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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Electrochemical CO2 Reduction over Metal-/Nitrogen-Doped Graphene Single-Atom Catalysts Modeled Using the Grand-Canonical Density Functional Theory

Renewably driven, electrochemical conversion of carbon dioxide into value-added products is expected to be a critical tool in global decarbonization. However, theoretical studies based on the computational hydrogen electrode largely ignore the nonlinear effects of the applied potential on the calculated results, leading to inaccurate predictions of catalytic behavior or mechanistic pathways. Here, we use grand canonical density functional theory (GC-DFT) to model electrochemical CO2 reduction (CO2R) over metal- and nitrogen-doped graphene catalysts (MNCs) and explicitly include the effects of the applied potential. We used GC-DFT to compute the CO2 to CO reaction intermediate energies at -0.3, -0.7, and -1.2 VSHE catalyzed by MNCs each doped with 1 of the 10 3d block metals coordinated by four pyridinic nitrogen atoms. Our results predict that Sc-, Ti-, Co-, Cu-, and Zn-N4Cs effectively catalyze CO2R at moderate to large reducing potentials (-0.7 to -1.2 VSHE). ZnN4C is a particularly promising electrocatalyst for CO2R to CO both at low and moderate applied potentials based on our thermodynamic analysis. Our findings also explain the observed pH independence of CO production over FeN4C and predict that the rate-determining step of CO2R over FeN4C is not *CO2- formation but rather *CO desorption. Additionally, the GC-DFT-computed density of states analysis illustrates how the electronic states of MNCs and adsorbates change non-uniformly with applied potential, resulting in a significantly increased *CO2- stability relative to other intermediates and demonstrating that the formation of the adsorbed *CO2- anion is critical to CO2R activation. This work demonstrates how GC-DFT paves the way for physically realistic and accurate theoretical simulations of reacting electrochemical systems.

CO2 reduction↗
NASA NTRS1993

Conventional modeling of the multilayer perceptron using polynomial basis functions

A technique for modeling the multilayer perceptron (MLP) neural network, in which input and hidden units are represented by polynomial basis functions (PBFs), is presented. The MLP output is expressed as a linear combination of the PBFs and can therefore be expressed as a polynomial function of its inputs. Thus, the MLP is isomorphic to conventional polynomial discriminant classifiers or Volterra filters. The modeling technique was successfully applied to several trained MLP networks.

Chen, Mu-Song↗
DOE OSTI2013

Local structures of Sr{sub 2}FeMnO{sub 5+y} (y=0, 0.5) and Sr{sub 2}Fe{sub 1.5}Cr{sub 0.5}O{sub 5} from reverse Monte Carlo modeling of pair distribution function data and implications for magnetic order

