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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Theoretical Modeling of Electrochemical Proton-Coupled Electron Transfer

Proton-coupled electron transfer (PCET) plays an essential role in a wide range of electrocatalytic processes. Here, a vast array of theoretical and computational methods have been developed to study electrochemical PCET. These methods can be used to calculate redox potentials and pKa values for molecular electrocatalysts, proton-coupled redox potentials and bond dissociation free energies for PCET at metal and semiconductor interfaces, and reorganization energies associated with electrochemical PCET. Periodic density functional theory can also be used to compute PCET activation energies and perform molecular dynamics simulations of electrochemical interfaces. Various approaches for maintaining a constant electrode potential in electronic structure calculations and modeling complex interactions in the electric double layer (EDL) have been developed. Theoretical formulations for both homogeneous and heterogeneous electrochemical PCET spanning the adiabatic, nonadiabatic, and solvent-controlled regimes have been developed and provide analytical expressions for the rate constants and current densities as functions of applied potential. The quantum mechanical treatment of the proton and inclusion of excited vibronic states have been shown to be critical for describing experimental data, such as Tafel slopes and potential dependent kinetic isotope effects. The calculated rate constants can be used as input to microkinetic models and voltammogram simulations to elucidate complex electrocatalytic processes.

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

QM Investigation of Rare Earth Ion Interactions with First Hydration Shell Waters and Protein-Based Coordination Models

Here, conventional methods for extracting rare earth metals (REMs) from mined mineral ores are inefficient, expensive, and environmentally damaging. Recent discovery of lanmodulin (LanM), a protein that coordinates REMs with high-affinity and selectivity over competing ions, provides inspiration for new REM refinement methods. Here, we used quantum mechanical (QM) methods to investigate trivalent lanthanide cation (Ln 3+ ) interactions with coordination systems representing bulk solvent water and protein binding sites. Energy decomposition analysis (EDA) showed differences in the energetic components of Ln 3+ interaction with representatives of solvent (water, H 2 O) and protein binding sites (acetate, CH 3 COO – ), highlighting the importance of accurate description of electrostatics and polarization in computational modeling of REM interactions with biological and bioinspired molecules. Relative binding free energies were obtained for Ln 3+ with coordination complexes originating from binding sites in PDB structures of a lanthanum binding peptide (PDB entry 7CCO) and LanM, with explicit consideration of the first hydration shell waters, according to quasi-chemical theory (QCT). Beyond the first shell, the bulk solvent environment was represented with an implicit continuum model. Ln 3+ interactions with (H 2 O) 9 and both binding site models became more favorable, moving down the periodic series. This trend was more pronounced with the protein binding site models than with water, resulting in affinity increasing with periodic number, except for the last REM, Lu 3+ , which bound less favorably than the preceding element, Yb 3+ . Using the truncated 7CCO binding site model, the magnitude and trend of the experimental Ln 3+ relative binding free energies for the whole 7CCO peptide were reproduced. Conversely, the previously reported experimental data for LanM show a preference for the earlier lanthanides; this is likely due to longer-range interactions and cooperative effects, which are not represented by the reduced models. Using the truncated 7CCO binding site model, the magnitude and trend of the experimental Ln 3+ relative binding free energies for the whole 7CCO peptide were reproduced. In contrast to the previously reported experimental data for LanM, the peptide preferentially binds the earlier lanthanides. This difference likely arises due to longer-range interactions and cooperative effects not represented by the peptide. Further investigation of Ln 3+ interactions with whole proteins using polarizable molecular mechanics models with explicit solvent is warranted to understand the influence of longer-ranged interactions, cooperativity, and bulk solvent. Nevertheless, the present work provides new insights into Ln 3+ interactions with biomolecules and presents an effective computational platform for designing specific single-site REM binding peptides more efficiently.

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

Upscaling Reactive Transport and Clogging in Shale Microcracks by Deep Learning

Fracture networks in shales exhibit multiscale features. A rock system may contain a few main fractures and thousands of microcracks, whose length and aperture are orders of magnitude smaller than the former. It is computationally prohibitive to resolve all the fractures explicitly for such multiscale fracture networks. One traditional approach is to model the small-scale features (e.g., microcracks in shales) as an effective medium. Although this fracture-matrix conceptualization significantly reduces the problem complexity, there are classes of physical processes that cannot be accurately upscaled by effective medium approximations, e.g., microcrack clogging during mineral reactions. Here, we employ deep learning in place of effective medium theory to upscale physical processes in small-scale features. Specifically, we consider reactive transport in a fracture-microcrack network where microcracks can be clogged by precipitation. A deep learning multiscale algorithm is developed, in which the microcracks are upscaled as a wall boundary condition of the main fractures. The wall boundary condition is constructed by recurrent neural networks, which take concentration histories as input and predict the solute transport from main fractures to microcracks. The deep learning multiscale algorithm is firstly employed in specific scenarios, then a general model is developed which can work under various conditions. The new approach is validated against fully resolved simulations and an analytical solution, providing a reliable and efficient solution for problems that cannot be upscaled by effective medium models.

