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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Solid-state Precipitation in Molecular Dynamics: KMC-MD Hybrid Simulations

A critical drawback of molecular dynamics (MD) simulations when modeling physical properties is the limitation to short timescales. Solid state precipitation is one behavior that is not significantly observable at timescales accessible to MD, and thus has been difficult to simulate at an MD scale. Taking inspiration from Kinetic Monte-Carlo (KMC) methods for simulating diffusion on a rigid lattice, we have developed a hybrid KMC-MD approach to enable simulation of solid-state precipitation during MD simulation implemented in LAMMPS. This method incorporates the atomic neighbor hopping behavior utilized by KMC simulations into a MD simulation with a variable local lattice configuration. By accelerating nearest-neighbor atomic hopping with this technique, solid-state precipitation can be observed at an MD timescale. Utilizing theory based on persistent-embryo methods for liquid-solid precipitation in MD we demonstrate the calculation of critical nucleus size for the gamma’ precipitation out of gamma phase in the Ni-Al system.

Molecular Dynamics↗
NASA NTRSDate not supplied

Solid-state Precipitation in Molecular Dynamics: kMC-MD Hybrid Simulations

A critical drawback of molecular dynamics (MD) simulations when modeling physical properties is the limitation to short timescales. Solid state precipitation is one behavior that is not significantly observable at timescales accessible to MD, and thus has been difficult to simulate at an MD scale. Taking inspiration from Kinetic Monte-Carlo (KMC) methods for simulating diffusion on a rigid lattice, we have developed a hybrid KMC-MD approach to enable simulation of solid-state precipitation during MD simulation implemented in LAMMPS. This method incorporates the atomic neighbor hopping behavior utilized by KMC simulations into a MD simulation with a variable local lattice configuration. By accelerating nearest-neighbor atomic hopping with this technique, solid-state precipitation can be observed at an MD timescale. Utilizing theory based on persistent-embryo methods for liquid-solid precipitation in MD we demonstrate the calculation of critical nucleus size for the gamma’ precipitation out of gamma phase in the Ni-Al system.

Molecular Dynamics↗
NASA NTRS2018

Simple Ion Channels: From Structure to Electrophysiology and Back

A reliable way to establish whether our understanding of a channel is satisfactory is to reproduce its measured ionic conductance over a broad range of applied voltages in computer simulations. In molecular dynamics (MD), this can be done by way of applying an external electric field to the system and counting the number of ions that traverse the channel per unit time. Since this approach is computationally very expensive, we have developed a markedly more efficient alternative in which MD is combined with the electrodiffusion (ED) equation. In this approach, the assumptions of the ED equation can be rigorously tested, and the precision and consistency of the calculated conductance can be determined. We have demonstrated that the full current/voltage dependence and the underlying free energy profile for a simple channel can be reliably calculated from equilibrium or non-equilibrium MD simulations at a single voltage. To carry out MD simulations, a structural model of a channel has to be assumed, which is an important constraint, considering that high-resolution structures are available for only very few simple channels. If the comparison of calculated ionic conductance with electrophysiological data is satisfactory, it greatly increases our confidence that the structure and the function are described sufficiently accurately. We examined the validity of the ED for several channels embedded in phospholipid membranes - four naturally occurring channels: trichotoxin, alamethicin, p7 from hepatitis C virus (HCV) and Vpu from the HIV-1 virus, and a synthetic, hexameric channel, formed by a 21-residue peptide that contains only leucine and serine. All these channels mediate transport of potassium and chloride ions. It was found that the ED equation is satisfactory for these systems. In some of them experimental and calculated electrophysiological properties are in good agreement, whereas in others there are strong indications that the structural models are incorrect.

molecular dynamics (MD↗
NASA NTRS2008

New Developments in the Embedded Statistical Coupling Method: Atomistic/Continuum Crack Propagation

