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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Determination of O2(a1Delta g) and O2(b1Sigma + g) yields in the reaction O + ClO yields Cl + O2 - Implications for photochemistry in the atmosphere of Venus

A discharge flow apparatus with a chemiluminescence detector was used to investigate the reaction O + ClO yields Cl + O2(asterisk), where O2(asterisk) = O2(a1Delta g) or O2(b1Sigma + g). It is found that the observed O2(a1Delta g) airglow of Venus cannot be explained in the framework of standard photochemistry using the experimental results obtained here and those reported in the recent literature. The possibility of an alternative source of O atoms derived from SO2 photolysis in the Venus mesosphere is suggested.

Leu, Ming-Taun↗
NASA NTRS1997

Temperature-Dependent Kinetics Studies of the Reactions Br((sup 2)P3/2) + H2S yields SH + HBr and Br((sup 2)P3/2) + CH3SH yields CH3S + HBr. Heats of Formation of SH and CH3S Radicals

Time resolved resonance fluorescence detection of Br(sup 2)P3/2) atom disappearance or appearance following 266-nm laser flash photolysis of CF2Br2/H2S/H2/N2, CF2Br2/CH3SH/H2/N2, Cl2CO/H2S/HBr/N2, and CH3SSCH3/HBr/H2/N2 mixtures has been employed to study the kinetics of the reactions Br((sup 2)P3/2) + H2S = SH + HBr (1,-1) and Br((sup2)P3/2) + CH3SH = CH3S + HBr (2, -2) as a function of temperature over the range 273-431K. Arrhenius expressions in units of 10(exp -12) cu cm/molecule/s which describe the results are k1 = (14.2 +/- 3.4) exp[(-2752 +/- 90)/T],(k-1) = (4.40 +/- 0.92) exp[(-971 +/- 73)/T],k(2) = (9.24 +/- 1.15) exp[(-386 +/- 41)/T], and k(-2) = (1.46 +/-0.21) exp[(-399 +/-41)/T; errors are 2 sigma and represent precision only. By examining Br((sup 2)P3/2) equilibrium kinetics following 355nm laser flash photolysis of Br2/CH3SH/H2/N2 mixtures, a 298 K rate coefficient of (1.7 +/- 0.5) x 10(exp -10) cu cm/molecule/s has been obtained for the reaction CH3S + Br2 yields CH3SBr + Br. To our knowledge, these are the first kinetic data reported for each of the reactions studied. Measured rate coefficients, along with known rate coefficients for similar radical + H2S, CH3SH, HBr,Br2 reactions are considered in terms of possible correlations of reactivity with reaction thermochemistry and with IP - EA, the difference between the ionization potential of the electron donor and the electron affinity of the electron acceptor. Both thermochemical and charge-transfer effects appear to be important in controlling observed reactivities. Second and third law analyses of the equilibrium data for reactions 1 and 2 have been employed to obtain the following enthalpies of reaction in units of kcal/mol: for reaction 1, Delta-H(298) = 3.64 +/- 0.43 and Delta-H(0) = 3.26 +/-0.45; for reaction 2, Delta-H(298) = -0.14 +/- 0.28 and Delta-H(0) = -0.65 +/- 0.36. Combining the above enthalpies of reaction with the well-known heats of formation of Br, HBr, H2S, and CH3SH gives the following heats of formation for the RS radicals in units of kcal/mol: Delta-H(sub f)(sub 0)(SH) = 34.07 +/- 0.72, Delta-H(sub f)(sub 298)(SH) = 34.18 +/- 0.68, Delta-H(sub f)(sub 0)(CH3S) = 31.44 +/- 0.54, Delta-H(sub f)(sub 298)(CH3S) = 29.78 +/- 0.44; errors are 2 sigma and represent estimates of absolute accuracy. The SH heat of formation determined from our data agrees well with literature values but has reduced error limits compared to other available values. The CH3S heat of formation determined from our date is near the low end of the range of previous estimates and is 3-4 kcal/mol lower than values derived from recent molecular beam photofragmentation studies.

