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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Nitromethane Decomposition via Automated Reaction Discovery and an Ab Initio Corrected Kinetic Model

In the explore the systematic construction of kinetic models from in silico reaction data for the decomposition of nitromethane. Our models are constructed in a computationally affordable manner by using reactions discovered through accelerated molecular dynamics simulations using the ReaxFF reactive force field. The reaction paths are then optimized to determine reaction rate parameters. We introduce a reaction barrier correction scheme that combines accurate thermochemical data from density functional theory with ReaxFF minimal energy paths. We validate our models across different thermodynamic regimes, showing predictions of gas phase CO and NO concentrations and high-pressure induction times that are similar to experimental data. The kinetic models are analyzed to find fundamental decomposition reactions in different thermodynamic regimes.

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

Liquid-Vapor Coexistence and Critical Point of Mg 2 SiO 4 From Ab Initio Simulations

Hypervelocity impact-driven vaporization is characteristic of late-stage planet formation. Yet the behavior and properties of liquid-vapor mixtures of planetary materials of interest are typically unknown. Multiphase equations of state used in hydrodynamic simulations of planet impacts therefore lack reliable data for this important phenomenon. Here, we present the first constraints on the liquid-vapor critical point and coexistence phase boundary of Mg2SiO4 computed from ab initio molecular dynamics simulations. We found that the vapor is depleted in magnesium and enriched in silica and oxygen, while the coexisting liquid is enriched in magnesium and depleted in oxygen, from which we infer vaporization is incongruent. The critical point was estimated from an equation of state fit to the data. The results are in line with recent calculations of MgSiO3 and together confirm that extant multiphase equation of state (EOS) models used in planetary accretion modeling significantly underestimate the amount of supercritical material postimpact.

58 GEOSCIENCES↗
DOE OSTI2021

Radiative properties of quantum emitters in boron nitride from excited state calculations and Bayesian analysis

Abstract Point defects in hexagonal boron nitride (hBN) have attracted growing attention as bright single-photon emitters. However, understanding of their atomic structure and radiative properties remains incomplete. Here we study the excited states and radiative lifetimes of over 20 native defects and carbon or oxygen impurities in hBN using ab initio density functional theory and GW plus Bethe-Salpeter equation calculations, generating a large data set of their emission energy, polarization and lifetime. We find a wide variability across quantum emitters, with exciton energies ranging from 0.3 to 4 eV and radiative lifetimes from ns to ms for different defect structures. Through a Bayesian statistical analysis, we identify various high-likelihood charge-neutral defect emitters, among which the native V N N B defect is predicted to possess emission energy and radiative lifetime in agreement with experiments. Our work advances the microscopic understanding of hBN single-photon emitters and introduces a computational framework to characterize and identify quantum emitters in 2D materials.

Chemistry↗
DOE OSTI2021

Characterization of the molten salt FMgNaK through ab initio molecular dynamics and experimental density measurements

The selection of a salt species for use in a molten salt reactor MSR is a key part of any MSR design. However, many salts have sparse or no thermophysical property data sets, especially those with higher melting points. One such salt is the eutectic mixture of (NaF)0.345(KF)0.59(MgF 2 )0.065, or FMgNaK, and is explored here through ab initio molecular dynamics (AIMD) simulation (1023-1273K) as well as experimental measurement of the liquid density using the Archimedean method (973-1223K). Predicted densities from AIMD are similar to experimentally-measured densities, though with more noise, suggesting that the small scale necessitated by AIMD simulations may be problematic for simulating FMgNaK in particular. Here the coefficient of thermal expansion is predicted from simulation, and salt structure is characterized. Mg-F-Mg chaining is observed in the salt network, though the low concentration of Mg inhibits chaining on the scale that is observed in (LiF) 0.67 (BeF 2 ) 0.33 , or FLiBe.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A high-dimensional neural network potential for molecular dynamics simulations of condensed phase nickel and phase transitions

