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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Interplanetary Lyman-alpha observations with UVS on Voyager - Data, first analysis, implications for the ionization lifetime

A fraction of the measurements of the interplanetary Lyman-alpha background collected by the Ultraviolet Spectrometer during the cruise of Voyager 1 and 2 between 1977 and 1983 is presented and compared with results from current models of the interaction between the sun and the neutral interstellar gas. An analysis of two sets of data indicates that the same H atom lifetime cannot fit all the data. The actual ionization rate is inferred from the intensity gradient in the maximum emissivity region observed from a sidewind Voyager position at 6 AU, yielding a lifetime of about 1 exp 6 s at 1 AU, whereas the upwind/downwind intensity ratio in the inner solar system favors 2 x 10 exp 6 s, as measured by Voyager, Prognoz, and Pioneer Venus instruments. It is proposed that there is an excess of Ly-alpha emission in the downwind region which forces the model toward excessively high values of the lifetime. Possible explanations are discussed, like incorrect modeling or an additional source of H atoms.

Lallement, R.↗
NASA NTRS1983

Oxygen atom reaction with Shuttle materials at orbital altitudes - Data and experiment status

Significant surface characteristics changes have been noticed on materials that were exposed in the payload bay of the Space Shuttle Orbiter on the first four flights. The most notable change was mass loss of Kapton film used as a component of thermal blankets. This film exhibited as much as 35 percent mass loss on STS-3 and loss of material was noticed on all flights. Other changes consist of rapid aging of paints and oxidation of Torlon surfaces. A mechanism has been proposed for the effects described, which involves the interaction of these organic materials with atomic oxygen available at low earth orbital altitudes. Evidence derived from measurements made on Shuttle materials that supports this mechanism will be presented. Experiments planned for near-term Shuttle flights are being developed to obtain quantitative data on reaction rates.

Leger, L.↗
DOE OSTI2025

High Mobility and Electrostatics in GeSn Quantum Wells With SiGeSn Barriers

GeSn is an emerging material with potential applications in next‐generation integrated optoelectronics and quantum information processing. While GeSn/SiGeSn quantum wells exhibit promising optical properties, their electrical transport characteristics and governing electrostatics in gated structures remain unexplored. Heterostructure field‐effect transistors are fabricated using GeSn/SiGeSn quantum wells and electronic transport properties of 2D holes are characterized. At 2 K, heterostructure field‐effect transistors with well/barrier compositions of Ge 0.945 Sn 0.055 /Si 0.03 Ge 0.93 Sn 0.04 and Ge 0.9 Sn 0.1 /Si 0.017 Ge 0.927 Sn 0.056 , show peak mobilities of 9000 and 19 000 cm 2 /Vs, respectively, the latter setting a record for the highest mobility reported for GeSn quantum wells with a Sn concentration around 6 % or greater. Remarkably, at low carrier densities, devices with a SiGeSn barrier exhibit mobilities several times higher than previously reported for GeSn quantum wells with a Ge barrier. This higher mobility contrasts with the expectation that alloy scattering from the barrier would reduce carrier mobility. Two mechanisms based on atom probe tomography data analyses are proposed: i) unintentionally improved SiGeSn/GeSn interface and/or ii) reduced alloy scattering from short‐range order. Significant current–voltage hysteresis is observed, with the effective threshold gate voltage shifting by more than 5 V, attributed to non‐equilibrium trapped charge at various interfaces within the SiGeSn heterostructure.

GeSn↗
DOE OSTI2023

Concepts of association between cancer and ionising radiation: accounting for specific biological mechanisms

The probability that an observed cancer was caused by radiation exposure is usually estimated using cancer rates and risk models from radioepidemiological cohorts and is called assigned share (AS). This definition implicitly assumes that an ongoing carcinogenic process is unaffected by the studied radiation exposure. However, there is strong evidence that radiation can also accelerate an existing clonal development towards cancer. In this work, we define different association measures that an observed cancer was newly induced, accelerated, or retarded. The measures were quantified exemplarily by Monte Carlo simulations that track the development of individual cells. Three biologically based two-stage clonal expansion (TSCE) models were applied. In the first model, radiation initiates cancer development, while in the other two, radiation has a promoting effect, i.e. radiation accelerates the clonal expansion of pre-cancerous cells. The parameters of the TSCE models were derived from breast cancer data from the atomic bomb survivors of Hiroshima and Nagasaki. For exposure at age 30, all three models resulted in similar estimates of AS at age 60. For the initiation model, estimates of association were nearly identical to AS. However, for the promotion models, the cancerous clonal development was frequently accelerated towards younger ages, resulting in associations substantially higher than AS. This work shows that the association between a given cancer and exposure in an affected person depends on the underlying biological mechanism and can be substantially larger than the AS derived from classic radioepidemiology.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2023

