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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Computational Fluid Dynamics Simulations of the Transonic Dynamics Tunnel Airstream Oscillator System

This paper presents computational fluid dynamics simulations of the flow in the NASA Langley Research Center Transonic Dynamics Tunnel (TDT) with the airstream oscillator system (AOS) in operation. Test section flow angle can be modulated using sinusoidally oscillating vanes which are located in pairs within the contraction section of the tunnel circuit. A compilation of previously published experimental data for validation has been reviewed that contains hot-wire anemometer and fast-response probe data acquired in an empty test section with the vanes oscillating in-phase and out-of-phase. These experimental data have not previously been compared with computational results. The present results provide an opportunity for validation of the simulations of the sinusoidal AOS flow field in the TDT test section. Computed tunnel centerline, lateral and cross-section contour data of flow angle and vorticity show that resolving the vane tip vortex is critical to accurately predicting the test section center flow angle. The computed results show, as do the experimental data, what appears to be a resonance at higher frequencies. It is currently not known what is the cause of that resonance. Further refinement of the mesh is expected to improve the comparisons with experimental data

Robert E Bartels↗
DOE OSTI2020

Reactive Molecular Dynamics Simulations and Quantum Chemistry Calculations To Investigate Soot-Relevant Reaction Pathways for Hexylamine Isomers

Sooting tendencies of a series of nitrogen-containing hydrocarbons (NHCs) have been recently characterized experimentally using the yield sooting index (YSI) methodology. This work aims to identify soot-relevant reaction pathways for three selected C6H15N amines, namely, dipropylamine (DPA), diisopropylamine (DIPA), and 3,3-dimethylbutylamine (DMBA) using ReaxFF molecular dynamics (MD) simulations and quantum mechanical (QM) calculations and to interpret the experimentally observed trends. ReaxFF MD simulations are performed to determine the important intermediate species and radicals involved in the fuel decomposition and soot formation processes. QM calculations are employed to extensively search for chemical reactions involving these species and radicals based on the ReaxFF MD results and also to quantitatively characterize the potential energy surfaces. Specifically, ReaxFF simulations are carried out in the NVT ensemble at 1400, 1600, and 1800 K, where soot has been identified to form in the YSI experiment. These simulations account for the interactions among test fuel molecules and pre-existing radicals and intermediate species generated from rich methane combustion, using a recently proposed simulation framework. ReaxFF simulations predict that the reactivity of the amines decrease in the order DIPA > DPA > DMBA, independent of temperature. Both QM calculations and ReaxFF simulations predict that C2H4, C3H6, and C4H8 are the main nonaromatic soot precursors formed during the decomposition of DPA, DIPA, and DMBA, respectively, and the associated reaction pathways are identified for each amine. Both theoretical methods predict that sooting tendency increases in the order DPA, DIPA, and DMBA, consistent with the experimentally measured trend in YSI. This work demonstrates that sooting tendencies and soot-relevant reaction pathways of fuels with unknown chemical kinetics can be identified efficiently through combined ReaxFF and QM simulations. Overall, predictions from ReaxFF simulations and QM calculations are consistent, in terms of fuel reactivity, major intermediates, and major nonaromatic soot precursors.

fuel decomposition↗
DOE OSTI2017

A novel energy conversion based method for velocity correction in molecular dynamics simulations

Molecular dynamics (MD) simulation has become an important tool for studying micro- or nano-scale dynamics and the statistical properties of fluids and solids. In MD simulations, there are mainly two approaches: equilibrium and non-equilibrium molecular dynamics (EMD and NEMD). In this paper, a new energy conversion based correction (ECBC) method for MD is developed. Unlike the traditional systematic correction based on macroscopic parameters, the ECBC method is developed strictly based on the physical interaction processes between the pair of molecules or atoms. The developed ECBC method can apply to EMD and NEMD directly. While using MD with this method, the difference between the EMD and NEMD is eliminated, and no macroscopic parameters such as external imposed potentials or coefficients are needed. With this method, many limits of using MD are lifted. The application scope of MD is greatly extended.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

GPU-accelerated Tersoff potentials for massively parallel Molecular Dynamics simulations

The Tersoff potential is one of the empirical many-body potentials that has been widely used in simulation studies at atomic scales. Unlike pair-wise potentials, the Tersoff potential involves three-body terms, which require much more arithmetic operations and data dependency. In this contribution, we have implemented the GPU-accelerated version of several variants of the Tersoff potential for LAMMPS, an open-source massively parallel Molecular Dynamics code. Compared to the existing MPI implementation in LAMMPS, the GPU implementation exhibits a better scalability and offers a speedup of 2.2X when run on 1000 compute nodes on the Titan supercomputer. On a single node, the speedup ranges from 2.0 to 8.0 times, depending on the number of atoms per GPU and hardware configurations. The most notable features of our GPU-accelerated version include its design for MPI/accelerator heterogeneous parallelism, its compatibility with other functionalities in LAMMPS, its ability to give deterministic results and to support both NVIDIA CUDA- and OpenCL-enabled accelerators. Our implementation is now part of the GPU package in LAMMPS and accessible for public use.

