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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The ab initio amorphous materials database: Empowering machine learning to decode diffusivity

Amorphous materials exhibit unique properties that make them suitable for various applications in science and technology, ranging from optical and electronic devices and solid-state batteries to protective coatings. However, data-driven ex- ploration and design of amorphous materials is hampered by the absence of a com- prehensive database covering a broad chemical space. In this work, we present the largest computed amorphous materials database to date, generated from sys- tematic and accurate ab initio molecular dynamics (AIMD) calculations. We also show how the database can be used in simple machine-learning models to connect properties to composition and structure, here specifically targeting ionic conductiv- ity. These models predict the Li-ion diffusivity with speed and accuracy, offering a cost-effective alternative to expensive density functional theory (DFT) calculations. Furthermore, the process of computational quenching amorphous materials provides a unique sampling of out-of-equilibrium structures, energies, and force landscape, and we anticipate that the corresponding trajectories will inform future work in uni- versal machine learning potentials, impacting design beyond that of non-crystalline materials.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Recommended direct simulation Monte Carlo collision model parameters for modeling ionized air transport processes

A systematic approach for calibrating the direct simulation Monte Carlo (DSMC) collision model parameters to achieve consistency in the transport processes is presented. The DSMC collision cross section model parameters are calibrated for high temperature atmospheric conditions by matching the collision integrals from DSMC against ab initio based collision integrals that are currently employed in the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) and Data Parallel Line Relaxation (DPLR) high temperature computational fluid dynamics solvers. The DSMC parameter values are computed for the widely used Variable Hard Sphere (VHS) and the Variable Soft Sphere (VSS) models using the collision-specific pairing approach. The recommended best-fit VHS/VSS parameter values are provided over a temperature range of 1000-20 000 K for a thirteen-species ionized air mixture. Use of the VSS model is necessary to achieve consistency in transport processes of ionized gases. The agreement of the VSS model transport properties with the transport properties as determined by the ab initio collision integral fits was found to be within 6% in the entire temperature range, regardless of the composition of the mixture. The recommended model parameter values can be readily applied to any gas mixture involving binary collisional interactions between the chemical species presented for the specified temperature range.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Ab initio structure determination of nanocrystals of organic pharmaceutical compounds by electron diffraction at room temperature using a Timepix quantum area direct electron detector

A specialized quantum area detector for electron diffraction studies makes it possible to solve the structure of small organic compound nanocrystals in non-cryo conditions by direct methods. Until recently, structure determination by transmission electron microscopy of beam-sensitive three-dimensional nanocrystals required electron diffraction tomography data collection at liquid-nitrogen temperature, in order to reduce radiation damage. Here it is shown that the novel Timepix detector combines a high dynamic range with a very high signal-to-noise ratio and single-electron sensitivity, enabling ab initio phasing of beam-sensitive organic compounds. Low-dose electron diffraction data (∼0.013 e{sup −} Å{sup −2} s{sup −1}) were collected at room temperature with the rotation method. It was ascertained that the data were of sufficient quality for structure solution using direct methods using software developed for X-ray crystallography (XDS, SHELX) and for electron crystallography (ADT3D/PETS, SIR2014)

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

High-pressure phase transition of alkali metal–transition metal deuteride Li 2 PdD 2

A combined theoretical and experimental study of lithium palladium deuteride (Li 2 PdD 2 ) subjected to pressures up to 50 GPa reveals one structural phase transition near 10 GPa, detected by synchrotron powder x-ray diffraction, and metadynamics simulations. We report the ambient-pressure tetragonal phase of Li 2 PdD 2 transforms into a monoclinic $C2/m$ phase that is distinct from all known structures of alkali metal–transition metal hydrides/deuterides. The structure of the high-pressure phase was characterized using ab initio computational techniques and from refinement of the powder x-ray diffraction data. In the high-pressure phase, the PdD 2 complexes lose molecular integrity and are fused to extended [PdD 2 ] ∞ chains. The discovered phase transition and new structure are relevant to the possible hydrogen storage application of Li 2 PdD 2 and alkali metal–transition metal hydrides in general.

