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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Mechanistic insights into electrochemical reduction of CO 2 over Ag using density functional theory and transport models

Significance Chemical storage of solar energy can be achieved by electrochemical reduction of CO 2 to CO and H 2 , and subsequent conversion of this mixture to fuels. Identifying optimal conditions for electrochemical cell operation requires knowledge of the CO 2 reduction mechanism and the influence of all factors controlling cell performance. We report a multiscale model for predicting the current densities for H 2 and CO formation from first principles. Our approach brings together a quantum-chemical analysis of the reaction pathway, a microkinetic model of the reaction dynamics, and a continuum model for mass transport of all species through the electrolyte. This model is essential for identifying a physically correct representation of product current densities dependence on the cell voltage and CO 2 partial pressure.

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

Hydrologic Modeling of Subsurface Brine Density Stratification for Deep Borehole Disposal - 20213

Density-dependent and topographically-driven subsurface brine flow was modeled in regional-scale and Deep Borehole Disposal-scale domains under varying conditions. These conditions included variable basement permeability, brine density, and hydraulic head. Findings revealed the possibility of hydraulic isolation of deep basement for at least 1 million years under appropriate conditions, which supports the viability of the Deep Borehole Disposal concept. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Learning protein fitness models from evolutionary and assay-labeled data

Machine learning-based models of protein fitness typically learn from either unlabeled, evolutionarily related sequences or variant sequences with experimentally measured labels. For regimes where only limited experimental data are available, recent work has suggested methods for combining both sources of information. Toward that goal, we propose a simple combination approach that is competitive with, and on average outperforms more sophisticated methods. Our approach uses ridge regression on site-specific amino acid features combined with one probability density feature from modeling the evolutionary data. Within this approach, we find that a variational autoencoder-based probability density model showed the best overall performance, although any evolutionary density model can be used. Moreover, our analysis highlights the importance of systematic evaluations and sufficient baselines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Quantifying the Influence of Size, Shape, and Density of Microplastics on Their Transport Modes: A Modeling Approach

Microplastics (MPs) pose significant risks to marine ecosystems and human health, necessitating accurate predictions of their distributions in aquatic environments for effective risk mitigation. However, understanding MP transport dynamics is challenging because of the inadequate representation of MP characteristics such as size, shape, and density in numerical models. Further, the accuracy of the MP vertical profiles in existing models has not been thoroughly validated. Thus, we developed an MP transport model within the Finite Volume Community Ocean Model framework (FVCOM-MP) by integrating MP characteristics. We validated FVCOM-MP against experimental and analytical data, focusing on various MP transport modes and transitions. FVCOM-MP successfully replicates MP profiles in different transport modes, including the bedload, surface-load, suspended-load, and mixed-load modes. Additionally, we introduce phase diagrams for classifying MP transport modes based on particle characteristics, enhancing our understanding of MP dynamics in aquatic systems. The transport modes for a number of real-world MP particles, including fishing line, plastic bag/bottle fragments, synthetic fibers, tire wear particles, polyvinyl chloride and expanded polystyrene pellets, were analyzed with these phase diagrams.

Microplastic transport, Settling velocity, Rising ↗
DOE OSTI2017

Numerical Optimization of Density Functional Tight Binding Models: Application to Molecules Containing Carbon, Hydrogen, Nitrogen, and Oxygen

New parametrizations for semiempirical density functional tight binding (DFTB) theory have been developed by the numerical optimization of adjustable parameters to minimize errors in the atomization energy and interatomic forces with respect to ab initio calculated data. Initial guesses for the radial dependences of the Slater- Koster bond integrals and overlap integrals were obtained from minimum basis density functional theory calculations. The radial dependences of the pair potentials and the bond and overlap integrals were represented by simple analytic functions. The adjustable parameters in these functions were optimized by simulated annealing and steepest descent algorithms to minimize the value of an objective function that quantifies the error between the DFTB model and ab initio calculated data. The accuracy and transferability of the resulting DFTB models for the C, H, N, and O system were assessed by comparing the predicted atomization energies and equilibrium molecular geometries of small molecules that were not included in the training data from DFTB to ab initio data. The DFTB models provide accurate predictions of the properties of hydrocarbons and more complex molecules containing C, H, N, and O.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Reference interaction site model with hydrophobicity induced density inhomogeneity: An analytical theory to compute solvation properties of large hydrophobic solutes in the mixture of polyatomic solvent molecules

