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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

AP-Net: An atomic-pairwise neural network for smooth and transferable interaction potentials

Intermolecular interactions are critical to many chemical phenomena, but their accurate computation using ab initio methods is often limited by computational cost. The recent emergence of machine learning (ML) potentials may be a promising alternative. Useful ML models should not only estimate accurate interaction energies but also predict smooth and asymptotically correct potential energy surfaces. However, existing ML models are not guaranteed to obey these constraints. Indeed, systemic deficiencies are apparent in the predictions of our previous hydrogen-bond model as well as the popular ANI-1X model, which we attribute to the use of an atomic energy partition. As a solution, we propose an alternative atomic-pairwise framework specifically for intermolecular ML potentials, and we introduce AP-Net—a neural network model for interaction energies. The AP-Net model is developed using this physically motivated atomic-pairwise paradigm and also exploits the interpretability of symmetry adapted perturbation theory (SAPT). We show that in contrast to other models, AP-Net produces smooth, physically meaningful intermolecular potentials exhibiting correct asymptotic behavior. Initially trained on only a limited number of mostly hydrogen-bonded dimers, AP-Net makes accurate predictions across the chemically diverse S66x8 dataset, demonstrating significant transferability. On a test set including experimental hydrogen-bonded dimers, AP-Net predicts total interaction energies with a mean absolute error of 0.37 kcal mol−1, reducing errors by a factor of 2–5 across SAPT components from previous neural network potentials. The pairwise interaction energies of the model are physically interpretable, and an investigation of predicted electrostatic energies suggests that the model “learns” the physics of hydrogen-bonded interactions.

Glick, Zachary L. (ORCID:0000000309002849)↗
DOE OSTI2023

Applying Bayesian inference and deterministic anisotropy to retrieve the molecular structure ∣Ψ(R)∣2 distribution from gas-phase diffraction experiments

Abstract Currently, our general approach to retrieving molecular structures from ultrafast gas-phase diffraction heavily relies on complex ab initio electronic or vibrational excited state simulations to make conclusive interpretations. Without such simulations, inverting this measurement for the structural probability distribution is typically intractable. This creates a so-called inverse problem. Here we address this inverse problem by developing a broadly applicable method that approximates the molecular frame structure ∣Ψ( R , t )∣ 2 distribution independent of these complex simulations. We retrieve the vibronic ground state ∣Ψ( R )∣ 2 for both simulated stretched NO 2 and measured N 2 O. From measured N 2 O, we observe 40 mÅ coordinate-space resolution from 3.75 Å −1 reciprocal space range and poor signal-to-noise, a 50X improvement over traditional Fourier transform methods. In simulated NO 2 diffraction experiments, typical to high signal-to-noise levels predict 100–1000X resolution improvements, down to 0.1 mÅ. By directly measuring the width of ∣Ψ( R )∣ 2 , we open ultrafast gas-phase diffraction capabilities to measurements beyond current analysis approaches. This method has the potential to effectively turn gas-phase ultrafast diffraction into a discovery-oriented technique to probe systems that are prohibitively difficult to simulate.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Recent Developments in the General Atomic and Molecular Electronic Structure System

A discussion of many of the recently implemented features of GAMESS (General Atomic and Molecular Electronic Structure System) and LibCChem (the C++ CPU/GPU library associated with GAMESS) is presented. These features include fragmentation methods like the fragment molecular orbital, effective fragment potential and effective fragment molecular orbital methods, hybrid MPI/OpenMP approaches to Hartree-Fock and resolution of the identity second order perturbation theory. Many new coupled cluster theory methods have been implemented in GAMESS, as have multiple levels of density functional/tight binding theory. The role of accelerators, especially graphical processing units, is discussed in the context of the new features of LibCChem, as is the associated problem of power consumption as the power of computers increases dramatically. The process by which a complex program suite like GAMESS is maintained and developed is considered. Future developments are briefly summarized.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Real-time data reduction at 100 Tbps: Challenge and opportunity for AI-based data reduction for next-generation large-scale nuclear physics collider experiment

The modern large-scale nuclear physics (NP) experiments in high-energy particle colliders utilize streaming-readout electronics to digitize detector response at O(100) Tbps bandwidth. Prominent examples at Brookhaven National Lab (BNL) include the sPHENIX experiment at Relativistic Heavy Ion Collider (RHIC), which is under construction, and the experiments proposed for the Electron-Ion Collider (EIC), planned for the 2030s . One of the main challenges for these streaming readout systems is to manage the data rate with sufficient data reduction in real time so the end-data fit persistent storage for offline analysis, which is typically at O(1000) times smaller and O(100) Gbps. Such data reduction traditionally is achieved via real-time high level triggers, which select and save a small subset of collisions of interest. Although triggering is applicable to high energy collider experiments such as those at the Large Hardron Collider at CERN, it is insufficient for these nuclear physics experiments which study diverse collision topologies. And traditional triggering approach is inefficient to preserve the max information harvested from the operation of colliders that costs O(100)M per year to DOE. Meanwhile, in recent years, ML-based high-throughput data reduction has emerged as a promising approach to efficiently preserve max information for a given space of persistent storage, e.g. via AI data compression, feature extraction, and noise filtering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1984

NGC 7213 - A key to the nature of liners?

