Symposium Organizers
Peter Coveney, University College London
Valeriy Ginzburg, Dow Chemical Company
Olga Kuksenok, Clemson Univ
Veena Tikare, Sandia National Laboratories
Symposium Support
Clemson University, Department of Materials Science and Engineering
The Dow Chemical Company
Goodyear Tire and Rubber Company
PPG Industries, Inc.
Sandia National Laboratories
CM3.1: Gels, Biopolymers and Active Matter
Session Chairs
Peter Coveney
Russell Thompson
Tuesday PM, April 18, 2017
PCC North, 100 Level, Room 127 A
11:30 AM - *CM3.1.01
Surface-Bound Enzymatic Reactions Organize Microcapsules and Protocells in Solution
Anna Balazs 1 , Oleg Shklyaev 1 , Henry Shum 1 , Ayusman Sen 2
1 , University of Pittsburgh, Pittsburgh, Pennsylvania, United States, 2 , The Pennsylvania State University, University Park, Pennsylvania, United States
Show AbstractBy developing new computational models, we examine how enzymatic reactions on an underlying surface can be harnessed to direct the motion and organization of reagent-laden microcapsules in a fluid-filled microchannel. In the presence of the appropriate reagents, surface-bound enzymes can act as pumps, which drive large-scale fluid flows. When the reagents diffuse through the capsules’ porous shells, they can react with enzymatic sites on the bottom surface. The ensuing reaction generates fluid density variations, which result in fluid flows. These flows carry the suspended microcapsules and drive them to aggregate into “colonies” on and near the enzyme-covered sites. This aggregation continues until the reagent has been depleted and the convection stops. We show that the shape of the assembled colonies can be tailored by patterning the distribution of enzymes on the surface. This fundamental physicochemical mechanism could have played a role in the self-organization of early biological cells (protocells) and can be utilized to regulate the autonomous motion and targeted delivery of microcarriers in microfluidic devices.
12:00 PM - CM3.1.02
Magnonics in Hydrogels—Modeling Magnetomechanical Effects in GHz Frequency Range
Oksana Savchak 1 , Yao Xiong 1 , Tyler Morrison 2 , Konstantin Kornev 1 , Olga Kuksenok 1
1 , Clemson University, Clemson, South Carolina, United States, 2 , University of Tulsa, Tulsa, Oklahoma, United States
Show AbstractVia theoretical and computational modeling, we focus on the gel composites with magnetic nanoparticles uniformly dispersed within the gel matrix. For the polymer matrix, we take Poly(N-isopropylacrylamide) (PNIPAM) gels that shrink upon heating above critical temperatures. When the gigahertz EM waves interact with magnetic nanoparticles exciting the spin waves, magnons, the absorbency of these gels composites near the Ferro-Magnetic Resonance (FMR) frequency dramatically increases. We show that magnetic heating is sufficient to drive the volume phase transitions of gels and can cause significant shrinking of the composites for a range of experimental parameters. We propose the model for the system that accounts for the coupling between the elastodynamics of polymer gel and electrodynamics of interactions between magnetic nanoparticles. This coupling is non-linear: as the system is heated and the gel layer undergoes shrinking at the temperatures close to the volume phase transition, the particles concentration increases, which in turn results in a higher heating rate (positive feedback). We elucidated conditions at which even a low power EM signal comparable to that used in communication protocols can lead to a significant mechanical response of the gel film, hence the gel’s motion can be effectively controlled by the low power signal.
12:15 PM - *CM3.1.03
Mesoscale Modelling of Active Matter
Julia Yeomans 1
1 , University of Oxford, Oxford United Kingdom
Show AbstractDense active matter, from bacterial suspensions and microtubule bundles driven by motor proteins to cellular monolayers and synthetic Janus particles, is characterised by mesoscale turbulence, the emergence of chaotic flow structures. We use lattice Boltzmann simulations to show how a regular lattice of flow vortices can be stabilised by confinement of an active material in a channel, and discuss the transition from the vortex lattice to active turbulence [1]. Considering confinement within an array of rotating discs we discuss possible ways of exploiting active matter to create namomachines [2].
[1] Onset of meso-scale turbulence in living fluids, A. Doostmohammadi, T.N. Shendruk, K. Thijssen and J.M. Yeomans , arXiv:1607.01376
[2] Active micromachines: Microfluidics powered by mesoscale turbulence, S.P. Thampi, A. Doostmohammadi, T.N. Shendruk, R. Golestanian and J.M. Yeomans, Science Advances 2, e1501854 (2016).
12:45 PM - CM3.1.04
Understanding Micromechanics of Stimuli-Sensitive Microgels Using Dissipative Particle Dynamics
Alexander Alexeev 1 , Svetoslav Nikolov 1 , Alberto Fernandez-Nieves 1
1 , Georgia Institute of Technology, Atlanta, Georgia, United States
Show AbstractNeutral stimuli-sensitive gels are part of an emerging class of soft materials that has actualized a variety of microscale applications such as self-propulsion, sensing, and self-assembly. In response to external stimuli (such as light intensity, temperature, pH, and electric/magnetic fields), these materials undergo a reversible volume phase transition, characterized by large deformations and complex changes in internal structure. In the present work, we develop a mesoscale computational model of stimuli-sensitive hydrogels using dissipative particle dynamics. We employ our computational approach to probe how the micromechanical behavior of these gels changes as they go through the volume phase transition. We compare our model with Flory’s statistical-thermodynamics theory to characterize the swelling behavior of the gels. We also probe how non-homogeneous crosslinking affects the micromechanics of the hydrogel particles.
CM3.2: Polymers for Water, Energy and Separations—Membranes, Porous Materials and Foams
Session Chairs
Alexander Alexeev
Olga Kuksenok
Tuesday PM, April 18, 2017
PCC North, 100 Level, Room 127 A
2:30 PM - *CM3.2.01
From Toy Models to Materials Models—Integrating Experiment-Specific Morphologies in Mesoscale Simulations of Porous Media
Ulf Schiller 1
1 , Clemson University, Clemson, South Carolina, United States
Show AbstractMultiscale modeling and simulation techniques have become standard tools in science and engineering. They are used across the boundaries of traditional disciplines and help tackle challenging problems at the forefront of science. In materials science, advanced computational techniques are arguably transforming the way in which we can address the feedback loop of design, characterization, and optimization of novel materials. An enabling factor of this success is the increasing performance of supercomputing systems - a development that continues as exascale supercomputers are anticipated to emerge. In order to harvest this raw power for predictive science, however, we need computational approaches that capture the essential details of physico-chemical processes with sufficient accuracy and fidelity. Moreover, the simulation models need to be linked to their experimental realization in order to implement the necessary feedback mechanisms that enable validation and optimization.
A particular class of materials where integration of experimental and simulation data promises to promote new discoveries are porous media. Research topics in porous media keep spawning as novel micro- and nanoscale engineering applications emerge. These applications often pose multiple physics problems. For example, the utilization of nonwoven fibrous membranes as filters or detectors depends on morphology, wettability, and interactions of dissolved components. An induced flow through the fibrous membrane can couple with diffusive and dispersive transport phenomena in a non-trivial way. Simple analytical theories can explain the basic effects but fail to predict more complex transport phenomena. Mesoscopic simulation techniques have proven successful in solving the coupled partial differential equations numerically, especially when complex boundary conditions have to be taken into account.
In this talk, I will review some recent developments in mesoscopic modeling and present pore-scale simulations of electro-osmotic flow through a charged porous geometry using a combination of lattice Boltzmann, link-flux and moment propagation techniques. I will then discuss how these techniques can be utilized to simulate porous materials with realistic morphology based on experimental data. To this end, we have developed a workflow that integrates the generation of nonwoven fiber structures with prescribed properties. Preliminary results for permeability measurements will be presented to illustrate how the simulation data can provide feedback to experiment in order to optimize the materials properties of nonwoven fibrous membranes.
3:00 PM - CM3.2.02
Development of Laminar Graphene Oxide Water Separation Membrane Using Computer Simulation and Experiment
Ram Devanathan 1 , Yongsoon Shin 1 , Leonard Fifield 1 , Tiffany Kaspar 1 , Jian Liu 1 , David Gotthold 1
1 , Pacific Northwest National Laboratory, Richland, Washington, United States
Show AbstractWe have integrated molecular dynamics (MD) simulations with experiment to understand changes in interlayer spacing, water diffusion, and selective molecular transport in laminar graphene oxide (GO) membranes.1 The study used classical molecular dynamics simulations with conventional force fields to look at molecular transport in ethanol-water mixtures between model GO layers as a function of temperature and ethanol content. These simulations were performed in conjunction with corresponding synthesis efforts and experimental study of water permeation and selective separation of water from ethanol. We observed that water diffusion through GO layers was an order of magnitude slower than that in bulk water, because of strong hydrogen bonded interactions. Most of the water molecules were bound to OH groups even at the highest hydration level examined. We will present our findings on the interaction of ethanol and water with GO layers and shed light on the effect of structure and chemistry on selective water transport through laminar GO membranes.
1Devanathan, R., Chase-Woods, D., Shin, Y. & Gotthold, D. W. Molecular Dynamics Simulations Reveal that Water Diffusion between Graphene Oxide Layers is Slow. Scientific Reports 6 (2016) 29484.
3:15 PM - *CM3.2.03
Developing New Nanoporous Materials for Practical Applications Using Computational Modeling—How Close is the Dream to Reality?
David Sholl 1
1 , Georgia Institute of Technology, Atlanta, Georgia, United States
Show AbstractNanoporous materials such as zeolite or metal-organic frameworks have many potential applications, including as adsorbents and active components in membranes for chemical separations. The ability to use computational modeling in a genuinely predictive way to develop new nanoporous materials for targeted applications has been a long standing goal (dream?) in the research community. I will talk about how recent advances are bringing this goal within reach and what opportunities and barriers exist with these approaches in the future.
4:15 PM - *CM3.2.04
Self-Assembly and Transport in Polyelectrolyte Membranes
Alexander Neimark 1 , Ming-Tsung Lee 1 , Aleksey Vishnyakov 1
1 , Rutgers University, Piscataway, New Jersey, United States
Show AbstractPolyelectrolyte membranes composed of hydrophilic and hydrophobic fragments segregate upon solvation and form mesoscopic structures with interpenetrating hydrophilic and hydrophobic subphases. A typical example is Nafion polymer with sulfonate sidechains attached to perfluorinated backbone. Water concentrates around the sulfonate groups in nanometer size clusters, which grow and coalesce into a 3-dimentional network of water channels as the degree of hydration increases. This segregated morphology determines the transport properties of Nafion membranes that are widely used as compartment separators in fuel cells and other electro-chemical devices, as well as permselective diffusion barriers in protective fabrics. We introduce a coarse-grained s0ft-core model of Nafion membrane, which accounts explicitly for polymer rigidity and electrostatic interactions, and is matched to atomistic molecular dynamics simulations. By means of dissipative particle dynamics (DPD) and Monte Carlo (MC) simulations, we explore geometrical, transport, and sorption properties of hydrated membranes of various composition. Novel methodology will be presented for coarse-grained modeling of proton transport accounting for vehicular and hopping mechanisms.
4:45 PM - CM3.2.05
A Predictive Equation of State for Solubilities—Nanocellular Polymeric Foams and Hydrogen Storage Applications
Russell Thompson 1 , Chul Park 2 , Kier von Konigslow 1
1 Physics and Astronomy, University of Waterloo, Waterloo, Ontario, Canada, 2 Mechanical Engineering, University of Toronto, Toronto, Ontario, Canada
Show AbstractThe Sanchez-Lacombe equation of state, despite an inherent thermodynamic inconsistency, can be shown to be consistent, predictive and quantitative for numerical solubility calculations. The theory can thus be shown to be one of the simplest and most versatile equations of state with a predictive capacity which, in a sense, has no free parameters. Diverse solubility phenomena such as blowing agents dissolved in polymer melts for the creation of lightweight nanocellular polymeric foams, and hydrogen storage in metal organic frameworks will be mentioned.
5:00 PM - CM3.2.06
Simple Coarse-Grained Modeling of Regioregularity Controlled P3HT Molecules
YongJoo Kim 1 , Hyeong Jun Kim 1 , Jin-Seong Kim 1 , Yeon Sik Jung 1 , Bumjoon Kim 1
1 , KAIST, Daejeon Korea (the Republic of)
Show AbstractOver the past decade, conjugate polymers have been extensively evaluated as the active component in organic electronics due to their great potential in the mass production of large area, light-weight and flexible electronic devices by cost-effective solution processing. While a significant number of conjugated polymers have been reported to date, poly(3-hexylthiophene) (P3HT) represents most widely investigated model system because of its high performances in various organic electronics such as field-effect transistor, solar cell and thermoelectric devices. Among the various factors that affects the intrinsic properties of P3HTs, regio-chemical control over head-to-tail (HT) coupling between thiophene rings, defined by regioregularity (RR), has been considered most critical factor for the primary crystalline structure and resulting optoelectronic properties. Alkyl side chains in irregularly substituted head-to-head (HH) linkages causes a sterically driven twist of thiophene rings, resulting in a loss of conjugation and crystallinity. On contrary, highly regioregular P3HT, containing only HT coupling, allows to form highly crystalline structures with broader delocalization of π-electrons along the conjugated backbones and across the adjacent aligned polymer chains, leading to high optoelectronic properties. In this study, we suggest highly efficient coarse-grained model of RR controlled P3HT molecules to study thermodynamical properties. We found that our P3HT model successfully predicts crystalline temperature as a function of RR and phase diagram of solution assembled RR controlled P3HT. We believe that our model can be efficiently used for designing various organic electronic devices based on RR controlled P3HT.
5:15 PM - CM3.2.07
Coarse-Grained Forcefield for Mesoscale Interface Morphology Design in Polymer Solar Cells
Meilin Li 1 2 , Stefan Adams 1
1 Materials Science and Engineering, National University of Singapore, Singapore Singapore, 2 , Solar Energy Research Institute of Singapore, Singapore Singapore
Show AbstractRecently, organic photovoltaics have drawn substantial attention due to their advantages including solution-based processability, low processing cost, flexible architecture and improving efficiency. Bulk-heterojunction devices based on blends of donor and acceptor polymers have potential advantages of higher open-circuit voltage, higher extinction coefficients, and flexibility in materials design.
Due to its excellent charge carrier mobility poly(9,9'-dioctylfluorene-co-benzothiadiazole) (F8BT) has been extensively studied as active layer in electronic devices, including donor-acceptor bilayer solar cells of F8BT with PFB (Poly(9,9’-di-n-octylfluorene-alt-bis-N-N’-(4-butylphenyl) bis-N,N’-phenyl-1,4-Phenylene-diamine)). However, polymer blends often suffer from recombination of electron-hole pairs at the donor-acceptor interface. To solve this problem, an interfacial layer of F(NSO3)2 (Poly[(9,9–bis((N-(4-sulfonate-1-butyl)-N,N-dimethylammonium)-ethanyl)-2,7-fluorene)-alt-2,7-(9,9-dioctyl fluorene)]) was reported to affect the energetics of the states controlling charge separation at the interface, thus increasing open-circuit voltage, short-circuit current and fill factor. Still the effects of the interfacial layer on the morphology of the active layer are hardly accessible to experimental studies.
