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Algorithm simulates three-dimensional hypersonic flow of air or another mixture of gases around blunt body. Accounts for nonequilibrium thermochemical effects via two-temperature mathematical model of molecular excitations and equations for finite-rate chemical reactions. These equations fully coupled to fluid dynamical equations.
Ultra high temperature ceramics (UHTC) including ZrB2 and HfB2 have a number of properties that make them attractive for applications in extreme environments. One such property is their high thermal conductivity. Computational modeling of these materials will facilitate understanding of fundamental mechanisms, elucidate structure-property relationships, and ultimately accelerate the materials design cycle. Progress in computational modeling of UHTCs however has been limited in part due to the absence of suitable interatomic potentials. Recently, we developed Tersoff style parameterizations of such potentials for both ZrB2 and HfB2 appropriate for atomistic simulations. As an application, Green-Kubo molecular dynamics simulations were performed to evaluate the lattice thermal conductivity for single crystals of ZrB2 and HfB2. The atomic mass difference in these binary compounds leads to oscillations in the time correlation function of the heat current, in contrast to the more typical monotonic decay seen in monoatomic materials such as Silicon, for example. Results at room temperature and at elevated temperatures will be reported.
Ultra high temperature ceramics (UHTC) including ZrB2 and HfB2 have a number of properties that make them attractive for applications in extreme environments. One such property is their high thermal conductivity. Computational modeling of these materials will facilitate understanding of fundamental mechanisms, elucidate structure-property relationships, and ultimately accelerate the materials design cycle. Progress in computational modeling of UHTCs however has been limited in part due to the absence of suitable interatomic potentials. Recently, we developed Tersoff style parameterizations of such potentials for both ZrB2 and HfB2 appropriate for atomistic simulations. As an application, Green-Kubo molecular dynamics simulations were performed to evaluate the lattice thermal conductivity for single crystals of ZrB2 and HfB2. The atomic mass difference in these binary compounds leads to oscillations in the time correlation function of the heat current, in contrast to the more typical monotonic decay seen in monoatomic materials such as Silicon, for example. Results at room temperature and at elevated temperatures will be reported.
The dynamics and structure of the crystal melt interface are of great importance in crystal growth, melting, and other properties of the solid-liquid interface. The Embedded Atom Method (EAM), a semiempirical method developed by Daw and Baskes for determining the energetics of atoms in a bulk environment, is a useful method in the computer simulation. The EAM functions of PB in conjunction with the MD code are employed to study melting and disordering of the Pb(100) surface. The EAM functions are fitted to the bulk experimental data at zero temperature, and it is not clear if it will behave correctly at higher temperatures. In fact, it is shown that use of a similar type of potential at higher temperatures might result in a negative coefficient of thermal expansion. The primary purpose here is to perform MD simulation combined with the EAM functions of PB to study melting of the Pb(100) surface. This provides an accurate test of the EAM functions at higher temperatures. In particular, we calculate the two dimensional structure factor, the two dimensional distribution function, and density profile as a function of temperature up to the melting point of lead.
Nanomechanics of individual carbon and boron-nitride nanotubes and their application as reinforcing fibers in polymer composites has been reviewed with interplay of theoretical modeling, computer simulations and experimental observations. The emphasis in this work is on elucidating the multi-length scales of the problems involved, and of different simulation techniques that are needed to address specific characteristics of individual nanotubes and nanotube polymer-matrix interfaces. Classical molecular dynamics simulations are shown to be sufficient to describe the generic behavior such as strength and stiffness modulus but are inadequate to describe elastic limit and nature of plastic buckling at large strength. Quantum molecular dynamics simulations are shown to bring out explicit atomic nature dependent behavior of these nanoscale materials objects that are not accessible either via continuum mechanics based descriptions or through classical molecular dynamics based simulations. As examples, we discus local plastic collapse of carbon nanotubes under axial compression and anisotropic plastic buckling of boron-nitride nanotubes. Dependence of the yield strain on the strain rate is addressed through temperature dependent simulations, a transition-state-theory based model of the strain as a function of strain rate and simulation temperature is presented, and in all cases extensive comparisons are made with experimental observations. Mechanical properties of nanotube-polymer composite materials are simulated with diverse nanotube-polymer interface structures (with van der Waals interaction). The atomistic mechanisms of the interface toughening for optimal load transfer through recycling, high-thermal expansion and diffusion coefficient composite formation above glass transition temperature, and enhancement of Young's modulus on addition of nanotubes to polymer are discussed and compared with experimental observations.
