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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Subtle changes in hydrogen bond orientation result in glassification of carbon capture solvents

Water-lean CO 2 capture solvents show promise for more efficient and cost-effective CO 2 capture, although their long-term behavior in operation has yet to be well studied. New observations of extended structure solvent behavior show that some solvent formulations transform into a glass-like phase upon aging at operating temperatures after contact with CO 2 . The glassification of a solvent would be detrimental to a carbon-capture process due to plugging of infrastructure, introducing a critical need to decipher the underlying principles of this phenomenon to prevent it from happening. In this work, we present the first integrated theoretical and experimental study to characterize the nano-structure of metastable and glassy states of an archetypal single-component alkanolguanidine carbon-capture solvent and assess how minute changes in atomic-level interactions convert the solvent between metastable and glass-like states. Small-angle neutron scattering and neutron diffraction coupled with small- and wide-angle X-ray scattering analysis demonstrate that minute structural changes in solution precipitae reversible aggregation of zwitterionic alkylcarbonate clusters in solution. Our findings indicate that our test system, an alkanolguanidine, exhibits a first-order phase transition, similar to a glass transition, at approximately 40 °C—close to the operating absorption temperature for post-combustion CO 2 capture processes. We anticipate that these phenomena are not specific to this system, but are present in other classes of colvents as well. We discuss how molecular-level interactions can have vast implications for solvent-based carbon-capture technologies, concluding that fortunately in this case, glassification of water-lean solvents can be avoided as long as the solvent is run above its glass transition temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Dehydration Pathway Study of Ultrathin Ni (OH) 2 Probed via In Situ X-Ray Photoelectron Spectromicroscopy

In this work, the conversion of ultrathin 2D-Ni (OH) 2 to NiO is studied using in situ X-ray absorption near edge spectroscopy at the Ni L 3 and O K edges and using variable photon energy X-ray photoelectron spectroscopy at the Ni 2p 3/2 and O 1s edges. The Ni L 3 X-ray absorption spectroscopy and corresponding 2p 3/2 X-ray photoelectron spectroscopy show the oxidation state of the Ni atom to be Ni 2+ in the course of the reaction; however, the film surface and oxygen defect structure show the presence of a large metallic Ni component before the complete disappearance of the hydroxide phase indicating oxygen vacancy formation before the completion of water desorption. O 1s spectral changes during heat treatment under ultrahigh vacuum, O 2 dosing, and H 2 O dosing suggest the spectral features are due to water desorption and adsorption. Furthermore, by comparing the relative probe depths of X-ray photoelectron spectroscopy and X-ray absorption spectroscopy, it is determined that the surface, at each step in the dehydration process, consists of a combination of Ni, NiO, and Ni (OH) 2 phases, which each contain a mixture of adsorbed hydroxyl groups. Repeated dosing with H 2 O, studied with O 1s X-ray photoelectron spectroscopy, suggests that the dissociation of water facilitates the formation of oxygen vacancies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Predictive models enhance feedstock quality of corn stover via air classification

Feedstock heterogeneity is a fundamental obstacle to cost-competitive biobased products. Agricultural products like corn stover have anatomical components that vary in their chemical composition, mechanical properties, structure, and response to chemical and biological treatments. A technique that can enrich streams in select anatomical fractions would allow a tailored deconstruction approach to increase overall process efficiency. Air classification can be leveraged for such refining, however, fundamental characterization and understanding of the particle properties that underly the physics of air classification are only modestly documented. Here, we determine fundamental particle properties including mass-to-area ratio, drag coefficient, and partition velocity that describe how anatomical tissues of corn stover behave during air classification. In this work, mass-to-area ratios of anatomical tissues vary by nearly two orders of magnitude from 2.3 mg/mm 2 for cob to 0.04 mg/mm 2 for leaf. Drag coefficients of longer, fibrous materials (i.e., rind, husk, and sheath) are shown to correlate with particle area (p-value < 0.001) whereas granular tissues (i.e., cob, pith, and leaf) correlate better with mass-to-area ratio (p-values < 0.001). When compared to experimental observations, a simulated two-stage air classification and size reduction scenario predicts the overall partitioning of anatomical tissues within 15% for pith, husk, rind, and cob tissues. The model predicts an air-classified fraction preferentially enriched in cob (purity = 20%), rind (purity = 74%), and pith (purity = 4.5%) with a mass yield of 47%. Empirical relations for these properties can be used to predict the partitioning of corn stover during air classification based on anatomical type and size.

