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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Tuning anisotropic bonding via chemistry and pressure in layered pnictides and chalcogenides. Final Report

The overarching goal of this research program, as originally delineated in the proposal “Tuning anisotropic bonding via chemistry and pressure in layered pnictides and chalcogenides” was to develop a predictive, chemistry-driven understanding of the impact of the phonon behavior on thermal properties of bulk layered materials. At finite temperatures, atomic vibrations (phonons) strongly impact the thermodynamics, thermal and electrical transport, and phase-switching properties of functional materials. In particular, soft phonon modes and strongly anharmonic potentials can have spectacular consequences, including structural phase transitions (for example in ferroelectrics and phase-change memory materials), metal-insulator transitions, and extreme thermal resistance preventing heat propagation. Bulk materials with highly-anisotropic bonding may provide unique strategies to induce soft-phonon modes and lattice instabilities. Recently, increasingly detailed investigations of the lattice dynamics in layered materials have been made possible by the advent of first-principles phonon calculations and advanced characterization techniques based on neutron and X-ray scattering. However, due to the lack of studies in which composition and bonding character are systematically varied, there are still fundamental questions regarding the impacts of anisotropic bonding and anharmonicity on lattice stability and thermal transport. One of the major goals of this research program is therefore to address this gap by coherently tuning bonding anisotropy and anharmonicity across families of related compounds. Such approaches have revealed new strategies for exploiting structural anisotropy in quasi-1D and 2D bulk materials to obtain tailored functional properties. This project systematically explored the lattice dynamics, phase stability, and transport properties in bulk layered materials by using both composition and applied pressure to tune the degree of bonding anisotropy and anharmonicity. To accomplish this work, we combined i) single-crystal growth of key material systems with tunable anisotropy, ii) in-situ high-temperature/high-pressure characterization of structure and phonons to probe bonding anisotropy and anharmonicity, including state-of-the-art inelastic X-ray scattering (IXS) and inelastic neutron scattering (INS), and iii) first-principles simulations leveraging large-scale computing to identify the fundamental origins of the observed effects, by relating atomic structure and dynamics to electronic orbital interactions. Finally, we modeled and verified the impact of the phonon behavior on thermal transport to identify new strategies for a-priori design of thermal conductivity. Our integrated collaborative approach helped to systematically unravel the effects of anisotropy and bonding anharmonicity on phonon transport, thermodynamics, and thermal properties of complex anisotropic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Variations in proton transfer pathways and energetics on pristine and defect-rich quartz surfaces in water: Insights into the bimodal acidities of quartz

Hypothesis. Understanding the mechanisms of proton transfer on quartz surfaces in water is critical for a range of processes in geochemical, environmental, and materials sciences. The wide range of surface acidities (>9 pKa units) found on the ubiquitous mineral quartz is caused by the structural variations of surface silanol groups. Molecular scale simulations provide essential tools for elucidating the origin of site-specific surface acidities. Simulations. Here, we used density-functional tight-binding-based molecular dynamics combined with rare-event metadynamics simulations to probe the mechanisms of deprotonation reactions from ten representative surface silanol groups found on both pristine and defect-rich quartz (1 0 1) surfaces with Si vacancies. Findings. The results show that deprotonation is a highly dynamic process where both the surface hydroxyls and bridging oxygen atoms serve as the proton acceptors, in addition to water. Deprotonation of embedded silanols through intrasurface proton transfer exhibited lower pKa values with less H-bond participation and higher energy barriers, suggesting a new mechanism to explain the bimodal acidity observed on quartz surface. Defect sites, recently shown to comprise a significant portion of the quartz (1 0 1) surface, diversify the coordination and local H-bonding environments of the surface silanols, changing both the deprotonation pathways and energetics, leading to a wider range of pKa values (2.4 to 11.5) than that observed on pristine quartz surface (10.4 and 12.1).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Solution Structure and Scaling Laws of Cylindrical and Tapered Bottlebrush Polymers

