Matching Items (11)
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- All Subjects: Molecular Dynamics
- Creators: Dai, Lenore
- Creators: Heyden, Matthias
- Resource Type: Text
Description
Metal-organic frameworks (MOFs) are a new set of porous materials comprised of metals or metal clusters bonded together in a coordination system by organic linkers. They are becoming popular for gas separations due to their abilities to be tailored toward specific applications. Zirconium MOFs in particular are known for their high stability under standard temperature and pressure due to the strength of the Zirconium-Oxygen coordination bond. However, the acid modulator needed to ensure long range order of the product also prevents complete linker deprotonation. This leads to a powder product that cannot easily be incorporated into continuous MOF membranes. This study therefore implemented a new bi-phase synthesis technique with a deprotonating agent to achieve intergrowth in UiO-66 membranes. Crystal intergrowth will allow for effective gas separations and future permeation testing. During experimentation, successful intergrown UiO-66 membranes were synthesized and characterized. The degree of intergrowth and crystal orientations varied with changing deprotonating agent concentration, modulator concentration, and ligand:modulator ratios. Further studies will focus on achieving the same results on porous substrates.
ContributorsClose, Emily Charlotte (Author) / Mu, Bin (Thesis director) / Shan, Bohan (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
A hybrid molecular dynamics (MD) simulation framework is developed to emulate mechanochemical reaction of mechanophores in epoxy-based nanocomposites. Two different force fields, a classical force field and a bond order based force field are hybridized to mimic the experimental processes from specimen preparation to mechanical loading test. Ultra-violet photodimerization for mechanophore synthesis and epoxy curing for thermoset polymer generation are successfully simulated by developing a numerical covalent bond generation method using the classical force field within the framework. Mechanical loading tests to activate mechanophores are also virtually conducted by deforming the volume of a simulation unit cell. The unit cell deformation leads to covalent bond elongation and subsequent bond breakage, which is captured using the bond order based force field. The outcome of the virtual loading test is used for local work analysis, which enables a quantitative study of mechanophore activation. Through the local work analysis, the onset and evolution of mechanophore activation indicating damage initiation and propagation are estimated; ultimately, the mechanophore sensitivity to external stress is evaluated. The virtual loading tests also provide accurate estimations of mechanical properties such as elastic, shear, bulk modulus, yield strain/strength, and Poisson’s ratio of the system. Experimental studies are performed in conjunction with the simulation work to validate the hybrid MD simulation framework. Less than 2% error in estimations of glass transition temperature (Tg) is observed with experimentally measured Tgs by use of differential scanning calorimetry. Virtual loading tests successfully reproduce the stress-strain curve capturing the effect of mechanophore inclusion on mechanical properties of epoxy polymer; comparable changes in Young’s modulus and yield strength are observed in experiments and simulations. Early damage signal detection, which is identified in experiments by observing increased intensity before the yield strain, is captured in simulations by showing that the critical strain representing the onset of the mechanophore activation occurs before the estimated yield strain. It is anticipated that the experimentally validated hybrid MD framework presented in this dissertation will provide a low-cost alternative to additional experiments that are required for optimizing material design parameters to improve damage sensing capability and mechanical properties.
In addition to the study of mechanochemical reaction analysis, an atomistic model of interphase in carbon fiber reinforced composites is developed. Physical entanglement between semi-crystalline carbon fiber surface and polymer matrix is captured by introducing voids in multiple graphene layers, which allow polymer matrix to intertwine with graphene layers. The hybrid MD framework is used with some modifications to estimate interphase properties that include the effect of the physical entanglement. The results are compared with existing carbon fiber surface models that assume that carbon fiber has a crystalline structure and hence are unable to capture the physical entanglement. Results indicate that the current model shows larger stress gradients across the material interphase. These large stress gradients increase the viscoplasticity and damage effects at the interphase. The results are important for improved prediction of the nonlinear response and damage evolution in composite materials.
