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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Structures of the mycobacterial membrane protein MmpL3 reveal its mechanism of lipid transport

The mycobacterial membrane protein large 3 (MmpL3) transporter is essential and required for shuttling the lipid trehalose monomycolate (TMM), a precursor of mycolic acid (MA)-containing trehalose dimycolate (TDM) and mycolyl arabinogalactan peptidoglycan (mAGP), in Mycobacterium species, including Mycobacterium tuberculosis and Mycobacterium smegmatis. However, the mechanism that MmpL3 uses to facilitate the transport of fatty acids and lipidic elements to the mycobacterial cell wall remains elusive. Here, we report 7 structures of the M. smegmatis MmpL3 transporter in its unbound state and in complex with trehalose 6-decanoate (T6D) or TMM using single-particle cryo-electron microscopy (cryo-EM) and X-ray crystallography. Combined with calculated results from molecular dynamics (MD) and target MD simulations, we reveal a lipid transport mechanism that involves a coupled movement of the periplasmic domain and transmembrane helices of the MmpL3 transporter that facilitates the shuttling of lipids to the mycobacterial cell wall.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Periodic boundary conditions for arbitrary deformations in molecular dynamics simulations

A generalization of the Lees-Edwards periodic boundary conditions (gLE-PBC) for molecular dynamics (MD) simulations is developed to allow for arbitrary deformations to be applied to the domain. The gLE-PBC domain remains a rectangular cuboid regardless of the applied deformation in contrast with the Lagrangian-rhomboid periodic boundary conditions (LR-PBC) where the domain deforms according to the applied deformation. Furthermore, the kinematics of gLE-PBC are validated against pure shear. The gLE-PBC method for interacting systems is then validated against the LR-PBC method and analytical solutions for a solid under isotropic compression, one-dimensional shearing, three-dimensional extension and shearing and for a liquid under Couette flow. Bulk physical properties extracted from the gLE-PBC simulations agree well with values calculated from equilibrium MD simulations. Three dimensional shearing and a deformation with a full velocity gradient matrix are also simulated, showing the range of problems gLE-PBC can explore.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Impact of classical statistics on thermal conductivity predictions of BAs and diamond using machine learning molecular dynamics

Machine learning interatomic potentials (MLIPs) have greatly enhanced molecular dynamics (MD) simulations, achieving near-first-principles accuracy in thermal conductivity studies. In this work, we reveal that this accuracy, observed in BAs and diamond at sub-Debye temperatures, stems from an accidental error cancelation: classical statistics overestimates specific heat while underestimating phonon lifetimes, balancing out in thermal conductivity predictions. However, this balance is disrupted when isotopes are introduced, leading MLIP-based MD to significantly underpredict thermal conductivity compared to experiments and quantum statistics-based Boltzmann transport equation. This discrepancy arises not from classical statistics affecting phonon–isotope scattering rates but from its impact on the interplay between phonon–isotope and phonon–phonon scattering in the normal scattering-dominated BAs and diamond. In conclusion, this work underscores the limitations of MLIP-based MD for thermal conductivity studies at sub-Debye temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Enabling Predictive Scale-Bridging Simulations through Active Learning (Institutional Computing Annual Report (Project w21_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. Transport in nanoporous media, critical to hydrocarbon extraction from tight shale formations, is affected by molecular-level interactions. Several coarse-scale Lattice Boltzmann model (LBM) parameters cannot be directly computed, so instead we calibrate them to molecular dynamics (MD) simulations, by building emulators that mimic MD and LBM behavior and then training an upscaler. The resulting machine learning (ML)-based scale-bridging framework is up to 7 orders of magnitude faster than direct MD.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Validating continuum theory for Cottrell atmosphere solute drag by molecular dynamics simulations

When a dislocation moves through a field of mobile solute atoms, solutes segregate to the dislocation and form Cottrell atmospheres which exert solute drag forces. Over the last 70 years, continuum theory has been used extensively to estimate these drag forces and their dependence on the dislocation velocity, however few prior works have validated the accuracy of continuum theories. Here, in this work, molecular dynamics (MD) simulations of dislocation motion in face-centered cubic Ni containing interstitial H atoms were performed in order to test the accuracy of continuum theory predictions. Our results demonstrate that continuum theory provides an accurate estimate of the solute drag force for velocities below the critical velocity at which the solute drag force is maximized. Above the critical velocity, continuum theory systematically deviates from MD. Additional analysis reveals that this deviation results from the multi-valued and unstable nature of solute drag under load control, and also from the transition to random solute drag which occurs at high velocities.