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

Localized basis set for plutonium

The implementation of optimal strictly localized atomic orbitals basis for plutonium (Pu) using norm-conserving pseudopotential density-functional theory (DFT) is presented. The basis set was applied to the α, β, γ, δ, δ', and ε phases of Pu, δ-Pu surface, and δ-PuGa alloys. The computed properties of the Pu phases and δ-Pu surface were in good agreement with both available experimental data and prior DFT calculations based on plane-wave methodologies. Results for the δ-PuGa alloys were also in good agreement with experimental data. Finally, the reliability of the basis set was further demonstrated by using ab initio molecular dynamics to model the diffusion coefficient and activation barrier for atomic diffusion in a δ-PuGa alloy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

In-Silico Analysis of High Refractive Index Materials Through Principles of Materials Design

The intent of the paper is to use specific principles of Materials Design that were developed and applied in the electronics industry for enabling understanding and design of improved high refractive index materials. Further, by combining first-principle based ab-initio, semiempirical interatomic potential methods, and machine learning approaches in conjunction with experimental data, we identified specific determinants of high refractive index materials, which can be critically applied for informing materials design and accelerating discovery. Specifically, it was demonstrated that chalcogenides and perovskites as bulk materials can exhibit higher refractive indices with appropriate engineering of specific aspects of the materials.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Reaction pathways of cyclopentanone oxidation intermediates

Despite the promising role of cyclopentanone as a bio-derived fuel, thermodynamic and kinetic data are lacking for low-temperature oxidation regimes. This talk will present ab initio calculations of the subsequent reactivity that results from O2-addition to 2- and 3-oxo cyclopentyl radicals, including expected reaction classes such as intra-H migration, HO2-elimination, cyclic ether formation, and β-scission along with their thermodynamic parameters. Some of the rates are similar to the analogous reactions of cyclopentane, but some other reactions of cyclopentanone are very different. Comparison of the reactivity of α- and β- substituted ketone will also be discussed. These findings will be valuable for evaluating the potential of cyclopentanone as a biofuel.

09 BIOMASS FUELS↗
DOE OSTI2017

Ab initio calculations of reactions of light nuclei

An ab initio (i.e., from first principles) theoretical framework capable of providing a unified description of the structure and low-energy reaction properties of light nuclei is desirable as a support tool for accurate evaluations of crucial reaction data for nuclear astrophysics, fusion-energy research, and other applications. We present an efficient many-body approach to nuclear bound and scattering states alike, known as the ab initio no-core shell model with continuum. In this approach, square-integrable energy eigenstates of the A-nucleon system are coupled to (A-A)+A target-plus-projectile wave functions in the spirit of the resonating group method to obtain an efficient description of the many-body nuclear dynamics both at short and medium distances and at long ranges. We show that predictive results for nucleon and deuterium scattering on 4 He nuclei can be obtained from the direct solution of the Schröedinger equation with modern nuclear potentials.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Magnetic Transitions in Iron Porphyrin Halides by Inelastic Neutron Scattering and Ab-initio Studies of Zero-Field Splittings