58 GEOSCIENCES↗
DOE OSTI2021

Probing the thermodynamics and kinetics of ethylene carbonate reduction at the electrode–electrolyte interface with molecular simulations

Understanding the formation of the solid-electrolyte interphase (SEI) in lithium-ion batteries (LIBs) is an ongoing area of research due to its high degree of complexity and the difficulties encountered by experimental studies. Herein, we investigate the initial stage of SEI growth, the reduction reaction of ethylene carbonate (EC), from both a thermodynamic and kinetic approach with theory and molecular simulation. We employed both the potential distribution theorem (PDT) and the SMD implicit solvent model to EC solvation for the estimation of reduction potentials of Li$^+$, EC, and Li$^+$-solvating EC (s-EC), as well as reduction rate constants of EC and s-EC. We find that solvation effects greatly influence these quantities of interest, particularly the Li$^+$/Li reference electrode potential in EC solvent. Further, we also compute the inner- and outer-sphere reorganization energies for both EC and s-EC at the interface of liquid EC and a hydroxyl-terminated graphite surface, where total reorganization energies are predicted to be 76.6 and 88.9 kcal/mol, respectively. With the computed reorganization energies, we estimate reduction rate constants across a range of overpotentials and show that EC has a larger electron transfer rate constant than s-EC at equilibrium, despite s-EC being more thermodynamically favorable. Furthermore, this manuscript demonstrates how ion solvation effects largely govern the prediction of reduction potentials and electron transfer rate constants at the electrode-electrolyte interface.

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

Properties of the neutron star crust: Quantifying and correlating uncertainties with improved nuclear physics

A compressible liquid-drop model (CLDM) is used to correlate uncertainties associated with the properties of the neutron star (NS) crust with theoretical estimates of the uncertainties associated with the equation of state (EOS) of homogeneous neutron and nuclear matter. For the latter, we employ recent calculations based on Hamiltonians constructed using chiral effective-field theory (χEFT). Fits to experimental nuclear masses are employed to constrain the CLDM further, and we find that they disfavor some of the χEFT Hamiltonians. The CLDM allows us to study the complex interplay between bulk, surface, curvature, and Coulomb contributions, and their impact on the NS crust. It also reveals how the curvature energy alters the correlation between the surface energy and the bulk symmetry energy. Here our analysis quantifies how the uncertainties associated with the EOS of homogeneous matter implies significant uncertainties for the composition of the crust, its proton fraction, and the volume fraction occupied by nuclei. We find that the finite-size effects impact the crust composition but have a negligible effect on the net isospin asymmetry of matter. The isospin asymmetry is largely determined by the bulk properties and the isospin dependence of the surface energy. The most significant uncertainties associated with matter properties in the densest regions of the crust, the precise location of the crust-core transition, are found to be strongly correlated with uncertainties associated with the Hamiltonians. By adopting a unified model to describe the crust and the core of NSs, we tighten the correlation between their global properties such as their mass-radius relationship, moment of inertia, crust thickness, and tidal deformability with uncertainties associated with the nuclear Hamiltonians.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Autoregressive Neural Network for Simulating Open Quantum Systems via a Probabilistic Formulation

The theory of open quantum systems lays the foundation for a substantial part of modern research in quantum science and engineering. Rooted in the dimensionality of their extended Hilbert spaces, the high computational complexity of simulating open quantum systems calls for the development of strategies to approximate their dynamics. In this Letter, we present an approach for tackling open quantum system dynamics. Using an exact probabilistic formulation of quantum physics based on positive operator-valued measure, we compactly represent quantum states with autoregressive neural networks; such networks bring significant algorithmic flexibility due to efficient exact sampling and tractable density. We further introduce the concept of string states to partially restore the symmetry of the autoregressive neural network and improve the description of local correlations. Efficient algorithms have been developed to simulate the dynamics of the Liouvillian superoperator using a forward-backward trapezoid method and find the steady state via a variational formulation. Our approach is benchmarked on prototypical one-dimensional and two-dimensional systems, finding results which closely track the exact solution and achieve higher accuracy than alternative approaches based on using Markov chain Monte Carlo method to sample restricted Boltzmann machines. Our Letter provides general methods for understanding quantum dynamics in various contexts, as well as techniques for solving high-dimensional probabilistic differential equations in classical setups.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Integrated System and Application Continuous Performance Monitoring and Analysis Capability

