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At least 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Diffusion and migration in polymer electrolytes

Mixtures of neutral polymers and lithium salts have the potential to serve as electrolytes in next-generation rechargeable Li-ion batteries. The purpose of this review is to expose the delicate interplay between polymer-salt interactions at the segmental level and macroscopic ion transport at the battery level. Since complete characterization of this interplay has only been completed in one system: mixtures of poly(ethylene oxide) and lithium bis(trifluoromethanesulfonyl)imide (PEO/LiTFSI), we focus on data obtained from this system. We begin with a discussion of the activity coefficient, followed by a discussion of six different diffusion coefficients: the Rouse motion of polymer segments is quantified by D seg , the self-diffusion of cations and anions is quantified by D self,+ and D self,- , and the build-up of concentration gradients in electrolytes under an applied potential is quantified by Stefan-Maxwell diffusion coefficients, D 0+ , D 0- , and D +- . The Stefan-Maxwell diffusion coefficients can be used to predict the velocities of the ions at very early times after an electric field is applied across the electrolyte. The surprising result is that D 0- is negative in certain concentration windows. A consequence of this finding is that at these concentrations, both cations and anions are predicted to migrate toward the positive electrode at early times. We describe the controversies that surround this result. Knowledge of the Stefan-Maxwell diffusion coefficients enable prediction of the limiting current. We argue that the limiting current is the most important characteristic of an electrolyte. Excellent agreement between theoretical and experimental limiting current is seen in PEO/LiTFSI mixtures. What sequence of monomers that, when polymerized, will lead to the highest limiting current remains an important unanswered question. It is our hope that the approach presented in this review will guide the development of such polymers.

25 ENERGY STORAGE↗
NASA NTRSDate not supplied

The PACE-MAPP Algorithm: Coupled Ocean/Aerosol Products

The PACE-MAPP algorithm, under development for combined SPEXone, HARP2 and OCI observations from NASA’s future Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission, directly inverts the coupled atmosphere-ocean system to retrieve aerosol optical and microphysical properties and ocean optical properties simultaneously. PACE-MAPP thus retrieves the spectrally-resolved inherent optical properties of the Earth’s waters: the spectral particulate scattering coefficient, b_p (λ), the spectral absorption coefficient for particulates and color-dissolved matter, a_tot (λ), and the spectral particulate backscatter efficiency, b ̃_"bp". From these three spectrally-resolved components, we can derive the spectral particulate hemispherical backscattering coefficient b_bp (λ) and the spectral diffuse attenuation coefficient K_"d" (λ). Direct comparisons of b_"bp" (532) and K_"d" (532) are made to collocated High-Spectral Resolution Lidar (HSRL) in-water measurements. The PACE-MAPP algorithm was tested using PACE-analog datasets collected by Research Scanning Polarimeter (RSP) observations during the NASA NAAMES (The North Atlantic Aerosols and Marine Ecosystems Study) and SABOR (Ship-Aircraft Bio-Optical Research) airborne campaigns, both of which also include ship-based in situ measurements.

Snorre Alfred Moen Stamnes↗
NASA NTRS1983

Coastal Zone Color Scanner data of rich coastal waters

Comparisons of chlorophyll concentrations and diffuse attenuation coefficients measured from ships off the central California coast were made with satellite derived estimates of the same parameters using data from the Coastal Zone Color Scanner. Very high chlorophyll concentrations were encountered in Monterey Bay. Although lower chlorophyll values acquired off Pt. Sur agreed satisfactorily with the satellite data, the high chlorophyll values departed markedly from agreement. Two possible causes for the disagreement are suggested. Comparison of diffuse attenuation coefficients from the same data sets showed closer agreement.