In order to study the effect of F(NSO3)2 on the interface morphology with affordable computational cost, we developed and validated coarse-grained forcefields for F8BT, PFB and F(NSO3)2. Coarse-graining simplifies the F8BT, PFB and F(NSO3)2 molecules and energy contributions describing interactions between the resulting beads are derived by identifying suitable functional forms and fitting the interaction parameters to the variation of corresponding energy terms in atomistic structure models using the validated COMPASS forcefield. The individual coarse-grained forcefields allow for a nearly two orders of magnitude gain in computational efficiency with only minor loss in accuracy. The three individual coarse-grained forcefields were then combined into one forcefield that unified the parameters involving common beads among the three copolymers scaling the distinct forcefield parameters to maintain the density of each copolymer. Finally, the combined forcefield is used to compare the morphology of PFB/F(NSO3)2/F8BT and PFB/ F8BT interface systems in mesoscale (10-100 nm)3 simulations.
5:30 PM - CM3.2.08
Multiscale Modeling of Carbon Nanotube Bundle Agglomeration inside a Gas Phase Pyrolysis Reactor
Guangfeng Hou 1 , Vianessa Ng 1 , Chenhao Xu 1 , Lu Zhang 1 , Vesselin Shanov 1 , David Mast 1 , Mark Schulz 1 , Yijun Liu 1
1 , University of Cincinnati, Cincinnati, Ohio, United States
Show AbstractCarbon nanotube (CNT) sock is critical for continuous synthesis of CNT thread or sheet using gas phase pyrolysis method. The nanoscale CNTs are carried downstream the reactor by the fluid flow, which then stick with each other and form sock under proper conditions. During this process, the nanoscale CNTs attach together to form millimeter-scale bundles. The coupling of these CNT bundles with fluid flow leads to the formation of inch-scale CNT sock. The understanding of this multiscale phenomena is vital for optimizing the CNT synthesis and manufacturing process. In this work, we present a multiscale model for the CNT bundle agglomeration inside a horizontal gas phase pyrolysis reactor. The interaction between CNT bundles has been analyzed, considering the attraction forces between them with discrete phase modeling method. The macro scale reactor has been studied using computational fluid dynamics (CFD) technique with multiphase flow analysis. A model has been proposed to resolve the coupling between CNT bundle and the gas flow. The influence of different CNT bundles on the agglomeration phenomenon has been analyzed. The modeling results have been compared with experimental observations.
5:45 PM - CM3.2.09
Effect of pH on the Interfacial Properties of Silicate Glasses
Ross Stewart 1 , Hendrik Heinz 2 , Sushmit Goyal 1 , Sung-Hoon Lee 1 , Aravind Rammohan 1 , John C. Mauro 1
1 , Corning Inc., Painted Post, New York, United States, 2 Chemical Engineering, University of Colorado, Boulder, Colorado, United States
Show AbstractUnderstanding the impact of glass composition on its interactions with a biological or chemical solution interface is a topic of interest for implants, pharmaceuticals, cell signaling and attachment, chemical durability, etc. [Kurella, A., J. Biomater. Appl., 20, 2005] In this work, the structure of the electric double layer and the immersion energy, representing energetic stability, is calculated for silicate glasses in solutions of varying composition and pH. Molecular dynamic simulations with the INTERFACE force field are used to provide accurate interfacial atomic interactions, which help to elucidate details not readily available through common experiments, such as the possible difference in the structure of water around mono- vs. divalent cations. It is seen that the immersion energy of the glass interface increases with an increase in ionic surface density and pH. This can be attributed to the stronger interaction between water and cations, as opposed to water and silanol groups. Changes in the local ion concentration and electric double layer structure will be explained. When holding a constant pH of the solution, the addition of network modifiers to the silicate glass increases the immersion energy. The developed models and methods provide new insights into the structure of glass-solution interfaces and the effect of cation surface density in a number of common nanoscale environments.
Symposium Organizers
Peter Coveney, University College London
Valeriy Ginzburg, Dow Chemical Company
Olga Kuksenok, Clemson Univ
Veena Tikare, Sandia National Laboratories
Symposium Support
Clemson University, Department of Materials Science and Engineering
The Dow Chemical Company
Goodyear Tire and Rubber Company
PPG Industries, Inc.
Sandia National Laboratories
CM3.3/CM7.2: Joint Session: Accelerating Materials Discovery and Design with Computing
Session Chairs
Alexander Alexeev
Veena Tikare
Wednesday AM, April 19, 2017
PCC North, 100 Level, Room 124 B
9:00 AM - *CM3.3.01/CM7.2.01
NIST—The Materials Genome Initiative, and Computation
James Warren 1
1 , National Institute of Standards and Technology, Gaithersburg, Maryland, United States
Show AbstractIn this talk I will present an overview of the US Materials Genome Initiative, and then focus on NIST’s efforts in support of the MGI. After an overview where I will provide insight into community-led activities, I will discuss our attempts at NIST to address some of the challenges to creating the materials innovation infrastructure that lies at the heart of the Materials Genome Initiative. In particular NIST is now devoting considerable effort, in concert with its partners in industry, academia and government, to develop the tools, standards and techniques for (i) establishing model and data exchange infrastructure (ii) establishing best practices and new methods for ensuring data and model quality and (iii) developing the data analytics to enable "data driven" materials science. Given the focus of the conference, I will tie these efforts into the essential role of the MGI data infrastructure in enabling multiscale materials simulation, including specifc platforms targeted at soft materials.
9:30 AM - CM3.3.02/CM7.2.02
Intelligently Navigating Parameter Space with Machine Learning
Matthew Spellings 1 , Sharon Glotzer 1
1 , University of Michigan, Ann Arbor, Michigan, United States
Show AbstractAdvances in hardware and algorithms have increased the space of computationally-feasible simulations available to scientists by orders of magnitude. With processing power amplified by supercomputers, the most difficult component of modern computational science is sometimes the act of deciding the best experimental conditions to test. The most common response to this problem is a uniform grid in parameter space, but for categorical data we often care more about where the transition between two types of behavior in parameter space occurs instead of what happens on the interior of uniform regions. When we design a grid of input parameters and then perform experiments, how much information is lost “in the cracks” between points? Here we discuss approaches to incorporate machine learning into live simulations to maximize the variety of obtained results (in our example, the self-assembled crystal structures within a phase diagram) while minimizing computational time spent re-sampling behaviors that have already been seen.
9:45 AM - CM3.3.03/CM7.2.03
Materials Data Management with Signac
Carl Simon Adorf 1 , Paul Dodd 1 , Sharon Glotzer 1
1 , University of Michigan, Ann Arbor, Michigan, United States
Show AbstractResearchers in computational materials science are regularly posed with the challenge of managing large and heterogeneous data spaces. The amount of data increases in lockstep with computational efficiency multiplied by the amount of available computational resources, which shifts the bottleneck within the scientific process from data acquisition to data post-processing and analysis. We present a framework designed to aid in the integration of various specialized formats, tools and workflows. The signac framework provides all basic components required to create a well-defined and thus collectively accessible data space, simplifying data access and modification through a homogeneous data interface, largely agnostic of the data source, i.e., computation or experiment. The framework's data model is designed not to require absolute commitment to the presented implementation, simplifying adaption into existing data sets and workflows. This approach not only increases the efficiency for the production of scientific results, but also significantly lowers barriers for collaborations requiring shared data access.
10:00 AM - CM3.3.04/CM7.2.04
Digital Alchemy—An Inverse Approach to Mesoscale Soft Materials Design
Greg van Anders 1 , Paul Dodd 1 , Yina Geng 1 , Sharon Glotzer 1
1 , University of Michigan, Ann Arbor, Michigan, United States
Show AbstractTheory-led approaches have the potential to revolutionize the design of soft materials, but developing them is a challenge. We present recent advances on a mesoscale method for inverse materials design we term “digital alchemy.” Digital alchemy is a first-principles, statistical mechanics technique that can be used to compute thermodynamically optimal attributes of colloidal particles to self-assemble target materials. We present results from several recent investigations that demonstrate the use of digital alchemy to design colloid attributes such as particle shape for target materials, even in cases where collective behavior and competing interactions complicate the underlying materials physics. We demonstrate applications to high-dimensional design-parameter spaces that are beyond the reach of high throughput computing techniques.
10:15 AM - CM3.3.05/CM7.2.05
Pressure-Induced Phase Transitions in Shape Space
Rose Cersonsky 1 , Greg van Anders 1 , Paul Dodd 1 , Sharon Glotzer 1
1 , University of Michigan, Ann Arbor, Michigan, United States
Show AbstractIn designing new materials for synthesis, the inverse materials design approach posits that, given a structure, we can predict a building block optimized for self-assembly. How does that building block change as pressure is varied to maintain the same crystal structure? We address this question for entropically stabilized colloidal crystals by working in a generalized statistical thermodynamic ensemblewhere an “alchemical potential” variable is fixed and its conjugate variable -- particle shape – is allowed to fluctuate. We show that there are multiple regions of shape behavior and phase transitions in shape space between these regions. Furthermore, while past literature has looked towards packing arguments for proposing shape-filling candidate building blocks for structure formation, we show that even at very high pressures, a structure will attain lowest free energy by modifying these space-filling shapes.
10:30 AM - CM3.3.06/CM7.2.06
Determining Molecular Orientation via Physics Based Polymer Models with Polarized X-Ray Scattering
Adam Hannon 1 2 , Daniel Sunday 1 , Donald Windover 1 , Christopher Liman 1 , Alec Bowen 3 , Gurdaman Khaira 4 , Juan de Pablo 3 , Dean DeLongchamp 1 , R. Kline 1
1 , NIST, Gaithersburg, Maryland, United States, 2 , Georgetown University, Washington, District of Columbia, United States, 3 , University of Chicago, Chicago, Illinois, United States, 4 , Mentor Graphics, Wilsonville, Oregon, United States
Show AbstractFlexible electronics and photovoltaics, composites, and stimuli-responsive materials all require better methods to characterize molecular orientation at the nanoscale. The optical, mechanical, electronic, and transport properties of the devices made from such materials are determined from how the molecules orient in space. Methods such as scanning transmission electron microscopy (STEM) can obtain atomic resolution in inorganic materials, but severely damage organic polymer systems. Resonant soft X-ray scattering (RSoXS) has been used to determine the morphology of organic systems such as block copolymers and disordered organic semiconductors. This technique is non-destructive when performed below the absorption edge used to obtain resonance. Molecular orientation information can be obtained in addition to the morphology in anisotropic samples by varying the polarization of the incident X-ray beam (P-RSoXS).
Because RSoXS does not directly measure the real space structure, we develop inverse search methods to find the structure that best fits the measured scattering. We have incorporated physics based models such as self-consistent field theory (SCFT) and theoretically informed coarse-grained Monte Carlo (TI-CGMC) simulations into our RSoXS inverse search algorithm to fit scattering profiles for isotropic thin film block copolymer systems. These models allow for the measurement of thermodynamic properties in addition to the morphological shape while limiting the number of model parameters for such morphological detail rich systems. We have extended these models to obtain the molecular orientation in anisotropic systems from P-RSoXS measurements by considering polarization and molecular orientation effects explicitly. In this presentation, we first show examples of how the methodology has been successful for isotropic block copolymer samples. We then show the implementation of an SCFT model using a wormlike chain partition function to model a rigid-rod block in a rod-coil block copolymer. The density profiles and orientation profiles of the rod block is used to simulate the theoretical scattering profile for a P-RSoXS experiment. These simulated profiles are used with an inverse fitting evolutionary strategy algorithm that shows the model can be used in P-RSoXS experiments to find the average molecular orientation. Based on the results, experimental systems to explore with the technique are suggested.
10:45 AM - CM3.3/CM7.2
BREAK
11:15 AM - *CM3.3.07/CM7.2.07
Evolutionary Structure Prediction from Complex Crystals to Defects
Qiang Zhu 1
1 , University of Nevada, Las Vegas, Las Vegas, Nevada, United States
Show AbstractNowadays, the urgent demand for new technologies has greatly exceeds the capabilities of materials research. Understanding the atomic structure of a material is the first step in materials design. There have been tremendous progresses in the accurate prediction of crystal structures from first principles based on a variety of global optimization methods combing density functional theory (DFT) calculations. However, there remain many challenges on predicting complex systems such as organic crystals. Furthermore, recent experiments have revealed highly complex interface structures in different solids. The understanding of the atomic arrangements in the interfaces is crucial for the engineering control of materials properties on an upper level. In this talk, I will discuss the recent progresses in applying the evolutionary algorithm to study the organic crystal polymorphism and the structural phase transformations in metallic grain boundaries. The encouraging results so far suggest a major role of this approach in the prediction and design future functional and structural materials.
11:45 AM - CM3.3.08/CM7.2.08
Large-Scale Molecular Dynamics Simulation on Fracture Properties of Ni Anode for Highly Durable Solid Oxide Fuel Cell
Jingxiang Xu 1 , Yuji Higuchi 1 , Nobuki Ozawa 1 , Momoji Kubo 1
1 , Institute for Materials Research, Tohoku University, Sendai Japan
Show AbstractSolid oxide fuel cell (SOFC) is used as a highly efficient electronic-energy conversion device without environmental pollution and greenhouse gases. Currently, Ni-based anode is widely used as an anode for the SOFC; however it possesses a fracture problem due to the heat cycle operation of the SOFC. Moreover, the fracture of Ni-based anode is affected by the content of the water vapor in the fuel. Thus, an understanding of fracture properties of the Ni-based anode in water vapor is necessary for improving the durability of the SOFC and many experimental results have been reported so far. For the design of the durable anode, we need not only experimental but also atomic-scale theoretical studies. However, atomic-scale theoretical studies on fracture properties in the water vapor based on molecular dynamics (MD) simulation are not carried out widely. In this study, we investigated the fracture properties of polycrystalline Ni substrate in the water vapor by using our developed large-scale MD simulator [1]. In the tensile test simulation in the presence of the water vapor, a stacking fault firstly generates in the surface area of the polycrystalline Ni substrate when the strain is 0.033. In the tensile test simulation in the absent of the water vapor, the polycrystalline Ni substrate shows little change when the strain is 0.033. A large compressive stress is observed in the surface area of the polycrystalline Ni substrate in the presence of the water vapor by calculating the atomic stress distribution, whereas it does not be observed in the absent of the water vapor. Then, we investigate the component of stress and find that the coulomb interaction induced by the charge transfer between Ni and water molecules contributes to the large compressive stress. Thus, our large-scale MD simulation reveals that the water vapor accelerates the generation of stacking fault in the surface of the polycrystalline Ni substrate. Next, the effect of the grain size in polycrystalline Ni substrate in the water vapor are also discussed. Our study can provide a database for the development of the new anode material. [1] J. Xu et al., J. Mater. Chem. A 3 (2015) 21518.
