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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 OSTI2019

Systems and methods for determining optimal parameters for dynamic quantum clustering analyses

In the present work, quantum clustering is extended to provide a dynamical approach for data clustering using a time-dependent Schrodinger equation. To expedite computations, we can approximate the time-dependent Hamiltonian formalism by a truncated calculation within a set of Gaussian wave-functions (coherent states) centered around the original points. This allows for analytic evaluation of the time evolution of all such states, opening up the possibility of exploration of relationships among data points through observation of varying dynamical-distances among points and convergence of points into clusters. This formalism may be further supplemented by preprocessing, such as dimensional reduction through singular value decomposition and/or feature filtering. Additionally, the parameters of the analysis can be modified in order to improve the efficiency of the dynamic quantum clustering processes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Light-Promoted C(sp 3 )–C(sp 3 ) Reductive Elimination from Dialkyl NiII Complexes

Ni-catalyzed cross-coupling is a powerful strategy to forge C(sp 3 )–C(sp 3 ) bonds. Typically, to do so requires overcoming a challenging C–C bond-forming reductive elimination, often enabled by the intermediacy of highly oxidized Ni species or outer-sphere processes. While direct C(sp 3 )–C(sp 3 ) reductive elimination from the Ni II base oxidation state is normally thermally inaccessible, light-activation provides an avenue to affect such transformations. Here, we investigate the mechanism of light-induced C(sp 3 )–C(sp 3 ) bond formation from dialkyl bipyridine Ni II complexes through a variety of organometallic, spectroscopic, and computational studies. Wavelength-dependent quantum yields, ligand electronics–reactivity relationships, excited-state lifetimes, computed barriers, and product distributions from crossover studies support a photolysis/radical rebound mechanism. Furthermore, this reactivity paradigm complements existing strategies in the literature to promote reductive elimination from Ni II , such as the use of destabilizing, sterically hindered ligands and reduction of electron density at Ni through the binding of electron-deficient olefins. Hence, we envision that light-induced reductive elimination may enable the development of challenging C(sp 3 )–C(sp 3 ) couplings.

Alkyls↗
DOE OSTI2016

Assessment of Multi-Step CADIS Parameter Sensitivity to Neutron Flux Spectrum in Shutdown Dose Rate Calculations

