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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

3D Nanomagnetism in Low Density Interconnected Nanowire Networks

Free-standing, interconnected metallic nanowire networks with densities as low as 40 mg/cm 3 have been achieved over centimeter-scale areas, using electrodeposition into polycarbonate membranes that have been ion-tracked at multiple angles. Networks of interconnected magnetic nanowires further provide an exciting platform to explore 3-dimensional nanomagnetism, where their structure, topology, and frustration may be used as additional degrees of freedom to tailor the materials properties. New magnetization reversal mechanisms in cobalt networks are captured by the first-order reversal curve method, which demonstrate the evolution from strong demagnetizing dipolar interactions to intersection-mediated domain wall pinning and propagation, and eventually to shape-anisotropy dominated magnetization reversal. These findings open up new possibilities for 3-dimensional integrated magnetic devices for memory, complex computation, and neuromorphics.

36 MATERIALS SCIENCE↗
NASA NTRS1992

Deep Space Network information system architecture study

The purpose of this article is to describe an architecture for the Deep Space Network (DSN) information system in the years 2000-2010 and to provide guidelines for its evolution during the 1990s. The study scope is defined to be from the front-end areas at the antennas to the end users (spacecraft teams, principal investigators, archival storage systems, and non-NASA partners). The architectural vision provides guidance for major DSN implementation efforts during the next decade. A strong motivation for the study is an expected dramatic improvement in information-systems technologies, such as the following: computer processing, automation technology (including knowledge-based systems), networking and data transport, software and hardware engineering, and human-interface technology. The proposed Ground Information System has the following major features: unified architecture from the front-end area to the end user; open-systems standards to achieve interoperability; DSN production of level 0 data; delivery of level 0 data from the Deep Space Communications Complex, if desired; dedicated telemetry processors for each receiver; security against unauthorized access and errors; and highly automated monitor and control.

Beswick, C. A.↗
DOE OSTI2022

My Virtual Cancer

Since each cancer has its own unique characteristics, each one can respond differently to the same treatments. Therefore, the creation of a digital twin (DT) of cancer can assist us in predicting the evolution of an individual's cancer through modeling each tumor's characteristics and response to treatment. Hence, we propose to take advantage of new advances in computational approaches and combine mechanistic, machine learning, and stochastic modeling approaches to create “My Virtual Cancer", a DT platform. To establish a personalized DT, we use patient-specific data for parameter estimations, sensitivity analysis, and uncertainty quantification. For each patient, we will estimate the values of parameters of their QSP model using the patient's data. We perform a multi-dimensional sensitivity analysis and uncertainty quantification on the mechanistic model to find a set of critical interactions and predict the intervals of confidence. Since this QSP model includes the data-driven mechanistic model of cells and molecules' interaction networks, one of the ultimate results of this DT would be the prediction of evolution of tumors.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2022

The expanding network of mineral chemistry throughout earth history reveals global shifts in crustal chemistry during the Proterozoic.

Earth surface redox conditions are intimately linked to the co-evolution of the geosphere and biosphere. Minerals provide a record of Earth’s evolving surface and interior chemistry in geologic time due to many diferent processes (e.g. tectonic, volcanic, sedimentary, oxidative, etc.). Here, we show how the bipartite network of minerals and their shared constituent elements expanded and evolved over geologic time. To further investigate network expansion over time, we derive and apply a novel metric (weighted mineral element electronegativity coefcient of variation; wMEECV) to quantify intra-mineral electronegativity variation with respect to redox. We fnd that element electronegativity and hard soft acid base (HSAB) properties are central factors in mineral redox chemistry under a wide range of conditions. Global shifts in mineral element electronegativity and HSAB associations represented by wMEECV changes at 1.8 and 0.6 billion years ago align with decreased continental elevation followed by the transition from the intermediate ocean and glaciation eras to postglaciation, increased atmospheric oxygen in the Phanerozoic, and enhanced continental weathering. Consequently, network analysis of mineral element electronegativity and HSAB properties reveal that orogenic activity, evolving redox state of the mantle, planetary oxygenation, and climatic transitions directly impacted the evolving chemical complexity of Earth’s crust.