Wrigley, R. C.↗
NASA NTRS2022

Spectrally Simplified Approach for Leveraging Legacy Geostationary Oceanic Observations

The use of multispectral geostationary satellites to study aquatic ecosystems improves the temporal frequency of observations and mitigates cloud obstruction, but no operational capability presently exists for the coastal and inland waters of the United States. The Advanced Baseline Imager (ABI) on the current iteration of the Geostationary Operational Environmental Satellites, termed the R Series (GOES-R), however, provides sub-hourly imagery and the opportunity to overcome this deficit and to leverage a large repository of existing GOES-R aquatic observations. The fulfillment of this opportunity is assessed herein using a spectrally simplified, two-channel aquatic algorithm consistent with ABI wave bands to estimate the diffuse attenuation coefficient for photosynthetically available radiation, K(d)(PAR). First, an in situ ABI dataset was synthesized using a globally representative dataset of above- and in-water radiometric data products. Values of K(d)(PAR) were estimated by fitting the ratio of the shortest and longest visible wave bands from the in situ ABI dataset to coincident, in situ K(d)(PAR) data products. The algorithm was evaluated based on an iterative cross-validation analysis in which 80% of the dataset was randomly partitioned for fitting and the remaining 20% was used for validation. The iteration producing the median coefficient of determination (R2) value (0.88) resulted in a root mean square difference of 0.319 m−1, or 8.5% of the range in the validation dataset. Second, coincident mid-day images of central and southern California from ABI and from the Moderate Resolution Imaging Spectroradiometer (MODIS) were compared using Google Earth Engine (GEE). GEE default ABI reflectance values were adjusted based on a near infrared signal. Matchups between the ABI and MODIS imagery indicated similar spatial variability (R2 = 0.60) between ABI adjusted blue-to-red reflectance ratio values and MODIS default diffuse attenuation coefficient for spectral downward irradiance at 490 nm, K(d)(490), values. This work demonstrates that if an operational capability to provide- ABI aquatic data products was realized, the spectral configuration of ABI would potentially support a sub-hourly, visible aquatic data product that is applicable to water-mass tracing and physical oceanography research.

Advanced Baseline Imager↗
NASA NTRS1999

Global Mapping of Underwater UV Irradiances and DNA-Weighted Exposures using TOMS and SeaWiFS Data Products

The global stratospheric ozone-layer depletion results In an increase in biologically harmful ultraviolet (UV) radiation reaching the surface and penetrating to ecologically significant depths in natural waters. Such an increase can be estimated on a global scale by combining satellite estimates of UV irradiance at the ocean surface from the Total Ozone Mapping Spectrometer (TOMS) satellite instrument with the SeaWIFS satellite ocean-color measurements in the visible spectral region. In this paper we propose a model of seawater optical properties in the UV spectral region based on the Case I water model in the visible range. The inputs to the model are standard monthly SeaWiFS products: chlorophyll concentration and the diffuse attenuation coefficient at 490nm. Penetration of solar UV radiation to different depths in open ocean waters is calculated using the RT (radiative transfer) quasi-single scattering approximation (QSSA). The accuracy of the QSSA approximation in the water is tested using more accurate codes. The sensitivity study of the underwater UV irradiance to atmospheric and oceanic optical properties have shown that the main environmental parameters controlling the absolute levels of the UVB (280-320nm) and DNA-weighted irradiance underwater are: solar-zenith angle, cloud transmittance, water optical properties, and total ozone. Weekly maps of underwater UV irradiance and DNA-weighted exposure are calculated using monthly-mean SeaWiFS chlorophyll and diffuse attenuation coefficient products, daily SeaWiFS cloud fraction data, and the TOMS-derived surface UV irradiance daily maps. The final products include global maps of weekly-average UVB irradiance and DNA-weighted daily exposures at 3m and 10m, and depths where the UVB irradiance and DNA-weighted dose rate at local noon are equal to 10% of their surface values.