The local structures of the oxygen deficient perovskites Sr{sub 2}FeMnO{sub 5}, Sr{sub 2}FeMnO{sub 5.5}, and Sr{sub 2}Fe{sub 1.5}Cr{sub 0.5}O{sub 5} have been analyzed using neutron pair distribution function data. The results show that locally all three structures are more complex than implied by their average cubic structures and that the distributions of oxygen vacancies are not completely random on a local level. For both Sr{sub 2}FeMnO{sub 5+y} compounds it is found that there is no short range ordering of the Fe and Mn cations. For Sr{sub 2}Fe{sub 1.5}Cr{sub 0.5}O{sub 5} there is evidence to suggest that the Fe/Cr distribution is not completely random and is locally ordered such that there are fewer Fe--Fe nearest neighbor pairs than in a random distribution. Reverse Monte Carlo modeling of the pair distribution function data has provided the Fe--O, Mn--O, and Cr--O bond length distributions and information on the coordination numbers of the Fe, Mn, and Cr cations. In Sr{sub 2}FeMnO{sub 5} it is found that the Fe{sup 3+} cations are most often in 4-fold coordination but there is also a large amount of Fe{sup 3+} in 5-fold coordination and a small amount in 6-fold coordination. The Mn{sup 3+} is split between 5-fold and 6-fold coordination. The Mn--O bond length distributions indicate that the Mn{sup 3+}O{sub 6} octahedra and Mn{sup 3+}O{sub 5} square pyramids are locally Jahn-Teller distorted. In Sr{sub 2}FeMnO{sub 5.5} the Fe{sup 3+} is almost entirely 5 coordinate while the Mn{sup 4+} is almost entirely 6 coordinate. The Cr{sup 3+} in Sr{sub 2}Fe{sub 1.5}Cr{sub 0.5}O{sub 5} is almost entirely 6-fold coordinated, giving the Fe{sup 3+} an average coordination number of 4.67. In Sr{sub 2}FeMnO{sub 5} and Sr{sub 2}Fe{sub 1.5}Cr{sub 0.5}O{sub 5} the Fe{sup 3+} and Sr{sup 2+} cations undergo local displacements which are driven by the oxygen vacancies, while the Mn{sup 3+} and Cr{sup 3+} cations remain near their positions in the average structures. In Sr{sub 2}FeMnO{sub 5.5} these cations are not significantly displaced. The local coordination geometries are used to explain previously observed but yet poorly understood magnetic properties of these materials. - Graphical abstract: The actual bond angle distributions in the cubic perovskite Sr{sub 2}FeMnO{sub 5} obtained from reverse Monte Carlo modeling of the local structure using neutron pair distribution function data. Highlights: Black-Right-Pointing-Pointer No long range ordering of oxygen vacancies, but short range order is present. Black-Right-Pointing-Pointer No short range Fe/Mn order but short range Fe/Cr order is present. Black-Right-Pointing-Pointer Fe tends to have lower coordination numbers while Mn and Cr have higher ones. Black-Right-Pointing-Pointer Local bond distances and bond angles have been determined. Black-Right-Pointing-Pointer Local structures can help explain long range magnetic ordering behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The Effects of Atmospheric Models on the Estimation of Infrasonic Source Functions at the Source Physics Experiment

We invert infrasound signals for an equivalent seismoacoustic source function using different atmospheric models to produce the necessary Green’s functions. The infrasound signals were produced by a series of underground chemical explosions as part of the Source Physics Experiment (SPE). In a previous study, we inverted the infrasound data using so-called predictive atmospheric models, which were based on historic, regional-scaled, publicly available weather observations interpolated onto a 3D grid. For the work presented here, we invert the same infrasound data, but using atmospheric models based on weather data collected in a time window that includes the approximate time of the explosion experiments, which we term postdictive models. We build two versions of the postdictive models for each SPE event: one that is based solely on the regional scaled observations, and one that is based on both regional scaled observations combined with on-site observations obtained by a weather sonde released at the time of the SPE. We then invert the observed data set three times, once for each atmospheric model type. We find that the estimated seismoacoustic source functions are relatively similar in waveform shape regardless of which atmospheric model that we used to construct the Green’s functions. However, we find that the amplitude of the estimated source functions is systematically dependent on the atmospheric model type: using the predictive atmospheric models to invert the data generally yields estimated source functions that are larger in amplitude than those estimated using the postdictive models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Functional characterization and regulatory modeling of lignocellulose deconstruction in the saprophytic bacterium Cellvibrio japonicus (Final Technical Report)

The goal of this project was to establish a fundamental systems-level model of lignocellulose deconstruction by saprophytic soil bacteria while simultaneously identifying and characterizing novel enzymes that can be used for applied bioenergy technologies. This project was significant because it elevated our mechanistic and regulatory understanding of bacterial plant biomass degradation and led to technologies to enable bottlenecks in biofuel production R&D. Furthermore, the completed work was novel because it integrated in vivo, in vitro, and in silico approaches with bioenergy-relevant substrates. We identified the required enzymes for lignocellulose degradation and mechanisms of regulation through a combination of transcriptomic profiling (RNAseq), enzymatic analysis, the functional characterization of mutants, and modeling of the regulatory networks used to detect and degrade lignocellulose. This project employed the lignocellulose-degrading bacterium Cellvibrio japonicus to dissect the functional properties and underlying regulatory networks saprophytic bacteria use to depolymerize and utilize lignocellulose. There were four Objectives to this project, the specific metrics of which are summarized in this report.