Bottlebrush polymers are a unique class of macromolecular architectures with a plethora of potential industrial and pharmaceutical applications that critically depend on the bottlebrush shape and dimensions. Here, a systematic series of 12 cylindrical and 12 cone-shaped (tapered) bottlebrush polymers with poly(tert-butyl acrylate) (PtBA) or polystyrene (PS) side chains were synthesized using the sequential addition of macromonomers ring-opening metathesis polymerization (SAM-ROMP) grafting-through method. Small-angle neutron scattering (SANS) studies on dilute solutions of the two types of bottlebrush polymers provided noninvasive characterization of their structural dimensions and chain conformations. Simulated SANS traces, generated using coarse-grained molecular dynamics simulations, reproduced the distinctive features observed in the experimental SANS signals and provided necessary validation for data modeling. The combined analysis of experimental and simulated SANS signals yielded key structural and conformational parameters, including the bottlebrush radius, length, and Kuhn length as well as the excluded volume parameter and the correlation length of the polymer side chains. Importantly, the obtained structural parameters followed well-defined scaling laws as a function of the backbone and side chain degrees of polymerization, as predicted by mean field theories. In conclusion, these findings provide clear experimental and computational evidence of the interdependence of structural and conformational properties in an important class of polymer architectures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Surface Dynamics of Selective Hydration of Rutile TiO 2 : A Kinetic Monte Carlo Approach

The utility of atomic layer deposition (ALD) continues to expand beyond conformal thin-film fabrication to include area- or site-selective ALD. We previously identified a strategy for site-selective ALD (SS-ALD) via the evaluation of thermodynamically preferred hydration of rutile TiO 2 surfaces, as deduced from electronic structure calculations. Here, we report a novel kinetic Monte Carlo (KMC) model that allows for the investigation of surface dynamics and kinetics that improves our understanding of and intuition for the selective hydration strategy. Here we demonstrate the validity of the strategy with respect to step-edge defects for the lowest energy (110) facet as well as report results for the other common facets which agree with experimental STM observations. The results here indicate that the selective hydration strategy is feasible both thermodynamically (evaluated in our previous publication) and kinetically (from the KMC model). Because diffusion has a slower rate than others, we find that any proximity effects between terrace and defect sites are unlikely to affect the selective hydration strategy for rutile TiO 2 . The KMC model further provides relevant timescales for achieving selectivity experimentally and establishes the kinetic viability of the selective hydration approach to SS-ALD.

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

Molecular dynamics on quantum annealers

Abstract In this work we demonstrate a practical prospect of using quantum annealers for simulation of molecular dynamics. A methodology developed for this goal, dubbed Quantum Differential Equations (QDE), is applied to propagate classical trajectories for the vibration of the hydrogen molecule in several regimes: nearly harmonic, highly anharmonic, and dissociative motion. The results obtained using the D-Wave 2000Q quantum annealer are all consistent and quickly converge to the analytical reference solution. Several alternative strategies for such calculations are explored and it was found that the most accurate results and the best efficiency are obtained by combining the quantum annealer with classical post-processing (greedy algorithm). Importantly, the QDE framework developed here is entirely general and can be applied to solve any system of first-order ordinary nonlinear differential equations using a quantum annealer.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Excess Density as a Descriptor for Electrolyte Solvent Design

Electrolytes mediate interactions between the cathode and anode and determine performance characteristics of batteries. Mixtures of multiple solvents are often used in electrolytes to achieve desired properties, such as viscosity, dielectric constant, boiling point, and melting point. Conventionally, multi-component electrolyte properties are approximated with linear mixing, but in practice, significant deviations are observed. Excess quantities can provide insights into the molecular behavior of the mixture and could form the basis for designing high-performance electrolytes. Here we investigate the excess density of commonly used Li-ion battery solvents such as cyclic carbonates, linear carbonates, ethers, and nitriles with molecular dynamics simulations. We additionally investigate electrolytes consisting of these solvents and a salt. The results smoothly vary with mole percent and are fit to permutation-invariant Redlich-Kister polynomials. Mixtures of similar solvents, such as cyclic-cyclic carbonate mixtures, tend to have excess properties that are lower in magnitude compared to mixtures of dissimilar substances, such as carbonate-nitrile mixtures. We perform experimental testing using our automated test stand, Clio, to provide validation to the observed simulation trends. We quantify the structure similarity using SOAP fingerprints to create a descriptor for excess density, enabling the design of electrolyte properties. To a first approximation, this will allow us to estimate the deviation of a mixture from ideal behavior based solely upon the structural dissimilarity of the components.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Quantum phases of Rydberg atoms on a kagome lattice

Significance Programmable quantum simulators based on Rydberg atom arrays have recently emerged as versatile platforms for exploring exotic many-body phases and quantum dynamics of strongly correlated systems. In this work, we theoretically investigate the quantum phases that can be realized by arranging such Rydberg atoms on a kagome lattice. Along with an extensive analysis of the states which break lattice symmetries due to classical correlations, we identify an intriguing regime that constitutes a promising candidate for hosting a phase with long-range quantum entanglement and topological order. Our results provide a route to experimentally realizing and probing highly entangled quantum matter.