Scientific applications run on high-performance computing (HPC) systems are critical for many national security missions within Sandia and the NNSA complex. However, these applications often face performance degradation and even failures that are challenging to diagnose. To provide unprecedented insight into these issues, the HPC Development, HPC Systems, Computational Science, and Plasma Theory & Simulation departments at Sandia crafted and completed their FY21 ASC Level 2 milestone entitled "Integrated System and Application Continuous Performance Monitoring and Analysis Capability." The milestone created a novel integrated HPC system and application monitoring and analysis capability by extending Sandia's Kokkos application portability framework, Lightweight Distributed Metric Service (LDMS) monitoring tool, and scalable storage, analysis, and visualization pipeline. The extensions to Kokkos and LDMS enable collection and storage of application data during run time, as it is generated, with negligible overhead. This data is combined with HPC system data within the extended analysis pipeline to present relevant visualizations of derived system and application metrics that can be viewed at run time or post run. This new capability was evaluated using several week-long, 290-node runs of Sandia's ElectroMagnetic Plasma In Realistic Environments ( EMPIRE ) modeling and design tool and resulted in 1TB of application data and 50TB of system data. EMPIRE developers remarked this capability was incredibly helpful for quickly assessing application health and performance alongside system state. In short, this milestone work built the foundation for expansive HPC system and application data collection, storage, analysis, visualization, and feedback framework that will increase total scientific output of Sandia's HPC users.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Integrated System and Application Continuous Performance Monitoring and Analysis Capability (Final)

Scientific applications run on high-performance computing (HPC) systems are critical for many national security missions within Sandia and the NNSA complex. However, these applications often face performance degradation and even failures that are challenging to diagnose. To provide unprecedented insight into these issues, the HPC Development, HPC Systems, Computational Science, and Plasma Theory & Simulation departments at Sandia crafted and completed their FY21 ASC Level 2 milestone entitled "Integrated System and Application Continuous Performance Monitoring and Analysis Capability." The milestone created a novel integrated HPC system and application monitoring and analysis capability by extending Sandia’s Kokkos application portability framework, Lightweight Distributed Metric Service (LDMS) monitoring tool, and scalable storage, analysis, and visualization pipeline. The extensions to Kokkos and LDMS enable collection and storage of application data during run time, as it is generated, with negligible overhead. This data is combined with HPC system data within the extended analysis pipeline to present relevant visualizations of derived system and application metrics that can be viewed at run time or post run. This new capability was evaluated using several week-long, 290-node runs of Sandia’s ElectroMagnetic Plasma In Realistic Environments (EMPIRE) modeling and design tool and resulted in 1TB of application data and 50TB of system data. EMPIRE developers remarked this capability was incredibly helpful for quickly assessing application health and performance alongside system state. In short, this milestone work built the foundation for expansive HPC system and application data collection, storage, analysis, visualization, and feedback framework that will increase total scientific output of Sandia’s HPC users.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Understanding Twinning and Deformation in High Entropy Alloys

A combination of high strength and high ductility has been observed in multi-principal element alloys due to twin formation attributed to low stacking fault energy (SFE). In the pursuit of low SFE alloys, a key bottleneck is the lack of understanding of the composition–SFE cor- relations that would guide tailoring SFE via alloy composition. Using density functional theory (DFT), we show that dopant radius, which have been postulated as a key descriptor for SFE in dilute alloys, does not fully explain SFE trends across different host metals. Instead, charge density is a much more central descriptor. It allows us to (1) explain contrasting SFE trends in Ni and Cu host metals due to various dopants in dilute concentrations, (2) explain the large SFE variations observed in the literature even within a given alloy composition due to the nearest neighbor environments in “model” concentrated alloys, and (3) develop a machine learning model that can be used to predict SFEs in multi-elemental alloys. This model opens a possibility to use charge density as a descriptor for predicting SFE in alloys. Furthermore, a descriptor-less machine learning (ML) model based only on charge density images extracted from density functional theory (DFT) is developed to predict stacking fault energies (SFE) in concentrated alloys. The model is based on convolutional neural networks (CNNs) as one of the promising ML techniques for dealing with complex images and data. Identification of correct descriptors is a key bottleneck to develop ML models for predicting materials properties. Often, in most ML models, textbook physical descriptors such as atomic radius, valence charge and electronegativity are used as descriptors which have limitations because these properties change in concentrated alloys when multiple elements are mixed to form a solid solution. We illustrate that, within the scope of DFT, the search for descriptors can be circumvented by electronic charge density, which is the backbone of the Kohn-Sham DFT and describes the system completely. The performance of our model is demonstrated by predicting SFE of concentrated alloys with an RMSE and R2 of 6.18 mJ/m2 and 0.87, respectively, validating the accuracy of the proposed approach.