Reference interaction site model (RISM) has recently become a popular approach in the study of thermodynamical and structural properties of the solvent around macromolecules. On the other hand, it was widely suggested that there exists water density depletion around large hydrophobic solutes (>1 nm), and this may pose a great challenge to the RISM theory. In this paper, we develop a new analytical theory, the Reference Interaction Site Model with Hydrophobicity induced density Inhomogeneity (RISM-HI), to compute solvent radial distribution function (RDF) around large hydrophobic solute in water as well as its mixture with other polyatomic organic solvents. To achieve this, we have explicitly considered the density inhomogeneity at the solute-solvent interface using the framework of the Yvon-Born-Green hierarchy, and the RISM theory is used to obtain the solute-solvent pair correlation. In order to efficiently solve the relevant equations while maintaining reasonable accuracy, we have also developed a new closure called the D2 closure. With this new theory, the solvent RDFs around a large hydrophobic particle in water and different water-acetonitrile mixtures could be computed, which agree well with the results of the molecular dynamics simulations. Furthermore, we show that our RISM-HI theory can also efficiently compute the solvation free energy of solute with a wide range of hydrophobicity in various water-acetonitrile solvent mixtures with a reasonable accuracy. We anticipate that our theory could be widely applied to compute the thermodynamic and structural properties for the solvation of hydrophobic solute.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2024

Dust Model Sensitivity to Dust Source Mask, Sandblasting Efficiency, Air Density, and Land Use: Implications for Model Improvement

This study compares dust storm simulations using two commonly adopted methods for representing four important dust emission parameters. Compared to a dynamic dust source mask based on land use and vegetation cover, a static mask based solely on land use overestimates dust concentration and optical depth by a factor of 2, besides generating spurious emissions. The results reinforce that seasonal variations in vegetation cover can significantly affect dust emissions. For sandblasting efficiency, a clay-dependent semiempirical expression produces 10 times more dust than a physics-based expression. Simulations using model-predicted versus a fixed constant for air density differ by only 8%. However, this difference could range between 12 and 22% for annual simulations over global dust source regions. Simulations with updated versus old land use data, using the same dust source mask, differ twofold, indicating the significant impact of land use change on regional dust emission in central Arizona. The differences in the pairs of these simulations are generally larger than the uncertainty due to meteorology. The simulations align better with observation when using the dynamic dust source mask, the physics-based sandblasting efficiency, and the up-to-date land use data. Given the high sensitivity of dust to surface conditions, the results discussed have implications for improving the dust cycle in weather and climate models and for interpreting model intercomparisons.

Dust-emission source↗
DOE OSTI2023

Revealing quasi-excitations in the low-density homogeneous electron gas with model exchange–correlation kernels

Time-dependent density functional theory within the linear response regime provides a solid mathematical framework to capture excitations. The accuracy of the theory, however, largely depends on the approximations for the exchange–correlation (xc) kernels. Away from the long-wavelength (or q = 0 short wave-vector) and zero-frequency (ω = 0) limit, the correlation contribution to the kernel becomes more relevant and dominant over exchange. The dielectric function, in principle, can encompass xc effects relevant to describe low-density physics. Furthermore, besides collective plasmon excitations, the dielectric function can reveal collective electron–hole excitations, often dubbed “ghost excitons.” Besides collective excitons, the physics of the low-density regime is rich, as exemplified by a static charge-density wave that was recently found for r s > 69, and was shown to be associated with softening of the plasmon mode. These excitations are seen to be present in much higher density 2D homogeneous electron gases of r s ≳ 4. Here, in this work, we perform a thorough analysis with xc model kernels for excitations of various nature. The uniform electron gas, as a useful model of real metallic systems, is used as a platform for our analysis. We highlight the relevance of exact constraints as we display and explain screening and excitations in the low-density region.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Why Are There so Few Reports of High-Energy Electron Drift Resonances? Role of Radial Phase Space Density Gradients