A concurrent multiscale modeling methodology that embeds a molecular dynamics (MD) region within a finite element (FEM) domain has been enhanced. The concurrent MD-FEM coupling methodology uses statistical averaging of the deformation of the atomistic MD domain to provide interface displacement boundary conditions to the surrounding continuum FEM region, which, in turn, generates interface reaction forces that are applied as piecewise constant traction boundary conditions to the MD domain. The enhancement is based on the addition of molecular dynamics-based cohesive zone model (CZM) elements near the MD-FEM interface. The CZM elements are a continuum interpretation of the traction-displacement relationships taken from MD simulations using Cohesive Zone Volume Elements (CZVE). The addition of CZM elements to the concurrent MD-FEM analysis provides a consistent set of atomistically-based cohesive properties within the finite element region near the growing crack. Another set of CZVEs are then used to extract revised CZM relationships from the enhanced embedded statistical coupling method (ESCM) simulation of an edge crack under uniaxial loading.

Saether, E.↗
NASA NTRS2001

Molecular Dynamic Simulations of Interaction of an AFM Probe with the Surface of an SCN Sample

Molecular dynamic (MD) simulations is conducted in order to estimate forces of probe-substrate interaction in the Atomic Force Microscope (AFM). First a review of available molecular dynamic techniques is given. Implementation of MD simulation is based on an object-oriented code developed at the University of Delft. Modeling of the sample material - succinonitrile (SCN) - is based on the Lennard-Jones potentials. For the polystyrene probe an atomic interaction potential is used. Due to object-oriented structure of the code modification of an atomic interaction potential is straight forward. Calculation of melting temperature is used for validation of the code and of the interaction potentials. Various fitting parameters of the probe-substrate interaction potentials are considered, as potentials fitted to certain properties and temperature ranges may not be reliable for the others. This research provides theoretical foundation for an interpretation of actual measurements of an interaction forces using AFM.

Bune, Adris↗
NASA NTRS2001

Carbon Nanotubes in Water: MD Simulations of Internal and External Flow, Self Organization

We have developed computational tools, based on particle codes, for molecular dynamics (MD) simulation of carbon nanotubes (CNT) in aqueous environments. The interaction of CNTs with water is envisioned as a prototype for the design of engineering nano-devices, such as artificial sterocillia and molecular biosensors. Large scale simulations involving thousands of water molecules are possible due to our efficient parallel MD code that takes long range electrostatic interactions into account. Since CNTs can be considered as rolled up sheets of graphite, we expect the CNT-water interaction to be similar to the interaction of graphite with water. However, there are fundamental differences between considering graphite and CNTs, since the curvature of CNTs affects their chemical activity and also since capillary effects play an important role for both dynamic and static behaviour of materials inside CNTs. In recent studies Gordillo and Marti described the hydrogen bond structure as well as time dependent properties of water confined in CNTs. We are presenting results from the development of force fields describing the interaction of CNTs and water based on ab-initio quantum mechanical calculations. Furthermore, our results include both water flows external to CNTs and the behaviour of water nanodroplets inside heated CNTs. In the first case (external flows) the hydrophobic behaviour of CNTs is quantified and we analyze structural properties of water in the vicinity of CNTs with diagnostics such as hydrogen bond distribution, water dipole orientation and radial distribution functions. The presence of water leads to attractive forces between CNTs as a result of their hydrophobicity. Through extensive simulations we quantify these attractive forces in terms of the number and separation of the CNT. Results of our simulations involving arrays of CNTs indicate that these exhibit a hydrophobic behaviour that leads to self-organising structures capable of trapping water clusters. In the second case (internal flows) we study the behaviour of water droplets confined inside CNTs. Constant temperature simulations allow us to capture structural properties such as the contact angles and density profiles of the equilibrated drops. By heating and subsequently cooling of the CNT, we are able to measure the evaporation and the condensation rate of the entrapped water.

