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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 235 records · Page 13

Quantifying the Entropy and Enthalpy of Insertion Materials for Battery Applications Via the Multi-Species, Multi-Reaction Model

The entropy coefficient of a battery cell is the property that governs the amount of reversible heat that is generated during operation. In this work, we propose an extension of the Multi-Species, Multi-Reaction (MSMR) model to capture the entropy coefficient of a large format lithium-ion battery cell. We utilize the hybridized time-frequency domain analysis (HTFDA) method using a multi-functional calorimeter to probe the entropy coefficient of a large format pouch type lithium-ion battery with a NMC 811 cathode and a graphite anode. The measured entropy coefficient profile of the battery cell is deconvoluted into an entropy coefficient for each active material, which is then estimated using an extension of the MSMR model. Finally, we extend the entropy of a material to individual entropy for each gallery as treated by the model.

Electrochemistry↗

Exploring Li-Ion Transport Properties of Li 3 TiCl 6 : A Machine Learning Molecular Dynamics Study

We performed large-scale molecular dynamics simulations based on a machine-learning force field (MLFF) to investigate the Li-ion transport mechanism in cation-disordered Li 3 TiCl 6 cathode at six different temperatures, ranging from 25°C to 100°C. In this work, deep neural network method and data generated by ab − initio molecular dynamics (AIMD) simulations were deployed to build a high-fidelity MLFF. Radial distribution functions, Li-ion mean square displacements (MSD), diffusion coefficients, ionic conductivity, activation energy, and crystallographic direction-dependent migration barriers were calculated and compared with corresponding AIMD and experimental data to benchmark the accuracy of the MLFF. From MSD analysis, we captured both the self and distinct parts of Li-ion dynamics. The latter reveals that the Li-ions are involved in anti-correlation motion that was rarely reported for solid-state materials. Similarly, the self and distinct parts of Li-ion dynamics were used to determine Haven’s ratio to describe the Li-ion transport mechanism in Li 3 TiCl 6 . Obtained trajectory from molecular dynamics infers that the Li-ion transportation is mainly through interstitial hopping which was confirmed by intra- and inter-layer Li-ion displacement with respect to simulation time. Ionic conductivity (1.06 mS/cm) and activation energy (0.29eV) calculated by our simulation are highly comparable with that of experimental values. Overall, the combination of machine-learning methods and AIMD simulations explains the intricate electrochemical properties of the Li 3 TiCl 6 cathode with remarkably reduced computational time. Thus, our work strongly suggests that the deep neural network-based MLFF could be a promising method for large-scale complex materials.

Selvaraj, Selva Chandrasekaran (ORCID:000000029023↗

Basal glycogenolysis in mouse skeletal muscle: in vitro model predicts in vivo fluxes

A previously published mammalian kinetic model of skeletal muscle glycogenolysis, consisting of literature in vitro parameters, was modified by substituting mouse specific Vmax values. The model demonstrates that glycogen breakdown to lactate is under ATPase control. Our criteria to test whether in vitro parameters could reproduce in vivo dynamics was the ability of the model to fit phosphocreatine (PCr) and inorganic phosphate (Pi) dynamic NMR data from ischemic basal mouse hindlimbs and predict biochemically-assayed lactate concentrations. Fitting was accomplished by optimizing four parameters--the ATPase rate coefficient, fraction of activated glycogen phosphorylase, and the equilibrium constants of creatine kinase and adenylate kinase (due to the absence of pH in the model). The optimized parameter values were physiologically reasonable, the resultant model fit the [PCr] and [Pi] timecourses well, and the model predicted the final measured lactate concentration. This result demonstrates that additional features of in vivo enzyme binding are not necessary for quantitative description of glycogenolytic dynamics.

Non-NASA Center↗

Incorporation of measured photosynthetic rate in a mathematical model for calculation of non-structural saccharide concentration

A simple mathematical model for calculating the concentration of mobile carbon skeletons in the shoot of soya bean plants [Glycine max (L.) Merrill cv. Ransom] was built to examine the suitability of measured net photosynthetic rates (PN) for calculation of saccharide flux into the plant. The results suggest that either measurement of instantaneous PN overestimated saccharide influx or respiration rates utilized in the model were underestimated. If neither of these is the case, end-product inhibition of photosynthesis or waste respiration through the alternative pathway should be included in modelling of CH2O influx or efflux; and even if either of these is the case, the model output at a low coefficient of leaf activity indicates that PN still may be controlled by either end-product inhibition or alternative respiration.

