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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Influence of temperature on accessible pyrolysis pathways of homopolymerized bisphenol A/F epoxies and copolymers

Understanding the thermal pyrolysis of epoxies and their copolymers is important for identifying structural changes resultant from thermal transients, enabling identification of failure modes of high-performance composite materials. This work expands our understanding of the thermal pyrolysis of cured epoxies and the role of temperature and composition on products, pathways, and relative rates. Numerous researchers have explored the pyrolysis of bisphenol A (BPA) epoxy. Significantly fewer have studied bisphenol F (BPF), and copolymers of BPA and BPF have been neglected. In this work, a pyrolysis gas chromatography mass spectrometer (PY-GC-MS) was used to investigate the degradation mechanism of homopolymerized BPA, BPF epoxies and their copolymers. Additionally, for polymer identification, pyrolysis >450 °C resulted in the most extensive fragmentation and is useful for material identification, though lower temperatures show different degradation product profiles that provide mechanistic insight into thermal degradation pathways. Temperature greatly influences the accessible pyrolysis pathways of BPA, revealing dual mechanisms of formation for products p-isopropylphenol and p-isopropenylphenol. For BPF at low pyrolysis temperature the p,p-bisphenol F isomer is produced at significantly lower relative abundance compared to the abundance at higher temperatures tested, but production of the other two isomers changes little with respect to temperature. This suggests the epoxy components consisting of the p,p-bisphenol F isomer have higher thermal stability. Overall, the copolymer epoxies were found to have similar degradation products in stoichiometric distributions. The major exception was the formation of the p,p-bisphenol F isomer, which shows evidence of thermal stabilizing effects from addition of BPA epoxy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Evolution and Degradation Patterns of Electrochemical Cells Based on the Analysis of Interfacial Phenomena at Li Metal Anode/Electrolyte Interfaces

In this work, we report the results of a theoretical–computational analysis of the solid electrolyte interphase (SEI) growth and degradation dynamics occurring in lithium metal batteries during cycling. We use ab initio-kinetic Monte Carlo simulations to generate a synthetic data set, which is analyzed by machine learning methods. We aim to determine: (i) how modifications in interfacial interaction energies between solid electrolyte interphase (SEI) blocks and between Li ions and SEI facets impact the Coulombic efficiency (CE) of the battery and (ii) what factors, including reactions, microscopic transport, and other interfacial events, may lead to cell performance “failure” during prolonged charge and discharge cycles, signaled as a sharp decay in the CE over cycling. The demonstration of our approach is done on a cell including a Li metal surface interfacing with a previously introduced state-of-the-art electrolyte, and the idea can be applied to any electrochemical system. Outcomes include the identification of the leading chemical, physical, and structural variables causing cell failure and relating them to the electrolyte formulation, thus paving the way to future more refined analysis and electrolyte design.

batteries↗
DOE OSTI2024

Terahertz parametric amplification as a reporter of exciton condensate dynamics

Condensates are a hallmark of emergence in quantum materials with superconductors and charge density wave as prominent examples. An excitonic insulator (EI) is an intriguing addition to this library, exhibiting spontaneous condensation of electron-hole pairs. However, condensate observables can be obscured through parasitic coupling to the lattice. Time-resolved terahertz (THz) spectroscopy can disentangle such obscurants through measurement of the quantum dynamics. We target Ta 2 NiSe 5 , a putative room-temperature EI where electron-lattice coupling dominates the structural transition (T c = 326 K), hindering identification of excitonic correlations. A pronounced increase in the THz reflectivity manifests following photoexcitation and exhibits a BEC-like temperature dependence. This occurs well below the T c , suggesting a novel approach to monitor exciton condensate dynamics. Nonetheless, dynamic condensate-phonon coupling remains as evidenced by peaks in the enhanced reflectivity spectrum at select infrared-active phonon frequencies. This indicates that parametric reflectivity enhancement arises from phonon squeezing, validated using Fresnel-Floquet theory and density functional calculations. In conclusion, our results highlight that coherent dynamics can drive parametric stimulated emission with concomitant possibilities, including entangled THz photon generation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Spotlight: efficient automated global optimization in rietveld analysis of diffraction data