A high-dimensional neural network interatomic potential was developed and used in molecular dynamics simulations of condensed phase Ni and Ni systems with liquid–solid phase coexistence. The reference data set was generated by sampling the potential energy surface over a broad temperature-pressure domain using ab initio MD simulations to train a unified potential. Excellent agreement was achieved between bulk face-centered cubic nickel thermal expansion simulations and relevant experimental data. The same potential also yields accurate structures and diffusivities in the liquid state. The phase transition between liquid and solid phases was simulated using the two-phase interface method. The predicted melting point temperature is within a few kelvins of the literature value. Here, the general methodology could be applied to describe crystals with much more complex phase behaviors.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

Constructing diabatic representations using adiabatic and approximate diabatic data – Coping with diabolical singularities

We have recently introduced a diabatization scheme, which simultaneously fits and diabatizes adiabatic ab initio electronic wave functions, Zhu and Yarkony J. Chem. Phys. 140, 024112 (2014). The algorithm uses derivative couplings in the defining equations for the diabatic Hamiltonian, H{sup d}, and fits all its matrix elements simultaneously to adiabatic state data. This procedure ultimately provides an accurate, quantifiably diabatic, representation of the adiabatic electronic structure data. However, optimizing the large number of nonlinear parameters in the basis functions and adjusting the number and kind of basis functions from which the fit is built, which provide the essential flexibility, has proved challenging. In this work, we introduce a procedure that combines adiabatic state and diabatic state data to efficiently optimize the nonlinear parameters and basis function expansion. Further, we consider using direct properties based diabatizations to initialize the fitting procedure. To address this issue, we introduce a systematic method for eliminating the debilitating (diabolical) singularities in the defining equations of properties based diabatizations. We exploit the observation that if approximate diabatic data are available, the commonly used approach of fitting each matrix element of H{sup d} individually provides a starting point (seed) from which convergence of the full H{sup d} construction algorithm is rapid. The optimization of nonlinear parameters and basis functions and the elimination of debilitating singularities are, respectively, illustrated using the 1,2,3,4{sup 1}A states of phenol and the 1,2{sup 1}A states of NH{sub 3}, states which are coupled by conical intersections.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2012

A Group Increment Scheme for Infrared Absorption Intensities of Greenhouse Gases

A molecule's absorption in the atmospheric infrared (IR) window (IRW) is an indicator of its efficiency as a greenhouse gas. A model for estimating the absorption of a fluorinated molecule within the IRW was developed to assess its radiative impact. This model will be useful in comparing different hydrofluorocarbons and hydrofluoroethers contribution to global warming. The absorption of radiation by greenhouse gases, in particular hydrofluoroethers and hydrofluorocarbons, was investigated using ab initio quantum mechanical methods. Least squares regression techniques were used to create a model based on this data. The placement and number of fluorines in the molecule were found to affect the absorption in the IR window and were incorporated into the model. Several group increment models are discussed. An additive model based on one-carbon groups is found to work satisfactorily in predicting the ab initio calculated vibrational intensities.

Kokkila, Sara I.↗
DOE OSTI2024

First β -delayed neutron spectroscopy of 24 O

The β decay of 24 O was investigated at NSCL/MSU using a combination of neutron and γ-ray spectroscopy. For the first time, the β-delayed neutron energy spectrum of 24 O was measured, revealing three intensely populated, isolated neutron-unbound states in 24 F. This allowed for the extraction of the decay strength in 24 F up to 6.2 MeV. A comprehensive comparison of the experimental results with various nuclear theories, ranging from the empirical shell model to the most advanced ab initio calculations, was conducted. While most theoretical predictions align with the experimental data for low-lying states, discrepancies arise at higher excitation energies. Finally, in the transition from 24 O to 24 F, shell model calculations using the empirical USDB interaction predicted the structure of both nuclei without invoking the need for a stronger proton-neutron tensor force, which was postulated for the neighboring isotone 25 F.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Theoretical level energies and transition data for 4p{sup 6}4d{sup 5}, 4p{sup 5}4d{sup 6} and 4p{sup 6}4d{sup 4}4f configurations of W{sup 33+} ion