Computer Science↗
DOE OSTI2017

Molecular Dynamics Simulations of the Interfacial Region between Boehmite and Gibbsite Basal Surfaces and High Ionic Strength Aqueous Solutions

Classical molecular dynamics (MD) simulations were used to study the interactions of up to 2 M NaCl and NaNO3 aqueous solutions with the presumed inert boehmite (010) and gibbsite (001) surfaces. The force field parameters used in these simulations were validated against density functional theory calculations of Na+ and Cl- hydrated complexes adsorbed at the boehmite (010) surface. In all the classical MD simulations and regardless of the ionic strength or the nature of the anion, Na+ ions were found to preferably form inner-sphere complexes over outer-sphere complexes at the aluminum (oxy)hydroxide surfaces, adsorbing closer to the surface than both water molecules and anions. In contrast, Cl- ions were distributed almost equally between inner- and outer-sphere positions. The resulting asymmetry in adsorption strengths offers molecular-scale evidence for the observed isoelectric point (IEP) shift to higher pH at high ionic strength for aluminum (oxy)hydroxides. As such, the MD simulations also provided clear evidence against the assumption that the basal surfaces of boehmite and gibbsite are inert to background electrolytes. Finally, the MD simulations indicated that, although the adsorption behavior of Na+ in NaNO3 and NaCl solutions was similar, the different affinities of NO3- and Cl- for the aluminum (oxy)hydroxide surfaces might have macroscopic consequences, such as difference in the sensitivity of the IEP to the electrolyte concentration.

Shen, Zhizhang↗
DOE OSTI2018

Cytosolic expression, solution structures, and molecular dynamics simulation of genetically encodable disulfide‐rich de novo designed peptides

Abstract Disulfide‐rich peptides represent an important protein family with broad pharmacological potential. Recent advances in computational methods have made it possible to design new peptides which adopt a stable conformation de novo. Here, we describe a system to produce disulfide‐rich de novo peptides using Escherichia coli as the expression host. The advantage of this system is that it enables production of uniformly 13 C‐ and 15 N‐labeled peptides for solution nuclear magnetic resonance (NMR) studies. This expression system was used to isotopically label two previously reported de novo designed peptides, and to determine their solution structures using NMR. The ensemble of NMR structures calculated for both peptides agreed well with the design models, further confirming the accuracy of the design protocol. Collection of NMR data on the peptides under reducing conditions revealed a dependency on disulfide bonds to maintain stability. Furthermore, we performed long‐time molecular dynamics (MD) simulations with tempering to assess the stability of two families of de novo designed peptides. Initial designs which exhibited a stable structure during simulations were more likely to adopt a stable structure in vitro , but attempts to utilize this method to redesign unstable peptides to fold into a stable state were unsuccessful. Further work is therefore needed to assess the utility of MD simulation techniques for de novo protein design.

Buchko, Garry W.↗
DOE OSTI2019

Transferable Kinetic Monte Carlo Models with Thousands of Reactions Learned from Molecular Dynamics Simulations

Molecular dynamics (MD) simulation of complex chemistry typically involves thousands of atoms propagating over millions of time steps, generating a wealth of data. Traditionally these data are used to calculate some aggregate properties of the system and then discarded, but we propose that these data can be reused to study related chemical systems. Using approximate chemical kinetic models and methods from statistical learning, we study hydrocarbon chemistries under extreme thermodynamic conditions. We discover that a single MD simulation can contain sufficient information about reactions and rates to predict the dynamics of related yet different chemical systems using kinetic Monte Carlo (KMC) simulation. Our learned KMC models identify thousands of reactions and run four orders of magnitude faster than MD. In conclusion, the transferability of these models suggests that we can viably reuse data from existing MD simulations to accelerate future simulation studies and reduce the number of new MD simulations required.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Insights into Spontaneous Solid Electrolyte Interphase Formation at Magnesium Metal Anode Surface from Ab Initio Molecular Dynamics Simulations

Spontaneous chemical reactivity at multivalent (Mg, Ca, Zn, Al) electrode surfaces is critical to solid electrolyte interphase (SEI) formation, and hence, directly affects the longevity of batteries. Here, we report an investigation of the reactivity of 0.5 M Mg(TFSI)2 in 1,2-dimethoxyethane (DME) solvent at a Mg(0001) surface using ab initio molecular dynamics (AIMD) simulations and detailed Bader charge analysis. Based on the simulations, the initial degradation reactions of the electrolyte strongly depend on the structure of the Mg(TFSI)2 species near the anode surface. At the surface, the dissociation of Mg(TFSI)2 species occurs via cleavage of the N-S bond for the solvent separated ion pair (SSIP) and via cleavage of the C-S bond for the contact ion pair (CIP) configuration. In the case of the CIP, both TFSI anions undergo spontaneous bond dissociation reactions to form atomic O, C, S, F, and N species adsorbed on the surface of the Mg anode. These products indicate that the initial SEI layer formed on the surface of the pristine Mg anode consists of a complex mixture of multiple components such as oxides, carbides, sulfides, fluorides, and nitrides. We believe that the atomic level insights gained from these simulations will lay the groundwork for the rational design of tailored and functional interphases that are critical for the success of multivalent battery technology.

