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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Cluster-Spin-Glass Magnetic Behavior and Morphology in the Coordination Polymer Alloys Fe y Co 1– y BTT

We report the synthesis of a series of pseudo-1D coordination polymer (CP) materials with the formula Fe y Co 1–y BTT (BTT = 1,3,5-benzenetrithiolate). These materials were structurally characterized by PXRD Rietveld, EXAFS, and PDF analyses, revealing that the CP superstructure enables a continuous and isomorphous alloy between the two homometallic compounds. Lower Fe loadings exhibit emergent spin glass magnetic behavior, such as memory effects and composition-dependent spin glass response time constants ranging from 6.9 × 10 –9 s to 1.8 × 10 –6 s. These data are consistent with the formation of spin clusters within the lattice. The magnetic behavior in these materials was modeled via replica exchange Monte Carlo simulation, which provides a good match for the experimentally measured spin glassing and magnetic phase transitions. Furthermore, these findings underscore how the rigid superstructure of CP and MOF scaffolds can enable the systematic tuning of physical properties, such as the spin glass behavior described here.

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

Wetter Summers Mitigated Temperature Stress on Rocky Mountain Forests During the Last Interglacial Warm Period

Recent droughts have highlighted concerns of how rising summer temperatures will increase tree mortality rates across the western United States. We analyzed subfossil wood samples from Colorado dating to the last interglacial to assess the response of two common conifers to a previous warm period. The trees experienced comparable growth rates and water use efficiency during the interglacial relative to modern despite evidence from model simulations of a ~30% increase in evaporative demand during the peak of the growing season. High-resolution isotopic analysis of the wood samples show an enrichment in the late season cellulosic δ 18 O relative to modern samples, which we find was associated with increased reliance on summer rain. The data are consistent with model simulations showing the interglacial was associated with wetter summers across the western US. Here, we propose enhanced summer rain during this period compensated for drought stress imposed by higher evaporative demand.

58 GEOSCIENCES↗
DOE OSTI2022

Marine Boundary Layer Decoupling and the Stable Isotopic Composition of Water Vapor

Decoupling of the subcloud layer in stratocumulus-topped marine boundary layers (STMBL) influences low-cloud cover by limiting the supply of water vapor from the surface. However, the relative importance of mixing between surface fluxes and other reservoirs of water vapor as a function of the degree of decoupling is poorly understood. Water vapor transport within the STMBL and its response to decoupling is explored using surface measurements of water vapor isotopic composition that were obtained from Graciosa Island, Azores, during the summer and fall of 2018. The data show an inverse relationship between the decoupling metric, Δq, and the degree of drying from an isotopically depleted water vapor source. The isotopic data require some degree of drying with an isotopically depleted source for coupled conditions, and likely require a small amount of mixing even for strongly decoupled conditions. The data are consistent with mixing between purely local reservoirs of water vapor, subjected to a small amount of condensation and fractionation, and do not require the invocation of large-scale transport of water vapor aloft or additional cloud-formation effects aloft.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Improving Seasonal Forecast Using Probabilistic Deep Learning

The path toward realizing the potential of seasonal forecasting and its socioeconomic benefits relies on improving general circulation model (GCM) based dynamical forecast systems. To improve dynamical seasonal forecasts, it is crucial to set up forecast benchmarks, and clarify forecast limitations posed by model initialization errors, formulation deficiencies, and internal climate variability. With huge costs in generating large forecast ensembles, and limited observations for forecast verification, the seasonal forecast benchmarking and diagnosing task proves challenging. Here, we develop a probabilistic deep learning-based statistical forecast methodology, drawing on a wealth of climate simulations to enhance seasonal forecast capability and forecast diagnosis. By explicitly modeling the internal climate variability and GCM formulation differences, the proposed Conditional Generative Forecasting (CGF) methodology enables bypassing crucial barriers in dynamical forecast, and offers a top-down viewpoint to examine how complicated GCMs encode the seasonal predictability information. We apply the CGF methodology for global seasonal forecast of precipitation and 2 m air temperature, based on a unique data set consisting 52,201 years of climate simulation. Results show that the CGF methodology can faithfully represent the seasonal predictability information encoded in GCMs. We successfully apply this learned relationship in real-world seasonal forecast, achieving competitive performance compared to dynamical forecasts. Using this CGF as benchmark, we reveal the impact of insufficient forecast spread sampling that limits the skill of the considered dynamical forecast system. Finally, we introduce different strategies for composing ensembles using the CGF methodology, highlighting the potential for leveraging the strengths of multiple GCMs to achieve advantgeous seasonal forecast.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High–Resolution Global Warming Experiment

Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Physical properties of asteroid Dimorphos as derived from the DART impact

On 26 September 2022, NASA’s Double Asteroid Redirection Test (DART) mission successfully impacted Dimorphos, the natural satellite of the binary near-Earth asteroid (65803) Didymos. Numerical simulations of the impact provide a means to find the surface material properties and structures of the target that are consistent with the observed momentum deflection efficiency, ejecta cone geometry and ejected mass. Our simulation that best matches the observations indicates that Dimorphos is weak, with a cohesive strength of less than a few pascals, like asteroids (162173) Ryugu and (101955) Bennu. We find that the bulk density of Dimorphos ρ B is lower than ~2,400 kg m – 3 and that it has a low volume fraction of boulders (≲40 vol%) on the surface and in the shallow subsurface, which are consistent with data measured by the DART experiment. These findings suggest that Dimorphos is a rubble pile that might have formed through rotational mass shedding and reaccumulation from Didymos. Our simulations indicate that the DART impact caused global deformation and resurfacing of Dimorphos. ESA’s upcoming Hera mission may find a reshaped asteroid rather than a well-defined crater.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Metal Ion Fluxes Controlling Amphibian Fertilization

Mammalian oocytes undergo major changes in zinc content and localization to be fertilized, the most striking being the rapid exocytosis of over 10 billion zinc ions in what are known as zinc sparks. Here, we report that fertilization of amphibian Xenopus laevis eggs also initiates a zinc spark that progresses across the cell surface in coordination with dynamic calcium waves. This zinc exocytosis is accompanied by a newly recognized loss of intracellular manganese. Synchrotron-based X-ray fluorescence and analytical electron microscopy reveal that zinc and manganese are sequestered in a system of cortical granules that are abundant at the animal pole. Through electron-nuclear double-resonance studies, we rule out Mn2+ complexation with phosphate or nitrogenous ligands in intact eggs, but the data are consistent with a carboxylate coordination environment. Our observations suggest that zinc and manganese fluxes are a conserved feature of fertilization in vertebrates and that they function as part of a physiological block to polyspermy.

Seeler, John F.↗
DOE OSTI2023

Observation of spin-momentum locked surface states in amorphous Bi 2 Se 3

Crystalline symmetries have played a central role in the identification and understanding of quantum materials. Here we investigate whether an amorphous analogue of a well-known three-dimensional strong topological insulator has topological properties in the solid state. We show that amorphous Bi 2 Se 3 thin films host a number of two-dimensional surface conduction channels. Our angle-resolved photoemission spectroscopy data are consistent with a dispersive two-dimensional surface state that crosses the bulk gap. Spin-resolved photoemission spectroscopy shows this state has an anti-symmetric spin texture, confirming the existence of spin-momentum locked surface states. We discuss these experimental results in light of theoretical photoemission spectra obtained with an amorphous topological insulator tight-binding model, contrasting it with alternative explanations. In conclusion, the discovery of spin-momentum locked surface states in amorphous materials opens a new avenue to characterize amorphous matter and triggers the search for an overlooked subset of quantum materials outside of current classification schemes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

HDBind: encoding of molecular structure with hyperdimensional binary representations