The ab initio quasirelativistic approach developed specifically for the calculation of spectral parameters of highly charged ions was used to derive transition data for the Nb-like tungsten ion W{sup 33+}. The configuration interaction method was applied to include electron correlation effects. The relativistic effects were taken into account in the Breit–Pauli approximation. The level energies, radiative lifetimes τ, Landé g-factors were determined for the ground configuration 4p{sup 6}4d{sup 5} and two excited configurations 4p{sup 5}4d{sup 6} and 4p{sup 6}4d{sup 4}4f. The radiative transition wavelengths λ and emission transition probabilities A for the electric dipole, electric quadrupole, electric octupole, magnetic dipole, and magnetic quadrupole transitions among the levels of these configurations were produced. The uncertainties of computed spectroscopic parameters were evaluated.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

Verification of Anderson superexchange in MnO via magnetic pair distribution function analysis and ab initio theory

Here, we present a temperature-dependent atomic and magnetic pair distribution function (PDF) analysis of neutron total scattering measurements of antiferromagnetic MnO, an archetypal strongly correlated transition-metal oxide. The known antiferromagnetic ground-state structure fits the low-temperature data closely with refined parameters that agree with conventional techniques, confirming the reliability of the newly developed magnetic PDF method. The measurements performed in the paramagnetic phase reveal significant short-range magnetic correlations on a ~1 nm length scale that differ substantially from the low-temperature long-range spin arrangement. Ab initio calculations using a self-interaction-corrected local spin density approximation of density functional theory predict magnetic interactions dominated by Anderson superexchange and reproduce the measured short-range magnetic correlations to a high degree of accuracy. Further calculations simulating an additional contribution from a direct exchange interaction show much worse agreement with the data. Furthermore, the Anderson superexchange model for MnO is thus verified by experimentation and confirmed by ab initio theory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

A classical mechanics model for the interpretation of piezoelectric property data

In order to provide a means of understanding, the relationship between the primary electromechanical coefficients and simple crystal chemistry parameters for piezoelectric materials, a static analysis of a 3 atom, dipolar molecule has been undertaken to derive relationships for elastic compliance s{sup E}, dielectric permittivity ε{sup X}, and piezoelectric charge coefficient d in terms of an effective ionic charge and two inter-atomic force constants. The relationships demonstrate the mutual interdependence of the three coefficients, in keeping with experimental evidence from a large dataset of commercial piezoelectric materials. It is shown that the electromechanical coupling coefficient k is purely an expression of the asymmetry in the two force constants or bond compliances. The treatment is extended to show that the quadratic electrostriction relation between strain and polarization, in both centrosymmetric and non-centrosymmetric systems, is due to the presence of a non-zero 2nd order term in the bond compliance. Comparison with experimental data explains the counter-intuitive, positive correlation of k with s{sup E} and ε{sup X} and supports the proposition that high piezoelectric activity in single crystals is dominated by large compliance coupled with asymmetry in the sub-cell force constants. However, the analysis also shows that in polycrystalline materials, the dielectric anisotropy of the constituent crystals can be more important for attaining large charge coefficients. The model provides a completely new methodology for the interpretation of piezoelectric and electrostrictive property data and suggests methods for rapid screening for high activity in candidate piezoelectric materials, both experimentally and by novel interrogation of ab initio calculations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Reaction Pathways, Thermodynamics, and Kinetics of Cyclopentanone Oxidation Intermediates: A Theoretical Approach

Despite the promising role of cyclopentanone as a bio-derived fuel, thermodynamic and kinetic data are lacking for low temperature oxidation regimes. In this study, ab initio calculations at the CBS-QB3 level explore the subsequent reactivity that results from O 2 -addition to 2- and 3-oxo cyclopentyl radicals, including expected reaction classes such as intra-H migration, HO 2 -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. The carbonyl group hinders H-migration from the α’ position but promotes HO 2 -elimination. Enol peroxy formation from some hydroperoxy alkyl radicals of cyclopentanone is unexpectedly important, and so is HO 2 -elimination by β-scission. Our calculations also indicated that at engine relevant conditions the α-RO 2 prefers to go back to reactants 2-oxo cyclopentyl radical and O 2 . Therefore, the reactions resulting from HO2-addition to 2-oxo cyclopentyl is also provided. The lowest barrier channel identified on the singlet surface corresponds to an unexpected intra OH-migration path concerted with ring opening. In conclusion, this valuable information will advance the construction of improved kinetic models for the oxidation of cylopentanone.