74 ATOMIC AND MOLECULAR PHYSICS↗
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 OSTI2023

Impact of Soret effect on hydrogen and helium retention in PFC tungsten under ELM-like conditions

Abstract In our previous work, we have demonstrated using nonequilibrium molecular-dynamics simulations that the fluxes of helium and self-interstitial atoms in the presence of a thermal gradient in tungsten are directed opposite to the heat flux, indicating that species transport is governed by a Soret effect, namely, thermal-gradient-driven diffusion, characterized by a negative heat of transport that drives species transport uphill, i.e. from the cooler to the hot regions of the tungsten sample. In this work, the findings of our thermal and species transport analysis have been implemented in our cluster-dynamics code, Xolotl, which has been used to compute temperature and species profiles over spatiotemporal scales representative of plasma-facing component (PFC) tungsten under typical reactor operating conditions, including extreme heat loads at the plasma-facing surface characteristic of plasma instabilities that induce edge localized modes (ELMs). We demonstrate that the steady-state species profiles, when properly accounting for the Soret effect, vary significantly from those where temperature-gradient-driven transport is not accounted for and discuss the implications of such a Soret effect on the response to plasma exposure of plasma-facing tungsten. Although our cluster-dynamics simulations do not yet include self-clustering of helium or hydrogen blister formation, our simulation results show that the Soret effect substantially reduces helium and hydrogenic species retention inside PFC tungsten.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The Single Residue K12 Governs the Exceptional Voltage Sensitivity of Mitochondrial Voltage-Dependent Anion Channel Gating

The voltage-dependent anion channel (VDAC) is a β-barrel channel of the mitochondrial outer membrane (MOM) that passively transports ions, metabolites, polypeptides, and single-stranded DNA. VDAC responds to a transmembrane potential by “gating,” i.e. transitioning to one of a variety of low-conducting states of unknown structure. The gated state results in nearly complete suppression of multivalent mitochondrial metabolite (such as ATP and ADP) transport, while enhancing calcium transport. Voltage gating is a universal property of β-barrel channels, but VDAC gating is anomalously sensitive to transmembrane potential. Here, we show that a single residue in the pore interior, K12, is responsible for most of VDAC’s voltage sensitivity. Using the analysis of over 40 μs of atomistic molecular dynamics (MD) simulations, we explore correlations between motions of charged residues inside the VDAC pore and geometric deformations of the β-barrel. Residue K12 is bistable; its motions between two widely separated positions along the pore axis enhance the fluctuations of the β-barrel and augment the likelihood of gating. Single channel electrophysiology of various K12 mutants reveals a dramatic reduction of the voltage-induced gating transitions. The crystal structure of the K12E mutant at a resolution of 2.6 Å indicates a similar architecture of the K12E mutant to the wild type; however, 60 μs of atomistic MD simulations using the K12E mutant show restricted motion of residue 12, due to enhanced connectivity with neighboring residues, and diminished amplitude of barrel motions. We conclude that β-barrel fluctuations, governed particularly by residue K12, drive VDAC gating transitions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Molecular Dynamics Simulation of the Structures, Dynamics, and Aggregation of Dissolved Organic Matter

Dissolved organic matter (DOM) plays a significant role in the transport and transformation of pollutants in the aquatic environment. However, the experimental characterization of DOM has been limited mainly to bulk properties, and the molecular-level interactions among various components of DOM remain to be fully characterized. In this study, we use molecular dynamics (MD) simulations to probe the structural properties of model DOM systems at atomic detail. The 200 ns simulations, validated by available experimental data, reveal processes and mechanisms by which chemical species (cations, peptides, lipids, lignin, carbohydrates, and some low-molecular-weight aliphatic and aromatic compounds) aggregate to form complex DOM. The DOM aggregates are dynamic, consisting of a hydrophobic core and amphiphilic exterior. The lipid tails and other hydrophobic fragments form the core, with hydrophilic and amphiphilic groups exposed to water, making DOM accessible to both polar and nonpolar species. Thus, the lipid component acts as a nucleator, whereas cations (especially Ca 2+ ) connect the molecular fragments on the surface by coordinating with the O-containing functional groups of DOM. The structural details revealed here provide new insights including surface accessible atoms, overall assemblage, and interactions among the molecules of DOM for understanding the kinetics and mechanisms through which DOM interacts with metal and other contaminants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Physics-assisted Latent Space Dynamics Learning for Stiff Collisional-radiative Models