Zero-field splitting (ZFS) parameters of nondeuterated metalloporphyrins [Fe(TPP)X] (X = F, Br, I; H 2 TPP = tetraphenylporphyrin) are determined by inelastic neutron scattering (INS). The ZFS values are D = 4.49(9) cm –1 for tetragonal polycrystalline [Fe(TPP)F], and D = 8.8(2) cm –1 , E = 0.1(2) cm –1 and D = 13.4(6) cm –1 , E = 0.3(6) cm –1 for monoclinic polycrystalline [Fe(TPP)Br] and [Fe(TPP)I], respectively. Along with our recent report of the ZFS value of D = 6.33(8) cm –1 for tetragonal polycrystalline [Fe(TPP)Cl], these data provide a rare, complete determination of ZFS parameters in a metalloporphyrin halide series. The electronic structure of [Fe(TPP)X] (X = F, Cl, Br, I) has been studied by multireference ab initio methods: the complete active space self-consistent field (CASSCF) and the N-electron valence perturbation theory (NEVPT2) with the aim of exploring the origin of the large and positive zero-field splitting D of the 6 A 1 ground state. D was calculated from wave functions of the electronic multiplets spanned by the d 5 configuration of Fe(III) along with spin–orbit coupling accounted for by quasi degenerate perturbation theory. Results reproduce trends of D from inelastic neutron scattering data increasing in the order from F, Cl, Br, to I. A mapping of energy eigenvalues and eigenfunctions of the S = 3/2 excited states on ligand field theory was used to characterize the σ- and π-antibonding effects decreasing from F to I. This is in agreement with similar results deduced from ab initio calculations on CrX 6 3- complexes and also with the spectrochemical series showing a decrease of the ligand field in the same directions. A correlation is found between the increase of D and decrease of the π- and σ-antibonding energies e λ X (λ = σ, π) in the series from X = F to I. Analysis of this correlation using second-order perturbation theory expressions in terms of angular overlap parameters rationalizes the experimentally deduced trend. Furthermore, D parameters from CASSCF and NEVPT2 results have been calibrated against those from the INS data, yielding a predictive power of these approaches. Methods to improve the quantitative agreement between ab initio calculated and experimental D and spectroscopic transitions for high-spin Fe(III) complexes are proposed.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Quasielastic electromagnetic scattering cross sections and world data comparisons in the GENIE Monte Carlo event generator

The usage of Monte Carlo neutrino event generators (MC$\textit{ν}$EGs) is a norm within the high-energy $\textit{ν}$ scattering community. The relevance of quasielastic (QE) energy regimes to $\textit{ν}$ oscillation experiments implies that accurate calculations of $\textit{ν}$A cross sections in this regime will be a key contributor to reducing the systematic uncertainties affecting the extraction of oscillation parameters. In spite of this, many MC$\textit{ν}$EGs utilize highly phenomenological, parametrized models of QE scattering cross sections. Moreover, a culture of validation of MC$\textit{ν}$EGs against prolific electron ($\textit{e}$) scattering data has been historically lacking. In this work, we implement new eA cross sections obtained from nuclear ab initio approaches in GENIE, the primary MC$\textit{ν}$EG utilized by the FNAL community. In particular, we utilize results from quantum MC methods which solve the many-body nuclear problem in the short-time approximation (STA), allowing consistent retention of two-nucleon dynamics which are crucial to explain available nuclear electromagnetic (electroweak) data over a wide range of energy and momentum transfers. This new implementation in GENIE is fully tested against the world QE electromagnetic data, finding agreement with available data below ~2 GeV of beam energy with the aid of a scaling function formalism. The STA is currently limited to study $\textit{A}$ ≤ 12 nuclei, however, its semi-inclusive multibody identity components are exportable to other many-body computational techniques such as auxiliary field diffusion MC which can reach $\textit{A}$ ≤ 40 systems while continuing to realize the factorization contained within the STA’s multinucleon dynamics. Together, these developments promise to make future experiments such as DUNE more accurate in their assessment of MC$\textit{ν}$EG systematics, $\textit{ν}$ properties, and potentially empower the discovery of physics beyond the Standard Model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Ab Initio Modeling on The Thermodynamic and Temperature-Dependent Elastic Properties of Subsystems of The FCC FeNiCoCr Medium Entropy Alloys (MEAs)

The stability, phonon spectra, thermodynamic, and temperature-dependent elasticity of subsystems of the FCC FeNiCoCr MEAs are systematically studied by the ab initio approach. Especially, the quasi-harmonic approximation (QHA) and the innovative Zentropy theory were utilized to predict the thermodynamic properties and elastic properties of FeNi, NiCo, FeNiCo, and FeNiCoCr MEAs with the consideration of magnetic transition. With the ensemble of the partition function based on the multiplicity of each magnetic configuration, the current work successfully reproduced the Curie temperature and the Schottky anomaly of heat capacity of these four MEAs purely based on the ab initio input. Meanwhile, the elastic properties of these alloys at finite temperatures are also successfully predicted with the consideration of magnetic transition. The overall results agree well with the available experimental data and CALPHAD prediction.

