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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Elucidating the Mechanical Energy for Cyclization of a DNA Origami Tile

DNA origami has emerged as a versatile method to synthesize nanostructures with high precision. This bottom-up self-assembly approach can produce not only complex static architectures, but also dynamic reconfigurable structures with tunable properties. While DNA origami has been explored increasingly for diverse applications, such as biomedical and biophysical tools, related mechanics are also under active investigation. Here we studied the structural properties of DNA origami and investigated the energy needed to deform the DNA structures. We used a single-layer rectangular DNA origami tile as a model system and studied its cyclization process. This origami tile was designed with an inherent twist by placing crossovers every 16 base-pairs (bp), corresponding to a helical pitch of 10.67 bp/turn, which is slightly different from that of native B-form DNA (~10.5 bp/turn). We used molecular dynamics (MD) simulations based on a coarse-grained model on an open-source computational platform, oxDNA. We calculated the energies needed to overcome the initial curvature and induce mechanical deformation by applying linear spring forces. We found that the initial curvature may be overcome gradually during cyclization and a total of ~33.1 kcal/mol is required to complete the deformation. These results provide insights into the DNA origami mechanics and should be useful for diverse applications such as adaptive reconfiguration and energy absorption.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Resolving Lonsdaleite's decade-long controversy: Atomistic insights into a metastable diamond polymorph

Lonsdaleite, a theoretically proposed hexagonal diamond polymorph, has remained at the center of a five-decade scientific controversy since its 1967 identification. While some studies claim it exhibits superior hardness through compression-induced structural changes, others contend it is merely a stacking-faulted cubic diamond. Meteoritic samples and synthetic preparations have yielded conflicting evidence, with even advanced characterisation techniques like XRD and TEM failing to provide definitive proof. In this work, we employ first-principles density functional theory (DFT) and molecular dynamics (MD) simulations to generate unambiguous theoretical fingerprints through XRD, Raman, and SAED patterns that distinguish true Lonsdaleite from cubic diamond and its defective variants. Our atomistic approach quantifies the thermodynamic metastability of Lonsdaleite under realistic pressure-temperature conditions, reveals distinct spectral signatures through simulated Raman and resolves the structural ambiguity through generalised stacking fault energy analysis. By establishing clear criteria for definitive identification, this study provides long-awaited clarity to the Lonsdaleite debate while offering a robust computational framework for characterising metastable carbon phases in meteoritic, synthetic and industrial materials.

DFT↗
DOE OSTI2020

Molecular-Level Behavior of Imidazolium-Based Ionic Liquid Mixtures

Understanding the molecular-level organization of anions and cations in a mixture of different ionic liquids (ILs) is challenging, but it can be very important for designing solvents and IL-based membrane materials. In this work, we perform all-atom molecular dynamics (MD) simulations to understand the intermolecular interactions and structuring of both neat and mixed IL compositions containing 1-benzyl-3-methylimidazolium [ZMIM + ], 1-butyl-3-methylimidazolium [BMIM + ], bistriflimide [Tf 2 N – ], and tetrafluoroborate [BF 4 – ]. We observe very strong underlying molecular-level migrations in these mixtures, and this tends to mainly involve the anion species. As compared to the systems with a single anion, the mixed anions lead to large increases/decreases in the radial distribution function peak heights, whereas the cation mixing is relatively benign. The [BF 4 – ] anions have a strong tendency to displace the [Tf 2 N – ] anions in the mixtures, and this is seen with respect to both [BMIM + ] and [ZMIM + ].