Models of monochromatic Pc5 (2–7 mHz) ultralow frequency (ULF) wave interactions with high energy (greater than ~1 MeV) electrons predict drift resonant interactions that can cause rapid radial transport and acceleration. There are few reports of electron drift resonance at energies greater than ~1 MeV, in contrast to lower energies; moreover, all previous reports occur in the aftermath of interplanetary shocks. These two facts are difficult to reconcile with theory and numerical simulations predicting that greater than ~1 MeV drift resonances should occur more often and in a wider variety of driving conditions. In this study, we show that a combination of observational sampling biases and nominal radial phase space density gradients is one explanation for this discrepancy between theory and observations. In particular, we examine electron dynamics in two case studies with very similar satellite coverage, solar wind conditions, and Pc5 wave properties, yet with different radial phase space density profiles. Using global wave and particle observations, we show that the events have vastly different particle responses despite having similar wave properties. Placing these results in context with past studies, we further show here that nominal radial PSD gradients near geostationary orbit can mask the expected drift resonance particle response and explain (1) the small number of past greater than ~1 MeV drift resonance reports and (2) the restriction of these reports to interplanetary shock events. We argue that future observational studies characterizing radial transport via drift resonance should examine global particle dynamics, including observations of the radial phase space density profile.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2002

Temperature Dependence of the Rate Constant for the CH3 Recombination Reaction: A Loss Process in Outer Planet Atmospheres

The methyl free radical (CH3) has been observed in the atmospheres of Saturn and Neptune by the ISO satellite. There are discrepancies between the column densities for the CH3 radical derived from the ISO observations and the column densities derived from atmospheric photochemical models. For Neptune the model column density is 1.5 times that derived from ISO. For Saturn the model is 6 times that from ISO. The recombination of methyl radicals is the major loss process for methyl in these atmospheres. The serious disagreement between observed and calculated levels of CH3 has led to suggestions that the atmospheric models greatly underestimated the loss of CH3 due to poor knowledge of the rate of the reaction (1) CH3 + CH3 + M goes to C2H6 + M at the low temperatures and pressures of these atmospheric systems. Although the reaction CH3 + CH3 + M goes to C2H6 + M has been extensively studied both theoretically and experimentally, the laboratory conditions have been, with only a few exceptions, higher temperatures (T greater than 298K), higher pressures (P greater than or equal to 10 Torr - 13.3 mbar) or M=Ar rather than H2 or He as the bath gas.

Cody, R. J.↗
DOE OSTI2017

Accurate model annotation of a near-atomic resolution cryo-EM map

Electron cryomicroscopy (cryo-EM) has been used to determine the atomic coordinates (models) from density maps of biological assemblies. These models can be assessed by their overall fit to the experimental data and stereochemical information. However, these models do not annotate the actual density values of the atoms nor their positional uncertainty. Here, we introduce a computational procedure to derive an atomic model from a cryo- EM map with annotated metadata. The accuracy of such a model is validated by a faithful replication of the experimental cryo-EM map computed using the coordinates and associated metadata. The functional interpretation of any structural features in the model and its utilization for future studies can be made in the context of its measure of uncertainty. We applied this protocol to the 3.3-Å map of the mature P22 bacteriophage capsid, a large and complex macromolecular assembly. With this protocol, we identify and annotate previously undescribed molecular interactions between capsid subunits that are crucial to maintain stability in the absence of cementing proteins or cross-linking, as occur in other bacteriophages.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Modeling Pb(II) Adsorption on Mineral Surfaces: Bridging Density Functional Theory and Experiment with Thermodynamic Insights