Performing reliable Rietveld analysis on tens or hundreds of powder diffraction datasets from parametric or time-resolved experiments often poses a bottleneck in extracting meaningful results from the data. While automated analysis of data has recently been demonstrated, high temperature annealing studies, during which phase transformations occur and lattice parameters may change due to repartitioning of elements, are prime examples where automation by a simple phase identification from a database of room temperature structures or automation by sequential refinements is likely to fail. To enable reliable, efficient, automated Rietveld analysis, we present a Python package named Spotlight , building on established Rietveld packages such as MAUD, GSAS , or GSAS-II , which extends the refinement of best fit parameters to a global optimization using an ensemble of optimizers leveraging hierarchical parallel execution on high-performance computing clusters. Spotlight further enables the efficient design of refinement plans through the iterative automated machine-learning of a surrogate for the refinement on which the global optimizations are performed until results from the surrogate converge to the response surface data. We demonstrate Spotlight with the analysis of uranium molybdenum and Ti–6Al–4V datasets, as well as in two open-source tutorials analyzing aluminium oxide and lead sulphate.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Cryo-electron tomography provides topological insights into mutant huntingtin exon 1 and polyQ aggregates

Huntington disease (HD) is a neurodegenerative trinucleotide repeat disorder caused by an expanded poly-glutamine (polyQ) tract in the mutant huntingtin (mHTT) protein. The formation and topology of filamentous mHTT inclusions in the brain (hallmarks of HD implicated in neurotoxicity) remain elusive. Using cryo-electron tomography and subtomogram averaging, here we show that mHTT exon 1 and polyQ-only aggregates in vitro are structurally heterogenous and filamentous, similar to prior observations with other methods. Yet, we find filaments in both types of aggregates under ~2 nm in width, thinner than previously reported, and regions forming large sheets. In addition, our data show a prevalent subpopulation of filaments exhibiting a lumpy slab morphology in both aggregates, supportive of the polyQ core model. This provides a basis for future cryoET studies of various aggregated mHTT and polyQ constructs to improve their structure-based modeling as well as their identification in cells without fusion tags.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Active Learning-driven Quantitative Synthesis-Structure-Property Relations for Improving Performance and Revealing Active Sites of Nitrogen-Doped Carbon for the Hydrogen Evolution Reaction

While quantitative structure-properties relations (QSPRs) have been developed successfully in multiple fields, catalyst synthesis affects structure and in turn performance, making simple QSPRs inadequate. Furthermore, catalysts often have multiple active sites preventing one from obtaining insights into structure-property relations. Here, we develop a data-driven quantitative synthesis-structure-property relation (QS2PRs) methodology to elucidate correlations between catalyst synthesis conditions, structural properties as well as observed performance and to provide fundamental insights into active sites and a systematic way to optimize practical catalysts. Here, we demonstrate the approach to the synthesis of nitrogen-doped catalysts (NDC) made via pyrolysis for the performance of the electrochemical hydrogen evolution reaction (HER), quantified by the onset potential and the current density. We determine crystallinity, nitrogen species type and fraction, surface area, and pore structure of the NDC’s using XRD, XPS, and BET characterization. We demonstrated that an active learning-based optimization combined with various elementary machine learning tools (regression, principal component analysis, partial least squares) can efficiently identify optimum pyrolysis conditions to tune structural characteristics and performance with concomitant savings in materials and experimental time. Unlike previous reports on the importance of pyridinic or graphitic nitrogen, we discover that the electrochemical performance is not driven by a single catalyst property; rather, it arises from a multivariate influence of nitrogen dopants, pore structure and disorder in the NDC materials. Identification of active sites can help mechanistic understanding and further catalyst improvement.