Jaffe, Richard L.↗
NASA NTRS2015

Free-Energy Calculations. A Mathematical Perspective

Ion channels are pore-forming assemblies of transmembrane proteins that mediate and regulate ion transport through cell walls. They are ubiquitous to all life forms. In humans and other higher organisms they play the central role in conducting nerve impulses. They are also essential to cardiac processes, muscle contraction and epithelial transport. Ion channels from lower organisms can act as toxins or antimicrobial agents, and in a number of cases are involved in infectious diseases. Because of their important and diverse biological functions they are frequent targets of drug action. Also, simple natural or synthetic channels find numerous applications in biotechnology. For these reasons, studies of ion channels are at the forefront of biophysics, structural biology and cellular biology. In the last decade, the increased availability of X-ray structures has greatly advanced our understanding of ion channels. However, their mechanism of action remains elusive. This is because, in order to assist controlled ion transport, ion channels are dynamic by nature, but X-ray crystallography captures the channel in a single, sometimes non-native state. To explain how ion channels work, X-ray structures have to be supplemented with dynamic information. In principle, molecular dynamics (MD) simulations can aid in providing this information, as this is precisely what MD has been designed to do. However, MD simulations suffer from their own problems, such as inability to access sufficiently long time scales or limited accuracy of force fields. To assess the reliability of MD simulations it is only natural to turn to the main function of channels - conducting ions - and compare calculated ionic conductance with electrophysiological data, mainly single channel recordings, obtained under similar conditions. If this comparison is satisfactory it would greatly increase our confidence that both the structures and our computational methodologies are sufficiently accurate. Channel conductance, defined as the ratio of ionic current through the channel to applied voltage, can be calculated in MD simulations by way of applying an external electric field to the system and counting the number of ions that traverse the channel per unit time. If the current is small, a voltage significantly higher than the experimental one needs to be applied to collect sufficient statistics of ion crossing events. Then, the calculated conductance has to be extrapolated to the experimental voltage using procedures of unknown accuracy. Instead, we propose an alternative approach that applies if ion transport through channels can be described with sufficient accuracy by the one-dimensional diffusion equation in the potential given by the free energy profile and applied voltage. Then, it is possible to test the assumptions of the equation, recover the full voltage/current dependence, determine the reliability of the calculated conductance and reconstruct the underlying (equilibrium) free energy profile, all from MD simulations at a single voltage. We will present the underlying theory, model calculations that test this theory and simulations on ion conductance through a channel that has been extensively studied experimentally. To our knowledge this is the first case in which the complete, experimentally measured dependence of the current on applied voltage has been reconstructed from MD simulations.

free energy↗
NASA NTRSDate not supplied

Multiscale Analysis of Thermo-Mechanical Behavior of Boron Nitride-Reinforced Epoxy Nanocomposites

The effect of size, shape, morphology, and arrangement of micro constituents of Boron Nitrite (BN) nanoplatelet/epoxy composites on their properties were investigated using a multi scale approach that includes Molecular Dynamics (MD) and micromechanics. The thermo-mechanical properties of the composites were evaluated using molecular theory and the analysis showed that the elastic constants of BN/epoxy composites were not severely affected by temperature. Also, the micromechanical analysis of Generalized Method of Cells (GMC) was utilized at higher length scale to evaluate elastic properties of the composites, for different geometries and arrangements of micro constituents. The predicted results of the analysis showed that the size, aspect ratios, morphology, and the arrangements of inclusions in BN/epoxy nanocomposites all have remarkable effect on the mechanical performances of the material systems.

nanocomposites↗
NASA NTRSDate not supplied

Fracture Prediction of Epoxy Resin using Morse Bond Potential Embedded in GAFF using Molecular Dynamics Simulations