Shutdown dose rate (SDDR) analysis requires (a) a neutron transport calculation to estimate neutron flux fields, (b) an activation calculation to compute radionuclide inventories and associated photon sources, and (c) a photon transport calculation to estimate final dose rate. In some applications, accurate full-scale Monte Carlo (MC) SDDR simulations are needed for very large systems with massive amounts of shielding materials. For example, SDDR assessments are required throughout the biological shield (bio-shield) of the ITER experimental facility to evaluate the required waiting period after the shutdown of ITER and to identify the locations where human accessibility should be prohibited. The bio-shield is a large cylindrical concrete structure (30 m tall and 34 m in diameter) surrounding the very complex tokamak machine. Determining the effects on SDDR of important factors, such as the cross talk (interactions) between the different ports of ITER, is possible only through full-scale simulations that involve all the complex inner details of the ITER tokamak machine. These simulations are impractical because calculation of space- and energy-dependent neutron fluxes throughout the structural materials is needed to estimate the distribution of radioisotopes causing the SDDR. Determining a good importance function that can be used in biasing a neutron MC calculation for SDDR is complicated because it is difficult to explicitly express the SDDR response function, which depends on subsequent computational steps. The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) hybrid MC/deterministic method was developed to speed up the SDDR MC neutron transport calculation using an importance function that represents the neutron importance to the final SDDR. The MS-CADIS method uses the CADIS method, which has been Notice: This manuscript has been authored by UT-Battelle, LLC, under Contract No. DE-AC0500OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for the United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). successfully used for more than a decade in radiation shielding applications to generate consistent source biasing and weight window (WW) variance reduction parameters to accelerate continuous-energy MC simulations. However, because MS-CADIS focuses on multi-step shielding calculations such as SDDR calculations, it develops an importance function for the initial radiation transport calculation (e.g., the neutron calculations in SDDR simulations) that represents the importance of particles to the final response of the overall simulation. To develop this importance function, the MS-CADIS method uses an adjoint calculation with a specific neutron adjoint source that represents the neutron's contribution to the final SDDR. Brute force calculation of the MS-CADIS neutron adjoint source requires a deterministic neutron transport calculation coupled with activation calculations in each element of the deterministic mesh. These calculations are needed to determine the MS-CADIS parameter for the neutron interactions that produce radioisotopes contributing to the SDDR. The MS-CADIS parameter is the microscopic cross section of the radioisotope-producing interaction, multiplied by the mass of this radioisotope existing at the end of the irradiation and decay scenario, and divided by the steady-state rate of the interaction. Because the activation calculations are performed for each radionuclide in each mesh element, implementation of the MS-CADIS method can be computationally expensive. However, these neutron transport and activation calculations are not needed if we assume that the radioisotopes are created due to single neutron interactions and their concentrations do not change as a result of burnup by neutron irradiation. The use of this approximation, which renders the MS-CADIS parameter independent of the neutron flux, seems reasonable in calculating the MS-CADIS importance function because this function is needed only to speed up the MC calculation, not to calculate the final SDDR. In this work, we investigate the validity of this approximation by investigating the behavior of the MS-CADIS parameter as a function of the neutron flux spectra in the Fusion Evaluated Nuclear Data Library (FENDL) Neutronics and Shielding Benchmark problem that contains representative isotopes and flux environments of fusion energy systems. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2017

FIVE YEARS OF SYNTHESIS OF SOLAR SPECTRAL IRRADIANCE FROM SDID/SISA AND SDO /AIA IMAGES

In this paper we describe the synthetic solar spectral irradiance (SSI) calculated from 2010 to 2015 using data from the Atmospheric Imaging Assembly (AIA) instrument, on board the Solar Dynamics Observatory spacecraft. We used the algorithms for solar disk image decomposition (SDID) and the spectral irradiance synthesis algorithm (SISA) that we had developed over several years. The SDID algorithm decomposes the images of the solar disk into areas occupied by nine types of chromospheric and 5 types of coronal physical structures. With this decomposition and a set of pre-computed angle-dependent spectra for each of the features, the SISA algorithm is used to calculate the SSI. We discuss the application of the basic SDID/SISA algorithm to a subset of the AIA images and the observed variation occurring in the 2010–2015 period of the relative areas of the solar disk covered by the various solar surface features. Our results consist of the SSI and total solar irradiance variations over the 2010–2015 period. The SSI results include soft X-ray, ultraviolet, visible, infrared, and far-infrared observations and can be used for studies of the solar radiative forcing of the Earth’s atmosphere. These SSI estimates were used to drive a thermosphere–ionosphere physical simulation model. Predictions of neutral mass density at low Earth orbit altitudes in the thermosphere and peak plasma densities at mid-latitudes are in reasonable agreement with the observations. The correlation between the simulation results and the observations was consistently better when fluxes computed by SDID/SISA procedures were used.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Sci-Thur AM: YIS – 06: A Monte Carlo study of macro- and microscopic dose descriptors and the microdosimetric spread using detailed cellular models