New optical spectra of the nearby S0 galaxy NGC 7213 are analyzed. The observations are described and a brief overview of the spectrum is given. The subtraction of the stellar component is presented, and the measurement of various emission lines is discussed in detail. Important physical parameters are derived, including those pertaining to atomic data, line widths, physical conditions, geometry and kinematics, the Balmer decrement, and ultraviolet emission lines. The Seyfert characteristics of NGC 7213 are reviewed, and the galaxy's shock features are reconciled with photoionization models. The presented arguments may apply to classical liners as well. Theoretical models that can help explain the relationships discovered among the emission lines are examined.

Filippenko, A. V.↗
DOE OSTI2023

Relativistic Hartree–Fock chiral Lagrangians with confinement, nucleon finite size and short-range effects

A relativistic Hartree–Fock Lagrangian including a chiral potential and nucleon polarisation is investigated in hopes of providing a better description of dense nuclear matter. Here, we fully consider the contribution of the exchange Fock term to the energy and the self-energies, and in addition we investigate the nucleon’s compositeness and finite size effects (confinement and form factors) and short range correlations modeled by a Jastrow ansatz. These effects are added step by step, such that their impact on the dense matter properties can be analysed in details. The parameters of the model are adjusted to reproduce fundamental properties related to the QCD theory at low energy, such as the chiral symmetry breaking, nucleon’s quark substructure and Lattice-QCD predictions, as well as two empirical properties at saturation: the binding energy and the density. All other empirical parameters, e.g., symmetry energy and its slope, incompressibility modulus, effective mass, as well as spin–isospin Landau–Midgal parameter are predictions of the models and can be used to evaluate the gain of the different approximation schemes in describing nuclear properties. Bayesian statistics is employed in order to propagate parameter uncertainties into predictions for the nuclear matter properties. We show that the splitting of the effective Landau mass is largely influenced by the value of the ρ T coupling, and we show that the fit to the symmetry energy, which induces an increase of the coupling constant g ρ by about 20–25% compared to the case where it is fixed by the quark model, provides a very good EoS compatible with the present nuclear physics knowledge.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Near-surface damage and mixing in Si-Cl 2 -Ar atomic layer etching processes: Insights from molecular dynamics simulations

Silicon-chlorine-argon (Si-Cl 2 -Ar) atomic layer etching (ALE) is simulated using classical molecular dynamics (MD). The simulations provide a detailed view into the near-surface region during ALE processing. Bombardment of Ar + ions creates a mixed amorphous region that significantly differs from the picture of ideal ALE. There is also a significant change in the Si etch yield and the etch product distribution as a function of Ar + ion fluence. The Si etch yield is the highest at the beginning of the bombardment step but eventually decays to the physical sputtering yield. Atomic Cl and silicon chlorides are major etch products at the start of an ion bombardment step, but quickly decay. Atomic Si yields remain relatively constant as a function of Ar + ion fluence. As a result, a new schematic of Si-Cl 2 -Ar ALE is presented in order to emphasize the complex behavior observed in MD simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1956

Energy of Cohesion, Compressibility, and the Potential Energy Functions of the Graphite System

The lattice summations of the potential energy of importance in the graphite system have been computed by direct summation assuming a Lennard‐Jones 6–12 potential between carbon atoms. From these summations, potential energy curves were constructed for interactions between a carbon atom and a graphite monolayer, between a carbon atom and a graphite surface, between a graphite monolayer and a semi‐infinite graphite crystal and between two graphite semi‐infinite crystals. Using these curves, the equilibrium distance between two isolated physically interacting carbon atoms was found to be 2.70 a, where a is the carbon‐carbon distance in a graphite sheet. The distance between a surface plane and the rest of the crystal was found to be 1.7% greater than the interlayer spacing. Theoretical values of the energy of cohesion and the compressibility were calculated from the potential curve for the interaction between two semi‐infinite crystals. They were ΔE c = —330 ergs/cm 2 and β = 3.18×10 —12 cm 2 /dyne, respectively. These compared favorably with the experimental values of ΔE c = —260 ergs/cm 2 and β = 2.97×10 —2 cm 2 /dyne.

L A Girifalco↗
NASA NTRS1927

High-speed Oil Engines for Vehicles. Part II

Further progress toward the satisfactory solution of the difficult problem of the distribution and atomization of the injected fuel was made by extensive experimentation with various fuel valves, nozzles, and atomizing devices. Valuable information was also obtained through numerous experimental researches on the combustion of oils and the manner of introducing the combustion air into the cylinder, as well as on the physical processes of atomization, the determination of the size of drops, etc. These researches led to the conclusion that it is possible, even without producing great turbulence in the combustion chamber and at moderate pump pressure, if the degree of atomization and the penetrative power of the fuel jet are adapted to the shape of the combustion chamber and to the dimensions of the cylinder.

