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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Ion Transport in 2D Nanostructured $\pi$-Conjugated Thieno[3,2- b ]thiophene-Based Liquid Crystal

Leveraging the self-assembling behavior of liquid crystals designed for controlling ion transport is of both fundamental and technological significance. Here, we have designed and prepared a liquid crystal that contains (2,5-bis(5-(2,5,8,11-tetraoxatridecan-13-yl)thiophen-2yl)thieno[3,2-b]thiophene (BTTT) as mesogenic core and conjugated segment and symmetric tetra(ethylene oxide) (EO4) as polar side chains for ionic conducting regions. Driven by the crystallization of the BTTT cores, BTTT/dEO4 exhibits well-ordered smectic phases below 71.5 °C as confirmed by differential scanning calorimetry, polarized optical microscope, temperature dependent wide-angle X-ray scattering and grazing incidence wide-angle X-ray scattering (GIWAXS). We adopted a combination of experimental GIWAXS and molecular dynamics (MD) simulations to better understand the molecular packing of BTTT/dEO4 films, particularly when loaded with the ion conducting salt, lithium bis(trifluoromethanesulfonyl)imide (LiTFSI). Ionic conduction of BTTT/dEO4 is realized by the addition of LiTFSI, with the material able to maintain smectic phases up to r = [Li + ]/[EO] = 0.1. In this work, The highest ionic conductivity of 8 × 10 -3 S/cm was attained at an intermedium salt concentration of r = 0.05. It was also found that ion conduction in BTTT/dEO4 is enhanced by forming a smectic layered structure with irregular interfaces between the BTTT and EO4 layers and by the lateral film expansion upon salt addition. This can be explained by the enhancement of the misalignment and configurational entropy of the side chains, which increase their local mobility and that of the solvated ions. Our molecular design thus illustrates how, beyond the favorable energetic interactions that drive the assembly and ion solvating domains, modulation of entropic effects can also be favorably harnessed to improve ion conduction.

thin film electrochemical impedance spectroscopy↗
DOE OSTI2024

Interfacial Reactivity-Triggered Oscillatory Lattice Strains of Nanoalloys

Understanding the structure evolution of nanoalloys under reaction conditions is vital to the design of active and durable catalysts. Herein, we report an operando measurement of the dynamic lattice strains of dual-noble-metal alloyed with an earth-abundant metal as a model electrocatalyst in a working proton-exchange membrane fuel cell using synchrotron high-energy X-ray diffraction coupled with pair distribution function analysis. Additionally, the results reveal an interfacial reaction-triggered oscillatory lattice strain in the alloy nanoparticles upon surface dealloying. Analysis of the lattice strains with an apparent oscillatory irregularity in terms of frequency and amplitude using time-frequency domain transformation and theoretical calculation reveals its origin from a metal atom vacancy diffusion pathway to facilitate realloying upon dealloying. This process, coupled with surface metal partial oxidation, constitutes a key factor for the nanoalloy's durability under the electrocatalytic oxygen reduction reaction condition, which serves as a new guiding principle for engineering durable or self-healable electrocatalysts for sustainable fuel cell energy conversion.

Wu, Zhi-Peng [State University of New York (SUNY),↗
DOE OSTI2025

Electrodepositing Textured Sn Film as a Highly Reversible Anode for Aqueous Batteries