Eli K. Moore↗
DOE OSTI2020

Rapid Mineral Precipitation During Shear Fracturing of Carbonate-Rich Shales

Target subsurface reservoirs for emerging low-carbon energy technologies and geologic carbon sequestration typically have low permeability and thus rely heavily on fluid transport through natural and induced fracture networks. Sustainable development of these systems requires deeper understanding of how geochemically mediated deformation impacts fracture microstructure and permeability evolution, particularly with respect to geochemical reactions between pore fluids and the host rock. Here, a series of triaxial direct shear experiments was designed to evaluate how fractures generated at subsurface conditions respond to penetration of reactive fluids with a focus on the role of mineral precipitation. Calcite-rich shale cores were directly sheared under 3.5 MPa confining pressure using BaCl 2 -rich solutions as a working fluid. Experiments were conducted within an X-ray computed tomography (xCT) scanner to capture 4-D evolution of fracture geometry and precipitate growth. Three shear tests evidenced nonuniform precipitation of barium carbonates (BaCO 3 ) along through-going fractures, where the extent of precipitation increased with increasing calcite content. Precipitates were strongly localized within fracture networks due to mineral, geochemical, and structural heterogeneities and generally concentrated in smaller apertures where rock:water ratios were highest. The combination of elevated fluid saturation and reactive surface area created in freshly activated fractures drove near-immediate mineral precipitation that led to an 80% permeability reduction and significant flow obstruction in the most reactive core. While most previous studies have focused on mixing-induced precipitation, this work demonstrates that fluid–rock interactions can trigger precipitation-induced permeability alterations that can initiate or mitigate risks associated with subsurface energy systems.

58 GEOSCIENCES↗
DOE OSTI2025

Coupled cluster and dislocation dynamics modeling of microstructure evolution in irradiated materials

We develop here a coupled cluster and dislocation dynamics framework to study the microstructure evolution of irradiated materials. The framework not only accounts for the three dimensional diffusion of radiation-generated clusters, but also their interaction with dislocation networks and the resultant climb motion of discrete dislocations within finite crystals. The framework is solved with a superposition solution scheme, and is applied to investigate the evolution of the irradiation-induced dislocation loops in zirconium (Zr), considering the effects of various bias factors including the diffusion anisotropy difference (DAD) of interstitials and interstitial clusters, the dislocation bias of defects to discrete dislocation segments, and the production bias of defects from the radiation cascade. We find that the DAD is the most critical factor influencing the kinetics of the loop evolution in Zr, while the recombination/interaction of mobile defects can induce a strong spatial dependence of the loop evolution together with the DAD. Here, the method is also adopted to study the evolution of interstitial $\langle$a$\rangle$ and vacancy $\langle$c$\rangle$ dislocation loop ensembles consistent with the microstructure observed during irradiation-induced growth of Zr. Our findings not only reveal the spatial dependence of the size and ellipticity of the dislocation loops, but also suggest a limit on the anisotropy factor of interstitials to reproduce the co-growth of $\langle$a$\rangle$ and $\langle$c$\rangle$ loops in zirconium, in good agreement with experimental observations and other simulation results.

Bias factors↗
DOE OSTI2024

Unlocking High Capacity and Reversible Alkaline Iron Redox Using Silicate-Sodium Hydroxide Hybrid Electrolytes

Alkaline iron (Fe) batteries are attractive due to the high abundance, low cost, and multiple valent states of Fe but show limited columbic efficiency and storage capacity when forming electrochemically inert Fe 3 O 4 on discharging and parasitic H 2 on charging. Herein, sodium silicate is found to promote Fe(OH) 2 /FeOOH against Fe(OH) 2 /Fe 3 O 4 conversions. Electrochemical experiments, operando X-ray characterization, and atomistic simulations reveal that improved Fe(OH) 2 /FeOOH conversion originates from (i) strong interaction between sodium silicate and iron oxide and (ii) silicate-induced strengthening of hydrogen-bond networks in electrolytes that inhibits water transport. Furthermore, the silicate additive suppresses hydrogen evolution by impairing energetics of water dissociation and hydroxyl de-sorption on iron surfaces. In conclusion, this new silicate-assisted redox chemistry mitigates H 2 and Fe 3 O 4 formation, improving storage capacity (199 mAh g -1 in half-cells) and coulombic efficiency (94 % after 400 full-cell cycles), paving a path to realizing green battery systems built from earth-abundant materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Effects of Synthesis Conditions on the Structure and Conductivity of Hydrogen-Substituted Graphdiyne

