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At least 289 records · Page 16

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NASA NTRS1999

The value of assessing pulmonary venous flow velocity for predicting severity of mitral regurgitation: A quantitative assessment integrating left ventricular function

Although alteration in pulmonary venous flow has been reported to relate to mitral regurgitant severity, it is also known to vary with left ventricular (LV) systolic and diastolic dysfunction. There are few data relating pulmonary venous flow to quantitative indexes of mitral regurgitation (MR). The object of this study was to assess quantitatively the accuracy of pulmonary venous flow for predicting MR severity by using transesophageal echocardiographic measurement in patients with variable LV dysfunction. This study consisted of 73 patients undergoing heart surgery with mild to severe MR. Regurgitant orifice area (ROA), regurgitant stroke volume (RSV), and regurgitant fraction (RF) were obtained by quantitative transesophageal echocardiography and proximal isovelocity surface area. Both left and right upper pulmonary venous flow velocities were recorded and their patterns classified by the ratio of systolic to diastolic velocity: normal (>/=1), blunted (<1), and systolic reversal (<0). Twenty-three percent of patients had discordant patterns between the left and right veins. When the most abnormal patterns either in the left or right vein were used for analysis, the ratio of peak systolic to diastolic flow velocity was negatively correlated with ROA (r = -0.74, P <.001), RSV (r = -0.70, P <.001), and RF (r = -0.66, P <.001) calculated by the Doppler thermodilution method; values were r = -0.70, r = -0.67, and r = -0.57, respectively (all P <.001), for indexes calculated by the proximal isovelocity surface area method. The sensitivity, specificity, and predictive values of the reversed pulmonary venous flow pattern for detecting a large ROA (>0.3 cm(2)) were 69%, 98%, and 97%, respectively. The sensitivity, specificity, and predictive values of the normal pulmonary venous flow pattern for detecting a small ROA (<0.3 cm(2)) were 60%, 96%, and 94%, respectively. However, the blunted pattern had low sensitivity (22%), specificity (61%), and predictive values (30%) for detecting ROA of greater than 0.3 cm(2) with significant overlap with the reversed and normal patterns. Among patients with the blunted pattern, the correlation between the systolic to diastolic velocity ratio was worse in those with LV dysfunction (ejection fraction <50%, r = 0.23, P >.05) than in those with normal LV function (r = -0.57, P <.05). Stepwise linear regression analysis showed that the peak systolic to diastolic velocity ratio was independently correlated with RF (P <.001) and effective stroke volume (P <.01), with a multiple correlation coefficient of 0.71 (P <.001). In conclusion, reversed pulmonary venous flow in systole is a highly specific and reliable marker of moderately severe or severe MR with an ROA greater than 0.3 cm(2), whereas the normal pattern accurately predicts mild to moderate MR. Blunted pulmonary venous flow can be seen in all grades of MR with low predictive value for severity of MR, especially in the presence of LV dysfunction. The blunted pulmonary venous flow pattern must therefore be interpreted cautiously in clinical practice as a marker for severity of MR.

Non-NASA Center↗

DOE OSTI2021

Synthesis of new two-dimensional titanium carbonitride Ti 2 C 0.5 N 0.5 T x MXene and its performance as an electrode material for sodium-ion battery

Two-dimensional (2D) layered transition metal carbides/nitrides, called MXenes, are attractive alternative electrode materials for electrochemical energy storage. Owing to their metallic electrical conductivity and low ion diffusion barrier, MXenes are promising anode materials for sodium-ion batteries (SIBs). Herein, we report on a new 2D carbonitride MXene, viz ., Ti 2 C 0.5 N 0.5 T x (T x stands for surface terminations), and the only second carbonitride after Ti 3 CNT x so far. A new type of in situ HF (HCl/KF) etching condition was employed to synthesize multilayer Ti 2 C 0.5 N 0.5 T x powders from Ti 2 AlC 0.5 N 0.5 . Spontaneous intercalation of tetramethylammonium followed by sonication in water allowed for large-scale delamination of this new titanium carbonitride into 2D sheets. Multilayer Ti 2 C 0.5 N 0.5 T x powders showed higher specific capacities and larger electroactive surface area than those of Ti 2 CT x powders. Multilayer Ti 2 C 0.5 N 0.5 T x powders show a specific capacity of 182 mAh g -1 at 20 mA g -1 , the highest among all reported MXene electrodes as SIBs with excellent cycling stability.