09 BIOMASS FUELS↗
DOE OSTI2020

Electronic correlations and flattened band in magnetic Weyl semimetal candidate Co 3 Sn 2 S 2

The interplay between electronic correlations and topological protection may offer a rich avenue for discovering emergent quantum phenomena in condensed matter. However, electronic correlations have so far been little investigated in Weyl semimetals (WSMs) by experiments. Here, we report a combined optical spectroscopy and theoretical calculation study on the strength and effect of electronic correlations in a magnet Co 3 Sn 2 S 2 . The electronic kinetic energy estimated from our optical data is about half of that obtained from single-particle ab initio calculations in the ferromagnetic ground state, which indicates intermediate-strength electronic correlations in this system. Furthermore, comparing the energy and side-slope ratios between the interband-transition peaks at high energies in the experimental and single-particle-calculation-derived optical conductivity spectra with the bandwidth-renormalization factors obtained by many-body calculations enables us to estimate the Coulomb-interaction strength (U ~ 4 eV) in Co 3 Sn 2 S 2 . Besides, a sharp experimental optical conductivity peak at low energy, which is absent in the single-particle-calculation-derived spectrum but is consistent with the optical conductivity peaks obtained by many-body calculations with U ~ 4 eV, indicates that an electronic band connecting the two Weyl cones is flattened by electronic correlations and emerges near the Fermi energy in Co 3 Sn 2 S 2 . Our work paves the way for exploring flat-band-generated quantum phenomena in WSMs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Active Learning Framework

Machine learning (ML) of interatomic potentials show great promise to accelerate scientific simulation, e.g., by emulating expensive computations at a high accuracy but much reduced computational cost. Training datasets are calculated from computationally expensive ab initio quantum mechanics methods, density functional theory (DFT). Trained on this data, an ML model can be very successful in predicting energy and forces for new atomic configurations. A critical factor is the quality and diversity of the training dataset. Thus, a highly automated approach to dataset construction based on active learning framework is designed suitable for material physics. The active learning scheme begins with fully randomized atomic configurations. Then, many Molecular Dynamics (MD) trajectories are simulated using current ML potentials, where each MD trajectory is initialized to a random disordered configuration. The temperature is varied in order to diversify the sampled configuration during these simulations. The variance of predictions for eight neural networks within an ensemble is analyzed to determine whether the model is operating as expected. This helps in determining whether collecting more data would be helpful to the model by checking the ensemble variance is greater than the threshold. In this case, the MD trajectory is terminated and the final atomic configuration is placed on a queue (SQL database) for DFT calculations and added to training dataset. Periodically, ML model is retrained to the updated training model. This Active Learning loop is iterated until the cost of MD simulations becomes prohibitively expensive. The MD simulations will hopefully be sufficiently robust to support nucleation after many active learning iterations. In this sense, active learning scheme must automatically discover the important low energy and nonequilibrium physics.