Dislocations↗
DOE OSTI2021

Using Computationally-Determined Properties for Machine Learning Prediction of Self-Diffusion Coefficients in Pure Liquids

The ability to predict transport properties of liquids quickly and accurately will greatly improve our understanding of fluid properties both in bulk and complex mixtures, as well as in confined environments. Such information could then be used in the design of materials and processes for applications ranging from energy production and storage to manufacturing processes. As a first step, we consider the use of machine learning (ML) methods to predict the diffusion properties of pure liquids. Recent results have shown that Artificial Neural Networks (ANNs) can effectively predict the diffusion of pure compounds based on the use of experimental properties as the model inputs. In the current study, a similar ANN approach is applied to modeling diffusion of pure liquids using fluid properties obtained exclusively from molecular simulations. A diverse set of 102 pure liquids is considered, ranging from small polar molecules (e.g., water) to large nonpolar molecules (e.g., octane). Self-diffusion coefficients were obtained from classical molecular dynamics (MD) simulations. Since nearly all the molecules are organic compounds, a general set of force field parameters for organic molecules was used. The MD methods are validated by comparing physical and thermodynamic properties with experiment. Computational input features for the ANN include physical properties obtained from the MD simulations as well as molecular properties from quantum calculations of individual molecules. Furthermore, fluid properties describing the local liquid structure were obtained from center of mass radial distribution functions (COM-RDFs). Feature sensitivity analysis revealed that isothermal compressibility, heat of vaporization, and the thermal expansion coefficient were the most impactful properties used as input for the ANN model to predict the MD simulated self-diffusion coefficients. The MD-based ANN successfully predicts the MD self-diffusion coefficients with only a subset (2 to 3) of the available computationally determined input features required. A separate ANN model was developed using literature experimental self-diffusion coefficients as model targets. Although this second ML model was not as successful due to a limited number of data points, a good correlation is still observed between experimental and ML predicted self-diffusion coefficients.

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

Influence of misfit dislocations on ionic conductivity at oxide interfaces

Mismatched complex oxide thin films and heterostructures have gained significant traction for use as electrolytes in intermediate temperature solid oxide fuel cells, wherein interfaces exhibit variation in ionic conductivity as compared to the bulk. Although misfit dislocations present at interfaces in these structures impact ionic conductivity, the fundamental mechanisms responsible for this effect are not well understood. To this end, a kinetic lattice Monte Carlo (KLMC) model was developed to trace oxygen vacancy diffusion at misfit dislocations in SrTiO 3 /BaZrO 3 heterostructures and elucidate the atomistic mechanisms governing ionic diffusion at oxide interfaces. The KLMC model utilized oxygen vacancy migration energy barriers computed using molecular statics. While some interfaces promote oxygen vacancy diffusion, others impede their transport. Fundamental factors such as interface layer chemistry, misfit dislocation structure, and starting and ending sites of migrating ions play a crucial role in oxygen diffusivity. Molecular dynamics (MD) simulations were further performed to support qualitative trends for oxygen vacancy diffusion. Overall, the agreement between KLMC and MD is quite good, though MD tends to predict slightly higher conductivities, perhaps a reflection of nuanced structural relaxations that are not captured by KLMC. The current framework comprising KLMC modeling integrated with molecular statics offers a powerful tool to perform mechanistic studies focused on ionic transport in thin film oxide electrolytes and facilitate their rational design.

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

Effect of helium bubbles on the mobility of edge dislocations in copper

Abstract Helium bubbles can form in materials upon exposure to irradiation. It is well known that the presence of helium bubbles can cause changes in the mechanical behavior of materials. To improve the lifetime of nuclear components, it is important to understand deformation mechanisms in helium-containing materials. In this work, we investigate the interactions between edge dislocations and helium bubbles in copper using molecular dynamics (MD) simulations. We focus on the effect of helium bubble pressure (equivalently, the helium-to-vacancy ratio) on the obstacle strength of helium bubbles and their interaction with dislocations. Our simulations predict significant differences in the interaction mechanisms as a function of helium bubble pressure. Specifically, bubbles with high internal pressure are found to exhibit weaker obstacle strength as compared to low-pressure bubbles of the same size due to the formation of super-jogs in the dislocation. Activation energies and rate constants extracted from the MD data confirm this transition in mechanism and enable upscaling of these phenomena to higher length-scale models.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Thiocyanate Ions Form Antiparallel Populations at the Concentrated Electrolyte/Charged Surfactant Interface