25 ENERGY STORAGE↗

DOE OSTI2026

Xanthos-Lake Dataset

The Xanthos-Lake v1.0 dataset provides the input data, trained machine-learning models, and simulation outputs needed to characterize lake water balance, snow and ice conditions, and mixing-layer temperature within the Xanthos global hydrological modeling framework. The dataset supports lake representation across a wide range of lake sizes and hydroclimatic conditions by combining xLSIM, a basin-specific machine-learning emulator of lake snow, ice, ice-cover fraction, and mixing-layer temperature, with the Xanthos-Lake water-balance model. The archive contains NetCDF datasets used to train and evaluate xLSIM, trained model weights, processed meteorological and lake-property inputs, and basin- and lake-category-specific simulation outputs. These materials are organized into four primary data groups, described below. Snowice_model_inputs: Contains the NetCDF input data used to train xLSIM. The xLSIM machine-learning framework uses three lake-based datasets. The meteorological forcing dataset provides monthly relative humidity, specific humidity, surface wind speed, maximum and minimum air temperature, downward longwave and shortwave radiation, snowfall, surface air pressure, and total precipitation. Lake surface area is included as an additional static predictor. The target-state dataset provides lake ice thickness, snow depth, snow cover, and lake mixing-layer temperature, while a companion lake-surface dataset provides the lake ice-cover fraction. Before training, ice thickness and snow depth are converted from meters to centimeters, mixing-layer temperature is converted from kelvin to degrees Celsius and constrained to nonnegative values, and ice-cover fraction is converted from a fraction to a percentage. The predictor variables are normalized using statistics calculated across the selected lakes and time steps. Snowice_model_outputs: Contains the NetCDF outputs generated by xLSIM. For each basin, xLSIM produces a file containing observed and predicted lake-state variables for the training, validation, and testing periods. The modeled variables include lake ice thickness, snow depth, snow cover, mixing-layer temperature, and lake ice-cover fraction. For basins without a sufficiently persistent snow-and-ice signal, the emulator predicts only mixing-layer temperature. The outputs also include training and validation loss histories, the selected model configuration, identifiers of the lakes used in training, and SHAP-based feature-importance information at the global, lake, and seasonal-regime levels. The trained machine-learning model weights are provided separately within the dataset archive. Together, these files support model evaluation and subsequent coupling with the Xanthos-Lake water-balance framework. XanthosLAKES: Contains the NetCDF input data used by the Xanthos-Lake framework. Monthly meteorological inputs include relative and specific humidity, downward shortwave and longwave radiation, mean, maximum, and minimum air temperature, wind speed, precipitation, snowfall, and surface air pressure. Static lake-property datasets provide lake identifiers, geographic locations, surface area, volume, mean depth, elevation, drainage area, fetch, outlet-routing information, and associated Xanthos grid-cell attributes. Separate bathymetric datasets provide the coefficients of the area–depth and volume–depth relationships for each aggregated lake unit. GLEV-based records provide observed lake surface area and evaporation data used to initialize lake states, define reference conditions, and calibrate and evaluate the model. Xanthos-Lake Outputs: Contains the basin- and lake-category-specific NetCDF outputs generated by Xanthos-Lake. Monthly variables include lake surface area, storage volume, outlet discharge, evaporation rate, evaporation volume, lake–groundwater exchange, lake inflow, ice thickness, snow depth, snow-cover fraction, ice-cover fraction, and mixing-layer temperature. The files also contain lake-specific calibration and validation statistics, including normalized root-mean-square error, mean absolute error, Nash–Sutcliffe efficiency, Kling–Gupta efficiency, and percent bias. Stored calibrated and derived parameters include the weir discharge coefficient, fractional freeboard, groundwater exchange coefficient, reference water level, corresponding reference surface area and storage volume, weir-width adjustment factor, and the fraction of routed inflow entering the lake. Basin identifiers, lake category, simulation period, calibration and validation periods, and parameter-schema information are retained as NetCDF metadata.

Abeshu, Guta [Pacific Northwest National Laborator↗

DOE OSTI2021

Efficient Hydrogen Delivery for Microbial Electrosynthesis via 3D-Printed Cathodes

