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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Restructuring of Enterococcus faecalis biofilm architecture in response to antibiotic-induced stress

Bacterial biofilms are intrinsically resistant to antimicrobial treatment, which contributes to microbial persistence in clinical infections. Enterococcus faecalis is an opportunistic pathogen that readily forms biofilms and is the most prevalent enterococcal species identified in healthcare-associated infections. Since intrinsic resistance to multiple antibiotics is common for enterococci, and antibiotic resistance is elevated in biofilm populations, it is imperative to understand the mechanisms involved. Previously, we identified two glycosyltransferase genes whose disruption resulted in impaired nascent biofilm formation in the presence of antibiotic concentrations subinhibitory for parent growth and biofilm formation. The glycosyltransferases are involved in synthesis of the cell-wall-associated rhamnopolysaccharide Epa. Here we examined the effect of epa mutations on the temporal development of E. faecalis biofilms, and on the effects of antibiotics on pre-formed biofilms using scanning electron microscopy. We show that ΔepaOX mutant cells arrange into complex multidimensional biofilms independent of antibiotic exposure, while parent cells form biofilms that are monolayers in the absence of antibiotics. Remarkably, upon exposure to antibiotics parent biofilm cells restructure into complex three-dimensional biofilms resembling those of the ΔepaOX mutant without antibiotics. All biofilms exhibiting complex cellular architectures were less structurally stable than monolayer biofilms, with the biofilm cells exhibiting increased detachment. Our results indicate that E. faecalis biofilms restructure in response to cellular stress whether induced by antibiotics in the case of parent cells, or by deficiencies in Epa composition for the ΔepaOX strain. The data demonstrate a link between cellular architecture and antibiotic resistance of E. faecalis biofilms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Tensor factorization for elucidating mechanisms of piezoresponse relaxation via dynamic Piezoresponse Force Spectroscopy

Spatially resolved time and voltage-dependent polarization dynamics in PbTiO 3 thin films is explored using dynamic piezoresponse force microscopy (D-PFM) in conjunction with interferometric displacement sensing. This approach gives rise to 4D data sets containing information on bias-dependent relaxation dynamics at each spatial location without long-range electrostatic artifacts. To interpret these data sets in the absence of defined physical models, we employ a non-negative tensor factorization method which clearly presents the data as a product of simple behaviors allowing for direct physics interpretation. Correspondingly, we perform phase-field modeling finding the existence of ‘hard’ and ‘soft’ domain wall edges. This approach can be extended to other multidimensional spectroscopies for which even exploratory data analysis leads to unsatisfactory results due to many components in the decomposition.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Gaussian process analysis of electron energy loss spectroscopy data: multivariate reconstruction and kernel control

Abstract Advances in hyperspectral imaging including electron energy loss spectroscopy bring forth the challenges of exploratory and physics-based analysis of multidimensional data sets. The multivariate linear unmixing methods generally explore similarities in the energy dimension, but ignore correlations in the spatial domain. At the same time, Gaussian process (GP) explicitly incorporate spatial correlations in the form of kernel functions but is computationally intensive. Here, we implement a GP method operating on the full spatial domain and reduced representations in the energy domain. In this multivariate GP, the information between the components is shared via a common spatial kernel structure, while allowing for variability in the relative noise magnitude or image morphology. We explore the role of kernel constraints on the quality of the reconstruction, and suggest an approach for estimating them from the experimental data. We further show that spatial information contained in higher-order components can be reconstructed and spatially localized.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Fast Bayesian optimization of Needle-in-a-Haystack problems using zooming memory-based initialization (ZoMBI)