Nicovich, J. M.↗
NASA NTRS1976

Rates of reactions ClO + ClO yields Cl2 + O2 and ClO + O yields Cl + O2 at elevated temperatures

Results are reported for an experiment in which a shock tube was employed to measure the reaction rates of chlorine-oxygen systems at high temperatures. In this experiment, a mixture of chlorine and ozone, diluted by oxygen and argon, was heated by two consecutive shock waves (primary and reflected) to produce a temperature in the range from 1000 to 1400 K and a pressure of between 3.5 and 9 atm. The reflected shock thermally decomposed the ozone; the resulting atomic oxygen reacted with molecular chlorine to produce ClO; and the variation in ClO concentration after passage of the reflected shock was observed by monitoring the intensity of 2537-A radiation passing through the test gas. The rates of the two cited reactions are deduced from the variation pattern. The rate coefficient values are found to be compatible with existing data obtained in lower pressure and temperature ranges.

Park, C.↗
NASA NTRS1986

Calculated potential surfaces for the reactions: O + N2 yields NO + N and N + O2 yields NO + O

Complete Active Space SCF/Contracted CI (CASSCF/CCI) calculations, using large Gaussian basis sets, are presented for selected portions of the potential surfaces for the reactions in the Zeldovich mechanism for the conversion of N2 to NO. The N + O2 reaction is exoergic by 32 kcal/mole and is computed to have an early barrier of 10.2 kcal/mole for the (sup 2)A(sup prime) surface and 18.0 kcal/mole for the (sup 4)A(sup prime) surface. The O + N2 reaction is endoergic by 75 kcal/mole. The (sup 3)A(sup double prime) surface is calculated to have a late barrier of 0.5 kcal/mole, while the (sup 3)A(sup prime) surface is calculated to have a late barrier of 14.4 kcal/mole.

Walch, Stephen P.↗
NASA NTRS1989

Theoretical characterization of the potential energy surface for H + O2 yields HO2(asterisk) yields HO + O. II - The potential for H atom exchange in HO2

The results of CASSCF multireference contracted CI calculations with large ANO basis sets are presented for the exchange region of the HO2 potential-energy surface. The saddle point for H atom exchange is about 13 kcal/mol below the energy of H + O2; therefore, this region of the surface should be accessible during H + O2 recombination and methathesis reactions.

Walch, Stephen P.↗
NASA NTRS1993

Theoretical characterization of the reaction CH3 + OH yields CH3OH yields products - The (1)CH2 + H2O, H2 + HCOH, and H2 + H2CO channels

The potential energy surface (PES) for the CH3OH system has been characterized for the (1)CH2 + H2O, H2 + HCOH, and H2 + H2CO product channels using complete-active-space self-consistent-field (CASSCF) gradient calculations to determine the stationary point geometries and frequencies followed by CASSCF/internally contracted configuration-interaction (CCI) calculations to refine the energetics. The (1)CH2 + H2O channel is found to have no barrier. The long range interaction is dominated by the dipole-dipole term, which orients the respective dipole moments parallel to each other but pointing in opposite directions. At shorter separations there is a dative bond structure in which a water lone pair donates into the empty 'a' orbital of CH2. Subsequent insertion of CH2 into an OH bond of water have barriers located at -5.2 kcal/mol and 1.7 kcal/mol, respectively, with respect to CH3 + OH. From comparison of the computed energetics of the reactants and products to known thermochemical data it is estimated that the computed PES is accurate to plus or minus 2 kcal/mol.