This study investigates how synthesis conditions influence the structure and conductivity of hydrogen-substituted graphdiyne (HsGDY). By varying the reaction temperature and solvent, we find that small changes in conditions markedly affect triple-bond retention and electronic continuity. Solid-state 13 C NMR and Raman spectroscopy reveal that elevated temperatures drive alkyne loss and partial graphitization, with N,N-dimethylformamide (DMF) promoting faster degradation than pyridine. The resulting decline in alkyne content directly correlates with reduced conductivity, indicating that preserving conjugation is essential for charge transport. These findings clarify how the synthetic environment governs the structural and electronic evolution of graphdiyne frameworks, providing insight into the controlled preparation of conjugated carbon networks.

alkyne retention↗
DOE OSTI2021

Porosity-Permeability Evolution During Simultaneous Mineral Dissolution and Precipitation

Permeability in reactive porous media evolves in complex ways that are hard to predict. Macroscopic empirical equations are often used to estimate permeability evolution but fail to reflect the impact of pore scale reactions on permeability. This work aims to understand the evolution of permeability in systems where mineral dissolution and precipitation occur simultaneously. Pore network models are used for permeability simulation of a Paluxy sandstone using pore and pore-throat size distributions from the analysis of X-ray CT images. Pore and pore-throat radii are increased and decreased to reflect the effects of dissolution and precipitation reactions. Varying spatial distributions of reactions are simulated and the resulting porosity and permeability values compared with commonly used macroscopic equations. It is observed that when dissolution occurs at the inlet and precipitation at the outlet, porosity increases while permeability decreases. Similar results are also observed in the respective opposite scenario where precipitation occurs at the inlet and dissolution at the outlet. When dissolution and precipitation reactions are randomly distributed throughout the network, porosity increases with little change in permeability that is not captured by the empirical equations. When reactions are controlled by pore and pore-throat sizes, such as dissolution occurring in pores and pore-throats of small size and precipitation in pores and pore-throats of larger size, porosity and permeability decrease. When precipitation occurs in pores and pore-throats of smaller size and dissolution in pores and pore-throats of larger size, porosity and permeability increase and is described relatively well by the Verma-Pruess porosity-permeability equation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

StressNet - Deep learning to predict stress with fracture propagation in brittle materials

Abstract Catastrophic failure in brittle materials is often due to the rapid growth and coalescence of cracks aided by high internal stresses. Hence, accurate prediction of maximum internal stress is critical to predicting time to failure and improving the fracture resistance and reliability of materials. Existing high-fidelity methods, such as the Finite-Discrete Element Model (FDEM), are limited by their high computational cost. Therefore, to reduce computational cost while preserving accuracy, a deep learning model, StressNet, is proposed to predict the entire sequence of maximum internal stress based on fracture propagation and the initial stress data. More specifically, the Temporal Independent Convolutional Neural Network (TI-CNN) is designed to capture the spatial features of fractures like fracture path and spall regions, and the Bidirectional Long Short-term Memory (Bi-LSTM) Network is adapted to capture the temporal features. By fusing these features, the evolution in time of the maximum internal stress can be accurately predicted. Moreover, an adaptive loss function is designed by dynamically integrating the Mean Squared Error (MSE) and the Mean Absolute Percentage Error (MAPE), to reflect the fluctuations in maximum internal stress. After training, the proposed model is able to compute accurate multi-step predictions of maximum internal stress in approximately 20 seconds, as compared to the FDEM run time of 4 h, with an average MAPE of 2% relative to test data.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Three-dimensional imaging of grain boundaries via quantitative fluorescence X-ray tomography analysis

Abstract Three-dimensional visualization of material composition within multiple grains and across complex networks of grain boundaries at nanoscales can provide new insight into the structure evolution and emerging functional properties of the material for diverse applications. Here, using nanoscale scanning X-ray fluorescence tomography, coupled with an advanced self-absorption correction algorithm developed in this work, we analyze the three-dimensional gain distributions and compositions in a Ce 0.8 Gd 0.2 O 2-δ -CoFe 2 O 4 mixed ionic-electronic conductor system with high accuracy and statistical significance. Our systematic investigation reveals an additional emergent phase and uncovers highly intriguing composition stability ranges for the multiple material phases within this system. The presented visualization of composition variations across complex interfaces, supported by our quantitative composition analysis, discloses mechanistic pathways of the diverse phase transformations occurring in the material synthesis, providing insights for the optimization of transport properties in the mixed ionic-electronic conductor system.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Nonequilibrium physics in biology

