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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Accurate prediction of global-density-dependent range-separation parameters based on machine learning

In this work, we develop an accurate and efficient XGBoost machine learning model for predicting the global-density-dependent range-separation parameter, ωGDD, for long-range corrected functional (LRC)-ωPBE. This ωGDDML model has been built using a wide range of systems (11 466 complexes, ten different elements, and up to 139 heavy atoms) with fingerprints for the local atomic environment and histograms of distances for the long-range atomic correlation for mapping the quantum mechanical range-separation values. The promising performance on the testing set with 7046 complexes shows a mean absolute error of 0.001 117 a0−1 and only five systems (0.07%) with an absolute error larger than 0.01 a0−1, which indicates the good transferability of our ωGDDML model. In addition, the only required input to obtain ωGDDML is the Cartesian coordinates without electronic structure calculations, thereby enabling rapid predictions. LRC-ωPBE(ωGDDML) is used to predict polarizabilities for a series of oligomers, where polarizabilities are sensitive to the asymptotic density decay and are crucial in a variety of applications, including the calculations of dispersion corrections and refractive index, and surpasses the performance of all other popular density functionals except for the non-tuned LRC-ωPBE. Finally, LRC-ωPBE (ωGDDML) combined with (extended) symmetry-adapted perturbation theory is used in calculating noncovalent interactions to further show that the traditional ab initio system-specific tuning procedure can be bypassed. The present study not only provides an accurate and efficient way to determine the range-separation parameter for LRC-ωPBE but also shows the synergistic benefits of fusing the power of physically inspired density functional LRC-ωPBE and the data-driven ωGDDML model.

Chemistry↗
DOE OSTI2026

Maximizing efficiency of dataset compression for machine learning potentials with information theory

Machine learning interatomic potentials (MLIPs) balance high accuracy and lower costs compared to density functional theory calculations, but their performance often depends on the size and diversity of training datasets. Large datasets improve model accuracy and generalization but are computationally expensive to produce and train on, while smaller datasets risk discarding rare but important atomic environments and compromising MLIP accuracy/reliability. Here, we develop an information-theoretical framework to quantify the efficiency of dataset compression methods and propose an algorithm that maximizes this efficiency. By framing atomistic dataset compression as an instance of the minimum set cover (MSC) problem over atom-centered environments, our method identifies the smallest subset of structures that contains as much information as possible from the original dataset while pruning redundant information. The approach is extensively demonstrated on the GAP-20 and TM23 datasets and validated on 64 varied datasets from the ColabFit repository. Across all cases, MSC consistently retains outliers, preserves dataset diversity, and reproduces the long-tail distributions of forces even at high compression rates, outperforming other subsampling methods. Furthermore, MLIPs trained on MSC-compressed datasets exhibit reduced error for out-of-distribution data even in low-data regimes. We explain these results using an outlier analysis and show that such quantitative conclusions could not be achieved with conventional dimensionality reduction methods. The algorithm is implemented in the open-source QUESTS package and can be used for several tasks in atomistic modeling, from data subsampling, outlier detection, and training improved MLIPs at a lower cost.

36 MATERIALS SCIENCE↗
NASA NTRS1989

Workshop summary. Biomedical and Space-Related Research with Heavy Ions at the BEVALAC

The authors provide an overview of papers presented at a workshop on Biomedical and Space-Related Research with Heavy Ions at the BEVALAC at Lawrence Berkeley Laboratory. Goals of the meeting were to determine the critical experiments using heavy ions as probes in radiation physics, radiation chemistry, macromolecular and cellular biology, evolution science, basic neurophysiology, and medical therapies; how beam lines and facilities at Lawrence Berkeley Laboratory can be improved for these experiments; and implications in priorities and funding for national policy. Workshop topics included physics and facilities, cellular and molecular biology, tissue radiobiology, and the future of heavy ion research.