Walch, Stephen P.↗
NASA NTRS1994

A comparison of CO(J = 1 yields 0) and CO(J = 2 yields 1) emission in the Milky Way molecular ring

We have carried out a CO (J = 2 right arrow 1) survey of the Scutum Arm region of the Milky Way molecular ring. Our goals are to compare CO (J = 2 right arrow 1) maps of individual Galactic clouds with the large-scale CO (J = 2 right arrow 1) emission from the Galactic plane, and to predict the CO (J = 2 right arrow 1) appearance of a Galactic cloud ensemble in an external galaxy. The angular resolution and spatial coverage of our survey are compatible with the existing CO (J = 1 right arrow 0) survey of this region by Sanders et al., which we use for comparison. We identify 34 molecular clouds in our map region; their relationships between size and line width and between virial mass and luminosity are consistent with the relationships seen in CO (J = 1 right arrow 0) emission. However, we note that previous studies have shown considerable variation in these relationships; we attribute much of this variation to differences in their cloud definition algorithm and statistical method. We find that the median ratio of integrated emission in the two lowest CO transitions for the clouds in our sample is I(2 right arrow 1)/ I(1 right arrow 0) = 0.69, implying that the typical emitting region in the line of sight contains cold gas that is not actively star-forming. Our conclusion that the molecular ring emission is not dominated by star-forming regions is consistent with other large-scale studies of the Milky Way. Our distributions of cloud size and temperature also imply that relatively massive molecular clouds that lac k star formation, such as Maddalena's cloud, are not rare in the inner Galaxy.

Chiar, Jean E.↗
NASA NTRS1995

MP2 Studies of Relativistic Effects on the Linear Stationary Points of the H+Cl2 Yields HCl+Cl and Cl+HCl Yields ClH+Cl Reactions

The influence of relativistic effects on the linear stationary points of the potential energy surfaces of the ClHCl and HCl2 systems is studied. Scalar relativistic effects have little influence on the geometries and the energies of these points. Spin-orbit effects have no influence on the barrier of the forward reaction of H with Cl2, but increase the reaction energy. The total relativistic effect is an increase of the reaction energy by 2.3 kJ /mol. The barrier for the iso-energetic exchange reaction of HCl with Cl is decreased by 0.5 kJ /mol due to the scalar relativistic effects. This small decrease is cancelled by the larger increase of 2.5 kJ /mol due to spin-orbit effects, giving a total relativistic effect of 2.0 kJ /mol.

Visscher, L.↗
NASA NTRS2021

Methodology to Assess the Changing Risk of Yield Failure Due to Heat and Drought Stress Under Climate Change

While the understanding of average impacts of climate change on crop yields is improving, few assessments have quantified expected impacts on yield distributions and the risk of yield failures. Here we present the relative distribution as a method to assess how the risk of yield failure due to heat and drought stress (measured in terms of return period between yields falling 15% below previous five year Olympic average yield) responds to changes of the underlying yield distributions under climate change. Relative distributions are used to capture differences in the entire yield distribution between baseline and climate change scenarios, and to further decompose them into changes in the location and shape of the distribution. The methodology is applied here for the case of rainfed wheat and grain maize across Europe using an ensemble of crop models under three climate change scenarios with simulations conducted at 25 km resolution. Under climate change, maize generally displayed shorter return periods of yield failures (with changes under RCP 4.5 between −0.3 and 0 years compared to the baseline scenario) associated with a shift of the yield distribution towards lower values and changes in shape of the distribution that further reduced the frequency of high yields. This response was prominent in the areas characterized in the baseline scenario by high yields and relatively long return periods of failure. Conversely, for wheat, yield failures were projected to become less frequent under future scenarios (with changes in the return period of −0.1 to +0.4 years under RCP 4.5) and were associated with a shift of the distribution towards higher values and a change in shape increasing the frequency of extreme yields at both ends. Our study offers an approach to quantify the changes in yield distributions that drive crop yield failures. Actual risk assessments additionally require models that capture the variety of drivers determining crop yield variability and scenario climate input data that samples the range of probable climate variation.