Abstract Needle-in-a-Haystack problems exist across a wide range of applications including rare disease prediction, ecological resource management, fraud detection, and material property optimization. A Needle-in-a-Haystack problem arises when there is an extreme imbalance of optimum conditions relative to the size of the dataset. However, current state-of-the-art optimization algorithms are not designed with the capabilities to find solutions to these challenging multidimensional Needle-in-a-Haystack problems, resulting in slow convergence or pigeonholing into a local minimum. In this paper, we present a Zooming Memory-Based Initialization algorithm, entitled ZoMBI, that builds on conventional Bayesian optimization principles to quickly and efficiently optimize Needle-in-a-Haystack problems in both less time and fewer experiments. The ZoMBI algorithm demonstrates compute time speed-ups of 400× compared to traditional Bayesian optimization as well as efficiently discovering optima in under 100 experiments that are up to 3× more highly optimized than those discovered by similar methods.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Data-driven computational prediction and experimental realization of exotic perovskite-related polar magnets

Rational design of technologically important exotic perovskites is hampered by the insufficient geometrical descriptors and costly and extremely high-pressure synthesis, while the big-data driven compositional identification and precise prediction entangles full understanding of the possible polymorphs and complicated multidimensional calculations of the chemical and thermodynamic parameter space. Here we present a rapid systematic data-mining-driven approach to design exotic perovskites in a high-throughput and discovery speed of the A 2 BB ’O 6 family as exemplified in A 3 TeO 6 . The magnetoelectric polar magnet Co 3 TeO 6 , which is theoretically recognized and experimentally realized at 5 GPa from the six possible polymorphs, undergoes two magnetic transitions at 24 and 58 K and exhibits helical spin structure accompanied by magnetoelastic and magnetoelectric coupling. We expect the applied approach will accelerate the systematic and rapid discovery of new exotic perovskites in a high-throughput manner and can be extended to arbitrary applications in other families.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nanoscopic strain evolution in single-crystal battery positive electrodes

Single-crystal Ni-rich layered oxides (SC-NMC) with a grain-boundary-free configuration have effectively addressed the long-standing cracking issue of conventional polycrystalline Ni-rich materials (PC-NMC) in lithium-ion batteries, prompting a shift in optimization strategies. However, continued reliance on anisotropic lattice volume change—a well-established failure indicator in PC-NMC—as a metric for understanding strain and guiding compositional design for SC-NMC becomes controversial. Here, in this study, by leveraging multiscale diagnostic techniques, we unravelled the distinct nanoscopic strain evolution in SC-NMC during battery operation, challenging the conventional composition-driven strategies and mechanical degradation indicators used for PC-NMC. Through particle-level chemomechanical analysis, we reveal a decoupling between mechanical stability and lattice volume change in SC-NMC, identifying that structural instability in SC materials is primarily driven by multidimensional lattice distortions induced by kinetics-driven reaction heterogeneity and progressively deactivating chemical phases. Using this mechanical failure mode, we redefine the roles of cobalt and manganese in maintaining mechanical stability. Unlike cobalt’s detrimental role in PC-NMC, we find cobalt to be critical in enhancing the longevity of SC-NMC by mitigating localized strain along the extended diffusion pathway, whereas manganese exacerbates mechanical degradation.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Coherent soft X-ray pulses from an echo-enabled harmonic generation free-electron laser

It is known that X-ray free-electron lasers (FELs), which amplify light emitted by a relativistic electron beam, are extending nonlinear optical techniques to shorter wavelengths, adding element specificity by exciting and probing electronic transitions from core levels. These techniques would benefit tremendously from having a stable FEL source, generating spectrally pure and wavelength-tunable pulses. Here, we show that such requirements can be met by operating the FEL in the so-called echo-enabled harmonic generation (EEHG) configuration. Here, two external conventional lasers are used to precisely tailor the longitudinal phase space of the electron beam before emission of X-rays. We demonstrate high-gain EEHG lasing producing stable, intense, nearly fully coherent pulses at wavelengths as short as 5.9 nm (~211 eV) at the FERMI FEL user facility. Low sensitivity to electron-beam imperfections and observation of stable, narrow-band, coherent emission down to 2.6 nm (~474 eV) make the technique a prime candidate for generating laser-like pulses in the X-ray spectral region, opening the door to multidimensional coherent spectroscopies at short wavelengths.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Quantum coherence tomography of light-controlled superconductivity