09 BIOMASS FUELS↗
DOE OSTI2020

Resolving Triblock Terpolymer Morphologies by Vapor-Phase Infiltration

The spontaneous formation of well-organized three-dimensional (3D) nanostructures from self-assembled block copolymers (BCPs) holds promise for nanofabrication and lithography. The addition of a third block to BCPs provides access to a plethora of 3D geometries, but it remains difficult to resolve the geometry of such “three-color” structures when there is low contrast between the polymeric components at length scales of a few nm. Here, we apply vapor-phase infiltration synthesis to a silicon-containing triblock terpolymer, poly(1,1- dimethyl silacyclobutane-b-styrene-b-lactide) (PDMSB-b-PS-b-PLA or DSL) to distinguish the 3D microdomain morphologies of the two organic blocks, PLA and PS. Selective infiltration of ZnO within the PLA microdomains reveals morphologies consisting of three-color lamellae or lamellae combined with vertically aligned core-shell cylinders, depending on the volume fractions of each block. The infiltration produces ZnO nanoparticles throughout the 260 nm thickness of the DSL film, generating 3D nanocomposites containing ZnO and SiO x . These results provide a strategy for synthesizing multicomponent 3D nanostructures as well as visualizing the phase behavior of multi-block copolymers.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Operando Infrared Nanospectroscopy of the Silicon/Electrolyte Interface during Initial Stages of Solid-Electrolyte-Interphase Layer Formation

The solid electrolyte interphase (SEI) is a critical component in Li-ion batteries; however, its nanoscale structure and composition and unstable nature make it difficult to characterize and ascertain primary functional mechanisms. We use operando nanoscale Fourier transform infrared spectroscopy (nano-FTIR) with a broadband synchrotron IR source to study the SEI formation on a thin-film Si electrode at nanometer-scale spatial resolution as a function of time and voltage. By probing the Si/carbonate electrolyte interface through a 25 nm-thick amorphous Si window/electrode, we detect molecular vibrational modes within a 10s of nanometers region adjacent to the Si surface and observe that PF6 – anions react to form LiF at 0.5 V. Spatially resolved nano-FTIR spectra showcase subtle nanoscale heterogeneities in the initial solid/liquid interface and the resulting deposited LiF. With its nanoscale resolution and high chemical specificity, operando nano-FTIR provides unique insights into the dynamics and heterogeneous formation of SEIs and opens opportunities for connecting nanoscale interfacial properties to bulk performance metrics.

Dopilka, Andrew↗
DOE OSTI2022

Molecular basis for polysaccharide recognition and modulated ATP hydrolysis by the O antigen ABC transporter

O antigens are ubiquitous protective extensions of lipopolysaccharides in the extracellular leaflet of the Gram-negative outer membrane. Following biosynthesis in the cytosol, the lipid-linked polysaccharide is transported to the periplasm by the WzmWzt ABC transporter. Often, O antigen secretion requires the chemical modification of its elongating terminus, which the transporter recognizes via a carbohydrate-binding domain (CBD). Here, using components from A. aeolicus, we identify the O antigen structure with methylated mannose or rhamnose as its cap. Crystal and cryo electron microscopy structures reveal how WzmWzt recognizes this cap between its carbohydrate and nucleotide-binding domains in a nucleotide-free state. ATP binding induces drastic conformational changes of its CBD, terminating interactions with the O antigen. ATPase assays and site directed mutagenesis reveal reduced hydrolytic activity upon O antigen binding, likely to facilitate polymer loading into the ABC transporter. Our results elucidate critical steps in the recognition and translocation of polysaccharides by ABC transporters.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Application of a long short-term memory for deconvoluting conductance contributions at charged ferroelectric domain walls