Vasilkov, Alexander↗
DOE OSTI2024

Multiscale, mechanistic modeling of irradiation-enhanced silver diffusion in TRISO particles

Tristructural isotropic (TRISO) particles are under consideration for use in several proposed advanced nuclear reactor concepts. The silicon carbide (SiC) layer in TRISO acts as a barrier to prevent the release of the fission products. However, despite remarkable retention, silver (Ag) release has been observed from intact particles, which requires investigation since the Ag isotope ( 110m Ag) has a long half-life. Previous work focused on developing a multiscale, mechanistic model for Ag diffusion accounting for temperature and microstructure effect and has been successfully validated. In this work, we expand the previous model to account for irradiation-enhanced Ag diffusivity in SiC and improve its accuracy over a wider grain size and temperature ranges relevant for advanced reactor conditions. A temperature, grain size, and flux dependent diffusivity is therefore derived using the mesoscale code MARMOT and implemented in the fuel performance code BISON. The irradiation-enhanced Ag diffusivity in SiC is compared against experimental data and validated using BISON against Ag release measurements from the Advanced Gas Reactor Fuel Development and Qualification Program (AGR-1 and AGR-2). Herein, we quantify the impact of SiC grain size, irradiation, and temperature on Ag release. In agreement with previous studies, we find accounting for SiC grain size improves agreement between BISON predictions and experimental observations for most cases. In conclusion, we also find that accounting for irradiation improves agreement for cases where Ag release was underestimated, but the impact was less significant than accounting for microstructure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2015

A Semianalytical Ocean Color Inversion Algorithm with Explicit Water Column Depth and Substrate Reflectance Parameterization

A semianalytical ocean color inversion algorithm was developed for improving retrievals of inherent optical properties (IOPs) in optically shallow waters. In clear, geometrically shallow waters, light reflected off the seafloor can contribute to the water-leaving radiance signal. This can have a confounding effect on ocean color algorithms developed for optically deep waters, leading to an overestimation of IOPs. The algorithm described here, the Shallow Water Inversion Model (SWIM), uses pre-existing knowledge of bathymetry and benthic substrate brightness to account for optically shallow effects. SWIM was incorporated into the NASA Ocean Biology Processing Group's L2GEN code and tested in waters of the Great Barrier Reef, Australia, using the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua time series (2002-2013). SWIM-derived values of the total non-water absorption coefficient at 443 nm, at(443), the particulate backscattering coefficient at 443 nm, bbp(443), and the diffuse attenuation coefficient at 488 nm, Kd(488), were compared with values derived using the Generalized Inherent Optical Properties algorithm (GIOP) and the Quasi-Analytical Algorithm (QAA). The results indicated that in clear, optically shallow waters SWIM-derived values of at(443), bbp(443), and Kd(443) were realistically lower than values derived using GIOP and QAA, in agreement with radiative transfer modeling. This signified that the benthic reflectance correction was performing as expected. However, in more optically complex waters, SWIM had difficulty converging to a solution, a likely consequence of internal IOP parameterizations. Whilst a comprehensive study of the SWIM algorithm's behavior was conducted, further work is needed to validate the algorithm using in situ data.

Great Barrier Reef↗
DOE OSTI2020

Where did the tumor start? An inverse solver with sparse localization for tumor growth models

In this work, we present a numerical scheme for solving an inverse problem for parameter estimation in tumor growth models for glioblastomas, a form of aggressive primary brain tumor. The growth model is a reaction–diffusion partial differential equation (PDE) for the tumor concentration. We use a PDE-constrained optimization formulation for the inverse problem. The unknown parameters are the reaction coefficient (proliferation), the diffusion coefficient (infiltration), and the initial condition field for the tumor PDE. Segmentation of magnetic resonance imaging (MRI) scans drive the inverse problem where segmented tumor regions serve as partial observations of the tumor concentration. Like most cases in clinical practice, we use data from a single time snapshot. Moreover, the precise time relative to the initiation of the tumor is unknown, which poses an additional difficulty for inversion. We perform a frozen-coefficient spectral analysis and show that the inverse problem is severely ill-posed. We introduce a biophysically motivated regularization on the structure and magnitude of the tumor initial condition. In particular, we assume that the tumor starts at a few locations (enforced with a sparsity constraint on the initial condition of the tumor) and that the initial condition magnitude in the maximum norm is equal to one. We solve the resulting optimization problem using an inexact quasi-Newton method combined with a compressive sampling algorithm for the sparsity constraint. Our implementation uses PETSc and AccFFT libraries. We conduct numerical experiments on synthetic and clinical images to highlight the improved performance of our solver over a previously existing solver that uses standard two-norm regularization for the calibration parameters. The existing solver is unable to localize the initial condition. Our new solver can localize the initial condition and recover infiltration and proliferation. In clinical datasets (for which the ground truth is unknown), our solver results in qualitatively different solutions compared to the two-norm regularized solver.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1971

Damage and recovery characteristics of lithium-containing solar cells.