Purpose: To develop Monte Carlo models of cell clusters to investigate the relationships between macro- and microscopic dose descriptors, quantify the microdosimetric spread in energy deposition for subcellular targets, and determine how these results depend on the computational model. Methods: Microscopic tissue structure is modelled as clusters of 13 to 150 cells, with cell (nuclear) radii between 5 and 10 microns (2 and 9 microns). Energy imparted per unit mass (specific energy or dose) is scored in the nucleus (D{sub nuc}) and cytoplasm (D{sub cyt}) for incident photon energies from 20 to 370 keV. Dose-to-water (D{sub w,m}) and dose-to-medium (D{sub m,m}) are compared to D{sub nuc} and D{sub cyt}. Single cells and single nuclear cavities are also simulated. Results: D{sub nuc} and D{sub cyt} are sensitive to the surrounding environment with deviations of up to 13% for a single nucleus/cell compared with a multicellular cluster. These dose descriptors vary with cell and nucleus size by up to 10%. D{sub nuc} and D{sub cyt} differ from D{sub w,m} and D{sub m,m} by up to 32%. The microdosimetric spread is sensitive to whether cells are arranged randomly or in a hexagonal lattice, and whether subcellular compartment sizes are sampled from a normal distribution or are constant throughout the cluster. Conclusions: D{sub nuc} and D{sub cyt} are sensitive to cell morphology, elemental composition and the presence of surrounding cells. The microdosimetric spread was investigated using realistic elemental compositions for the nucleus and cytoplasm, and depends strongly on subcellular compartment size, source energy and dose.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Defect Diffusion Graph Neural Networks for Materials Discovery in High-Temperature Energy Applications

Here, the migration of crystallographic defects dictates material properties and performance for a plethora of technological applications. Density functional theory (DFT)-based nudged elastic band (NEB) calculations are a powerful computational technique for predicting defect migration activation energy barriers, yet they become prohibitively expensive for high-throughput screening of defect diffusivities. Without introducing hand-crafted (i.e., chemistry- or structure-specific) descriptors, we propose a generalized deep learning approach to train surrogate models for NEB energies of vacancy migration by hybridizing graph neural networks with transformer encoders and simply using pristine host structures as input. With sufficient training data, computationally efficient and simultaneous inference of vacancy defect thermodynamics and migration activation energies can be obtained to compute temperature-dependent vacancy diffusivities and to down-select candidates for more thorough DFT analysis or experiments. Thus, as we specifically demonstrate for potential water-splitting materials, candidates with desired defect thermodynamics, kinetics, and host stability properties can be more rapidly targeted from open-source databases of experimentally validated or hypothetical materials.

14 SOLAR ENERGY↗
DOE OSTI2018

A mesh-independent method for planar three-dimensional crack growth in finite domains: A mesh-independent method for crack growth in 3D finite domains

The discrete crack mechanics (DCM) method is a dislocation-based crack modeling technique where cracks are constructed using Volterra dislocation loops. The method allows for the natural introduction of displacement discontinuities, avoiding numerically expensive techniques. Mesh dependence in existing computational modeling of crack growth is eliminated by utilizing a superposition procedure. The elastic field of cracks in finite bodies is separated into two parts: the infinite-medium solution of discrete dislocations and an finite element method solution of a correction problem that satisfies external boundary conditions. In the DCM, a crack is represented by a dislocation array with a fixed outer loop determining the crack tip position encompassing additional concentric loops free to expand or contract. Solving for the equilibrium positions of the inner loops gives the crack shape and stress field. The equation of motion governing the crack tip is developed for quasi-static growth problems. Additionally, convergence and accuracy of the DCM method are verified with two- and three-dimensional problems with well-known solutions. Crack growth is simulated under load and displacement (rotation) control. In the latter case, a semicircular surface crack in a bent prismatic beam is shown to change shape as it propagates inward, stopping as the imposed rotation is accommodated.