42 ENGINEERING↗
DOE OSTI2023

The spontaneous symmetry breaking in Ta 2 NiSe 5 is structural in nature

The excitonic insulator is an electronically driven phase of matter that emerges upon the spontaneous formation and Bose condensation of excitons. Detecting this exotic order in candidate materials is a subject of paramount importance, as the size of the excitonic gap in the band structure establishes the potential of this collective state for superfluid energy transport. However, the identification of this phase in real solids is hindered by the coexistence of a structural order parameter with the same symmetry as the excitonic order. Only a few materials are currently believed to host a dominant excitonic phase, Ta 2 NiSe 5 being the most promising. Here, we test this scenario by using an ultrashort laser pulse to quench the broken-symmetry phase of this transition metal chalcogenide. Tracking the dynamics of the material’s electronic and crystal structure after light excitation reveals spectroscopic fingerprints that are compatible only with a primary order parameter of phononic nature. We rationalize our findings through state-of-the-art calculations, confirming that the structural order accounts for most of the gap opening. Our results suggest that the spontaneous symmetry breaking in Ta 2 NiSe 5 is mostly of structural character, hampering the possibility to realize quasi-dissipationless energy transport.

Science & Technology - Other Topics↗
DOE OSTI2024

Contact-dependent growth inhibition (CDI) systems deploy a large family of polymorphic ionophoric toxins for inter-bacterial competition

Contact-dependent growth inhibition (CDI) is a widespread form of inter-bacterial competition mediated by CdiA effector proteins. CdiA is presented on the inhibitor cell surface and delivers its toxic C-terminal region (CdiA-CT) into neighboring bacteria upon contact. Inhibitor cells also produce CdiI immunity proteins, which neutralize CdiA-CT toxins to prevent auto-inhibition. Here, we describe a diverse group of CDI ionophore toxins that dissipate the transmembrane potential in target bacteria. These CdiA-CT toxins are composed of two distinct domains based on AlphaFold2 modeling. The C-terminal ionophore domains are all predicted to form five-helix bundles capable of spanning the cell membrane. The N-terminal "entry" domains are variable in structure and appear to hijack different integral membrane proteins to promote toxin assembly into the lipid bilayer. The CDI ionophores deployed by E. coli isolates partition into six major groups based on their entry domain structures. Comparative sequence analyses led to the identification of receptor proteins for ionophore toxins from groups 1 & 3 (AcrB), group 2 (SecY) and groups 4 (YciB). Using forward genetic approaches, we identify novel receptors for the group 5 and 6 ionophores. Group 5 exploits homologous putrescine import proteins encoded by puuP and plaP, and group 6 toxins recognize di/tripeptide transporters encoded by paralogous dtpA and dtpB genes. Finally, we find that the ionophore domains exhibit significant intra-group sequence variation, particularly at positions that are predicted to interact with CdiI. Accordingly, the corresponding immunity proteins are also highly polymorphic, typically sharing only ~30% sequence identity with members of the same group. Competition experiments confirm that the immunity proteins are specific for their cognate ionophores and provide no protection against other toxins from the same group. The specificity of this protein interaction network provides a mechanism for self/nonself discrimination between E. coli isolates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Quantitative multi-image analysis in metals research

Abstract Quantitative multi-image analysis (QMA) is the systematic extraction of new information and insight through the simultaneous analysis of multiple, related images. We present examples illustrating the potential for QMA to advance materials research in multi-image characterization, automatic feature identification, and discovery of novel processing-structure–property relationships. We conclude by discussing opportunities and challenges for continued advancement of QMA, including instrumentation development, uncertainty quantification, and automatic parsing of literature data. Graphical abstract

36 MATERIALS SCIENCE↗
DOE OSTI2024

African Swine Fever Virus Protein–Protein Interaction Prediction

The African swine fever virus (ASFV) is an often deadly disease in swine and poses a threat to swine livestock and swine producers. With its complex genome containing more than 150 coding regions, developing effective vaccines for this virus remains a challenge due to a lack of basic knowledge about viral protein function and protein–protein interactions between viral proteins and between viral and host proteins. In this work, we identified ASFV-ASFV protein–protein interactions (PPIs) using artificial intelligence-powered protein structure prediction tools. We benchmarked our PPI identification workflow on the Vaccinia virus, a widely studied nucleocytoplasmic large DNA virus, and found that it could identify gold-standard PPIs that have been validated in vitro in a genome-wide computational screening. We applied this workflow to more than 18,000 pairwise combinations of ASFV proteins and were able to identify seventeen novel PPIs, many of which have corroborating experimental or bioinformatic evidence for their protein–protein interactions, further validating their relevance. Two protein–protein interactions, I267L and I8L, I267L__I8L, and B175L and DP79L, B175L__DP79L, are novel PPIs involving viral proteins known to modulate host immune response.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1972