12:00 PM - CM3.3.09/CM7.2.09
Integrated Imaging and Simulation to Investigate Lattice Deformations in Externally Stimulated Nanocrystals
Kiran Sasikumar 1 , Mathew Cherukara 1 , Thomas Peterka 1 , Ross Harder 1 , Subramanian Sankaranarayanan 1
1 , Argonne National Laboratory, Lemont, Illinois, United States
Show AbstractDespite the increasing role of nanomaterials in technology, their mechanical and dynamical properties under external stimulation are not well understood. One such problem is the pulsed laser excitation of a diverse class of nanomaterials, such as ZnO nanorods, WSe2 nanopillars, and Au-Al core-shell bimetallic nanocrystals. Another class of problems is the investigation of lattice deformations in nanostructured catalysts during multi-electron transfer processes. These constitute an important class of materials systems for catalysis, biomedical and energy applications. Understanding the temporal behavior of such nanomaterials under conditions of external stimulation is, thus, crucially important for energy research. In addition, characterizing lattice distortions can provide key insights into the behavior of nanomaterials and nanoscale interfaces.
Recently, experimental techniques have evolved to conduct time-dependent lattice dynamics measurements in nanomaterials. In particular, Bragg Coherent Diffraction Imaging (BCDI) has been used to directly image ultrafast lattice distortions in laser-heated nanocrystals. BCDI measurements have also been successfully used to observe reversible lattice distortions in metallic nanocrystals facilitating chemical reactions at low-coordination corner and edge sites. Suitable simulation models prove to be an ideal foil to explore the underlying mechanisms behind the observed lattice deformations. With the convergence of time and length scales accessible by both experiments and simulations, we are now able to integrate experimental observations with classical molecular dynamics (MD) simulations and continuum finite element calculations to enhance the fundamental understanding of materials behavior under external stimulation.
Here, we demonstrate the workflow(s) to integrate BCDI measurements with large-scale atomistic molecular dynamics simulations and finite element models to investigate lattice dynamics in externally stimulated nanocrystals. We will demonstrate the suitability of the workflow(s) as applied to a diverse class of materials systems and external stimulus. We show that direct comparisons between experiments and simulations are possible by using the appropriate level of theory or a combination of simulation techniques. In addition, the integrated experiment-informed simulation approach yields new insight into deformation mechanisms of nanomaterials that cannot be obtained and validated by either approach alone.
12:15 PM - CM3.3.10/CM7.2.10
DFT Applied to Transition Metals and Binaries—Developing the V/DM-17 Test Set
Elizabeth Decolvenaere 1 , Ann Mattsson 2
1 , University of California, Santa Barbara, Santa Barbara, California, United States, 2 Multiscale Computational Materials Methods, Sandia National Laboratories, Albuquerque, New Mexico, United States
Show AbstractDensity functional theory (DFT) is undergoing a shift from a descriptive to a predictive tool in the field of solid state physics, with undertakings like the Materials Project, OQMD, and AFLOW leading the way in utilizing high-throughput data to predict and seek novel materials properties. However, methods to rigorously evaluate the validity and accuracy of these studies is lacking in both the availability and utilization of techniques. The natural disconnect between simulated and experimental length-scales and temperatures, combined with this lack of validation, raises serious questions when simulation and experiment disagree. In response, we have developed the V-DM/17 test set, designed to evaluate the experimental accuracy of DFT’s various implementations for periodic transition metal solids. Our test set evaluates 26 transition metal elements and 80 transition metal alloys across three physical observables: lattice constants, elastic coefficients, and formation energy of alloys. Whether or not a functional can accurately evaluate the formation energy offers key insights into whether the relevant physics are being captured in a simulation, an especially important question in transition metals where active d-electrons can thwart the accuracy of an otherwise well-performing functional. Our test set captures a wide variety of cases where the unique physics present in transition metal binaries can undermine the effectiveness of “traditional” functionals. By application of the V/DM-17 test set, we aim to better characterize the performance of existing functionals on transition metals, and to offer a new tool to rigorously evaluate the performance of new functionals in the future.
Sandia National Laboratories is a multi-mission laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energys National Nuclear Security Administration under contract DE-AC04-94AL85000.
12:30 PM - CM3.3.11/CM7.2.11
Development of Crystal Structure Prediction Method for Magnet Materials
Tomoki Yamashita 1 2 , Hiori Kino 1 , Takashi Miyake 3 1 , Koji Tsuda 4 1 , Tamio Oguchi 2 1
1 , National Institute for Materials Science (NIMS), Tsukuba, Ibaraki, Japan, 2 , Osaka University, Ibaraki, Osaka, Japan, 3 , National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan, 4 , The University of Tokyo, Kashiwa, Chiba, Japan
Show AbstractSm-Co and Nd-Fe-B intermetallic compounds are known for high-performance rare-earth permanent magnets which are one of the key materials in magnetic and energy conversion devices. For material search of permanent magnets, developments of basic methods with data-driven approaches have been highly desired because of the rapid growth of supercomputer performances. One of the difficulties in finding new permanent magnet materials is how to predict the complex crystal structures. For example, the best magnet, Nd2Fe14B, contains 68 atoms in the unit cell. This system is quite difficult to predict the crystal structure because number of configuration explosively increases as atoms increase. In this study, we have developed and investigated methods of crystal structure predictions to overcome those difficulties. First, random search algorithm in combination with structure optimization technique using first-principles calculations was employed. Furthermore, Bayesian optimization method was added to accelerate crystal searches. The usability of crystal structure predictions for finding new rare-earth magnet materials is discussed.
We started with simple systems to test the random search algorithm. Crystal structure prediction simulations were carried out for RCo5 and R2Co17 (R means rare-earth element such as Y and Sm) which are important compositions of Sm-Co magnets. Our predicted structures were in complete agreement with structures in experiments. The most stable structures of YCo5 and Y2Co17 were obtained with probabilities of 8 and 3%, respectively. These results show that the random search algorithm is highly efficient for relatively small unit cell (less than 20 atoms). For a large unit cell including 4 Y and 34 Co atoms, however, we could not obtain stable structures within trials of 300 structures. We further try a Bayesian optimization method to search the vast space of Y4Co34 efficiently, and demonstrate the usability of Bayesian optimization for large systems. Several descriptors of crystal structures are discussed.
CM3.4: Industrial Applications of Polymer Modeling I
Session Chairs
Valeriy Ginzburg
Russell Thompson
Wednesday PM, April 19, 2017
PCC North, 100 Level, Room 127 A
2:30 PM - *CM3.4.01
Towards Accelerated Materials Discovery and Design
Turab Lookman 1
1 , Los Alamos National Laboratory, Los Alamos, New Mexico, United States
Show AbstractLearning from data using inference and optimization tools
to iteratively guide new synthesis or calculations is increasingly allowing
us to realize some of the objectives of codesign. After briefly reviewing
what we can learn from the use of such tools and issues involved, I will
describe recent collaborative work on functional materials, including
polymer dielectrics, where the design questions can relate to
optimizing multiple properties.
3:00 PM - *CM3.4.02
Multiscale by Focusing on Bridging between Established Fields and Codes
Ann Mattsson 1
1 , Sandia National Laboratories, Albuquerque, New Mexico, United States
Show AbstractIn this talk I will discuss an alternative view on multiscale materials science, a view that focuses less on codes and code interfaces and more on the bridging between different fields and established codes.
All codes need input information. The code then transforms this input information, through well established equations and algorithms from established and mature fields of science, into output information. The basic idea of multiscale science is to obtain the input needed for one code from the output of a lower scale method/code, stringing methods and codes together to span the entire range of length and time scales. However, it is often the case that the output from one code is hard to transform into input to another code. It can be easily understood that bridging between two particular codes is a hard process by considering that no well established code is available for this task. This, in turn, means that transforming the output from one field/method/code into input for another field/method/code, while being a field of its own, is NOT a mature and well established field.
I will discuss several of these bridging efforts, among them, exchange-correlation functionals for bridging between the Schrödinger equation (SE) level and the Density Functional Theory (DFT) level, classical force fields to bridge between DFT and classical Molecular Dynamics (MD), and Equations of State (EOS) that bridges from SE, DFT, MD, and experiments to engineering codes. I will also touch upon the need for specific and targeted research in the bridge fields for verification, validation, and uncertainty quantification.
Sandia National Laboratories is a multi-mission laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000.
4:30 PM - *CM3.4.03
Stimuli Interactive Materials: Making Materials Locomote
Benjamin Treml 1 2 , Ruel McKenzie 2 , David Wang 1 2 , Andrew Gillman 1 2 , Michael Kuhn 1 2 , Phil Buskohl 2 , Loon-Seng Tan 2 , Richard Vaia 2
1 , UES, Dayton, Ohio, United States, 2 , Air Force Research Laboratory, Dayton, Ohio, United States
Show AbstractImagine a contact lens that provides both adaptive night vision and data display; an energy harvester that autonomously deploys and retracts based on resource availability; a robust aircraft skin that maintains aerodynamic loads and conformal antennas as it morphs between energy-efficient profiles for take-off and transient flight. These concepts all require intimate closed-loop feedback between the environment and device, mediated by materials that do not just respond to a stimulus, but interact with it. The behavior of a stimuli interactive material can be highly non-linear, as an initial response alters the local environment, driving further response in the material, etc. To advance the understanding of these material-environment synergies, we discuss the hygromorphic response of glassy and semi-crystalline polymer films with modest water uptake (~8 wt% at saturation) and elastic modulus (~0.1-1 GPa). In particular, we emphasize autonomic locomotion, including fundamental biological motifs of rolling, crawling, and jumping, in commercial nylon films powered and directed by local humidity gradients. We describe the energy flow during the process through a combination of experimentally observed film dynamics, theoretical considerations of energy transfer and computational modeling of the dynamic local environment. Using this framework, design guidelines for complex behaviors are demonstrated for films consisting of active and inactive nodes.
5:00 PM - CM3.4.04
Characterizing the Fundamental Adhesion of Polyimide on Crystalline and Glassy Silica Surfaces—A Molecular Dynamics Study
Sushmit Goyal 1 , Hyunhang Park 1 , Sung-Hoon Lee 1 , Elisabeth Savoy 1 , Mathew McKenzie 1 , Aravind Rammohan 1 , John C. Mauro 1 , Hyunbin Kim 1 , Kyoungmin Min 2 , Eunseog Cho 2 , Ross Stewart 1
1 , Corning Inc, Painted Post, New York, United States, 2 , Samsung Inc., Seoul Korea (the Republic of)
Show AbstractUnderstanding the interaction between polyimide and inorganic surfaces is vital for controlling interfacial adhesion behavior. In this work, we use molecular dynamics simulations to study the adhesion of polyimide on crystalline and glassy silica surfaces. The effects of hydroxylation, silica structure, polyimide chemistry, chain length, and rigidity on adhesion are investigated. The results reveal that polyimide monomers have stronger adhesion on hydroxylated surfaces compared to non-hydroxylated surfaces. Also, adhesion of polyimide onto silica glass is stronger compared to the corresponding crystalline surfaces of identical hydroxyl density. We also find that polyimides such as Kapton have a greater adhesion than BPDA; further analysis reveals that the concentration of oxygens is a key factor in this trend. Finally, we explore the effect of the correlation length of the polymer chains. By studying these factors, we hope to provide insights to help tailor the adhesion behavior between organic-inorganic surfaces.
5:15 PM - CM3.4.05
Computational Screening and Design of Complex Structures
Julia Dshemuchadse 1 , Michael Engel 1 2 , Matthew Spellings 1 , Sharon Glotzer 1 3
1 Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan, United States, 2 Department of Chemical and Biological Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen Germany, 3 Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, United States
Show AbstractRecently, soft-matter scientists have discovered increasingly complex structures, from large cluster-based unit cells to quasicrystals. Many of these geometries were previously known from structures on the atomic scale, while others were completely novel. We perform high-throughput molecular-dynamics simulations of different physically-realizable, attractive interactions to screen large sections of their phase spaces. Based on crystallographic analysis of the resulting data, we investigate the conditions under which complex structures with large unit cells form in different kinds of soft-matter systems. Using machine learning, we find distinct phases automatically and distill the structure-forming factors that underlie the resulting particle configurations. With this knowledge, the targeted design of crystal structures with functional properties will enable soft-matter scientists to specifically choose building blocks that will self-assemble into the structures that they desire in the future.
5:30 PM - CM3.4.06
Calculation of Solvation Free Energies for the Predictive Design of Functional Molecular Systems
Wenkun Wu 1 , John Kieffer 1
1 , University of Michigan, Ann Arbor, Michigan, United States
Show AbstractAssociative thickeners are widely used in aqueous polymer systems to obtain the specific degree of viscosity needed for the proper application of coatings. The pKa and the solvation free energy of the hydrophobe on the end of the thickener characterize its responsive range. The determination of the solvation free energy for the hydrophobe molecule is therefore essential for the predictive design of effective thickener formulations. To improve the accuracy in calculating solvation free energies we developed a hybrid cluster-continuum approach, where explicit solvent molecules are added to the traditionally employed continuum model. Our computational workflow includes several validation checks. First, the minimum number of explicit water molecules beyond which addition of more water molecules no longer improve the accuracy of the cluster-continuum model must be carefully established. To this end we use a convergence criterion, as well as the comparison of the results achieved using fully relaxed molecular configurations with those obtained by sampling thermally disordered configurations using single-point calculations. We find that the dielectric constant does not have a significant influence on the solvation free energy, while accounting for the placement of a counter ion is necessary for the accurate calculation of the solvation free energy. Finally, given currently available computational resources, the statistical sampling procedure is the only viable approach for tackling the design of large hydrophobe molecules.
5:45 PM - CM3.4.07
Peptide Coated Gold Cluster Designed as Target Probe by Computational and Experimental Methods
Lina Zhao 1
1 , Institute of High Energy Physics, Chinese Academic Sciences, Beijing China
Show AbstractPeptide coated gold clusters have precise chemical formulas and exact molecular structures, which are critical for the target probe design in the serious disease diagnosis. Both molecular structure and targeting mechanism are essential problems in the probe design for targeting to the disease related protein. To solve the above problems in molecular details, we studied peptide coated gold cluster on electronic and molecular levels by computational methods. We proposed a universal approach to control the chemicophysical properties of gold cluster by regulating the coating ligands on the gold atom/amino acid interface. Furthermore, based on the coating peptide sequence design and the specific interaction mechanism of gold cluster/protein interface, we could design a series of novel peptide coated gold cluster targeting systems for probe development. More important, we employed experimental method to synthesize these novel probes, and verified their targeting abilities to different proteins as disease markers. As a result, we brought a new insight from theoretical and experimental viewpoints to peptide coated gold cluster study for target probe application in serious disease diagnosis.