Life is characterized by a myriad of complex dynamic processes allowing organisms to grow, reproduce, and evolve. Physical approaches for describing systems out of thermodynamic equilibrium have been increasingly applied to living systems, which often exhibit phenomena not found in those traditionally studied in physics. Spectacular advances in experimentation during the last decade or two, for example, in microscopy, single-cell dynamics, in the reconstruction of subcellular and multicellular systems outside of living organisms, and in high throughput data acquisition, have yielded an unprecedented wealth of data on cell dynamics, genetic regulation, and organismal development. These data have motivated the development and refinement of concepts and tools to dissect the physical mechanisms underlying biological processes. Notably, landscape and flux theory as well as active hydrodynamic gel theory have proven useful in this endeavor. Together with concepts and tools developed in other areas of nonequilibrium physics, significant progress has been made in unraveling the principles underlying efficient energy transport in photosynthesis, cellular regulatory networks, cellular movements and organization, embryonic development and cancer, neural network dynamics, population dynamics and ecology, as well as aging, immune responses, and evolution. In this paper, recent advances in nonequilibrium physics are reviewd and their application to biological systems is surveyed. Many of these results are expected to be important cornerstones as the field continues to build our understanding of life.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

The mycorrhizal symbiosis: research frontiers in genomics, ecology, and agricultural application

Summary Mycorrhizal symbioses between plants and fungi are vital for the soil structure, nutrient cycling, plant diversity, and ecosystem sustainability. More than 250 000 plant species are associated with mycorrhizal fungi. Recent advances in genomics and related approaches have revolutionized our understanding of the biology and ecology of mycorrhizal associations. The genomes of 250+ mycorrhizal fungi have been released and hundreds of genes that play pivotal roles in regulating symbiosis development and metabolism have been characterized. rDNA metabarcoding and metatranscriptomics provide novel insights into the ecological cues driving mycorrhizal communities and functions expressed by these associations, linking genes to ecological traits such as nutrient acquisition and soil organic matter decomposition. Here, we review genomic studies that have revealed genes involved in nutrient uptake and symbiosis development, and discuss adaptations that are fundamental to the evolution of mycorrhizal lifestyles. We also evaluated the ecosystem services provided by mycorrhizal networks and discuss how mycorrhizal symbioses hold promise for sustainable agriculture and forestry by enhancing nutrient acquisition and stress tolerance. Overall, unraveling the intricate dynamics of mycorrhizal symbioses is paramount for promoting ecological sustainability and addressing current pressing environmental concerns. This review ends with major frontiers for further research.

Plant Sciences↗
DOE OSTI2022

Widespread transposon co-option in the Caenorhabditis germline regulatory network

The movement of selfish DNA elements can lead to widespread genomic alterations with potential to create novel functions. We show that transposon expansions in Caenorhabditis nematodes led to extensive rewiring of germline transcriptional regulation. We find that about one-third of Caenorhabditis elegans germline-specific promoters have been co-opted from two related miniature inverted repeat transposable elements (TEs), CERP2 and CELE2. These promoters are regulated by HIM-17, a THAP domain–containing transcription factor related to a transposase. Expansion of CERP2 occurred before radiation of the Caenorhabditis genus, as did fixation of mutations in HIM-17 through positive selection, whereas CELE2 expanded only in C. elegans. Through comparative analyses in Caenorhabditis briggsae, we find not only evolutionary conservation of most CERP2 co-opted promoters but also a substantial fraction that are species-specific. Our work reveals the emergence and evolutionary conservation of a novel transcriptional network driven by TE co-option with a major impact on regulatory evolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Surrogate Modeling of Landau Damping with Deep Operator Networks

Kinetic simulations excel at capturing microscale plasma physics phenomena with high accuracy, but their computational demands make them impractical for modeling large-scale space and astrophysical systems. In this context, we build a surrogate model, using Deep Operator Networks (DeepONets), based upon the Vlasov–Poisson simulation data to model the dynamical evolution of plasmas, focusing on the Landau damping process—a fundamental kinetic phenomenon in space and astrophysical plasmas. The trained DeepONets are able to capture the evolution of electric field energy in both linear and nonlinear regimes under various conditions. Extensive validation highlights DeepONets’ robust performance in reproducing complex plasma behaviors with high accuracy, paving the way for large-scale modeling of space and astrophysical plasmas.

plasma astrophysics↗
NASA NTRS2006

Mathematical Modeling of the Origins of Life

The emergence of early metabolism - a network of catalyzed chemical reactions that supported self-maintenance, growth, reproduction and evolution of the ancestors of contemporary cells (protocells) was a critical, but still very poorly understood step on the path from inanimate to animate matter. Here, it is proposed and tested through mathematical modeling of biochemically plausible systems that the emergence of metabolism and its initial evolution towards higher complexity preceded the emergence of a genome. Even though the formation of protocellular metabolism was driven by non-genomic, highly stochastic processes the outcome was largely deterministic, strongly constrained by laws of chemistry. It is shown that such concepts as speciation and fitness to the environment, developed in the context of genomic evolution, also held in the absence of a genome.