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

Ettringite hysteresis under sorption from molecular simulations

Highlights: • Hybrid Grand Canonical Monte Carlo (GCMC) and Molecular Dynamics (MD) simulations are performed. • Anisotropic large strain coefficient of crystal shrinkage of ettringite is provided. • Entropy increases when ettringite converts into metaettringite. • Sorption-induced stress may lead to columns collapse upon drying. • H-bonds involving OH groups in columns play a role in hysteresis. The response of ettringite under sorption is critical for the utilization of this mineral as an energy storage material and to understand the concrete durability problems associated with ettringite formation. We report molecular simulations directly sampling the osmotic ensemble to understand the sorption processes and structural changes in ettringite-metaettringite transition. Desorption branch and sorption-induced volume changes from simulations agree with the experiments. The structural changes at low relative humidity are analyzed, revealing for the first time details of metaettringite structure. The reversibility under sorption observed experimentally is captured by simulation in the ettringite domain. The reversibility in the conversion of metaettringite into ettringite is not captured by the direct simulations in the osmotic ensemble due to the large volume changes associated with ettringite desorption. Finally, we discuss the role of hydrogen bonds on the hysteresis in ettringite.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Enhanced resistance to helium irradiations through unusual interaction between high-entropy-alloy and helium

Finding high performance plasma-facing materials (PFMs) is one of the most important and challenging tasks for realizing the commercial application of fusion reactors. Herein, we found the CrMoTaWV high entropy alloy (HEA) is highly resistant to low-energy and high-flux He plasma exposure. The nanochannel HEA film has 20 times higher initial fluence for the formation of fuzz and a remarkable 8.9 times slower fuzz growth rate than those of W. Combining the in-situ TEM observation and the Molecular dynamics (MD) simulation of the He bubble growth process, a new mechanism for the enhanced radiation resistance in HEA with the unusual interaction between HEA and He is found, where, differing from traditional metal, bubble growth in HEA leads to non-directional emission of interstitial atoms while HEA greatly suppress the growth of He bubbles. Additionally, the special nanochannel structure further rise the radiation resistance through releasing He out of the HEA film and reducing the He concentration. This new nanochannel refractory HEA material presents a promising choice as the PFMs with excellent performance and a much longer serving lifetime for future commercial fusion reactors.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Effects of Ionic Group Distribution on the Structure and Dynamics of Amorphous Polymer Melts

Ionizable groups tethered to a polymer backbone often associate to form ionic clusters, whose features are determined by the balance of the polymer backbone and electrostatics. These assemblies impact the dynamics of the macromolecules and their ability to transport ions. Here, using fully atomistic molecular dynamics (MD) simulations, we investigate the effects of the distribution of ionizable groups along the polymer backbone on cluster characteristics and the resulting impacts on the structure and dynamics of amorphous polymers. Particularly, we probe polystyrene sulfonates (PSS) with random, precise, and block configurations of the SO 3 – sulfonate groups along the backbone with Na + as the counterion. We find that the distribution of the ionic groups affects the shape and distribution of the clusters as well as the internal packing of the ionizable groups in the cluster and the number of unique chains that participate in each cluster, affecting the structure and the dynamics of the polymers. Furthermore, the signature of ionic clusters, observed in the static structure factor S(q) for all three distributions, is significantly more pronounced for the precise and blocky polymers compared to the random one. Remarkably, we find that the local mobility of the polymer segments is not only affected by the number and size of the clusters but also by the number of polymer chains associated with clusters.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Enabling Predictive Scale-Bridging Simulations through Active Learning (Institutional Computing Annual Report (Project w20_alscalebridging)) [Slides]

The goal of this project was to develop, demonstrate, and provide a new capability to achieve greater physical fidelity in large-scale simulations, rather than the usual brute-force increases in the number of mesh elements or particles. This was done by using machine learning (ML) techniques to develop emulators for subscale physics that can be used in coarse-scale continuum simulations, trained on fine-scale molecular dynamics (MD) simulations that are launched on-the-fly via active learning. raditional inertial confinement fusion (ICF) simulations rely on numerical diffusion to simulate molecular effects such as non-local transport and mixing without truly accounting for molecular interactions; our approach directly accounts for this physics.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

A modified many-body dissipative particle dynamics model for mesoscopic fluid simulation: methodology, calibration, and application for hydrocarbon and water

The many-body dissipative particle dynamics (mDPD) is a prominent mesoscopic multiphase model for fluid transport in mesoconfinement. However, it has been a long-standing challenge for mDPD (and other multiphase-enabled DPD models) to accurately predict real-fluid static and dynamic properties simultaneously. We have developed a modified mDPD model to overcome the issue and a rigorous calibration approach that uses reference data, including experimental and/or molecular dynamics (MD) simulations to parameterise the modified mDPD for real fluids. We choose heptane as a representative example of hydrocarbon in source rocks to demonstrate the model's capability to accurately predict the equation of state (EOS), free surface tension, diffusivity, and viscosity. Our timing test shows that the modified mDPD is 400–500 times faster than its MD counterpart for simulating bulk heptane in equivalent volumes. To further demonstrate the robustness of the model, we revisited the benchmark problem of mesoscopic modelling of water, in which all the previous works on DPD reported only a limited portion of the water properties. Here, we show that the modified mDPD can provide accurate modelling of water static and dynamic properties and an EOS that matches the experimental data to a large range of confinement pressure.

