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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 OSTI2021

Modifying Li + and Anion Diffusivities in Polyacetal Electrolytes: A Pulsed-Field-Gradient NMR Study of Ion Self-Diffusion

Polyacetal electrolytes have been demonstrated as promising alternatives to liquid electrolytes and poly(ethylene oxide) (PEO) for rechargeable lithium-ion batteries; however, the relationship between polymer structure and ion motion is difficult to characterize. Here, we study structure-property trends in ion diffusion with respect to polymer composition for a systematic series of five polyacetals with varying ratios of ethylene oxide (EO) to methylene oxide (MO) units, denoted as P(xEO-yMO), and PEO. We first use 7 Li and 19 F pulsed-field-gradient NMR spectroscopy to measure cation and anion self-diffusion, respectively, in polymer/lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) salt mixtures. At 90 °C, we observe modest changes in Li + diffusivity across all polymer compositions, while anion (TFSI - ) self-diffusion coefficients decrease significantly with increasing MO content. At a given reduced temperature (T - T g ), all polyacetal electrolytes exhibit faster Li + self-diffusion than PEO. Intriguingly, P(EO-MO) and P(EO-2MO) also show slower TFSI - anion self-diffusion than PEO at a given reduced temperature. Molecular dynamics simulations reveal that shorter distances between acetal oxygen atoms (O-CH 2 -O) compared to ether oxygens (O-CH 2 -CH 2 -O) promote more diverse, often asymmetric, Li + coordination environments. Finally, Raman spectra reveal that anion-rich ion clusters in P(EO-MO) and P(EO-2MO) lead to decreased anion diffusivity, which along with increased cation diffusivity, support the viability of polyacetals as high-performance polymer electrolytes.

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

Local-scale Arctic tundra heterogeneity affects regional-scale carbon dynamics

In northern Alaska nearly 65% of the terrestrial surface is composed of polygonal ground, where geomorphic tundra landforms disproportionately influence carbon and nutrient cycling over fine spatial scales. Process-based biogeochemical models used for local to Pan-Arctic projections of ecological responses to climate change typically operate at coarse-scales (1km 2 –0.5°) at which fine-scale (<1km 2 ) tundra heterogeneity is often aggregated to the dominant land cover unit. Here, we evaluate the importance of tundra heterogeneity for representing soil carbon dynamics at fine to coarse spatial scales. We leveraged the legacy of data collected near Utqiagvik, Alaska between 1973 and 2016 for model initiation, parameterization, and validation. Simulation uncertainty increased with a reduced representation of tundra heterogeneity and coarsening of spatial scale. Hierarchical cluster analysis of an ensemble of 21 st -century simulations reveals that a minimum of two tundra landforms (dry and wet) and a maximum of 4km 2 spatial scale is necessary for minimizing uncertainties (<10%) in regional to Pan-Arctic modeling applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Ionic Polymers Under Dynamic Conditions

Combining neutron scattering tools and exascale molecular dynamics simulations, research was carried out to resolve the structure and motion of ionic polymers under dynamic conditions. Ionizable polymers constitute a key component in current and potential transformative lightweight energy generation and storage devices. However, the inherent segregation of these polymers to ionic clusters and non-ionic domains, or clusters, that on one hand enables their function, confines the dynamics of the polymer chains, leading to the formation of far-from equilibrium states. These non-equilibrium states morph under in situ conditions, affecting the performance-longevity-safety-cost foundation that underlines the use of these polymers. On route to controlling the assemblies of ionizable polymers into stable functional materials, the research focused on a) understanding the inherent confinement of the polymer chains by the ionic clusters and b) resolving of the response of these polymers to flow fields that are integral to the processing and function of these macromolecules.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Robust training of machine learning interatomic potentials with dimensionality reduction and stratified sampling

Abstract Machine learning interatomic potentials (MLIPs) enable accurate simulations of materials at scales beyond that accessible by ab initio methods and play an increasingly important role in the study and design of materials. However, MLIPs are only as accurate and robust as the data on which they are trained. Here, we present DImensionality-Reduced Encoded Clusters with sTratified (DIRECT) sampling as an approach to select a robust training set of structures from a large and complex configuration space. By applying DIRECT sampling on the Materials Project relaxation trajectories dataset with over one million structures and 89 elements, we develop an improved materials 3-body graph network (M3GNet) universal potential that extrapolates more reliably to unseen structures. We further show that molecular dynamics (MD) simulations with the M3GNet universal potential can be used instead of expensive ab initio MD to rapidly create a large configuration space for target systems. We combined this scheme with DIRECT sampling to develop a reliable moment tensor potential for titanium hydrides without the need for iterative augmentation of training structures. This work paves the way for robust high-throughput development of MLIPs across any compositional complexity.