The efficient delivery of electrochemically in situ produced H 2 can be a key advantage of microbial electrosynthesis over traditional gas fermentation. However, the technical details of how to supply large amounts of electric current per volume in a biocompatible manner remain unresolved. Here, we explored for the first time the flexibility of complex 3D-printed custom electrodes to fine tune H 2 delivery during microbial electrosynthesis. Using a model system for H 2 -mediated electromethanogenesis comprised of 3D fabricated carbon aerogel cathodes plated with nickel-molybdenum and Methanococcus maripaludis, we showed that novel 3D-printed cathodes facilitated sustained and efficient electromethanogenesis from electricity and CO 2 at an unprecedented volumetric production rate of 2.2 L CH4 /L catholyte /day and at a coulombic efficiency of 99%. Importantly, our experiments revealed that the efficiency of this process strongly depends on the current density. At identical total current supplied, larger surface area cathodes enabled higher methane production and minimized escape of H 2 . Specifically, low current density (<1 mA/cm 2 ) enabled by high surface area cathodes was found to be critical for fast start-up times of the microbial culture, stable steady state performance, and high coulombic efficiencies. Our data demonstrate that 3D-printing of electrodes presents a promising design tool to mitigate effects of bubble formation and local pH gradients within the boundary layer and, thus, resolve key critical limitations for in situ electron delivery in microbial electrosynthesis.

03 NATURAL GAS↗

DOE OSTI2022

Tuning Surface Acidity of Mixed Conducting Electrodes: Recovery of Si‐Induced Degradation of Oxygen Exchange Rate and Area Specific Resistance

Abstract Metal oxides are an important class of functional materials, and for many applications, ranging from solid oxide fuel/electrolysis cells, oxygen permeation membranes, and oxygen storage materials to gas sensors (semiconducting and electrolytic) and catalysts, the interaction between the surface and oxygen in the gas phase is central. Ubiquitous Si‐impurities are known to impede this interaction, commonly attributed to the formation of glassy blocking layers on the surface. Here, the surface oxygen exchange coefficient ( k chem ) is examined for Pr 0.1 Ce 0.9 O 2‐δ (PCO), a model mixed ionic electronic conductor, via electrical conductivity relaxation measurements, and the area‐specific resistance (ASR) by electrochemical impedance spectroscopy. It is demonstrated that even low silica levels, introduced by infiltration, depress k chem by a factor 4000, while the ASR increases 40‐fold and we attribute this to its acidity relative to that of PCO. The ability to fully regenerate the poisoned surface by the subsequent addition of basic Ca‐ or Li‐species is further shown. This ability to not only recover Si‐poisoned surfaces by tuning the relative surface acidity of an oxide surface, but subsequently outperform the pre‐poisoned response, promises to extend the operating life of materials and devices for which the catalytic oxygen/solid interface reaction is central.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2025

Site-specific surface reactivity on SnO 2 : Evaluating selective atomic layer deposition processes

Area selective atomic layer deposition (AS-ALD) is a bottom-up synthesis approach with potential for deposition with molecular level precision. Here, the site-specific hydration of metal oxide substrates, combined with surface H 2 O-selective ALD processes, provides a potentially powerful path to targeted synthesis. Density functional theory (DFT) calculations are used to predict the thermodynamics of ALD precursor reactivity and hydration for (001), (101), (110), and (100) rutile SnO 2 facets as a function of temperature. Trimethylaluminum (TMA) and dimethyl aluminum isopropoxide (DMAI) dimers are predicted to react with both dehydrated and hydrated SnO 2 (001), (101), and (110) facets at ALD-relevant temperatures, while the SnO 2 (100) facet is predicted to be uniquely unreactive with TMA and DMAI monomers as well as dehydrate near 177 °C making this facet more amenable to targeted ALD. In situ ellipsometric studies of Al 2 O 3 ALD on polycrystalline SnO 2 at 150 °C are consistent with the computational predictions of rapid and unselective nucleation, in stark contrast to inhibited and selective ALD on isostructural rutile TiO 2 .

Atomic Layer Deposition↗

DOE OSTI2020

Establishing a Theoretical Landscape for Identifying Basal Plane Active 2D Metal Borides (MBenes) toward Nitrogen Electroreduction

Abstract To achieve efficient ammonia synthesis via electrochemical nitrogen reduction reaction (NRR), a qualified catalyst should have both high specific activity and large active surface area. However, integrating these two merits into one single material remains a big challenge due to the difficulty in balancing multiple reaction intermediates. Here, it is demonstrated that the boron‐analogues of MXenes, namely “MBenes”, could cope with the challenge and achieve the high activity and large reaction region simultaneously toward NRR. Using extensive density functional theory computations and taking 16 MBenes as representatives, it is identified that seven MBenes (CrB, MoB, WB, Mo 2 B, V 3 B 4 , CrMnB 2 , and CrFeB 2 ) not only have intrinsic basal plane activity for NRR with limiting potentials ranging from −0.22 to −0.82 V, but also possess superior capability of suppressing the competitive hydrogen evolution reaction. Particularly, different from the MXenes whose surface oxidation may block the active sites, once oxidized, these MBenes can catalyze NRR via the self‐activating process, reducing O*/OH* into H 2 O* under reaction conditions, and favoring the N 2 electroreduction. As a result, the exceptional activity and selectivity, high active area (≈10 19 m −2 ), and antioxidation nature render these MBenes as pH‐universal catalysts for NH 3 production without introducing any dopants and defects.