In this review we summarize recent progress in our understanding of the structure of aqueous interfaces emerging from molecular level computer simulations. It is emphasized that the presence of the interface induces specific structural effects which, in turn, influence a wide variety of phenomena occurring near the phase boundaries. At the liquid-vapor interface, the most probable orientations of a water molecule is such that its dipole moment lies parallel to the interface, one O-H bond points toward the vapor and the other O-H bond is directed toward the liquid. The orientational distributions are broad and slightly asymmetric, resulting in an excess dipole moment pointing toward the liquid. These structural preferences persist at interfaces between water and nonpolar liquids, indicating that the interactions between the two liquids in contact are weak. It was found that liquid-liquid interfaces are locally sharp but broadened by capillary waves. One consequence of anisotropic orientations of interfacial water molecules is asymmetric interactions, with respect to the sign of the charge, of ions with the water surface. It was found that even very close to the surface ions retain their hydration shells. New features of aqueous interfaces have been revealed in studies of water-membrane and water-monolayer systems. In particular, water molecules are strongly oriented by the polar head groups of the amphiphilic phase, and they penetrate the hydrophilic head-group region, but not the hydrophobic core. At infinite dilution near interfaces, amphiphilic molecules exhibit behavior different from that in the gas phase or in bulk water. This result sheds new light on the nature of hydrophobic effect in the interfacial regions. The presence of interfaces was also shown to affect both equilibrium and dynamic components of rates of chemical reactions. Applications of continuum models to interfacial problems have been, so far, unsuccessful. This, again, underscores the importance of molecular-level information about interfaces.
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.
The James Webb Space Telescope (JWST) launched from the Centre Spatial Guyanais (CSG) in December 2021. JWST’s requirements permitted processing in International Organization for Standardization (ISO) Class 7 or better facilities, but CSG was only equipped with ISO Class 8 facilities. To temporarily upgrade the air cleanliness in the Payload Processing Facility, Fueling Hall, and Final Assembly Building Encapsulation Hall, NASA provided two portable High Efficiency Particulate Air (HEPA) and carbon filter walls that were used in each location. The walls were comprised of stacks of two modules high and arranged in push-push configurations as shown to be most effective via Computational Fluid Dynamics simulations of expected floor layouts in each facility. After delivery to NASA’s Goddard Space Flight Center in 2020, the walls underwent initial verification measurements inside a cleanroom and validation testing in an uncontrolled area to quantify their improvement of air cleanliness and particle and molecular fallout. Validation testing showed improvements of 83-99% for airborne particle counts, 79-91% for particle fallout, and 50-90% for molecular fallout. The particle improvements were applied to the contamination budget analysis that tracked current and predicted future cleanliness against End-of-Life requirements for JWST’s critical surfaces. At CSG, the walls successfully maintained an ISO Class 7 environment or better within their envelope in each location, despite their presence in ISO Class 8 facilities with dense integration operations.
The James Webb Space Telescope (JWST) launched from the Centre Spatial Guyanais (CSG) in December 2021. JWST’s requirements permitted processing in International Organization for Standardization (ISO) Class 7 or better facilities, but CSG was only equipped with ISO Class 8 facilities. To temporarily upgrade the air cleanliness in the Payload Processing Facility, Fueling Hall, and Final Assembly Building Encapsulation Hall, NASA provided two portable High Efficiency Particulate Air (HEPA) and carbon filter walls that were used in each location. The walls were comprised of stacks of two modules high and arranged in push-push configurations as shown to be most effective via Computational Fluid Dynamics simulations of expected floor layouts in each facility. After delivery to NASA’s Goddard Space Flight Center in 2020, the walls underwent initial verification measurements inside a cleanroom and validation testing in an uncontrolled area to quantify their improvement of air cleanliness and particle and molecular fallout. Validation testing showed improvements of 83-99% for airborne particle counts, 79-91% for particle fallout, and 50-90% for molecular fallout. The particle improvements were applied to the contamination budget analysis that tracked current and predicted future cleanliness against End-of-Life requirements for JWST’s critical surfaces. At CSG, the walls successfully maintained an ISO Class 7 environment or better within their envelope in each location, despite their presence in ISO Class 8 facilities with dense integration operations.
A spectral model with spherical harmonics and Fourier components that can simulate atmospheric perturbations in the global geometry of a multiconstituent atmosphere is presented. The boundaries are the planetary surface where the transport velocities vanish and the exobase where molecular heat conduction and viscosity dominate. The time consuming integration of the conservation equations is reduced to computing the transfer function (TF) which describes the dynamic properties of the medium divorced from the complexities in the temporal and horizontal variations of the excitation source. Given the TF, the atmospheric response to a chosen source distribution is then obtained in short order. Theoretical studies are presented to illuminate some properties of gravity waves on earth, Venus and Mars.
