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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Tasting nuclear pasta made with classical molecular dynamics simulations

Nuclear clusters or voids in the inner crust of neutron stars were predicted to have various shapes collectively nicknamed nuclear pasta. Furthermore, the recent review by López, Dorso and Frank summarized their systematic investigations into properties especially the morphological and thermodynamical phase transitions of the nuclear pasta within a Classical Molecular Dynamics model, providing further stimuli to find more observational evidences of the predicted nuclear pasta in neutron stars.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Molecular dynamics simulations of radiation response of $\mathrm{LiAlO_2}$ and $\mathrm{LiAl_5O_8}$

Here, we report the findings of a computational investigation of defect production and migration in two lithium aluminate ceramics: LiAlO 2 and LiAl 5 O 8 . Although the first ceramic, LiAlO 2 has been widely investigated computationally, especially via molecular dynamics (MD), there have been no MD studies done on LiAl 5 O 8 up to date, due to the lack of interatomic potentials for this system. This work implemented an existing set of Li-Al-O coulombic and Buckingham potential parameters for the LiAl 5 O 8 system from the literature, followed by validating it based on experimental values of density, crystallinity, bond lengths and melting point. The Li + diffusion in the two ceramics was examined and was found to be one order of magnitude slower in LiAl 5 O 8 (D 0 = 3.17 x 10 -11 m 2 /s) as compared to that in LiAlO 2 (D 0 = 4.02 x 10 -10 m 2 /s) at 600 K. The lithium vacancy migration barrier of 4.15 eV in LiAl 5 O 8 was more than three times that in LiAlO 2 (1.31 eV) possibly due to stronger ordering in the Li-O 6 octahedra of LiAl 5 O 8 than in Li-O 4 tetrahedra of LiAlO 2 . The Li displacement threshold energy (E d ) in LiAl 5 O 8 was found to have a median value of 68 eV which is much higher than that in LiAlO 2 (40 eV). The greater E d for Li signifies a lower likelihood for defect formation and clustering and thus lower tendency for amorphization in LiAl 5 O 8 . The presented results show the difference in defect dynamics in the two ceramics that may help us understand the susceptibility of the two ceramics to amorphization caused by irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Strong adsorption of guanidinium cations to the air–water interface

Combining Deep-UV second harmonic generation spectroscopy with molecular simulations, we confirm and quantify the specific adsorption of guanidinium cations to the air–water interface. Using a Langmuir analysis of measurements at multiple concentrations, we extract the Gibbs free energy of adsorption, finding it larger than typical thermal energies. Molecular simulations clarify the role of polarizability in tuning the thermodynamics of adsorption, and establish the preferential parallel alignment of guanidinium at the air–water interface. As a polyatomic cation, guanidinium represents one of the few examples of a positively charged species to exhibit a propensity for the air-water interface. As such, these results expand on the growing body of work on specific ion adsorption.

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

Quantum-Based Molecular Dynamics Simulations Using Tensor Cores

Tensor cores, along with tensor processing units, represent a new form of hardware acceleration specifically designed for deep neural network calculations in artificial intelligence applications. Tensor cores provide extraordinary computational speed and energy efficiency but with the caveat that they were designed for tensor contractions (matrix–matrix multiplications) using only low-precision floating-point operations. Despite this perceived limitation, we demonstrate how tensor cores can be applied with high efficiency to the challenging and numerically sensitive problem of quantum-based Born–Oppenheimer molecular dynamics, which requires highly accurate electronic structure optimizations and conservative force evaluations. The interatomic forces are calculated on-the-fly from an electronic structure that is obtained from a generalized deep neural network, where the computational structure naturally takes advantage of the exceptional processing power of the tensor cores and allows for high performance in excess of 100 Tflops on a single Nvidia A100 GPU. Stable molecular dynamics trajectories are generated using the framework of extended Lagrangian Born–Oppenheimer molecular dynamics, which combines computational efficiency with long-term stability, even when using approximate charge relaxations and force evaluations that are limited in accuracy by the numerically noisy conditions caused by the low-precision tensor core floating-point operations. A canonical ensemble simulation scheme is also presented, where the additional numerical noise in the calculated forces is absorbed into a Langevin-like dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Elucidating Lithium Transport Mechanisms in Disordered LiF from Machine-Learning Molecular Dynamics Simulations