Agarwal, Garvit↗
DOE OSTI2016

System-size corrections for self-diffusion coefficients calculated from molecular dynamics simulations: The case of CO{sub 2}, n-alkanes, and poly(ethylene glycol) dimethyl ethers

Molecular dynamics simulations were carried out to study the self-diffusion coefficients of CO{sub 2}, methane, propane, n-hexane, n-hexadecane, and various poly(ethylene glycol) dimethyl ethers (glymes in short, CH{sub 3}O–(CH{sub 2}CH{sub 2}O){sub n}–CH{sub 3} with n = 1, 2, 3, and 4, labeled as G1, G2, G3, and G4, respectively) at different conditions. Various system sizes were examined. The widely used Yeh and Hummer [J. Phys. Chem. B 108, 15873 (2004)] correction for the prediction of diffusion coefficient at the thermodynamic limit was applied and shown to be accurate in all cases compared to extrapolated values at infinite system size. The magnitude of correction, in all cases examined, is significant, with the smallest systems examined giving for some cases a self-diffusion coefficient approximately 15% lower than the infinite system-size extrapolated value. The results suggest that finite size corrections to computed self-diffusivities must be used in order to obtain accurate results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Molecular dynamics simulations of zinc oxide solubility: From bulk down to nanoparticles

The solubility of metal oxides is one of the key descriptors for the evaluation of their potential toxic effects, both in the bulk form and in nanoparticulated aggregates. Current work presents a new methodology for the in silico assessment of the solubility of metal oxides, which is demonstrated using a well-studied system, ZnO. The calculation of the solubility is based on statistical thermodynamics tools combined with Density Functional Tight Binding theory for the evaluation of the free energy exchange during the dissolution process. Models of small ZnO clusters are used for describing the final dissolved material, since the complete ionic dissolution of ZnO is hindered by the formation of O2- anions in solution, which are highly unstable. Results show very good agreement between the computed solubility values and experimental data for ZnO bulk, up to 0.5 mg·L-1 and equivalents of 50 g·L-1 for the free Zn2+ cation in solution. However, the reference model for solid nanoparticles formed by free space nanoparticles can only give a limited quantitative solubility evaluation for ZnO nanoparticles.

DFTB modelling↗
DOE OSTI2018

Molecular Dynamics Simulations of Water Structure and Diffusion in a 1 nm Diameter Silica Nanopore as a Function of Surface Charge and Alkali Metal Counterion Identity

Water confined in nanopores-particularly in pores narrower than 2 nm-displays distinct physicochemical properties that remain incompletely examined despite their importance in nanofluidics, molecular biology, geology, and materials sciences. In this study, we use molecular dynamics simulations to investigate the coordination structure and mobility of water and alkali metals (Li, Na, K, Cs) inside a 1 nm diameter cylindrical silica nanopore as a function of surface charge density, a model system particularly relevant to the alteration kinetics of silicate glasses and minerals in geologic formations. We find that the presence of a negative surface charge and adsorbed counterions within the pore strongly impacts water structure and dynamics. In particular, it significantly orients water O-H bonds toward the surface and slows water diffusion by almost 1 order of magnitude. Ion crowding in the charged nanopore enhances the tendency of counterions to coordinate closely with the silica surface, which moderates the impact of ions on water dynamics. Co-ions are strongly excluded from the nanopore at all surface charges, suggesting that the 1 nm diameter cylindrical silica nanopores likely exhibit nearly ideal semipermeable membrane transport properties.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Visual Analytics for Deep Embeddings of Large Scale Molecular Dynamics Simulations

Molecular Dynamics (MD) simulation have been emerging as an excellent candidate for understanding complex atomic and molecular scale mechanism of bio-molecules that control essential bio-physical phenomenon in a living organism. But this MD technique produces large-size and long-timescale data that are inherently high-dimensional and occupies many terabytes of data. Processing this immense amount of data in a meaningful way is becoming increasingly difficult. Therefore, specific dimensionality reduction algorithm using deep learning technique has been employed here to embed the high-dimensional data in a lower-dimension latent space that still preserves the inherent molecular characteristics i.e. retains biologically meaningful information. Subsequently, the results of the embedding models are visualized for model evaluation and analysis of the extracted underlying features. However, most of the existing visualizations for embeddings have limitations in evaluating the embedding models and understanding the complex simulation data. We propose an interactive visual analytics system for embeddings of MD simulations to not only evaluate and explain an embedding model but also analyze various characteristics of the simulations. Our system enables exploration and discovery of meaningful and semantic embedding results and supports the understanding and evaluation of results by the quantitatively described features of the MD simulations (even without specific labels).

Chae, Junghoon↗