09 BIOMASS FUELS↗
DOE OSTI2015

Adsorption of a metalorganic complex at a metal surface: A density functional theory study vs. model description

A modification of the electronic and magnetic structure of a metalorganic complex by chemisorption at a metallic surface is addressed. The density functional theory (DFT) is applied to investigate a simplified form of a copper-dioxolene complex in a free state and connected to Au(111) surface with alkanethiol linkers. A systematic study of the dependence of the system electronic structure on the linker length is performed. It is found that the electronic structure of the complex is well preserved during the adsorption process. The magnetic moment of the Cu-dioxolene functional group is shown to be strictly correlated with the amount of the charge residing at the complex. On the basis of the DFT results, a model Hamiltonian of the adsorbed metalorganic system is proposed. The model is an extension of the Sandorfy's model of the alkanes and includes explicitly Coulomb interaction between electrons both within the alkane's backbone and the end group. We show that the latter feature is necessary to understand the evolution of the system's properties with the length of the linkers. The advantage of this approach is that it not only reproduces the main results of our DFT analysis but also provides a simple common basis to analyse a wide class of metal complexes bound to metal surfaces with alkanethiol linkers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Screened Range-Separated Hybrid Functional with Polarizable Continuum Model Overcomes Challenges in Describing Triplet Excitations in the Condensed Phase Using TDDFT

Long range-corrected (LRC) or range-separated hybrid (RSH) functionals where the long-range (LR) limit of electronic interactions is set to the exact exchange have been shown to correct the tendency of traditional density functional theory (DFT) to underestimate the frontier orbital gap. Consequently, the use of such functionals in calculating electronic excited states using linear response based time-dependent DFT (TDDFT) has been successful in correcting the tendency for underestimating the energies of charge transfer states by DFT-based calculations. More recently formulations of functionals that attenuate the LR limit to address condensed-phase effects to polarize the electronic density have been reported. In particular screened RSH (SRSH) combined with polarizable continuum model (PCM) was benchmarked successfully in reproducing the fundamental gap and charge transfer state energies of molecular systems in the condensed phase. Here we use SRSH-PCM to address triplet excited states, and show its success in obtaining correspondence of the low-lying triplet states to the singlet–triplet gap in a similar way that the fundamental orbital gap corresponds to electron removal and addition energies. Importantly, the accuracy of the SRSH-PCM in calculating triplet excitations stands on the polarization consistent framework in addressing the scalar dielectric constant and without affecting the optimal tuning by triplet energies. Finally, the prospect of even further improving the SRSH-PCM accuracy in calculating triplet states can be achieved by optimal tuning on the basis of the spin multiplicity gap.

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

Linear functional minimization for inverse modeling

In this paper, we present a novel inverse modeling strategy to estimate spatially distributed parameters of nonlinear models. The maximum a posteriori (MAP) estimators of these parameters are based on a likelihood functional, which contains spatially discrete measurements of the system parameters and spatiotemporally discrete measurements of the transient system states. The piecewise continuity prior for the parameters is expressed via Total Variation (TV) regularization. The MAP estimator is computed by minimizing a nonquadratic objective equipped with the TV operator. We apply this inversion algorithm to estimate hydraulic conductivity of a synthetic confined aquifer from measurements of conductivity and hydraulic head. The synthetic conductivity field is composed of a low-conductivity heterogeneous intrusion into a high-conductivity heterogeneous medium. Our algorithm accurately reconstructs the location, orientation, and extent of the intrusion from the steady-state data only. Finally, addition of transient measurements of hydraulic head improves the parameter estimation, accurately reconstructing the conductivity field in the vicinity of observation locations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Validation of sea ice models using an uncertainty-based distance metric for multiple model variables: NEW METRIC FOR SEA ICE MODEL VALIDATION

Here, we implement a variance-based distance metric (D n ) to objectively assess skill of sea ice models when multiple output variables or uncertainties in both model predictions and observations need to be considered. The metric compares observations and model data pairs on common spatial and temporal grids improving upon highly aggregated metrics (e.g., total sea ice extent or volume) by capturing the spatial character of model skill. The D n metric is a gamma-distributed statistic that is more general than the χ 2 statistic commonly used to assess model fit, which requires the assumption that the model is unbiased and can only incorporate observational error in the analysis. The D n statistic does not assume that the model is unbiased, and allows the incorporation of multiple observational data sets for the same variable and simultaneously for different variables, along with different types of variances that can characterize uncertainties in both observations and the model. This approach represents a step to establish a systematic framework for probabilistic validation of sea ice models. The methodology is also useful for model tuning by using the D n metric as a cost function and incorporating model parametric uncertainty as part of a scheme to optimize model functionality. We apply this approach to evaluate different configurations of the standalone Los Alamos sea ice model (CICE) encompassing the parametric uncertainty in the model, and to find new sets of model configurations that produce better agreement than previous configurations between model and observational estimates of sea ice concentration and thickness.