A first look at geological aspects of ERTS imagery of Wyoming

There are no author-identified significant results in this report. The analysis of six MSS-5 frames covering most of the western half of Wyoming is discussed. The frames under consideration covered the following areas: (1) Rock Springs, (2) Western Wind River Basin, and (3) Bighorn Basin-Absarokas Mountains. Miscellaneous observations concerning identification of natural and man-made structures are included.

Short, N.↗
NASA NTRS1973

Identification of an object by input and output spectral characteristics

The problem is discussed of identification of a linear object of known structure, the movement of which is described by a system of differential equations of the type y = Ay + Bu, where y is an n-dimensional output vector, u is an m-dimensional vector of stationary, random disturbances (inputs), A and B are matrices of unknown parameters of the dimension, n x n and n x m, respectively. The spectral and reciprocal spectral densities of the inputs and outputs are used as the initial information on the object.

Redko, S. F.↗
NASA NTRS1977

The distribution of seismic velocities and attenuation in the earth

Estimates of the radial distribution of seismic velocities and density and of seismic attenuation within the earth are obtained through inversion of body wave, surface wave, and normal mode data. The effect of attenuation related dispersion on gross earth structure, and on the reliability of eigenperiod identifications is discussed. The travel time baseline discrepancies between body waves and free oscillation models are examined and largely resolved.

Hart, R. S.↗
NASA NTRS1976

A reliable dual-redundant sensor FDI system for the NASA F8C-DFBW aircraft

In this paper we outline the structure of a sensor failure detection and identification (FDI) system designed for the NASA F8C DFBW aircraft. The system is for use in a dual-redundant environment, and it takes maximal advantage of all functional and kinematic relationships among the sensed variables. The technique is reliable in that we have designed the system to account for a variety of unmodeled effects and have introduced a new concept - the quality sequential probability ratio (QSPR) - that provides a useful measure of our confidence in each test. The methodology used for determining detector parameters and the 'outer loop logic' for combining the various sources of information are described.

Deckert, J. C.↗
NASA NTRS1981

The reduced order model problem in distributed parameter systems adaptive identification and control

The basic assumption that a large space structure can be decoupled preceding the application of reduced order active control was considered and alternative solutions to the control of such structures (in contrast to the strict modal control) were investigated. The transfer function matrix from the actuators to the sensors was deemed to be a reasonable candidate. More refined models from multivariable systems theory were studied and recent results in the multivariable control field were compared with respect to theoretical deficiencies and likely problems in application to large space structures.

Johnson, C. R., Jr.↗
NASA NTRS1981

LANDSAT 3 return beam vidicon response artifacts: A report on RBV photographic product characteristics and quality coding system

Analysis of large volumes of LANDSAT 3 RBV digital data that were converted to photographic form led to the firm identification of several visible artifacts (objects or structures not normally present, but producted by an external agency or action) in the imagery. These artifacts were identified, categorized, and traced directly to specific sensor response characteristics. None of these artifacts is easily removed and all cases remain under active study of possible future enhancement. The seven generic categories of sensor response artifacts identified to date include: (1) shading and stairsteps; (2) corners out of focus; (3) missing reseaus; (4) reseau distortion and data distortion; (5) black vertical line; (6) grain effect; and (7) faceplate contamination. An additional category under study, but not yet determined to be caused by sensor response, is a geometric anomaly. Examples of affected imagery are presented to assist in distinguishing between image content and innate defects caused by the sensor system.

Clark, B. P.↗