Traditional methods for identifying “hit” molecules from a large collection of potential drug-like candidates rely on biophysical theory to compute approximations to the Gibbs free energy of the binding interaction between the drug and its protein target. These approaches have a significant limitation in that they require exceptional computing capabilities for even relatively small collections of molecules. Increasingly large and complex state-of-the-art deep learning approaches have gained popularity with the promise to improve the productivity of drug design, notorious for its numerous failures. However, as deep learning models increase in their size and complexity, their acceleration at the hardware level becomes more challenging. Hyperdimensional Computing (HDC) has recently gained attention in the computer hardware community due to its algorithmic simplicity relative to deep learning approaches. The HDC learning paradigm, which represents data with high-dimension binary vectors, allows the use of low-precision binary vector arithmetic to create models of the data that can be learned without the need for the gradient-based optimization required in many conventional machine learning and deep learning methods. This algorithmic simplicity allows for acceleration in hardware that has been previously demonstrated in a range of application areas (computer vision, bioinformatics, mass spectrometery, remote sensing, edge devices, etc.). To the best of our knowledge, our work is the first to consider HDC for the task of fast and efficient screening of modern drug-like compound libraries. We also propose the first HDC graph-based encoding methods for molecular data, demonstrating consistent and substantial improvement over previous work. We compare our approaches to alternative approaches on the well-studied MoleculeNet dataset and the recently proposed LIT-PCBA dataset derived from high quality PubChem assays. We demonstrate our methods on multiple target hardware platforms, including Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs), showing at least an order of magnitude improvement in energy efficiency versus even our smallest neural network baseline model with a single hidden layer. Our work thus motivates further investigation into molecular representation learning to develop ultra-efficient pre-screening tools. We make our code publicly available at https://github.com/LLNL/hdbind.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Learning robust parameter inference and density reconstruction in flyer plate impact experiments

Estimating physical parameters or material properties from experimental observations is a common objective in many areas of physics and material science. In many experiments, especially in shock physics, radiography is the primary means of observing the system of interest. However, radiography does not provide direct access to key state variables, such as density, which prevents the application of traditional parameter estimation approaches. Here we focus on flyer plate impact experiments on porous materials, and resolving the underlying parameterized equation of state (EoS) and crush porosity model parameters given radiographic observation(s). We use machine learning as a tool to demonstrate with high confidence that using only high impact velocity data does not provide sufficient information to accurately infer both EoS and crush model parameters, even with fully resolved density fields or a dynamic sequence of images. We thus propose an observable data set consisting of low and high impact velocity experiments/simulations that capture different regimes of compaction and shock propagation, and proceed to introduce a generative machine learning approach which produces a posterior distribution of physical parameters directly from radiographs. We demonstrate the effectiveness of the approach in estimating parameters from simulated flyer plate impact experiments, and show that the obtained estimates of EoS and crush model parameters can then be used in hydrodynamic simulations to obtain accurate and physically admissible density reconstructions. Finally, we examine the robustness of the approach to model mismatches, and find that the learned approach can provide useful parameter estimates in the presence of out-of-distribution radiographic noise and previously unseen physics, thereby promoting a potential breakthrough in estimating material properties from experimental radiographic images.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Direct observation of diamond formation in a shock-compressed high explosive

Understanding the formation timescale and structure of carbonaceous reaction products is critical for modeling the high-pressure equation-of-state of organic materials. We use the National Ignition Facility to shock-compress polycrystalline TATB (C 6 H 6 N 6 O 6 ) samples to ~70–130 GPa and ~4000–5500 K, employing in situ nanosecond X-ray diffraction to probe reaction products and velocimetry to measure transmitted compression wave profiles. Our diffraction data is consistent with the formation of diamond over timescales less than ~60 ns. This represents carbon condensation from a molecular explosive on timescales three times faster than previously reported and the earliest observation of diamond produced from reacting TATB. Reactive flow simulations with explicit chemistry reproduce the observed temporal structure within wave profiles to inform the distribution of P-T states. These findings provide direct evidence of ultrafast diamond formation in a reactive system at extreme conditions and provide new constraints for models of shock and detonation chemistry.

