Matching Items (38)
Description
Improved knowledge connecting the chemistry, structure, and properties of polymers is necessary to develop advanced materials in a materials-by-design approach. Molecular dynamics (MD) simulations can provide tremendous insight into how the fine details of chemistry, molecular architecture, and microstructure affect many physical properties; however, they face well-known restrictions in their applicable temporal and spatial scales. These limitations have motivated the development of computationally-efficient, coarse-grained methods to investigate how microstructural details affect thermophysical properties. In this dissertation, I summarize my research work in structure-based coarse-graining methods to establish the link between molecular-scale structure and macroscopic properties of two different polymers. Systematically coarse-grained models were developed to study the viscoelastic stress response of polyurea, a copolymer that segregates into rigid and viscous phases, at time scales characteristic of blast and impact loading. With the application of appropriate scaling parameters, the coarse-grained models can predict viscoelastic properties with a speed up of 5-6 orders of magnitude relative to the atomistic MD models. Coarse-grained models of polyethylene were also created to investigate the thermomechanical material response under shock loading. As structure-based coarse-grained methods are generally not transferable to states different from which they were calibrated at, their applicability for modeling non-equilibrium processes such as shock and impact is highly limited. To address this problem, a new model is developed that incorporates many-body interactions and is calibrated across a range of different thermodynamic states using a least square minimization scheme. The new model is validated by comparing shock Hugoniot properties with atomistic and experimental data for polyethylene. Lastly, a high fidelity coarse-grained model of polyethylene was constructed that reproduces the joint-probability distributions of structural variables such as the distributions of bond lengths and bond angles between sequential coarse-grained sites along polymer chains. This new model accurately represents the structure of both the amorphous and crystal phases of polyethylene and enabling investigation of how polymer processing such as cold-drawing and bulk crystallization affect material structure at significantly larger time and length scales than traditional molecular simulations.
ContributorsAgrawal, Vipin (Author) / Oswald, Jay (Thesis advisor) / Peralta, Pedro (Committee member) / Chamberlin, Ralph (Committee member) / Solanki, Kiran (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2016
Description
Ionic liquids (ILs), or low-temperature liquid salts, are a class of materials with unique and useful properties. Made up entirely of ions, ILs are remarkably tunable and diverse as cations and anions can be mixed and matched to yield desired properties. Because of this, IL/water systems range widely—from homogeneous mixtures to multiphasic systems featuring ionic liquid/liquid interfaces. Even more diversity is added when particles are introduced to these systems, as hard particles or soft-matter microgels interact with both ILs and water in complex ways. This work examines both miscible ionic liquid/water mixture and two-phase, immiscible ionic liquid/water systems. Extensive molecular dynamics (MD) simulations are utilized in conjunction with physical measurements to inform theoretical understanding of the nature of these systems, and this theoretical understanding is related to practical applications—in particular, the development of a low-temperature liquid electrolyte for use in molecular electronic transducer (MET) seismometers, and particle self-assembly and transport at ionic liquid/liquid interfaces such as those in Pickering emulsions.
The homogenous mixture of 1-butyl-3-methylimidazolium iodide and water is examined extensively through MD as well as physical characterization of properties. Molecular ordering within the liquid mixture is related to macroscopic properties. These mixtures are then used as the basis of an electrolyte with unusual characteristics, specifically a wide liquid temperature range with an extremely low lower bound combined with relatively low viscosity allowing excellent performance in the MET sensor. Electrolyte performance is further improved by the addition of fullerene nanoparticles, which dramatically increase device sensitivity. The reasons behind this effect are explored by testing the effect of graphene surface size and through MD simulations of fullerene and a silica nanoparticle (for contrast) in [BMIM][I]/water mixtures.
Immiscible ionic liquid/water systems are explored through MD studies of particles at IL/water interfaces. By increasing the concentration of hydrophobic nanoparticles at the IL/water interface, one study discovers the formation of a commingled IL/water/particle pseudo-phase, and relates this discovery to previously-observed unique behaviors of these interfaces, particularly spontaneous particle transport across the interface. The other study demonstrates that IL hydrophobicity can influence the deformation of thermo-responsive soft particles at the liquid/liquid interface.
The homogenous mixture of 1-butyl-3-methylimidazolium iodide and water is examined extensively through MD as well as physical characterization of properties. Molecular ordering within the liquid mixture is related to macroscopic properties. These mixtures are then used as the basis of an electrolyte with unusual characteristics, specifically a wide liquid temperature range with an extremely low lower bound combined with relatively low viscosity allowing excellent performance in the MET sensor. Electrolyte performance is further improved by the addition of fullerene nanoparticles, which dramatically increase device sensitivity. The reasons behind this effect are explored by testing the effect of graphene surface size and through MD simulations of fullerene and a silica nanoparticle (for contrast) in [BMIM][I]/water mixtures.