36 MATERIALS SCIENCE↗
NASA NTRS1978

Stirling engine design manual

This manual is intended to serve both as an introduction to Stirling engine analysis methods and as a key to the open literature on Stirling engines. Over 800 references are listed and these are cross referenced by date of publication, author and subject. Engine analysis is treated starting from elementary principles and working through cycles analysis. Analysis methodologies are classified as first, second or third order depending upon degree of complexity and probable application; first order for preliminary engine studies, second order for performance prediction and engine optimization, and third order for detailed hardware evaluation and engine research. A few comparisons between theory and experiment are made. A second order design procedure is documented step by step with calculation sheets and a worked out example to follow. Current high power engines are briefly described and a directory of companies and individuals who are active in Stirling engine development is included. Much remains to be done. Some of the more complicated and potentially very useful design procedures are now only referred to. Future support will enable a more thorough job of comparing all available design procedures against experimental data which should soon be available.

Martini, W. R.↗
NASA NTRS1985

Overview of Structural Response: Probabilistic Structural Analysis

Advanced analysis methods are required to predict accurately the structural response (static, transient, cyclic, etc.) and accompanying local stresses in space propulsion system components operating in a fatigue environment consisting of complex thermal and mechanical load spectra. The probabilistic approach to structural response consists of the following program elements: (1) composite load spectra, (2) probabilistic structural analysis methods development, (3) probabilitic finite element theory, (4) probabilistic structural analysis application, (5) structural tailoring of turbopump blades, (6) unified theory of dynamic creep buckling/ratcheting, (7) creep buckling/ratcheting analyzer, and (8) nonlinear COBSTRAN development. Research activities on all of these program elements (except the creep buckling/ratcheting analyzer) are under way.

Chamis, C. C.↗
NASA NTRS1986

The chemical composition of comets and possible contribution to planet composition and evolution

The theory of cold aggregation of interstellar dust into comets is shown to support the ideas that comets provided not only a substantial part of the earth's water but also of its complex organic surface material. Comparison of the density of interstellar dust with meteor densities leads to the conclusion that comets are very fluffy bodies whose solid matter occupies no more than 2/5 of the total volume and possibly substantially less. This implies an extremely low comet albedo of about 0.05 in the visual even for slightly absorbing individual components.

Greenberg, J. Mayo↗
NASA NTRS1989

Acoustic wave propagation in heterogeneous structures including experimental validation

A finite element model was developed to solve for the acoustic pressure and energy fields in a heterogeneous suppressor. The derivations from the governing equations assumed that the material properties could vary with position resulting in a heterogeneous variable property two-dimensional wave equation. This eliminated the necessity of finding the boundary conditions between different materials. For a two media region consisting of part air and part bulk absorber, a model was used to describe the bulk absorber properties in two directions. Complex metallic structures inside the air duct are simulated by simply changing element properties from air to the structural material in a pattern to describe the desired shapes. To verify the numerical theory, experiments were conducted without flow in a rectangular duct with a single folded cavity mounted above the duct and absorbing material mounted inside a cavity. Changes in a nearly plane wave sound field were measured on the wall opposite the absorbing cavity. Fairly good agreement was found in the standing wave pattern upstream of the absorber and in the decay of pressure level opposite the absorber, as a function of distance along the duct. The finite element model provides a convenient method for evaluating the acoustic properties of bulk absorbers.

Baumeister, Kenneth J.↗
NASA NTRS1989

Acoustic wave propagation in heterogeneous structures including experimental validation

A finite element model was developed to solve for the acoustic pressure and energy fields in a heterogeneous suppressor. The derivations from the governing equations assumed that the material properties could vary with position resulting in a heterogeneous variable property two-dimensional wave equation. This eliminated the necessity of finding the boundary conditions between different materials. For a two-media region consisting of part air and part bulk absorber, a model was used to describe the bulk absorber properties in two directions. Complex metallic structures inside the air duct are simulated by simply changing element properties from air to the structural material in a pattern to describe the desired shapes. To verify the numerical theory, experiments were conducted without flow in a rectangular duct with a single folded cavity mounted above the duct and absorbing material mounted inside a cavity. Changes in a nearly plane wave sound field were measured on the wall opposite the absorbing cavity. Fairly good agreement was found in the standing wave pattern upstream of the absorber and in the decay of pressure level opposite the absorber, as a function of distance along the duct. The finite element model provides a convenient method for evaluating the acoustic properties of bulk absorbers.