42 ENGINEERING↗
DOE OSTI2026

Trigonometric continuous-variable gates and hybrid quantum simulations of the sine-Gordon model

Hybrid qubit-qumode quantum computing platforms provide a natural setting for simulating interacting bosonic quantum field theories. However, existing continuous-variable gate constructions rely predominantly on polynomial functions of canonical quadratures. In this work, we introduce a complementary universality paradigm based on trigonometric continuous-variable gates, which enable a Fourier-like representation of bosonic operators and are particularly well suited for periodic and non-perturbative interactions. We present an ancilla-based framework for implementing trigonometric gates with arguments given by arbitrary Hermitian functions of qumode quadratures. The protocol yields unitary gates deterministically, and non-unitary gates through probabilistic post-selection. As a concrete application, we develop a hybrid qubit-qumode quantum simulation of the lattice sine-Gordon model. Using these gates, we prepare ground states via quantum imaginary-time evolution, simulate real-time dynamics, compute time-dependent vertex two-point correlation functions, and extract quantum kink profiles under topological boundary conditions. Our results demonstrate that trigonometric continuous-variable gates provide a physically natural framework for simulating interacting field theories on near-term hybrid quantum hardware, while establishing a parallel route to universality beyond polynomial gate constructions. We expect that the trigonometric gates introduced here to find broader applications, including quantum simulations of condensed matter systems, quantum chemistry, and biological models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Running decompactification, sliding towers, and the distance conjecture

We study towers of light particles that appear in infinite-distance limits of moduli spaces of 9-dimensional $\mathcal{N}$ = 1 string theories, some of which notably feature decompactification limits with running string coupling. The lightest tower in such decompactification limits consists of the non-BPS Kaluza-Klein modes of Type I' string theory, whose masses depend nontrivially on the moduli of the theory. We work out the moduli-dependence by explicit computation, finding that despite the running decompactification the Distance Conjecture remains satisfied with an exponential decay rate α ≥ 1 / $\sqrt{d-2}$ in accordance with the sharpened Distance Conjecture. The related sharpened Convex Hull Scalar Weak Gravity Conjecture also passes stringent tests. Our results non-trivially test the Emergent String Conjecture, while highlighting the important subtlety that decompactifcation can lead to a running solution rather than to a higher-dimensional vacuum.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Graph neural networks for efficient learning of mechanical properties of polycrystals

Herein we present graph neural networks (GNNs) as an efficient and accurate machine learning approach to predict mechanical properties of polycrystalline materials. Here, a GNN was developed based on graph representation of polycrystals incorporating only fundamental features of grains including their crystallographic orientation, size, and grain neighbor connectivity information. We tested our method on modeling stiffness and yield strength of α -Ti microstructures, varying in their crystallographic texture. We find the GNN predicts both properties with high accuracy with mean relative errors of ~1% for unseen microstructures from a given set of textures and < 2% for microstructures of unseen texture, even when presented with limited training data. This accuracy is comparable to methods that require high-resolution three-dimensional (3D) microstructure data, such as 3D convolutional neural networks (3D-CNNs) and models that depend on the computation of spatial statistics. The present results show that graph-based deep learning is a promising framework for property prediction, especially considering the high cost associated with obtaining high-resolution 3D microstructure data and the general scarcity of experimental materials datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Understanding the Existence of a Na 2 Dimer in a High-Spin State

The recent observation of a high-spin Na 2 dimer formed on the surface of liquid helium nanodroplets raises some fundamental questions, as the ground state of Na 2 is known to have zero spin. Is it protected against spontaneous dissociation? What is its binding energy and interatomic distance? Is it stable at a higher temperature? Using calculations based on density functional theory (with and without long-range interaction) and coupled cluster methods, CCSD(T), we show that the bonding in the high-spin Na 2 dimer is governed by van der Waals interaction with binding energy (bond length) varying between −0.030 eV (5.108 Å) and −0.192 eV (4.231 Å), depending on the computational method used. Thus, the experimental method used by Kresin and coworkers can be very useful to study larger metastable high-spin clusters such as Li 4 which was predicted in 1985 to have a tetrahedral structure carrying a magnetic moment of 2 μ B , while its ground state is planar and nonmagnetic.