Ferroelectric domain walls are promising quasi-2D structures that can be leveraged for miniaturization of electronics components and new mechanisms to control electronic signals at the nanoscale. Despite the significant progress in experiment and theory, however, most investigations on ferroelectric domain walls are still on a fundamental level, and reliable characterization of emergent transport phenomena remains a challenging task. Here, we apply a neural-network-based approach to regularize local I ( V )-spectroscopy measurements and improve the information extraction, using data recorded at charged domain walls in hexagonal (Er 0.99 ,Zr 0.01 )MnO 3 as an instructive example. Using a sparse long short-term memory autoencoder, we disentangle competing conductivity signals both spatially and as a function of voltage, facilitating a less biased, unconstrained and more accurate analysis compared to a standard evaluation of conductance maps. The neural-network-based analysis allows us to isolate extrinsic signals that relate to the tip-sample contact and separating them from the intrinsic transport behavior associated with the ferroelectric domain walls in (Er 0.99 ,Zr 0.01 )MnO 3 . Our work expands machine-learning-assisted scanning probe microscopy studies into the realm of local conductance measurements, improving the extraction of physical conduction mechanisms and separation of interfering current signals.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Effect of graphitic anode surface functionalization on the structure and dynamics of electrolytes at the interface

Surface termination on a graphitic surface and the type of electrolytes in lithium-ion batteries (LIBs) play an important part in determining the structure, composition, and thus, the quality of the emergent solid electrolyte interphase. In this paper, we analyze the structure and dynamics of electrolyte molecules in multi-component electrolyte with varying species compositions combinatorially paired with four different graphitic surfaces terminated with hydrogen, hydroxyl, carbonyl, and carboxyl to explore the interplay between surface chemistry and electrolyte dynamics at electrode/electrolyte interfaces. Addition of dimethyl carbonate and fluoroethylene carbonate brought substantial changes in the ethylene carbonate (EC) and LiPF6 surface population density for hydroxyl and carbonyl surfaces. Strong density oscillation and drastic slowing of the dynamics of the electrolyte molecules at the interface are reported for all the systems. While these observations are universal, carboxyl surfaces have the strongest local and long-range effects. Characterization of the average dipole direction at the interface shows strong orientational preferences of ethylene carbonate molecules. EC molecules are preferred to be oriented either almost parallel or perpendicular to the hydroxyl surface, are tilted between parallel and perpendicular with a higher angle of incidence of the dipole vs surface normal on the carbonyl surface than on the hydroxyl surface, and are oriented perpendicularly against the carboxyl surface. These differences highlight the significant effect of graphite surface termination on the dynamics of the electrolytes and provide insight into the complex interplays between electrolyte species and graphite anode in LIBs.

Rustam, Sabiha (ORCID:0000000224248153)↗
DOE OSTI2021

Surface equilibration mechanism controls the molecular packing of glassy molecular semiconductors at organic interfaces

Significance Because glasses are nonequilibrium materials, even a single-component system has an enormous number of distinct glass structures. Physical vapor deposition (PVD) is an important tool for preparing a wide range of these glasses. While the substrate can influence structure for hundreds of nanometers for crystalline and liquid crystalline systems, little is known about the structure of PVD glasses near an underlying substrate. This is important for organic electronics, as layers of PVD glasses as thin as 10 nm are used as active elements in organic light-emitting diodes, and molecular packing is vital to performance. We show that the free surface controls molecular packing of PVD glasses near a buried interface rather than the substrate, in sharp contrast with crystalline systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Interacting dark sector within ETHOS: Cosmological constraints from SPT cluster abundance with DES and HST weak lensing data