In addition to the study of mechanochemical reaction analysis, an atomistic model of interphase in carbon fiber reinforced composites is developed. Physical entanglement between semi-crystalline carbon fiber surface and polymer matrix is captured by introducing voids in multiple graphene layers, which allow polymer matrix to intertwine with graphene layers. The hybrid MD framework is used with some modifications to estimate interphase properties that include the effect of the physical entanglement. The results are compared with existing carbon fiber surface models that assume that carbon fiber has a crystalline structure and hence are unable to capture the physical entanglement. Results indicate that the current model shows larger stress gradients across the material interphase. These large stress gradients increase the viscoplasticity and damage effects at the interphase. The results are important for improved prediction of the nonlinear response and damage evolution in composite materials.
ContributorsKoo, Bonsung (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Jiang, Hanqing (Committee member) / Jiao, Yang (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2017
Description
Amine-modified solid sorbents and membrane separation are promising technologies for separation and capture of carbon dioxide (CO2) from combustion flue gas. Amine absorption processes are mature, but still have room for improvement. This work focused on the synthesis of amine-modified aerogels and metal-organic framework-5 (MOF-5) membranes for CO2 separation. A series of solid sorbents were synthesized by functionalizing amines on the surface of silica aerogels. This was done by three coating methods: physical adsorption, magnetically assisted impact coating (MAIC) and atomic layer deposition (ALD). CO2 adsorption capacity of the sorbents was measured at room temperature in a Cahn microbalance. The sorbents synthesized by physical adsorption show the largest CO2 adsorption capacity (1.43-1.63 mmol CO2/g). An additional sorbent synthesized by ALD on hydrophilic aerogels at atmospheric pressures shows an adsorption capacity of 1.23 mmol CO2/g. Studies on one amine-modified sorbent show that the powder is of agglomerate bubbling fluidization (ABF) type. The powder is difficult to fluidize and has limited bed expansion. The ultimate goal is to configure the amine-modified sorbents in a micro-jet assisted gas fluidized bed to conduct adsorption studies. MOF-5 membranes were synthesized on α-alumina supports by two methods: in situ synthesis and secondary growth synthesis. Characterization by scanning electron microscope (SEM) imaging and X-ray diffraction (XRD) show that the membranes prepared by both methods have a thickness of 14-16 μm, and a MOF-5 crystal size of 15-25 μm with no apparent orientation. Single gas permeation results indicate that the gas transport through both membranes is determined by a combination of Knudsen diffusion and viscous flow. The contribution of viscous flow indicates that the membranes have defects.
ContributorsRosa, Teresa M (Author) / Lin, Jerry (Thesis advisor) / Pfeffer, Robert (Thesis advisor) / Dai, Lenore (Committee member) / Nielsen, David (Committee member) / Arizona State University (Publisher)
Created2010
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
Intelligent engineering designs require an accurate understanding of material behavior, since any uncertainties or gaps in knowledge must be counterbalanced with heightened factors of safety, leading to overdesign. Therefore, building better structures and pushing the performance of new components requires an improved understanding of the thermomechanical response of advanced materials under service conditions. This dissertation provides fundamental investigations of several advanced materials: thermoset polymers, a common matrix material for fiber-reinforced composites and nanocomposites; aluminum alloy 7075-T6 (AA7075-T6), a high-performance aerospace material; and ceramic matrix composites (CMCs), an advanced composite for extreme-temperature applications. To understand matrix interactions with various interfaces and nanoinclusions at their fundamental scale, the properties of thermoset polymers are studied at the atomistic scale. An improved proximity-based molecular dynamics (MD) technique for modeling the crosslinking of thermoset polymers is carefully established, enabling realistic curing simulations through its ability to dynamically and probabilistically perform complex topology transformations. The proximity-based MD curing methodology is then used to explore damage initiation and the local anisotropic evolution of mechanical properties in thermoset polymers under uniaxial tension with an emphasis on changes in stiffness through a series of tensile loading, unloading, and reloading experiments. Aluminum alloys in aerospace applications often require a fatigue life of over 109 cycles, which is well over the number of cycles that can be practically tested using conventional fatigue testing equipment. In order to study these high-life regimes, a detailed ultrasonic cycle fatigue study is presented for AA7075-T6 under fully reversed tension-compression loading. The geometric sensitivity, frequency effects, size effects, surface roughness effects, and the corresponding failure mechanisms for ultrasonic fatigue across different fatigue regimes are investigated. Finally, because CMCs are utilized in extreme environments, oxidation plays an important role in their degradation. A multiphysics modeling methodology is thus developed to address the complex coupling between oxidation, mechanical stress, and oxygen diffusion in heterogeneous carbon fiber-reinforced CMC microstructures.