Electrodepositing metal materials in large capacity, at low potential, and with high reversibility serves as the foundation for any aqueous rechargeable battery chemistry to realize the promises of high energy, low cost, and high safety. However, such a foundation is not solid because of the natural tendency of metals to form irregular, nonplanar, and often dendritic morphologies during electrochemical crystallization, which is further amplified in an acidic environment due to the faster kinetics of the coupled proton and mass-transport processes between hydrated metal ions and free metal atoms. As a typical representative, tin metal (Sn 0 ) has potential to achieve high energy in acidic batteries, but its nonuniform large-particle morphology, obtained from traditional electrodeposition, leads to dead Sn 0 formation and deteriorating reversibility, accompanied by the sustained hydrogen evolution reaction (HER) and active Sn 0 loss. Here, in this study, we report quaternary onium salts as effective interfacial cocations that, via selective adsorption, steadily texturize Sn 0 deposition along the (211) plane, which is intrinsically inert to the HER, thus regulating the film deposition process by favoring the formation of planar Sn 0 film. Such Sn 0 film brings exceptional reversibility in acidic electrolytes, which translates into sustained cycling stability at applicable areal capacities in both anode-half cells (similar to 1500 deposition/dissolution cycles at 5 mAh cm -2 ) and full cells (350 charge/discharge cycles at 5 mAh cm -2 ). Textured electrodeposition with intrinsic HER-suppression capability provides a universal solution for diverse metal anode materials in rechargeable energy-dense aqueous batteries.

Sn metal↗
DOE OSTI2020

Permeability Hysteresis From Microchannels Opening During Dissolution/Reprecipitation Cycle

Abstract Permeability is a critical parameter for geological resources characterization. Its evolution with respect to porosity is particularly interesting and many research initiatives focus on deriving such relationships, to understand some hydraulic impacts of microstructure alteration. Permeability evolution from chemical reactions, for instance, can become complex as flow channels may open during rock dissolution. In this contribution, we show that this phenomenon can lead to irregular porosity‐permeability curves and permeability hysteresis after reprecipitation. Current approaches describing permeability as a simple function of porosity can therefore not capture this behavior, and we advocate instead the use of dynamic modeling for such scenarios. We demonstrate our approach by modeling a dissolution/precipitation cycle for a unit cell pore channel and quantify the process at larger scale on three different rock samples, whose microstructures are reconstructed from segmented micro‐Computerised Tomography scans.

Lesueur, Martin↗
DOE OSTI2020

Modeling the Transmission of Optical Lightning Signals Through Complex 3‐D Cloud Scenes

Abstract Space‐based lightning imagers have shown that complex cloud scenes consisting of multiple tall convective features, anvil clouds, and warm boundary cloud layers are illuminated by lightning in many different ways depending on where the lightning occurs and how energetic it is. Modifications to the optical lightning signals from radiative transfer in the cloud medium can lead to reductions in detection efficiency and location accuracy for these instruments and can also cause some of the optical signals that are detected to have unexpected spatial energy distributions. In this study, we perform Monte Carlo radiative transfer simulations of optical lightning emissions in clouds with complex 3‐D geometries to shed some light on the origins of certain irregular radiance patterns that have been recorded from orbit. We show that diffuse reflections off nearby cloud faces can explain lightning signals in nonelectrified clouds, tall clouds can result in poor optical transmission and suppressed radiances that could lead to missed events and that particularly favorable viewing conditions can cause otherwise normal lightning to produce a superbolt that is orders of magnitude brighter than the same flash seen from a different angle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Acceleration of Oxygen Ions in Dipolarization Events: 1. CPS Distributions

Abstract Using an MHD simulation of near tail reconnection associated with a flow burst and the collapse (dipolarization) of the inner tail in combination with test particle tracing we study the acceleration and flux increases of energetic oxygen ions (O + ). The characteristic orbits, distributions, and acceleration mechanisms are governed by the dimensionless parameter σ = ω ci t n , where ω ci is the ion gyro frequency and t n a characteristic Alfvén time of the MHD simulation. For σ < 1, central plasma sheet (CPS) populations after the passage of the dipolarization front are found to resemble half‐shells in velocity space oriented toward dusk. They originate from within the CPS and are energized typically by a single encounter of the region of enhanced cross‐tail electric field associated with the flow burst. For larger σ values ( σ > 1) the O + distributions resemble more closely those of protons, consisting of two counter‐streaming field‐aligned beams and an, albeit more tenuous and irregular, ring population perpendicular to the magnetic field. The existence of the beams, however, depends on suitable earthward moving source populations in the plasma sheet boundary layer or the adjacent lobes. The acceleration to higher energies is found to indicate a charge dependence, consistent with a dominance of more highly charged ions at energies of a few hundred keV. As in earlier simulations, the simulated fluxes show large anisotropies and nongyrotropic effects, phase bunching, and spatially and temporally localized beams.