Collisional-radiative (CR) models describe the atomic processes in a plasma by tracking the population density in the ground and excited states for each charge state of the atom/ion. These models predict important plasma properties such as charge state distributions and radiative emissivity and opacity. Accurate descriptions of the CR balance of the plasma are essential in fusion whole device modeling, especially when significant impurities are introduced into the plasmas. In an integrated fusion plasma and CR simulation, a CR model, which is a high-dimensional stiff ODE, needs to be solved on each grid point in the configuration space, and can overwhelm the overall computational cost. In this work, we propose a machine-learning-based method that discovers a latent space and learns its corresponding latent dynamics, which can capture the essential physics to make accurate predictions at much lower online computational cost. The proposed approach is physics-assisted, due to its combination of a physical latent space and a data-driven latent space. It has been demonstrated that the proposed architecture can predict both the full-order CR dynamics and a physical quantity of interest accurately.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Mass-selected ion–molecule cluster beam apparatus for ultrafast photofragmentation studies

We describe an apparatus for investigating the excited-state dissociation dynamics of mass-selected ion–molecule clusters by mass-resolving and detecting photofragment-ions and neutrals, in coincidence, using an ultrafast laser operating at high repetition rates. The apparatus comprises a source that generates ion–molecule clusters, a time-of-flight spectrometer, and a mass filter that selects the desired anions, and a linear-plus-quadratic reflectron mass spectrometer that discriminates the fragment anions after the femtosecond laser excites the clusters. The fragment neutrals and anions are then captured by two channeltron detectors. The apparatus performance is tested by measuring the photofragments: I – , CF 3 I – , and neutrals from photoexcitation of the ion–molecule cluster CF 3 I·I – using femtosecond UV laser pulses with a wavelength of 266 nm. Here, the experimental results are compared with our ground state and excited state electronic structure calculations as well as the existing results and calculations, with particular attention to the generation mechanism of the anion fragments and dissociation channels of the ion–molecule cluster CF 3 I·I – in the charge-transfer excited state.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

Mapping valence electron distributions with multipole density formalism using 4D-STEM

Recent advancement in aberration correction and detector technology opened a door to various applications using 4D-STEM, which yields a diffraction pattern for each scanning position within a crystal unit-cell in scanning transmission electron microscopy (STEM) and generates incredible amounts of data in momentum space. Currently 4D-STEM analysis relies on the center-of-mass of the diffraction patterns in electric field and charge density mapping. It only derives the total projected charge density and is limited to phase objects, e.g. extremely thin samples. Here, we propose a new analytical method to accurately map aspherical valence electron distributions with atom-centered multipolar functions formalism using the whole 4D-STEM dataset. We demonstrate that, with the full dynamical calculations for various sample thicknesses, the method is sensitive not only to the miniscule charge transfer, but also to the atomic site symmetry and aspherical electron orbitals. The process of the refinement is much more robust and reliable than quantitative convergent beam electron diffraction.

4D-STEM↗
DOE OSTI2022

High resolution atomic force microscopy with an active piezoelectric microcantilever

Active microcantilevers with on-chip sensing and actuation provide significant advantages in tapping mode Atomic Force Microscopy (AFM). Collocated transduction allows for effective manipulation of cantilever dynamics through feedback control, enabling higher scan rates. However, the adjacency of the sensing and actuation electrodes is known to result in a high level of feedthrough, leading to a low imaging resolution. Readout circuit noise further deteriorates the imaging precision. Here, we investigate the noise sources that affect AFM microcantilevers with collocated aluminum nitride (AlN) actuator–sensor pairs. We reported these cantilevers in earlier work and demonstrated that they display a very low level of feedthrough between the actuation and sensing electrodes. We present a high signal-to-noise ratio (SNR) sensing method that enables us to demonstrate high-resolution AFM on a calibration grating with nm-step silicon carbide (SiC) terraces. In conclusion, measuring the Lorentzian response of the cantilever’s Brownian motion with the on-chip active sensor at resonance enables us to calibrate the dynamic stiffness at the first fundamental resonance mode, without utilizing an optical sensor.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