Anions play significant roles in the separation of lanthanides and actinides. The molecular-scale details of how these anions behave at aqueous interfaces are not well understood, especially at high ionic strengths. Here, we describe the interfacial structure of thiocyanate anions at a soft charged interface up to 5 M bulk concentration with combined classical and phase-sensitive and molecular dynamics (MD) simulations. At low concentrations thiocyanate ions are mostly oriented with their sulfur end pointing toward the charged surfactants. In this work, the VSFG signal reaches a plateau at around 100 mM bulk concentration, followed by significant changes above 1 M. At high concentrations a new thiocyanate population emerges with their sulfur end pointing toward the bulk liquid. The –CN stretch frequency is different for up and down oriented SCN – ions, indicating different coordination environments. These results provide key molecular-level insights for the interfacial behavior of complex anions in highly concentrated solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Multi-scale characterization and simulation of impact welding between immiscible Mg/steel alloys

Vaporizing foil actuator spot welding method is used in this paper to join magnesium alloy AZ31 and uncoated high-strength steel DP590, which are typically considered as un-weldable due to their high physical property disparities, low mutual solubility, and the lack of any intermetallic phases. Characterization results from scanning electron microscopy (SEM) and high-resolution transmission electron microscopy (HRTEM) of the weld interface indicate that the impact creates an Mg nanocrystalline interlayer with abundant Fe particles. The interlayer exhibits intact bonding with both DP590 and AZ31 substrates. To investigate the fundamental bond formation mechanisms at the interface, a finite element (FE)-based process simulation is first performed to calculate the local temperature and deformation at the interface under the given macroscopic experimental condition. Finally, taking the FE results at the interface as inputs, molecular dynamics (MD) simulations are conducted to study the interlayer formation at the Mg/Fe interface during the impact and cooling. The results found a high velocity shearing-induced mechanical mixing mechanism that mixes Mg/Fe atoms at the interface and creates the interlayer, leading to the metallurgical bond between Mg/steel alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Elucidating and contrasting the mechanisms for Mg and Ca sulfate ion-pair formation with multi-level embedded quantum mechanics/molecular dynamics simulations

Here, solutions and minerals containing sulfate (SO 4 2- ), and Ca 2+ and Mg 2+ cations, are ubiquitous throughout the lithosphere and are significant components of seawater, thus presenting a prototypical system for the study of strong electrolytes and crystal nucleation mechanisms. However, despite their relative abundance, key questions remain unanswered about the most fundamental atomic-level steps of their mineralization pathways and aqueous dynamics. Here, we carry out enhanced sampling multi-level molecular dynamics (MD) embedded correlated wavefunction theory simulations to elucidate ion-pairing mechanisms for Mg–SO 4 and Ca–SO 4 in concentrated aqueous solution, accurately capturing effects arising from both structural dynamics and electron exchange–correlation. We predict contact-ion-pair formation to be barrierless and highly exoergic for Ca–SO 4 , in agreement with its minimal solubility, whereas for Mg–SO 4 , solvent-shared and contact ion pairs have similar free energies, qualitatively consistent with its higher solubility. Finally, we demonstrate that brief high-temperature pre-equilibration may be utilized to accelerate convergence of free energies in blue-moon-ensemble enhanced-sampling MD.

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

From Electronic Structure to Ion Transport: Photoelectron Spectroscopy and Molecular Dynamics Simulations Reveal the Role of Anions in Lithium Battery Electrolytes

Electrolyte anions are pivotal for lithium battery performance, yet their fundamental electronic structural properties are not well understood. In this work, we employ a combination of negative-ion photoelectron spectroscopy (NIPES), ab initio calculations, and molecular dynamics (MD) simulations to investigate the electronic structures of three representative electrolyte anions. This multiscale approach enables us to elucidate how their intrinsic electronic properties govern anion–solvent interactions in gas-phase clusters, as well as lithium-ion (Li + ) solvation structures and ion transport behavior in the condensed phase. NIPES reveals that difluoro(oxalato)borate (DFOB – ), bis(fluorosulfonyl)imide (FSI – ), and bis(oxalato)borate (BOB – ) all exhibit high electron binding energies, with vertical/adiabatic detachment energies increasing from DFOB – (6.09/5.70 eV) to FSI – (6.80/6.10 eV) to BOB – (6.82/6.40 eV), correlating with enhanced oxidation stability. Ab initio calculations reveal that DFOB – /FSI – –solvent complexes bind Li + ∼ 10 kcal/mol stronger than BOB – series, aligning with the strength of a Li + –anion model. DFOB – exhibits pronounced charge localization on both oxygen and fluorine atoms, enabling their involvement in Li + coordination. In contrast, fluorine atoms in FSI – are largely electron-depleted and remain excluded from direct Li + binding. MD simulations further demonstrate that LiDFOB and LiFSI systems exhibit Li + diffusion coefficients three and five times higher than those of LiBOB across four common solvents. Notably, LiFSI salt in acetonitrile (AN) exhibits the fastest Li + diffusion among 12 electrolyte systems, highlighting the synergistic effect of FSI – and AN in promoting ion mobility. In conclusion, these findings provide a molecular-level understanding of the critical roles of anion and its microsolvation in optimizing Li + diffusion dynamics, once again emphasizing the positioning of FSI – and DFOB – as prime candidates for next-generation electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2023