One of the main goals of astrobiology is to understand the origin of cellular life. The most direct approach to this problem is to construct laboratory models of protocells. Such efforts, currently underway in the NASA Astrobiology Program, are accompanied by computational studies aimed at explaining self-organization of simple molecules into ordered structures that are capable of performing protocellular functions. Many of these functions, such as importing nutrients, capturing energy and responding to changes in the environment, are carried out by proteins bound to membranes. We use computer simulations to address the following questions about these proteins: (1) How do small proteins self-organize into ordered structures at water-membrane interfaces and insert into membranes? (2) How do peptides form membrane-spanning structures (e.g. channels)? (3) By what mechanisms do such structures perform their functions? The simulations are performed using the molecular dynamics method. In this method, Newton's equations of motion for each atom in the system are solved iteratively. At each time step, the forces exerted on each atom by the remaining atoms are evaluated by dividing them into two parts. Short-range forces are calculated in real space while long-range forces are evaluated in reciprocal space, using a particle-mesh algorithm which is of order O(NInN). With a time step of 2 femtoseconds, problems occurring on multi-nanosecond time scales (10(exp 6)-10(exp 8) time steps) are accessible. To address a broader range of problems, simulations need to be extended by three orders of magnitude, which requires algorithmic improvements and codes scalable to a large number of processors. Work in this direction is in progress. Two series of simulations are discussed. In one series, it is shown that nonpolar peptides, disordered in water, translocate to the nonpolar interior of the membrane and fold into helical structures (see Figure). Once in the membrane, the peptides exhibit orientational flexibility with changing conditions, which may have provided a mechanism of transmitting signals between the protocell and its environment. In another series of simulations, the mechanism by which a simple protein channel efficiently mediates proton transport across membranes was investigated. This process is a key step in cellular bioenergetics. In the channel under study, proton transport is gated by four histidines that occlude the channel pore. The simulations identify the mechanisms by which protons move through the gate.
NASA’s approach to computational materials modeling is detailed in the NASA Vision 2040 Roadmap for Multiscale Modeling and Simulation of Materials and Systems. This report is in the spirit of national initiatives such as the Material Genome Initiative (MGI), Integrated Computational Materials Engineering (ICME), and others. We utilize a combination of fundamental modeling, computational high-throughput screening, and data science methods, e.g., machine learning, are used to find innovative solutions to NASA or national technology challenges. Applications of interest are wide ranging from advanced alloys to batteries to coatings, among others. In this talk, we present three examples for recent work related to NASA applications. First, doping advanced sulfur battery cathodes with selenium boosts electrical conductivity important for electric aircraft applications. First principles calculations will be discussed that result in compositional design maps for these materials. Second, development of icephobic coatings is important to mitigate safety hazards associated with icing for aircraft. Molecular dynamics simulations are reported for ice-surface interfaces to understand adhesion mechanisms and help screen optimal ice-phobic coatings. Third, shape memory alloys have numerous applications as actuators, superelastic materials, etc. for aerospace. We report machine learning models that predict martensitic transition temperatures across a broad swath of compositional space.
One of the main goals of astrobiology is to understand the origin of cellular life. In the absence of any record of the earliest ancestors of contemporary cells, protocells, the most direct way to test our understanding of their characteristics is to construct laboratory models of protocells. Such efforts, currently underway in the NASA Astrobiology Program, are accompanied by computational studies aimed at explaining self-organization of simple molecules into ordered structures and developing designs of molecules that are capable of performing protocellular functions. Many of these functions, such as importing nutrients, capturing and storing energy, and responding to changes in the environment, are carried out by proteins bound to membranes. We use computer simulations to address the following, questions about these proteins: (1) How do small proteins (peptides) organize themselves into ordered structures at water-membrane interfaces and insert into membranes? (2) How do peptides aggregate to form membrane-spannin(y structures (e.g., channels)? (3) By what mechanisms do such aggregates perform their functions? The simulations are performed using the molecular dynamics (MD) method. In this method, Newton's equations of motion for each atom in the system are solved iteratively. At each time step, the forces exerted on each atom by the remaining atoms are evaluated by dividing them into two parts. Short-range forces are calculated directly in real space while long-range forces are evaluated in reciprocal space, usually using a particle-mesh algorithm which is of order O(NlnN). Currently, a time step of 2 femtoseconds is typically used, thereby making studies of problems occurring on multi-nanosecond time scales (10(exp 6) - 10(exp 8) time steps) accessible. To address a broader range of problems, simulations need to be extended by three orders of magnitude. Such an extension requires both algorithmic improvements and codes scalable to a large number of parallel processors. Work in this direction is in progress. Two specific series of simulations that demonstrate how peptides self-organize and function in membranes are discussed. In one series of simulations, it was shown that nonpolar peptides, disordered in water, translocate to the nonpolar interior of the membrane and, simultaneously, fold into two different helical structures, which remain in equilibrium. Once in the membrane, the peptides can readily change their orientation, especially in response to local electric fields. This structural and orientational flexibility of peptides with changing conditions may have provided a mechanism of transmitting signals between the environment and the interior of the protocell. In another series of simulations, the mechanism by which a simple protein channel efficiently mediates proton transport across membranes was investigated. This process is a key step in cellular bioenergetics. In the channel under study, proton transport is gated by four histidines that occlude the channel pore. The simulations demonstrate that protons move through the gate by a "shuttle" mechanism, wherein one histidine is protonated on the extracellular side and, subsequently, the proton bound on the opposite side is released.