We use galaxy cluster abundance measurements from the South Pole Telescope enhanced by multicomponent matched filter confirmation and complemented with mass information obtained using weak-lensing data from Dark Energy Survey Year 3 (DES Y3) and targeted Hubble Space Telescope observations for probing deviations from the cold dark matter paradigm. Concretely, we consider a class of dark sector models featuring interactions between dark matter (DM) and a dark radiation (DR) component within the framework of the effective theory of structure formation (ETHOS). We focus on scenarios that lead to power suppression over a wide range of scales, and thus can be tested with data sensitive to large scales, as realized, for example, for DM–DR interactions following from an unbroken non-Abelian 𝑆⁢𝑈⁡(𝑁) gauge theory (interaction rate with power-law index 𝑛 = 0 within the ETHOS parametrization). Cluster abundance measurements are mostly sensitive to the amount of DR interacting with DM, parametrized by the ratio of DR temperature to the cosmic microwave background (CMB) temperature, 𝜉 DR = 𝑇 DR /𝑇 CMB . We find an upper limit 𝜉 DR < 17% at 95% credibility. When the cluster data are combined with Planck 2018 CMB data along with baryon acoustic oscillation (BAO) measurements we find 𝜉 DR < 10%, corresponding to a limit on the abundance of interacting DR that is around 3 times tighter than that from CMB + BAO data alone. We also discuss the complementarity of weak lensing informed cluster abundance studies with probes sensitive to smaller scales, explore the impact on our analysis of massive neutrinos, and comment on a slight preference for the presence of a nonzero interacting DR abundance, which enables a physical solution to the 𝑆 8 tension.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Probing the nonexponential decay regime in open quantum systems

The most important law of radioactivity is that of the exponential decay. In the realm of quantum mechanics, however, this decay law is neither rigorous nor fundamental. The deviations from the exponential decay have been observed experimentally at the early stage of a decay process, but there is little evidence for non-exponential behavior at long times. Yet such long-term non-exponentiality is expected theoretically to probe the non-resonant background components of the initial wave function which preserve the structural interference and the memory of how the state was created. In this paper, we propose new observables that can be used for experimental investigations of the post-exponential decay regime, including the decay of threshold resonances, particle correlations in three-body decays, and interference between near-lying resonances. While the specific examples presented in this work pertain to atomic nuclei, the properties of non-exponential decay are generic, i.e., they apply to other many-body open quantum systems, such as hadrons, atoms, molecules, and nanostructures.

6 ≤ A ≤ 19↗
DOE OSTI2021

Multiscale Data-Driven Seismic Full-Waveform Inversion With Field Data Study

Seismic full-waveform inversion (FWI), which uses iterative methods to estimate high-resolution subsurface models from seismograms, is a powerful imaging technique in exploration geophysics. In recent years, the computational cost of FWI has grown exponentially due to the increasing size and resolution of seismic data. Moreover, it is a nonconvex problem and can encounter local minima due to the limited accuracy of the initial velocity models or the absence of low frequencies in the measurements. To overcome these computational issues, we develop a multiscale data-driven FWI method based on fully convolutional networks (FCNs). In preparing the training data, we first develop a real-time style transform method to create a large set of synthetic subsurface velocity models from natural images. We then develop two convolutional neural networks with encoder-decoder structures to reconstruct the low- and high-frequency components of the subsurface velocity models, separately. To validate the performance of our data-driven inversion method and the effectiveness of the synthesized training set, we compare it with conventional physics-based waveform inversion approaches using both synthetic and field data. Finally, these numerical results demonstrate that, once our model is fully trained, it can significantly reduce the computation time and yield more accurate subsurface velocity models in comparison with conventional FWI.