A statistical mechanics framework for polymer chain scission, based on the concepts of distorted bond potential and asymptotic matching

To design increasingly tough, resilient, and fatigue-resistant elastomers and hydrogels, the relationship between controllable network parameters at the molecular level (bond type, non-uniform chain length, entanglement density, etc.) to macroscopic quantities that govern damage and failure must be established. Many of the most successful constitutive models for elastomers have been rooted in statistical mechanical treatments of polymer chains. Typically, such constitutive models have used variants of the freely jointed chain model with rigid links. However, since the free energy state of a polymer chain is dominated by enthalpic bond distortion effects as the chain approaches its rupture point, bond extensibility ought to be accounted for if the model is intended to capture chain rupture. To that end, a new bond potential is supplemented to the freely jointed chain model (as derived in the u FJC framework of Buche and Silberstein (2021) and Buche et al. (2022)), which we have extended to yield a tractable, closed-form model of single chain behavior that should be amenable to continuum-level constitutive model development. Inspired by the asymptotically matched u FJC model response in both the low/intermediate chain force and high chain force regimes, a simple, quasi-polynomial bond potential energy function is derived. This bond potential exhibits harmonic behavior near the equilibrium state and anharmonic behavior for large bond stretches tending to a characteristic energy plateau (akin to the Lennard-Jones and Morse bond potentials). Using this bond potential, approximate yet highly-accurate analytical functions for bond stretch and chain force dependent upon chain stretch are established. Then, using this polymer chain model, a stochastic thermal fluctuation-driven chain rupture framework is developed. This framework is based upon a force-modified tilted bond potential that accounts for distortional bond potential energy, allowing for the derivation and subsequent calculation of the dissipated chain scission energy. Here, the cases of rate-dependent and rate-independent scission are accounted for throughout the rupture framework. The impact of Kuhn segment number on chain rupture behavior is also investigated. The model is fit to single chain mechanical response data collected from atomic force microscopy tensile tests for validation and to glean deeper insight into the molecular physics taking place. Due to their analytical nature, this polymer chain model and the associated rupture framework can in the future be implemented in finite element models accounting for fracture and fatigue in polydisperse elastomer networks.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Integrating Machine Learning Potential and X-ray Absorption Spectroscopy for Predicting the Chemical Speciation of Disordered Carbon Nitrides

Precise determination of atomic structural information in functional materials holds transformative potential and broad implications for emerging technologies. Spectroscopic techniques, such as X-ray absorption near-edge structure (XANES), have been widely used for material characterization; however, extracting chemical information from experimental probes remains a significant challenge, particularly for disordered materials. We present an integrated approach that combines atomic simulations, data-driven techniques, and experimental measurements to investigate chemical speciation of amorphous carbon nitride systems as a case study. Here, we discuss the development of machine learning potentials that can efficiently explore the vast configuration space of amorphous carbon nitrides. By employing statistical methods, this structural database enables the elucidation of the most representative local structures and how they evolve with chemical compositions and density. Density functional theory simulations are used to establish a correlation between the local structure and spectroscopic signatures, which then serve as the basis for interpreting and extracting chemical content from experimental data. Although our framework is specifically demonstrated for XANES and carbon nitrides, the approach described herein is readily adaptable as applied to other experimental characterization probes and materials classes.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An automatically curated first-principles database of ferroelectrics

Ferroelectric materials have technological applications in information storage and electronic devices. The ferroelectric polar phase can be controlled with external fields, chemical substitution and size-effects in bulk and ultrathin film form, providing a platform for future technologies and for exploratory research. In this work, we integrate spin-polarized density functional theory (DFT) calculations, crystal structure databases, symmetry tools, workflow software, and a custom analysis toolkit to build a library of known, previously-proposed, and newly-proposed ferroelectric materials. With our automated workflow, we screen over 67,000 candidate materials from the Materials Project database to generate a dataset of 255 ferroelectric candidates, and propose 126 new ferroelectric materials. We benchmark our results against experimental data and previous first-principles results. The data provided includes atomic structures, output files, and DFT values of band gaps, energies, and the spontaneous polarization for each ferroelectric candidate. Finally, we contribute our workflow and analysis code to the open-source python packages atomate and pymatgen so others can conduct analogous symmetry driven searches for ferroelectrics and related phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Transformation of atomically dispersed platinum in SAPO-37 into platinum clusters: catalyst for ethylene hydrogenation