Damage and recovery characteristics were measured on lithium-containing solar cells irradiated by 1-MeV electrons. Empirical expressions for cell recovery time, diffusion-length damage coefficient immediately after irradiation, and diffusion-length damage coefficient after recovery were derived using results of short-circuit current, diffusion-length, and reverse-bias capacitance measurements. The damage coefficients were expressed in terms of a single lithium density parameter, the lithium gradient. A fluence dependence was also established, this dependence being the same for both the immediate-post-irradiation and post-recovery cases. Cell recovery rates were found to increase linearly with lithium gradient.

Faith, T. J.↗
DOE OSTI2023

Molecular Dynamics Simulation Study of the Protonation State Dependence of Glutamic Acid Transport through a Cyclic Peptide Nanotube

The effect of the protonation state of glutamic acid on its translocation through cyclic peptide nanotubes (CPNs) was assessed by using molecular dynamics (MD) simulations. Anionic (GLU–), neutral zwitterionic (GLU0), and cationic (GLU+) forms of glutamic acid were selected as three different protonation states for an analysis of energetics and diffusivity for acid transport across a cyclic decapeptide nanotube. Based on the solubility-diffusion model, permeability coefficients for the three protonation states of the acid were calculated and compared with experimental results for CPN-mediated glutamate transport through CPNs. Potential of mean force (PMF) calculations reveal that, due to the cation-selective nature of the lumen of CPNs, GLU–, so-called glutamate, shows significantly high free energy barriers, while GLU+ displays deep energy wells and GLU0 has mild free energy barriers and wells inside the CPN. The considerable energy barriers for GLU– inside CPNs are mainly attributed to unfavorable interactions with DMPC bilayers and CPNs and are reduced by favorable interactions with channel water molecules through attractive electrostatic interactions and hydrogen bonding. Unlike the distinct PMF curves, position-dependent diffusion coefficient profiles exhibit comparable frictional behaviors regardless of the charge status of three protonation states due to similar confined environments imposed by the lumen of the CPN. The calculated permeability coefficients for the three protonation states clearly demonstrate that glutamic acid has a strong protonation state dependence for its transport through CPNs, as determined by the energetics rather than the diffusivity of the protonation state. In addition, the permeability coefficients also imply that GLU– is unlikely to pass through a CPN due to the high energy barriers inside the CPN, which is in disagreement with experimental measurements, where a considerable amount of glutamate permeating through the CPN was detected. To resolve the discrepancy between this work and the experimental observations, several possibilities are proposed, including a large concentration gradient of glutamate between the inside and outside of lipid vesicles and bilayers in the experiments, the glutamate activity difference between our MD simulations and experiments, an overestimation of energy barriers due to the artifacts imposed in MD simulations, and/or finally a transformation of the protonation state from GLU– to GLU0 to reduce the energy barriers. Altogether, our study demonstrates that the protonation state of glutamic acid has a strong effect on the transport of the acid and suggests a possible protonation state change for glutamate permeating through CPNs.