The coupling between superconductors and oscillation cycles of light pulses, i.e., lightwave engineering, is an emerging control concept for superconducting quantum electronics. Although progress has been made towards terahertz-driven superconductivity and supercurrents, the interactions able to drive non-equilibrium pairing are still poorly understood, partially due to the lack of measurements of high-order correlation functions. In particular, the sensing of exotic collective modes that would uniquely characterize light-driven superconducting coherence, in a way analogous to the Meissner effect, is very challenging but much needed. Here we report the discovery of parametrically driven superconductivity by light-induced order-parameter collective oscillations in iron-based superconductors. The time-periodic relative phase dynamics between the coupled electron and hole bands drives the transition to a distinct parametric superconducting state out-of-equalibrium. This light-induced emergent coherence is characterized by a unique phase–amplitude collective mode with Floquet-like sidebands at twice the Higgs frequency. We measure non-perturbative, high-order correlations of this parametrically driven superconductivity by separating the terahertz-frequency multidimensional coherent spectra into pump–probe, Higgs mode and bi-Higgs frequency sideband peaks. We find that the higher-order bi-Higgs sidebands dominate above the critical field, which indicates the breakdown of susceptibility perturbative expansion in this parametric quantum matter.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Probing inhomogeneous cuprate superconductivity by terahertz Josephson echo spectroscopy

Abstract Inhomogeneities crucially influence the properties of quantum materials, yet methods that can measure them remain limited and can access only a fraction of relevant observables. For example, local probes such as scanning tunnelling microscopy have documented that the electronic properties of cuprate superconductors are inhomogeneous over nanometre length scales. However, complementary techniques that can resolve higher-order correlations are needed to elucidate the nature of these inhomogeneities. Furthermore, local tunnelling probes are often effective only far below the critical temperature. Here we develop a two-dimensional terahertz spectroscopy method to measure Josephson plasmon echoes from an interlayer superconducting tunnelling resonance in a near-optimally doped cuprate. The technique allows us to study the multidimensional optical response of the interlayer Josephson coupling in the material and disentangle intrinsic lifetime broadening from extrinsic inhomogeneous broadening for interlayer superconducting tunnelling. We find that inhomogeneous broadening persists up to a substantial fraction of the critical temperature, above which this is overcome by the thermally increased lifetime broadening.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Chemical screening by time-resolved X-ray scattering to discover allosteric probes

Abstract Drug discovery relies on efficient identification of small-molecule leads and their interactions with macromolecular targets. However, understanding how chemotypes impact mechanistically important conformational states often remains secondary among high-throughput discovery methods. Here, we present a conformational discovery pipeline integrating time-resolved, high-throughput small-angle X-ray scattering (TR-HT-SAXS) and classic fragment screening applied to allosteric states of the mitochondrial import oxidoreductase apoptosis-inducing factor (AIF). By monitoring oxidized and X-ray-reduced AIF states, TR-HT-SAXS leverages structure and kinetics to generate a multidimensional screening dataset that identifies fragment chemotypes allosterically stimulating AIF dimerization. Fragment-induced dimerization rates, quantified with time-resolved SAXS similarity analysis ( k VR ), capture structure–activity relationships (SAR) across the top-ranked 4-aminoquinoline chemotype. Crystallized AIF–aminoquinoline complexes validate TR-SAXS-guided SAR, supporting this conformational chemotype for optimization. AIF–aminoquinoline structures and mutational analysis reveal active site F482 as an underappreciated allosteric stabilizer of AIF dimerization. This conformational discovery pipeline illustrates TR-HT-SAXS as an effective technology for targeting chemical leads to important macromolecular states.