Predicted viscosity of liquid HMX up to 40 GPa

Viscous flow serves as a significant heating mechanism during the formation of hot spots, but the shear viscosity which determines this response is poorly characterized for most high explosives. Most recently, a model was proposed for the shear viscosity of liquid HMX (1,3,5,7-tetranitro-1,3,5,7-tetrazocane) that was fit to pressures reaching 5 GPa, but this work uncovered uncertainties in the viscosity at 0 GPa and remains untested at higher pressures. We use molecular dynamics (MD) simulations and the Green-Kubo formalism to predict the temperature- and pressure-dependent shear viscosity of HMX over the pressure interval 0 GPa≤P≤40 GPa. Reassessment of the viscosity at 0 GPa rules out several potential explanations for discrepancies between earlier reports; we attribute these differences to details of MD trajectory integration impacting molecular flexibility. The shear viscosity of HMX exhibits an Arrhenius temperature dependence at each pressure considered, with exponential prefactor and activation energy terms that are also strong functions of pressure. An analytic form for the viscosity is developed based on an extension of the well-known Andrade equation that simultaneously captures the temperature and pressure dependencies in the MD data up to 40 GPa. Comparison against a recently developed model for the viscosity of liquid RDX (1,3,5-trinitro-1,3,5-triazinane) shows that both materials exhibit similar functional dependencies with the viscosity of HMX being higher by roughly an order of magnitude at a given temperature-pressure state.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Molecular-based analysis of nanoparticle solvation: Classical density functional approach

Proper statistical mechanics understanding of nanoparticle solvation processes requires an accurate description of the molecular structure of the solvent. Achieving this goal with standard molecular dynamics (MD) simulation methods is challenging due to large length scales. An alternative approach to this problem can be formulated using classical density functional theory (cDFT), where a full configurational description of the positions of all the atoms is replaced by collective atomic site densities in the molecule. Using an example of the negatively charged silica-like system in an aqueous polar environment represented by a two-site water model, we demonstrate here that cDFT can reproduce MD data at a fraction of the computational cost. An important implication of this result is the ability to understand how the solvent molecular features may affect the system’s properties at the macroscopic scale. A concrete example highlighted in this work is the analysis of nanoparticle interactions with sizes of up to 100 nm in diameter.

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

In situ ion irradiation of amorphous TiO 2 nanotubes

Understanding of structural and morphological evolution in nanomaterials is critical in tailoring their functionality for applications such as energy conversion and storage. Here, we examine irradiation effects on the morphology and structure of amorphous TiO 2 nanotubes in comparison with their crystalline counterpart, anatase TiO 2 nanotubes, using high-resolution transmission electron microscopy (TEM), in situ ion irradiation TEM, and molecular dynamics (MD) simulations. Anatase TiO 2 nanotubes exhibit morphological and structural stability under irradiation due to their high concentration of grain boundaries and surfaces as defect sinks. On the other hand, amorphous TiO 2 nanotubes undergo irradiation-induced crystallization, with some tubes remaining only partially crystallized. The partially crystalline tubes bend due to internal stresses associated with densification during crystallization as suggested by MD calculations. Furthermore, these results present a novel irradiation-based pathway for potentially tuning structure and morphology of energy storage materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Simulating dielectric spectra: A demonstration of the direct electric field method and a new model for the nonlinear dielectric response

Here we demonstrate a method to compute the dielectric spectra of fluids in molecular dynamics (MD) by directly applying electric fields to the simulation. We obtain spectra from MD simulations with low magnitude electric fields (≈0.01 V/Å) in agreement with spectra from the fluctuation–dissipation method for water and acetonitrile. We examine this method’s trade-off between noise at low field magnitudes and the nonlinearity of the response at higher field magnitudes. We then apply the Booth equation to describe the nonlinear response of both fluids at low frequency (0.1 GHz) and high field magnitude (up to 0.5 V/Å). We develop a model of the frequency-dependent nonlinear response by combining the Booth description of the static nonlinear dielectric response of fluids with the frequency-dependent linear dielectric response of the Debye model. We find good agreement between our model and the MD simulations of the nonlinear dielectric response for both acetonitrile and water.