42 ENGINEERING↗
DOE OSTI2020

The effects of stress, temperature and facet structure on growth of { 10 1 ¯ 2 } twins in Mg: a molecular dynamics and phase field study

The present study focuses on the roles of structure, stress and temperature on the mobility of facets bounding twin domains and on the overall impact on the growth kinetics of { 10 1 ¯ 2 } twins in Mg. We first use molecular dynamics simulations (MD) to study the relationship between interface structures, stress, temperature and mobility. As facets can exhibit distinct atomic scale structures, we also quantify the effect of stress relaxation mediated by misfit dislocations on the mobility of the basal-prismatic interface. The information gathered for ten different facets is used to calibrate an anisotropic phase field model predicting the effects of temperature and stress on the kinetics and shape of a growing { 10 1 ¯ 2 } 3D twin, by comparison with MD data. The comparative analysis suggests that, as compared to simulations of individual facets, the effective mobility of facets can be significantly different during growth of a 3D twin. This can be attributed to the complex three-dimensional internal stress state of the twin and to coupling in facet motion triggered by facet junctions. As such, by directly fitting both the twin growth kinetics and morphology as predicted by MD for different stresses and temperatures, we can identify a limited set of rate-limiting facets that control twin growth and morphology, and measure their effective mobility.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Accurate and efficient interatomic potentials are essential for molecular dynamics (MD) simulations of radiation damage, gas diffusion, and phase stability in complex ceramics such as LiAlO 2 , especially under extreme conditions relevant to tritium production. Here, we evaluate the performance of six machine-learned interatomic potentials (MLIPs), moment tensor potential (MTP), Gaussian approximation potential, deep potential (DeePMD), atomic cluster expansion (ACE), message-passing ACE (multilayer atomic cluster expansion (MACE) pretrained) and MACE (trained from-scratch), all trained on the same density functional theory dataset with inclusion of tritium. The MLIPs are benchmarked against traditional Buckingham and ReaxFF potentials in terms of energy accuracy, density predictions, thermal equilibration behavior, threshold displacement energy (E d ), tritium diffusivity, and computational cost. Among the models, MTP shows the best overall balance between efficiency and accuracy, with low force and energy errors and realistic E d values for Li and Al. The ACE and MACE (pretrained and trained from scratch) models exhibit high E d (>200 eV) and unphysical pair interactions. DeePMD underestimates Ed due to overly repulsive behavior even at equilibrium distances. All models over-estimate tritium diffusion but the pretrained MACE model behaves well during tritium-diffusion simulations up to 500 K, maintaining diffusivities in the physically consistent 10 −11 m 2 /s range. Finally, we quantify the computational cost of each potential in large-scale atomic/molecular massively parallel simulator, finding that only MTP is more efficient than traditional empirical potentials, while others are significantly more expensive. These findings explain the trade-offs between accuracy and computational cost in MLIP development and provide essential guidance for use in high-throughput radiation damage and gas diffusion simulations in nuclear ceramics.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Methyl α‐D‐galactopyranosyl‐(1→3)‐β‐D‐galactopyranoside and methyl β‐D‐galactopyranosyl‐(1→3)‐β‐D‐galactopyranoside: Glycosidic linkage conformation determined from MA'AT analysis