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

Accelerated cryo-EM-guided determination of three-dimensional RNA-only structures

The discovery and design of biologically important RNA molecules is outpacing three-dimensional structural characterization. In this work, we demonstrate that cryo-electron microscopy can routinely resolve maps of RNA-only systems and that these maps enable subnanometer-resolution coordinate estimation when complemented with multidimensional chemical mapping and Rosetta DRRAFTER computational modeling. Furthermore ,this hybrid ‘Ribosolve’ pipeline detects and falsifies homologies and conformational rearrangements in 11 previously unknown 119- to 338-nucleotide protein-free RNA structures: full-length Tetrahymena ribozyme, hc16 ligase with and without substrate, full-length Vibrio cholerae and Fusobacterium nucleatum glycine riboswitch aptamers with and without glycine, Mycobacterium SAM-IV riboswitch with and without S-adenosylmethionine, and the computer-designed ATP-TTR-3 aptamer with and without AMP. Simulation benchmarks, blind challenges, compensatory mutagenesis, cross-RNA homologies and internal controls demonstrate that Ribosolve can accurately resolve the global architectures of RNA molecules but does not resolve atomic details. These tests offer guidelines for making inferences in future RNA structural studies with similarly accelerated throughput.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Automated Interpretation and Extraction of Topographic Information from Time of Flight Secondary Ion Mass Spectrometry Data

Time of flight secondary ion mass spectrometry (ToF SIMS) is one of the most powerful characterization tools allowing imaging of the chemical properties of various systems and materials. It allows precise studies of the chemical composition with sub-100-nm lateral and nanometer depth spatial resolution. However, comprehensive interpretation of ToF SIMS results is challengeable, because of the data volume and its multidimensionality. Furthermore, investigation of the samples with pronounced topographical features are complicated by the spectral shift. In this work we developed approach for the comprehensive ToF SIMS data interpretation based on the data analytics and automated extraction of the sample topography based on time of flight shift. We further applied this approach to investigate correlation between biological function and chemical composition in Arabidopsis roots.

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

Block segmentation in feature space for realtime object detection in high granularity images

Computer vision has applications in object detection, image recognition and classification, and object tracking. One of the challenges of computer vision is the presence of useful information at multiple distance scales. Filtering techniques may sacrifice details at small scales in order to prioritize the analysis of large-scale features of the image. We present a strategy for coarse-graining multidimensional data while maintaining fine-grained detail for subsequent analysis. The algorithm is based on fixed-size block segmentation in the feature space. We apply this strategy to solve the long-standing challenge of detecting particle trajectories at the Large Hadron Collider in real time.

Computer vision↗
DOE OSTI2016

A comprehensive simulation framework for imaging single particles and biomolecules at the European X-ray Free-Electron Laser

The advent of newer, brighter, and more coherent X-ray sources, such as X-ray Free-Electron Lasers (XFELs), represents a tremendous growth in the potential to apply coherent X-rays to determine the structure of materials from the micron-scale down to the Angstrom-scale. There is a significant need for a multi-physics simulation framework to perform source-to-detector simulations for a single particle imaging experiment, including (i) the multidimensional simulation of the X-ray source; (ii) simulation of the wave-optics propagation of the coherent XFEL beams; (iii) atomistic modelling of photon-material interactions; (iv) simulation of the time-dependent diffraction process, including incoherent scattering; (v) assembling noisy and incomplete diffraction intensities into a three-dimensional data set using the Expansion-Maximisation-Compression (EMC) algorithm and (vi) phase retrieval to obtain structural information. Furthermore, we demonstrate the framework by simulating a single-particle experiment for a nitrogenase iron protein using parameters of the SPB/SFX instrument of the European XFEL. This exercise demonstrably yields interpretable consequences for structure determination that are crucial yet currently unavailable for experiment design.

