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Molecular Vibrations And Shape-Selectivity: A Computational Model Of Biofuel Precursors In Zeolites, Babgen Manookian 2022 University of Massachusetts Amherst

Molecular Vibrations And Shape-Selectivity: A Computational Model Of Biofuel Precursors In Zeolites, Babgen Manookian

Doctoral Dissertations

We have used Density Functional Theory (DFT) to model acyclic and cyclic olefins in acidic zeolites. We have studied the impact of host-guest interactions between adsorbed molecules and zeolite frameworks through the lens of molecular vibrations and shape-selectivity. This work considered three zeolite frameworks with varying pore structures and environments: large pore zeolite HMOR and medium pore zeolites HZSM-5 and HZSM-22. A key finding is that for acyclic olefins in acidic zeolites there exists two regimes of host-guest interaction: a strong interaction leading to protonation and a weak interaction between charged guest and zeolite framework. We found that these interactions ...


Ab Initio Study Of The Rotation Of The C≡C Group In Benzvalyne, Advait Praveen 2022 University of Mississippi

Ab Initio Study Of The Rotation Of The C≡C Group In Benzvalyne, Advait Praveen

Honors Theses

For benzvalyne, we have characterized the minima and transition states of the molecule using the B3LYP, MP2, and M06-2X methods and aug-cc-pVTZ basis set. This was done by calculating the energy of the molecule while rotating the alkyne bond contained within it. After the initial rotation, optimized parameters for the molecule are found. Following this, imaginary frequencies were attempted to be found at the local maximum produced by the graph of the Energy v. rotation angle. Should the negative frequencies be found, the energy of the molecule will be characterized by the CCSD (T) method and aug-cc-pVQZ basis sets. This ...


Nitro-Aromatic Polymers For Conversion-Style Battery Cathodic Materials, Brady P. Samuelson 2022 University of South Dakota

Nitro-Aromatic Polymers For Conversion-Style Battery Cathodic Materials, Brady P. Samuelson

Honors Thesis

The development of organic electrode materials in rechargeable batteries has seen a resurgence in recent decades. This spike in interest is mostly due to the increased investments in renewable energy sources, grid-scale energy storage, and the rapid transition to electric vehicles. Current lithium battery cathode materials typically use some form of lithium metal oxide (specific capacity: 272 mAh g-1 which has problems with limited capacity, thermal runaway, and an unreliable supply chain. Our research group’s solution involves investigating new lightweight, organic redox groups combined with a conductive polymer backbone to serve as a possible replacement for the cathode ...


Theoretical Studies Of Benzoquinone Reactivity In Acidic And Basic Environments, Natali Majoras 2022 University of Tennessee at Chattanooga

Theoretical Studies Of Benzoquinone Reactivity In Acidic And Basic Environments, Natali Majoras

Honors Theses

Quinones are a class of organic compounds containing a six-membered unsaturated ring with two carbonyl groups. They are biologically relevant mostly due to their ability to participate in redox reactions. Prior experiments in our lab showed that quinones can induce protein modifications that are pH dependent. In an acidic environment the modifications were less significant than in a basic environment. Previous computational studies have also been carried out to model, in neutral solutions, the reaction between various quinones and various amines. Various amine groups are used as a model for the amino group of lysine to represent protein modification. The ...


Gas-Phase Proton Affinities For Twenty Of The Proline-Containing Dipeptides, Henry Cardwell 2022 William & Mary

Gas-Phase Proton Affinities For Twenty Of The Proline-Containing Dipeptides, Henry Cardwell

Undergraduate Honors Theses

Peptide fragmentation plays a crucial role in the analysis of proteins through mass spectrometry-based proteomics. Most proteomics experiments take place in the low-energy regime and are governed by the mobile proton model which predicts random cleavages along the peptide backbone; however, there sometimes arise circumstances where the mobile proton model fails causing sequencing algorithms to misidentify peptides. One such example is noted in the “proline effect” wherein proline-containing peptides preferentially fragment N-terminal. While it has been established that the “proline effect” is due to the rigidity and basicity of the proline N-terminus, a further understanding of the factors influencing the ...


Implications Of Metal Coordination In Damage And Recognition Of Nucleic Acids And Lipid Bilayers, Ana Dreab 2022 Old Dominion University

Implications Of Metal Coordination In Damage And Recognition Of Nucleic Acids And Lipid Bilayers, Ana Dreab

Chemistry & Biochemistry Theses & Dissertations

Metal ions have a myriad of biological functions from structural stability to enzymatic (de)activation and metabolic electron transfer. Redox-active metals also mediate the formation of reactive oxygen species which may either cause oxidative damage or protect cellular components. Computational modeling is used here to investigate the role of (1) metal-ion binding to antimicrobial peptides, (2) metal-ion removal and disulfide formation on zinc finger (ZF) proteins, and (3) coordination of thiones/selones for the prevention of metal-mediated redox damage.