Birn, J.↗
DOE OSTI2023

Floods and Heavy Precipitation at the Global Scale: 100‐Year Analysis and 180‐Year Reconstruction

Floods and heavy precipitation have disruptive impacts worldwide, but their historical variability remains only partially understood at the global scale. This article aims at reducing this knowledge gap by jointly analyzing seasonal maxima of streamflow and precipitation at more than 3,000 stations over a 100‐year period. The analysis is based on Hidden Climate Indices (HCIs). Like standard climate indices (e.g., Nino 3.4, NAO), HCIs are used as covariates explaining the temporal variability of data, but unlike them, HCIs are estimated from the data. In this work, a distinction is made between common HCIs, that affect both heavy precipitation and floods, and specific HCIs, that exclusively affect one or the other. Overall, HCIs do not show noticeable autocorrelation, but some are affected by noticeable trends. In particular, strong and wide‐ranging trends are identified in precipitation‐specific HCIs, while trends affecting flood‐specific HCIs are weaker and have more localized effects. A probabilistic model is then derived to link HCIs and large‐scale atmospheric variables (pressure, wind, temperature) and to reconstruct HCIs since 1836 using the 20CRv3 reanalysis. In turn this allows estimating the probability of occurrence of floods and heavy precipitation at the global scale. This 180‐year reconstruction highlights flood hot‐spots and hot‐moments in the distant past, well before the establishment of perennial monitoring networks. Finally, the approach presented in this study is generic and paves the way for an improved characterization of historical variability by making a better use of long but highly irregular station data sets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Machine Learning Classification Strategy to Improve Streamflow Estimates in Diverse River Basins in the Colorado River Basin

Streamflow in the Colorado River Basin (CRB) is significantly altered by human activities including land use/cover alterations, reservoir operation, irrigation, and water exports. Climate is also highly varied across the CRB which contains snowpack-dominated watersheds and arid, precipitation-dominated basins. Recently, machine learning methods have improved the generalizability and accuracy of streamflow models. Previous successes with LSTM modeling have primarily focused on unimpacted basins, and few studies have included human impacted systems in either regional or single-basin modeling. We demonstrate that the diverse hydrological behavior of river basins in the CRB are too difficult to model with a single, regional model. We propose a method to delineate catchments into categories based on the level of predictability, hydrological characteristics, and the level of human influence. Lastly, we model streamflow in each category with climate and anthropogenic proxy data sets and use feature importance methods to assess whether model performance improves with additional relevant data. Overall, land use cover data at a low temporal resolution was not sufficient to capture the irregular patterns of reservoir releases, demonstrating the importance of having high-resolution reservoir release data sets at a global scale. On the other hand, the classification approach reduced the complexity of the data and has the potential to improve streamflow forecasts in human-altered regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Deep Learning Reconstruction of Daily Soil CO 2 Efflux Reveals Biogeochemical Insights and Reduces Annual Estimate Uncertainty Despite Limited Daily Predictability