Clarke, Samantha M. [Lawrence Livermore National L↗
DOE OSTI2026

Semi-Dynamic Leach Testing of Densified Silicon-based Iodine Waste Forms

Iodine waste forms (IWF) require a conceptual corrosion release model (CCRM) to provide iodine (I) release rates for performance modeling nuclear waste disposal repositories. To develop a CCRM, an understanding of the corrosion mechanisms of the IWF are required along with data from consistent test methods to parameterize the model. The present study has advanced both areas by providing and assessing the corrosion resistance of IWF types based on their processing history in minor variations of semi-dynamic leach tests. The test included a series of semi-dynamic leach tests using monolithic IWFs in deionized water (leachant). Several experiments were conducted under alternate test conditions with changes to temperature, leachant replacement, leachant pH, leachant volume, masking, and surface finish to elucidate if varying these conditions impacted IWF corrosion behavior. Tests were conducted on two classes of IWFs: (1) I-bearing silver-mordenite (AgZ) materials processed by hot isostatic pressing (HIP) at different temperatures, pressures, sizes, and times; and (2) I-bearing silver-functionalized silica aerogels (SFA) processed by either HIP or spark plasma sintering (SPS). The corrosion susceptibility of AgZ samples was influenced by HIP temperature and pressure. The SPS SFAs retained I far better than HIP SFAs. Additional findings in this study include: (1) The iodine dissolution rate decreased with decreasing temperature, (2) a common ion effect may occur and slow dissolution of the host phase if the leachant is not regularly replaced, (3) pH controls the dissolution rate, and (4) the iodine dissolution rate slows with extended test time (up to 224 days). Based on this work, these parameters should thus be represented when developing a CCRM.

corrosion↗
DOE OSTI2020

Catalytic C 2 H 2 synthesis via low temperature CO hydrogenation on defect-rich 2D-MoS 2 and 2D-MoS 2 decorated with Mo clusters

Rational design of novel catalytic materials used to synthesize storable fuels via the CO hydrogenation reaction has recently received considerable attention. In this work, defect poor and defect rich 2D-MoS 2 as well as 2D-MoS 2 decorated with Mo clusters are employed as catalysts for the generation of acetylene (C 2 H 2 ) via the CO hydrogenation reaction. Temperature programmed desorption is used to study the interaction of CO and H2 molecules with the MoS 2 surface as well as the formation of reaction products. The experiments indicate the presence of four CO adsorption sites below room temperature and a competitive adsorption between the CO and H 2 molecules. The investigations show that CO hydrogenation is not possible on defect poor MoS 2 at low temperatures. However, on defect rich 2D-MoS 2 , small amounts of C 2 H 2 are produced, which desorb from the surface at temperatures between 170 K and 250 K. A similar C 2 H 2 signal is detected from defect poor 2D-MoS 2 decorated with Mo clusters, which indicates that low coordinated Mo atoms on 2D-MoS 2 are responsible for the formation of C 2 H 2 . Density functional theory investigations are performed to explore possible adsorption sites of CO and understand the formation mechanism of C 2 H 2 on MoS 2 and Mo 7 /MoS 2 . The theoretical investigation indicates a strong binding of C 2 H 2 on the Mo sites of MoS 2 preventing the direct desorption of C 2 H 2 at low temperatures as observed experimentally. Instead, the theoretical results suggest that the experimental data are consistent with a mechanism in which CHO radical dimers lead to the formation of C 2 H 2 that presents an exothermic desorption.

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

Defect-mediated metastability and carrier lifetimes in polycrystalline (Ag,Cu)(In,Ga)Se 2 absorber materials

Using a combination of optical and electrical measurements, we develop a model for metastable defects in Ag-alloyed Cu(In,Ga)Se 2 , one of the leading thin film photovoltaic materials. By controlling the pre-selenization conditions of the back contact prior to the growth of polycrystalline (Ag,Cu)(In,Ga)Se 2 absorbers and subsequently exposing them to various stresses (light soaking and dark-heat), we explore in this paper the nature and role of metastable defects on the electro-optical and photovoltaic performance of high-efficiency solar cell materials and devices. Positron annihilation spectroscopy indicates that dark-heat exposure results in an increase in the concentration of the selenium–copper divacancy complex (V Se –V Cu ), attributed to depassivation of donor defects. Deep-level optical spectroscopy finds a corresponding increase of a defect at Ev+0.98 eV, and deep-level transient spectroscopy suggests that this increase is accompanied by a decrease in the concentration of mid-bandgap recombination centers. Time-resolved photoluminescence excitation spectroscopy data are consistent with the presence of the V Se –V Cu divacancy complex, which may act as a shallow trap for the minority carriers. Light-soaking experiments are consistent with the V Se –V Cu optical cycle proposed by Lany and Zunger, resulting in the conversion of shallow traps into recombination states that limit the effective minority carrier recombination time (and the associated carrier diffusion length) and an increase in the doping density that limits carrier extraction in photovoltaic devices.