ContributorsSchichtel, Jacob (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Ghoshal, Anindya (Committee member) / Huang, Huei-Ping (Committee member) / Jiao, Yang (Committee member) / Oswald, Jay (Committee member) / Arizona State University (Publisher)
Created2022
Description
Transition metal ions such as Zn2+, Mn2+, Co2+, and Fe2+ play crucial roles in organisms from all kingdoms of life. The homeostasis of these ions is mainly regulated by a group of secondary transporters from the cation diffusion facilitator (CDF) family. The mammalian zinc transporters (ZnTs), a subfamily of CDF, have been an important target for study as they are associated with several diseases, such as diabetes, delayed growth and osteopenia, Alzheimer’s disease, and Parkinsonism. The bacterial homolog of ZnTs, YiiP, is the first CDF transporter with a determined structure and is used as a model for studying the structural and mechanistic properties of CDF transporters. On the other hand, Molecular dynamics simulation has emerged as a valuable computational tool for exploring the physical basis of biological macromolecules' structure and function with atomic precision at femtosecond resolution. This work aims to elucidate the roles of the three Zn$2+ binding sites found on each YiiP protomer and the role of protons in the transport process of CDFs, which remain under debate despite previous thermodynamic and structural studies on YiiP. Cryo-EM, microscale thermophoresis (MST) and molecular dynamics (MD) simulations were used to address these questions. With a Zn2+ model that accurately reproduces experimental structures of the binding clusters, the dynamical influence of zinc binding on the transporter was accessed through MD simulations, which was consistent with the new cryo-EM structures. Zinc binding affinities obtained through MST were used to infer the stoichiometry of Zn2+/H+ antiport in combination with a microscopic thermodynamic model and constant pH simulations. The most likely microstates of H$^+$ and Zn2+ binding indicated a transport stoichiometry of 1 Zn2+ to 2-3 H+ depending on the external pH. A model describing the entire transport cycle of YiiP was finally built on these findings, providing insight into the structural and mechanistic properties of CDF transporters.
ContributorsFan, Shujie (Author) / Beckstein, Oliver (Thesis advisor) / Ozkan, Banu (Committee member) / Heyden, Matthias (Committee member) / Van Horn, Wade (Committee member) / Arizona State University (Publisher)
Created2023
Description
Understanding solvent-mediated interactions in biomolecular systems at the molecular level is important for the development of predictive models for processes such as protein folding and ligand binding to a host biomolecule. Solvent-mediated interactions can be quantified as changes in the solvation free energy of solvated molecules. Theoretical models of solvent-mediated interactions thus need to include ensemble-averaged solute-solvent interactions. In this thesis, molecular dynamics simulations were coupled with the 3D-2PT method to decompose solvation free energies into spatially resolved local contributions. In the first project, this approach was applied to benzene derivatives to guide the development of efficient and predictive models of solvent-mediated interactions in the context of computational drug design. Specifically, the effects of carboxyl and nitro groups on solvation were studied due to their similar sterical requirements but distinct interactions with water. A system of solvation free energy arithmetics was developed and showed that non-additive contributions to the solvation free energy originate in electrostatic solute-solvent interactions, which are qualitatively reproduced by computationally efficient continuum models. In the second project, a simple model system was used to analyze hydrophilic water-mediated interactions (water-mediated hydrogen bonds), which have been previously suggested to play a key role in protein folding. Using the spatially resolved analysis of solvation free energies, the sites of bridging water molecules were identified as the primary origin of solvent-mediated forces and showed that changes in hydration shell structure can be neglected. In the third project, the analysis of solvation free energy contributions is applied to proteins in inhomogeneous electric fields to explore water-mediated contributions to protein dielectrophoresis. The results provide a potential explanation for negative dielectrophoretic forces on proteins, which have been observed experimentally but cannot be explained with previous theoretical models.