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.
In nature, anti-freeze proteins present in fish utilize specific organic functionalities to disrupt ice crystal formation and propagation. Based on these structures, surfaces with controlled chemical functionality and chain length were evaluated both experimentally and computationally to assess the effect of both parameters in mitigating ice formation. Linear aliphatic dimethylethoxysilanes terminated with methyl or hydroxyl groups were prepared, characterized, and used to coat aluminum. The effect upon icing using a microdroplet freezing apparatus and the Adverse Environment Rotor Test Stand found hydroxyl-terminated materials exhibited a greater propensity for ice formation and adhesion. Molecular dynamics simulations of a silica substrate bearing functionalized species of similar composition were brought into contact with a pre-equilibrated ice crystal. Several parameters including chain mobility were monitored to ascertain the size of a quasi-liquid layer. The studies suggested that chain mobility affected the interface between ice and the surface more than terminal group chemical composition.
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.
Transmembrane ion channels mediate a number of essential physiological processes in a cell ranging from regulating osmotic pressure to transmission of neural signals. Kinetics and selectivity of ion transport is of critical importance to a cell and, not surprisingly, it is a subject of numerous experimental and theoretical studies. In this presentation we will analyze in detail computer simulations of two simple channels from fungi - antiamoebin and trichotoxin. Each of these channels is made of an alpha-helical bundle of small, nongenomically synthesized peptides containing a number of rare amino acids and exhibits strong antimicrobial activity. We will focus on calculating ionic conductance defined as the ratio of ionic current through the channel to applied voltage. From molecular dynamics simulations, conductance can be calculated in at least two ways, each involving different approximations. Specifically, the current, given as the number of charges transferred through the channel per unit of time, can be obtained from the number of events in which ions cross the channel during the simulation. This method works well for large currents (high conductance values and/or applied voltages). If the number of crossing events is small, reliable estimates of current are difficult to achieve. Alternatively, conductance can be estimated assuming that ion transport can be well approximated as diffusion in the external potential given by the free energy profile. Then, the current can be calculated by solving the one-dimensional diffusion equation in this external potential and applied voltage (the generalized Nernst-Planck equation). To do so three ingredients are needed: the free energy profile, the position-dependent diffusion coefficient and the diffusive flux of ions into the channel. All these quantities can be obtained from molecular dynamics simulations. An important advantage of this method is that it can be used equally well to estimating large and small currents. In addition, once the free energy profile becomes available the full current-voltage dependence can be readily obtained. For both channels we carried out calculations using both approaches. We also tested the main assumptions underlying the diffusive model, such as uncorrelated nature of individual crossing events and Fickian diffusion. The accuracy and consistency of different methods will be discussed. Finally we will discuss how comparisons between calculated and measured ionic conductance and selectivity of transport can be used for determining structural models of the channels.
The Ku70/80 heterodimer is the first repair protein in the initial binding of double-strand break (DSB) ends following DNA damage, and is a component of nonhomologous end joining repair, the primary pathway for DSB repair in mammalian cells. In this study we constructed a full-length human Ku70 structure based on its crystal structure, and performed 20 ns conventional molecular dynamic (CMD) simulations on this protein and several other complexes with short DNA duplexes of different sequences. The trajectories of these simulations indicated that, without the topological support of Ku80, the residues in the bridge and C-terminal arm of Ku70 are more flexible than other experimentally identified domains. We studied the two missing loops in the crystal structure and predicted that they are also very flexible. Simulations revealed that they make an important contribution to the Ku70 interaction with DNA. Dislocation of the previously studied SAP domain was observed in several systems, implying its role in DNA binding. Targeted molecular dynamic (TMD) simulation was also performed for one system with a far-away 14bp DNA duplex. The TMD trajectory and energetic analysis disclosed detailed interactions of the DNA-binding residues during the DNA dislocation, and revealed a possible conformational transition for a DSB end when encountering Ku70 in solution. Compared to experimentally based analysis, this study identified more detailed interactions between DNA and Ku70. Free energy analysis indicated Ku70 alone is able to bind DNA with relatively high affinity, with consistent contributions from various domains of Ku70 in different systems. The functional implications of these domains in the processes of Ku heterodimerization and DNA damage recognition and repair can be characterized in detail based upon this analysis.