CM3.5: Poster Session: Computer-Based Modelling and Experiment for the Design of Soft Materials
Session Chairs
Peter Coveney
Valeriy Ginzburg
Olga Kuksenok
Veena Tikare
Thursday AM, April 20, 2017
Sheraton, Third Level, Phoenix Ballroom
9:00 PM - CM3.5.01
Morphological Control—A Correlation between Theoretical and Experimental Findings on Ag2CrO4 Microcrystals
Gabriela Silva 1 , Lourdes Gracia 2 , Maria Fabbro 1 , Luis Santos 1 , Hector Beltran-Mir 2 , Eloisa Cordoncillo 2 , Elson Longo 1 , Juan Adres 2
1 , Federal University of São Carlos, São Carlos Brazil, 2 , Universitat Jaume I, Castellón de la Plana Spain
Show AbstractThe morphological control is fundamental to control the physical and chemical properties and improve the performance in applications of micro- and nanomaterials. The morphology of particles depends on two main types of influences that act simultaneously: thermodynamic and kinetic. The thermodynamic factors determine the morphology of equilibrium energetically more favorable while the kinetic factors determine how easily the thermodynamically favored morphology can be achieved. Silver chromate, Ag2CrO4, belongs to the important family of Ag-containing compounds with the formula Ag2MO4 (M = Cr, Mo, W). Ag2MO4-based materials have been the subject of extensive research because of their excellent structural, optical and morphological properties. The aim of our study was to combine the use of experimental findings and first-principles calculations to reach a deeper knowledge of the electronic, structural, and energetic properties controlling the morphology. Three samples were synthesized by varying some kinetic parameters. The reactions were done by precipitation method. In the first sample (1), the addition rate of AgNO3 into Na2CrO4 was 25 mL/s, whereas, in the second (2) and third samples (3), the addition rate was 10 mL/min. However, only the third sample was sonicated for 10 min. The XRD patterns of the three samples presented orthorhombic structure and no deleterious phases. All diffraction peaks are in good in agreement with the ICSD card n° 16298. Furthermore, all samples showed well-defined diffraction peaks, indicating structural order at long range. These observations were confirmed by the Rietveld refinement data. Micro-Raman spectra showed two strong peaks in the high frequency region at 780 and 816 cm-1 corresponding to the symmetric stretching vibrations of Cr–O bond in [CrO4] clusters. Therefore, there were no significant differences regarding order/structural disorder at short range among the samples. The sample 1, 2 and 3 showed optical band-gap values of 1.80 eV, 1.70 eV and 1.78 eV, respectively. The theoretical value was 1.37 eV. In the FE-SEM imaging, sample 1 presented average size particles of 1 µm with a few well-faceted particles. Sample 2 showed average size of 2.5 µm and the particles presented fewer well-faceted particles. Sample 3 presented average size of 0.7 µm and well-faceted particles. The PL spectra showed the existence of a binodal curve that characterizes two types of defects in the structure of Ag2CrO4. The differences in the band gap values, PL and morphology are associated with the kinetics of the synthesis and the relative surface energy value of each surface. Wulff construction and DFT calculations helped us to understand the mechanism of morphological formation of microparticles. In addition, DFT calculations were very useful to discuss the relationship among the structural order/disorder effects, morphology, and photoluminescence of the Ag2CrO4.
9:00 PM - CM3.5.02
The Theoretical Engineering and Experimental Synthesis of Molecularly Imprinted Polymers as More Specific Potential Platforms for Chemical Sensing
Ghada Selim 1 , Tarek Madkour 1
1 , American University in Cairo, Cairo Egypt
Show AbstractBiochemical sensors or assays are usually based on enzymes/proteins to detect a particular analyte, owing to their high selectivity and specificity. However, enzymes/proteins are highly delicate, labile to slight medium changes, and expensive. Research has been continuously seeking novel materials to substitute enzymes/proteins in chemical sensing applications. One of the most promising materials are Molecularly Imprinted Polymers (MIP). They are polymer based, so they are highly stable under many circumstances, and much cheaper. MIP networks are synthesized in the presence of the analyte intended to be detected, which at the end of the polymerization process is removed leaving behind nano-scaled cavities. Such cavities are the sites responsible for rebinding the analyte back during chemical sensing.
However, a main drawback within MIP is that they are not as specific as enzyme/proteins, owing to the partial deterioration of many cavities during MIP synthesis stages, and consequently the final binding capacity is compromised. Researchers tended to resolve this issue by synthesizing MIP that can bind strongly or through multiple interaction points with the analyte. It has been manifested that this is not always enough.
In this poster, a novel strategy was attempted to resolve this issue. The hypothesis was to study the effect of inducing the formation of nano-scaled cavities that not only could bind strongly to a particular analyte, but also that could maintain their stable integral structures during the MIP synthesis stages.
The adopted methodology started by a theoretical computational approach followed by the experimental MIP synthesis in order to validate the theoretical approach. The theoretical approach relied on the creation of a virtual library of monomers (MIP building blocks), followed by a three-staged screening process in order to select the highest two scoring candidates. Then the selected candidates together with a low scoring monomer were employed in the experimental synthesis of the two new MIP and a control MIP respectively. The binding performances of all the synthesized MIP were assayed against a role model template (glucose). Also, the binding performances of their respective non-imprinted counterparts (NIP) were estimated.
Results showed that the binding capacities of all MIP exceeded that of their respective NIP. And interestingly, the new MIP had higher binding capacities over the control MIP. The characterization methods employed (SEM, FTIR, BET) showed clear morphological, functionality, and porosity differences between the synthesized polymers.
In conclusion, the adopted strategy could tailor-design MIP that are highly effective and economic to replace proteins/enzymes in the next generation of chemical sensors.
9:00 PM - CM3.5.03
Modelling the Effect of Copolymer Concentration on Thermal Stability of Lysozyme-Copolymer Conjugates
Chandan Choudhury 1 , Sidong Tu 1 , Nataraja Yadavalli 2 , Nikolay Borodinov 1 , Tatiana Quinones-Ruiz 3 , Igor Lednev 3 , Igor Luzinov 1 , Sergiy Minko 2 , Olga Kuksenok 1
1 , Clemson University, Clemson, South Carolina, United States, 2 , University of Georgia, Athens, Georgia, United States, 3 , University at Albany, Albany, New York, United States
Show AbstractVia computer simulations integrated with the experimental studies, we focus on improving the thermal stability of enzymes; this stability is vital for a variety of applications. Herein, we develop a suitable molecular dynamics simulation approach to study the effect of copolymer concentration on the thermal stability of the hen egg white lysozyme (HEWL)-copolymer conjugate. First, we develop and validate the force field for the copolymer OEGMA-GMA-OEGMA (triads) that we use in our experiments. We then conjugate the lysine residues of HEWL with the triads; in addition, we add free-floating triads. Then we hydrate the system with 50%, 30% and 10% (w/w) of water, respectively. Thermal stability of these systems was studied at temperatures ranging for 300 K to 500 K. Our studies showed that the system with 10% (w/w) water concentration was the most efficient in preserving the secondary structures of HEWL at 500 K. We characterized these conformations using the Dictionary of Secondary Structure of Proteins. Overall our results pinpoint to the range of parameters that could be optimized to achieve higher thermal stability of HEWL-copolymer conjugates.
9:00 PM - CM3.5.04
Simulative Study on Vaporization Condition of OMCTS by COMSOL for SiO2 Clean Production
Jun Ho Lee 1 , Seong Gyu Park 1 , Sung Jin An 1
1 , Kumoh National Institute of Technology, Gumi Korea (the Republic of)
Show AbstractSiO2 is earth abundant materials and promising candidate for optical fibers due to its outstanding optical properties. Among starting materials for production of SiO2 based optical fibers, the octamethylcyclotetrasilxan (OMCTS) is a new promising candidate for clean production of SiO2 based optical fibers due to lower contaminations of environment relatively. In this study, we have demonstrated fluid dynamic simulation of advanced clean manufacturing processes to optimize vaporization condition of OMCTS. The vaporization conditions of OMCTS in processes of host materials for clad have been thoroughly studied by using COMSOL software. And then the vaporization of OMCTS to be SiO2 was simulated in the aluminium alloy reactor under optimized condition that customized initial temperature of OMCTS and reactor. The resulting of fluid dynamic simulation using COMSOL software shows that optimized temperatures and vaporization conditions of OMCTS were successfully simulated. Finally, we have comparatively studied on SiO2 production either SiCl4 combustion or OMCTS vaporization process. The amount of chlorine and waste water were decreased above 90% compared with SiCl4 combustion. Otherwise, the CO2 evolution was decreased above 30% compared with SiCl4 combustion. The amount of SiO2 produced by SiCl4 combustion and vaporization of the OMCTS will be further discussed.
9:00 PM - CM3.5.05
Coupling Experimental Results and Computational Models to Evaluate Peptide-Surface Interactions
Kristi Singh 1 , Claretta Sullivan 1 , Zhifeng Kuang 1 , Joseph Slocik 1 , Patrick Dennis 1 , Rajesh Naik 2
1 Materials & Manufacturing Directorate, Air Force Research Laboratory, Wright Patterson Air Force Base, Ohio, United States, 2 711th Human Performance Wing, Air Force Research Laboratory, Wright-Patterson Air Force Base, Ohio, United States
Show AbstractUnderstanding the principles of biotic-abiotic interfacial interactions is key to the development of unique biocomposites, tailorable biosensors, and novel functional materials. Peptides provide a promising route to template material growth and enhance functionality of materials and biosensors. Quartz Crystal Microbalance (QCM) and Multi-Parametric Surface Plasmon Resonance (MP-SPR) are characterization techniques that provide information about the bulk binding kinetics for peptide-substrate systems of interest. Both of these techniques provide insight into different aspects of binding behavior (ex., QCM includes peptide-associated water and MP-SPR does not). Computational modeling has also been employed, along with experiments, to validate binding behavior and to investigate the potential of the models to predict peptide-substrate interaction behavior. Atomic Force Microscopy (AFM) provides the missing link in experimental characterization by providing a concrete route to measure single molecule interactions and correlate those back to bulk binding behavior. By combining these four techniques (QCM, MP-SPR, AFM, and computational modeling) we are elucidating the peptide-substrate binding mechanisms and developing computational models to accurately predict interactions at the biotic-abiotic interface.
Symposium Organizers
Peter Coveney, University College London
Valeriy Ginzburg, Dow Chemical Company
Olga Kuksenok, Clemson Univ
Veena Tikare, Sandia National Laboratories
Symposium Support
Clemson University, Department of Materials Science and Engineering
The Dow Chemical Company
Goodyear Tire and Rubber Company
PPG Industries, Inc.
Sandia National Laboratories
CM3.6: Industrial Applications of Polymer Modeling II
Session Chairs
Thursday AM, April 20, 2017
PCC North, 100 Level, Room 127 A
9:00 AM - *CM3.6.01
Atomistic and Coarse-Grained Simulations of Ion-Conducting Polymers
Amalie Frischknecht 1
1 , Sandia National Labs, Albuquerque, New Mexico, United States
Show AbstractSimulations of ion transport in ionomers, polymers containing a small fraction of covalently bound ionic groups, are challenging because dynamical processes relevant to the ion transport occur across many orders of magnitude in time. Additionally, designing improved ionomers requires an understanding of how both polymer architecture and ionomer morphology affect ion dynamics, which requires knowledge across multiple length scales. To build a better understanding of the relationships among ionomer chemistry, morphology, and ion transport, we have performed a series of molecular dynamics simulations and connected aspects of these simulations with experiment. In this talk I will describe our recent results on two different ionomers. The first is a series of precise poly(ethylene-co-acrylic acid) ionomers, which have acid groups precisely spaced along the polymer backbone. Our previous atomistic and coarse-grained simulations of these ionomers showed excellent agreement with X-ray scattering data, allowing us to better understand the morphology of ionic aggregates which self-assemble in the ionomers. More recent atomistic MD simulations of these ionomers are in relatively good agreement with quasi-elastic neutron scattering data at short time scales. The comparison with experiment validates the dynamics in the simulations, which we then use to probe ion dynamics at longer time scales. The second system is a sulfonated poly(phenylene), which conducts protons when hydrated. Atomistic simulations of the structure are in good agreement with X-ray scattering data. I will describe efforts to develop a coarse-grained model of this polymer to extend the length and time scales of the simulations, as well as additional comparisons between simulation and experimental data.
Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.
9:30 AM - CM3.6.02
Prediction of Phase Diagram in Thermoset/Thermoplastic Mixtures
Chunyu Li 1 , Alejandro Strachan 1
1 , Purdue University, West Lafayette, Indiana, United States
Show Abstract
Chunyu Li and Alejandro Strachan
Purdue University, West Lafayette, Indiana 47906
Toughening thermoset polymers with thermoplastics has been widely accepted as effective approach for enhancing material properties of theromosets, which is a main structural matrix for fiber composites used in aerospace and automotive industries. But the effectiveness depends on the phase morphology resulted from reaction-induced phase separation in the curing process. Thus a fundamental understanding of the reaction-induced phase separation is of great interests for designing theomoset/thermoplastic mixtures. Molecular modeling of phase separation has been restricted so far to simple binary mixtures and linear polymers and little is known about how the development of a 3D networked architecture in thermosets affects reaction induced phase separation. In this talk, we will report our recent efforts in predicting phase separation diagram from atomistic simulations for a DGEBA/33DDS system mixed with short-length polysulfone chains. The solubility parameters, cohesive energy density and free energy of mixing for different compositions under different temperatures will be discussed and will the kinetics of the phase separation. The prediction of phase diagram is compared with existing experimental studies in the literature.
9:45 AM - CM3.6.03
Advanced Understanding of Paper Coating Structure and Its Relationship to Coating Performance
Jian Yang 1 , Lanfang Li 2 , John Roper III 3 , Valeriy Ginzburg 3 , Colmar Wocke 4 , Rebecca Smith 2
1 , The Dow Chemical Company, Freeport, Texas, United States, 2 , The Dow Chemical Company, Collegeville, Pennsylvania, United States, 3 , The Dow Chemical Company, Midland, Michigan, United States, 4 , The Dow Chemical Company, Horgen Switzerland
Show AbstractPaper coatings have been utilized to improve paper performance for decades, for example, for improving brightness, opacity, gloss, stiffness, ink acceptance, printability, and smoothness. In thermal paper, coatings are employed to impart improved thermal, morphological and mechanical properties often through the incorporation of hollow spheres into the coating film. Hollow sphere pigments having well controlled size and narrow size distribution provide a unique opportunity to model and study the particle packing phenomenon and its effect on coating film strength, smoothness and thermal properties. This talk introduces a multi-dimensional modeling approach in paper coating modeling, with a special focus on a microscopic mechanistic model. Based on this approach we have seen that control of binary packing and local structure lead to improved and balanced coating mechanical property and thermal conductivity. This will allow the creation of better coating materials using guided design of single particle geometry and formulation.
