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- Creators: Barrett, The Honors College
Description
In order to better understand the physical properties of polyethylene, an extremely common plastic used mostly in packaging, many scientists and engineers use olecular dynamics. To reduce the computational expense associated with traditional atomistic molecular dynamics, coarse-grained molecular dynamics is often used. Coarse-grained molecular dynamics groups multiple atoms into single beads, reducing the number of degrees of freedom in a system and eliminating smaller atoms with faster kinematics. However, even coarse-grained methods have their limitations, one of which is timestep duration, which is limited by the maximum vibrational frequency in the coarse-grained system. To study this limitation, a coarse-grained model of polyethylene was created such that every C 2 H 4 unit was replaced with a bead. Coarse-grained potentials for bond-stretching, bond-bending, and non-bonded interaction were generated using the iterative Boltzmann inversion method, which matches coarse-grained distribution functions to atomistic distribution functions. After the creation of the model, the coarse-grained potentials were rescaled by a constant so that they were less stiff, decreasing the maximum vibrational frequency of the system. It is found that by diminishing the bond-stretching potential to 6.25% of its original value, the maximum stable timestep can be increased 85% over that of the unmodified potential functions. The results of this work suggest that it may be possible to simulate lengthy processes, such as the crystallization of polyethylene, in less time with adjusted coarse-grained potentials. Additionally, the large discrepancies in the speed of bond-stretching, bond-bending, and non- bonded interaction dynamics suggest that a multi-timestep method may be worth investigating in future work.
ContributorsWiles, Christian Scott (Author) / Oswald, Jay (Thesis director) / Dai, Lenore (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
Ionic liquids are salts with low melting temperatures that maintain their liquid form below 100 °C, or even at ambient temperature. Ionic liquids are conductive, electrochemically stable, non-volatile, and have a low vapor pressure, making them a class of excellent candidate materials for electrolytes in energy storage, electrodeposition, batteries, fuel cells, and supercapacitors. Due to their multiple advantages, the use of ionic liquids on Earth has been widely studied; however, further research must be done before their implementation in space. The extreme temperatures encountered during space travel and extra-terrestrial deployment have the potential to greatly affect the liquid electrolyte system. Examples of low temperature planetary bodies are the permanently shadowed sections of the moon or icy surfaces of Jupiter’s moons. Recent studies have explored the limits of glass transition temperatures for ionic liquid systems. The project is centered around the development of an ionic liquid system for a molecular electronic transducer seismometer that would be deployed on the low temperature system of Europa. For this project, molecular dynamics simulations used input intermolecular and intramolecular parameters that then simulated molecular interactions. Molecular dynamics simulations are based around the statistical mechanics of chemistry and help calculate equilibrium properties that are not easily calculated by hand. These simulations will give insight into what interactions are significant inside a ionic liquid solution. The simulations aim to create an understanding how ionic liquid electrolyte systems function at a molecular level. With this knowledge one can tune their system and its contents to adapt the systems properties to fit all environments the seismometers will experience.
ContributorsDavis, Vincent Champneys (Author) / Dai, Lenore (Thesis director) / Gliege, Marisa (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
RNA granules are assemblies of RNA and proteins inside cells that serve multiple roles and functions. Some of the functions they serve in include a variety of organelles such as germ cell P granules, stress granules, and neuronal granules with diverse functions. Intrinsically disordered domains are abundant in the proteins responsible for RNA granules, and they have been attributed to the formation and degradation of RNA granules through a liquid-liquid phase separation (LLPS) process. LLPS is typically a reversible process where a homogenous fluid de- mixes into two distinct liquid phases. Here, 47 RNA granule proteins with such disordered regions have been surveyed. These proteins have been simulated using coarse-grained molecular simulations to determine size dependence on temperature change. Upper critical solution temperature (UCST) and lower critical solution temperature (LCST) are phase behaviors that can be calculated using the data gathered for scaling and phase behaviors of these proteins. We discovered that less charged amino acid contents are present in RNA granules in comparison to general disordered sequences. This is in line with the observation that charged amino acids are less preferred for the sequence to phase separate at physiological-relevant temperatures. More interestingly, there seems to be an even mix of sequences contributing to both UCST, LCST, and no phase behaviors and the average temperature dependent behaviors of all these proteins have a relatively weak temperature dependence within the temperature range 300 and 325K. The average suggest that these proteins might collectively contribute to RNA granules in a way that adapts to small temperature fluctuations.