A generic method is developed to investigate the fracture behavior of an epoxy resin using atomistic molecular (MD) dynamics simulations. The epoxy system consisted of the stoichiometric mixture of tetra-/tri-functional epoxies and di-functional hardener molecules and was cured with a step-growth crosslinking algorithm. A hybrid force field (hFF) in which Morse bond function were added in second generation-general Amber Force Field (GAFF2) was used to capture bond breaking of the crosslinked epoxy system under uniaxial deformation. The Morse bond parameters for covalent bonds in the crosslinked backbone were fit to dissociation curves computed by CASPT2/6-311+G**. After the systems in various crosslink densities were obtained and equilibrated, the full length of stress-strain (𝜎-𝜀) curve was produced including initial elastic regime, yielding, plastic flow, strain hardening, and progressive failure. We found that the hFF was effective in studying the dissociation of crosslinked polymers and understanding the failure mechanism. In the results, the hFF delivered the same elastic property obtained from the unmodified force field GAFF. The stress-strain curve, however, began to be distinct in the plastic regime due to broken covalent bonds capable of altering the tensile behavior. Once the stress reached maximum, it progressively decreased until the ultimate failure (𝜎=0). Since hFF employed the existing GAFF functions with including a minimal change of its bond potential, this approach is easier to perform and computationally more efficient for unveiling the fracture behavior of polymer materials at the molecular level than other approaches with reactive force fields. We expect this approach will be utilized to accelerate the material-by-design process for thermosets by incorporate data from molecular models.

Changwoon Jang↗
NASA NTRSDate not supplied

Computationally Guided Design of Polymer-Coated Microparticles as Reusable Materials

Long-duration space exploration missions and sustained lunar or Martian surface operations present greater demands for multifunctional and reusable materials. By scaling down the amount of material to be launched from Earth, both mission cost and risk can be reduced. In this regard, leveraging in-space manufacturing capabilities with reusable feedstock materials is an attractive option, as it will allow for articles to be generated on demand, utilized, and then recycled for additional use. NASA’s Enabling Sustained Presence Using Recyclables (ESPUR) project aims to develop reusable materials using polymer-coated microparticles that are bonded via reversible Diels-Alder reactions, where only modest heat is needed to trigger the reverse reaction and enable reuse. For proof-of-concept demonstration, research is currently focused on the fabrication of epoxy microparticles that contain a copoly(carbonate urethane) coating with maleimide and furan functionalities. Here, we discuss the integration of computational materials modeling approaches to help navigate the large design space in this development effort. We perform molecular dynamics (MD) simulations with atomistic and coarse-grained models of the copolymer, which allow us to evaluate the effects of design parameters like the molecular weight and composition on the molecular interactions and chain dynamics. We show how the properties change with the reversible bonds. We also leverage discrete element method (DEM) simulations to assess how microparticle design parameters like the size ratio and volume fraction can be tuned to increase the packing density and number of microparticle contacts to improve the mechanical properties. Our results demonstrate how computational tools can be used in close collaboration with experimental efforts to accelerate material design.

reusable materials↗
NASA NTRS2004

Stress Distribution During Deformation of Polycrystalline Aluminum by Molecular-Dynamics and Finite-Element Modeling

In this paper, a multiscale modelling strategy is used to study the effect of grain-boundary sliding on stress localization in a polycrystalline microstructure with an uneven distribution of grain size. The development of the molecular dynamics (MD) analysis used to interrogate idealized grain microstructures with various types of grain boundaries and the multiscale modelling strategies for modelling large systems of grains is discussed. Both molecular-dynamics and finite-element (FE) simulations for idealized polycrystalline models of identical geometry are presented with the purpose of demonstrating the effectiveness of the adapted finite-element method using cohesive zone models to reproduce grain-boundary sliding and its effect on the stress distribution in a polycrystalline metal. The yield properties of the grain-boundary interface, used in the FE simulations, are extracted from a MD simulation on a bicrystal. The models allow for the study of the load transfer between adjacent grains of very different size through grain-boundary sliding during deformation. A large-scale FE simulation of 100 grains of a typical microstructure is then presented to reveal that the stress distribution due to grain-boundary sliding during uniform tensile strain can lead to stress localization of two to three times the background stress, thus suggesting a significant effect on the failure properties of the metal.

