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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Molecular dynamics simulations of concentration-dependent defect production in Fe-Cr and Fe-Cu alloys

Molecular dynamics simulations are conducted to study the effects of alloying elements on the primary damage behaviors in three Fe-based ferritic alloy systems: (1) a Fe-Cr system in which the heat of mixing changes its sign with the Cr concentration; (2) a Fe-Cu system that has a positive heat of mixing; and (3) an ideal but artificial Fe-Cr system that has a zero heat of mixing, which is used as a reference system to investigate solute interstitial formation based on probability. It is found that in these alloys, the solute type and concentration do not have a significant effect on the total number of surviving Frenkel pairs. However, the fraction of solute interstitials has distinct behaviors. In Fe-Cr, the Cr interstitial fraction is much higher than the Cr solute concentration and the Cr interstitial production efficiency decreases with the increasing Cr concentration. By contrast, in Fe-Cu, Cu interstitials are barely produced. In the ideal alloy, the solute interstitial fraction is close to the solute concentration. The defect formation energies in both dilute and concentrated alloys, interstitial binding energies, liquid diffusivities of Fe and solute atoms, and heat of mixing have been calculated for both Fe-Cr and Fe-Cu alloys. Among them, we find that the relative thermodynamic stability between Fe self-interstitials and solute interstitials plays the most important role in the solute interstitial production behaviors. The decrease of Cr interstitial production efficiency with increasing Cr concentration can be explained by the probability distribution functions of solute interstitial formation energy in concentrated alloys.

Zhang, Yaxuan↗
DOE OSTI2017

Thermal Hydraulic Computational Fluid Dynamics Simulations and Experimental Investigation of Deformed Fuel Assemblies

The project, Toward a Longer Life Core: Thermal Hydraulic CFD Simulations and Experimental Investigation of Deformed Fuel Assemblies, DOE Project code DE-NE0008321, was a verification and validation project for flow and heat transfer through wire wrapped simulated liquid metal fuel assemblies that included both experiments and computational fluid dynamics simulations of those experiments. This project was a two year collaboration between AREVA, TerraPower, Argonne National Laboratory and Texas A&M University. Experiments were performed by AREVA and Texas A&M University. Numerical simulations of these experiments were performed by TerraPower and Argonne National Lab. Project management was performed by AREVA Federal Services. The first of a kind project resulted in the production of both local point temperature measurements and local flow mixing experiment data paired with numerical simulation benchmarking of the experiments. The project experiments included the largest wire-wrapped pin assembly Mass Index of Refraction (MIR) experiment in the world, the first known wire-wrapped assembly experiment with deformed duct geometries and the largest numerical simulations ever produced for wire-wrapped bundles.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Combining Reactive Quantum-Mechanical Molecular-Dynamics Simulations with Mutagenesis, Crystallography, and Enzyme Kinetics to Reveal Plausible Steps of Isocyanide Hydratase Catalysis

A complete understanding of enzyme mechanisms requires atomistic details of chemical reactions. Quantum-based molecular dynamics simulations (QMD) are a potential source of this information, but trade-offs between accuracy and computational cost have limited their use. We previously developed extended Lagrangian Born–Oppenheimer molecular dynamics (XL-BOMD) methods that leverage a negligible compromise in accuracy to substantially decrease the cost of QMD simulations. Here, we develop a reactive QMD approach using the latest XL-BOMD formulation, which enables efficient simulations of highly reactive systems, and use it to investigate mechanisms of intermediate formation in isocyanide hydratase (ICH) catalysis. In QMD simulations, molecular analogs of ICH active site residues reacted with para-nitrophenyl isocyanide, forming a thioimidate. Analysis of simulated atomic configurational and charge dynamics revealed a pathway where protonation of the isocyanide carbon occurs prior to thioimidate formation and suggested a possible role of Asp17 as a proton donor in the early phase of ICH catalysis. To test whether the pathway seen using the reactive QMD approach might be relevant to ICH catalysis, we performed X-ray crystallography and pre-steady-state enzyme kinetics studies of wild-type and D17N mutant ICH. Both the structure and kinetics are sensitive to the D17N mutation in a manner that is consistent with the order of the reaction steps seen in the simulations. Mobile protons play essential roles in many enzymes, yet they are difficult to observe experimentally, making the ordering of proton-dependent steps ambiguous in many enzyme mechanisms. The ability to directly simulate model reactions for the design of experiments that provide information about enzyme mechanisms involving mobile protons demonstrates the significance of our reactive QMD approach and motivates further biological applications.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Internal protein motions in molecular-dynamics simulations of Bragg and diffuse X-ray scattering