58 GEOSCIENCES↗
DOE OSTI2020

The plant endoplasmic reticulum: an organized chaos of tubules and sheets with multiple functions

The endoplasmic reticulum is a fascinating organelle at the core of the secretory pathway. It is responsible for the synthesis of one third of the cellular proteome and, in plant cells, it produces receptors and transporters of hormones as well as the proteins responsible for the biosynthesis of critical components of a cellulosic cell wall. The endoplasmic reticulum structure resembles a spider-web network of interconnected tubules and cisternae that pervades the cell. The study of the dynamics and interaction of this organelles with other cellular structures such as the plasma membrane, the Golgi apparatus and the cytoskeleton, have been permitted by the implementation of fluorescent protein and advanced confocal imaging. In this review,we report on the findings that contributed towards the understanding of the endoplasmic reticulum morphology and function with the aid of fluorescent proteins, focusing on the contributions provided by pioneering work from the lab of the late Professor Chris Hawes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Structure functions from renormalization group improved small x evolution

Abstract We perform the fit to the structure function $$F_2$$ F 2 data from HERA including terms due to the resummation at small x . The equation for the unintegrated gluon density is solved, previously established within the renormalization group improved small x framework. We find very good description of the structure function $$F_2$$ F 2 and its charm component $$F_2^c$$ F 2 c . The resulting unintegrated gluon density is found to be consistent with the calculations based on similar approaches available in the literature, with only slightly higher intercept value.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Uncertainty Quantification of Metal Additive Manufacturing Processing Conditions Through the use of Exascale Computing

Metal additive manufacturing (AM) is a disruptive manufacturing technology that opens the design space for parts outside those possible from traditional manufacturing methods. In order to accelerate industry and R&D needs to certify AM parts, the Exascale Additive Manufacturing project (ExaAM) has developed a suite of exascale-ready computational tools to model the process-to-structure-to-properties (PSP) relationship for additively manufactured metal components. One such tool is an uncertainty quantification (UQ) pipeline to quantify the effect that uncertainty in processing conditions has on local mechanical responses. We present an overview of this pipeline and its required simulation and workflow codes. Using the Oak Ridge National Laboratory’s (ORNL) exascale computer, Frontier, we utilize this pipeline to cross multiple length and time scales to predict the local mechanical response of a location within a complex AM bridge part, AMB2018-01 produced by the National Institute of Standards and Technology (NIST) as part of their 2018 AM-Bench test series. Our results are then compared to experimental mechanical tests of parts from the NIST build to quantify the error in the ExaAM UQ workflow.

Carson, Robert↗
DOE OSTI2021

krowkee

krowkee is a toolkit for scalably and efficiently summarizing many data streams in distributed memory. krowkee is intended for applications where one needs to summarize huge loosely structured data, such as matrices or graphs, where individual components such rows/columns or vertex adjacency information are impractical to store and directly inspect. krowkee ingests these objects as data streams - unstructured, arbitrarily ordered lists of updates - and accumulates summaries thereof in the form of data sketches.

Dunton, AlecM.↗
DOE OSTI2023

Sustainable chemistry with plasmonic photocatalysts

There is a pressing global need to increase the use of renewable energy sources and limit greenhouse gas emissions. Towards this goal, highly efficient and molecularly selective chemical processes that operate under mild conditions are critical. Plasmonic photocatalysis uses optically resonant metallic nanoparticles and their resulting plasmonic, electronic, and phononic light-matter interactions to drive chemical reactions. The promise of simultaneous high-efficiency and product-selective reactions with plasmon photocatalysis provides a compelling opportunity to rethink how chemistry is achieved. Plasmonic nanoparticles serve as nanoscale ‘antennas’ that enable strong light–matter interactions, surpassing the light-harvesting capabilities one would expect purely from their size. Complex composite structures, combining engineered light harvesters with more chemically active components, are a focal point of current research endeavors. In this review, we provide an overview of recent advances in plasmonic catalysis. We start with a discussion of the relevant mechanisms in photochemical transformations and explain hot-carrier generation and distributions from several ubiquitous plasmonic antennae. Then we highlight three important types of catalytic processes for sustainable chemistry: ammonia synthesis, hydrogen production and CO 2 reduction. To help elucidate the reaction mechanism, both state-of-art electromagnetic calculations and quantum mechanistic calculations are discussed. This review provides insights to better understand the mechanism of plasmonic photocatalysis with a variety of metallic and composite nanostructures toward designing and controlling improved platforms for green chemistry in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