Immiscible ionic liquid/water systems are explored through MD studies of particles at IL/water interfaces. By increasing the concentration of hydrophobic nanoparticles at the IL/water interface, one study discovers the formation of a commingled IL/water/particle pseudo-phase, and relates this discovery to previously-observed unique behaviors of these interfaces, particularly spontaneous particle transport across the interface. The other study demonstrates that IL hydrophobicity can influence the deformation of thermo-responsive soft particles at the liquid/liquid interface.
ContributorsNickerson, Stella Day (Author) / Dai, Lenore L (Thesis advisor) / Yu, Hongyu (Committee member) / Lind, Mary Laura (Committee member) / Mu, Bin (Committee member) / Emady, Heather (Committee member) / Arizona State University (Publisher)
Created2016
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
Na+/H+ antiporters are vital membrane proteins for cell homeostasis, transporting Na+ ions in exchange for H+ across the lipid bilayer. In humans, dysfunction of these transporters are implicated in hypertension, heart failure, epilepsy, and autism, making them well-established drug targets. Although experimental structures for bacterial homologs of the human Na+/H+ have been obtained, the detailed mechanism for ion transport is still not well-understood. The most well-studied of these transporters, Escherichia coli NhaA, known to transport 2 H+ for every Na+ extruded, was recently shown to bind H+ and Na+ at the same binding site, for which the two ion species compete. Using molecular dynamics simulations, the work presented in this dissertation shows that Na+ binding disrupts a previously-unidentified salt bridge between two conserved residues, suggesting that one of these residues, Lys300, may participate directly in transport of H+. This work also demonstrates that the conformational change required for ion translocation in a homolog of NhaA, Thermus thermophilus NapA, thought by some to involve only small helical movements at the ion binding site, is a large-scale, rigid-body movement of the core domain relative to the dimerization domain. This elevator-like transport mechanism translates a bound Na+ up to 10 Å across the membrane. These findings constitute a major shift in the prevailing thought on the mechanism of these transporters, and serve as an exciting launchpad for new developments toward understanding that mechanism in detail.
ContributorsDotson, David L (Author) / Beckstein, Oliver (Thesis advisor) / Ozkan, Sefika B (Committee member) / Ros, Robert (Committee member) / Van Horn, Wade (Committee member) / Arizona State University (Publisher)
Created2016
Description
The rheological properties at liquid-liquid interfaces are important in many industrial processes such as manufacturing foods, pharmaceuticals, cosmetics, and petroleum products. This dissertation focuses on the study of linear viscoelastic properties at liquid-liquid interfaces by tracking the thermal motion of particles confined at the interfaces. The technique of interfacial microrheology is first developed using one- and two-particle tracking, respectively. In one-particle interfacial microrheology, the rheological response at the interface is measured from the motion of individual particles. One-particle interfacial microrheology at polydimethylsiloxane (PDMS) oil-water interfaces depends strongly on the surface chemistry of different tracer particles. In contrast, by tracking the correlated motion of particle pairs, two-particle interfacial microrheology significantly minimizes the effects from tracer particle surface chemistry and particle size. Two-particle interfacial microrheology is further applied to study the linear viscoelastic properties of immiscible polymer-polymer interfaces. The interfacial loss and storage moduli at PDMS-polyethylene glycol (PEG) interfaces are measured over a wide frequency range. The zero-shear interfacial viscosity, estimated from the Cross model, falls between the bulk viscosities of two individual polymers. Surprisingly, the interfacial relaxation time is observed to be an order of magnitude larger than that of the PDMS bulk polymers. To explore the fundamental basis of interfacial nanorheology, molecular dynamics (MD) simulations are employed to investigate the nanoparticle dynamics. The diffusion of single nanoparticles in pure water and low-viscosity PDMS oils is reasonably consistent with the prediction by the Stokes-Einstein equation. To demonstrate the potential of nanorheology based on the motion of nanoparticles, the shear moduli and viscosities of the bulk phases and interfaces are calculated from single-nanoparticle tracking. Finally, the competitive influences of nanoparticles and surfactants on other interfacial properties, such as interfacial thickness and interfacial tension are also studied by MD simulations.