42 ENGINEERING↗
DOE OSTI2015

Enhancing Biological Analyses with Three Dimensional Field Asymmetric Ion Mobility, Low Field Drift Time Ion Mobility and Mass Spectrometry (µFAIMS/IMS-MS) Separations

We report the first evaluation of a platform coupling a high speed field asymmetric ion mobility spectrometry microchip (µFAIMS) with drift tube ion mobility and mass spectrometry (IMS-MS). The µFAIMS/IMS-MS platform was used to analyze biological samples and simultaneously acquire multidimensional information of detected features from the measured FAIMS compensation fields and IMS drift times, while also obtaining accurate ion masses. These separations thereby increase the overall separation power, resulting increased information content, and provide more complete characterization of more complex samples. The separation conditions were optimized for sensitivity and resolving power by the selection of gas compositions and pressures in the FAIMS and IMS separation stages. The resulting performance provided three dimensional separations, benefitting both broad complex mixture studies and targeted analyses by e.g. improving isomeric separations and allowing detection of species obscured by “chemical noise” and other interfering peaks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Visualizing Surface Plasmons with Photons, Photoelectrons, and Electrons

Both photons and electrons may be used to excite surface plasmon polaritons, the collective charge density fluctuations at the surface of metal nanostructures. By virtue of their nanoscopic and dissipative nature, a detailed characterization of surface plasmon (SP) eigenmodes in real space-time ultimately requires joint sub-nanometer spatial and sub-femtosecond temporal resolution. The latter realization has driven significant developments in the past few years, aimed at interrogating both localized and propagating SP modes over the relevant length and time scales. In this mini-review, we briefly highlight different techniques we employ to visualize the enhanced electric fields associated with SPs. Specifically, we discuss recent hyperspectral optical microscopy, tip-enhanced Raman nano-spectroscopy, nonlinear photoemission electron microscopy, as well as correlated scanning transmission electron microscopy-electron energy loss spectroscopy measurements targeting prototypical plasmonic nanostructures and constructs. Through selected practical examples, we examine the information content in multidimensional images recorded by taking advantage of each of the aforementioned techniques. In effect, we illustrate how SPs can be visualized at the ultimate limits of space and time.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2017

Structural elucidation of a mononuclear titanium methylidene

The first example of a structurally characterized titanium methylidene, (PN) 2 Ti=CH 2 , has been prepared via one-electron oxidation of (PN) 2 Ti(CH 3 ) followed by deprotonation or by H-atom abstraction using an aryloxyl radical. The Ti=C distance was found to be 1.939(3) Å, and variable temperature, multinuclear, and multidimensional NMR spectroscopic experiments revealed the methylidene to engage in long range interactions with protons on the ligand framework. Here, computational studies showed that the Ti=C bond, which until now has eluded structural studies, displays all the hallmarks of a prototypical Schrock-carbene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

A structural examination and collision cross section database for over 500 metabolites and xenobiotics using drift tube ion mobility spectrometry

The confident identification of metabolites and xenobiotics in biological and environmental studies is an analytical challenge due to their immense dynamic range, vast chemical space and structural diversity. Ion mobility spectrometry (IMS) is widely used for small molecule analyses since it can separate isomeric species and be easily coupled with front end separations and mass spectrometry for multidimensional characterizations. However, to date IMS metabolomic and exposomic studies have been limited by an inadequate number of accurate collision cross section (CCS) values for small molecules, causing features to be detected but not confidently identified. In this work, we utilized drift tube IMS (DTIMS) to directly measure CCS values for over 450 small molecules including primary metabolites, secondary metabolites and xenobiotics. Since DTIMS measurements do not need calibrates, they avoid calibration errors which can cause CCS accuracy problems and difficulties identifying structurally similar molecules. Furthermore, all measurements were performed in triplicate in both positive and negative polarities with nitrogen gas and seven different electric fields, so that relative standard deviations (RSD) could be assessed for each molecule and structural differences studied. The primary metabolites selected for the database are from key metabolism pathways such as glycolysis, the pentose phosphate pathway, and the tricarboxylic acid (TCA) cycle, while the secondary metabolites consist of classes such as terpenes and flavonoids, and the xenobiotics represent a range of molecules from antibiotics to polycyclic aromatic hydrocarbons. Different CCS trends were observed for several of the diverse small molecule classes, allowing insight in their separations and a possible why of classifying unknowns. This CCS database and structural information are freely available for download at http://panomics.pnnl.gov/metabolites/ with new molecules being added monthly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