58 GEOSCIENCES↗
DOE OSTI2022

Implementation and evaluation of the unified stomatal optimization approach in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES)

Abstract. Stomata play a central role in regulating the exchange of carbon dioxide and water vapor between ecosystems and the atmosphere. Their function is represented in land surface models (LSMs) by conductance models. The Functionally Assembled Terrestrial Ecosystem Simulator (FATES) is a dynamic vegetation demography model that can simulate both detailed plant demographic and physiological dynamics. To evaluate the effect of stomatal conductance model formulation on forest water and carbon fluxes in FATES, we implemented an optimality-based stomatal conductance model – the Medlyn (MED) model – that simulates the relationship between photosynthesis (A) and stomatal conductance to water vapor (gsw) as an alternative to the FATES default Ball–Woodrow–Berry (BWB) model. To evaluate how the behavior of FATES is affected by stomatal model choice, we conducted a model sensitivity analysis to explore the response of gsw to climate forcing, including atmospheric CO2 concentration, air temperature, radiation, and vapor pressure deficit in the air (VPDa). We found that modeled gsw values varied greatly between the BWB and MED formulations due to the different default stomatal slope parameters (g1). After harmonizing g1 and holding the stomatal intercept parameter (g0) constant for both model formulations, we found that the divergence in modeled gsw was limited to conditions when the VPDa exceeded 1.5 kPa. We then evaluated model simulation results against measurements from a wet evergreen forest in Panama. Results showed that both the MED and BWB model formulations were able to capture the magnitude and diurnal changes of measured gsw and A but underestimated both by about 30 % when the soil was predicted to be very dry. Comparison of modeled soil water content from FATES to a reanalysis product showed that FATES captured soil drying well, but translation of drying soil to modeled physiology reduced the models' ability to match observations. Our study suggests that the parameterization of stomatal conductance models and current model response to drought are the critical areas for improving model simulation of CO2 and water fluxes in tropical forests.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

A subgrid-scale model based on the second-order velocity structure function

A series of tests were performed to help extend the use of a subgrid-scale model to compressible and wall-bounded flows. A priori tests were done in the case of the incompressible turbulent channel flow. They showed that a 1-D formulation of the structure-function model is more appropriate, leading to a satisfactory behavior of the model at the walls without requiring any damping function. This model is consistent with the original formulation of Metais & Lesieur (1990). In large-eddy simulations of compressible isotropic turbulence, both models performed well up to an initial rms Mach number of 0.6.

Comte, P.↗
DOE OSTI2026

Radiative strength functions from the energy-localized Brink-Axel hypothesis

Radiative strength functions (RSFs) model the bulk electromagnetic response of highly excited nuclei and are critical inputs for statistical reaction codes. In this paper, we present a definition of the RSF that is consistent with Hauser-Feshbach reaction codes and that can be efficiently computed with the shell model using the Lanczos strength-function (LSF) method. Here, we introduce a variant of the shell-model LSF method that exploits the energy-localized Brink-Axel hypothesis, which makes it possible to compute both electric and magnetic RSFs across all energies relevant to capture reactions. We verify agreement with the conventional definition of RSFs with benchmark calculations of 24 Mg and then present novel results for 56 Fe. For 56 Fe we find that (i) the 𝑀⁢1 RSF shape evolves smoothly with excitation energy, consistent with the energy-localized Brink-Axel hypothesis; (ii) both 𝑀⁢1 and 𝐸⁢1 transitions contribute significantly to the radiative strength below the photoabsorption threshold; and (iii) within the sdpf model space, the strength below 3 MeV observed in Oslo-type experiments cannot be fully reproduced. These results pave the way for a coherent microscopic description of RSFs and further motivate the use of energy-dependent RSFs in modern reaction codes.

Physics - Nuclear physics and radiation physics↗