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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Collecting, analyzing and archiving of ground based infrared solar spectra obtained from several locations

The infrared solar spectrum as observed from the ground under high resolution contains thousands of absorption lines. The majority of these lines are due to compounds that are present in the Earth's atmosphere. Ground based infrared solar spectra contain information concerning the composition of the atmosphere at the time the spectra were obtained. The objective of this program is to record solar spectra from various ground locations, and to analyze and archive these spectra. The analysis consists of determining, for as many of the absorption lines as possible, the molecular species responsible for the absorption, and to verify that current models of infrared transmission match the observed spectra. Archiving is an important part of the program, since a number of the features in the spectra have not been identified. At some later time, when the features are identified, it will be possible to determine the amount of that compound that was present in the atmosphere at the time the spectrum was taken.

Murcray, David G.↗
DOE OSTI2021

Two-Dimensional and Three-Dimensional Tetrel-Arsenide Frameworks Templated by Li and Cs Cations

Two new ternary tetrel pnictide phases, Li 1.08 Ge 4.92 As 7 and Cs 0.11 Zn 0.05 Si 0.95 As, have been synthesized. Both compounds crystallize in new structure types, which demonstrate the flexibility of Ge(Si)–As layers when accommodating electropositive cations of various sizes. Li 1.08 Ge 4.92 As 7 displays a Ge-As layer motif that has not been observed in ternary Ge-As systems, while Cs 0.11 Zn 0.05 Si 0.95 As exhibits a 3D framework composed of fragments of the 2D parent-phase SiAs. For Li 1.08 Ge 4.92 As 7 , a combination of computational modeling and solid-state 7 Li MAS NMR was used to establish the correct crystal structure with one mixed occupied Ge/Li site. The compositions of the phases were confirmed through energy-dispersive X-ray spectroscopy. Transport properties and UV–Vis spectroscopy reveal both reported compounds to be semiconductors. Cs 0.11 Zn 0.05 Si 0.95 As shows high thermal stability with congruent melting at 1300 K and an exceptionally low thermal conductivity of 0.5 W m –1 K –1 at 300 K. Temperature-dependent Li-ion hopping dynamics in Li 1.08 Ge 4.92 As 7 was characterized using 7 Li solid-state NMR.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Performance of sweeping gas membrane distillation for treating produced water: Modeling and experiments

Membrane distillation (MD) has shown promise for desalination of produced water (PW), but there are very few studies reported on the performance of MD with real PW and the characteristics of the fouling and scaling in MD. Among different MD configurations, sweeping gas MD (SGMD) is the least studied configuration. Here we report the application of SGMD for treating high-salinity PW (123 g L -1 ). The SGMD operating conditions were first carefully optimized through pure water MD experiments by varying operating conditions. The flux evaluation was accompanied by a detailed Aspen Custom Modeler simulation based on the electrolyte-NRTL thermodynamic model to better understand the heat and mass transfer in the feed and permeate channel. Supported by experiments, modeling results confirmed the partial condensation of the vapor in the permeate channel. Furthermore, it was concluded that the saturation of the sweeping gas is controlling the overall mass transfer through the membrane. Selected membranes and optimized conditions were then used to conduct short-term and long-term performance tests with PW. In long-term MD test, the concentration of the PW increased by a factor of two (50% water recovery), while the membrane exhibited small flux decline. Elemental analysis showed that strontium and sodium were the major scalant compounds.

42 ENGINEERING↗
DOE OSTI2024

Model associated with: "Thermodynamic control on the decomposition of organic matter across different electron acceptors"

This model data package is associated with the publication “Thermodynamic control on the decomposition of organic matter across different electron acceptors” submitted to Soil Biology and Biochemistry (Zheng et al., 2023; https://doi.org/10.1016/j.soilbio.2024.109364).In this research, a thermodynamic modeling framework is built to flexibly incorporate both organic matter (OM) molecules and electron acceptors for estimating potential free energy release from various redox reactions and to further predict reaction rates based on Microbial Transition State Theory. The model package includes scripts for thermodynamic modeling and postprocessing. Input Fourier-transform ion cyclotron resonance (FTICR) data are from a previous experimental study (Boye et al., 2018), and model outputs are free energy predictions and stoichiometric coefficients associated with all possible redox reactions.This data package is associated with the project GitHub repository found at MM_bioenergetic_modeling.This data package contains four folders (Input_FTICR, Model, Output, and Output_processing), a file-level metadata (FLMD) csv, and a data dictionary (dd) csv. Please see Zheng_bioenergetic_modeling_flmd.csv for a list of all files contained in this data package and descriptions for each. The Zheng_bioenergetic_modeling_dd.csv file describes the csv column headers. The “Model” folder contains scripts to run energy balance calculations for each electron acceptor. The “Output” folder contains csv files with stoichiometric information from model simulations. And the "Output_processing" folder contains scripts for reaction rate calculations and to generate plots.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1974