ContributorsSong, Yanmei (Author) / Dai, Lenore L (Thesis advisor) / Jiang, Hanqing (Committee member) / Lin, Jerry Y S (Committee member) / Raupp, Gregory B (Committee member) / Sierks, Michael R (Committee member) / Arizona State University (Publisher)
Created2011
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
Natures hardworking machines, proteins, are dynamic beings. Comprehending the role of dynamics in mediating allosteric effects is paramount to unraveling the intricate mechanisms underlying protein function and devising effective protein design strategies. Thus, the essential objective of this thesis is to elucidate ways to use protein dynamics based tools integrated with evolution and docking techniques to investigate the effect of distal allosteric mutations on protein function and further rationally design proteins. To this end, I first employed molecular dynamics (MD) simulations, Dynamic Flexibility Index (DFI) and Dynamic Coupling Index (DCI) on PICK1 PDZ, Butyrylcholinesterase (BChE), and Dihydrofolate reductase (DHFR) to uncover how these proteins utilize allostery to tune activity. Moreover, a new classification technique (“Controller”/“Controlled”) based on asymmetry in dynamic coupling is developed and applied to DHFR to elucidate the effect of allosteric mutations on enzyme activity. Subsequently, an MD driven dynamics design approach is applied on TEM-1 β-lactamase to tailor its activity against β-lactam antibiotics. New variants were created, and using a novel analytical approach called "dynamic distance analysis" (DDA) the degree of dynamic similarity between these variants were quantified. The experimentally confirmed results of these studies showed that the implementation of MD driven dynamics design holds significant potential for generating variants that can effectively modulate activity and stability. Finally, I introduced an evolutionary guided molecular dynamics driven protein design approach, integrated co-evolution and dynamic coupling (ICDC), to identify distal residues that modulate binding site dynamics through allosteric mechanisms. After validating the accuracy of ICDC with a complete mutational data set of β-lactamase, I applied it to Cyanovirin-N (CV-N) to identify allosteric positions and mutations that can modulate binding affinity. To further investigate the impact of mutations on the identified allosteric sites, I subjected putative mutants to binding analysis using Adaptive BP-Dock. Experimental validation of the computational predictions demonstrated the efficacy of integrating MD, DFI, DCI, and evolution to guide protein design. Ultimately, the research presented in this thesis demonstrates the effectiveness of using evolutionary guided molecular dynamics driven design alongside protein dynamics based tools to examine the significance of allosteric interactions and their influence on protein function.
ContributorsKazan, Ismail Can (Author) / Ozkan, Sefika Banu (Thesis advisor) / Ghirlanda, Giovanna (Thesis advisor) / Mills, Jeremy (Committee member) / Beckstein, Oliver (Committee member) / Arizona State University (Publisher)
Created2023
Description
High-entropy alloys (HEAs) is a new class of materials which have been studied heavily due to their special mechanical properties. HEAs refers to alloys with multiple equimolar or nearly equimolar elements. HEAs show exceptional and attractive properties currently absent from conventional alloys, which make them the center of intense investigation. HEAs obtain their properties from four core effects that they exhibit and most of the work on them have been dedicated to study their mechanical properties. In contrast, little or no research have gone into studying the functional or even thermal properties of HEAs. Some HEAs have also shown exceptional or very high melting points. According to the definition of HEAs, Si-Ge-Sn alloys with equal or comparable concentrations of the three group IV elements belong to the category of HEAs. Thus, the equimolar components of Si-Ge-Sn alloys probably allow their atomic structures to display the same fundamental effects of metallic HEAs. The experimental fabrication of such alloys has been proven to be very difficult, which is mainly due to differences between the properties of their constituent elements, as indicated from their binary phase diagrams. However, previous computational studies have shown that SiGeSn HEAs have some very interesting properties, such as high electrical conductivity, low thermal conductivity and semiconducting properties. In this work, going for a complete characterization of the SiGeSn HEA properties, the melting point of this alloy is studied using classical molecular dynamics (MD) simulations and density functional theory (DFT) calculations. The aim is to investigate the effects of high Sn content in this alloy on the melting point compared with the traditional SiGe alloys. Classical MD simulations results strongly indicates that none of the available empirical potentials is able to predict accurate or reasonable melting points for SiGeSn HEAs and most of its subsystems. DFT calculations results show that SiGeSn HEA have a melting point which represent the mean value of its constituent elements and that no special deviations are found. This work contributes to the study of SiGeSn HEA properties, which can serve as guidance before the successful experimental fabrication of this alloy.
ContributorsAlqaisi, Ahmad Madhat Odeh (Author) / Hong, Qi-Jun (Thesis advisor) / Zhuang, Houlong (Thesis advisor) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2023
Description
Molecular Dynamics (MD) simulations are ubiquitous throughout the physical sci-ences; they are critical in understanding how particle structures evolve over time
given a particular energy function. A software package called ParSplice introduced a
new method to generate these simulations in parallel that has significantly inflated
their length. Typically, simulations are short discrete Markov chains, only captur-
ing a few microseconds of a particle’s behavior and containing tens of thousands of
transitions between states; in contrast, a typical ParSplice simulation can be as long
as a few milliseconds, containing tens of millions of transitions. Naturally, sifting
through data of this size is impossible by hand, and there are a number of visualiza-
tion systems that provide comprehensive and intuitive analyses of particle structures
throughout MD simulations. However, no visual analytics systems have been built
that can manage the simulations that ParSplice produces. To analyze these large
data-sets, I built a visual analytics system that provides multiple coordinated views
that simultaneously describe the data temporally, within its structural context, and
based on its properties. The system provides fluid and powerful user interactions
regardless of the size of the data, allowing the user to drill down into the data-set to
get detailed insights, as well as run and save various calculations, most notably the
Nudged Elastic Band method. The system also allows the comparison of multiple
trajectories, revealing more information about the general behavior of particles at different temperatures, energy states etc.
ContributorsHnatyshyn, Rostyslav (Author) / Maciejewski, Ross (Thesis advisor) / Bryan, Chris (Committee member) / Ahrens, James (Committee member) / Arizona State University (Publisher)
Created2022