Abstract MA'ATanalysis has been applied to two biologically‐importantO‐glycosidic linkages in two disaccharides, α‐D‐Galp‐(1→3)‐β‐D‐GalpOMe (3) and β‐D‐Galp‐(1→3)‐β‐D‐GalpOMe (4). Using density functional theory (DFT) to obtain parameterized equations relating a group of trans‐O‐glycosidic NMR spin‐couplings to eitherphi(ϕ') orpsi(ψ'), and experimental 3 J COCH , 2 J COC , and 3 J COCC spin‐couplings measured in aqueous solution in 13 C‐labeled isotopomers, probability distributions ofϕ'andψ'in each linkage were determined and compared to those determined by aqueous 1‐μs molecular dynamics (MD) simulation. Good agreement was found between theMA'ATand single‐state MD conformational models of these linkages for the most part, with modest (approximately <15°) differences in the mean values ofϕ'andψ', although the envelope of allowed angles (encoded in circular standard deviations or CSDs) is consistently larger forϕ'determined fromMA'ATanalysis than from MD for both linkages. TheMA'ATmodel of the α‐Galp‐(1→3)‐β‐Galplinkage agrees well with those determined previously using conventional NMR methods ( 3 J COCH values and/or 1 H‐ 1 H NOEs), but some discrepancy was observed for the β‐Galp‐(1→3)‐β‐Galplinkage, which may arise from errors in the conventions used to describe the linkage torsion angles. Statistical analyses of X‐ray crystal structures show ranges ofϕ'andψ'for both linkages that include the mean angles determined fromMA'ATanalyses, although both angles adopt a wide range of values in the crystalline state, withϕ'in β‐Galp‐(1→3)‐β‐Galplinkages showing greater‐than‐expected conformational variability.

Chemistry↗
DOE OSTI2026

High-pressure melt dynamics in shock-compressed titanium

In this work we study the high-pressure melting behavior of titanium using laser-driven shock compression with in situ femtosecond x-ray diffraction and molecular-dynamics simulations based on a machine-learned interatomic potential. The MD simulations predict the solid-liquid coexistence on the Hugoniot in the ∼111−124GPa range. Experimentally, we observe the first evidence of liquid at 86 GPa. We also observe pronounced microstructural changes with pressure, with strong grain refinement associated with the emergence of liquid, within the solid-liquid coexistence (∼110−126GPa). Above 126 GPa, we observe the persistence of residual levels of highly textured crystalline Ti to ∼180GPa, well above the expected melt completion pressure. We discuss the accuracy that current laser-shock experimental platforms have at determining the melt onset and completion pressures.

36 MATERIALS SCIENCE↗
NASA NTRS1991

Disordering and H-embrittlement of Pb(110) surface using embedded atom method and molecular dynamics

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.

Karimi, Majid↗
DOE OSTI2025

Intermetallic phase formation in Al-Si-Zr alloys during hot isostatic pressing revealed by experiments and molecular dynamics

Understanding phase transformations at alloy interfaces is critical for the design of advanced structural materials. Here, in this study, we investigate the formation mechanisms of the Al 2 SiZr intermetallic phase in the Al-Si-Zr system under hot isostatic pressing (HIP) using molecular dynamics (MD) simulations and thermodynamic analysis. A unique aspect of our approach in MD involves the replacement of a disordered Al 2 SiZr stoichiometry with an ordered phase at the Al-Zr interface once HIP results in the desired Al 2 SiZr stoichiometry, allowing us to compute the total energetic cost of transformation by accounting for both formation energies and diffusion barriers. Diffusion coefficients and activation energies, extracted across a range of temperatures, reveal that HIP substantially enhances atomic mobility, creating favorable stoichiometry for phase evolution. Our results show that Al 2 SiZr phase formation is kinetically unfavorable at lower temperatures but becomes feasible when the thermodynamic driving energy surpass a critical energy threshold.