NASA Discipline Radiation Health↗
DOE OSTI2022

Plasma thermal-chemical instability of low-temperature dimethyl ether oxidation in a nanosecond-pulsed dielectric barrier discharge

Plasma stability in reactive mixtures is critical for various applications from plasma-assisted combustion to gas conversion. To generate stable and uniform plasmas and control the transition towards filamentation, the underlying physics and chemistry need a further look. Here, this work investigates the plasma thermal-chemical instability triggered by dimethyl-ether (DME) low-temperature oxidation in a repetitive nanosecond pulsed dielectric barrier discharge. First, a plasma-combustion kinetic mechanism of DME/air is developed and validated using temperature and ignition delay time measurements in quasi-uniform plasmas. Then the multi-stage dynamics of thermal-chemical instability is experimentally explored: the DME/air discharge was initially uniform, then contracted to filaments, and finally became uniform again before ignition. By performing chemistry modeling and analyzing the local thermal balance, it is found that such nonlinear development of the thermal-chemical instability is controlled by the competition between plasma-enhanced low-temperature heat release and the increasing thermal diffusion at higher temperature. Further thermal-chemical mode analysis identifies the chemical origin of this instability as DME low-temperature chemistry. This work connects experiment measurements with theoretical analysis of plasma thermal-chemical instability and sheds light on future chemical control of the plasma uniformity.

repetitive nanosecond pulses↗
DOE OSTI2021

Demonstration of neutron radiation-induced nucleation of supercooled water

In this study, we present direct evidence for neutrons causing nucleation of supercooled water. Highly purified water (20 nm filtration) is cooled to well below freezing (as low as −20 °C) with a radioactive calibration source of neutrons/gamma-rays either present or removed during each of many control cooling runs for the same volume of water. When it is primarily neutrons irradiating the sample bulk, the non-equilibrium freezing point (also known as the “supercooling point”) is, on average, +0.7 °C warmer than the control equivalent, with a statistical significance of greater than 5 Sigma, with systematic uncertainty included. This effect is not observed with water in the presence of gamma-rays instead of neutrons. While these neutrons should have theoretically had sufficient energy to mount the energy barrier, corroborating our results, their raising of supercooling temperature has never been reported experimentally to the best of our knowledge. The potential to use deeply supercooled solutions, not only water, as metastable detectors for radiation and perhaps dark matter or neutrino physics presents now a new avenue for exploration.

Szydagis, Matthew↗
DOE OSTI2024

Insights into the structure and dynamics of K + ions at the muscovite–water interface from machine learning potential simulations

The surfaces of many minerals are covered by naturally occurring cations that become partially hydrated and can be replaced by hydronium or other cations when the surface is exposed to water or an aqueous solution. These ion exchange processes are relevant to various chemical and transport phenomena, yet elucidating their microscopic details is challenging for both experiments and simulations. Here, in this work, we make a first step in this direction by investigating the behavior of the native K + ions at the interface between neat water and the muscovite mica (001) surface with ab-initio -based machine learning molecular dynamics and enhanced sampling simulations. Our results show that the desorption of the surface K + ions in pure ion-free water has a significant free energy barrier irrespective of their local surface arrangement. In contrast, facile K + diffusion between mica’s ditrigonal cavities characterized by different Al/Si orderings is observed. This behavior suggests that the K + ions may favor a dynamic disordered surface arrangement rather than complete desorption when exposed to deionized water.

Ab-initio molecular dynamics↗
NASA NTRS1999

Ethnic Differences in Physical Fitness, Blood Pressure and Blood Chemistry in Women (AGES 20-63)

This study examined the role of ethnicity on the aerobic fitness, blood pressure, and selected blood chemistry values of women. One hundred twenty-four females (mean age 41.37 +/- 9.0) were medically Examined at the NASA/Johnson Space Center occupational health clinic. Ethnic groups consisted of 23 Black (B), 18 Hispanic (H) and 83 Non-minority (NM). Each woman had a maximum Bruce treadmill stress test (RER greater than or = 1.1) and a negative ECG. Indirect calorimetry, skinfolds, self-report physical activity (NASA activity scale), seated blood pressure, and blood chemistry panel determined VO2max, percent fat, level of physical activity, blood pressure and blood chemistry values. ANOVA revealed that the groups did not differ (p greater than 0.05) in age, VO2 max, weight, percent fat, level of physical activity, total cholesterol, or HDL-C. However, significant differences (p greater than 0.05) were noted in BMI, diastolic blood pressure, and blood chemistries. BMI was 3.17 higher in H than in NM; resting diastolic pressures were 5.69 and 8.05 mmHg. lower in NM and H than in B; triglycerides were 48.07 and 37.21 mg/dl higher in H than in B and NM; hemoglobin was .814 gm/dl higher in NM than B; fasting blood sugar was 15.41 mg/dl higher in H than NM; The results of this study showed that ethnic groups differed in blood pressure and blood chemistry values but not aerobic fitness or physical activity. There was an ethnic difference in BMI but not percent fat.