Despite decades of work on aqueous lead (Pb) adsorption on a-Fe2O3 (hematite) and a-Al2O3 (alumina), gaps between measurements and modeling obscure molecular-level understanding. Achieving well-matched geometries between theory and experimental for mineral-water interfaces is a hurdle, as surface functional group type and distribution must be accounted for in determining mechanisms. Additionally, computational methods that can describe the substrate are often not appropriate to capture aqueous effects. Progress requires focusing on well-studied and relevant systems, such as key facets (001),(012), and (110) of hematite and alumina, and ubiquitous contaminants such as aqueous Pb. In the past, bulk-parametrized bond-valence principles were used to rationalize Pb(II) adsorption trends. These approaches can break down at surfaces, where flexible bonding environments and adsorption-induced surface relaxations play a critical role. Here, we adapt and apply a density functional theory (DFT) and thermodynamics framework, integrating DFT-calculated energies with experimental data and electrochemical principles, to predict Pb(II) adsorption. Our model results capture trends across the full set of surfaces and predict that inner-sphere Pb(II) sorption on (001) alumina varies from unfavorable to weakly favorable across a range of pH conditions. This aligns with experiment insights that Pb(II) interacts at that surface through outer-sphere interactions. Extending to Fe(II) adsorption, we demonstrate a coverage-dependent site preference, potentially explaining disorder in overlayers grown by the oxidative adsorption of Fe(II) on hematite (001).

lead contamination↗
DOE OSTI2021

Electrocatalytic Reduction of CO 2 to CO over Ag(110) and Cu(211) Modeled by Grand-Canonical Density Functional Theory

We report the results of modeling CO 2 reduction (CO 2 R) to CO over Ag(110) and Cu(211) surfaces at different applied potentials using grand-canonical density functional theory (GC-DFT), a method specifically designed to accurately model electrochemical systems. In addition to demonstrating GC-DFT’s ability to accurately model electrochemical processes, we also compare it with the computational hydrogen electrode (CHE) approach. GC-DFT predicts that the geometries of these reacting systems strongly depend on the applied potential and the Helmholtz free energies vary nonlinearly with the applied potential, which contradicts a central assumption of the CHE approach. The CHE approach neglects the change in the number of electrons on the electrode surface at different applied potentials, which reduces its accuracy as the potential changes from the potential of zero charge. Our results further demonstrate that the grand free energies of the reaction intermediates not only depend on the value of the applied potential but also on the metal surface type, adsorption site, and adsorbate. GC-DFT’s ability to predict the effect of the applied potential on adsorbate geometry enables it to evaluate different possible reaction mechanisms at different applied potentials. For instance, GC-DFT predicts that the first step of CO2R likely switches from proton-coupled electron transfer to sequential electron transfer and then proton transfer at more reducing potentials, a result that cannot be determined by the CHE because it assumes that all electron transfers are coupled to proton transfers and neglects the effect of the applied potential on the adsorbate geometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1985

A Monte Carlo study of parameters affecting computer simulations of crater saturation density

Computer models of cratered surfaces often use inputs of uncertain nature and importance. This work evaluates the sensitivity of the resulting crater-saturation estimates to the input parameters, principally applicable to the study of craters upward from 8 km diameter. In order of decreasing importance, crater saturation simulations are found to be sensitive to: (1) the dynamic range of crater diameters used, (2) the effectiveness of ejecta-blanket obliteration assumed, and (3) the number of points taken to describe the crater rim. The size of the largest crater in proportion to the size of the simulated surface has no effect on the results when the edges of the simulated surface are correctly treated and craters are not counted simply by integers. Craters should be counted by their fractions lying within the simulated area. A similar procedure is recommended when gathering crater size-density data from images.