ENGINES, OIL↗
NASA NTRS1980

Methods for Monte Carlo simulation of the exospheres of the moon and Mercury

A general form of the integral equation of exospheric transport on moon-like bodies is derived in a form that permits arbitrary specification of time varying physical processes affecting atom creation and annihilation, atom-regolith collisions, adsorption and desorption, and nonplanetocentric acceleration. Because these processes usually defy analytic representation, the Monte Carlo method of solution of the transport equation, the only viable alternative, is described in detail, with separate discussions of the methods of specification of physical processes as probabalistic functions. Proof of the validity of the Monte Carlo exosphere simulation method is provided in the form of a comparison of analytic and Monte Carlo solutions to three classical, and analytically tractable, exosphere problems. One of the key phenomena in moonlike exosphere simulations, the distribution of velocities of the atoms leaving a regolith, depends mainly on the nature of collisions of free atoms with rocks. It is shown that on the moon and Mercury, elastic collisions of helium atoms with a Maxwellian distribution of vibrating, bound atoms produce a nearly Maxwellian distribution of helium velocities, despite the absence of speeds in excess of escape in the impinging helium velocity distribution.

Hodges, R. R., Jr.↗
DOE OSTI2022

Advanced Physics Models for Particle-Particle Interactions (UCD final report)

The LDRD "Advanced Physics Models for Particle-Particle Interactions” collaborative research with Professor Jennifer Sinclair Curtis and PhD student Chanh Nguyen at the University of California, Davis involved meso-scale, discrete element method (DEM) modeling of micron-sized particles impacting a substrate. Using DEM, physical insight into the details of particle response upon impact can be obtained. Such details provide the type of information necessary to enhance existing continuum or macro-scale simulation tools so that modeling for material strength and particle breakage models is based on particle physics versus empirical relationships. While molecular dynamics simulations of atoms can also provide physical insight into the particle response to impact, the scale of particles that are treated is on the order of angstroms, not microns. This study gives evidence to the ability of the DEM simulation technique to provide such fundamental, detailed insight for micron-sized particles as a function of particle properties and impact velocity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles

The molecular dipole moment ( μ ) is a central quantity in chemistry. It is essential in predicting infrared and sum-frequency generation spectra as well as induction and long-range electrostatic interactions. Furthermore, it can be extracted directly—via the ground state electron density—from high-level quantum mechanical calculations, making it an ideal target for machine learning (ML). Here, we choose to represent this quantity with a physically inspired ML model that captures two distinct physical effects: local atomic polarization is captured within the symmetry-adapted Gaussian process regression framework which assigns a (vector) dipole moment to each atom, while the movement of charge across the entire molecule is captured by assigning a partial (scalar) charge to each atom. The resulting “MuML” models are fitted together to reproduce molecular μ computed using high-level coupled-cluster theory and density functional theory (DFT) on the QM7b dataset, achieving more accurate results due to the physics-based combination of these complementary terms. The combined model shows excellent transferability when applied to a showcase dataset of larger and more complex molecules, approaching the accuracy of DFT at a small fraction of the computational cost. We also demonstrate that the uncertainty in the predictions can be estimated reliably using a calibrated committee model. The ultimate performance of the models—and the optimal weighting of their combination—depends, however, on the details of the system at hand, with the scalar model being clearly superior when describing large molecules whose dipole is almost entirely generated by charge separation. These observations point to the importance of simultaneously accounting for the local and non-local effects that contribute to μ ; furthermore, they define a challenging task to benchmark future models, particularly those aimed at the description of condensed phases.

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

The road to atomically thin metasurface optics

Abstract The development of flat optics has taken the world by storm. The initial mission was to try and replace conventional optical elements by thinner, lightweight equivalents. However, while developing this technology and learning about its strengths and limitations, researchers have identified a myriad of exciting new opportunities. It is therefore a great moment to explore where flat optics can really make a difference and what materials and building blocks are needed to make further progress. Building on its strengths, flat optics is bound to impact computational imaging, active wavefront manipulation, ultrafast spatiotemporal control of light, quantum communications, thermal emission management, novel display technologies, and sensing. In parallel with the development of flat optics, we have witnessed an incredible progress in the large-area synthesis and physical understanding of atomically thin, two-dimensional (2D) quantum materials. Given that these materials bring a wealth of unique physical properties and feature the same dimensionality as planar optical elements, they appear to have exactly what it takes to develop the next generation of high-performance flat optics.

Brongersma, Mark L.↗
NASA NTRS1972

Evidence on the composition and mineralogy of the lunar highlands

Analyses of rare earth elements in various lunar samples are shown. The elements are listed in order of increasing atomic number, and the abundances are relative to primordial abundances as determined from stony meteorites. Analyses of soils from Apollo 11, 12, and 14 and Luna 16 missions are also shown. These elements show small regular differences in chemical and physical properties with atomic number.

Schnetzler, C. C.↗