Molecular-dynamics (MD) simulations of Bragg and diffuse X-ray scattering provide a means of obtaining experimentally validated models of protein conformational ensembles. This paper shows that compared with a single periodic unit-cell model, the accuracy of simulating diffuse scattering is increased when the crystal is modeled as a periodic supercell consisting of a 2 × 2 × 2 layout of eight unit cells. The MD simulations capture the general dependence of correlations on the separation of atoms. There is substantial agreement between the simulated Bragg reflections and the crystal structure; there are local deviations, however, indicating both the limitation of using a single structure to model disordered regions of the protein and local deviations of the average structure away from the crystal structure. Although it was anticipated that a simulation of longer duration might be required to achieve maximal agreement of the diffuse scattering calculation with the data using the supercell model, only a microsecond is required, the same as for the unit cell. Rigid protein motions only account for a minority fraction of the variation in atom positions from the simulation. The results indicate that protein crystal dynamics may be dominated by internal motions rather than packing interactions, and that MD simulations can be combined with Bragg and diffuse X-ray scattering to model the protein conformational ensemble.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Molecular Dynamics Simulations of Complexation of Am(III) with a Preorganized Dicationic Ligand in an Ionic Liquid

Preorganized ligands with imidazolium arms have been found to be highly selective in extracting Am(III) into ionic liquids (ILs), but the detailed structure and mechanism of the complexation process in the ionic solvation environment are unclear. Here, we carry out molecular dynamics simulation of the complexation of Am(III) with a preorganized 1,10-phenanthroline-2,9-dicarboxamide complexant (L) functionalized with alkyl chains and imidazolium cations in the butylmethylimidazolium bistriflimide ([BMIM][NTf 2 ]) IL. Both Am:L (1:1) and Am:L 2 (1:2) complexes are examined. In the absence of the ligand, Am(III) is found to be coordinated by six NTf 2 anions via nine O donors in the first solvation shell. In the Am:L complex, Am(III) is coordinated to the ligand via two O donors and four NTf 2 anions via seven O donors in the first coordination shell. In the Am:L 2 complex, Am(III) is coordinated to the two ligands via four O donors and four NTf 2 anions via five O donors. The imidazolium arms of the ligands play an important role in the secondary solvation environment by attracting NTf 2 anions closer to the metal center. As a result, we find that the binding free energy for the second L 2+ ligand is twice that for the first L 2+ ligand, making the Am:L 2 complex significantly more stable than the Am:L complex. This study highlights the multiple factors and tunability in using preorganized ligands with charged functional groups in an ionic solvation environment, which could hold the key to achieving desired selectivity in ion extraction efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Conformational sampling enhancement of replica exchange molecular dynamics simulations using swarm particle intelligence

In this paper, we present a new method based on swarm particle social intelligence for use in replica exchange molecular dynamics simulations. In this method, the replicas (representing the different system configurations) are allowed communicating with each other through the individual and social knowledge, in additional to considering them as a collection of real particles interacting through the Newtonian forces. The new method is based on the modification of the equations of motion in such way that the replicas are driven towards the global energy minimum. The method was tested for the Lennard-Jones clusters of N = 4, 5, and 6 atoms. Our results showed that the new method is more efficient than the conventional replica exchange method under the same practical conditions. In particular, the new method performed better on optimizing the distribution of the replicas among the thermostats with time and, in addition, ergodic convergence is observed to be faster. We also introduce a weighted histogram analysis method allowing analyzing the data from simulations by combining data from all of the replicas and rigorously removing the inserted bias.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Dynamics of the EAG1 K{sup +} channel selectivity filter assessed by molecular dynamics simulations

EAG1 channels belong to the KCNH family of voltage gated potassium channels. They are expressed in several brain regions and increased expression is linked to certain cancer types. Recent cryo-EM structure determination finally revealed the structure of these channels in atomic detail, allowing computational investigations. In this study, we performed molecular dynamics simulations to investigate the ion binding sites and the dynamical behavior of the selectivity filter. Our simulations suggest that sites S2 and S4 form stable ion binding sites, while ions placed at sites S1 and S3 rapidly switched to sites S2 and S4. Further, ions tended to dissociate away from S0 within less than 20 ns, due to increased filter flexibility. This was followed by water influx from the extracellular side, leading to a widening of the filter in this region, and likely non-conductive filter configurations. Simulations with the inactivation-enhancing mutant Y464A or Na{sup +} ions lead to trapped water molecules behind the SF, suggesting that these simulations captured early conformational changes linked to C-type inactivation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Stochastic symplectic reduced-order modeling for model-form uncertainty quantification in molecular dynamics simulations in various statistical ensembles

Here, this work focuses on the representation of model-form uncertainties in molecular dynamics simulations in various statistical ensembles. In prior contributions, the modeling of such uncertainties was formalized and applied to quantify the impact of, and the error generated by, pair-potential selection in the microcanonical ensemble (NVE). In this work, we extend this formulation and present a linear-subspace reduced-order model for the canonical (NVT) and isobaric (NPT) ensembles. The symplectic reduced-order basis is randomized on the tangent space of the Stiefel manifold to provide topological relationships and capture model-form uncertainty. Using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS), we assess the relevance of these stochastic reduced-order atomistic models on canonical problems involving a Lennard-Jones fluid and an argon crystal melt.