Yamakov, V.↗
NASA NTRSDate not supplied

Machine-Learned Committor Functions for Reactive Molecular Dynamics

Reactive molecular dynamics (MD) is a powerful tool for atomistic-scale modeling of a diverse range of chemical processes. However, scaling these simulations to large systems and long times scales remains a challenge because of the complexity of the potential energy function required. The authors previously developed a heuristic approach, called REACTER, that incorporates reactivity in MD simulations in a less general but much more computationally efficient manner. REACTER uses standard, fixed valence force fields as the underlying potentialenergy surface for describing all interatomic interactions but adds a procedure for enforcing user-defined reactions that occur when certain geometric constraints on relative atomic positions are satisfied. Further, these bonding changes can be accepted or rejected with a probability related tothe local thermal energy. This work seeks to generalize this approach by replacing the set of user defined geometric constraints and energetic criteria with a committor function that specifies the probability of a reaction occurring on the basis of the local atomic configuration. The committor function is a useful mathematical tool for modeling rare events but, unfortunately, is very difficult to compute for realistic systems in a general way. This work describes a method for approximating the committor function using a machine learning approach, specifically a deep neural network trained with data from reactive MD and DFT-based dynamics simulations. This network is coupled to the existing REACTER protocol, as implemented in the LAMMPS MD package, and used to make on-the-fly predictions of reaction probabilities without the more extensive user input previously required. The new method is demonstrated using the polymerization of polystyrene as a case study. Although very dependent on the quality and quantity of training data, machine-learned committor functions show promise as a method for incorporating reaction probability from higher level calculations into highly scalable MD simulations.

polymer simulations↗
NASA NTRS2017

Modeling Chemical Reactions in Classical Molecular Dynamics Simulations

An algorithm capable of incorporating multi-step reaction mechanisms into atomistic molecular dynamics (MD) simulations using traditional fixed valence force fields is proposed and implemented within the framework of LAMMPS (Large-scale Atomic Molecular Massively Parallel Simulator). This extension, referred to as fix bond/react, enables bonding topology modifications during a running MD simulation using pre- and post-reaction bonding templates to carry out a pre-specified reaction. Candidate reactants are first identified by interatomic separation, followed by the application of a generalized topology matching algorithm to confirm they match the pre-reaction template. This is followed by a topology conversion to match the post-reaction template and a dynamic relaxation to minimize high energy configurations. Two case studies, the condensation polymerization of nylon 6,6 and the formation of a highly-crosslinked epoxy, are simulated to demonstrate the robustness, stability, and speed of the algorithm. Improvements which could increase its utility are discussed.

Jacob R Gissinger↗
NASA NTRS2018

Molecular Dynamics Simulations of Liquid and Polymer Electrolytes for Energy Storage Devices

Advancing beyond current lithium-ion technology is necessary in order to enable energy storage devices for electric airplanes. Electrolyte stability is a key limiting factor, yet the design of improved electrolytes remains a formidable challenge. Molecular dynamics (MD) simulations are a powerful tool for studying electrolytes, since they can be used to evaluate structural, thermodynamic, and transport properties, and can provide molecular-level detail often inaccessible to experimental techniques. Our computational materials groups at the NASA Ames Research Center has developed models and methods to accurately simulate both liquid and polymer electrolytes.We report the results from atomistic MD simulations of several electrolyte materials, with lithium salts dissolved in ionic liquids, dimethoxyethane (DME), and polyethylene oxide (PEO). For improved accuracy, we employ polarizable models, where each atom is given an environment-dependent atomic dipole. The simulations accurately predict bulk transport properties, including viscosity, diffusion, and ionic conductivity, in quantitative agreement with available experimental data. Moreover, the simulations provide important insights into the solvation structure of the lithium ions.We also report the results from coarse-grained MD simulations of polyanion electrolytes. In order to more efficiently capture the longer length- and time-scales of these systems, we employ a generic bead-spring model. These simulations provide important insight into how the polymer chain architecture and ionic interaction strengths affect the ionic aggregation behavior and cation dynamics. Despite the simplicity of the model, the simulations yield qualitative agreement with experimental data for similar systems.