36 MATERIALS SCIENCE↗
NASA NTRS1982

The rotational spectra of HCNH/+/ and COH/+/ from quantum mechanical calculations

A description is provided of ab initio molecular orbital calculations designed to provide accurate predictions for the J = 1 to 0 rotational line of the candidate interstellar molecules HCNH(+) and COH(+). The former is believed to be important in the formation of both HCN and HNC in the interstellar medium. The latter, a metastable isomer of HCO(+), was first proposed as an interstellar molecule by Herbst et al. (1976). Attention is given to thermochemical arguments that this molecule can be formed in the same reactions which are proposed to form HCO(+), taking into account theoretical data which establish its stability to intramolecular rearrangement. Rotational constants are derived by applying an empirical correction to the ab initio rotational constants.

Defrees, D. J.↗
DOE OSTI2024

The ab initio non-crystalline structure database: empowering machine learning to decode diffusivity

Non-crystalline materials exhibit unique properties that make them suitable for various applications in science and technology, ranging from optical and electronic devices and solid-state batteries to protective coatings. However, data-driven exploration and design of non-crystalline materials is hampered by the absence of a comprehensive database covering a broad chemical space. In this work, we present the largest computed non-crystalline structure database to date, generated from systematic and accurate ab initio molecular dynamics (AIMD) calculations. We also show how the database can be used in simple machine-learning models to connect properties to composition and structure, here specifically targeting ionic conductivity. These models predict the Li-ion diffusivity with speed and accuracy, offering a cost-effective alternative to expensive density functional theory (DFT) calculations. Furthermore, the process of computational quenching non-crystalline structures provides a unique sampling of out-of-equilibrium structures, energies, and force landscape, and we anticipate that the corresponding trajectories will inform future work in universal machine learning potentials, impacting design beyond that of non-crystalline materials. In addition, combining diffusion trajectories from our dataset with models that predict liquidus viscosity and melting temperature could be utilized to develop models for predicting glass-forming ability.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quantum Molecular Charge-Transfer Model for Multistep Auger–Meitner Decay Cascade Dynamics

The fragmentation of molecular cations following inner-shell decay processes in molecules containing heavy elements underpins the X-ray damage effects observed in X-ray scattering measurements of biological and chemical materials, as well as in medical applications involving Auger electron-emitting radionuclides. Traditionally, these processes are modeled using simulations that describe the electronic structure at an atomic level, thereby omitting molecular bonding effects. This work addresses the gap by introducing a novel approach that couples Auger–Meitner decay to nuclear dynamics across multiple decay steps, by developing a decay spawning dynamics algorithm and applying it to potential energy surfaces characterized with ab initio molecular dynamics simulations. We showcase the approach on a model decay cascade following K-shell ionization of IBr and subsequent Kβ fluorescence decay. We examine two competing channels that undergo two decay steps, resulting in ion pairs with a total 3+ charge state. This approach provides a continuous description of the electron transfer dynamics occurring during the multistep decay cascade and molecular fragmentation, revealing the combined inner-shell decay and charge transfer time scale to be approximately 75 fs. In conclusion, our computed kinetic energies of ion fragments show good agreement with experimental data.

Ab initio molecular dynamics↗
DOE OSTI2025

Toward a Generalizable Prediction Model of Molten Salt Mixture Density with Chemistry‐Informed Transfer Learning

Optimally designing applications of molten salts requires knowledge of their thermophysical properties over a wide range of temperatures and compositions. There exist significant gaps in existing databases and this data can be challenging to experimentally measure due to high temperatures, salt corrosivity, and salt hygroscopicity. Existing databases have been used to create Redlich–Kister (RK) models for mixture density showing improved accuracy with respect to ideal mixing assumptions, but these models require subcomponent data measurements for each new system, therefore lacking generality. In order to address generalizability and data sparsity, a transfer learning procedure is proposed to train deep neural networks (DNNs) using a combination of semi‐empirical relationships (RK), data from the thermophysical arm of the molten salt thermal properties database and universal ab initio properties of component mixtures taken from the joint automated repository for various integrated simulations (JARVIS) classical force‐field inspired descriptors database to predict density in molten salts. Herein, it is shown that DNNs predict molten salt density with an r 2 over 0.99 and a mean absolute percentage error under 1%, outperforming alternative methods.