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

Performance Advantaged ..beta..-Ketone Containing Polymers - Benefits in Manufacturing, Performance, and End-of-Life

Biomass derived chemicals can possess extended functionality, often in the form of heteroatoms like oxygen and nitrogen, that can enable performance advantaged properties in emergent materials. These performance advantages can manifest in multiple ways such as reduced manufacturing intensity, better performance, or enhanced end-of-life options. One illustrative example of this concept is ..beta..-ketoadipic acid (..beta..KA), a C6 dicarboxylic acid with a ketone in its backbone. ..beta..KA can be obtained via biological cultivation from aromatic compounds, sugars, and even waste plastics. When ..beta..KA is implemented into polymers, namely nylons, in place of adipic acid the overall material properties are increased. Specifically, the glass transition temperature (which is the measurement at which temperature a plastic softens) is increased by 69 degrees C and the water permeability is reduced by 20%. Molecular dynamic (MD) simulations reveal that the ..beta..-ketone in ..beta..KA leads to restricted movement across multiple backbone carbons when compared to adipic acid. Furthermore, MD simulations reveal that the ..beta..-ketone, when compared to no-ketone or an a-ketone, can lead to an increase in hydrogen bonding between neighboring chains. Both phenomena may help explain the molecular origin of the increases in polymer performance. When implemented into polyesters, namely PET, ..beta..KA can maintain the requisite performance while enabling enhanced degradation. Aside from performance advantages in thermomechanical performance, the production of ..beta..KA also is advantaged in its manufacturing. Although estimates for the minimum selling price (MSP) of ..beta..KA exceed adipic acid the manufacture of ..beta..KAwould reduce supply chain energy and GHG emissions by >50% and >30% respectively. Further TEA analysis reveals that the MSP of ..beta..KA is primarily driven by the feedstock cost while the capital expenditures are driven largely by fermentation costs. Overall, the work presented within will be illustrative of how biomass derived molecules, namely ..beta..KA, can manifest performance advantages across multiple benchmarks and may enable a path to market for biomass-derived materials.

ADVANCED PROPULSION SYSTEMS,BIOMASS FUELS↗
DOE OSTI2022

..beta..-Ketoadipic Acid Production in P. putida for Performance-Advantaged Nylons

Biomass derived chemicals can possess extended functionality, often in the form of heteroatoms like oxygen and nitrogen, that can enable performance advantaged properties in emergent materials. One illustrative example of this concept is ..beta..-ketoadipic acid (..beta..KA), a C6 dicarboxylic acid with a ketone in its backbone. ..beta..KA can be obtained via biological cultivation from aromatic compounds, sugars, and even waste plastics. When ..beta..KA is implemented into polymers, namely nylons, in place of adipic acid the overall material properties are increased. Specifically, the glass transition temperature (which is the measurement at which temperature a plastic softens) is increased by 69 degrees C and the water permeability is reduced by 20%. Molecular dynamic (MD) simulations reveal that the ..beta..-ketone in ..beta..KA leads to restricted movement across multiple backbone carbons when compared to adipic acid. Furthermore, MD simulations reveal that the ..beta..-ketone, when compared to no-ketone or an a-ketone, can lead to an increase in hydrogen bonding between neighboring chains. Both phenomena may help explain the molecular origin of the increases in polymer performance. Aside from performance advantages in thermomechanical performance, the production of ..beta..KA also is advantaged in its manufacturing. Although estimates for the minimum selling price (MSP) of ..beta..KA exceed adipic acid the manufacture of ..beta..KA would reduce supply chain energy and GHG emissions by >50% and >30% respectively. Further TEA analysis reveals that the MSP of ..beta..KA is primarily driven by the feedstock cost while the capital expenditures are driven largely by fermentation costs. Overall, the work presented within will be illustrative of how biomass derived molecules, namely ..beta..KA, can manifest performance advantages across multiple benchmarks and may enable a path to market for biomass-derived materials.

beta-ketoadipic acid↗