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

Proton diffusion and hydrogen/deuterium exchange in amorphous solid water at temperatures from 114 to 134 K

The reaction coefficient for hydrogen/deuterium (H/D) exchange and the diffusion of hydrated excess protons within amorphous solid water (ASW) are characterized as a function of temperature. For these experiments, water films are deposited on a Pt(111) substrate at 108 K, and reactions with pre-adsorbed hydrogen atoms produce hydrated protons. Upon heating, protons diffuse within the water, and H/D exchange occurs when they encounter D2O probe molecules deposited in the films. The time-dependent concentration of D2O is monitored with infrared spectroscopy, and it indicates the protons diffusion from the substrate and establish an equilibrium distribution prior to significant H/D exchange for temperatures 114 K ≤T≤ 134 K. By controlling the distance between the D2O molecules and the substrate, we probe the distribution of protons within the film. It decays as x−2 for the examined range of x (12–52 nm) due to the electric field that develops between the diffusing protons and their image charges in the metal substrate. This agrees with the theoretical distance scaling for the equilibrated proton concentration in a dielectric near a metal boundary. From the proton concentration and the measured D2O decay rate, a lower bound for the proton diffusion coefficient ranging from 10−20 m2/s at 114 K to 10−18 m2/s at 134 K is estimated. The diffusion coefficient has an activation energy of 0.40 eV, which is comparable to energies reported for molecular translations and rotations of H2O, suggesting they may play a critical role in the proton diffusion mechanism within ASW.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Statistical distributions for transient transport

Here, this paper introduces the use of statistical distributions based on transport differential equations for clear distinction of transport modes within transient kinetic experiments. More specifically, novel techniques are developed for the transient data obtained through the Temporal Analysis of Products (TAP) reactor and are applicable to experiments where pulse response into a gas flow is used. The methodology allows distinguishing between two domains of diffusion transport in heterogeneous catalytic systems, i.e., Knudsen and non-Knudsen diffusion, using statistical fingerprints, and finding the transition domain. Two distribution parameters were obtained that directly result in coefficients that correspond to the concentration and the rate of transport. Using a linear relationship between the rate and concentration coefficients, Knudsen diffusion is revealed when the rate of transport is constant and non-Knudsen diffusion is confirmed when the rate of transport coefficient is a function of the concentration coefficient. As a result, accurate transport information can be extracted from experimental data even in the presence of comprising instrument drift or noise particularly when analyzing higher pressure pulse responses with complex transport. This enables more direct investigation of experiments influenced by gas-phase reactions.

TAP reactor↗
NASA NTRS2012

System to Measure Thermal Conductivity and Seebeck Coefficient for Thermoelectrics

The Seebeck coefficient, when combined with thermal and electrical conductivity, is an essential property measurement for evaluating the potential performance of novel thermoelectric materials. However, there is some question as to which measurement technique(s) provides the most accurate determination of the Seebeck coefficient at elevated temperatures. This has led to the implementation of nonstandardized practices that have further complicated the confirmation of reported high ZT materials. The major objective of the procedure described is for the simultaneous measurement of the Seebeck coefficient and thermal diffusivity within a given temperature range. These thermoelectric measurements must be precise, accurate, and reproducible to ensure meaningful interlaboratory comparison of data. The custom-built thermal characterization system described in this NASA-TM is specifically designed to measure the inplane thermal diffusivity, and the Seebeck coefficient for materials in the ranging from 73 K through 373 K.

Kim, Hyun-Jung↗
NASA NTRS2021

A Three-Step Semi Analytical Algorithm (3SAA) for Estimating Inherent Optical Properties Over Oceanic, Coastal, and Inland Waters From Remote Sensing Reflectance

We present a three-step inverse model (3SAA) for estimating the inherent optical properties (IOPs) of surface waters from the remote sensing reflectance spectra, Rrs(). The derived IOPs include the total (a()), phytoplankton (aphy()), and colored detrital matter (acdm()), absorption coefficients, and the total (bb()) and particulate (bbp()) backscattering coefficients. The first step uses an improved neural network approach to estimate the diffuse attenuation coefficient of downwelling irradiance from Rrs. a() and bbp() are then estimated using the LS2 model (Loisel et al., 2018), which does not require spectral assumptions on IOPs and hence can assess a() and bb() at any wavelength at which Rrs() is measured. Then, an inverse optimization algorithm is combined with an optical water class (OWC) approach to assess aphy() and acdm() from anw().The proposed model is evaluated using an in situ dataset collected in open oceanic, coastal, and inland waters. Comparisons with other standard semi-analytical algorithms (QAA and GSM), as well as match-up exercises, have also been performed. The applicability of the algorithm on OLCI observations was assessed through the analysis of global IOPs spatial patterns derived from 3SAA and GSM. The good performance of 3SAA is manifested by median absolute percentage differences (MAPD) of 13%, 23%, 34% and 34% for bbp(443), anw(443), aphy(443) and acdm(443), respectively for oceanic waters. Due to the absence of spectral constraints on IOPs in the inversion of total IOPs, and the adoption of an OWC-based approach, the performance of 3SAA is only slightly degraded in bio-optical complex inland waters.

