry underpins a wide range of interdisciplinary fields, including radiation biology, redox chemistry, astrochemistry and biomaterial design. A growing interest in the chemistry of LEEs concerns the radiative damage to DNA. Studies have found that LEEs can induce single and double-strand breaks in DNA by forming a negative ion resonance (NIR). These processes are remarkably site-specific and have been utilized to synthesize radiosensitizers, which aid in identifying target cells in hypoxic tumors in radiation therapy. Despite the prevalence of LEE-induced reactions, computational studies of such processes are limited compared to thermal and photochemical reactions. The relative scarcity in computational studies of LEE-induced reactions stems from the difficulties in the theoretical treatment of NIRs. In our work, we report new developments on the application of quantum chemical methods to NIRs. We demonstrate that the combination of approaches developed for resonances with multi reference electronic structure methods enables the computation of various types of NIRs in a single calculation. Additionally, we show that multi-reference methods can also quantify the mixing between NIRs. It is observed that the mixing between resonances can have significant consequences on their lifetimes. We also report the development of a new technique, the continuum remover Feshbach projection operator approach, which uses the conventional methods developed for bound states to characterize resonances. We show that this new approach is straightforward to implement with standard electronic structure packages, it is efficient, and provides promising results. / Chemistry