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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Path-space variational inference for non-equilibrium coarse-grained systems

In this paper we discuss information-theoretic tools for obtaining optimized coarse-grained molecular models for both equilibrium and non-equilibrium molecular simulations. The latter are ubiquitous in physicochemical and biological applications, where they are typically associated with coupling mechanisms, multi-physics and/or boundary conditions. In general the non-equilibrium steady states are not known explicitly as they do not necessarily have a Gibbs structure. The presented approach can compare microscopic behavior of molecular systems to parametric and non-parametric coarse-grained models using the relative entropy between distributions on the path space and setting up a corresponding path-space variational inference problem. The methods can become entirely data-driven when the microscopic dynamics are replaced with corresponding correlated data in the form of time series. Furthermore, we present connections and generalizations of force matching methods in coarse-graining with path-space information methods. We demonstrate the enhanced transferability of information-based parameterizations to different observables, at a specific thermodynamic point, due to information inequalities. We discuss methodological connections between information-based coarse-graining of molecular systems and variational inference methods primarily developed in the machine learning community. However, we note that the work presented here addresses variational inference for correlated time series due to the focus on dynamics. The applicability of the proposed methods is demonstrated on high-dimensional stochastic processes given by overdamped and driven Langevin dynamics of interacting particles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Restricted Collision List method for faster Direct Simulation Monte-Carlo (DSMC) collisions

The ‘Restricted Collision List’ (RCL) method for speeding up the calculation of DSMC Variable Soft Sphere collisions, with Borgnakke–Larsen (BL) energy exchange, is presented. The method cuts down considerably on the number of random collision parameters which must be calculated (deflection and azimuthal angles, and the BL energy exchange factors). A relatively short list of these parameters is generated and the parameters required in any cell are selected from this list. The list is regenerated at intervals approximately equal to the smallest mean collision time in the flow, and the chance of any particle re-using the same collision parameters in two successive collisions is negligible. The results using this method are indistinguishable from those obtained with standard DSMC. The CPU time saving depends on how much of a DSMC calculation is devoted to collisions and how much is devoted to other tasks, such as moving particles and calculating particle interactions with flow boundaries. For 1-dimensional calculations of flow in a tube, the new method saves 20% of the CPU time per collision for VSS scattering with no energy exchange. With RCL applied to rotational energy exchange, the CPU saving can be greater; for small values of the rotational collision number, for which most collisions involve some rotational energy exchange, the CPU may be reduced by 50% or more.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

DG-IMEX method for a two-moment model for radiation transport in the $\mathscr{O}$($v$/$c$) limit

Here, we consider neutral particle systems described by moments of a phase-space density and propose a realizability-preserving numerical method to evolve a spectral two-moment model for particles interacting with a background fluid moving with nonrelativistic velocities. The system of nonlinear moment equations, with special relativistic corrections to $\mathscr{O}$($v$/$c$), expresses a balance between phase-space advection and collisions and includes velocity-dependent terms that account for spatial advection, Doppler shift, and angular aberration. The model is conservative for the correct $\mathscr{O}$($v$/$c$) Eulerian-frame number density and is consistent, to $\mathscr{O}$($v$/$c$), with Eulerian-frame energy and momentum conservation. This model is closely related to the one promoted by Lowrie et al. and similar to models currently used to study transport phenomena in large-scale simulations of astrophysical environments. The proposed numerical method is designed to preserve moment realizability, which guarantees that the moments correspond to a nonnegative phase-space density. The realizability-preserving scheme consists of the following key components: (i) a strong stability-preserving implicit-explicit (IMEX) time-integration method; (ii) a discontinuous Galerkin (DG) phase-space discretization with carefully constructed numerical uxes; (iii) a realizability-preserving implicit collision update; and(iv) a realizability-enforcing limiter. In time integration, nonlinearity of the moment model necessitates solution of nonlinear equations, which we formulate as fixed-point problems and solve with tailored iterative solvers that preserve moment realizability with guaranteed global convergence. We also analyze the simultaneous Eulerian-frame number and energy conservation properties of the semi-discrete DG scheme and propose a "spectral redistribution" scheme that promotes Eulerian-frame energy conservation. Through numerical experiments, we demonstrate the accuracy and robustness of this DG-IMEX method and investigate its Eulerian-frame energy conservation properties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Analytical local stress model for UMo/Al dispersion fuel