Baumeister, Kenneth J.↗
NASA NTRS1991

A review of fatigue crack growth analyses

Stress intensity factor range, Delta K, has been shown to correlate well with fatigue crack growth rate, da/dN. A number of fatigue crack growth theories have been developed for such correlations. Often, conjectory theories of fatigue crack growth are constructed from experimental data. On the other hand, fatigue crack growth theories can also be derived rigorously with deductive logic. Four such deductive theories are reviewed: (1) that for the growth of a small crack in a very wide homogeneous plate, (2) the theory of similitude for the correlation of da/dN with Delta K, (3) a theory of crack growth in homogeneous materials in small-scale yielding, and (4) the unzipping theory of fatigue crack growth. This paper synthesizes these four theories into a logic framework useful for fatigue crack growth analysis. The deductive theories and the conjectory theories complement each other in the advances of the understanding of fatigue crack growth. The applications of logic framework to formulating an overview of fatigue crack growth behavior and to defining the complex issues of the growth of small cracks and crack growth in composites are illustrated.

Liu, H. W.↗
NASA NTRS1993

An extended UTD analysis for the scattering and diffraction from cubic polynomial strips

Spline and polynomial type surfaces are commonly used in high frequency modeling of complex structures such as aircraft, ships, reflectors, etc. It is therefore of interest to develop an efficient and accurate solution to describe the scattered fields from such surfaces. An extended Uniform Geometrical Theory of Diffraction (UTD) solution for the scattering and diffraction from perfectly conducting cubic polynomial strips is derived and involves the incomplete Airy integrals as canonical functions. This new solution is universal in nature and can be used to effectively describe the scattered fields from flat, strictly concave or convex, and concave convex boundaries containing edges. The classic UTD solution fails to describe the more complicated field behavior associated with higher order phase catastrophes and therefore a new set of uniform reflection and first-order edge diffraction coefficients is derived. Also, an additional diffraction coefficient associated with a zero-curvature (inflection) point is presented. Higher order effects such as double edge diffraction, creeping waves, and whispering gallery modes are not examined. The extended UTD solution is independent of the scatterer size and also provides useful physical insight into the various scattering and diffraction processes. Its accuracy is confirmed via comparison with some reference moment method results.

Constantinides, E. D.↗
NASA NTRS1995

Wavenumber selection and hysteresis in nonlinear baroclinic flow

Wavenumber transition and hysteresis in a highly unstable baroclinic flow are investigated using a high-resolution spectral numerical model. As the flow becomes more supercritical, the dominant wave gradually shifts from the most unstable wave predicted by the linear theory to a longer wave with a larger time-averaged amplitude, while the rectified mean flow attains a stronger shear at the center of the channel. The numerical results display a complex hysteresis behavior, which occurs not only between the states of different dominant wavenumbers, but also between the states of identical dominant wavenumber but of different dynamic characteristics. In a certain parameter range three stable states, each with different dominant wavenumber, are possible, and in another parameter range four stable states are possible, among them three stable states with an identical dominant wave. The numerical results suggest that a multiple weather regime exists even without external forcing in which the flow aperiodically varies between two distinct behaviors. The effects of stable higher harmonics are assessed and it is found that their presence contributes not only to the better approximation of the model solutions but also to the selection of the final equilibrium state, due to the chaotic nature of the initial transient period.

Chou, Shih-Hung↗
NASA NTRS1997

Theoretical Characterization of the NNO...O3 and NNO...O Complexes

The bonding mechanisms and bond strengths of complexes between two molecular and/or atomic species will be discussed. The implications of complex formation for stratospheric chemistry will be presented. Results of theoretical calculations on NNO ... O3 and NNO ...O will be used as specific examples to illustrate the principles of complex formation. The equilibrium structures and binding energies of these complexes will be presented as well as shifts in other molecular properties due to complexation, such as vibrational frequencies. Thermal dissociation rates will be presented. The theoretical methodology used in this study consists of high-level coupled-cluster calculations and more approximate density functional theory approaches, together with large one-particle basis sets.

Lee, Timothy J.↗