Computational Chemistry Commons^™

Elucidating The Impacts Of Non-Covalent Interactions In Organic Materials Through A Multiscale Computational Approach, Sashen A. Ruhunage

Theses and Dissertations--Chemistry

Noncovalent interactions (NCIs) in π-conjugated organic materials serve as tunable levers that influence molecular structure and intermolecular interactions in the condensed phase and, in turn, impact the electronic, optical, and mechanical properties of these materials. NCIs include attractive dispersion, electrostatic, and induction interactions, as well as repulsive exchange interactions. However, how to design materials with NCI considerations remains an open question across many fields. Here, we seek to provide an electronic and atomistic perspective on these interactions through multiscale simulations to aid materials design, processing, and performance optimization. In this study, we investigate NCIs and their effects across various systems …

Towards Automating The Study And Discovery Of Electroactive Π-Conjugated Molecules, Rebekah Ann Duke-Crockett

Theses and Dissertations--Chemistry

Chemistry is entering a new paradigm of automation and data-driven discovery. Automated discovery is grounded in well-curated “big data.” As generative and predictive models fueled by simulation data see growing success, emerging robotic automation enables the generation of unprecedented volumes of experimental data. Automation-powered, data-driven approaches hold tremendous potential for groundbreaking insights and innovations, particularly in the study and discovery of electroactive π-conjugated molecules. Realizing this potential, however, requires democratizing chemical data and the automation needed to generate and use it. There is a need to expand access to the tools for findable, accessible, interoperable, and reusable (FAIR) data management …

Machine Learning Models For Molecular-Based Functional Organic Materials, Moses Ogbaje

Theses and Dissertations--Chemistry

Organic semiconductors (OSC) are of interest for a wide range of flexible optoelectronics applications, including transistors, solar cells, and sensors, to name a few. Despite their promise, the design and optimization of OSC pose significant challenges due to the complexity of the structures of the molecular building blocks, varied packing configurations of these building blocks in the solid state, which impacts the optical and electronic response, and sensitivity of the solid-state packing to material processing conditions. Accurately predicting the solid-state properties of OSC traditionally requires high-level quantum mechanical methods. These methods, however, can be computationally demanding, particularly for large molecules …

Response To Replication Stress And Maintenance Of Genome Stability By Wrn, The Werner Syndrome Protein, David K. Orren, Amrita Machwe

Markey Cancer Center Faculty Publications

Werner syndrome (WS) is an autosomal recessive disease caused by loss of function of WRN. WS is a segmental progeroid disease and shows early onset or increased frequency of many characteristics of normal aging. WRN possesses helicase, annealing, strand exchange, and exonuclease activities and acts on a variety of DNA substrates, even complex replication and re- combination intermediates. Here, we review the genetics, biochemistry, and probably physiological functions of the WRN protein. Although its precise role is unclear, evidence suggests WRN plays a role in pathways that respond to replication stress and maintain genome stability particularly in telomeric regions.

Inchi Isotopologue And Isotopomer Specifications, Hunter N. B. Moseley, Philippe Rocca-Serra, Reza M. Salek, Masanori Arita, Emma L. Schymanski

Markey Cancer Center Faculty Publications

This work presents a proposed extension to the International Union of Pure and Applied Chemistry (IUPAC) International Chemical Identifier (InChI) standard that allows the representation of isotopically‑resolved chemi‑ cal entities at varying levels of ambiguity in isotope location. This extension includes an improved interpretation of the current isotopic layer within the InChI standard and a new isotopologue layer specification for representing chemical intensities with ambiguous isotope localization. Both improvements support the unique isotopically‑ resolved chemical identification of features detected and measured in analytical instrumentation, specifically nuclear magnetic resonance and mass spectrometry.

Scientific contribution

This new extension to the InChI standard …

Molecular Understanding And Design Of Deep Eutectic Solvents And Proteins Using Computer Simulations And Machine Learning, Usman Lame Abbas

Theses and Dissertations--Chemical and Materials Engineering

Hydrophobic deep eutectic solvents (DESs) have emerged as excellent extractants. A major challenge is the lack of an efficient tool to discover DES candidates. Currently, the search relies heavily on the researchers’ intuition or a trial-and-error process, which leads to a low success rate or bypassing of promising candidates. DES performance depends on the heterogeneous hydrogen bond environment formed by multiple hydrogen bond donors and acceptors. Understanding this heterogeneous hydrogen bond environment can help develop principles for designing high performance DESs for extraction and other separation applications. This work investigates the structure and dynamics of hydrogen bonds in hydrophobic DESs …

Molecular Understanding Of Zwitterions And Quantum Computing For Sustainability, Manh Tien Nguyen