ELECTRONIC STRUCTURE METHODS AND PROTOCOLS WITH APPLICATION TO DYNAMICS, KINETICS AND THERMOCHEMISTRY

Hydrocarbon combustion involves the reaction dynamics of a tremendous number of species beginning with many-component fuel mixtures and proceeding via a complex system of intermediates to form primary and secondary products. Combustion conditions corresponding to new advanced engines and/or alternative fuels rely increasingly on autoignition and low-temperature-combustion chemistry. In these regimes various transient radical species such as HO2, ROO·, ·QOOH, HCO, NO2, HOCO, and Criegee intermediates play important roles in determining the detailed as well as more general dynamics. A clear understanding and accurate representation of these processes is needed for effective modeling. Given the difficulties associated with making reliable experimental measurements of these systems, computation can play an important role in developing these energy technologies. Accurate calculations have their own challenges since even within the simplest dynamical approximations such as transition state theory, the rates depend exponentially on critical barrier heights and these may be sensitive to the level of quantum chemistry. Moreover, it is well-known that in many cases it is necessary to go beyond statistical theories and consider the dynamics. Quantum tunneling, resonances, radiative transitions, and non-adiabatic effects governed by spin-orbit or derivative coupling can be determining factors in those dynamics. Building upon progress made during a period of prior support through the DOE Early Career Program, this project combines developments in the areas of potential energy surface (PES) fitting and multistate multireference quantum chemistry to allow spectroscopically and dynamically/kinetically accurate investigations of key molecular systems (such as those mentioned above), many of which are radicals with strong multireference character and have the possibility of multiple electronic states contributing to the observed dynamics. An ongoing area of investigation is to develop general strategies for robustly convergent electronic structure theory for global multichannel reactive surfaces including diabatization of energy and other relevant surfaces such as dipole transition. Combining advances in ab initio methods with automated interpolative PES fitting allows the construction of high-quality PESs (incorporating thousands of high-level data) to be done rapidly through parallel processing on high-performance computing (HPC) clusters. In addition, new methods and approaches to electronic structure theory will be developed and tested through applications. This project will explore limitations in traditional multireference calculations (e.g., MRCI) such as those imposed by internal contraction, lack of high-order correlation treatment and poor scaling. Methods such as DMRG-based extended active-space CASSCF and various Quantum Monte Carlo (QMC) methods will be applied (including VMC/DMC and FCIQMC). Insight into the relative significance of different orbital spaces and the robustness of application of these approaches on leadership class computing architectures will be gained. Synergy with other components of this research program such as automated PES fitting and multireference quantum chemistry will be used to address challenges encountered by the standard approaches to computational thermochemistry (those being single-reference quantum chemistry and perturbative treatments of the anharmonic vibrational energy, which break down for some cases of electronic structure or floppy strongly coupled vibrational modes).

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Molecular dynamics simulation of metallic Al–Ce liquids using a neural network machine learning interatomic potential

Al-rich Al-Ce alloys have the possibility of replacing heavier steel and cast-irons for use in high-temperature applications. Knowledge about the structures and properties of Al-Ce alloys at liquid state is vital for optimizing the manufacture process to produce desired allows. However, reliable molecular dynamics simulation of Al-Ce alloy systems remains a great challenge due to the lack of accurate Al-Ce interatomic potential. In this work, an artificial neural network (ANN) deep machine learning (ML) method is used to develop a reliable interatomic potential for Al-Ce alloy. Ab initio molecular dynamics (AIMD) simulation data on Al-Ce liquid with small unit cell (~200 atoms) and on the known Al-Ce crystalline compounds are collected to train the interatomic potential using ANN-ML. The obtained ANN-ML model reproduces well the energies, forces, and atomic structure of Al 90 Ce 10 liquid and crystalline phases of Al-Ce compounds in comparison with ab initio results. The developed ANN-ML potential is applied in molecular dynamics simulations to study the structures and properties of metallic Al 90 Ce 10 liquid, which would provide useful insight for guiding experimental process to produce desired Al-Ce allows.

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

Accurate and scalable graph neural network force field and molecular dynamics with direct force architecture

Abstract Recently, machine learning (ML) has been used to address the computational cost that has been limiting ab initio molecular dynamics (AIMD). Here, we present GNNFF, a graph neural network framework to directly predict atomic forces from automatically extracted features of the local atomic environment that are translationally-invariant, but rotationally-covariant to the coordinate of the atoms. We demonstrate that GNNFF not only achieves high performance in terms of force prediction accuracy and computational speed on various materials systems, but also accurately predicts the forces of a large MD system after being trained on forces obtained from a smaller system. Finally, we use our framework to perform an MD simulation of Li 7 P 3 S 11 , a superionic conductor, and show that resulting Li diffusion coefficient is within 14% of that obtained directly from AIMD. The high performance exhibited by GNNFF can be easily generalized to study atomistic level dynamics of other material systems.

Chemistry↗