14 SOLAR ENERGY↗
DOE OSTI2021

Effect of resistive wall on thermal quench in JET disruptions

In this paper, experimental data, simulations and theory are presented of a JET tokamak thermal quench. The emphasis is on the timescale of the bulk plasma thermal energy loss. The simulations suggest that the thermal energy loss is caused by a resistive wall tearing mode, and experimental data is consistent with this conclusion. The time scale of the thermal quench is the inverse of the mode growth rate.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Detecting topological phase transitions in cadmium arsenide films via the transverse magnetoresistance

Topological protection against localization causes electrical transport phenomena in disordered topological materials to differ from those in topologically trivial systems. For example, a transition between a regime of weak localization to one of weak antilocalization can occur in systems such as topological insulators and topological semimetals when an external potential is applied across the system. Here, we report on the transverse magnetoresistance of thin films of cadmium arsenide, a topological non-trivial material, as we tune the electronic states and the Fermi level. We show that the appearance of weak localization and weak antilocalization sensitively reflects the relative contributions of multiple transport channels involving both gapless (massless) and gapped (massive) Dirac fermion states present in these films. Furthermore, the data is consistent with expectations of the different topological states of these films. Weak (anti-) localization phenomena can therefore serve as a probe of the types of Dirac fermions present in topological semimetals.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

GdWN 3 is a nitride perovskite

Nitride perovskites ABN3 are an emerging and highly underexplored class of materials that are of interest due to their intriguing calculated ferroelectric, optoelectronic, and other functional properties. Incorporating novel A-site cations is one strategy to tune and expand such properties; for example, Gd 3+ is compelling due to its large magnetic moment, potentially leading to multiferroic behavior. However, the theoretically predicted ground state of GdWN 3 was a non-perovskite monoclinic structure. Here, we experimentally show that GdWN 3-y crystallizes in a perovskite structure. High-throughput combinatorial sputtering with activated nitrogen is employed to synthesize thin films of Gd 2-x W x N 3-y O y with oxygen content y < 0.05. Ex situ annealing crystallizes a polycrystalline perovskite phase in a narrow composition window near x = 1. LeBail fits of synchrotron grazing incidence wide angle x-ray scattering data are consistent with a perovskite ground-state structure. Refined density functional theory calculations that included antiferromagnetic configurations confirm that the ground-state structure of GdWN 3 is a distorted Pnma perovskite with antiferromagnetic ordering, in contrast to prior predictions. Initial property measurements find that GdWN 3-y is paramagnetic down to T = 2 K with antiferromagnetic correlations and that the absorption onset depends on cation stoichiometry. This work provides an important path toward both the rapid expansion of the emerging family of nitride perovskites and understanding their potential multiferroic properties.

14 SOLAR ENERGY↗
DOE OSTI2020

Investigation of compression of indirect-drive targets under conditions of the NIF facility using one-dimensional modelling

The indirect compression dynamics of targets containing capsules with ablators of a plastic, high-density carbon and beryllium is simulated in the framework of a one-dimensional model based on the 1D RADIAN code. Experiments with such targets are performed on the NIF facility in the Livermore Laboratory (USA) in 2014 – 2018. The 1D simulation data are consistent with the results of experiments and calculations made at this Laboratory. The effect of the hard part of hohlraum radiation on capsule compression parameters is confirmed. We demonstrate the feasibility of eliminating this influence not only by selecting the hohlraum material but also by introducing admixtures into the capsule that absorb this radiation. It is shown how varying the amount of admixture in the capsule ablator varies the spectrum of the radiation that heats the DT fuel. (interaction of laser radiation with matter. laser plasma)

36 MATERIALS SCIENCE↗