Atomically dispersed supported platinum catalysts were synthesized by the reaction of Pt(acac) 2 (acac = acetylacetonato) with the silicoaluminophosphate molecular sieve SAPO-37, with infrared spectra showing that the reaction involved SAPO OH groups. Extended X-ray absorption fine structure (EXAFS) spectra show that, after heating in air to 623 K, each platinum atom on average was bonded to approximately two oxygen atoms of the SAPO support, with no evidence of platinum clusters. X-ray absorption near edge spectra (XANES) indicate a platinum formal oxidation state of approximately +2. Here, these supported mononuclear species lacked catalytic activity for ethylene hydrogenation at 1 bar and room temperature, but activity arose during catalysis in a once-through flow reactor/X-ray absorption spectroscopy cell, as the XANES white line intensity decreased, indicating reduction of the platinum, and the EXAFS-determined Pt–Pt coordination number (CN) increased from essentially zero to 2.7 ± 0.5 after 2 h, indicating the formation of platinum clusters of only a few atoms each. The data indicate the almost instantaneous formation of the clusters and identify them as the catalytically active species. Subsequent exposure of the catalyst to ethylene as in situ EXAFS and XANES data were recorded led to a decrease in the Pt–Pt coordination number to 1.6 ± 0.3 and an increase in the white line intensity, indicating partial oxidative fragmentation of the clusters by ethylene. Platinum clusters in SAPO-37 formed in separate experiments by exposure to H 2 prior to catalysis were also catalytically active for ethylene hydrogenation. Here, the data thus show how to dial in the catalytic activity by forming platinum clusters by exposure of mononuclear platinum to H 2 and how to dial back the activity by oxidative fragmentation of the clusters by reaction with ethylene, all under mild conditions; the ethylene : H 2 ratio of the reactant gas determines the average platinum nuclearity and thus the catalytic activity.

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

Effects of cation stoichiometry on surface morphology and crystallinity of ZnGeN 2 films grown on GaN by metalorganic chemical vapor deposition

ZnGeN 2 films were grown on GaN-on-sapphire templates via metalorganic chemical vapor deposition. Energy dispersive X-ray spectroscopy was used to estimate the Zn/(Zn+Ge) composition ratio in the films. This ratio decreased with increase in growth temperature but increased with increase in total reactor pressure or Zn/Ge precursor flow rate ratio. Systematic mapping of these key growth parameters has allowed us to identify the growth window to achieve ZnGeN 2 with stoichiometric cation composition. Compositional and statistical analyses performed on data acquired from atom probe tomography provided insight into the local compositional homogeneity. The cations Zn and Ge did not demonstrate segregation or clustering at the sub-nanometer level. Based on X-ray diffraction 2θ-ω scan profiles and transmission electron microscope nano-diffraction patterns, the films with near-stoichiometric cation ratios were single crystalline with planar surfaces, whereas zinc-rich or zinc-poor films were polycrystalline with nonplanar surfaces. The growth direction of the single crystalline ZnGeN 2 films on GaN templates was along the c-axis. Room temperature Raman spectra showed features associated with the phonon density of states, indicating the presence of cation disorder in the lattice. A cathodoluminescence peak associated with transitions involving deep level defects was observed around 640 nm. The intensity of this peak increased by almost 2.5 times as the temperature was reduced to 77 K from room temperature. A similar peak was observed in photoluminescence spectra collected at 80 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Machine learning accelerated turbulence modeling of transient flashing jets

We report modeling the sudden depressurization of superheated liquids through nozzles is a challenge because the pressure drop causes rapid flash boiling of the liquid. The resulting jet usually demonstrates a wide range of structures, including ligaments and droplets, due to both mechanical and thermodynamic effects. As the simulation comprises increasingly numerous phenomena, the computational cost begins to increase. One way to moderate the additional cost is to use machine learning surrogacy for specific elements of the calculation. This study presents a machine learning-assisted computational fluid dynamics approach for simulating the atomization of flashing liquids accounting for distinct stages, from primary atomization to secondary breakup to small droplets using the Σ - Y model coupled with the homogeneous relaxation model. Notably, the models for thermodynamic non-equilibrium (HRM) and Σ - Y are coupled, for the first time, with a deep neural network that simulates the turbulence quantities, which are then used in the prediction of superheated liquid jet atomization. The data-driven component of this method is used for turbulence modeling, avoiding the solution of the two-equation turbulence model typically used for Reynolds-averaged Navier-Stokes simulations for these problems. Both the accuracy and speed of the hybrid approach are evaluated, demonstrating adequate accuracy and at least 25% faster computational fluid dynamics simulations than the traditional approach. This acceleration suggests that perhaps additional components of the calculation could be replaced for even further benefit. Published under an exclusive license by AIP Publishing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Mic-hackathon 2024: hackathon on machine learning for electron and scanning probe microscopy