10:00 AM - CM3.6.04
Inelastic Neutron Scattering Analysis of Polymorphic Crystals
Bruce Hudson 1
1 , Syracuse University, Syracuse, New York, United States
Show AbstractOrganic materials that form hydrogen bonds in their crystalline state often exist in multiple crystal forms. This “polymorphism” is of relevance in the pharmaceutical industry due to differing rates of dissolution of polymorphic forms and can be important for non-linear optical materials. In any case the existence of polymorphic forms is a challenge to use of “self-assembly” and in our ability to establish the relative internal energy or Gibbs energy even when all the atomic positions are known. In rare circumstances the difference in crystal structure is associated with a change in the location of H atoms (“tautomerism”) which convert hydrogen bond acceptors into hydrogen bond donors.[1] Tautomeric forms often co-mingle so that the resulting crystals are mosaics.[2] In several cases to be discussed it is found that the polymorphic form is influenced by replacement of exchangeable hydrogen by deuterium.[1,3] Our approach to the question of the relative stability of polymorphic forms and the effect of deuterium substitution on this relative stability involves atomic level lattice energy calculations including dispersion contributions with periodic methods followed by simulation of vibrational spectra, particularly inelastic neutron scattering (INS) vibrational spectra. Comparison of the observed INS spectra with experiment serves to validate the computed set of energy levels permitting computation of the vibrational zero point and thermal vibrational excitation of the crystalline materials in H and D forms.
The case of barbituric acid is of particular interest in this respect. The anhydrous material is known as a triketo form in two polymorphic modifications [4] and as an enol.[1] It has only recently been discovered that the enol is the thermodynamically most stable form. The preparation of this crystalline material suitable for single crystal diffraction study was facilitated by use of a liquid density gradient that separates the polymorphic forms.[5] This density gradient method can also separate crystals that are of the same polymorphic form but that differ in that one had deuterium replacing exchangeable H atoms. Because the CH2 group of barbituric acid is part of a cyclic beta diketone, -(O=C-CH2-C=O)-, all of the H atoms are exchangeable. Under thermodynamic equilibrium (“slurry”) conditions the replacement of H by D may be preferential at the enol OH positions. The results of such studies for barbituric and similar derivatives of uracil will be discussed.
[1] Marshall, M. G., Lopez-Diaz, V.; Hudson, B. S., Angew. Chem., Int. Ed. 2016, 55, 1309.
[2] Hudson, M. R.; Allis, D. G.; Hudson, B. S., Chem. Phys. Lett. 2009 473, 81.
[3] Rivera S.; Allis D. G.; Hudson B. S., Cryst. Gro. Des., 2008, 8, 3905.
[4] Lewis, T. C.; Tocher, D. A.; Price, S. L., Cryst. Gro. Des. 2004, 4, 979.
[5] Hudson, B. S.; Melton, J., U.S. Patent US 9,089,850 B2 (28 July, 2015)
10:15 AM - CM3.6.05
Modeling Thermal Conductivity of Polymer-Ceramic Composites by Using Scanning Electron Microscopy Images as Input to Finite Element Analysis
Ellen Keene 1 , Valeriy Ginzburg 1 , Kevin Howard 1 , Kurt Koppi 1 , Xiaofei Sun 1 , W.H. Hunter Woodward 1 , Jeff Zawisza 1
1 , The Dow Chemical Company, Midland, Michigan, United States
Show AbstractIn the lighting market, light emitting diodes (LED) are replacing conventional lighting technologies. Thermal management is becoming a great concern because LEDs generate a lot of heat at the LED junction. Without proper dissipation, its performance and lifetime will be negatively impacted. To remove heat, a heat sink with high thermal conductivity is typically attached to the LED circuitry. An emerging innovation is thermoplastic composite heat sinks. These composites are comprised of a thermoplastic matrix loaded with high thermal conductivity filler(s). This type of material offers additional benefits including being lighter weight, better manufacturability, corrosion resistance, and potentially lower cost. Hexagonal boron nitride (h-BN) and spherical alumina (Al2O3) filled thermoplastic has been identified as a potential composite material for LED heat sinks, because of their high thermal conductivity, electrical insulating property, and inherent white color. Understanding the relationship between formulations and their physical properties is crucial in the design of these materials. However, existing models can only be applied in a limited number of cases. Although numerous analytical theories and models exist to predict thermal conductivity as a function of filler loading for various morphologies, they are mainly used as qualitative predictors of trends. In real systems, morphologies are usually complex and particle size is not uniform. Implementing these factors in any analytical model is nearly impossible. Therefore, a new modeling approach aimed at predicting thermal conductivity of composite materials is necessary. Finite element analysis (FEA) models offer flexibility to account for these complexities. In order to successfully use the FEA approach, information about the filler particle distribution in the matrix is needed to directly compute the composite properties. Fabricated composite plaques were metallographically polished and imaged by scanning electron microscopy (SEM) in back-scattered electron mode. Image contrast is due to atomic number, making phase identification trivial, and easily show the locations of the matrix, fillers, and voids. These images are then digitized in ImageJ to create an array of numbers coding the locations of each component. This array is then imported into the FEA model and thermal conductivity is assigned to each grid point. Finally, the solid heat transfer model is applied and solved, and the ratio of heat flux to the temperature gradient gives the overall composite thermal conductivity. By changing the direction of the temperature gradient, the variation between through- and in-plane thermal conductivity can be studied (assuming local filler orientation anisotropy reflects the global anisotropy due to flow-induced alignment). Thermal conductivity calculations made by FEA were compared with experimental measurements of the same plaques showing good agreement between experiment and theory.
10:30 AM - CM3.6.06
Modeling the Dynamical Mechanical Behavior of Polyurethane Elastomers by Combining Self-Consistent Field Theory (SCFT) and Finite Element Analysis (FEA)
Valeriy Ginzburg 1 , Adam Broderick 1
1 , Dow Chemical Co, Midland, Michigan, United States
Show AbstractWe develop a new approach to modeling mechanical properties of segmented polyurethane (PU) elastomers. In this approach, the microstructure of a PU polymer is modeled by using Self-Consistent Field Theory (SCFT) for a pentablock copolymer, SHSHS, where S represents soft segment, and H represents hard segment. Using SCFT, we generate a “density map”fH(r) which takes value of 1 inside the hard-phase domains, 0 inside the soft-phase domains, and intermediate values in the interfacial regions. This output is then imported into Finite Element Analysis (FEA) software, and translated into the “modulus map”, E(r), using well-defined mixing rules. By applying a small external compression and computing the resulting displacement, we can evaluate the overall tensile/compressive (Young’s) modulus of the material as function of temperature. We synthesized several polyurethane elastomers and showed a good agreement between theory and experiment.
11:15 AM - *CM3.6.07
Computational Fluid Dynamics Modeling of Viscoelastic Droplet Breakup
Laura Dietsche 1 , Sylvie Vervoort 2
1 , The Dow Chemical Company, Midland, Michigan, United States, 2 , The Dow Chemical Company, Terneuzen Netherlands
Show AbstractWhen fluid droplets are dispersed in a second fluid under the influence of shear or elongational stresses, the droplets will tend to deform and often elongate and break. The deformation and breakup characteristics are highly dependent on the induced flow field and on the relative rheologies of the two fluids, as well as interfacial forces. For Newtonian fluids, the droplets tend to elongate in the direction of the applied shear or elongation field. The Grace curve (Grace HP. Chem Eng Commun 14: 225-277 (1982)) is often used to determine the critical capillary number (ratio of shear or elongation forces to interfacial forces) needed for the droplet to break up as a function of the viscosity ratio. The deformation and breakup characteristics for viscoelastic fluids can be quite unique due to the complex rheologies involved, including the buildup of normal stresses and stress relaxation responses.
Experimental studies have begun to explore some of the unique attributes of viscoelastic droplet break-up, including the observation of droplets stretching in a direction perpendicular to the shear flow field. In the present study, we are using computational fluid dynamics (CFD) methods to explore the effects of the polymer rheology and flow field characteristics on droplet deformation modes and breakup efficiencies. This requires a CFD code that can handle complex viscoelastic rheologies (with multiple relaxation times) and has multi-phase highly-deformable boundary tracking capabilities. Unfortunately, there are presently no commercial CFD codes that can handle both viscoelasticity and the required multiphase phenomena. This need prompted the development of a model using OpenFOAM® (open source CFD code) to simulate two-phase flow of viscoelastic materials. The numerical algorithm has been validated using two well-known viscoelastic free-surface effects, namely the die swell effect and the Weissenberg (rod climbing) effect. Additional effects such as transient and steady-state deformation of single droplets subject to shear and planar elongational flows were also used for validation.
In this paper, we will examine some of the results obtained when using the OpenFOAM model to simulate viscoelastic droplet deformation and break-up characteristics in pure shear and elongational flow fields. The effects of viscosity and elasticity will be discussed. Additionally, the ability to simulate the observed phenomenon of transverse stretching of a droplet in a shear field will be discussed.
11:45 AM - CM3.6.08
Computing Memory Effects in Coarse-Grained Modeling Derived from the Mori-Zwanzig Formalism—Application to Polymer Melts
Zhen Li 1 , Hee Sun Lee 2 , Eric Darve 2 , George Karniadakis 1
1 , Brown University, Providence, Rhode Island, United States, 2 , Stanford University, Stanford, California, United States
Show AbstractMemory effects are often introduced during coarse-graining of a complex dynamical system. In particular, a non-Markovian, generalized Langevin equation (GLE) for the coarse-grained (CG) system arises in the context of Mori-Zwanzig (MZ) formalism. Upon a pairwise decomposition, GLE can be reformulated into its pairwise version, i.e., non-Markovian dissipative particle dynamics (DPD). Both GLE and non-Markovian DPD contain long-term memory interactions. A direct computation of such terms requires the storage of historical information that significantly increases computational complexity. Alternatively, auxiliary variables can be employed to replace the non-Markovian dynamics with Markovian dynamics by augmenting the discrete system to higher dimensions. In this work, we compare different coarse-graining strategies with GLE and non-Markovian DPD models, and quantify different methods for practical implementation of the non-Markovian interactions. More specifically, the GLE and non-Markovian DPD models are constructed directly from molecular dynamics (MD) simulations of star-polymer melts via the MZ formulation. The memory kernel of friction and pairwise potential are computed from the MD trajectories. Simulation results show that Markovian dynamics with auxiliary variables successfully generates equivalent non-Markovian dynamics consistent with the reference MD system. The transient subdiffusion of the star-polymers observed in the MD system can be reproduced by the CG models. In terms of the reproduction of the short time dynamics of the reference MD system, both GLE and non-Markovian DPD models have good performance. However, for long-time hydrodynamics characterised by an algebraic decay in the velocity autocorrelation function (VACF), the DPD model can generate correct long-time tail in VACF, but the GLE model cannot because it does not conserve momentum. Our findings suggest that the non-Markovian DPD model with auxiliary variables can combine both the advantages of extended dynamics and pairwise formulation, where the former yields accurate short-time dynamics while the latter guarantees momentum conservation that generating the correct long-time hydrodynamics.
12:00 PM - CM3.6.09
Systematic and Simulation-Free Coarse Graining of Polymer Melts
Qiang Wang 1
1 , Colorado State University, Fort Collins, Colorado, United States
Show AbstractCoarse-grained (CG) models are currently needed to study polymeric systems, as full atomistic simulations of many-chain systems used in experiments are in most cases not feasible due to their formidable computational requirements. Polymeric systems are also best suited for coarse graining, as the large number of monomers on each chain allows high levels of coarse graining. Here we introduce a systematic and simulation-free strategy for coarse graining multi-component polymeric systems, and apply it to the structure-based coarse graining of homopolymers, polymer blends, and diblock copolymers in the melt state. We use the well-developed polymer reference interaction site model theory, instead of many-chain molecular simulations, for both the original and CG systems, and examine how the CG potentials vary with the coarse-graining level and how well the CG models at different levels can reproduce the structural and thermodynamic properties of the original system. Our strategy is quite general and versatile. It is at least several orders of magnitude faster than those using many-chain simulations, thus effectively solving the transferability problem in coarse graining. It also avoids the problems caused by finite-size effects and statistical uncertainties in many-chain simulations commonly used in coarse graining.
12:15 PM - CM3.6.10
Modeling the Interaction of Magnetically Capped Colloidal Particles
Gemming Sibylle 1 2 , Aaron Strobel 2 , Maximilian Neumann 2 , Gabi Steinbach 1 2 , Artur Erbe 1
1 , Helmholtz-Zentrum Dresden-Rossendorf, Dresden Germany, 2 Institute of Physics, Technische Universitaet Chemnitz, Chemnitz Germany
Show AbstractColloidal self-assembly bears significant potential for the bottom-up fabrication of advanced materials and micromechanical structures. A wide range of particles with different types of anisotropy have been recognized as promising precursors for controlled structure engineering. For analyzing correlations between the anisotropy at the particle level and the shape of the assembly, simplified theoretical models have been developed to simulate the self-assembly and resulting structures. By simulation, fast scanning of particle parameters is possible, which may serve to extend the experimentally accessible parameter ranges and thus contribute to the rational design of desired assembly structures.
Here, we concentrate on particles that interact via polar fields, which are intrinsically anisotropic. Additional anisotropy may be introduced by an asymmetric distribution of the polar material, which leads to even more complex assembly behavior. Observed self-assembled structures can be reproduced by models of dipolar spheres, where the dipole is shifted away from the particle center. Despite the amazing success of these simple models, there have been observations of polar particles in which the assembly deviated from these predictions, if the polar material inside the particles exhibits a spatially extended form and deviates from a point dipole picture. Recently developed models take this into account by including more complex higher-order interactions, which require a larger and highly correlated set of parameters.
In the present study, we introduce an alternative, three-dimenional model for magnetic particles with broad, anisotropic magnetization distribution. In this model, the extended magnetization distribution is approximated by a conductive coil enclosed inside a hard sphere, which exhibits an ideal ring current. The far field of that current reproduces the stray field of a point dipole model, whereas the near field reflects the extended nature of the magnetization distribution. Such a model exhibits only two parameters to describe the shape of the magnetization distribution: The radius of the coil controls the width of the magnetization distribution. The position, or shift, of the coil inside the sphere determines the magnetic asymmetry. Here, we present stable two-particle configurations as a function of both parameters and discuss the resulting stray fields. In the limit of very small coils the analytical solution for two particles with shifted point dipoles is correctly reproduced. The transition from a linear dipole arrangement at small asymmetry to an antiparallel magnetic configuration at large asymmetry occurs at the identical shift values. By extending the radius of the coil we obtain additional magnetic arrangements not covered by the shifted dipole models, but observed experimentally. Based on these findings we give an outlook for extended studies that take more particles into account.