Basis sets↗
DOE OSTI2018

Effect of Coulomb Correlation on the Magnetic Properties of Mn Clusters

In spite of decades of research, a fundamental understanding of the unusual magnetic behavior of small Mn clusters remains a challenge. Experiments show that Mn 2 is antiferromagnetic while small clusters containing up to five Mn atoms are ferromagnetic with magnetic moments of 5 μB/atom and become ferrimagnetic as they grow further. Theoretical studies based on density functional theory (DFT), however, find Mn2 to be ferromagnetic, with ferrimagnetic order setting in at different sizes that depend upon the computational methods used. While quantum chemical techniques correctly account for the antiferromagnetic ground state of Mn 2 , they are computationally too demanding to treat larger clusters, making it difficult to understand the evolution of magnetism. These studies clearly point to the importance of correlation and the need to find ways to treat it effectively for larger clusters and nanostructures. In this report we show that the DFT+U method can be used to account for strong correlation. We determine the on-site Coulomb correlation, Hubbard U self-consistently by using the linear response theory and study its effect on the magnetic coupling of Mn clusters containing up to five atoms. With a calculated U value of 4.8 eV, we show that the ground state of Mn 2 is antiferromagnetic with a Mn–Mn distance of 3.34 Å, which agrees well with the electron spin resonance experiment. Equally important, we show that on-site Coulomb correlation also plays an important role in the evolution of magnetic coupling in larger clusters, as the results differ significantly from standard DFT calculations. We conclude that for a proper understanding of magnetism of Mn nanostructures (clusters, chains, and layers) one must take into account the effect of strong correlation.

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

Realistic Ion Dynamics through Charge Renormalization in Nonaqueous Electrolytes

While many practically important electrolytes contain lithium ions, interactions of these ions are particularly difficult to probe experimentally because of their small X-ray and neutron scattering cross sections and large neutron absorption cross sections. Molecular dynamics (MD) is a powerful tool for understanding the properties of nonaqueous electrolyte solutions from the atomic level, but the accuracy of this computational method crucially depends on the physics built into the classical force field. In this study, we demonstrate that several force fields for lithium bistriflimide (LiTFSI) in acetonitrile yield a solution structure that is consistent with the neutron scattering experiments, yet these models produce dramatically different ion dynamics in solution. Such glaring discrepancies indicate that inadequate representation of long-range interactions leads to excessive ionic association and ion-pair clustering. We show that reasonable agreement with the experimental observations can be achieved by renormalization of the ion charges using a “titration” method suggested herewith. This simple modification produces realistic concentration dependencies for ionic diffusion and conductivity in <2 M solutions, without loss in quality for simulation of the structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Radiative Electronic Bound States in the Continuum from Defects in Semiconductors

Continuum-buried defect states in semiconductors are generally expected to be optically inactive because of their strong coupling to continuum bands. Here, we show that such defects can instead host radiative electronic bound states in the continuum (BICs) using the silicon G center as a prototypical example. Hybrid functional first-principles calculations with a Hubbard U correction reveal that a localized defect state, initially buried below the valence band maximum (VBM) in the ground state, undergoes exchange-driven energy-level reordering under optical excitation and shifts above the VBM. This exchange-induced transition suppresses nonradiative decay and enables a robust radiative emission. By computing temperature-dependent nonradiative lifetimes and comparing them to experimental photoluminescence (PL) lifetimes, we quantitatively reproduce the observed temperature dependence of the emission. These results uncover a stabilization mechanism for continuum-embedded defect states and establish electronic BICs as a general paradigm for designing defect-based optical systems, including quantum emitters and qubits.