Climate risk assessment↗
DOE OSTI2025

Switchgrass ( Panicum Virgatum ) and Miscanthus ( Miscanthus × Giganteus ) Long-Term Yield Patterns Reveal Consistent Productivity Declines

Perennial grasses like switchgrass ( Panicum virgatum ) and miscanthus ( Miscanthus × giganteus ) are expected to supply a substantial amount of the United States bioeconomy's feedstock demand. However, uncertainties around their long-term yields challenge the viability of their potential and limit their wider adoption. To resolve their long-term yield patterns, we analyzed over 200 plantings of switchgrass and miscanthus across Michigan and Wisconsin, USA, measured over 5–15 years. We found a consistent two-phase long-term yield dynamic; during a yield-building phase , peak yields occurred within 4–5 years after planting, followed by a yield-decline phase in which switchgrass and miscanthus lost 30%–47% and 14%–40% of peak yields, respectively. Among the potential drivers of this dynamic and the yield decline, we found that weather conditions had little impact, as the variation across years was not large enough to drive the observed yield differences. Added nitrogen increased peak yields by 10%–20% and attenuated the yield decline by 20%–50%. However, since fertilized stands still showed a yield decline, other factors became limiting as stands aged. This conserved long-term yield dynamic has direct implications on management. A farm-to-gate economic analysis suggests replanting switchgrass and miscanthus 5 and 9 years following their peak yields maximizes profit over a 30-year time horizon. Results call for further management and breeding strategies to mitigate the yield-decline phase, and for reparameterization of global bioenergy models with carbon capture and storage, which may overestimate yields and the economic and environmental benefits of crops grown for bioenergy feedstocks.

bioenergy↗
DOE OSTI2026

Data for Yield from Iowa’s first commercial miscanthus fields: implications of spatial variability for productivity and sustainability beyond research plots

This dataset contains biomass yield measurements and associated vegetation index data collected from commercial Miscanthus × giganteus fields in eastern Iowa during the 2022–2023 growing seasons. The data support the analyses presented in the article: “Yield From Iowa's First Commercial Miscanthus Fields: Implications of Spatial Variability for Productivity and Sustainability Beyond Research Plots.” We collected 105 ground-truth biomass samples from four mature commercial fields (>4 years old) covering 92.81 ha. Samples were taken from 3 m² quadrats that were hand-harvested in alignment with commercial harvest timing. Stem biomass (excluding leaves) was weighed, moisture-corrected, and converted to dry-matter yield expressed in Mg DM ha⁻¹. Sampling locations were selected to capture spatial variability visible in aerial imagery and were recorded using RTK GPS. Each biomass observation was paired with vegetation indices derived from high-resolution PlanetScope satellite imagery (3 m resolution). Images were acquired throughout the growing season, and indices were calculated to evaluate their ability to predict end-of-season biomass yield. Statistical and machine learning approaches were used to identify key predictors, and a linear regression model based on end-of-July Green Normalized Difference Vegetation Index (GNDVI) was developed and evaluated. This repository includes the data used in that modeling workflow. Management practices, economic data, full imagery time series, and additional methodological details are described in the associated publication and are not included here. The dataset consists of three comma-separated value (CSV) files: 1. Combine_Groundtruth_Yield_VI_22_23.csv This file contains ground-truth biomass yield measurements and associated key vegetation index values collected during the 2022 and 2023 growing seasons. Rows: 105 observations Columns: Year — Year of observation (2022 or 2023) Field — Field location identifier Sample_number — Unique sample identifier GNDVI_End_Jul — Green Normalized Difference Vegetation Index calculated at end of July GNDVI_End_Aug — Green Normalized Difference Vegetation Index calculated at end of August NDRE_End_Aug — Normalized Difference Red Edge index calculated at end of August Biomass_Stem_Yield_MgDM/ha — Measured stem biomass yield (megagrams dry matter per hectare) 2. trainData_GNDVI.csv This file contains the subset of observations used to train the predictive relationship between July GNDVI and biomass yield. Rows: 76 observations Columns: Unnamed: 0 — Row index retained from the original data processing workflow GNDVI_End_Jul — GNDVI at end of July Stem_Yield_MgDM/ha — Observed stem biomass yield (Mg DM ha⁻¹) 3. testData_GNDVI.csv This file contains the test dataset used to evaluate model performance. Rows: 29 observations Columns: Unnamed: 0 — Row index retained from the original data processing workflow GNDVI_End_Jul — GNDVI at end of July Predicted_Yield_MgDM/ha — Model-predicted stem biomass yield (Mg DM ha⁻¹) Observed_Yield_MgDM/ha — Measured stem biomass yield (Mg DM ha⁻¹)