Soil CO 2 efflux is commonly measured monthly or seasonally, leaving daily dynamics poorly resolved and contributing to global estimation uncertainty. We trained a single Long Short-Term Memory (LSTM) model to predict daily soil CO 2 efflux across 82 globally distributed sites in COSORE, with 0.2%–46.9% daily data coverage from 2003 to 2020. Despite using far fewer sites than are typically used to train a single deep learning model, with observations biased toward temperate mesic sites, the LSTM model performed well at approximately one-third of sites, reconstructed nearly 2 decades of daily efflux, and outperformed commonly used approaches for estimating daily efflux when applied to the same data set. Performance was weakest at pronounced peaks and troughs and at non-temperate sites with <1.5 years of observations and irregular data patterns. Nevertheless, annual efflux from reconstructed daily data had <40% error even at underperforming sites, substantially improving estimates derived from monthly and seasonal sampling (maximum errors of 95% and 136%, respectively). Temperature sensitivity (Q 10 ) estimated from reconstructed daily predictions closely matched estimates from daily observations, whereas Q 10 values derived from monthly or seasonal observations deviated substantially, suggesting that coarse temporal sampling may contribute to uncertainty in reported Q 10 values. Consistent daily reconstructions further enabled trend analyses for well-performing, predominantly temperate sites and showed increasing soil CO 2 efflux at most sites from 2003 to 2020, with more variable summer trends. Despite limitations, these results demonstrate the potential of LSTM models to reconstruct daily soil CO 2 efflux and reduce estimation uncertainties from sparse observations.

Smykalov, Valerie [Pennsylvania State University, ↗
DOE OSTI2025

Characterizing Greater Houston's Aerosol by Air Mass During TRACER

During the TRacking Aerosol and Convection interaction ExpeRiment (TRACER), a suite of aerosol and cloud measurements were made using the Texas A&M Rapid Onsite Atmospheric Measurement Van (ROAM-V) mobile instrument platform. Joint ROAM-V/radiosonde deployments focused on sampling polluted marine and continental air masses to understand summertime convection along and across the sea-breeze front as it propagated through Houston. The polluted marine air mass at Seawolf Park, Galveston, TX was defined by two characteristic aerosol populations. Although the background total particle concentrations averaged 2,500 cm −3 , the air mass was also influenced by frequent but irregular periods of ship emission with significantly higher aerosol concentrations at times exceeding 34,000 cm −3 . Ship emission influenced periods, typically lasting <10 min, contained smaller, less hygroscopic particles resulting in a 69% relative decline in cloud condensation nuclei (CCN) activated fraction at 1% supersaturation compared to background periods. Measurements in continental air masses northwest of Houston revealed an average aerosol concentration of 5,208 cm −3 with a κ value near 0.1 reasonably describing the CCN population, independent of particle size. In continental air masses, substantial differences in particle size and CCN activation over small distances (<42 miles between sites) suggest considerable site-to-site variability in addition to the expected day-to-day differences. This small-scale variability makes it difficult to generalize continental air mass aerosol properties. Both coastal and inland locations had effective ice nucleating particles, but inland deployments observed the warmest nucleation temperature at −15.6°C compared to −17.8°C close to the coast. These measurements can reduce uncertainties in regional convection allowing models to improve understanding of aerosol-cloud interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Surface oxygenation of multicomponent nanoparticles toward active and stable oxidation catalysts

Abstract The need for active and stable oxidation catalysts is driven by the demands in production of valuable chemicals, remediation of hydrocarbon pollutants and energy sustainability. Traditional approaches focus on oxygen-activating oxides as support which provides the oxygen activation at the catalyst-support peripheral interface. Here we report a new approach to oxidation catalysts for total oxidation of hydrocarbons (e.g., propane) by surface oxygenation of platinum (Pt)-alloyed multicomponent nanoparticles (e.g., platinum-nickel cobalt (Pt–NiCo)). The in-situ/operando time-resolved studies, including high-energy synchrotron X-ray diffraction and diffuse reflectance infrared Fourier transform spectroscopy, demonstrate the formation of oxygenated Pt–NiOCoO surface layer and disordered ternary alloy core. The results reveal largely-irregular oscillatory kinetics associated with the dynamic lattice expansion/shrinking, ordering/disordering, and formation of surface-oxygenated sites and intermediates. The catalytic synergy is responsible for reduction of the oxidation temperature by ~100 °C and the high stability under 800 °C hydrothermal aging in comparison with Pt, and may represent a paradigm shift in the design of self-supported catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Adsorbate chemical environment-based machine learning framework for heterogeneous catalysis