Woronow, A.↗
NASA NTRS2016

Forward Modeling of Ceres' Gravity Field for Planetary Protection Assessment

The Dawn spacecraft arrived at the dwarf planet Ceres in early 2015 after a two and a half-year cruise in deep space after departing Vesta. The nominal plan for Dawn included successively lower science orbits, the last of which is called the Low Altitude Mapping Orbit that also serves as the disposal orbit after the end of mission. Prior to Dawn’s arrival at Ceres, it was identified that Dawn would have to meet planetary protection requirements at Ceres by remaining on a stable orbit for 20 years past the end of the mission. With little a priori knowledge on Ceres’ interior we analyzed what gravitational perturbations influence the long-term dynamical evolution of Dawn around Ceres and validated that the gravitational model of Ceres with the then-current best estimate of the density distribution model does not exceed the permissible bounds. The forward modeling of gravity fields from various shape models and density distribution was deemed valid to satisfy the planetary protection guidelines. This analysis was further confirmed after a new shape model based on the actual optical images was created. The gravity field as measured in the High Altitude Mapping Orbit also fits within the bounds of gravitational field studied pre-arrival at Ceres to substantiate our methodology used to satisfy the planetary protection requirement.

Takahashi, Yu↗
DOE OSTI2019

Optimization of Condensed Matter Physics Application with OpenMP Tasking Model

The Density Matrix Renormalization Group (DMRG++) is a condensed matter physics application used to study superconductivity properties of materials. It’s main computations consist of calculating hamiltonian matrix which requires sparse matrix-vector multiplications. This paper presents task-based parallelization and optimization strategies of the Hamiltonian algorithm. The algorithm is implemented as a mini-application in C++ and parallelized with OpenMP. The optimization leverages tasking features, such as dependencies or priorities included in the OpenMP standard 4.5. The code refactoring targets performance as much as programmability. The optimized version achieves a speedup of 8.0× with 8 threads and 20.5× with 40 threads on a Power9 computing node while reducing the memory consumption to 90 MB with respect to the original code, by adding less than ten OpenMP directives.

Criado, Joel↗
DOE OSTI2016

Coarse-grained models using local-density potentials optimized with the relative entropy: Application to implicit solvation

Bottom-up multiscale techniques are frequently used to develop coarse-grained (CG) models for simulations at extended length and time scales but are often limited by a compromise between computational efficiency and accuracy. The conventional approach to CG nonbonded interactions uses pair potentials which, while computationally efficient, can neglect the inherently multibody contributions of the local environment of a site to its energy, due to degrees of freedom that were coarse-grained out. This effect often causes the CG potential to depend strongly on the overall system density, composition, or other properties, which limits its transferability to states other than the one at which it was parameterized. Here, we propose to incorporate multibody effects into CG potentials through additional nonbonded terms, beyond pair interactions, that depend in a mean-field manner on local densities of different atomic species. This approach is analogous to embedded atom and bond-order models that seek to capture multibody electronic effects in metallic systems. We show that the relative entropy coarse-graining framework offers a systematic route to parameterizing such local density potentials. We then characterize this approach in the development of implicit solvation strategies for interactions between model hydrophobes in an aqueous environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1998

A Study of Photon-Dominated Regions in Reflection Nebulae

The goals of this research were to determine the physical conditions of the Photon-Dominated Regions (PDRS) surrounding the cooler stars (B0-A0) of several reflection nebulae and to test theoretical "low-density" PDR models. In contrast to the substantial investigation on "high-density" PDRS, " low-density" PDRs have been adequately modelled, but have not been adequately tested. At the start of this project, we had reduced Kuiper Airborne Observatory spectra of several far-infrared (FIR) fine structure lines on eight reflection nebulae that cover a range in cooler stellar spectral types (A0-B0). We analyzed these data in the context of "los-density" PDR models asking the question: Do the physical conditions in these reflection nebulae change with stellar spectral type as predicted?

Meixner, Margaret↗