Qi, Ji (ORCID:0000000158089931)↗
DOE OSTI2021

Arrested Phase Separation in Double-Exchange Models: Large-Scale Simulation Enabled by Machine Learning

In this work, we present large-scale dynamical simulations of electronic phase separation in the single-band double-exchange model based on deep-learning neural-network potentials trained from small-size exact diagonalization solutions. We uncover an intriguing correlation-induced freezing behavior as doped holes are segregated from half filled insulating background during equilibration. While the aggregation of holes is stabilized by the formation of ferromagnetic clusters through Hund’s coupling between charge carriers and local magnetic moments, this stabilization also creates confining potentials for holes when antiferromagnetic spin-spin correlation is well developed in the background. The dramatically reduced mobility of the self-trapped holes prematurely disrupts further growth of the ferromagnetic clusters, leading to an arrested phase separation. Implications of our findings for phase separation dynamics in materials that exhibit colossal magnetoresistance effect are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Origin of Unusual Acidity and Li+ Diffusivity in a Series of Water-in-Salt Electrolytes.

Superconcentrated aqueous electrolytes ("water-in-salt" electrolytes, or WiSEs) enable various aqueous battery chemistries beyond the voltage limits imposed by the Pourbaix diagram of water. However, their detailed structural and transport properties remain unexplored and could be better understood through added studies. Here, we report on our observations of strong acidity (pH 2.4) induced by lithium bis(trifluoromethane sulfonyl)imide (LiTFSI) at superconcentration (at 20 mol/kg). Multiple nuclear magnetic resonance (NMR) and pulsed-field gradient (PFG) diffusion NMR experiments, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations reveal that such acidity originates from the formation of nanometric ion-rich structures. The experimental and simulation results indicate the separation of water-rich and ion-rich domains at salt concentrations >= 5 m and the acidity arising therefrom is due to deprotonation of water molecules in the ion-rich domains. As such, the ion-rich domain is composed of hydrophobic -CF3 (of TFSI-) and hydrophilic hydroxyl (OH-) groups. At 20 m concentration, the tortuosity and radius of water diffusion channels are estimated to be similar to 10 and similar to 1 nm, respectively, which are close to values obtained from hydrated Nafion membranes that also have hydrophobic polytetrafluoroethylene (PTFE) backbones and hydrophilic channels consisting of SO3- ion cluster networks providing for the transport of ions and water. Thus, we have discovered the structural similarity between WiSE and hydrated Nafion membranes on the nanometer scale.

Han, Kee Sung↗
DOE OSTI2022

Cluster dynamics modeling of Mn-Ni-Si precipitates coupled with radiation-induced segregation in low-Cu reactor pressure vessel steels

Formation of precipitates enhanced or induced by irradiation causes hardening and embrittlement of nuclear structural materials. Post-irradiation microstructure characterization of reactor pressure vessel (RPV) steels has shown that precipitation can be strongly associated with radiation-induced segregation (RIS) of solutes on dislocations. However, RIS and precipitation have not been coupled in previous precipitation modeling of RPV steels. Here in this study, a new hybrid and spatially-dependent precipitation model is developed that couples cluster dynamics with RIS, providing an unique way to account for concurrent evolution of heterogeneous cluster densities as well as solute and point defect concentration profiles. The model is applied to study the segregation of Mn, Ni, and Si on dislocations and heterogeneous nucleation of Mn-Ni-Si rich precipitates (MNSPs) in a low-Cu RPV steel. The result shows that the onset of MNSP nucleation on dislocations occurs at the fluence of 2 x 10 23 n.m -2 . The number density and mean radius can reach ~ 10 24 m -3 and 1-2 nm at high fluence, respectively. These observations suggest that the role of RIS and heterogeneous nucleation can be significant for RPV steels under a high fluence of irradiation. Results of simulations adopting various dose rates and dislocation densities show an increased fraction of MNSPs on dislocations at the condition of low dose rate, high dislocation density, and high fluence.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Healing of nanocracks by collision cascades in nickel

We use molecular dynamics simulations to investigate the interaction between collision cascades and pre-existing nano-cracks in nickel (Ni). We find that collision cascades cause the cracks to heal whenever a cascade initiates a thermal spike whose core overlaps with the crack. Moreover, crack healing affects the distribution of radiation-induced defects generated during a collision cascade: defect clusters, such as dislocations and stacking fault tetrahedra, dominate in the presence of crack healing, while isolated point defects dominate in its absence. Furthermore, this work indicates that irradiation may reduce the number of pre-existing crack-like flaws in metallic components, potentially improving their mechanical resilience.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The Evolution and Mass Dependence of Galaxy Cluster Pressure Profiles at 0.05 ≤ z ≤ 0.60 and 4 × 10 14 M ⊙ ≤ M 500 ≤ 30 × 10 14 M ⊙