ContributorsLazaric, Aleksandar (Author) / Heyden, Matthias (Thesis advisor) / Ozkan, Banu S (Committee member) / Sulc, Petr (Committee member) / Arizona State University (Publisher)
Created2022
Description
Biopolymers perform the majority of essential functions necessary for life. From a small amount of components emerges considerable complexity in both structure and function. The separated timescales of dynamic processes and intricate intra- and inter-molecular interactions of these molecules necessitate the development and utilization of computational approaches for biopolymer study and nanotechnology applications. Biopolymer nanotechnology exploits the natural chemistry of biopolymers to perform novel functions at the nanoscale. Molecular dynamics is the numerical simulation of chemical entities according to the physical laws of motion and statistical mechanics. The number of atoms in biopolymers require coarse-grained methods to fully sample the dynamics of the system with reasonable resources. Accordingly, a coarse-grained molecular dynamics model for the characterization of hybrid nucleic acid-protein nanotechnology was developed. Proteins are represented as an anisotropic network model (ANM) which show good agreement with experimentally derived protein dynamics for a small computational cost. The model was subsequently applied to hybrid DNA-protein cages systems and exhibited excellent agreement with experimental results. Ongoing development efforts look to apply network models to oxDNA origami to create multiscale models for DNA origami. The network approximation will allow for detailed simulation of DNA origami association, of concern to DNA crystal and lattice formation. Identification and design of target-specific binders (aptamers) has received considerable attention on account of their diagnostic and therapeutic potential. Generated in selection cycles from extensive random libraries, biopolymer aptamers are of particular interest due to their potential non-immunogenic properties. Machine learning leverages the use of powerful statistical principles to train a model to transform an input into a desired output. Parameters of the model are iteratively adjusted according to the gradient of the cost function. An unsupervised and generative machine learning model was applied to Thrombin aptamer sequence data. From the model, sequence characteristics necessary for binding were identified and new aptamers capable of binding Thrombin were sampled and verified experimentally. Future work on the development and utilization of an unsupervised and interpretable machine learning model for unaligned sequence data is also discussed.
ContributorsProcyk, Jonah (Author) / Sulc, Petr (Thesis advisor) / Stephanopoulos, Nicholas (Thesis advisor) / Hariadi, Rizal (Committee member) / Heyden, Matthias (Committee member) / Arizona State University (Publisher)
Created2022
Description
Functional materials can be characterized as materials that have tunable properties and are attractive solutions to the improvement and optimization of processes that require specific physiochemical characteristics. Through tailoring and altering these materials, their characteristics can be fine-tuned for specific applications. Computational modeling proves to be a crucial methodology in the design and optimization of such materials. This dissertation encompasses the utilization of molecular dynamics simulations and quantum calculations in two fields of functional materials: electrolytes and semiconductors. Molecular dynamics (MD) simulations were performed on ionic liquid-based electrolyte systems to identify molecular interactions, structural changes, and transport properties that are often reflected in experimental results. The simulations aid in the development process of the electrolyte systems in terms of concentrations of the constituents and can be invoked as a complementary or predictive tool to laboratory experiments. The theme of this study stretches further to include computational studies of the reactivity of atomic layer deposition (ALD) precursors. Selected aminosilane-based precursors were chosen to undergo density functional theory (DFT) calculations to determine surface reactivity and viability in an industrial setting. The calculations were expanded to include the testing of a semi-empirical tight binding program to predict growth per cycle and precursor reactivity with a high surface coverage model. Overall, the implementation of computational methodologies and techniques within these applications improves materials design and process efficiency while streamlining the development of new functional materials.
ContributorsGliege, Marisa Elise (Author) / Dai, Lenore (Thesis advisor) / Derecskei-Kovacs, Agnes (Thesis advisor) / Muhich, Christopher (Committee member) / Emady, Heather (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2021
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