Ayers, G. W.↗
DOE OSTI2026

Connecting collisional and photofragmentation resonances in the ungerade symmetry states of H 2

A recently developed energy-dependent frame transformation theory that incorporates both ionisation and dissociation channels of the H 2 molecule, is extended to treat the ungerade states that occur both in dissociative recombination and as the final state in ground state photoabsorption. The theoretical treatment includes the rotational degrees of freedom and is benchmarked against a two-dimensional model that can be solved with high accuracy and also compared with photoabsorption experiments. Analysis of the resulting spectra demonstrates how the same resonances appear in very different observables, often with quite different line shapes.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Competing ionization and dissociation: Extension of the energy-dependent frame transformation to the gerade symmetry of H 2

This article solves two major tasks that frequently arise in the theory of electron collisions with a target molecular cation. First, it extends the energy-dependent frame transformation (EDFT) treatment, which is needed to map fixed-nuclei electron-molecule scattering matrices into an energy-dependent laboratory-frame scattering matrix with vibrational channel indices. The EDFT mapping can now be carried out even when the target molecule possesses multiple low-energy potential curves, significantly transcending previous applications. Second, it implements a method to extract the rest of the full laboratory-frame scattering matrix, i.e., the columns and rows describing input and/or output dissociation channels. The treatment is benchmarked in this article against the essentially exact solution of a refined two-dimensional model of the singlet gerade Σ symmetry of H 2 . Our tests demonstrate that the theory accurately maps fixed-nuclei scattering information, of the type provided by existing electron-molecule computer codes, into a laboratory-frame scattering matrix that includes both ionization and dissociation. Furthermore, this treatment can provide a general framework applicable to a broad class of electron collision processes involving diatomic target ions, suitable for an accurate description of challenging processes such as dissociative recombination.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Flow and extraction of energy and charge carriers in hybrid plasmonic nanostructures

Strong interactions of electromagnetic fields with plasmonic nanomaterials have been exploited in various applications. These applications have centred on plasmon-enhanced scattering rates in nearby molecules or plasmon-induced heating. A question that has emerged recently is whether it is possible to use plasmonic nanostructures in a range of hot electron (hole) applications, including photocatalysis, photovoltaics and photodetection. These applications require coupling of a plasmonic component, which amplifies the interaction of light with the material, to an attached non-plasmonic component that extracts this energy in the form of electronic excitations to perform a function. Here, in this Perspective, we discuss recent work in the emerging field of hybrid plasmonics. We focus on fundamental questions related to the nanoscopic flow of energy and excited charge carriers in these multicomponent materials. We also address critical misconceptions, challenges and opportunities that require more attention.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The Nuclei Of Atoms In The Third Period Of The Periodic Table Of Elements (Monograph No.3)

Nuclei are shown for the elements sodium, magnesium, aluminum, silicon, phosphorus, sulphur, chlorine, and argon. Individual nucleons are not identified as protons or neutrons. Nucleons are illustrated using a sphere schematic of the wave functions of singular, linear, and tetrahedral nucleon arrangements. Nucleon arrangements in protium, deuteron, triton, helion, and alpha are shown as building blocks in the nuclei of elements in the third period of the periodic table of elements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1987

Cometary MHD and chemistry

An MHD and chemical comet-coma model was developed, applying the computer program of Huebner (1985) for the detailed chemical evolution of a spherically expanding coma and the program of Schmidt and Wegman (1982) and Wegman (1987) for the MHD flow of plasma and magnetic field in a comet to the Giotto-mission data on the ion abundances measured by the HIS ion mass spectrometer. The physics and chemistry of the coma are modeled in great detail, including photoprocesses, gas-phase chemical kinetics, energy balance with a separate electron temperature, multifluid hydrodynamics with a transition to free molecular flow, fast-streaming atomic and molecular hydrogen, counter and cross streaming of the ionized species relative to the neutral species in the coma-solar wind interaction region with momentum exchange by elastic collisions, mass-loading through ion pick-up, and Lorentz forces of the advected magnetic field. The results, both inside and outside of the contact surface, are discussed and compared with the relevant HIS ion mass spectra.