Guo, Xiangyu↗

DOE OSTI2024

Machine Learning Design of Perovskite Catalytic Properties

Abstract Discovering new materials that efficiently catalyze the oxygen reduction and evolution reactions is critical for facilitating the widespread adoption of solid oxide fuel cell and electrolyzer (SOFC/SOEC) technologies. Here, machine learning (ML) models are developed to predict perovskite catalytic properties critical for SOFC/SOEC applications, including oxygen surface exchange, oxygen diffusivity, and area specific resistance (ASR). The models are based on trivial‐to‐calculate elemental features and are more accurate and dramatically faster than the best models based on ab initio‐derived features, potentially eliminating the need for ab initio calculations in descriptor‐based screening. The model of ASR enables temperature‐dependent predictions, has well calibrated uncertainty estimates and online accessibility. Use of temporal cross‐validation reveals the model to be effective at discovering new promising materials prior to their initial discovery, demonstrating the model can make meaningful predictions. Using the SHapley Additive ExPlanations (SHAP) approach, detailed discussion of different approaches of model featurization is provided for ML property prediction. Finally, the model is used to screen more than 19 million perovskites to develop a list of promising cheap, earth‐abundant, stable, and high performing materials, and find some top materials contain mixtures of less‐explored elements (e.g., K, Bi, Y, Ni, Cu) worth exploring in more detail.

25 ENERGY STORAGE↗

NASA NTRS1977

Determination of burning area and port volume in complex burning regions of a solid rocket motor

An analysis of the geometry of the burning in both star-cylindrical port interface regions and regions of partially inhibited slots is presented. Some characteristics parameters are defined and illustrated. Methods are proposed for calculating burning areas which functionally depend only on the total distance burned. According to this method, several points are defined where abrupt changes in geometry occur, and these are tracked throughout the burn. Equations are developed for computing port perimeter and port area at pre-established longitudinal positions. Some common formulas and some newly developed formulas are then used to compute burning surface area and port volume. Some specific results are presented for the solid rocket motor committed to the space shuttle project.

Kingsbury, J. A.↗

NASA NTRS2005

Detection With Rhessi of High Frequency X-ray Oscillations in the Tail of the 2004 Hyperflare From SGR 1806-20

The recent discovery of high frequency oscillations in giant flares from SGR 1806-20 and SGR 1900+14 may be the first direct detection of vibrations in a neutron star crust. If this interpretation is correct it offers a novel means of testing the neutron star equation of state, crustal breaking strain, and magnetic field configuration. Using timing data from RHESSI, we have confirmed the detection of a 92.5 Hz Quasi-Periodic Oscillation (QPO) in the tail of the SGR 1806-20 giant flare. We also find another, stronger, QPO at higher energies, at 626.5 Hz. Both QPOs are visible only at particular (but different) rotational phases, implying an association with a specific area of the neutron star surface or magnetosphere. At lower frequencies we confirm the detection of an 18 Hz QPO, at the same rotational phase as the 92.5 Hz QPO, and report the additional presence of a broad 26 Hz QPO. We are however unable to make a robust confirmation of the presence of a 30 Hz QPO, despite higher count rates. We discuss our results in the light of neutron star vibration models.

Watts, Anna L.↗

DOE OSTI2020

Heat dissipation systems with hygroscopic working fluid

A heat dissipation system apparatus and method of operation using hygroscopic working fluid for use in a wide variety of environments for absorbed water in the hygroscopic working fluid to be released to minimize water consumption in the heat dissipation system apparatus for effective cooling in environments having little available water for use in cooling systems. The system comprises a low-volatility, hygroscopic working fluid to reject thermal energy directly to ambient air. The low-volatility and hygroscopic nature of the working fluid prevents complete evaporation of the fluid and a net consumption of water for cooling, and direct-contact heat exchange allows for the creation of large interfacial surface areas for effective heat transfer. Specific methods of operation prevent the crystallization of the desiccant from the hygrosopic working fluid under various environmental conditions.