Lithium fluoride (LiF) is a ubiquitous component of solid- and cathode–electrolyte interphases, yet its functional role remains unclear under the structural and chemical heterogeneity typical of cycling batteries. Here, we systematically quantify how structural disorder, off-stoichiometry, and strain govern Li-ion transport in LiF. Using a machine-learning potential to enable extensive molecular-dynamics sampling, we compare crystalline and amorphous LiF, Li 0.95 F, and LiF 0.95 , and evaluate the impact of small homogeneous deformations. Defect-free crystalline LiF is effectively ion-blocking at 300−500 K, whereas amorphization generates free-volume–assisted percolation pathways that facilitates Li-ion diffusion. At elevated temperatures, thermodynamically driven crystallization disrupts these pathways, leading to non-Arrhenius behavior. In crystalline phases, Li deficiency activates vacancy-mediated diffusion, while in amorphous LiF, transport is governed primarily by network connectivity. Strain is found to have only a marginal effect on Li mobility in both crystalline and amorphous structures.

Batteries↗
DOE OSTI2020

Machine Learning-Based Upscaling of Finite-Size Molecular Dynamics Diffusion Simulations for Binary Fluids

Molecular diffusion coefficients calculated using molecular dynamics (MD) simulations suffer from finite-size (i.e., finite box size and finite particle number) effects. Results from finite-sized MD simulations can be upscaled to infinite simulation size by applying a correction factor. For self-diffusion of single-component fluids, this correction has been well-studied by many researchers including Yeh and Hummer (YH); for binary fluid mixtures, a modified YH correction was recently proposed for correcting MD-predicted Maxwell–Stephan (MS) diffusion rates. In this study we use both empirical and machine learning methods to identify improvements to the finite-size correction factors for both self-diffusion and MS diffusion of binary Lennard-Jones (LJ) fluid mixtures. Using artificial neural networks (ANNs), the error in the corrected LJ fluid diffusion is reduced by an order of magnitude versus existing YH corrections, and the ANN models perform well for mixtures with large dissimilarities in size and interaction energies where the YH correction proves insufficient.

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

Carbon fiber synthesis from pitch: Insights from ReaxFF based molecular dynamics simulations

Despite the potential to lowering fabrication costs of pitch-based carbon fiber (CF) compared to polyacrylonitrile-based CF, large scale utilization is currently limited by the complexity in manufacturing. This is mainly due to the lack of consistency between the pitch structure/chemistry and CF properties under different processing conditions. Here, we employed full atomistic simulations based on reactive force fields to investigate the conversion of pitch precursors to CFs. Additionally, it was found that at the carbonization stage, the consumption rates of precursors, gas formations, and solid yields (carbonized CFs) are all dependent on the composition and arrangement of molecular moieties in the precursor. Specifically, precursors with sp 3 carbons in the cata-condensed core area have limited decomposition pathways (i.e., limited reaction sites), which leads to the formation of carbonized CFs with similar compositions. Furthermore, carbonized CFs possess distinct structural characteristics, and finally lead to the formation of CFs with different moduli. By analyzing CF crystallinity and elemental composition, general rationales are proposed for the selection of optimal precursors and processing conditions, and thus shed lights on parameter screening during industrial CF synthesis. For instance, inclusion of sp 3 carbons in cata- condensed rings can be preferred over the presence of sp 3 carbons on side chains.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Machine learning molecular dynamics simulations toward exploration of high-temperature properties of nuclear fuel materials: case study of thorium dioxide

Predicting materials properties of nuclear fuel compounds is a challenging task in materials science. Their thermodynamical behaviors around and above the operational temperature are essential for the design of nuclear reactors. However, they are not easy to measure, because the target temperature range is too high to perform various standard experiments safely and accurately. Moreover, theoretical methods such as first-principles calculations also suffer from the computational limitations in calculating thermodynamical properties due to their high calculation-costs and complicated electronic structures stemming from f-orbital occupations of valence electrons in actinide elements. Here, we demonstrate, for the first time, machine-learning molecular-dynamics to theoretically explore high-temperature thermodynamical properties of a nuclear fuel material, thorium dioxide. The target compound satisfies first-principles calculation accuracy because f-electron occupation coincidentally diminishes and the scheme meets sampling sufficiency because it works at the computational cost of classical molecular-dynamics levels. We prepare a set of training data using first-principles molecular dynamics with small number of atoms, which cannot directly evaluate thermodynamical properties but captures essential atomistic dynamics at the high temperature range. Then, we construct a machine-learning molecular-dynamics potential and carry out large-scale molecular-dynamics calculations. Consequently, we successfully access two kinds of thermodynamic phase transitions, namely the melting and the anomalous λ transition induced by large diffusions of oxygen atoms. Furthermore, we quantitatively reproduce various experimental data in the best agreement manner by selecting a density functional scheme known as SCAN. Our results suggest that the present scale-up simulation-scheme using machine-learning techniques opens up a new pathway on theoretical studies of not only nuclear fuel compounds, but also a variety of similar materials that contain both heavy and light elements, like thorium dioxide.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Microscopic Origin of Twist-Dependent Electron Transfer Rate in Bilayer Graphene