Abstract We have combined X-ray observations from Chandra with Sunyaev–Zel’dovich effect data from Planck and Bolocam to measure intracluster medium pressure profiles from 0.03 R 500 ≤ R ≤ 5 R 500 for a sample of 21 low- z galaxy clusters with a median redshift of 〈 z 〉 = 0.08 and a median mass of 〈 M 500 〉 = 6.1 × 10 14 M ⊙ and a sample of 19 mid- z galaxy clusters with 〈 z 〉 = 0.50 and 〈 M 500 〉 = 10.6 × 10 14 M ⊙ . The mean scaled pressure in the low- z sample is lower at small radii and higher at large radii, a trend that is accurately reproduced in similarly selected samples from The Three Hundred simulations. This difference appears to be primarily due to dynamical state at small radii, evolution at intermediate radii, and a combination of evolution and mass dependence at large radii. Furthermore, the overall flattening of the mean scaled pressure profile in the low- z sample compared to the mid- z sample is consistent with expectations due to differences in the mass accretion rate and the fractional impact of feedback mechanisms. In agreement with previous studies, the fractional scatter about the mean scaled pressure profile reaches a minimum of ≃20% near 0.5 R 500 . This scatter is consistent between the low- z and mid- z samples at all radii, suggesting it is not strongly impacted by sample selection, and this general behavior is reproduced in The Three Hundred simulations. Finally, analytic functions that approximately describe the mass and redshift trends in mean pressure profile shape are provided.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Response of extreme precipitation to uniform surface warming in quasi-global aquaplanet simulations at high resolution

Projections of precipitation extremes in simulations with global climate models are very uncertain in the tropics, in part because of the use of parameterizations of deep convection and model deficiencies in simulating convective organization. Here, we analyse precipitation extremes in high-resolution simulations that are run without a convective parameterization on a quasi-global aquaplanet. The frequency distributions of precipitation rates and precipitation cluster sizes in the tropics of a control simulation are similar to the observed distributions. In response to climate warming, 3 h precipitation extremes increase at rates of up to 9 % K - 1 in the tropics because of a combination of positive thermodynamic and dynamic contributions. The dynamic contribution at different latitudes is connected to the vertical structure of warming using a moist static stability. When the precipitation rates are first averaged to a daily timescale and coarse-grained to a typical global climate-model resolution prior to calculating the precipitation extremes, the response of the precipitation extremes to warming becomes more similar to what was found previously in coarse-resolution aquaplanet studies. However, the simulations studied here do not exhibit the high rates of increase of tropical precipitation extremes found in projections with some global climate models. This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.

Science & Technology - Other Topics↗
DOE OSTI2021

Real-time dynamics and structures of supported subnanometer catalysts via multiscale simulations

Understanding the performance of subnanometer catalysts and how catalyst treatment and exposure to spectroscopic probe molecules change the structure requires accurate structure determination under working conditions. Experiments lack simultaneous temporal and spatial resolution and could alter the structure, and similar challenges hinder first-principles calculations from answering these questions. Here, we introduce a multiscale modeling framework to follow the evolution of subnanometer clusters at experimentally relevant time scales. We demonstrate its feasibility on Pd adsorbed on CeO 2 (111) at various catalyst loadings, temperatures, and exposures to CO. We show that sintering occurs in seconds even at room temperature and is mainly driven by free energy reduction. It leads to a kinetically (far from equilibrium) frozen ensemble of quasi-two-dimensional structures that CO chemisorption and infrared experiments probe. CO adsorption makes structures flatter and smaller. High temperatures drive very rapid sintering toward larger, stable/metastable equilibrium structures, where CO induces secondary structure changes only.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Combined Machine Learning and Molecular Dynamics Reveal Two States of Hydration of a Single Functional Group of Cationic Polymeric Brushes