42 ENGINEERING↗

DOE OSTI2021

Surfactant-templated synthesis of nanostructured xerogel adsorbent platforms

A process for separations and recovery from mixtures via specific adsorption using high-surface area, flexible silica-based nanostructured gel adsorbents and articles of manufacture relating to same.

de Leon, Patricia Ignacio↗

DOE OSTI2023

Heat dissipation systems with hygroscopic working fluid

Martin, Christopher L.↗

DOE OSTI2024

Root exudation links root traits to soil functioning in agroecosystems

Root exudation is a key process for plant nutrient acquisition, but the controls on root exudation and its relationship to soil C and N processes in agroecosystems are unclear. We hypothesized that root exudation rates would be related to root morphological traits, N fertilization, and soil moisture. We also anticipated that root exudation would be correlated with bulk soil enzyme activity. Root exudation, root traits, and bulk soil extracellular enzyme activity were assessed in maize (Zea mays L.), soybean (Glycine max (L.) Merr.), biomass sorghum (Sorghum bicolor (L.) Moench), giant miscanthus (Miscanthus × giganteus), and switchgrass (Panicum virgatum L.). Measurements were taken in situ during two growing seasons with contrasting precipitation regimes, and N fertilization rate was varied in sorghum during one year. Specific root exudation (per unit root surface area) was negatively related to root diameter and was generally higher in annuals than perennials. Sorghum N fertilization did not affect root exudation rates, and soil moisture regime had no effect on annual root exudation rates within maize, sorghum, and miscanthus. Specific root exudation was negatively related to bulk soil C- and N-degrading soil enzyme activities. Intrinsic plant characteristics appeared more important than environmental variables in controlling in situ root exudation rates. The relationships between root diameter, root exudation, and soil C and N processes link root morphological traits to soil functions and demonstrate the potential tradeoffs among plant nutrient acquisition strategies in agroecosystems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Data for Root Exudation Links Root Traits to Soil Functioning in Agroecosystems

Biomass Analytics↗

NASA NTRS1976

Comparison of acoustic and strain gauge techniques for crack closure measurements

A quantitative study on the systems performances of the COD gauge and the acoustic transmission techniques to elastic deformation of part-through crack and compact tension specimens has been conducted. It is shown that the two instruments measure two completely different quantities: The COD gauge yields information on the length change of the specimen whereas the acoustic technique is sensitive directly to the amount of contract area between two surfaces, interfering with the acoustic signal. In another series of experiments, compression tests on parts with specifically prepared surfaces were performed so that the surface contact area could be correlated with the transmitted acoustic signal, as well as the acoustic with the COD gauge signal. A linear relation between contact area and COD gauge signal was obtained until full contact had been established.

Buck, O.↗

DOE OSTI2022

Electrochemical characterization of evolving ionomer/electrocatalyst interactions throughout accelerated stress tests

Here, the degradation of polymer electrolyte membrane fuel cells (PEMFCs) catalyst layers used for heavy-duty vehicles was examined using a catalyst-specific accelerated stress test (AST). High surface area carbon supported dispersed Pt (Pt/HSC), annealed Pt (a-Pt/HSC) and PtCo (PtCo/HSC) alloy catalysts were examined over the course of 90,000 cycles by measuring changes in mass activity, O 2 transport resistance, electrochemical active surface area (ECSA), catalyst accessibility and ionomer-electrocatalyst interactions. Compared to a-Pt/HSC and Pt/HSC catalyst, the PtCo/HSC showed better initial mass activity, a larger initial mass transport loss, and faster degradation after the first 30k AST cycles, as a large portion of Co leached out during potential cycling. Pt/HSC showed higher initial performance relative to a-Pt/HSC but had faster degradation. STEM characterizations show that the ECSA losses are largely related to Pt dissolution resulting in either catalyst particle growth via the Ostwald ripening mechanism or redeposition in the membrane. Catalyst accessibility measurements showed decreased RH sensitivity for all three samples, while CO impedance measurements revealed a decrease in both Pt-water and carbon-water interactions. This implies that, Pt is either preferentially redepositing on the exterior of the carbon support, or that the ionomer is undergoing morphological changes enabling the enhanced intrusion of mesopores.

25 ENERGY STORAGE↗

DOE OSTI2022

Modulation of recombination zone position for white perovskite/organic emitter hybrid light-emitting devices

We report metal halide perovskites present specific challenges as emitters in large area, surface emission lighting devices. Among these challenges is the vast difference in carrier mobilities between the perovskite and many organic buffer layers typically used in such device fabrication as transport and blocking layers. This can make it difficult to engineer recombination to achieve white emitting devices generally. However, in this work, we introduce unique modulation of excitonic confinement within the perovskite layer of the device stack to control overall placement of the recombination zone. This results in a white light emitter that is bright and highly tunable, providing a path to realize white perovskite related light-emitting devices.

42 ENGINEERING↗