Model systems for life processes on Mars

In the evolution of life forms nonphotosynthetic mechanisms are developed. The question remains whether a total life system could evolve which is not dependent upon photosynthesis. In trying to visualize life on other planets, the photosynthetic process has problems. On Mars, the high intensity of light at the surface is a concern and alternative mechanisms need to be defined and analyzed. In the UV search for alternate mechanisms, several different areas may be identified. These involve activated inorganic compounds in the atmosphere, such as the products of photodissociation of carbon dioxide and the organic material which may be created by natural phenomena. In addition, a life system based on the pressure of the atmospheric constituents, such as carbon dioxide, is a possibility. These considerations may be important for the understanding of evolutionary processes of life on another planet. Model systems which depend on these alternative mechanisms are defined and related to presently planned and future planetary missions.

Mitz, M. A.↗
DOE OSTI2020

Estimation of abatement potentials and costs of air pollution emissions in China

Understanding the air pollution emission abatement potential and associated control cost is a prerequisite to design cost ef?cient control policies. In this study, a linear programming algorithm model, International Control Cost Estimate Tool, was updated with cost data for applications of 56 types of end-of-pipe technologies and ?ve types of renewable energy in 10 major sectors namely power generation, industry combustion, cement pro-duction, iron and steel production, other industry processes, domestic combustion, transportation, solvent use, livestock rearing, and fertilizer use. The updated model was implemented to estimate the abatement potential and marginal cost of multiple pollutants in China. The total maximum abatement potentials of sulfur dioxide (SO2), nitrogen oxides (NOx), primary particulate matter (PM2.5), non-volatile organic compounds (NMVOCs), and ammonia (NH3) in China were estimated to be 19.2, 20.8, 9.1, 17.2 and 8.6 Mt, respectively, which accounted for 89.7%, 89.9%, 94.6%, 74.0%, and 80.2% of their total emissions in 2014, respectively. The associated control cost of such reductions was estimated as 92.5, 469.7, 75.7, 449.0, and 361.8 billion CNY in SO2, NOx, primary PM2.5, NMVOCs and NH3, respectively. Shandong, Jiangsu, Henan, Zhejiang, and Guangdong provinces exhibited large abatement potentials for all pollutants. Provincial disparity analysis shows that high GDP regions tend to have higher reduction potential and total abatement costs. End-of-pipe technologies tended be a cost-ef?cient way to control pollution in industries processes (i.e., cement plants, iron and steel plants, lime production, building ceramic production, glass and brick production), whereas such technologies were less cost- effective in fossil fuel-related sectors (i.e., power plants, industry combustion, domestic combustion, and transportation) compared with renewable energy. The abatement potentials and marginal abatement cost curves developed in this study can further be used as a crucial component in an integrated model to design optimized cost-ef?cient control policies.

Zhang, Fenfen↗
DOE OSTI2020

Linear in temperature resistivity in the limit of zero temperature from the time reparameterization soft mode

The most puzzling aspect of the ‘strange metal’ behavior of correlated electron compounds is that the linear in temperature resistivity often extends down to low temperatures, lower than natural microscopic energy scales. We consider recently proposed deconfined critical points (or phases) in models of electrons in large dimension lattices with random nearest-neighbor exchange interactions. The criticality is in the class of Sachdev–Ye–Kitaev models, and exhibits a time reparameterization soft mode representing gravity in dual holographic theories. We compute the low temperature resistivity in a large M limit of models with SU(M) spin symmetry, and find that the dominant temperature dependence arises from this soft mode. The resistivity is linear in temperature down to zero temperature at the critical point, with a co-efficient universally proportional to the product of the residual resistivity and the co-efficient of the linear in temperature specific heat. We argue that the time reparameterization soft mode offers a promising and generic mechanism for resolving the strange metal puzzle.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Plant myo -inositol transport influences bacterial colonization phenotypes