ocean color↗
NASA NTRS2014

Algorithm Development and Validation of CDOM Properties for Estuarine and Continental Shelf Waters Along the Northeastern U.S. Coast

An extensive set of field measurements have been collected throughout the continental margin of the northeastern U.S. from 2004 to 2011 to develop and validate ocean color satellite algorithms for the retrieval of the absorption coefficient of chromophoric dissolved organic matter (aCDOM) and CDOM spectral slopes for the 275:295 nm and 300:600 nm spectral range (S275:295 and S300:600). Remote sensing reflectance (Rrs) measurements computed from in-water radiometry profiles along with aCDOM() data are applied to develop several types of algorithms for the SeaWiFS and MODIS-Aqua ocean color satellite sensors, which involve least squares linear regression of aCDOM() with (1) Rrs band ratios, (2) quasi-analytical algorithm-based (QAA based) products of total absorption coefficients, (3) multiple Rrs bands within a multiple linear regression (MLR) analysis, and (4) diffuse attenuation coefficient (Kd). The relative error (mean absolute percent difference; MAPD) for the MLR retrievals of aCDOM(275), aCDOM(355), aCDOM(380), aCDOM(412) and aCDOM(443) for our study region range from 20.4-23.9 for MODIS-Aqua and 27.3-30 for SeaWiFS. Because of the narrower range of CDOM spectral slope values, the MAPD for the MLR S275:295 and QAA-based S300:600 algorithms are much lower ranging from 9.9 and 8.3 for SeaWiFS, respectively, and 8.7 and 6.3 for MODIS, respectively. Seasonal and spatial MODIS-Aqua and SeaWiFS distributions of aCDOM, S275:295 and S300:600 processed with these algorithms are consistent with field measurements and the processes that impact CDOM levels along the continental shelf of the northeastern U.S. Several satellite data processing factors correlate with higher uncertainty in satellite retrievals of aCDOM, S275:295 and S300:600 within the coastal ocean, including solar zenith angle, sensor viewing angle, and atmospheric products applied for atmospheric corrections. Algorithms that include ultraviolet Rrs bands provide a better fit to field measurements than algorithms without the ultraviolet Rrs bands. This suggests that satellite sensors with ultraviolet capability could provide better retrievals of CDOM. Because of the strong correlations between CDOM parameters and DOM constituents in the coastal ocean, satellite observations of CDOM parameters can be applied to study the distributions, sources and sinks of DOM, which are relevant for understanding the carbon cycle, modeling the Earth system, and to discern how the Earth is changing.

CDOM Properties↗
NASA NTRS1981

Albedo and flux extinction coefficient of impure snow for diffuse shortwave radiation

Impurities enter a snowpack as a result of fallout of scavenging by falling snow crystals. Albedo and flux extinction coefficient of soot contaminated snowcovers were studied using a two stream approximation of the radiative transfer equation. The effect of soot was calculated by two methods: independent scattering by ice grains and impurities and average refractive index for ice grains. Both methods predict a qualitatively similar effect of soot; the albedo is decreased and the extinction coefficient is increased compared to that for pure snow in the visible region; the infrared properties are largely unaffected. Quantitatively, however, the effect of soot is more pronounced in the average refractive index method. Soot contamination provides a qualitative explanation for several snow observations.

Choudhury, B. J.↗