NASA Program CELSS↗

AE Geomagnetic Index Predictability for High Speed Solar Wind Streams: A Wavelet Decomposition Technique

High speed solar wind streams cause geomagnetic activity at Earth. In this study we have applied a wavelet interactive filtering and reconstruction technique on the solar wind magnetic field components and AE index series to allowed us to investigate the relationship between the two. The IMF Bz component was found as the most significant solar wind parameter responsible by the control of the AE activity. Assuming magnetic reconnection associated to southward directed Bz is the main mechanism transferring energy into the magnetosphere, we adjust parameters to forecast the AE index. The adjusted routine is able to forecast AE, based only on the Bz measured at the L1 Lagrangian point. This gives a prediction approximately 30-70 minutes in advance of the actual geomagnetic activity. The correlation coefficient between the observed AE data and the forecasted series reached values higher than 0.90. In some cases the forecast reproduced particularities observed in the signal very well.The high correlation values observed and the high efficacy of the forecasting can be taken as a confirmation that reconnection is the main physical mechanism responsible for the energy transfer during HILDCAAs. The study also shows that the IMF Bz component low frequencies are most important for AE prediction.

Space weather↗

Using Active Learning to Rapidly Develop Machine Learned Diffusion Coefficients of CO 2 Conversion Reagents in Metal–Organic Frameworks

Here, we used a combined molecular dynamics/active learning (AL) approach to create machine learning models that can predict the diffusion coefficient of epichlorohydrin and chloropropene carbonate, the reactant and product of a common CO 2 cycloaddition reaction, in metal–organic frameworks (MOFs). Nanoporous MOFs are effective catalysts for the cycloaddition of CO 2 to epoxides. The diffusion rates within nanoporous catalysts can control the rate of reaction as the reactants and products must diffuse to the active sites within the MOF and then out of the nanoporous material for reusability. However, the diffusion process is routinely ignored when searching for new materials in catalytic applications. Here we verified improvement during the AL process by consistently tracking metrics on the same groups of MOFs to ensure consistency. Metal identity was found to have little impact on diffusion rates, while structural features like pore limiting diameter act as a threshold where a minimum value is needed for high diffusion rates. We identified the MOFs with the highest epichlorohydrin and chloropropene carbonate diffusion coefficients which can be used for further studies of reaction energetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measurement of distribution coefficients on TODGA resin and development of a group separation for mixed activation and fission product samples

Batch equilibrium experiments were performed to determine the distribution coefficients for Sc, Ir, and Ta on N,N,N’,N’tetraoctyl-1,5-diglycolamide (TODGA) resin in various acid matrices. Distribution coefficients were determined in hydrochloric acid (Sc, Ir), nitric acid (Sc, Ta), and a mixture of nitric acid and 0.2M hydrofluoric acid (Sc, Ir, Ta). The distribution coefficients determined through these experiments were then utilized to create a group separation method for activation products, fission products, and environmental constituents.

Louie, Christina A.↗

Iron catalyst chemistry in modeling a high-pressure carbon monoxide nanotube reactor

The high-pressure carbon monoxide (HiPco) technique for producing single-wall carbon nanotubes (SWNTs) is analyzed with the use of a chemical reaction model coupled with flow properties calculated along streamlines, calculated by the FLUENT code for pure carbon monoxide. Cold iron pentacarbonyl, diluted in CO at about 30 atmospheres, is injected into a conical mixing zone, where hot CO is also introduced via three jets at 30 degrees with respect to the axis. Hot CO decomposes the Fe(CO)5 to release atomic Fe. Then iron nucleates and forms clusters that catalyze the formation of SWNTs by a disproportionation reaction (Boudouard) of CO on Fe-containing clusters. Alternative nucleation rates are estimated from the theory of hard sphere collision dynamics with an activation energy barrier. The rate coefficient for carbon nanotube growth is estimated from activation energies in the literature. The calculated growth was found be about an order of magnitude greater than measured, regardless of the nucleation rate. A study of cluster formation in an incubation zone prior to injection into the reactor shows that direct dimer formation from Fe atoms is not as important as formation via an exchange reaction of Fe with CO in FeCO.