inorganic materials↗
DOE OSTI2025

Investigating the weak charge of 48 Ca using a dispersive optical model

A new nonlocal dispersive-optical-model analysis has been carried out for neutrons and protons in 48 Ca that reproduces the weak-form-factor measurement of CREX. In addition to elastic-scattering angular distributions, total and reaction cross sections, single-particle energies, the neutron and proton numbers, and the charge distribution, the CREX-measured weak form factor has been fit to extract the neutron and proton self-energies both above and below the Fermi energy. The resulting single-particle propagators yield a weak form factor of F w = 0.125 ± 0.05 and a neutron skin of R skin = 0.152 ± 0.05 fm, in good agreement with CREX. The rearrangement of the neutron distribution to accommodate such a thin neutron skin results in the high-momentum content of the neutrons exceeding that of the protons, in contrast to what is expected from high-energy two-nucleon knockout measurements by the CLAS collaboration and ab initio asymmetric matter calculations. The present analysis also emphasizes the importance of neutron experimental data in constraining weak charge observables necessary for a precise description of neutron densities. Notably, the neutron reaction cross section and further parity-violating experiments weak form factor measurements are essential to generate a unique way to determine the 48 Ca neutron distribution in this framework.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Combining Force Fields and Neural Networks for an Accurate Representation of Chemically Diverse Molecular Interactions

A key goal of molecular modeling is the accurate reproduction of the true quantum mechanical potential energy of arbitrary molecular ensembles with a tractable classical approximation. The challenges are that analytical expressions found in general purpose force fields struggle to faithfully represent the intermolecular quantum potential energy surface at close distances and in strong interaction regimes; that the more accurate neural network approximations do not capture crucial physics concepts, e.g., nonadditive inductive contributions and application of electric fields; and that the ultra-accurate narrowly targeted models have difficulty generalizing to the entire chemical space. We therefore designed a hybrid wide-coverage intermolecular interaction model consisting of an analytically polarizable force field combined with a short-range neural network correction for the total intermolecular interaction energy. Here, we describe the methodology and apply the model to accurately determine the properties of water, the free energy of solvation of neutral and charged molecules, and the binding free energy of ligands to proteins. The correction is subtyped for distinct chemical species to match the underlying force field, to segment and reduce the amount of quantum training data, and to increase accuracy and computational speed. For the systems considered, the hybrid ab initio parametrized Hamiltonian reproduces the two-body dimer quantum mechanics (QM) energies to within 0.03 kcal/mol and the nonadditive many-molecule contributions to within 2%. Simulations of molecular systems using this interaction model run at speeds of several nanoseconds per day.

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

Quantifying Uncertainties of Microscopic Nuclear Theories

The goal of this project was to produce modernized nuclear data libraries of light ion fusion reactions and actinide fission product yields. Such libraries are essential input in both stockpile science but also fundamental science (nucleosynthesis, superheavy nuclei). When such libraries are used to model complex processes involving exotic, very short-lived nuclei that have not been measured experimentally, the underlying nuclear data come from theoretical models, the predictive power of which needs to be quantified, together with its uncertainties. By teaming up nuclear theorists and statisticians, we built comprehensive theoretical frameworks based on the most fundamental theories of fusion and fission that we coupled for the first time with a Bayesian framework with machine learning techniques for uncertainty quantification. Our results include: (1) statistical emulators for neutron-alpha scattering, and the fission product mass yields of neutron-induced fission of 239 Pu, which will enable developers to generate random realizations of the corresponding data for uncertainty quantification (UQ) in applications; (2) the first complete and most accurate ab initio prediction of the S-factor for proton capture on 7 Be, which – combined with UQ – may become the recommended value at solar energies in the next review of solar fusion cross sections; (3) statistical emulators for fission mass yields in the neutron-induced fission of 239 Pu; (4) the first quantification of how uncertainties in nuclear forces impact fission properties that are relevant in nucleosynthesis simulations to explain how heavy elements are formed in the Cosmos.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