Plant microbiomes are assembled and modified through a complex milieu of biotic and abiotic factors. Despite dynamic and fluctuating contributing variables, specific host metabolites are consistently identified as important mediators of microbial interactions. We combine information from a large-scale metatranscriptomic dataset from natural poplar trees and experimental genetic manipulation assays in seedlings of the model plant Arabidopsis thaliana to converge on a conserved role for transport of the plant metabolite myo-inositol in mediating host-microbe interactions. While microbial catabolism of this compound has been linked to increased host colonization, we identify bacterial phenotypes that occur in both catabolism-dependent and -independent manners, suggesting that myo-inositol may additionally serve as a eukaryotic-derived signaling molecule to modulate microbial activities. Our data suggest host control of this compound and resulting microbial behavior are important mechanisms at play surrounding the host metabolite myo-inositol.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Protein–Ligand Binding Free-Energy Calculations with ARROW–A Purely First-Principles Parameterized Polarizable Force Field

Protein–ligand binding free-energy calculations using molecular dynamics (MD) simulations have emerged as a powerful tool for in silico drug design. Here, we present results obtained with the ARROW force field (FF)–a multipolar polarizable and physics-based model with all parameters fitted entirely to high-level ab initio quantum mechanical (QM) calculations. ARROW has already proven its ability to determine solvation free energy of arbitrary neutral compounds with unprecedented accuracy. The ARROW FF parameterization is now extended to include coverage of all amino acids including charged groups, allowing molecular simulations of a series of protein–ligand systems and prediction of their relative binding free energies. We ensure adequate sampling by applying a novel technique that is based on coupling the Hamiltonian Replica exchange (HREX) with a conformation reservoir generated via potential softening and nonequilibrium MD. ARROW provides predictions with near chemical accuracy (mean absolute error of ~0.5 kcal/mol) for two of the three protein systems studied here (MCL1 and Thrombin). The third protein system (CDK2) reveals the difficulty in accurately describing dimer interaction energies involving polar and charged species. Overall, for all of the three protein systems studied here, ARROW FF predicts relative binding free energies of ligands with a similar accuracy level as leading nonpolarizable force fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

NaRuO2: Kitaev-Heisenberg exchange in triangular-lattice setting

Abstract Kitaev exchange, a new paradigm in quantum magnetism research, occurs for 90° metal-ligand-metal links, $${t}_{2g}^{5}$$ t 2 g 5 transition ions, and sizable spin-orbit coupling. It is being studied in honeycomb compounds but also on triangular lattices. While for the former it is known by now that the Kitaev intersite couplings are ferromagnetic, for the latter the situation is unclear. Here we pin down the exchange mechanisms and determine the effective coupling constants in the $${t}_{2g}^{5}$$ t 2 g 5 triangular-lattice material NaRuO 2 , recently found to host a quantum spin liquid ground state. We show that, compared to honeycomb compounds, the characteristic triangular-lattice cation surroundings dramatically affect exchange paths and effective coupling parameters, changing the Kitaev interactions to antiferromagnetic. Quantum chemical analysis combined with subsequent effective spin model simulations provide perspective onto the nature of the experimentally observed quantum spin liquid—it seemingly implies fairly large antiferromagnetic second-neighbor isotropic exchange, and the atypical proximity to ferromagnetic order is related to ferromagnetic nearest-neighbor Heisenberg coupling.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Magnetic states of the quasi-one-dimensional iron chalcogenide Ba 2 FeS 3

Quasi-one-dimensional iron-based ladders and chains, with the 3d iron electronic density n=6, are attracting considerable attention. Recently, a new iron chain system Ba 2 FeS 3 , also with n=6, was prepared under high-pressure and high-temperature conditions. Here the magnetic and electronic phase diagrams are theoretically studied for this quasi-one-dimensional compound. Based on first-principles calculations, a strongly anisotropic one-dimensional electronic band behavior near the Fermi level was observed. In addition, a three-orbital electronic Hubbard model for this chain was constructed. Introducing the Hubbard and Hund couplings and studying the model via the density matrix renormalization group (DMRG) method, we studied the ground-state phase diagram. A robust staggered ↑-↓-↑-↓ AFM region was unveiled in the chain direction, consistent with our density functional theory (DFT) calculations. Furthermore, at intermediate Hubbard U coupling strengths, this system was found to display an orbital selective Mott phase (OSMP) with one localized orbital and two itinerant metallic orbitals. At very large U/W (W=bandwidth), the system displays Mott insulator characteristics, with two orbitals half-filled and one doubly occupied. Our results for high pressure Ba 2 FeS 3 provide guidance to experimentalists and theorists working on this one-dimensional iron chalcogenide chain material.