The state of hydration of a macromolecular system regulates a plethora of different properties of such a system. In this article, we develop a novel machine learning (ML) approach, based on the unsupervised clustering algorithm, for probing the hydration behavior of the {N(CH 3 ) 3 } + functional group of the PMETAC [Poly(2-(methacryloyloxy)ethyl trimethylammonium chloride] polyelectrolyte (PE) brush system. The PE brushes and the brush-supported water molecules and counterions (chloride ions) are first described using all-atom molecular dynamics (MD) simulations. The simulation data is subsequently used in our ML framework to identify that (1) the {N(CH 3 ) 3 } + functional groups of the PMETAC brushes have two distinct hydration states with one state (state 1) being characterized by less structured water molecules and the other state (state 2) being characterized by more structured water molecules and (2) an enhancement in the brush grafting density leads to the progressive dissapparenace of state 2. An increase in the grafting density increases the number of chloride counterions in a given volume around the {N(CH 3 ) 3 } + functional group and increases the number of shared water molecules between the {N(CH 3 ) 3 } + and Cl - . The chloride counterions are associated with a hydration layer with much less structured water molecules. Therefore, with an increase in the grafting density, an increase in the percentage of shared water molecules leads to the prevalence of the hydration state [of the {N(CH 3 ) 3 } + moiety] with less structured water molecules. Finally, we explain how the present findings are commensurate with two key previous related results, namely a significantly large chloride ion mobility inside the PMETAC brush layer and the {N(CH 3 ) 3 } + -Cl - average distance remaining independent of the PMETAC brush grafting density. Furthermore, we anticipate that the combined ML-MD-simulation approach proposed in this study can be adapted to probe other soft matter systems to reveal new insights of the underlying mechanisms of emergent phenomenon.

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

Perspective on Many-Body Methods for Molecular Polaritonic Systems

Recent advances in strong light–matter interactions have revealed a wealth of new physical phenomena in molecules embedded in optical cavities, including modified chemical reactivity, altered excitation spectra, and novel quantum correlations. To describe these effects from first-principles, the field of ab initio quantum electrodynamics (QED) has emerged as a compelling extension of quantum chemistry that treats electronic and photonic degrees of freedom on equal footing. In this Perspective, we review the growing landscape of many-body QED methods, including Hartree–Fock, density functional theory (QEDFT), time-dependent DFT (QED-TDDFT), configuration interaction (QED-CI), complete active space (QED-CASSCF), coupled cluster (QED-CC), quantum Monte Carlo (QED-QMC), and density matrix renormalization group (QED-DMRG), highlighting recent developments and implementations. We further explore real-time methods, gradient and Hessian formalisms, and the integration of nonadiabatic nuclear dynamics. Applications range from benchmark simulations of polaritonic chemistry to quantum simulations on emerging quantum hardware. We conclude by outlining future directions for theory development and interdisciplinary efforts at the interface of quantum chemistry, condensed matter, and quantum optics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Understanding Metal–Organic Framework Nucleation from a Solution with Evolving Graphs

A mechanistic understanding of metal–organic framework (MOF) synthesis and scale-up remains underexplored due to the complex nature of the interactions of their building blocks. In this work, we investigate the collective assembly of building units at the early stages of MOF nucleation, using MIL-101(Cr) as a prototypical example. Using large-scale molecular dynamics simulations, we observe that the choice of solvent (water and N,N-dimethylformamide), the introduction of ions (Na+ and F–) and the relative populations of MIL-101(Cr) half-secondary building unit (half-SBU) isomers have a strong influence on the cluster formation process. Additionally, the shape, size, nucleation and growth rates, crystallinity, and short and long-range order largely vary depending on the synthesis conditions. We evaluate these properties as they naturally emerge when interpreting the self-assembly of MOF nuclei as the time evolution of an undirected graph. Solution-induced conformational complexity and ionic concentration have a dramatic effect on the morphology of clusters emerging during assembly. While pure solvents lead to the rapid formation of a small number of large clusters, the presence of ions in aqueous solutions results in smaller clusters and slower nucleation. This diversity is captured by the key features of the graph representation. Principle component analysis on graph properties reveals that only a small number of molecular descriptors is needed to deconvolute MOF self-assembly. Furthermore, descriptors such as the average coordination number between half-SBUs and fractal dimension are of particular interest as they can be can be followed experimentally by techniques like by time-resolved spectroscopy. Ultimately, graph theory emerges as an approach that can be used to understand complex processes revealing molecular descriptors accessible by both simulation and experiment.