Nebgen, Benjamin↗
DOE OSTI2019

A Deep-UV Trigger for Ground-State Ring-Opening Dynamics of 1,3-Cyclohexadiene

While the ring-opening reaction of 1,3-cyclohexadiene upon excitation to the 1B state has been extensively studied, little is known about the reaction dynamics when exciting higher-lying states. The complexity of the potential energy surfaces found in computational studies suggests that the reaction outcome may depend sensitively on the excitation wavelength and the initially prepared electronic state. We explore the photo-induced kinetics of 1,3-cyclohexadiene upon excitation at 200 nm to the 3p state by ultrafast time-resolved, gas-phase X-ray scattering using the Linac Coherent Light Source (LCLS). Analysis of the experimental scattering data, particularly with respect to the anisotropy, and comparison to ab-initio calculations reveals that the excitation leads dominantly to the 3px and 3py Rydberg electronic states, which relax to the ground state with a time constant of 208 ±11 fs. Unlike in the conventional photochemically induced conrotatory electrocyclic reaction observed at lower excitation energies, at 200 nm the majority of the molecules (76 ± 3%) relax to vibrationally hot cyclohexadiene in the ground electronic state. Furthermore, the photoexcitation activates the reaction on the ground electronic state surface. An equilibrium between the hot cyclohexadiene and 1,3,5-hexatriene is reached by a thermal reaction, giving rates for the forward and backward reaction of 174 ±13 ps and 355 ±45 ps, respectively. The scattering pattern of the final hexatriene product reveals a thermal distribution of rotamers about the carbon-carbon single bonds. The rapid decay of the initially excited state back into the ring-closed form allows us to observe a ground state chemical reaction using ultrafast X-ray scattering.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

hippynn Python Package

hippynn is a python package for defining, training, and applying neural networks to atomistic systems. In particular, it focuses on Hierarchical Interacting Particle Neural Networks (HIP-NNs), a deep learning architecture for atomistic systems. HIP-NNs take input data describing the properties of atomistic systems (often generated using ab-initio quantum mechanics) to learn fast and accurate models. A trained HIP-NN can predict potential energy surfaces, atomic charges, and more. hippynn uses PyTorch for portable high-performance code, including both CPU and GPU support. hippynn allows for extensive customization, including user-defined models and loss functions, to facilitate future research into extensions of HIP-NN as well as other atomistic deep learning models.

Lubbers, Nicolas↗
DOE OSTI2016

Acceleration of saddle-point searches with machine learning

In atomistic simulations, the location of the saddle point on the potential-energy surface (PES) gives important information on transitions between local minima, for example, via transition-state theory. However, the search for saddle points often involves hundreds or thousands of ab initio force calls, which are typically all done at full accuracy. This results in the vast majority of the computational effort being spent calculating the electronic structure of states not important to the researcher, and very little time performing the calculation of the saddle point state itself. In this work, we describe how machine learning (ML) can reduce the number of intermediate ab initio calculations needed to locate saddle points. Since machine-learning models can learn from, and thus mimic, atomistic simulations, the saddle-point search can be conducted rapidly in the machine-learning representation. The saddle-point prediction can then be verified by an ab initio calculation; if it is incorrect, this strategically has identified regions of the PES where the machine-learning representation has insufficient training data. When these training data are used to improve the machine-learning model, the estimates greatly improve. This approach can be systematized, and in two simple example problems we demonstrate a dramatic reduction in the number of ab initio force calls. We expect that this approach and future refinements will greatly accelerate searches for saddle points, as well as other searches on the potential energy surface, as machine-learning methods see greater adoption by the atomistics community.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Ab Initio Electronic Structure Calculations of CNN for CN Excitation Studies

The CN molecule is an important contributor to radiative heat flux in shock layers around vehicles entering Titan’s atmosphere. Current data for heavy particle (de)excitation rate coefficients of CN leads to uncertainties in the population of CN in its first and second excited states. This in turn leads to uncertainties in the radiative heat flux predicted by Computational Fluid Dynamics (CFD) simulations of Titan atmospheric entry. This work performs ab initio electronic structure calculations of the CNN complex to create Potential Energy Surfaces (PESs) that correlate to the ground and first and second excited states of CN. Specifically, the state combinations of CN(X,A,B) + N(4S𝑜) correlate to six states of CNN (three Quintet A” and three Triplet A”). Initial calculations of these states suggest that heavy particle (de)excitation of CN by N atoms is likely to proceed through collinear geometries on triplet surfaces. Complete PESs will show all of the reaction pathways in detail, and will be used in nonadiabatic dynamics calculations to evaluate improved rate coefficients and reduce uncertainty in the radiative heat flux during Titan entry.

Eric C Geistfeld↗