Using molecular simulation and continuum dielectric theory, we consider how electrochemical kinetics are modulated by the twist angle in bilayer graphene electrodes. By establishing a connection between the twist angle and the screening length of charge carriers within the electrode, we investigate how tunable metallicity modifies the statistics of the electron transfer energy gap. Constant potential molecular simulations show that the activation free energy for electron transfer increases with screening length, leading to a non-monotonic dependence on the twist angle. Here, the twist angle alters the density of states, tuning the number of thermally accessible channels for electron transfer and the reorganization energy by affecting the stability of the vertically excited state through attenuated image charge interactions. Understanding these effects allows us to express the Marcus rate of interfacial electron transfer as a function of the twist angle in a manner consistent with experimental observations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Evaluation of δ-Phase ZrH1.4 to ZrH1.7 Thermal Neutron Scattering Laws Using Ab Initio Molecular Dynamics Simulations

Zirconium hydride is commonly used for next-generation reactor designs due to its excellent hydrogen retention capacity at temperatures below 1000 K. These types of reactors operate at thermal neutron energies and require accurate representation of thermal scattering laws (TSLs) to optimize moderator performance and evaluate the safety indicators for reactor design. In this work, we present an atomic-scale representation of sub-stoichiometric ZrH2−x(0.3≤x≤0.6), which relies on ab initio molecular dynamics (AIMD) in tandem with velocity auto-correlation (VAC) analysis to generate phonon density of states (DOS) for TSL development. The novel NJOY+NCrystal tool, developed by the European Spallation Source community, was utilized to generate the TSL formulations in the A Compact ENDF (ACE) format for its utility in neutron transport software. First, stoichiometric zirconium hydride cross sections were benchmarked with experiments. Then sub-stoichiometric zirconium hydride TSLs were developed. Significant deviations were observed between the new δ-phase ZrH2−x TSLs and the TSLs in the current ENDF release. It was also observed that varying the hydrogen vacancy defect concentration and sites did not cause as significant a change in the TSLs (e.g., ZrH1.4 vs. ZrH1.7) as was caused by the lattice transformation from ϵ- to δ-phase.

42 ENGINEERING↗
DOE OSTI2020

Vapor‐ and liquid‐phase adsorption of alcohol and water in silicalite‐1 synthesized in fluoride media

Abstract In this work, batch‐adsorption experiments and molecular simulations are employed to probe the adsorption of binary mixtures containing ethanol or a linear alkane‐1, n ‐diol solvated in water or ethanol onto silicalite‐1. Since the batch‐adsorption experiments require an additional relationship to determine the amount of solute (and solvent) adsorbed, as only the bulk liquid reservoir can be probed directly, molecular simulations are used to provide a relationship between solute and solvent adsorption for input to the experimental bulk measurements. The combination of bulk experimental measurements and simulated solute–solvent relationship yields solvent and solute loadings that are self‐consistent with simulation alone, and allow for an assessment of the various assumptions made in the literature. At low solution concentrations, the solute loading calculated is independent of the assumption made. At high concentrations, a negligent choice of assumption can lead to systematic overestimation or underestimation of calculated solute loading.

DeJaco, Robert F.↗
DOE OSTI2020

A comparative study of the effectiveness of empirical potentials for molecular dynamics simulations of borosilicate glasses

Despite their practical importance, atomistic modeling of B 2 O 3 containing glasses have been challenging due to the lack of reliable empirical potentials. Fortunately, a few recent developments have shown promises to simulate these glasses where the boron coordination has complex and non-linear dependence on glass composition. This work aims to provide an evaluation of the effectiveness of three recently developed potentials by a systematic study of a series (~20) of sodium borosilicate glasses with constant K (ratio of [SiO 2 ]/[B 2 O 3 ]) =2 and varying R (ratio of [Na 2 O]/[B 2 O 3 ] ranging from 0.1 to 4) values and several sodium boroaluminosilicate glasses. A comparative assessment was established on the basis of the short- and medium-range structure features, such as boron N 4 values, total correlation functions, bond angle distribution, oxygen speciation, and mechanical properties using experimental or well-established models as criteria. Furthermore, this work provides insights on the choices of empirical potentials for MD simulations of borosilicate glasses and gives directions of future potential development and refining.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