42 ENGINEERING↗
DOE OSTI2015

Water contact angles on quartz surfaces under supercritical CO 2 sequestration conditions: Experimental and molecular dynamics simulation studies

The ambiguity of contact angle experimental measurements due to surface chemistry changes resulted from sample contamination and/or the degrees of reaction with supercritical CO 2 has resulted in great difficulties to precisely understand the wetting behavior of CO 2 under the geological carbon sequestration (GCS) conditions. Water contact angles on quartz surface under GCS conditions were investigated through the combined experimental and molecular dynamics simulation (MDS) methods. The experimental results show that water contact angles increases as ionic strength increases. The effects of pressure and temperature are very weak. The dependence of ionic strength, pressure and temperature is same for monovalent and divalent ions solutions. In the MDS, a hydroxylated quartz surface was used as the base point. A good agreement between the MDS and experimental results were obtained. Using the MDS method, a clean mineral surface with a desired surface chemistry can be constructed, which is difficult in experiments. So by comparing MDS and experimental results, the mechanisms of the reservoir wettability can be better understood. Further investigation can be made on quartz surface with different functional groups to better understand wettability alteration caused by contamination and/or CO 2 reaction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data from "Deep Potential Molecular Dynamics Simulations of Low-Temperature Plasma-Surface Interactions"

Data and input files related to the paper "Deep Potential Molecular Dynamics Simulations of Low-Temperature Plasma-Surface Interactions" (https://doi.org/10.1116/6.0004027). This includes the final DP model used in all simulations, training data set, example input files to run DeepMD (with LAMMPS), and data tables summarizing the results obtained from the simulations.

machine learning models↗
DOE OSTI2017

Solvation and Dynamics of Sodium and Potassium in Ethylene Carbonate from ab Initio Molecular Dynamics Simulations

The development of sodium and potassium batteries offers a promising way to meet the scaling and cost challenges of energy storage. However, compared to Li + , several intrinsic properties of Na + and K + , including their solvation and dynamics in typical organic electrolytes utilized in battery applications, are less well-understood. Here in this paper, we report a systematic investigation of Na + and K + in ethylene carbonate (EC) using first-principles molecular dynamics simulations. Our simulations reveal significant differences in the solvation structure and dynamical properties of Na + and K + compared to Li + . We find that, in contrast to Li + which exhibits a well-defined first solvation shell, the larger Na+ and K+ ions show more disordered and flexible solvation structures. These differences in solvation were found to significantly influence the ion dynamics, leading to larger diffusion coefficients of Na + and K + compared to Li + . Our simulations also reveal a clear and interesting analog in the behavior of the ions in EC and aqueous environments, particularly in the specific ion effects on the solvent dynamics. Lastly, this work provides fundamental understanding of the intrinsic properties of Na + and K + in organic electrolytes, which may ultimately influence the intercalation mechanism at the electrode–electrolyte interface and therefore battery performance, lifetime, and safety.

25 ENERGY STORAGE↗
DOE OSTI2015

Parametrizing linear generalized Langevin dynamics from explicit molecular dynamics simulations

Fundamental understanding of complex dynamics in many-particle systems on the atomistic level is of utmost importance. Often the systems of interest are of macroscopic size but can be partitioned into a few important degrees of freedom which are treated most accurately and others which constitute a thermal bath. Particular attention in this respect attracts the linear generalized Langevin equation, which can be rigorously derived by means of a linear projection technique. Within this framework, a complicated interaction with the bath can be reduced to a single memory kernel. This memory kernel in turn is parametrized for a particular system studied, usually by means of time-domain methods based on explicit molecular dynamics data. Here, we discuss that this task is more naturally achieved in frequency domain and develop a Fourier-based parametrization method that outperforms its time-domain analogues. Very surprisingly, the widely used rigid bond method turns out to be inappropriate in general. Importantly, we show that the rigid bond approach leads to a systematic overestimation of relaxation times, unless the system under study consists of a harmonic bath bi-linearly coupled to the relevant degrees of freedom.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Emulation of dynamic simulators with application to hydrology