Microscopy is one of the primary sources of information on materials structure and functionality at the nanometer and atomic scales. The data generated through microscopy is often contained in well-structured datasets, enriched with extensive metadata and sample histories, although not always with the same level of detail or storage format. The broad incorporation of data management plans by major funding agencies ensures the preservation and accessibility of this data. However, deriving insights from these rich datasets remains challenging due to the lack of established code ecosystems, standardized benchmarks, and integration strategies. Correspondingly, the efficiency of data usage is very low, and time expenditures at the analysis stage are enormous. In addition to post-acquisition data analysis, the emergence of application programming interfaces by major microscope manufacturers now creates opportunities for real-time ML-based data analytics to enable automated decision making, and particularly ML-agent controlled real-time microscope operation. Despite these opportunities, there is a significant gap in integrating the ML community with the broader microscopy community, limiting the value that these methods bring to physics and materials discovery and materials optimization. Hackathons address these challenges by fostering collaboration between ML experts and microscopy professionals, encouraging the development of innovative solutions that leverage ML for microscopy and preparing the workforce of the future both for microscopy-intensive domains areas, instrument manufacturers, and ML scientists interested in real world applications for fundamental research, materials optimization, and manufacturing. The hackathon generated benchmark datasets and digital twins of microscopes that further contribute to the development of the field and establish data analysis ecosystems. All the codes can be found at GitHub(https://github.com/KalininGroup/Mic-hackathon-2024-codes-publication/tree/1.0.0.1) and Zenodo (https://zenodo.org/records/15579940).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Crystal structure of an Escherichia coli Hfq Core (residues 2–69)–DNA complex reveals multifunctional nucleic acid binding sites

Hfq regulates bacterial gene expression post-transcriptionally by binding small RNAs and their target mRNAs, facilitating sRNA-mRNA annealing, typically resulting in translation inhibition and RNA turnover. Hfq is also found in the nucleoid and binds double-stranded (ds) DNA with a slight preference for A-tracts. Here, we present the crystal structure of the Escherichia coli Hfq Core bound to a 30 bp DNA, containing three 6 bp A-tracts. Although previously postulated to bind to the ‘distal’ face, three statistically disordered double stranded DNA molecules bind across the proximal face of the Hfq hexamer as parallel, straight rods with B-DNA like conformational properties. One DNA duplex spans the diameter of the hexamer and passes over the uridine-binding proximal-face pore, whereas the remaining DNA duplexes interact with the rims and serve as bridges between adjacent hexamers. Binding is sequence-independent with residues N13, R16, R17 and Q41 interacting exclusively with the DNA backbone. Atomic force microscopy data support the sequence-independent nature of the Hfq-DNA interaction and a role for Hfq in DNA compaction and nucleoid architecture. Our structure and nucleic acid-binding studies also provide insight into the mechanism of sequence-independent binding of Hfq to dsRNA stems, a function that is critical for proper riboregulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Fayda

The Fayda application developed as a part of the Reaction Roulette m/q LDRD project (76006) primarily exists as a data visualization, analysis and predictive platform for data collected using atomic tandem inductively coupled plasma mass spectrometry (ICP-MS/MS)

Harouaka, Khadouja↗
DOE OSTI2020

Metalorganic chemical vapor deposition of ZnGeN 2 films on GaN: effects of cation stoichiometry on surface morphology and crystallinity