12:30 PM - CM3.6.11
Using Molecular Dynamics in Modeling Fluorescent Rosette Nanotubes
Arthur Gonzales III 1 , Belete Legesse 1 , Takeshi Yamazaki 2 , Hicham Fenniri 1
1 , Northeastern University, Boston, Massachusetts, United States, 2 , Vancouver Prostate Centre, Vancouver, British Columbia, Canada
Show AbstractRosette nanotubes (RNTs) are soft organic nanomaterials self-assembled from Watson-Crick inspired guanine-cytosine (GΛC) hybrid building blocks with complementary hydrogen bonding sites and stabilizing π-π interactions and hydrophobic effects. These materials have substantial design flexibility and a range of applications, which is partly attributed to their diverse surface functionalization and a chemically/physically tunable channel for guest molecule loading. With novel applications in mind, a new tricyclic GΛC motif was designed and synthesized to self-assemble into fluorescent RNT in solution. In this work, molecular modeling techniques, particularly molecular dynamics (MD), were applied to aid in the characterization of this new RNT, to predict its structure and self-assembly, and to determine its viability as a drug delivery vehicle.
MD and the statistical mechanical theory of solvation, also known as the 3 dimensional reference interaction site model (3D-RISM) theory were applied to predict the stable conformations of the RNT. RNT models were built from GΛC motifs and MD simulations were run at different conditions to determine its stability and probable structure. 3D-RISM integral equations were then solved to determine the thermodynamics of the system. The self-assembly was investigated further by randomly placing GΛC motifs on top of a template, a short helical coil RNT, and running MD simulations at experimental conditions to observe the growth of the RNT in silico. In addition, the potential for drug encapsulation using this novel RNT was tested by loading it with gemcitabine, a small molecule drug that is used to treat various carcinomas, and running MD simulations in physiological conditions to determine the stability the drug-RNT complex. All simulations were done using the Schrödinger Materials Science Suite on the Discovery Cluster of Northeastern University.
The results suggest that this tricyclic GΛC motif can either form helical coils (HC) or ring stacks (RS). Based on MD, the HC configuration of the RNT is more stable than the RS configuration, while the thermodynamics suggests that RS is slightly more stable than HC. Moreover, when a RS has formed, the 7-membered conformation seems more favorable than the 6-membered configuration. The self-assembly studies showed that π-π interactions drive the formation of aggregates of the motif at high temperatures. And for the first time, the growth of the helical coil RNT from free motifs in the solution was observed in silico. The stable helical coil seems to drive the alignment of free GΛC motifs to conform to the rest of the RNT. Finally, the MD simulations suggest that the gemcitabine-RNT complex is stable, making this fluorescent RNT a highly probable candidate for drug display and delivery. Experiments are currently being done to verify the molecular models.
12:45 PM - CM3.6.12
Parametric Study for Dimeric Anthracene-Based Mechanophore-Embedded Thermoset Polymer Matrix Using Molecular Dynamics
Bonsung Koo 1 , Aditi Chattopadhyay 1 , Lenore Dai 1
1 , Arizona State University, Tempe, Arizona, United States
Show AbstractThis paper presents a parametric study to investigate the effect of design variables on mechanochemical reaction and mechanical properties of a mechanophore-embedded thermoset polymer matrix. Mechanophores which emits fluorescence under mechanical loading, have attracted a large research interest as a damage sensor. Recently, dimeric 9-anthracene carboxylic acid (Di-AC), one of mechanophores, was synthesized successfully and incorporated into epoxy-based thermoset polymer matrix to detect damage precursor under the mechanical loading in the previous authors’ work. However, comprehensive understandings of the complex mechanochemistry associated with the Di-AC have not been addressed clearly. In this study, a hybrid MD simulation methodology is employed to explore this complex mechanochemistry mechanism along with the investigation of the effect of design parameters on the mechanophore performance. The hybrid MD simulation method enables to simulate Di-AC synthesis, epoxy curing, and mechanical loading test; therefore, the experimental process performed previously can be emulated accurately. In the previous numerical study, simulation results conducted under the room condition indicated that the hybrid MD method captured experimentally observed phenomena such as early signal detection and yield strength variation between neat epoxy system and 5 wt% Di-AC nanocomposite. Since the curing condition (temperature/pressure) does affect material properties of the epoxy system (host material of the Di-AC nanocomposite), it is reasonable to estimate that the mechanophore activation is also affected by curing condition. In this paper, the effect of curing condition (temperature/pressure) on mechanophore activation and mechanical properties is investigated. A series of temperature and pressure conditions is used in the curing simulation, which is experimentally available. The simulation results show that high curing temperature and pressure increase crosslinking degree as well as improve the self-sensing performance and mechanical properties compared to the Di-AC nanocomposite simulated under room condition; it provides an experimental design guideline.
CM3.7: Polymer-Based Composites and Nanocomposites
Session Chairs
Peter Coveney
Reid Van Lehn
Thursday PM, April 20, 2017
PCC North, 100 Level, Room 127 A
2:30 PM - *CM3.7.01
Understanding Nanoconfinement and Nanoscale Interfaces in Structural Materials
Sinan Keten 1
1 , Northwestern University, Evanston, Illinois, United States
Show AbstractNatural and engineered structural (load-bearing) nanocomposites often try to exploit microphases that are confined in nanoscale dimensions to achieve remarkable mechanical properties. However, the emergent performance of these materials depends strongly on both the chemistry of the interfaces and the microstructure of the material system, which complicates their design. In this talk, I will present a new computational materials-by-design paradigm for understanding phenomena occurring at such disparate scales. I will discuss several cases where the coupling between nanostructure and chemical structure will lead to intriguing phenomena, such as polymers with more or less identical bulk properties exhibiting contrasting behavior under nanoconfinement in thin films. Drawing an analogy between thin films and nanocomposites, I will illustrate how understanding thin film simulations help us design better load-bearing nanocomposites with graphitic and nanocellulosic fillers.
3:00 PM - CM3.7.02
Detailed Investigation of Interfacial Molecular Interactions for Graphene-Based Rubber Nanocomposites
Jeeno Jose 1 , Narasimhan Swaminathan 1
1 , Indian Institute of Technology Madras, Chennai India
Show AbstractAccurate prediction of the traction – separation law at the molecular interface between carbon additives and rubber is crucial to model the macroscopic constitutive behavior of rubber nanocomposites. In this work we simulate the traction – separation between cis-1,4-polyisoprene (PI) and graphene. Graphene is chosen to simulate the carbon black, carbon nanotube or graphite additives. We first build a network of dense cis-1,4-PI network on a sheet of graphene using a combination of energy based self avoiding random walk, molecular statics and dynamics methods. The physical and morphological properties of the samples we generated, compared well with experiments and simulation results in the literature [1].
Using molecular dynamics, graphene-polymer samples of various sizes were equilibrated to ~300K and atmospheric pressure after which the graphene layer was pulled off from the PI network in normal (opening mode) and shear (sliding mode) directions. After deciding on the appropriate sample size, several computational experiments were carried out to understand graphene-PI interfacial traction – separation behavior. Tests were conducted at several pull rates, temperatures and preloaded conditions. Molecular level physics governing the observed traction-separation curves was explained based on the generation and annihilation of voids at the interface.
[1] Doxastakis, M.; Mavrantzas, V. G.; Theodorou, D. N. Journal of Chemical Physics 2001, 115, 11339–11351
3:15 PM - CM3.7.03
Modeling Isolated Polymer-Grafted Nanoparticles on Surfaces—Effect of Adsorption Strength on Morphology and Dynamics
Jeffrey Ethier 1 , Lisa Hall 1
1 , Ohio State University, Columbus, Ohio, United States
Show AbstractSolvent free polymer-grafted nanoparticles, or hairy nanoparticles (HNPs), are organic-inorganic hybrid materials with interesting properties that depend on graft length and density, among other variables. Thin film HNP assemblies have recently garnered attention due to the potential to tune and optimize their optical, dielectric, or mechanical properties. Understanding the behavior of individual HNPs on surfaces is a first step to creating controlled assemblies, and individual or small groups of adsorbed HNPs may be directly useful in specialty printing or other applications. Here, we investigate the effect of substrate interactions on the canopy morphology, dynamics, and entanglements of one or more HNPs, using molecular dynamics (MD) simulations. We use a generic bead-spring model in which HNPs are composed of spherical particles with polymer chains grafted to their surface at various grafting densities and chain lengths (molecular weights), and the particles are ten times the diameter of monomers. We vary the well depth of the favorable monomer-substrate interaction, and observe the height profile of the polymer canopy surrounding the particle(s). As expected, the canopy flattens and spreads out across the surface significantly as monomers adsorb more strongly. Because entanglements are expected to be a key driver of material properties of HNP assemblies, we also analyze the entanglement network of our HNPs using a geometrical method. Of particular interest is understanding what system parameters lead to significant entanglements between two nearby HNPs on the surface. We report entanglement density and chain dynamics as a function of distance from the substrate and from the nanoparticle surface(s) for various polymer-wall adsorption strengths. We also compare with recent experimental findings, showing closely matched experimental and simulation canopy height profiles at various adsorption strengths.
3:30 PM - *CM3.7.04
Utilizing Multiscale Modeling in Elastomer Composite Research for Tire Applications
George Papakonstantopoulos 1 , Bing Jiang 1 , Craig Burkhart 1 , Mike Poldneff 1
1 Global Materials Science, Goodyear Tire and Rubber, Akron, Ohio, United States
Show AbstractTires are a highly engineered product with a great amount of research being devoted every year. The compounds used to make up our tires are truly nanocomposite materials with a unique set of properties that control the performance of the tire. Discovery and design of novel materials or new ways of using old ones to improve the properties of our compounds is of extreme importance. This is especially true for tire tread compounds which are a large contributing factor to the fuel efficiency of a tire. While traditional research approaches keep bearing fruit, the use of Multiscale Modeling in this effort is growing rapidly. Multiscale Modeling brings the ability to innovate faster, develop new materials in a shorter timeframe and subsequently introduce new products to the market quicker through more efficient and targeted experimentation. In addition, Multiscale Modeling has been proven as an extremely valuable tool for improving our fundamental understanding and providing new insights. Finally, the promise that Multiscale Modeling brings has also been recognized by our customers who are now requesting virtual design capabilities as part of the development process. We will present examples of how Multiscale Modeling has been recently used in our material research efforts to successfully deliver material approaches towards the development of new compounds.
4:30 PM - CM3.7.05
An Adaptive Design Approach for Exploring the Interphase Properties in Polymer Nanocomposites
Yixing Wang 1 , Yichi Zhang 1 , He Zhao 1 , Xiaolin Li 1 , Yanhui Huang 2 , Wei Chen 1 , Linda Schadler 2 , L. Catherine Brinson 1
1 Mechanical Engineering, Northwestern University, Evanston, Illinois, United States, 2 , Rensselaer Polytechnic Institute, Troy, New York, United States
Show AbstractMany researchers have focused on investigations of polymer nanocomposites because of their potential as future materials. The polymer segments near the particle is considered as an interphase layer, whose properties are significantly different from the matrix because of the differences in structure. In order to fully understand the behavior of the interphase and make accurate prediction and design of nanocomposite properties, efforts have been made to investigate the interphase analytically and experimentally. Recent experimental works concentrate on indirect measurements by correlating thin film and nanocomposite data, showing adequate evidence that the local polymer properties are significantly altered in the nearby surroundings of the particle surface. From modeling perspective, there have been lots of continuum models developed using the multi-core concept. The interphase properties are often obtained inversely after the bulk composite properties are obtained through experiments. Additionally, in order to fully capture the dispersion state of the fillers, multi-scale simulations have been developed. It has been shown that the interphase properties can be described by shifting factors based on the pure matrix. The amount of the shift is determined by a trial-and-error based iterative tuning procedure with the aim of achieving the best fit between the simulation and the experimental data. However, it is inefficient to determine the interphase properties through trial-and-error because of the relatively expensive computation cost from simulation. Furthermore, the manual tuning process also limits the potential of the FE model to be applied as a powerful design tool for new materials with desired performance.
In this work, we show how an adaptive design strategy can be applied to accelerate the search of the interphase properties in polymer nanocomposites. Our approach starts with identifying the objective and formulating objective functions. Then an adaptive optimizer is applied to effectively navigate the complex high-dimensional design space through iteratively selecting the next optimal points, providing augments for the training data, based on the feedback from surrogate regression model with uncertainties. The accuracy of the surrogate model and the optimal solution evolves until the desired objective is satisfied. This adaptive design approach has been tested on searching the interphase properties on dielectric and viscoelastic studies. Results show that it only takes tens of iterations before the optimal shifting factors and the interphase properties is determined. Comparisons are made among different searching algorisms to show that our approach improve the efficiency of exploring. Our work provides insight into identifying the interphase properties for polymer nanocomposites by adaptive design and provides mechanism to apply data mining principles to many data sets for deeper understanding of the interphase and its origins.
4:45 PM - CM3.7.06
Properties and Processing of Clay-Polymer Nanocomposites Modelled Using a Multiscale Approach
James Suter 1 , Derek Groen 2 , Peter Coveney 1
1 , University College London, London United Kingdom, 2 , Brunel University London, London United Kingdom
Show AbstractNano-composites are defined as multiphase solid materials where one of the phases has at least one dimension of less than 100 nanometres (nm) and their large scale properties are critically dependent on how the components interact on the molecular level. We have developed an advanced multiscale simulation environment to predict the properties of such nanocomposites based on their molecular structures and composition. These methods have applications in modelling a wide range of materials and it is our aim to create a “virtual laboratory” to compute the properties of these materials based simply on knowledge of their chemical composition, molecular structure and processing conditions [1].
Here we will present our findings from modelling chemically specific combinations of clay, polymers and organic surfactants. We use our multiscale methods and tools to take us from a parameter free quantum description to atomistic and coarse-grained molecular dynamics simulations, thereby leading to predictions of the materials properties of these nanocomposites. Our simulations approach realistic sizes of clay platelets (currently of diameter 100-200 Å) at low clay volume fractions (5%). These systems exhibit substantial property enhancements when compared to the pristine polymer (elastic properties, gas permeation), but homogeneous dispersion of the clay sheets is required.