ContributorsFrench, Nolan James (Author) / Zheng, Wenwei (Thesis director) / Garg, Vikas (Committee member) / College of Integrative Sciences and Arts (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
In recent years, experimental and theoretical evidence has pointed to the existence of biologically active proteins that either include unstructured regions or are entirely unstructured. Referred to as intrinsically disordered proteins (IDPs), they are now known to be involved in diverse functions, much as any folded protein. Mutations in IDPs have been implicated in multiple neurodegenerative diseases. Considering the disordered nature of IDPs, there are limited structure features that can be used to quantify the disordered state. One such pair of variables are the radius of gyration (Rg) and the corresponding Flory’s scaling exponent, both of which characterize the dimension and size of the protein. It is generally understood that the sequence of an IDP affects its Rg and scaling exponent. Properties such as amino acid hydrophobicity and charge can play important roles in determining the Rg of an IDP, much as they affect the structure of a folded protein. However, it is nontrivial to directly predict Rg and scaling exponent from an IDP sequence. In this thesis, a coarse-grained model is used to simulate the Rg and scaling exponents of 10,000 randomly generated sequences mimicking the amino acid propensities of a typical IDP sequence. Such a database is then fed into an artificial neural network model to directly predict the scaling exponent from the sequence. The framework has not only made accurate and precise predictions (<1% error) in comparing to the simulation-obtained scaling exponent, but also suggest important sequence descriptors for such prediction. In addition, through varying the number of sequences for training the model, we suggest a minimum dataset of 100 sequences might be sufficient to achieve a 5% error of prediction, shedding light upon possible predictive models with only experimental inputs.
ContributorsBrown, Matthew D (Author) / Zheng, Wenwei (Thesis director) / Huffman, Holly (Committee member) / College of Integrative Sciences and Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Titanium dioxide is an essential material under research for energy and environmental applications, chiefly through its photocatalytic properties. These properties allow it to be used for water-splitting, detoxification, and photovoltaics, in addition to its conventional uses in pigmentation and sunscreen. Titanium dioxide exists in several polymorphic structures, of which the most common are rutile and anatase. We focused on anatase for the purposes of this research, due to its promising results for hydrolysis.
Anatase exists often in its reduced form (TiO2-x), enabling it to perform redox reactions through the absorption and release of oxygen into/from the crystal lattice. These processes result in structural changes, induced by defects in the material, which can theoretically be observed using advanced characterization methods. In situ electron microscopy is one of such methods, and can provide a window into these structural changes. However, in order to interpret the structural evolution caused by defects in materials, it is often necessary and pertinent to use atomistic simulations to compare the experimental images with models.
In this thesis project, we modeled the defect structures in anatase, around oxygen vacancies and at surfaces, using molecular dynamics, benchmarked with density functional theory. Using a “reactive” forcefield designed for the simulation of interactions between anatase and water that can model and treat bonding through the use of bond orders, different vacancy structures were analyzed and simulated. To compare these theoretical, generated models with experimental data, the “multislice approach” to TEM image simulation was used. We investigated a series of different vacancy configurations and surfaces and generated fingerprints for comparison with TEM experiments. This comparison demonstrated a proof of concept for a technique suggesting the possibility for the identification of oxygen vacancy structures directly from TEM images. This research aims to improve our atomic-level understanding of oxide materials, by providing a methodology for the analysis of vacancy formation from very subtle phenomena in TEM images.
Anatase exists often in its reduced form (TiO2-x), enabling it to perform redox reactions through the absorption and release of oxygen into/from the crystal lattice. These processes result in structural changes, induced by defects in the material, which can theoretically be observed using advanced characterization methods. In situ electron microscopy is one of such methods, and can provide a window into these structural changes. However, in order to interpret the structural evolution caused by defects in materials, it is often necessary and pertinent to use atomistic simulations to compare the experimental images with models.
In this thesis project, we modeled the defect structures in anatase, around oxygen vacancies and at surfaces, using molecular dynamics, benchmarked with density functional theory. Using a “reactive” forcefield designed for the simulation of interactions between anatase and water that can model and treat bonding through the use of bond orders, different vacancy structures were analyzed and simulated. To compare these theoretical, generated models with experimental data, the “multislice approach” to TEM image simulation was used. We investigated a series of different vacancy configurations and surfaces and generated fingerprints for comparison with TEM experiments. This comparison demonstrated a proof of concept for a technique suggesting the possibility for the identification of oxygen vacancy structures directly from TEM images. This research aims to improve our atomic-level understanding of oxide materials, by providing a methodology for the analysis of vacancy formation from very subtle phenomena in TEM images.
ContributorsShindel, Benjamin Noam (Author) / Crozier, Peter (Thesis director) / Anwar, Shahriar (Committee member) / Singh, Arunima (Committee member) / Materials Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05