Many simulation-intensive tasks in the applied sciences, such as sensitivity analysis, parameter inference or real time control, are hampered by slow simulators. Emulators provide the opportunity of speeding up simulations at the cost of introducing some inaccuracy. An emulator is a fast approximation to a simulator that interpolates between design input–output pairs of the simulator. Increasing the number of design data sets is a computationally demanding way of improving the accuracy of emulation. We investigate the complementary approach of increasing emulation accuracy by including knowledge about the mechanisms of the simulator into the formulation of the emulator. To approximately reproduce the output of dynamic simulators, we consider emulators that are based on a system of linear, ordinary or partial stochastic differential equations with a noise term formulated as a Gaussian process of the parameters to be emulated. This stochastic model is then conditioned to the design data so that it mimics the behavior of the nonlinear simulator as a function of the parameters. The drift terms of the linear model are designed to provide a simplified description of the simulator as a function of its key parameters so that the required corrections by the conditioned Gaussian process noise are as small as possible. The goal of this paper is to compare the gain in accuracy of these emulators by enlarging the design data set and by varying the degree of simplification of the linear model. We apply this framework to a simulator for the shallow water equations in a channel and compare emulation accuracy for emulators based on different spatial discretization levels of the channel and for a standard non-mechanistic emulator. Our results indicate that we have a large gain in accuracy already when using the simplest mechanistic description by a single linear reservoir to formulate the drift term of the linear model. Adding some more reservoirs does not lead to a significant improvement in accuracy. However, the transition to a spatially continuous linear model leads again to a similarly large gain in accuracy as the transition from the non-mechanistic emulator to that based on one reservoir.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Dissipative particle dynamics simulation of dilute polymer solutions—Inertial effects and hydrodynamic interactions

We examine the accuracy of dissipative particle dynamics (DPD) simulations of polymers in dilute solutions with hydrodynamic interaction (HI), at the theta point, modeled by setting the DPD conservative interaction between beads to zero. We compare the first normal-mode relaxation time extracted from the DPD simulations with theoretical predictions from a normal-mode analysis for theta chains. We characterize the influence of bead inertia within the coil by a ratio L{sub m}/R{sub g}, where L{sub m} is the ballistic distance over which bead inertia is lost, and R{sub g} is the radius of gyration of the polymer coil, while the HI strength per bead h* is determined by the ratio of bead hydrodynamic radius (r{sub H}) to the equilibrium spring length. We show how to adjust h* through the spring length and monomer mass, and how to optimize the accuracy of DPD for fixed h* by increasing the friction coefficient (γ ≥ 9) and by incorporating a nonlinear distance dependence into the frictional interaction. Even with this optimization, DPD simulations exhibit deviations of over 20% from the theoretical normal-mode predictions for high HI strength with h* ≥ 0.20, for chains with as many as 100 beads, which is a larger deviation than is found for Stochastic rotation dynamics simulations for similar chains lengths and values of h*.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Constant-potential molecular dynamics simulations of molten salt double layers for FLiBe and FLiNaK

We report the results of constant-potential molecular dynamics simulations of the double layer interface between molten 2LiF–BeF 2 (FLiBe) and 23LiF–6NaF–21KF (FLiNaK) fluoride mixtures and idealized solid electrodes. Employing methods similar to those used in studies of chloride double layers, we compute the structure and differential capacitance of molten fluoride electric double layers as a function of applied voltage. The role of molten salt structure is probed through comparisons between FLiBe and FLiNaK, which serve as models for strong and weak associate-forming salts, respectively. In FLiBe, screening involves changes in Be–F–Be angles and alignment of the oligomers parallel to the electrode, while in FLiNaK, the electric field is screened mainly by rearrangement of individual ions, predominantly the polarizable potassium cation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Accelerating charge estimation in molecular dynamics simulations using physics-informed neural networks: corrosion applications

Molecular Dynamics (MD) simulations are used to understand the effects of corrosion on metallic materials in salt brine. Reactive force fields in classical MD enable accurate modeling of bond formation and breakage in the aqueous medium and at the metal-electrolyte interface, while also facilitating dynamic partial charge equilibration. However, MD simulations are computationally intensive and unsuitable for modeling the long time scales characteristic of corrosive phenomena. To address this, we develop reduced-order machine learning models that provide accurate and efficient predictions of charge density in corrosive environments. Specifically, we use Long Short-Term Memory (LSTM) networks to forecast charge density evolution based on atomic environments represented by Smooth Overlap of Atomic Positions (SOAP) descriptors. A physics-informed loss function enforces charge neutrality and electronegativity equivalence. The atomic charges predicted by the deep learning model trained on this work were obtained two orders of magnitude faster than those from molecular dynamics (MD) simulations, with an error of less than 3% compared to the MD-obtained charges, even in extrapolative scenarios, while adhering to physical constraints. This demonstrates the excellent accuracy, computational efficiency, and validity of the developed model. Lastly, even though developed for corrosion, these protocols are formulated in a phenomenon-agnostic manner, allowing application to various variable-charge interatomic potentials and related fields.

Atomistic models↗