Potential yield, yield gap, in-field management, y↗
NASA NTRS2021

Future Climate Change Significantly Alters Interannual Wheat Yield Variability Over Half of Harvested Areas

Climate change affects the spatial and temporal distribution of crop yields, which can critically impair food security across scales. A number of previous studies have assessed the impact of climate change on mean crop yield and future food availability, but much less is known about potential future changes in interannual yield variability. Here, we evaluate future changes in relative interannual global wheat yield variability (the coefficient of variation (CV)) at 0.25° spatial resolution for two representative concentration pathways (RCP4.5 and RCP8.5). A multi-model ensemble of crop model emulators based on global process-based models is used to evaluate responses to changes in temperature, precipitation, and CO2. The results indicate that over 60% of harvested areas could experience significant changes in interannual yield variability under a high-emission scenario by the end of the 21st century (2066–2095). About 31% and 44% of harvested areas are projected to undergo significant reductions of relative yield variability under RCP4.5 and RCP8.5, respectively. In turn, wheat yield is projected to become more unstable across 23% (RCP4.5) and 18% (RCP8.5) of global harvested areas—mostly in hot or low fertilizer input regions, including some of the major breadbasket countries. The major driver of increasing yield CV change is the increase in yield standard deviation, whereas declining yield CV is mostly caused by stronger increases in mean yield than in the standard deviation. Changes in temperature are the dominant cause of change in wheat yield CVs, having a greater influence than changes in precipitation in 53% and 72% of global harvested areas by the end of the century under RCP4.5 and RCP8.5, respectively. This research highlights the potential challenges posed by increased yield variability and the need for tailored regional adaptation strategies.

Climate change↗
NASA NTRS2016

Spatial and Temporal Uncertainty of Crop Yield Aggregations

The aggregation of simulated gridded crop yields to national or regional scale requires information on temporal and spatial patterns of crop-specific harvested areas. This analysis estimates the uncertainty of simulated gridded yield time series related to the aggregation with four different harvested area data sets. We compare aggregated yield time series from the Global Gridded Crop Model Inter-comparison project for four crop types from 14 models at global, national, and regional scale to determine aggregation-driven differences in mean yields and temporal patterns as measures of uncertainty. The quantity and spatial patterns of harvested areas differ for individual crops among the four datasets applied for the aggregation. Also simulated spatial yield patterns differ among the 14 models. These differences in harvested areas and simulated yield patterns lead to differences in aggregated productivity estimates, both in mean yield and in the temporal dynamics. Among the four investigated crops, wheat yield (17% relative difference) is most affected by the uncertainty introduced by the aggregation at the global scale. The correlation of temporal patterns of global aggregated yield time series can be as low as for soybean (r = 0.28).For the majority of countries, mean relative differences of nationally aggregated yields account for10% or less. The spatial and temporal difference can be substantial higher for individual countries. Of the top-10 crop producers, aggregated national multi-annual mean relative difference of yields can be up to 67% (maize, South Africa), 43% (wheat, Pakistan), 51% (rice, Japan), and 427% (soybean, Bolivia).Correlations of differently aggregated yield time series can be as low as r = 0.56 (maize, India), r = 0.05∗Corresponding (wheat, Russia), r = 0.13 (rice, Vietnam), and r = −0.01 (soybean, Uruguay). The aggregation to sub-national scale in comparison to country scale shows that spatial uncertainties can cancel out in countries with large harvested areas per crop type. We conclude that the aggregation uncertainty can be substantial for crop productivity and production estimations in the context of food security, impact assessment, and model evaluation exercises.

Aggregation uncertainty↗