1-dimensional systems↗
DOE OSTI2021

3,3’-Diindolylmethane Exhibits Significant Metabolism After Oral Dosing in Humans

3,3’-Diindolylmethane (DIM), a major phytochemical derived from ingestion of cruciferous vegetables such as Brussels sprouts, is also a dietary supplement. In preclinical models, DIM is an effective cancer chemopreventive agent and has been studied in a number of clinical trials. Previous pharmacokinetic studies in preclinical and clinical models have not reported DIM metabolites in plasma or urine following oral dosing and the pharmacological actions of DIM on target tissues is assumed to be solely via the parent compound. Seven subjects (6 males and 1 female) ranging from 26-65 years of age, on a cruciferous vegetable-restricted diet prior to and during the study, took 2 BioResponse-DIM® 150 mg capsules (45.3 mg DIM/capsule) in the evening for one week with a final dose the morning of the first blood draw. A complete time course was performed with plasma and urine collected over 48 hours and analyzed by UPLC-MS/MS. In addition to parent DIM, two mono-hydroxylated (2-ox- and 3-methylenehydroxy-DIM) and 1 dihydroxylated (3-methylenehydroxy-2-ox-DIM) metabolites, along with their sulfate and glucuronide conjugates, were present in both plasma and urine. The results reported here are indicative of significant phase 1 and phase 2 metabolism and differ from previous pharmacokinetic studies in rodents and humans which reported only parent DIM present following oral administration.

Vermillion-Maier, Monica↗
DOE OSTI2024

A Deep Multimodal Representation Learning Framework for Accurate Molecular Properties Prediction

Drug discovery is a complex and challenging process, requiring the optimization of candidate compounds to identify those with the potential to become safe and effective drugs. Predicting molecular properties is an indispensable step in the drug discovery pipeline. Traditionally, this process is costly and time-intensive, involving multiple rounds of experiments and clinical trials, rendering it impractical for every candidate compound. Deep learning techniques have emerged as a promising approach to drug discovery to reduce the cost and time required to identify novel drugs. However, prevalent research in deep learning models focused on predicting molecular properties has primarily fixated on single-modal models, which utilize a single modality of data, neglecting the potential benefits of combining different data modalities. To overcome this limitation, we introduce MRL-Mol: a deep \textbf{M}ultimodal \textbf{R}epresentation \textbf{L}earning framework for accurate \textbf{Mol}ecular properties prediction. MRL-Mol harnesses three data modalities: sequence, graph, and image, augmenting the depth of comprehension. Leveraging a large-scale unlabeled dataset~($\sim$1M unique molecules), we pretrain MRL-Mol to extract inter- and intra-modal information. Our study demonstrates the superior performance of MRL-Mol in predicting molecular properties across six benchmark datasets, including both classification and regression tasks. Notably, MRL-Mol outperforms other state-of-the-art molecular properties prediction models. These findings suggest that by combining information from multiple data modalities, MRL-Mol can comprehend molecules better than single-modal deep learning models and identify molecular properties with better accuracy.

Yang, Yuxin↗
DOE OSTI2021

A Comparison of Machine Learning Methods to Forecast Tropospheric Ozone Levels in Delhi

Ground-level ozone is a pollutant that is harmful to urban populations, particularly in developing countries where it is present in significant quantities. It greatly increases the risk of heart and lung diseases and harms agricultural crops. This study hypothesized that, as a secondary pollutant, ground-level ozone is amenable to 24 h forecasting based on measurements of weather conditions and primary pollutants such as nitrogen oxides and volatile organic compounds. We developed software to analyze hourly records of 12 air pollutants and 5 weather variables over the course of one year in Delhi, India. To determine the best predictive model, eight machine learning algorithms were tuned, trained, tested, and compared using cross-validation with hourly data for a full year. The algorithms, ranked by R2 values, were XGBoost (0.61), Random Forest (0.61), K-Nearest Neighbor Regression (0.55), Support Vector Regression (0.48), Decision Trees (0.43), AdaBoost (0.39), and linear regression (0.39). When trained by separate seasons across five years, the predictive capabilities of all models increased, with a maximum R 2 of 0.75 during winter. Bidirectional Long Short-Term Memory was the least accurate model for annual training, but had some of the best predictions for seasonal training. Out of five air quality index categories, the XGBoost model was able to predict the correct category 24 h in advance 90% of the time when trained with full-year data. Separated by season, winter is considerably more predictable (97.3%), followed by post-monsoon (92.8%), monsoon (90.3%), and summer (88.9%). These results show the importance of training machine learning methods with season-specific data sets and comparing a large number of methods for specific applications.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1983