We have used our multiscale approach to predict the melt intercalation behaviour and final morphologies of organo-treated montorillonite clay–polyvinyl-alcohol and montorillonite clay–polyethylene-glycol systems [2]. To represent common processing conditions, we have also examined the behaviour of these systems under shear, by subjecting our coarse-grained models to a polymer flow field. The simulations have allowed us to examine, in molecular detail, the role of polymer molecular weight and its attraction to the clay surface in determining the initialisation of clay platelet exfoliation and the final morphology of the clay layers. Shear forces can skew the clay slayer stack, but we show that the determining factor is the attraction of the polymer to the clay surface, which can be modified through surfactants present on the clay surface.
From our multiscale simulations, we can compute various characteristics of these nanocomposites, including clay-layer spacings, out-of-plane clay sheet bending energies, X-ray diffractograms and materials properties, which we relate to the system's final morphology.
[1] J. L. Suter, D. Groen, P. V. Coveney, Adv. Mater. 2015, 27, 966–984
[2] J. L. Suter, D. Groen, P. V. Coveney, Nano Lett., 2015, 15, 8108–8113.
5:00 PM - CM3.7.07
New Insights into Graphene Exfoliation with Molecular Dynamics
Robert Sinclair 1 , Peter Coveney 1 , James Suter 1
1 , University College London, London United Kingdom
Show AbstractGraphene based nano-composites hold great potential as novel and practical materials. Their manufacture has been held back by difficulties in controlling the synthesis of graphene and the subsequent dispersion into a polymer matrix. Much research has been devoted to understanding these processes through simulation. Here, we investigate the force-fields that have been used for molecular dynamics simulations of graphene, comparing against experimental and quantum simulation results, and find them lacking in their description of graphene-graphene interactions. Specifically, they underestimate the energy required to slide sheets of graphene over each other, thought to be a key mechanism for solution-phase exfoliation. A new force-field, GraFF, has been designed, which is better suited to describe the exfoliation of graphite in simulations. We use this new force-field to study the swelling characteristics of graphite in different solvents and the possible mechanisms for exfoliating graphite in solution.
Symposium Organizers
Peter Coveney, University College London
Valeriy Ginzburg, Dow Chemical Company
Olga Kuksenok, Clemson Univ
Veena Tikare, Sandia National Laboratories
Symposium Support
Clemson University, Department of Materials Science and Engineering
The Dow Chemical Company
Goodyear Tire and Rubber Company
PPG Industries, Inc.
Sandia National Laboratories
CM3.8: Liquid Crystals, Colloids and Granular Materials
Session Chairs
Valeriy Ginzburg
Qiang Wang
Friday AM, April 21, 2017
PCC North, 100 Level, Room 127 A
9:45 AM - CM3.8.02
Phase Transition in Plastic Crystalline Assemblies of Janus Colloids—Similarities with Isotropic-Nematic Liquid Crystals
Hossein Rezvantalab 1 , Daniel Beltran-Villegas 1 , Ronald Larson 1
1 , University of Michigan, Ann Arbor, Michigan, United States
Show AbstractThe pressure distribution in a stack of anisotropic colloids generally depends on the orientational distribution of neighboring particles. We demonstrate through Brownian Dynamics simulations that controlling pressure anisotropy can yield a rapid first-order rotator-to-lamellar phase transition in plastic crystalline assemblies of Janus spheres. We show that this transition, which occurs at constant temperature with almost no translational diffusion, bears similarities with the isotropic-to-nematic phase transition in liquid crystals: the order parameter at transition and the probability distribution function of particle orientation closely follow the predictions of the Maier-Saupe theory, originally developed for positionally disordered materials. Our unprecedented demonstration of the applicability of this theory to a colloidal phase transition allows all significant aspects of the transition to be mapped onto a single pressure and temperature dependent parameter, thus guiding the design of rapidly switchable colloidal crystals.
10:00 AM - CM3.8.03
Design of Membrane-Embedded Amphiphilic Nanoparticles from Multiscale Simulations
Reid Van Lehn 1
1 , University of Wisconsin-Madison, Madison, Wisconsin, United States
Show AbstractFunctionalized, monolayer-protected nanoparticles (NPs) are a versatile materials platform for applications relevant to human health because the protecting surface monolayer can be engineered to tailor interactions with the surrounding environment. NPs are of particular interest in biomedical applications because their small size enables long circulation times and unique cellular interactions. However, structure-function relationships correlating the nanoscale properties of engineered nanomaterials to their biological interactions remain unclear and are difficult to determine experimentally. Here, we demonstrate that molecular modeling across multiple length scales can aid in the interpretation of experiments and guide the design of novel nanomaterial functionalities. We focus on understanding the ability of a class of amphiphilic NPs to enter cells via a non-endocytic, non-disruptive mechanism that is of broad interest for applications in drug or gene delivery. This behavior is surprising because bypassing the cell membrane requires the NPs to translocate charged groups across the hydrophobic core of the lipid bilayer. We use atomistic molecular dynamics simulations to gain molecular insight into these experimental observations and predict outcomes in model membrane systems. Our results show that the amphiphilic NPs insert into the bilayer to obtain configurations resembling membrane-embedded proteins due to favorable interactions between the NP surface and the hydrophobic bilayer core. Membrane insertion is enabled by the rapid translocation of charged end groups due to the local deformation of the bilayer. We further develop an implicit solvent modeling approach that facilitates the high-throughput determination of how varying monolayer compositions affect the thermodynamics of bilayer insertion. Finally, we leverage this mechanistic understanding to provide design guidelines for monolayer compositions optimized for non-endocytic cellular uptake. This framework illustrates the power of multiscale modeling to understand and predict behavior at the nano-bio interface.
10:15 AM - CM3.8.04
Experimental and Computational Characterization of Wet Granular Media
Hosain Bagheri 1 , Spandana Vajrala 1 , Vishwarath Taduru 1 , Shawn White 1 , Heather Emady 1 , Hamid Marvi 1
1 , Arizona State University, Tempe, Arizona, United States
Show AbstractInteraction of foreign bodies with granular media, like that of sand and mud, introduces a highly nonlinear behavior. Complications arise when attempting to formulate mathematical models for these interactions, especially with wet granular media. Simulation tools, such as EDEM (a Discrete Element Method software package), provide an advantageous platform for circumstances when empirical data cannot be easily obtained or is found to be insufficient. While EDEM does not have a designated contact model that can directly simulate water, the effect of water can indirectly be simulated. Through the usage of additional contact models, such as Linear, Hertz-Mindlin and JKR (Johnson Kendall and Roberts) Cohesion, the cohesive nature of saturated granular media can be captured and implemented. All that would be required is the granular media’s surface energy value at different saturation levels. These surface energy values will need to be obtained experimentally and inputted into EDEM for simulations. Validations of the finding will be performed by dropping a solid sphere (with known parameters) upon a granular media bed at different saturation levels and observing its impact and penetration depth. Recreation of the experiment will be performed in EDEM. Through these series of experimental and computational simulations, the relationship between surface energy values and saturation levels can be obtained. These findings will provide a greater insight into wet granular media and a more comprehensive analysis of locomotion on such media. More importantly, the obtained information can be used to expatiate the design and optimization process of building robotic systems that will be able to traverse over granular media.
10:30 AM - CM3.8.05
Heterogeneous Nanomechanical Properties of Type I Collagen in the Longitudinal Direction
Ming Tang 1 , YuanTong Gu 1
1 , Queensland University of Technology, Brisbane, New South Wales, Australia
Show AbstractCollagen is the main structural protein in vertebrates, providing the mechanical integrity for connective tissues including tendon, skin, ligament, bone and cartilage. The mechanical behaviours of these tissues are determined by the nanomechanics of their structures at different hierarchies and the role of collagen structures in the extracellular matrix. Some studies revealed that there is significant microstructural difference in the longitudinal direction of the collagen fibril, which challenges the conventional rod-like assumption prevalently adopted in the existing studies. Motivated by this discrepancy, we investigated the longitudinal heterogeneous nanomechanical properties of type I collagen molecule to probe the origin of the longitudinal heterogeneity of the collagen fibril at the molecular level, taking into account the viscoelasticity. In this work, we studied the mechanical properties of the three intact ‘gap’ and three intact ‘overlap’ regions of a type I collagen molecule under different constant pulling forces in terms of elasticity and viscosity. The obtained mechanical properties are in good agreement with the values reported in previous experimental and computational studies. This suggests that our computational model can be used to capture the mechanical behaviours of the collagen molecules. Besides, we found that the six collagen segments present different mechanical properties, which indicates that there is significant mechanical heterogeneity in longitudinal direction of the collagen triple helix. We propose that this difference in mechanical properties originates from the longitudinal structural variations due to different amino acid sequences. This investigation provides insights into the origin of the longitudinal heterogeneity of collagen fibrils at the molecular level, and suggests that it is of significant importance to consider the longitudinal heterogeneous mechanical properties of the collagen molecule in the development of coarse-grained models of collagen-related tissues.
11:15 AM - *CM3.8.06
Constructing Novel Polymorphs from Predicted Nanoclusters Taken from the Hive
Scott Woodley 1 , Alexey Sokol 1 , John Buckeridge 1 , Matthew Farrow 1 , Tomas Lazauskas 1
1 Department of Chemistry, University College London, London United Kingdom
Show AbstractThe development of global optimization schemes for predicting atomistic frameworks with desired microporous architecture as well as the atomic structure of inorganic nanoclusters is one area I have worked extensively on for nearly two decades. With no direct experimental route to determining the atomic structure of nanoclusters, recently I have led the WASP@N project (Web Assisted Structure Prediction at the Nanoscale) that aims to create a searchable website database of atomic structures of nanoclusters. The database, or Hive, has been developed for the nanocluster community including those who actively predict local minima structures and also those who require atomic structure information in order to begin their simulations/ investigations. Moreover, novel and some familiar microporous framework polymorphs have been constructed from high symmetry nanoclusters taken from the Hive. For the selected compounds, high symmetry, nanoclusters are typically the global minima for their respective size; we have investigated secondary building units (SBUs) with point symmetry Th and Td, which are formed of three coordinated atoms that make a layer of hexagons that is curved in 3D by the presence of six tetragons. In these SBUs, the distance between the tetragons is maximized (they are only edge sharing in the smallest Td nanocluster, which is a cube of only tetragons). Clearly, stacking the cuboids will generate the well known NaCl rock salt polymorph, whereas using larger SBU can generate polymorphs containing larger pores. Initially we considered the stability of polymorphs as a function of density and then chose compounds in order to tune a desired property.
Although applications have a focus on hard materials, the methodology developed and applied could equally be employed for modeling, or predicting, soft materials. Time permitting, I will present more details of the constructed polymorphs, summarize a number of applications that exploit our global optimization software, as well as introduce the Hive web-database.
11:45 AM - CM3.8.07
Experimental and Computational Comparison of Granular Media Reactions
Andrew Thoesen 1 , Sierra Ramirez 1 , Erik Asphaug 2 , Hamid Marvi 1
1 SEMTE, Arizona State University, Tempe, Arizona, United States, 2 SESE, Arizona State University, Tempe, Arizona, United States
Show AbstractWe conduct experiments and simulations of the interaction of a spacecraft propulsion auger with the granular media similar to that found on asteroids, comets and small moons. Asteroid regoliths behave differently than analogs on Earth due to microgravity conditions and the airless, radiation-exposed environment. While simulations can be run in programs such as EDEM, the testing of spacecraft operations must also be done in real physical settings. A comparative experiment between simulations and a high fidelity environment can highlight discrepancies between the two and determine to an extent the usefulness of such simulations and experiments. Making comparisons using standard glass beads will allow for accurate model parameterization. These experiments will also be simulated in EDEM. Combined, this will give us a clearer picture into how small particles (a few hundred microns to a few millimeters in diameter) interact and whether an analogous environment can be tested on Earth.
12:00 PM - CM3.8.08
Design of Origami-Based Mechanical Instabilities to Amplify Active Material Responses
Andrew Gillman 2 , Benjamin Treml 2 , Richard Vaia 1 , Phil Buskohl 1
2 , UES, Inc, Beavercreek, Ohio, United States, 1 , Air Force Research Laboratory, Wright-Patterson Air Force Base, Ohio, United States
Show AbstractNext-generation materials for remote devices, sensors and regulators require mechanically adaptive and environmentally active behaviors, such as the conversion of light, heat, or humidity into functional mechanical deformation. Active materials with fast response times (~ seconds) have particular advantage for “real-time” sensing applications, such as using hydroscopic polymers to map humidity fields, which are dynamic, heterogeneous, and often very difficult to monitor. However, the rapid response rate comes at the expense of lower mechanical strain generation, limiting the useful motion and the mechanical work of the system. To amplify the mechanical response of these active materials, we designed and patterned origami fold topologies into active materials to create metastable equilibrium states that are accessed through the environmental stimulation. An origami optimization design tool was developed to predict optimal fold topologies and the placements of active material to tune the energy barriers between equilibrium states for a preferential transition order or to maintain an energetic parity between states to enable oscillations. Origami patterns that derive their mechanical instability from possessing a non-flat reference state, such as the “water-bomb” pattern, were also studied to evaluate the effect of the reference configuration on the energy landscape. Design concepts developed with the optimization tools were experimentally evaluated with a humidity responsive Nylon and polyimide material system. The combination of active materials with fast response times, local patterning and mechanical design provides a novel platform to amplify the mechanical response and increases functionalization of environmental stimuli for remote, autonomous activation.
12:15 PM - CM3.8.09
Diffusion of Water into Biopolymer Matrix under Different Mechanical Strain
Santhosh Mathesan 1 , Amrita Rath 1 , Pijush Ghosh 1
1 , Indian Institute of Technology Madras, Chennai India
Show AbstractHydrogels with excellent water absorbing capacity and stimuli responsive properties are considered to be an outstanding class of materials suitable for biomedical applications. Stimuli responsive hydrogels are capable of altering its shape and size depending on the external environment like pH, light, temperature etc. Self-folding phenomenon is one of the prominent responses of water responsive hydrogels which is widely used in biosensors and drug delivery. Chitosan (CS) is a biopolymer based hydrogel which exhibits the self-folding behavior in the presence of water. Self-folding phenomenon in hydrogel film is achieved due to differential swelling. Initially, the water molecules get adsorbed to film surface in contact with water and they diffuse into the bottom layer of CS film. The diffusion process introduces a water concentration gradient across the thickness of film. The bottom layer tends to swell more compared to the top layer (non-swelling) of CS film. Thus incorporating self-folding phenomenon in CS film in the presence of water and induces an out-of-plane curvature in the film. The swelling layer experiences tensile strain and the non-swelling layer experiences compressive strain. Also, it is noteworthy to mention, the tensile and compressive strain has significant influence on the pathway of water molecules which can be interpreted from root mean square displacement of water molecules. In this work, we have attempted to understand the relation between the diffusion of water molecules and mechanical strain, which induces the shape changing properties in hydrogel films. Molecular dynamics simulation is adopted to understand the atomistic level mechanisms responsible for the experimentally observed self-folding phenomenon. Chitosan has amine and hydroxyl group as hydrophilic functional sites. These sites are responsible for interaction with water molecules during the diffusion process. Here, we have computed the diffusion coefficient at different strain and also under different modes of loading path or stress path. With different modes of loading, the free volume available for the water molecules to diffuse is altered and also the accessibility of water molecules towards the reactive sites in the network is affected. The molecular mechanisms obtained from atomistic simulations can assist in designing the optimal properties of hydrogel films towards specific applications like microgrippers, detection of biomolecules etc..