Piscidins, natural-occurring antimicrobial peptides, efficiently kill bacteria by targeting their membranes. Their efficacy is enhanced in vitro by metal-binding and the ...


Synthesis And Characterization Of A Novel Reaction-Based Azaborine Fluorescent Probe Capable Of Selectively Detect Carbon Monoxide Based On Palladium-Mediated Carbonylation Chemistry, Samuel Moore, Carl Jacky Saint-Louis 2022 Kennesaw State University

Synthesis And Characterization Of A Novel Reaction-Based Azaborine Fluorescent Probe Capable Of Selectively Detect Carbon Monoxide Based On Palladium-Mediated Carbonylation Chemistry, Samuel Moore, Carl Jacky Saint-Louis

Symposium of Student Scholars

Azaborines are fascinating compounds because they possess valuable properties such as photochemical stability, have high molar absorption coefficient and high fluorescent quantum yields, as well as large Stokes shifts and tunable absorption/emission spectra. Here, we designed, synthesized, and will examine a novel reaction-based azaborine fluorescent probe capable of selectively detect carbon monoxide (CO) based on palladium-mediated carbonylation chemistry. This novel azaborine fluorescent probe will exhibit high selectivity for CO and display a robust turn-on fluorescent response in the presence of CO in aqueous buffer solution.


Ketal-Azaborine Versus Ketal-Azaborine With A Spacer: Structural Effects On The Photophysical Properties Of Tunable Heteroaromatic Polycyclic Chromophores, Albert Campbell, Janiyah Riley, Samuel Moore, Albert Campbell 2022 Kennesaw State University

Ketal-Azaborine Versus Ketal-Azaborine With A Spacer: Structural Effects On The Photophysical Properties Of Tunable Heteroaromatic Polycyclic Chromophores, Albert Campbell, Janiyah Riley, Samuel Moore, Albert Campbell

Symposium of Student Scholars

Flat-structured heteroaromatic polycyclic compounds with extended conjugated π-systems such as azaborines are in high demand in the material and imaging technology markets because of their unique features such as simultaneous tunability of fluorescence color and intensity. We have designed, synthesized, and investigated a series of novel conjugated thermally stable ketal-azaborine chromophores that contain a phenyl ring as a spacer between electronic moieties and the ketal-azaborine core as easily tunable high-luminescent organic materials. We investigated the impact of the phenyl spacer on the ketal-azaborine unit. We examined the structural effects on their photophysical properties by incorporating electron –donating and –withdrawing substituents ...


Azaborine Versus Azaborine With A Spacer: Structural Effects On The Photophysical Properties Of Tunable Azaborine Chromophores, Kaia Ellis, Janiyah Riley, Lyric Gordon, Janiyah Riley 2022 Kennesaw State University

Azaborine Versus Azaborine With A Spacer: Structural Effects On The Photophysical Properties Of Tunable Azaborine Chromophores, Kaia Ellis, Janiyah Riley, Lyric Gordon, Janiyah Riley

Symposium of Student Scholars

Azaborines are fascinating compounds because of their valuable and interesting optical properties making them suitable to be utilized in many optoelectronic devices. We have designed, synthesized, and investigated a series of novel conjugated thermally stable azaborine chromophores by incorporating a phenyl ring as a spacer linking the chromophore to different electronic moieties as easily tunable high-luminescent organic materials. We investigated the effect of the phenyl spacer on the azaborine unit. The substituent effects of different electronic moieties were investigated by the insertion of electron –withdrawing and –donating moieties to the phenyl spacer. We examined the role of the electron –donating ...


Computer Simulation Of Raman Spectra And Mode Assignment: Application To Methane, Oluwaseun Omodemi, Ciara Tyler, Martina Kaledin 2022 Kennesaw State University

Computer Simulation Of Raman Spectra And Mode Assignment: Application To Methane, Oluwaseun Omodemi, Ciara Tyler, Martina Kaledin

Symposium of Student Scholars

This work uses driven molecular dynamics (DMD) method, in conjunction with an analytic PES calculated using MP2/aug-cc-pVDZ energies to identify and assign Raman vibrational modes of methane. Recently, a new linearized approach was proposed for the Polarizability Tensor Surfaces (PTS) that yields a unique solution to the least-squares fitting problem and provides a competitive level of accuracy compared to the non-linear PTS model. We used the previously reported B3LYP/6-31+G(d) molecular geometries for CH4 and generated a new PTS at the MP2/aug-cc-pVDZ level of theory. The performance of the linearly parametrized functional form for the ...