Evaluation Studies↗

Applications of activation analysis to geochemical, meteoritic and lunar studies.

The application of activation analysis techniques to the analysis of cosmological materials, i.e., terrestrial, tektitic, meteoritic, and lunar matter, is reviewed. Elemental determinations can be made by instrumental fast-neutron and thermal-neutron activation analysis, photonuclear and charged-particle activation analysis, and by radiochemical neutron activation analysis. Partition-coefficient methods, autoradiography studies, gamma-gamma coincidence counting, and age determination by neutron activation are discussed. Attention is given to K-Ar and I-Xe dating of meteorites.

Showalter, D. L.↗

Reflection and transmission of electromagnetic waves by a multilayered solar cell containing organic materials

Light trapping or absorption is a key concept for design and fabricating solar cells. The propagation of electromagnetic waves through a multilayered solar cell containing organic materials has theoretically investigated. In particular, the reflected, transmitted, and absorbed powers are found and defined. The main parameters of the structure and the required equations for TE polarization are presented in detail. The boundary conditions of the electric and magnetic fields of the incident waves are imposed at each interface and Snell’s law is applied. Expressions for the overall reflection and transmission coefficients are provided by a recursive method. The reflected, transmitted, and absorbed powers are determined using these coefficients. In the numerical results, the mentioned powers are computed and illustrated as a function of the angle of incidence, the wavelength, and the thickness of the active layer when the extinction coefficient of the active layer changes.

14 SOLAR ENERGY↗

Characterizations of the radioactive waste by the remotely-controlled collimated spectrometric system

Decontamination and decommissioning of the research reactors MR (Testing Reactor) and RFT (Reactor of Physics and Technology) has recently been initiated in the National Research Center (NRC) 'Kurchatov institute', Moscow. In the building, neighboring to the reactor, the storage of HLRW is located. The storage is made of monolithic concrete in which steel cells depth 4 m are located. In cells of storage the HLRW packed into cases are placed. These the radioactive waste are also subject to export on long storage in the specialized organization. For characterization of the radioactive waste in cases the remote-controlled collimated spectrometer system was used. The system consists of a spectrometric collimated gamma-ray detector, a color video camera and a control unit, mounted on a rotator, which are mounted on a tripod with the host computer. For determination of specific activity of radionuclides in cases, it is developed programs of calculation of coefficients of proportionality of specific activity to the corresponding speeds of the account in peaks of full absorption at single specific activity of radionuclides in cases. For determination of these coefficients the mathematical model of spectrometer system based on the Monte-Carlo method was used. Dependences of calibration coefficients for various radionuclides from distance between the detector and a case at various values of the radioactive waste density in cases are given. Measurements of specific activity in cases are taken and are discussed. By results of measurements decisions on the appeal of the radioactive waste being in cases are made. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A method to quantify the 37 Ar emanation fraction in powders and rocks

In order to make predictions of the potential 37 Ar signal from an underground nuclear explosion, a value for the 37 Ar emanation fraction is needed. Here, a system was developed to quantify the emanation fraction from samples ranging in size from powder to small rocks. Assorted rock samples were irradiated with Watt fission spectrum neutrons to produce radioactive argon gas via activation of calcium. The argon produced was extracted on a custom apparatus and cryogenically trapped. The extracted gas was then processed to separate the argon and load it into a proportional counter for counting. The emanation fraction of argon gas from the rock samples was then calculated by comparing the measured and predicted activities.