12:30 PM - CM3.8.10
Computational Design of Biomimetic Nanoparticles for Nucleic Acid Packaging
Jessica Nash 1 , Yaroslava Yingling 1 , Hoshin Kim 1
1 , North Carolina State University, Raleigh, North Carolina, United States
Show AbstractGene therapy holds the promise of treatment of a myriad of diseases including many types of cancer, cardiovascular disease and genetic disorders. Despite promise, gene therapy is plagued by lack of safe, predictable, and reliable methods for packaging, delivery, and transport of DNA or RNA. Ligand-coated inorganic nanoparticles may be designed to bind and to package nucleic acids using approaches such as tailored size and shape and cationic or aromatic ligand functionalization. However, nanoparticle binding may cause undesired changes in nucleic acid structure and thus may influence delivery efficiency.
Recently, there has been interest in designing nanoparticles for packaging nucleic acids which mimic the behavior of biological proteins such as histones. In this work, we use all-atom molecular dynamics simulation to design and test NP behavior with nucleic acids. We have previously investigated conformational changes and DNA packaging induced by small gold nanoclusters and found that the distribution of charge on the nanoparticle impacts binding to double stranded DNA.
Here, we present results from all atom simulation of the binding of nucleic acids to nanoparticles of variable core size and charge. We have performed the largest simulations of these systems to date, investigating nucleic acids of up to 100 base pairs using all-atom simulation. We find that nanoparticle core size and ligand length affects nanoparticle-nucleic acid binding kinetics; nanoparticles with larger cores and shorter ligands bend and wrap DNA more slowly than nanoparticles with smaller cores and longer ligands, despite having the same overall charge and radius of gyration. We compare conformational changes induced by nanoparticles and find good agreement with that induced by biological particles, with the quality of wrapping depending on the properties of the nanoparticle. We also show that through proper nanoparticle design, we are able to induce smooth bending of double stranded RNA molecules. Our work to understand the compaction of nucleic acids by synthetic and designed nanoparticles has the potential to not only provide rules for designing nucleic acid carriers, but to give insight to the biological process of nucleic acid packaging.
12:45 PM - CM3.8.11
Improving Thermal Stability of Hen Egg White Lysozyme via Conjugation with Copolymer
Chandan Choudhury 1 , Sidong Tu 1 , Nataraja Yadavalli 2 , Nikolay Borodinov 1 , Tatiana Quinones-Ruiz 3 , Igor Lednev 3 , Igor Luzinov 2 , Sergiy Minko 2 , Olga Kuksenok 1
1 , Clemson University, Clemson, South Carolina, United States, 2 Department of Chemistry, University of Georgia, Athens, South Carolina, United States, 3 , University at Albany, Albany, New York, United States
Show AbstractImproving thermal stability of enzymes is vital for a variety of applications incorporating them into engineering materials. We demonstrate that by conjugating enzymes with copolymers with tailored architectures one can dramatically improve their thermal stability well beyond that of native enzymes. We use molecular dynamics simulations to study the thermal stability of the polymer-conjugated lysozyme (LPC) with respect to that of native lysozyme (HEWL). To design the LPC, we conjugated the lysine residues of lysozyme with OEGMA-GMA-OEGMA oligomer (triads). The system also contains free-floating triads which effectively allow us to more closely mimic our experimental system. Our studies show that LPC, unlike the native lysozyme, largely preserves its secondary structure under the same high temperature. To characterize the dynamics of both systems under heating quantitatively, we analyzed the time evolution of (a) the root mean square deviation (RMSD) of each structure with respect to its initial structure, (b) the number of intra H-bonds of the enzyme and (c) evolution of secondary structures. Our findings show that the 3D structure of lysozyme is significantly stabilized at 500 K when it is enveloped with the triads compared to that of the native enzyme. Notably, this secondary conformation content remains lower than that for the native HEWL at room temperature, confirming partial melting of the structure. Our simulation results are consistent with the observations in our experimental studies.
CM3.9: New Modeling Approaches on Multiple Length Scales
Session Chairs
Olga Kuksenok
Reid Van Lehn
Friday PM, April 21, 2017
PCC North, 100 Level, Room 127 A
2:30 PM - CM3.9.01
Effect of Graphene Oxidation on Structure and Dynamics of Biomolecules Using Computational Modeling
Hoshin Kim 1 , Barry Farmer 1 , Yaroslava Yingling 1
1 , North Carolina State University, Raleigh, North Carolina, United States
Show AbstractGraphene-based surfaces, including pristine graphene and graphene oxide (GO), have been used in various biomedical applications, such as bio-sensors or drug-delivery. It has been reported that surface polarity can either enhance or deteriorate the bio-compatibility, functionality, and stability of biomolecules. However, fundamental understanding of how surface properties influences biomolecular structure and properties remains to be elucidated. We performed atomistic molecular dynamics simulations in order to address the following questions: (1) relationship between biomolecule structure stability and surface polarity and (2) key interactions that govern the bio-functionalization process. Two types of biomolecules were examined: DNA and silk protein. Simulation results showed that both DNA and silk protein tended to lose their unfolded structures on pristine graphene surface via strong hydrophobic interactions with the surface (e.g. pi-pi stacking interactions), whereas folded structures were maintained during the entire simulation on GO surface with moderate oxygen coverages. However, on GO surfaces with high oxygen coverages, strong interfacial hydrogen bonds induced a loss of internal interactions of DNA and silk protein. We found that the balance between van der Waals and electrostatic interfacial interactions and geometrical hindrance induced by functional groups on the surface is critical for adsorption process. Most importantly, for silk protein, this balanced interactions observed in GO with moderate oxygen coverages can not only preserve secondary structures but also restore ordered structures from disrupted chain-like structures. Overall, our computational results not only revealed the underlying process of physisorption between bio-molecules and graphene-based surfaces but also provided insights in designing many applications of bio-functionalized surfaces.
2:45 PM - CM3.9.02
Incorporating Complex Reaction Mechanisms into Classical Molecular Dynamics
Jacob Gissinger 1 , Benjamin Jensen 2 , Kristopher Wise 2
1 , University of Colorado-Boulder, Boulder, Colorado, United States, 2 , NASA Langley Research Center, Hampton, Virginia, United States
Show AbstractAn algorithm capable of incorporating multi-step reaction mechanisms into running atomistic molecular dynamics (MD) simulations is proposed and implemented within the framework of the LAMMPS package. This extension has the potential to utilize traditional fixed valence force fields for reactive processes when the reaction mechanism of a given process is known. It relies on a generalized topology matching algorithm as well as dynamic relaxation of each individual reaction as it occurs. Two case studies, 1) the condensation polymerization of nylon 6,6 and 2) the formation of a highly-crosslinked epoxy, are simulated to confirm the robustness, stability and speed of the algorithm. Improvements which could increase its predictive power are discussed.
3:00 PM - *CM3.9.03
Multiscale Modelling of Nanoscale Materials and Electronic Transport
Pascal Friederich 1 2 , Velimir Meded 1 , Franz Symalla 1 , Tobias Neumann 2 , Vadim Rodin 3 , Florian von Wrochem 3 , Wolfgang Wenzel 1 2
1 , Karlsruhe Institute of Technology, Karlsruhe Germany, 2 , Nanomatch GmbH, Karlsruhe Germany, 3 , Sony Europe Ltd., Stuttgart Germany
Show AbstractSmall-molecule organic semiconductors are used in a wide spectrum of applications, ranging from organic light emitting diodes to organic photovoltaics. A number of factors determine the materials properties, such as molecular packing, electronic structure, dipole moment and polarizability. Presently, quantitative ab-initio models to assess the influence of these molecule-dependent properties are lacking. Here, we present a multi-scale model, which provides an accurate prediction of carrier mobilities over ten orders of magnitude in mobility and allows for the decomposition of the carrier mobility into molecule-specific quantities. We provide molecule-specific quantitative measures how two single molecule properties, the dependence of the orbital energy on conformation and the dipole induced polarization determine mobility for hole-transport materials and demonstrate that the model can be used predictively to develop new materials. In addition to efficient methods to model the structure at the molecular level, we discuss novel approaches to describe mesoscale structure formation with applications to organic solar cells. The availability of first-principles based models to compute key performance characteristics of organic semiconductors may enable in-silico screening of numerous chemical compounds for the development of highly efficient opto-electronic devices.
4:00 PM - CM3.9.04
DFT and Force Field Study on the Effect of Ions on Structure and Side-Chain Interactions in Peptoids
Marcel Baer 1
1 , PNNL, Richland, Washington, United States
Show AbstractThe description of peptides and the use of molecular dynamics simulations to refine structures and investigate the dynamics on an atomistic scale are well developed. Through a consensus in this community over multiple decades has resulted in the availability of parameterized force field that only require the sequence of amino-acids and an initial guess for the three-dimensional structure. The recent discovery of peptoids, that are designed with functionality attached to the nitrogen instead of the Ca is a significant departure from the standard force fields for peptides and will require a retooling of the currently available interaction potentials in order to have the same level of confidence in the predicted structures and pathways as there is presently in the peptide counterparts. Here we present modeling of peptoids using a combination of ab initio molecular dynamics (AIMD), atomistic resolution classical FF and coarse-grained models (CG) to span the relevant time and length scales. To make contact with experiments and identify features of the peptoid monomers that promote formation of stable/ordered nanostructures, both nucleation and aggregation will be explored using CG simulations. To properly account for the dominant forces that stabilize ordered structures of peptoids, namely steric-, electrostatic, and hydrophobic interactions mediated through sidechain-sidechain interactions in the CG model those have to be first mapped out using high fidelity atomistic representations. A key feature here is not only to use gas phase quantum chemistry tools, but also account for solvation effects in the condensed phase through ab inito molecular dynamics simulation. One major challenge is to elucidate ion binding to charged or polar regions of the peptoid and its concomitant role in the creation of local order. Here, similar to proteins, a specific ion effect is observed suggesting that both the net charge and the precise chemical nature of the ion will need to be described
4:15 PM - CM3.9.05
Phosphorescence from Pure Organic Bromofluorene Derivatives—Simulation and Experimental Studies
Hossein Hashemi 1 , Jaehun Jung 1 , Jinsang Kim 1 , John Kieffer 1
1 , University of Michigan, Ann Arbor, Michigan, United States
Show AbstractThe photophysical properties of a series of bromofluorene (BrFl) derivatives have been investigated using density functional theory (DFT) and time-dependent DFT(TDDFT). The calculated absorption properties emission properties, and phosphorescence quantum yield of the BrFl derivatives are in good agreement with the available experimental data. We also explored the spin orbit coupling values, the S → T intersystem-crossing matrix elements and crossing rate constants of the BrFl derivatives. Both radiative and non-radiative decay rates of the lowest triplet state (T1) are calculated for all representative BrFl derivatives. Our studies suggest that functional group modification can control not only phosphorescent properties and emission color, but also brightness. Our findings demonstrate how computational methods can be effectively used for the predictive design of organic materials in lighting devices.
4:30 PM - CM3.9.08
Mesoscale Modeling of Peptide Nanotube
Leela Rakesh 1 , Sophie Bedford 2
1 Department of Mathematical Sciences, Central Michigan University, Mt Pleasant, Michigan, United States, 2 Department of Mathematics & Chemistry - Biochemistry Center for Applied Math & Computational Polymer Fluid Dynamics, Central Michigan University, Mt Pleasant, Michigan, United States
Show AbstractProteins and peptides like biologically active materials have the inherent aptitude to self-assemble into elongated solid nano-fibrils, which may instigate applications in biomedical engineering, and bio-Nano electronics and may give rise to various disease such amyloid plaque formation in Alzheimer’s. It may also give rise protein-like self-assembly as similar to carbon nanotubes (CNTs). Nanotubes can arise from variety of materials such as, protein, amyloid proteins, DNA, carbohydrates, lipids, synthetic polymers etc. Presently, this has attracted research interest among nanotechnology scientist. The simple peptide building blocks of NTs are dipeptides from the diphenylalanine motif of β-amyloid peptide (which seen in Alzheimer’s disease) with 100-300 nm having 1-2 micron length, but under different chemical environment the same could reproduce other shapes such as spheroids . There seems to be a lack of theoretical insight into peptide NT formation and its self- assembly at various conditions. Therefore, using models of hierarchical multiscale modeling, we report growth of a mesoscopic model for peptide nanotubes with parameters derived from atomistic simulations. The parameters in the mesomodel fit to reproduce NT formation, self –assembly/folding, bundle formation, elasticity, tension, and adhesion properties of peptide nanotube. We will also investigate the adsorption of various molecule (such as chloroform, Lysophospholipids) interaction to the inner and outer surface to understand the hydrophobicity, and transmembrane-ion channel formation
4:45 PM - CM3.9.09
Magneto-Elastic Colloidal Membranes
Mykola Tasinkevych 1 , Pablo Vazquez-Montejo 1 , Joshua Dempster 2 , Monica Olvera de la Cruz 1 2
1 Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois, United States, 2 Department of Physics and Astronomy, Northwestern University, Evanston, Illinois, United States
Show AbstractParamagnetic colloidal particles are considered to be very attractive building blocks for advanced responsive materials because of the relative ease and precision with which their interactions may be tuned with dynamic magnetic fields. In this study, we combine molecular dynamics simulations and a continuum approximation analysis to investigate the behavior of elastic membranes composed of linked paramagnetic beads in precessing magnetic fields. In this system, the membrane conformations are controlled by the competition between the bending energy and the magnetic interaction. We characterize the resulting conformations in terms of the area and material parameters as well as of the strength and precession angle of the magnetic field. For open membranes we observe configurations with both one- and two-dimensional surface undulations or rippled helicoidal shapes, whereas closed membranes may elongate or flatten depending on the field precessing angle. Experimentally, such membranes may be realized by linking magnetic colloids into two-dimensional sheets which in turn might be suitable for many potential applications due to their controllable conformational changes.
Acknowledgements: This work was supported by the Center for Bio-Inspired Energy Science (CBES), an Energy Frontier Research Center funded by the U.S. Department of Energy (DOE), Office of Science, Basic Energy Sciences (BES) under Award No. DE-SC0000989.