Wegmann, R.↗
DOE OSTI2022

Stability Analysis of Substituted Cobaltocenium [Bis(cyclopentadienyl)cobalt(III)] Employing Chemistry-Informed Neural Networks

Cobaltocenium derivatives are promising components of the anion exchange membranes due to their excellent thermal and alkaline stability under the operating conditions of a fuel cell. Here we present an efficient modeling approach of assessing the chemical stability of substituted cobaltocenium CoCp 2 + based on the computed electronic structure enhanced by machine learning techniques. Within the aqueous environment, the positive charge of the metal cation is balanced by the hydroxide anion through formation of the CoCp 2 + OH¯ complexes, whose dissociation is studied within the implicit solvent employing density functional theory. The data set of about 118 species based on 42 substituent groups characterized by a range of electron- donating (ED) and electron-withdrawing (EW) properties is constructed and analyzed. Given 12 carefully chosen chemistry-informed descriptors of the complexes and relevant fragments, the stability of the complexes is found to strongly correlate with the energies of the highest occupied and lowest unoccupied molecular orbitals, modulated by a switching function of the Hirshfeld charge. The latter is used as a measure of the electron withdrawing-donating character of the substituents. Based on this observation from the conventional regression analysis, two fully connected, feed-forward neural network (FNN) models with different unit structures, called the chemistry-informed (CINN) and the quadratic (QNN) neural networks, are developed. Both models predict the bond dissociation energies of the cobaltocenium complexes with mean relative errors less than 5.40% and average absolute errors less than 0.94 kcal/mol. The results show the potential of QNN to efficiently capture more complex relationships. Here, the concept of incorporating the domain (chemical) knowledge/insight into the neural network structure paves the way to applications of machine learning techniques with small data sets, ultimately leading to better predictive models compared to the conventional regression analysis.

36 MATERIALS SCIENCE↗
NASA NTRS1984

Importance of formaldehyde in cloud chemistry

A physical-chemical model which is an extension of that of Hong and Carmichael (1983) is used to investigate the role of formaldehyde in cloud chemistry. This model takes into account the mass transfer of SO2, O3, NH3, HNO3, H2O2, CO2, HCl, HCHO, O2, OH and HO2 into cloud droplets and their subsequent chemical reactions. The model is used to assess the importance of S(IV)-HCHO adduct formation, the reduction of H2O2 by HCHO, HCHO-free radical interactions, and the formation of HCOOH in the presence of HCHO in cloud droplets. Illustrative calculations indicate that the presence of HCHO inhibits sulfate production rate in cloud droplets. The direct inhibition of sulfate production rate in cloudwater due to nucleophilic addition of HSO3(-) to HCHO(aq) to form hydroxymethanesulfonate is generally low for concentrations of HCHO typical of ambient air. However, inhibition of sulfate production due to formaldehyde-free radical interactions in solution can be important. These formaldehyde-free radical reactions can also generate appreciable quantities of formic acid.

Adewuyi, Y. G.↗
NASA NTRS1981

Spacecraft Dynamics as Related to Laboratory Experiments in Space

Proceedings are presented of a conference sponsored by the Physics and Chemistry Experiments in Space Working Group to discuss the scientific and engineering aspects involved in the design and performance of reduced to zero gravity experiments affected by spacecraft environments and dynamics. The dynamics of drops, geophysical fluids, and superfluid helium are considered as well as two phase flow, combustion, and heat transfer. Interactions between spacecraft motions and the atmospheric cloud physics laboratory experiments are also examined.

G. H. Fichtl↗