Theses and Dissertations--Chemical and Materials Engineering

The sustainable development of society needs sustainable energy solutions and the mitigation of greenhouse gas emissions. One key subject in this area is the development of safe and efficient ion-based batteries. Moreover, CO₂ capture is a crucial pathway in mitigating emissions from the combustion of fossil fuels. Ongoing efforts are to improve both technologies' safety and efficiency. This thesis presents our efforts to conduct computational research on understanding advanced zwitterionic electrolytes and CO₂ capture. Chapters 2-4 illustrate the computational research to understand ionic solvation in zwitterionic electrolytes. Solid-state electrolytes are essential for safer batteries. While solid polymer electrolytes …

Translating Chemistry, Structure, And Processing To The Solid-State Morphology And Function Of Organic Semiconductors Through Computational Modeling And Simulations, Chamikara D. Karunasena

Theses and Dissertations--Chemistry

The immense synthetic design space and material versatility have driven the exploration and development of organic semiconductors (OSC) over several decades. While many OSC designs focus on the chemistries of the molecular or polymer building blocks, a priori, multiscale control over the solid-state morphology is required for effective application of the active layer in a given technology. However, molecular assembly during solid-state formation is a complex function interconnecting the building block chemistry and the processing environment. Insufficient knowledge as to how these aspects engage, especially at the atomistic and molecular scales, has so far limited the ability to predict …

Developing And Deploying Data-Driven Tools For Accelerated Design Of Organic Semiconductors, Vinayak Bhat

Theses and Dissertations--Chemistry

Organic semiconductors have gained widespread attention due to their potential applications in flexible, low-cost, lightweight electronics, energy storage and generation technologies, and sensing applications. However, developing new organic semiconductors with improved performance remains a significant challenge due to the vast chemical space of possible molecular and materials structures. Furthermore, the high cost and time-consuming nature of experimental synthesis and characterization hinder the rapid discovery of new materials. To overcome these challenges, this dissertation presents a data-driven approach to organic semiconductor discovery. The primary focus of this work is the development of data-driven tools, namely machine learning models, to predict critical …

Water-Soluble Palladium, Copper, And Nickel Catalysts And Their Formation In Ligand-Free Suzuki-Miyaura Cross-Coupling Reactions, Priya Karna

Theses and Dissertations--Chemistry

Transition-metal catalyzed Suzuki-Miyaura (SM) cross coupling is a powerful synthetic method for constructing carbon-carbon and carbon-heteroatom bonds in designing organic compounds, agrochemicals, pharmaceuticals, and precursors for materials. However, the nature of catalysis and identity of the transition metal catalysts used in these reactions remain under debate or unknown. This dissertation reports the studies of three metals: Pd, Cu, and Ni. Pd-nanocluster catalysts and their formation in ligand-free SM reactions with Pd(II) nitrate as a precatalyst was investigated. The catalysts are water-soluble neutral Pd tetramer and trimer in their singlet electronic states as identified by UV-Vis absorption spectroscopy and are formed …

First Principles Calculations To Investigate Surface And Catalytic Properties Of Materials For Green Energy Generation, Keerthan Raghavendra Rao

Theses and Dissertations--Chemistry

Climate change due to greenhouse gas build up in the earth’s atmosphere is an existential threat to humanity. To mitigate climate change, a significant shift from fossil fuels is necessary. Over the years, several renewable energy sources like solar, wind, geothermal etc. have been explored with the aim providing carbon-free energy. In this work, we focus on using density functional theory (DFT) methods to investigate key functional properties of materials of interest for applications in solar cells and catalytic conversion for energy generation. We show geometric effects of carboxylic acid binding on a transition metal surface to impact the deoxygenation …

Computational Studies On Molecular Mechanisms For Dysregulation Of Monoamine Transporters By Hiv-1 Tat And Drug Discovery Of Novel Phosphodiesterase-2 Inhibitors, Charles A. Adeniran

Theses and Dissertations--Chemistry

Computational chemistry methods have been greatly used and has great potential in drug discovery and understanding the detailed molecular mechanism of biological processes. Scientific questions can initially be addressed using computational modeling and simulation studies. The common feature in this work is to understand intermolecular interactions related to protein targets in the brain, as it relates to HIV infection and Alzheimer’s Disease. HIV is among the world’s most deadly infectious diseases. Recent therapeutic advancements have begun to increase the life expectancy of people living with this virus. The mechanisms that lead to neurobiological complications known as HIV- associated neurocognitive disorders …

Development Of Accurate And Efficient Computational Methodologies For Predicting Protein-Ligand And Protein-Protein Binding Free Energies, Alexander Hamilton Williams

Theses and Dissertations--Pharmacy

Computational modeling is an invaluable tool in the drug discovery process either for small ligand or protein therapeutics. The widespread availability of protein X-Ray Crystal and Cryo-Electron Microscopy (Cryo-EM) structures has allowed for more accurate molecular dynamics (MD) simulations that are not reliant on methods such as homology modeling, which may produce structures that require significant computational time to demonstrate their stability. In this thesis we describe several novel methodologies for the computationally efficient modeling of protein/ligand and protein/protein complexes that may be employed within both large-scale virtual screenings and lead compound optimization. These methodologies may also be utilized in …