Hong, SeongYun↗
DOE OSTI2025

Density functional theory-based surrogate kinetic models for heterogeneous reactions of hydrocarbon intermediates on silicon carbide

The increasing demand for high-performance materials in advanced technologies highlights the importance of achieving a fundamental understanding and potential control of silicon carbide (SiC) deposition processes. However, existing models often lack sufficient theoretical detail, relying heavily on empirical data and offering limited predictive capability. In particular, the complex surface chemistry governing SiC growth remains poorly understood. This study addresses these challenges by employing density functional theory (DFT) to investigate key heterogeneous reactions involving hydrocarbon intermediates on SiC surfaces, including dehydrogenation, hydrogenation, and carbon deposition. Transition state searches were conducted to identify reaction pathways and energy barriers. While first-principles calculations offer high accuracy, they are computationally intensive. To extend the utility of these first-principles results, vibrational analyses were performed using phonon-based statistical thermochemistry to compute temperature-dependent reaction rates which were used to develop Arrhenius-type surrogate kinetic models. Furthermore, the resulting framework provides a more rigorous, physically grounded basis for integrating atomistic insights into continuum-scale modeling, ultimately enabling improved prediction and optimization of SiC film growth in high-performance material systems.

Density Functional Theory↗
DOE OSTI2016

Ice Ih anomalies: Thermal contraction, anomalous volume isotope effect, and pressure-induced amorphization

Ice Ih displays several anomalous thermodynamic properties such as thermal contraction at low temperatures, an anomalous volume isotope effect (VIE) rendering the volume of D{sub 2}O ice greater than that of H{sub 2}O ice, and a pressure-induced transition to the high-density amorphous (HDA) phase. Furthermore, the anomalous VIE increases with temperature, despite its quantum-mechanical origin. Here, embedded-fragment ab initio second-order many-body perturbation (MP2) theory in the quasiharmonic approximation (QHA) is applied to the Gibbs energy of an infinite, proton-disordered crystal of ice Ih at wide ranges of temperatures and pressures. The quantum effect of nuclei moving in anharmonic potentials is taken into account from first principles without any empirical or nonsystematic approximation to either the electronic or vibrational Hamiltonian. MP2 predicts quantitatively correctly the thermal contraction at low temperatures, which is confirmed to originate from the volume-contracting hydrogen-bond bending modes (acoustic phonons). It qualitatively reproduces (but underestimates) the thermal expansion at higher temperatures, caused by the volume-expanding hydrogen-bond stretching (and to a lesser extent librational) modes. The anomalous VIE is found to be the result of subtle cancellations among closely competing isotope effects on volume from all modes. Consequently, even ab initio MP2 with the aug-cc-pVDZ and aug-cc-pVTZ basis sets has difficulty reproducing this anomaly, yielding qualitatively varied predictions of the sign of the VIE depending on such computational details as the choice of the embedding field. However, the temperature growth of the anomalous VIE is reproduced robustly and is ascribed to the librational modes. These solid-state MP2 calculations, as well as MP2 Born–Oppenheimer molecular dynamics, find a volume collapse and a loss of symmetry and long-range order in ice Ih upon pressure loading of 2.35 GPa or higher. Concomitantly, rapid softening of acoustic phonons is observed starting around 2 GPa. They constitute a computational detection of a mechanical instability in ice Ih and the resulting pressure-induced amorphization to HDA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Mass density fluctuations in quantum and classical descriptions of liquid water

First principles molecular dynamics simulation protocol is established using revised functional of Perdew-Burke-Ernzerhof (revPBE) in conjunction with Grimme's third generation of dispersion (D3) correction to describe properties of water at ambient conditions. This study also demonstrates the consistency of the structure of water across both isobaric (NpT) and isothermal (NVT) ensembles. Going beyond the standard structural benchmarks for liquid water, we compute properties that are connected to both local structure and mass density fluctuations that are related to concepts of solvation and hydrophobicity. Finally, we directly compare our revPBE results to the Becke-Lee-Yang-Parr (BLYP) plus Grimme dispersion corrections (D2) and both the empirical fixed charged model (SPC/E) and many body interaction potential model (MB-pol) to further our understanding of how the computed properties herein depend on the form of the interaction potential.

74 ATOMIC AND MOLECULAR PHYSICS↗