Pohorille, Andrew↗
NASA NTRS2019

The Lunar Geophysical Network Mission

Overarching Principles: Must be better than Apollo (coverage, duration, instrument performance); Learn from the Apollo experience. Lunar Geophysical Network (LGN) New Frontiers (NF)-class mission, as part of the NF-5 call. “This mission consists of several identical landers distributed across the lunar surface, each carrying geophysical instrumentation. The primary science objectives are to characterize the Moon’s internal structure, seismic activity, global heat flow budget, bulk composition, & magnetic field.” Global distribution of multiple stations. Each station should contain a seismometer, heat flow probe, electromagnetic sounder, laser retroreflector (lunar nearside). Each station must be long-lived (e.g., approximately10 years)to allow other stations (from other countries?) to be integrated with the anchor nodes to form the International Lunar Network. Why LGN? Planetary Science: Moon represents an end-member in planetary evolution (large small body, small rocky planet); Primary planetary differentiation preserved; Key to understanding terrestrial planet initial differentiation. Lunar Science: Heat flow probes yield crustal heat budget estimates; Combined with EMS (ElectroMagnetic Sounding), the temperature profile of the deep interior can be modeled along with mineralogy; Seismic and LLR (Lunar Laser Ranging) data also yield structure and compositional information of the lunar interior; High fidelity data from LGN would enhance the usefulness of the GRAIL (Gravity Recovery and Interior Laboratory) and SELENE (Selenological and Engineering Explorer) gravity data. Human Exploration: LGN must be established prior to renewed human lunar activity - we do not know the exact locations or causes of the shallow moonquakes (SMQs) - the largest magnitude seismic events recorded by Apollo (1 event per year of magnitude greater than or equal to 5); Establishing surface infrastructure near SMQ epicenters must be avoided.

Neal, C. R.↗
NASA NTRS2013

An Investigation of the Kinematic and Microphysical Control of Lightning Rate, Extent and NOx Production using DC3 Observations and the NASA Lightning Nitrogen Oxides Model (LNOM)

The Deep Convective Clouds and Chemistry (DC3) experiment seeks to quantify the relationship between storm physics, lightning characteristics and the production of nitrogen oxides via lightning (LNOx). The focus of this study is to investigate the kinematic and microphysical control of lightning properties, particularly those that may govern LNOx production, such as flash rate, type and extent across Alabama during DC3. Prior studies have demonstrated that lightning flash rate and type is correlated to kinematic and microphysical properties in the mixed‐phase region of thunderstorms such as updraft volume and graupel mass. More study is required to generalize these relationships in a wide variety of storm modes and meteorological conditions. Less is known about the co‐evolving relationship between storm physics, morphology and three‐dimensional flash extent, despite its importance for LNOx production. To address this conceptual gap, the NASA Lightning Nitrogen Oxides Model (LNOM) is applied to North Alabama Lightning Mapping Array (NALMA) and Vaisala National Lightning Detection Network(TM) (NLDN) observations following ordinary convective cells through their lifecycle. LNOM provides estimates of flash rate, flash type, channel length distributions, lightning segment altitude distributions (SADs) and lightning NOx production profiles. For this study, LNOM is applied in a Lagrangian sense to multicell thunderstorms over Northern Alabama on two days during DC3 (21 May and 11 June 2012) in which aircraft observations of NOx are available for comparison. The LNOM lightning characteristics and LNOX production estimates are compared to the evolution of updraft and precipitation properties inferred from dual‐Doppler and polarimetric radar analyses applied to observations from a nearby radar network, including the UAH Advanced Radar for Meteorological and Operational Research (ARMOR). Given complex multicell evolution, particular attention is paid to storm morphology, cell mergers and possible dynamical, microphysical and electrical interaction of individual cells when testing various hypotheses.

Carey, Lawrence↗