Abbott, Lauren J.↗
NASA NTRS1998

Nanoscale Etching and Indentation of Silicon Surfaces with Carbon Nanotubes

The possibility of nanolithography of silicon and germanium surfaces with bare carbon nanotube tips of scanning probe microscopy devices is considered with large scale classical molecular dynamics (MD) simulations employing Tersoff's reactive many-body potential for heteroatomic C/Si/Ge system. Lithography plays a key role in semiconductor manufacturing, and it is expected that future molecular and quantum electronic devices will be fabricated with nanolithographic and nanodeposition techniques. Carbon nanotubes, rolled up sheets of graphene made of carbon, are excellent candidates for use in nanolithography because they are extremely strong along axial direction and yet extremely elastic along radial direction. In the simulations, the interaction of a carbon nanotube tip with silicon surfaces is explored in two regimes. In the first scenario, the nanotubes barely touch the surface, while in the second they are pushed into the surface to make "nano holes". The first - gentle scenario mimics the nanotube-surface chemical reaction induced by the vertical mechanical manipulation of the nanotube. The second -digging - scenario intends to study the indentation profiles. The following results are reported in the two cases. In the first regime, depending on the surface impact site, two major outcomes outcomes are the selective removal of either a single surface atom or a surface dimer off the silicon surface. In the second regime, the indentation of a silicon substrate by the nanotube is observed. Upon the nanotube withdrawal, several surface silicon atoms are adsorbed at the tip of the nanotube causing significant rearrangements of atoms comprising the surface layer of the silicon substrate. The results are explained in terms of relative strength of C-C, C-Si, and Si-Si bonds. The proposed method is very robust and does not require applied voltage between the nanotube tips and the surface. The implications of the reported controllable etching and hole-creating for nanolithography on silicon are discussed in detail.

Dzegilenko, Fedor N.↗
NASA NTRSDate not supplied

Semi-Empirical Interatomic Potential for Large-Scale Molecular Dynamics Simulation of Metal-Oxide Systems

Classical molecular dynamics (MD) simulation can be applied to systems containing billions of atoms during times up to microseconds. However, utilization of a large-scale MD simulation requires reliable but computationally cheap interatomic potentials. In the case of metallic systems, embedded atom method (EAM) and Finnis-Sinclair (FS) potentials are the reasonable choices, but their development for multicomponent alloys is a challenge. Addition of oxygen atoms makes the problem of developing semi-empirical potentials even more difficult because the long-range Coulomb interaction cannot be neglected, and different atoms have different charges which vary during MD relaxation such that a charge equilibration procedure should be applied every MD step. As results researchers tend to avoid simulating metal-oxide systems. In this talk, a new Finnis-Sinclair (FS) Ni-Co-Cr potential will be presented. Special attention will be paid to reproducing of the element melting temperatures and clustering. Next, a charge transfer ionic potential (CTIP) developed to simulate the NiO properties will be presented. This potential utilizes the Ni FS potential and accounts for the Coulomb interaction in the vicinity of oxygen atoms. Fitting of the CTIP parameters and FS potential functions describing the interaction with oxygen atoms to the available experimental and ab initio data will be discussed. Results of MD simulation of interaction of NiO particles with dislocations in Ni will be shown.

molecular dynamics simulation↗
NASA NTRS1987

Direct simulation of high-vorticity gas flows

The computational limitations associated with the molecular dynamics (MD) method and the direct simulation Monte Carlo (DSMC) method are reviewed in the context of the computation of dilute gas flows with high vorticity. It is concluded that the MD method is generally limited to the dense gas case in which the molecular diameter is one-tenth or more of the mean free path. It is shown that the cell size in DSMC calculations should be small in comparison with the mean free path, and that this may be facilitated by a new subcell procedure for the selection of collision partners.

Bird, G. A.↗