Novel optoelectronic device designs based on the heterostructures of III-N and II-IV-N 2 are promising to advance device performance significantly. For example, by utilizing InGaN-ZnGeN 2 quantum well (QW) structures instead of pure InGaN, the band structure engineering in the QW active region can lead to improved electron-hole wavefunction overlap, and thus enhance the radiative efficiency for photon generation. These novel heterostructures have great potential to address the current challenge of low quantum efficiency in InGaN QW based light emitting diodes emitting in green and beyond. The materials development of ZnGeN 2 is still at an early stage as compared to the much matured GaN material system. In an ideal octet rule preserving ordered structure of ZnGeN 2 , every N atom is coordinated by exactly two Zn and two Ge atoms. However, local violation of octet rule can be caused by non-ideal coordination of N by the cations. The disordered structure is thermodynamically less favorable but can still be achieved, for example, in kinetics-limited growth regime. The ordered ZnGeN 2 has a bandgap very close to that of GaN (~3.4 eV) and a lattice mismatch of <0.1% with GaN. Interestingly, the valence band of ZnGeN 2 has been predicted to be ~1 eV above that of GaN, which has inspired novel designs for high efficiency light emitters. In this work, we investigated the metalorganic chemical vapor deposition (MOCVD) of ZnGeN 2 films on GaN/c-sapphire templates. Diethylzinc (DEZn), germane (GeH4) and ammonia were used as the precursors for Zn, Ge and N, respectively. A systematic study was conducted to investigate the cation stoichiometry as a function of growth temperature (TG), total reactor pressure (P) and DEZn/GeH 4 molar flow rate ratio (RII/IV). Under the investigated growth window, the Zn/(Zn+Ge) composition in the films, determined from energy dispersive X-ray spectroscopy, decreased monotonically with increase in TG but increased with increase in P and RII/IV. Atom probe tomography data did not indicate the presence of any secondary phases such as Zn 3 N 2 or Ge 3 N 4 . The surface morphology and crystallinity of the grown films had strong correlation with the Zn/(Zn+Ge) composition. The scanning electron microscopy images showed that the near-stoichiometric films have planar surfaces whereas Zn-rich films had crystallites on their surface and the Zn-poor films had faceted surface. Scanning transmission electron microscopy (STEM) imaging revealed that the Zn-rich and Zn-poor films have columnar and filament-like morphology, respectively, whereas the near-stoichiometric films have continuous film-like cross-sectional morphology. TEM nano-diffraction patterns as well as X-ray diffraction 2θ-ω scan profiles indicate that the near stoichiometric films are single crystalline. Nano-diffraction pattern of the stoichiometric films resembled that of a disordered ZnGeN 2 structure. Room temperature Raman spectra of near-stoichiometric films showed only the phonon density of states like features of a cation disordered ZnGeN 2 . Cathodoluminescence and photoluminescence spectra measured at different temperatures had similar features with peak emission wavelength at ~ 2 eV. In conclusion, the stoichiometry of ZnGeN 2 films can be widely tuned by tuning the MOCVD growth parameters. The surface morphology and the crystallinity of the films were found to have strong correlation with the Zn/(Zn+Ge) composition. The stoichiometric ZnGeN 2 films grown on GaN were demonstrated with uniform surface morphology and high crystalline quality. The results from this work will provide pathway to implement ZnGeN 2 in device structures.

Karim, Md Rezaul↗
DOE OSTI2022

Step Catalysis to Synthesize Fossil-Free Ammonia at Atmospheric Pressure (Final Technical Report)

Affordable fossil-free ammonia synthesis will enable high-yield sustainable crop production for a growing world population while preserving the planet and making the best use of water and land. Simple technology amenable to intermittent operation using renewable energy will be made available through step catalysis activating dinitrogen at atmospheric pressure by nitride formation. Project objectives: (1) At the single particle level, quantify and analyze N2 activation by doped or alloyed manganese macroscopic- and nano particles at atmospheric pressure, (2) Quantify and analyze ammonia synthesis from doped or alloyed metal nitride particles when contacting them with hydrogen at atmospheric pressure, and (3) Integrate experimental data and atomic-level computational models to predict the behavior of metal alloys in nitrogen activation and subsequent ammonia synthesis.

10 SYNTHETIC FUELS↗
NASA NTRS1975

Interpretation of the X-ray spectra of solar active regions

This paper presents a review of recent analytical studies of the coronal X-ray spectrum below 25 A. The techniques used to compute the theoretical coronal spectrum, and the currently available atomic rate constant data are reviewed first. Spectroscopic techniques which have been proposed for the determination of coronal temperature and density structure, and the results derived from their application to coronal spectra are also reviewed. A number of coronal models based on X-ray observations have been developed recently, and the coronal temperature structure and composition predicted by these models is discussed, and compared with models of the corona and transition region derived from studies of the solar EUV spectrum.

Walker, A. B. C., Jr.↗
NASA NTRS1980

Chlorine chemistry in diffuse interstellar clouds

The results of recent observations of the column densities of chlorine species in diffuse interstellar clouds are inconsistent with the column densities predicted by model calculations. The use of new atomic and molecular data fails to decrease the discrepancy. It is speculated that the exothermic reaction Cl(+) yields HCl(+) + H may not be rapid at the low temperatures prevailing in diffuse interstellar clouds.

Black, J. H.↗