The stress evolution occurring in UMo/Al dispersion fuel is important since it affects the fuel performance during irradiation. In this study, a new analytical model was developed to predict the local stresses in UMo/Al dispersion fuel. In the model, a hypothetical unit sphere composed of a UMo fuel particle, interaction layer (IL), and Al matrix was considered, and the governing equations for the stress-strain relationship, strain-displacement, and mechanical equilibrium were established using a spherical coordinate system. The mathematical derivations were obtained for local stresses in the radial and circumferential direction using a thick-walled sphere model. Furthermore, this analytical model employed the stress distribution as the boundary condition, which is calculated using a finite element model with homogenized fuel meat. The developed model’s solution scheme was verified against Abaqus solutions obtained for two irradiated plates with heterogeneous meat. The model calculated consistent results for interfacial stresses in the IL and Al matrix, indicating that the newly developed model was reliable when simultaneously calculating fission gas pressurization on the UMo/IL/Al composite, and the use of the stress distribution in the homogenized fuel meat as the boundary condition for the analytical model was acceptable

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

The calculation of light element impurity (α, n) yield curves in a PuO 2 matrix and associated specific yield coefficients: Influence of the reaction cross sections

Most of the Pu separated from irradiated commercial nuclear fuel is stored as PuO 2 . The primary quantitative nondestructive measurement technique used to verify the amount of Pu in storage containers is passive neutron correlation counting. An important physical property of the oxide material is the ratio, α, of the rate of (α, n) neutrons produced inside the item to the rate of neutrons produced by spontaneous fission. This ratio influences the precision of the correlated counting method and affects the interpretation of the data because of how it changes both the primary total neutron production rate and the rate of induced fission events taking place inside the item. In addition to the main O(α, n) contribution, additional contributions come from α-particle interactions with light element impurities that are inevitably present. In this work, we calculate specific (α, n) yield coefficients, expressed in units of neutrons per second per gram of α-emitting nuclide per part per million by mass of the specified impurity element distributed in a pure PuO 2 matrix, for some key α-emitting actinides commonly present in reprocessed Pu ( 238–242 Pu+ 241 Am). These coefficients are directly applicable to nuclear safeguards verification work in which the α ratio is often calculated from the Pu-isotopic composition and chemical information obtained by other means. Further, they also provide a convenient up-to-date reference set against which values generated by other methods can be compared. Results are presented for impurities with atomic number from 3 to 17 inclusive, plus K and Fe. In most cases, these coefficients are not expected to change by more than 5%–10% at any time in the future. However, as new data become available, changes as large as 20% may be needed for some targets (e.g., F). The present yield calculations are limited by the general shortage of quality experimental total (α, n) reaction cross section data, which, together with unexplained variation between determinations, means that an objective and coherent evaluation is not possible. The situation is even less satisfactory for the partial differential cross section needed to calculate neutron spectra.

(𝛼, n) reactions↗
DOE OSTI2025

Simulations of neutron unbound physics for Geant4

The study of neutron unbound systems via the invariant mass technique is the primary focus of the MoNA Collaboration, which built and operates the Modular Neutron Array (MoNA) and the Large multi-Institutional Scintillator Array (LISA) at FRIB. Advancements in nuclear structure from theory and experiment along the neutron dripline have presented opportunities to understand the nature of unbound systems in higher mass nuclei. The GEometry ANd Tracking (Geant4) platform has been used in high-energy and nuclear physics to simulate particle interactions with as much detail as the user desires. Geant4 currently does not have a physics class to simulate neutron unbound systems. Given the advancement of accelerator facilities and active searches along the neutron dripline, detailed simulations to study the breakup of neutron unbound systems, are necessary. Furthermore, the implementation of the breakup of neutron unbound systems in Geant4 will be presented.

Neutron dripline↗
DOE OSTI2015

DAMIC at SNOLAB

We introduce the fully-depleted charge-coupled device (CCD) as a particle detector. We demonstrate its low energy threshold operation, capable of detecting ionizing energy depositions in a single pixel down to 50 eV ee . We present results of energy calibrations from 0.3 keV ee to 60 ke Vee , showing that the CCD is a fully active detector with uniform energy response throughout the silicon target, good resolution (Fano ~0.16), and remarkable linear response to electron energy depositions. We show the capability of the CCD to localize the depth of particle interactions within the silicon target. We discuss the mode of operation and unique imaging capabilities of the CCD, and how they may be exploited to characterize and suppress backgrounds. We present the first results from the deployment of 250 μm thick CCDs in SNOLAB, a prototype for the upcoming DAMIC100. DAMIC100 will have a target mass of 0.1 kg and should be able to directly test the CDMS-Si signal within a year of operation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Towards a theory of hadron resonances

In this review, we present the current state of the art of our understanding of the spectrum of excited strongly interacting particles and discuss methods that allow for a systematic and model-independent calculation of the hadron spectrum. These are lattice QCD and effective field theories. Synergies between both approaches can be exploited allowing for a deeper understanding of the hadron spectrum. Results based on effective field theories and hadron–hadron scattering in lattice QCD or combinations thereof are presented and discussed. We also show that the often used Breit–Wigner parametrization is at odds with chiral symmetry and should not be used in case of strongly coupled channels.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Essential barrier height and a probabilistic approach in characterizing potential landscape