Some results from studies on the effects of weightlessness on the growth of epiphytic orchids

Epidendrum orchids were placed in a Malakhit-2 micro-greenhouse aboard the Soyuz-36-Salyut-6 space station to test their growth under weightless conditions. Growth occurred but was less than in control plants left on Earth; cells were smaller and parenchymal development slowed in all tissues. Stems, roots, and leaves were smaller. The number of stomas on the leaves was about the same as in the controls, but, because of the smaller leaf size, there were more per unit area. A modeling experiment using a clinostat revealed a large decrease in gibberellin activity and auxin activity. It was assumed that weightlessness primarily affects gibberellin biosynthesis, inhibiting cell growth. Reestablishment of growth compound activity upon return of the plants to Earth was indicated by the fact that the orchids resumed growth thereafter.

Cherevchenko, T. M.↗
NASA NTRS1989

Cosmochemical implications of the physical processing of cometary nuclei

Comets are not necessarily pristine nebular and interstellar material, despite a common perception to that effect. Alteration processes may occur during comet formation in the outer planet region, during their dispersal to or residence within the Oort cloud, and after their return to the planetary region. Processes that may have significantly modified cometary nuclei include heating, impacts, and irradiation. Possible consequences include phase changes in ices, hydration reactions in silicates, synthesis of organic compounds, collisional disruption and re-accretion, shock and irradiation effects in minerals and ices, cosmogenic nuclide formation, redistribution or loss of volatiles, and formation of a refractory veneer. A model of cometary nuclei that emerges from these considerations provides a framework for understanding observations of comets and future samples.

Mcsween, Harry Y., Jr.↗
NASA NTRS1992

Latest developments in the display of large-scale ionospheric and thermospheric data sets

Over the past decade, data base sizes have continually increased and will continue to do so in the future. This problem of size is further compounded because the trend in present-day studies is to use data from many different locations and different instruments and then compare it with data from global scale physical models. The latter produce data bases of comparable if not even larger size. Much of the data can be viewed as 'image' time sequences and is most readily viewed on color display terminals. These data sets reside in national or owner-generated data bases linked together by computer networks. As the size increases, just moving this data around, taking 'quick-looks' at the data, or even storing it locally become severe problems compromising the scientific return from the data. Is the present-day technology with these analysis techniques being used in the best way? What are the prospects for reducing the storage and transmission size of the data sets? Examples of such problems and potential solutions are described in this paper.

Sojka, J. J.↗
NASA NTRS2010

Application of OMI Observations to a Space-Based Indicator of NOx and VOC Controls on Surface Ozone Formation

We investigated variations in the relative sensitivity of surface ozone formation in summer to precursor species concentrations of volatile organic compounds (VOCs) and nitrogen oxides (NOx) as inferred from the ratio of the tropospheric columns of formaldehyde to nitrogen dioxide (the "Ratio") from the Aura Ozone Monitoring Instrument (OMI). Our modeling study suggests that ozone formation decreases with reductions in VOCs at Ratios less than 1 and NOx at Ratios greater than 2; both NOx and VOC reductions may decrease ozone formation for Ratios between 1 and 2. Using this criteria. the OMI data indicate that ozone formation became: 1. more sensitive to NOx over most of the United States from 2005 to 2007 because of the substantial decrease in NOx emissions, primarily from stationary sources, and the concomitant decrease in the tropospheric column of NO2. and 2. more sensitive to NOx with increasing temperature, in part because emissions of highly reactive, biogenic isoprene increase with temperature, thus increasing the total VOC reactivity. In cities with relatively low isoprene emissions (e.g .. Chicago). the data clearly indicate that ozone formation became more sensitive to NOx from 2005 to 2007. In cities with relatively high isoprene emissions (e.g ., Atlanta), we found that the increase in the Ratio due to decreasing NOx emissions was not obvious as this signal was convolved with variations in the Ratio associated with the temperature dependence of isoprene emissions and, consequently, the formaldehyde concentration.

Duncan, Bryan N.↗