Roy, Ankit [Pacific Northwest National Laboratory ↗
DOE OSTI2024

A data-driven multiscale model for reactive wetting simulations

Here, we describe a data-driven, multiscale technique to model reactive wetting of a silver–aluminum alloy on a Kovar™ (Fe-Ni-Co alloy) surface. We employ molecular dynamics simulations to elucidate the dependence of surface tension and wetting angle on the drop’s composition and temperature. A design of computational experiments is used to efficiently generate training data of surface tension and wetting angle from a limited number of molecular dynamics simulations. The simulation results are used to parameterize models of the material’s wetting properties and compute the uncertainty in the models due to limited data. The data-driven models are incorporated into an engineering-scale (continuum) model of a silver–aluminum sessile drop on a Kovar™ substrate. Model predictions of the wetting angle are compared with experiments of pure silver spreading on Kovar™ to quantify the model-form errors introduced by the limited training data versus the simplifications inherent in the molecular dynamics simulations. The paper presents innovations in the determination of “convergence” of noisy MD simulations before they are used to extract the wetting angle and surface tension, and the construction of their models which approximate physio-chemical processes that are left unresolved by the engineering-scale model. Together, these constitute a multiscale approach that integrates molecular-scale information into continuum scale models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Computational Prediction of Water Sorption in Facilitated Transport Membranes

Polymeric facilitated transport membranes (FTMs) have emerged as an innovative class of promising carbon capture technology. Studies have shown that the transport properties of an FTM are significantly influenced by its water uptake. In order to better quantify FTM performance, we herein explore the potential of computational techniques to predict the equilibrium water uptake values of FTMs. Two prediction approaches were examined. First, the water sorption was explicitly simulated by iteratively conducting grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations. Second, the water sorption was predicted based on the chemical potential of the adsorbed water, which was calculated using the Widom insertion or continuous fractional component Monte Carlo (CFCMC) method. The chemical potential-based approach with CFCMC demonstrated good prediction of the equilibrium water uptake values of FTMs with poly(N-vinylformamide-co-vinylamine) as fixed-site carrier and 2-(1-piperazinyl)ethylamine sarcosinate as mobile carrier. The predicted water uptake values increased with increasing mobile carrier content and were in good agreement with the experimental values. Furthermore, the higher water uptake promoted the diffusion of CO 2 , N 2 , and mobile carrier as well as slightly stifled the sorption of N 2 . Such an approach significantly contributes to a more comprehensive theoretical evaluation of FTMs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Geometrically necessary dislocation fingerprints of dislocation loop absorption at grain boundaries

Here we present a numerical methodology to compute the Nye-tensor fingerprints of dislocation loop absorption at grain boundaries (GBs) for comparison with TEM observations of irradiated polycrystals. Our approach links atomistic simulations of self-interstitial atom (SIA) prismatic loops gliding toward and interacting with GBs in body-centered cubic iron with experimentally extracted geometrically necessary dislocation (GND) maps to facilitate the interpretation of damage processes. The Nye-tensor analysis is strongly mesh-size dependent—corresponding to resolution-dependent TEM observations. The method computes GND fingerprints from discretized dislocation line segments extracted from molecular dynamics simulations of dislocation loops being absorbed at a GB. Specifically, we perform MD simulation of prismatic loops of two diameters and monitor the three stages of the absorption process: loop glide, the partial, and full absorption of the loops at a [1 0 0] symmetric tilt GB. These methods provide a framework for future investigations of the nature of defect absorption by grain boundaries under irradiation conditions.

36 MATERIALS SCIENCE↗
NASA NTRS2013

Kinetic Monte Carlo Simulation of Cation Diffusion in Low-K Ceramics

Low thermal conductivity (low-K) ceramic materials are of interest to the aerospace community for use as the thermal barrier component of coating systems for turbine engine components. In particular, zirconia-based materials exhibit both low thermal conductivity and structural stability at high temperature, making them suitable for such applications. Because creep is one of the potential failure modes, and because diffusion is a mechanism by which creep takes place, we have performed computer simulations of cation diffusion in a variety of zirconia-based low-K materials. The kinetic Monte Carlo simulation method is an alternative to the more widely known molecular dynamics (MD) method. It is designed to study "infrequent-event" processes, such as diffusion, for which MD simulation can be highly inefficient. We describe the results of kinetic Monte Carlo computer simulations of cation diffusion in several zirconia-based materials, specifically, zirconia doped with Y, Gd, Nb and Yb. Diffusion paths are identified, and migration energy barriers are obtained from density functional calculations and from the literature. We present results on the temperature dependence of the diffusivity, and on the effects of the presence of oxygen vacancies in cation diffusion barrier complexes as well.

Good, Brian↗