In this work we propose a probabilistic approach to investigate the shape of landscapes of multi-dimensional potential functions. Under a suitable coupling scheme, two copies of the overdamped Langevin dynamics associated with the potential function are coupled, and the coupling times are collected. Assuming a set of intuitive yet technically challenging conditions on the coupling scheme, it is shown that the tail distributions of the coupling times exhibit qualitatively different dependencies on the noise magnitude for single-well versus multi-well potential functions. More specifically, for convex single-well potentials, the negative tail exponent of the coupling time distribution is uniformly bounded away from zero by the convexity parameter and is independent of the noise magnitude. In contrast, for multi-well potentials, the negative tail exponent decreases exponentially as the noise vanishes, with the decay rate governed by the essential barrier height, a quantity introduced in this paper to characterize the non-convex nature of the potential function. Numerical investigations are conducted for a variety of examples, including the Rosenbrock function, interacting particle systems, and loss functions arising in artificial neural networks. These examples not only illustrate the theoretical results in various contexts but also provide crucial numerical validation of the conjectured assumptions, which are essential to the theoretical analysis yet lie beyond the reach of standard technical tools.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Solvent and A-Site Cation Control Preferred Crystallographic Orientation in Bromine-Based Perovskite Thin Films

Preferred crystallographic orientation in polycrystalline films is desirable for efficient charge carrier transport in metal halide perovskites and semiconductors. However, the mechanisms that determine the preferred orientation of halide perovskites are still not well understood. In this work, we investigate crystallographic orientation in lead bromide perovskites. We show that the solvent of the precursor solution and organic A-site cation strongly affect the preferred orientation of the deposited perovskite thin films. Specifically, we show that the solvent, dimethylsulfoxide, influences the early stages of crystallization and induces preferred orientation in the deposited films by preventing colloidal particle interactions. Additionally, the methylammonium A-site cation induces a higher degree of preferred orientation than the formamidinium counterpart. We use density functional theory to show that the lower surface energy of the (100) plane facets in methylammonium-based perovskites, compared to the (110) planes, is the reason for the higher degree of preferred orientation. In contrast, the surface energy of the (100) and (110) facets is similar for formamidinium-based perovskites, leading to lower degree of preferred orientation. Furthermore, we show that different A-site cations do not significantly affect ion diffusion in bromine-based perovskite solar cells but impact ion density and accumulation, leading to increased hysteresis. Our work highlights the interplay between the solvent and organic A-site cation which determine crystallographic orientation and plays a critical role in the electronic properties and ionic migration of solar cells.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Including Physics-Informed Atomization Constraints in Neural Networks for Reactive Chemistry

Machine learning interatomic potentials (MLIPs) have emerged as powerful tools for investigating atomistic systems with high accuracy and a relatively low computational cost. However, a common and unaddressed challenge with many current neural network (NN) MLIP models is their limited ability to accurately predict the relative energies of systems containing isolated or nearly isolated atoms, which appear in various reactive processes. To address this limitation, we present a mathematical technique for modifying any existing atom-centered NN architecture to account for the energies of isolated atoms. The result produces a consistent prediction of the atomization energy (AE) of a system using minimal constraints on the model. Using this technique, we build a model architecture that we call hierarchically interacting particle neural network (HIP-NN)-AE, an AE-constrained version of the HIP-NN, as well as ANI-AE, the AE-constrained version of the accurate NN engine for molecular energies (ANI). Our results demonstrate AE consistency of AE-constrained models, which drastically improves the AE predictions for the models. We compare the AE-constrained approach to unconstrained models as well as models from the literature in other scenarios, such as bond dissociation energies, bond dissociation pathways, and extensibility tests. These results show that the constraints improve the model performance in some of these tasks and do not negatively affect the performance on any tasks. The AE constraint approach thus offers a robust solution to the challenges posed by isolated atoms in energy prediction tasks.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Physics-Driven Construction of Compact Primitive Gaussian Density Fitting Basis Sets

We present a model-assisted density fitting (MADF) basis set generator, an algorithm for generating primitive atomic Gaussian density fitting (DF) basis sets (DFBSs) from a contracted Gaussian orbital basis set (OBS). The MADF algorithm produces DFBSs suitable for accurate robust DF approximation of 2-particle interactions in mean-field and correlated electronic structures. The algorithm is designed to (a) saturate the OBS product space by a large regularized set of primitive solid-harmonic Gaussian shells with nonuniform distribution of exponents, followed by (b) pruning of the shells according to their contributions to the 2- body energy of a correlated atomic ensemble. Building the DFBS generator model almost exclusively on mathematical and physical principles allows one to limit the number of parameters that control the density fitting error to three, with a single set of parameters sufficient for computations with all basis cardinal numbers, with and without correlation of core electrons, with and without scalar and spin-dependent relativistic effects, spanning almost all of the Periodic Table. Performance assessment included basis sets up to quadruple-ζ quality from several major basis set families, using molecules composed of main-group, d-block, and f-block elements. The resulting DF errors in Hartree−Fock and second-order MP2 energies (with relativistic all-electron treatments, when appropriate) were on the order of 20 and 10 μE h per electron, respectively.