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

Evaluation of dynamical downscaling in a fully coupled regional earth system model

A set of decadal simulations has been completed and evaluated for gains using the Regional Arctic System Model (RASM) to dynamically downscale data from a global Earth system model and two atmospheric reanalyses. RASM is a fully coupled atmosphere–land–ocean–sea ice regional Earth system model. Nudging to the forcing data is applied to approximately the top half of the atmospheric domain. RASM simulations were also completed with a modification to the atmospheric physics for evaluating changes to the modeling system. The results show that for the top half of the atmosphere, the RASM simulations follow closely to that of the forcing data, regardless of the forcing data. The results for the lower half of the atmosphere, as well as the surface, show a clustering of atmospheric state and surface fluxes based on the modeling system. At all levels of the atmosphere the imprint of the weather from the forcing data is present as indicated in the pattern of the annual means. Biases, in comparison to reanalyses, are evident in the Earth system model forced simulations for the top half of the atmosphere but are not present in the lower atmosphere. This suggests that bias correction is not needed for fully coupled dynamical downscaling simulations. While the RASM simulations tended to go to the same mean state for the lower atmosphere, there are a differences in the variability and changes of weather patterns across the ensemble of simulations. These differences in the weather result in variances in the sea ice and oceanic states.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Performant automatic differentiation of local coupled cluster theories: Response properties and ab initio molecular dynamics

In this work, we introduce a differentiable implementation of the local natural orbital coupled cluster (LNO-CC) method within the automatic differentiation framework of the PySCFAD package. The implementation is comprehensively tuned for enhanced performance, which enables the calculation of first-order static response properties on medium-sized molecular systems using coupled cluster theory with single, double, and perturbative triple excitations [CCSD(T)]. We evaluate the accuracy of our method by benchmarking it against the canonical CCSD(T) reference for nuclear gradients, dipole moments, and geometry optimizations. In addition, we demonstrate the possibility of property calculations for chemically interesting systems through the computation of bond orders and Mössbauer spectroscopy parameters for a [NiFe]-hydrogenase active site model, along with the simulation of infrared spectra via ab initio LNO-CC molecular dynamics for a protonated water hexamer.

Chemistry↗
DOE OSTI2024

Detection of the large-scale tidal field with galaxy multiplet alignment in the DESI Y1 spectroscopic survey

We explore correlations between the orientations of small galaxy groups, or ‘multiplets’, and the large-scale gravitational tidal field. Using data from the Dark Energy Spectroscopic Instrument (DESI) Y1 survey, we detect the intrinsic alignment (IA) of multiplets to the galaxy-traced matter field out to separations of $100\,h^{-1}$ Mpc. Unlike traditional IA measurements of individual galaxies, this estimator is not limited by imaging of galaxy shapes and allows for direct IA detection beyond redshift $z=1$. Multiplet alignment is a form of higher order clustering, for which the scale-dependence traces the underlying tidal field and amplitude is a result of small-scale ($\lt 1h^{-1}$ Mpc) dynamics. Within samples of bright galaxies, luminous red galaxies (LRG) and emission-line galaxies, we find similar scale-dependence regardless of intrinsic luminosity or colour. This is promising for measuring tidal alignment in galaxy samples that typically display no IA. DESI’s LRG mock galaxy catalogues created from the A BACUS S UMMIT N -body simulations produce a similar alignment signal, though with a 33 per cent lower amplitude at all scales. An analytic model using a non-linear power spectrum (NLA) only matches the signal down to 20 $h^{-1}$ Mpc. Our detection demonstrates that galaxy clustering in the non-linear regime of structure formation preserves an interpretable memory of the large-scale tidal field. Multiplet alignment complements traditional two-point measurements by retaining directional information imprinted by tidal forces, and contains additional line-of-sight information compared to weak lensing. This is a more effective estimator than the alignment of individual galaxies in dense, blue, or faint galaxy samples.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Parallel algorithms for hyperdynamics and local hyperdynamics

Hyperdynamics (HD) is a method for accelerating the timescale of standard molecular dynamics (MD). It can be used for simulations of systems with an energy potential landscape that is a collection of basins, separated by barriers, where transitions between basins are infrequent. HD enables the system to escape from a basin more quickly while enabling a statistically accurate renormalization of the simulation time, thus effectively boosting the timescale of the simulation. In [Kim, Perez, Voter, J Chem Phys, 139:144110, 2013)1, a local version of HD was formulated, which exploits the intrinsic locality characteristic typical of most systems to mitigate the poor scaling properties of standard HD as the system size is increased. In this paper, we discuss how both HD and local HD can be formulated to run efficiently in parallel. We have implemented these ideas in the LAMMPS MD code, which means HD can be used with any interatomic potential LAMMPS supports. Together, these parallel methods allow simulations of any size to achieve the time acceleration offered by HD (which can be orders of magnitude), at a cost 3-5x that of standard MD. As examples, we performed two simulations of a million-atom system to model the diffusion and clustering of Pt adatoms on a large patch of Pt(100) surface for 80 and 160 μs.

74 ATOMIC AND MOLECULAR PHYSICS↗