37Ar↗

Effect of Solvent on the Local Structure, Dynamics, and Vibrational Density of States in Sn-BEA Zeolite

Lewis acid zeolites are attractive catalysts for epoxidation and biomass valorization, as they are highly active and selective in the liquid phase and can operate at or near ambient conditions. While a rich experimental literature exists on liquid-phase Lewis acid zeolite catalysis, our understanding of the molecular organization and solvent dynamics in the vicinity of Lewis acid sites with differing metal site speciation remains limited. In this work, we investigate the molecular coordination and diffusion of two common solvents (methanol and water) around the closed and open Sn-BEA zeolite active sites using molecular dynamics simulations with a machine-learned interatomic potential trained on ab initio molecular dynamics trajectories. Molecular dynamics simulations reveal that introducing active sites significantly enhances local order in the first and second solvation shells compared to the pure silica case. For methanol, both closed and open active sites are singly coordinated, while more than two water molecules coordinate the open site. In contrast to methanol, we observed that water molecules dissociate, leading to the formation of additional Sn-OH and silanol groups away from the active site. The diffusion coefficients of water and methanol are functions of the solvent population in the pore. Here, our work provides insights into how active site speciation in Lewis acid zeolites affects solvent coordination, diffusion, and vibrational signature. This information is foundational for catalyst design and optimization of liquid-phase catalytic processes in zeolites. It also demonstrates the suitability of machine-learned interatomic potentials for modeling reactive systems, enabling sufficiently long trajectories for appropriate statistical averaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Friction and wear behavior of single-crystal silicon carbide in sliding contact with various metals

Sliding friction experiments were conducted with single-crystal silicon carbide in contact with various metals. Results indicate the coefficient of friction is related to the relative chemical activity of the metals. The more active the metal, the higher the coefficient of friction. All the metals examined transferred to silicon carbide. The chemical activity of the metal and its shear modulus may play important roles in metal transfer, the form of the wear debris and the surface roughness of the metal wear scar. The more active the metal, and the less resistance to shear, the greater the transfer to silicon carbide and the rougher the wear scar on the surface of the metal. Hexagon shaped cracking and fracturing formed by cleavage of both prismatic and basal planes is observed on the silicon carbide surface.

Miyoshi, K.↗

Friction and wear behavior of single-crystal silicon carbide in sliding contact with various metals

Sliding friction experiments were conducted with single-crystal silicon carbide in contact with various metals. Results indicate the coefficient of friction is related to the relative chemical activity of the metals. The more active the metal, the higher the coefficient of friction. All the metals examined transferred to silicon carbide. The chemical activity of the metal and its shear modulus may play important roles in metal-transfer, the form of the wear debris and the surface roughness of the metal wear scar. The more active the metal, and the less resistance to shear, the greater the transfer to silicon carbide and the rougher the wear scar on the surface of the metal. Hexagon-shaped cracking and fracturing formed by cleavage of both prismatic and basal planes is observed on the silicon carbide surface.

Miyoshi, K.↗

EARLINET Evaluation of the CATS L2 Aerosol Backscatter Coefficient Product

We present the evaluation activity of the European Aerosol Research Lidar Network (EARLINET) for the quantitative assessment of the Level 2 aerosol backscatter coefficient product derived by the Cloud-Aerosol Transport System (CATS) onboard the International Space Station (ISS). The study employs correlative CATS and EARLINET backscatter measurements within 50km distance between the ground station and the ISS overpass and as close in time as possible, typically within 90min, from February 2015 to September 2016. The results demonstrate the good agreement of CATS Level 2 backscatter coefficient and EARLINET. Three ISS overpasses close to the EARLINET stations of Leipzig-Germany, Évora-Portugal and Dushanbe-Tajikistan are analysed here to demonstrate the performance of CATS lidar system under different conditions. The results show that under cloud-free, relative homogeneous aerosol conditions CATS is in good agreement with EARLINET, independently of daytime/nighttime conditions. CATS low negative biases, partially attributed to the deficiency of lidar systems to detect tenuous aerosol layers of backscatter signal below the minimum detection thresholds, may lead to systematic deviations and slight underestimations of the total Aerosol Optical Depth (AOD) in climate studies. In addition, CATS misclassification of aerosol layers as clouds, and vice versa, in cases of coexistent and/or adjacent aerosol and cloud features, may lead to non-representative, unrealistic and cloud contaminated aerosol profiles. The distributions of backscatter coefficient biases show the relatively good agreement between the CATS and EARLINET measurements, although on average underestimations are observed, 22.3% during daytime and 6.1% during nighttime.

EARLINET/CATS evaluation↗