Approximation↗
DOE OSTI2018

Transferable Dynamic Molecular Charge Assignment Using Deep Neural Networks

We report that the ability to accurately and efficiently compute quantum-mechanical partial atomistic charges has many practical applications, such as calculations of IR spectra, analysis of chemical bonding, and classical force field parametrization. Machine learning (ML) techniques provide a possible avenue for the efficient prediction of atomic partial charges. Modern ML advances in the prediction of molecular energies [i.e., the hierarchical interacting particle neural network (HIP-NN)] has provided the necessary model framework and architecture to predict transferable, extensible, and conformationally dynamic atomic partial charges based on reference density functional theory (DFT) simulations. Utilizing HIP-NN, we show that ML charge prediction can be highly accurate over a wide range of molecules (both small and large) across a variety of charge partitioning schemes such as the Hirshfeld, CM5, MSK, and NBO methods. To demonstrate transferability and size extensibility, we compare ML results with reference DFT calculations on the COMP6 benchmark, achieving errors of 0.004e – (elementary charge). This is remarkable since this benchmark contains two proteins that are multiple times larger than the largest molecules in the training set. An application of our atomic charge predictions on nonequilibrium geometries is the generation of IR spectra for organic molecules from dynamical trajectories on a variety of organic molecules, which show good agreement with calculated IR spectra with reference method. Critically, HIP-NN charge predictions are many orders of magnitude faster than direct DFT calculations. Lastly, these combined results provide further evidence that ML (specifically HIP-NN) provides a pathway to greatly increase the range of feasible simulations while retaining quantum-level accuracy.

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

Simulating Crystallization in a Colloidal System Using State Predictive Information Bottleneck Based Enhanced Sampling

Here, we investigate crystal nucleation in supersaturated colloid suspensions using enhanced molecular dynamics simulations augmented with machine learning techniques. The simulations reveal that crystallization in the model colloidal system studied here, with particles interacting through a repulsive screened Coulomb Yukawa potential, proceeds from vapor to dense liquid droplet to crystalline phases across multiple high barriers. Employing a one-dimensional reaction coordinate derived from the State Predictive Information Bottleneck framework, our simulations capture back-and-forth phase transitions across multiple barriers effectively in biased metadynamics simulations. We obtain relative free energy differences between different phases and also quantify the roles of different molecular level features in driving the phase changes.

Chemistry↗
DOE OSTI2018

Electrolyte-Assisted Hydrogen Storage Reactions

Use of electrolytes, in the form of LiBH 4 /KBH 4 and LiI/KI/CsI eutectics, is shown to significantly improve (by more than a factor of 10) both the dehydrogenation and full rehydrogenation of the MgH 2 /Sn destabilized hydride system and the hydrogenation of MgB 2 to Mg(BH 4 ) 2 . The improvement revealed that interparticle transport of atoms heavier than hydrogen can be an important rate-limiting step during hydrogen cycling in hydrogen storage materials consisting of multiple phases in powder form. Electrolytes enable solubilizing heavy ions into a liquid environment and thereby facilitate the reaction over full surface areas of interacting particles. In conclusion, the examples presented suggest that use of electrolytes in the form of eutectics, ionic liquids, or solvents containing dissolved salts may be generally applicable for increasing reaction rates in complex and destabilized hydride materials.

08 HYDROGEN↗
DOE OSTI2014

Selective Functionalization of the Nanogap of a Plasmonic Dimer

We report a self-developing anisotropic gold/polymer hybrid nanosystem that precisely places dye molecules at the plasmonic hotspot of metal nanostructures for sensing and photonics applications. Unlike conventional molecule-particle configurations, the anisotropic hybrid nanosystem (AHN) introduces an anisotropic spatial distribution of dye-containing active medium. This allows us to precisely overlap the near-field spatial distribution with the active medium and rule out the contribution from the background molecules. This overlap effect selectively highlights the optical response of the molecules of interest, i.e., molecules located at the hotspots. Our AHN consists of gold nanodimers whose gaps have been filled with methylene blue molecules. They have been studied by plasmon-enhanced Raman spectroscopy as a probing tool. The AHN opens new doors not only for fundamental studies and photonics applications of molecule-particle interactions, but also for molecular trapping methods at the nanoscale.

hybrid nanostructures↗