A Proposed Treatment Of Mixed Connective Tissue Disease By Competitive Inhibition Of Autoantibodies, Thomas Russell 2022 Liberty University

A Proposed Treatment Of Mixed Connective Tissue Disease By Competitive Inhibition Of Autoantibodies, Thomas Russell

Senior Honors Theses

Mixed Connective Tissue Disease is an autoimmune disease characterized by Raynaud’s phenomenon and arthritis among other symptoms. It is primarily caused by antibodies that target the U1-RNP 70K peptide. The treatment proposed in this paper uses competitive inhibition to prevent the binding of the anti-U1-RNP 70K antibodies with the U1-RNP 70K peptide. A method for testing the designed treatment in silico is proposed using AutoDock Vina docking software.


Nonhematopoietic Erythropoietin: A Study Of Signaling, Structure, And Behavior, Nicholas John Pekas 2022 University of South Dakota

Nonhematopoietic Erythropoietin: A Study Of Signaling, Structure, And Behavior, Nicholas John Pekas

Dissertations and Theses

Erythropoietin (EPO) is a cytokine hormone known for initiating red blood cell proliferation by binding to its homodimer receptor (EPOR)2 in the bone marrow. Recent progress in neurobiology has shown that EPO also exerts robust neurotrophic and neuroprotective activity in the CNS. It is widely thought that EPO’s neurotrophic activity is centrally involved in its antidepressant and cognitive enhancing effects. However, EPO’s potent erythropoietic effects prevent it from being used in the clinic to treat psychiatric disorders. A chemically engineered non-erythropoietic derivative of EPO, carbamoylated EPO (CEPO), produces psychoactive effects without activating hematopoiesis. However, CEPO is expensive ...


From Evaluating The Performance Of Approximations In Density Functional Theory To A Machine Learning Design, Pedram Tavazohi 2022 West Virginia University

From Evaluating The Performance Of Approximations In Density Functional Theory To A Machine Learning Design, Pedram Tavazohi

Graduate Theses, Dissertations, and Problem Reports

Density-functional theory (DFT) has gained popularity because of its ability to predict the properties of a large group of materials a priori. Even though DFT is exact, there are inaccuracies introduced into the theory due to the approximations in the exchange-correlation (XC) functionals. Over the 50 years of its existence, scientists have tried to improve the design of the XC functionals. The errors introduced by these functionals are not consistent across all types of solid-state materials. In this project, a high throughput framework was utilized to compare the theoretical DFT predictions with the experimental results available in the Inorganic Crystal ...


Analyzing The Free Energy Of Ions Sampling A Voltage Gated Sodium Ion Channel, Isabel Varghese 2022 Colby College

Analyzing The Free Energy Of Ions Sampling A Voltage Gated Sodium Ion Channel, Isabel Varghese

Honors Theses

Voltage gated sodium ion channels are implicated in cardiac diseases, seizures, etc., and they play a role in maintaining ionic homeostasis in cells. Computational studies use prokaryotic model because they are simpler but function similarly to human voltage gated sodium ion channels. This study uses molecular dynamics (MD) to study three specific questions regarding voltage gated sodium ion channels of Magnetococcus marinus. The first question in this study is how the free energy of sodium diffusion compares to that of calcium ion diffusion. We were not able to find any physically significant information due to poor sampling and a lack ...


Computational Catalyst Discovery: Active Classification Through Myopic Multiscale Sampling, Kevin Tran, Willie Neiswanger, Kirby Broderick, Eric Xing, Jeff Schneider, Zachary W. Ulissi 2021 Carnegie Mellon University

Computational Catalyst Discovery: Active Classification Through Myopic Multiscale Sampling, Kevin Tran, Willie Neiswanger, Kirby Broderick, Eric Xing, Jeff Schneider, Zachary W. Ulissi

Machine Learning Faculty Publications

The recent boom in computational chemistry has enabled several projects aimed at discovering useful materials or catalysts. We acknowledge and address two recurring issues in the field of computational catalyst discovery. First, calculating macro-scale catalyst properties is not straightforward when using ensembles of atomic-scale calculations [e.g., density functional theory (DFT)]. We attempt to address this issue by creating a multi-scale model that estimates bulk catalyst activity using adsorption energy predictions from both DFT and machine learning models. The second issue is that many catalyst discovery efforts seek to optimize catalyst properties, but optimization is an inherently exploitative objective that ...


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