Abstract Heterogeneous catalytic reactions are influenced by a subtle interplay of atomic-scale factors, ranging from the catalysts’ local morphology to the presence of high adsorbate coverages. Describing such phenomena via computational models requires generation and analysis of a large space of atomic configurations. To address this challenge, we present Adsorbate Chemical Environment-based Graph Convolution Neural Network (ACE-GCN), a screening workflow that accounts for atomistic configurations comprising diverse adsorbates, binding locations, coordination environments, and substrate morphologies. Using this workflow, we develop catalyst surface models for two illustrative systems: (i) NO adsorbed on a Pt 3 Sn(111) alloy surface, of interest for nitrate electroreduction processes, where high adsorbate coverages combined with low symmetry of the alloy substrate produce a large configurational space, and (ii) OH* adsorbed on a stepped Pt(221) facet, of relevance to the Oxygen Reduction Reaction, where configurational complexity results from the presence of irregular crystal surfaces, high adsorbate coverages, and directionally-dependent adsorbate-adsorbate interactions. In both cases, the ACE-GCN model, trained on a fraction (~10%) of the total DFT-relaxed configurations, successfully describes trends in the relative stabilities of unrelaxed atomic configurations sampled from a large configurational space. This approach is expected to accelerate development of rigorous descriptions of catalyst surfaces under in-situ conditions.

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

Order-disorder phase transition driven by interlayer sliding in lead iodides

A variety of phase transitions have been found in two-dimensional layered materials, but some of their atomic-scale mechanisms are hard to clearly understand. Here, we report the discovery of a phase transition whose mechanism is identified as interlayer sliding in lead iodides, a layered material widely used to synthesize lead halide perovskites. The low-temperature crystal structure of lead iodides is found not 2H polytype as known before, but non-centrosymmetric 4H polytype. This undergoes the order-disorder phase transition characterized by the abrupt spectral broadening of valence bands, taken by angle-resolved photoemission, at the critical temperature of 120 K. It is accompanied by drastic changes in simultaneously taken photocurrent and photoluminescence. The transmission electron microscopy is used to reveal that lead iodide layers stacked in the form of 4H polytype at low temperatures irregularly slide over each other above 120 K, which can be explained by the low energy barrier of only 10.6 meV/atom estimated by first principles calculations. Our findings suggest that interlayer sliding is a key mechanism of the phase transitions in layered materials, which can significantly affect optoelectronic and optical characteristics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Achieving tissue-level softness on stretchable electronics through a generalizable soft interlayer design

Soft and stretchable electronics have emerged as highly promising tools for biomedical diagnosis and biological studies, as they interface intimately with the human body and other biological systems. Most stretchable electronic materials and devices, however, still have Young’s moduli orders of magnitude higher than soft bio-tissues, which limit their conformability and long-term biocompatibility. Here, we present a design strategy of soft interlayer for allowing the use of existing stretchable materials of relatively high moduli to versatilely realize stretchable devices with ultralow tissue-level moduli. We have demonstrated stretchable transistor arrays and active-matrix circuits with moduli below 10 kPa—over two orders of magnitude lower than the current state of the art. Benefiting from the increased conformability to irregular and dynamic surfaces, the ultrasoft device created with the soft interlayer design realizes electrophysiological recording on an isolated heart with high adaptability, spatial stability, and minimal influence on ventricle pressure. In vivo biocompatibility tests also demonstrate the benefit of suppressing foreign-body responses for long-term implantation. With its general applicability to diverse materials and devices, this soft-interlayer design overcomes the material-level limitation for imparting tissue-level softness to a variety of bioelectronic devices.

42 ENGINEERING↗
DOE OSTI2024

Angle between DNA linker and nucleosome core particle regulates array compaction revealed by individual-particle cryo-electron tomography

Abstract The conformational dynamics of nucleosome arrays generate a diverse spectrum of microscopic states, posing challenges to their structural determination. Leveraging cryogenic electron tomography (cryo-ET), we determine the three-dimensional (3D) structures of individual mononucleosomes and arrays comprising di-, tri-, and tetranucleosomes. By slowing the rate of condensation through a reduction in ionic strength, we probe the intra-array structural transitions that precede inter-array interactions and liquid droplet formation. Under these conditions, the arrays exhibite irregular zig-zag conformations with loose packing. Increasing the ionic strength promoted intra-array compaction, yet we do not observe the previously reported regular 30-nanometer fibers. Interestingly, the presence of H1 do not induce array compaction; instead, one-third of the arrays display nucleosomes invaded by foreign DNA, suggesting an alternative role for H1 in chromatin network construction. We also find that the crucial parameter determining the structure adopted by chromatin arrays is the angle between the entry and exit of the DNA and the corresponding tangents to the nucleosomal disc. Our results provide insights into the initial stages of intra-array compaction, a critical precursor to condensation in the regulation of chromatin organization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Global climate mode resonance due to rapidly intensifying El Niño-Southern Oscillation

The El Niño-Southern Oscillation (ENSO) influences climate variability globally, encompassing various other modes of variability, and thus represents a key predictable climate signal on seasonal timescales. Yet, its response to greenhouse warming remains uncertain, with models projecting a range of outcomes. Here, we demonstrate that in response to warming, a state-of-the-art high-resolution climate model simulates a rapid transition from a moderate-amplitude irregular regime, as observed in the current climate, to a highly regular oscillation with intensifying amplitude. This behaviour can be attributed to increasing air-sea feedbacks, which approach criticality in the second half of this century, and growing atmospheric noise. As ENSO intensifies in this model, it synchronizes with other prominent climate modes, such as the North Atlantic Oscillation and the Indian Ocean Dipole, thereby imprinting its regular, predictable variability on them. If realized, this global climate mode resonance would have wide-ranging whiplash impacts on regional hydroclimates.

Atmospheric dynamics↗
DOE OSTI2026

Bubble explosion induced melt pool instabilities in electron beam melting of aluminum alloy

Electron beam melting (EBM) is an additive manufacturing technology that can process materials and manufacture components otherwise impossible or uneconomical. However, defects, including porosity and surface irregularities, are widely reported in EBM-built components, and their formation mechanisms are not fully understood. Here, using in-situ high-speed synchrotron X-ray imaging, we reveal that bubble explosions in Al6061 during EBM induce melt pool instabilities contributing to defect formation. The melt pool and keyhole evolve through three stages: (1) initial formation of a melt pool, (2) subsurface bubble formation and explosion, and (3) periodic keyhole oscillation. During scanning, periodic bubble explosions can eject molten liquid as spatters and disturb the vapor depression and melt pool, contributing to surface humping, that may trigger lack-of-fusion defects in subsequent layers. The physical insights we report could provide guidance for EBM machine development, process innovation, alloy design and model development.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Primitive to conventional geometry projection for efficient phonon transport calculations

Abstract The primitive Wigner-Seitz cell and corresponding first Brillouin zone (FBZ) are typically used in calculations of lattice vibrational and transport properties as they contain the smallest number of degrees of freedom and thus have the cheapest computational cost. However, in complex materials, the FBZ can take on irregular shapes where lattice symmetries are not apparent. Thus, conventional cells (with more atoms and regular shapes) are often used to describe materials, though dynamical and transport calculations are more expensive. Here we discuss an efficient anharmonic lattice dynamic method that maps conventional cell dynamics to primitive cell dynamics based on translational symmetries. Such symmetries have not been utilized in typical lattice dynamical calculations. This leads to phase interference conditions that act like conserved quantum numbers and a conservation rule for phonon scattering that is hidden in conventional dynamics which significantly reduces the computational cost. We demonstrate this method for phonon transport in a variety of materials with inputs from first-principles calculations and attribute its efficiency to reduced scattering phase space and fewer summations in scattering matrix element calculations.

36 MATERIALS SCIENCE↗