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At least 1,243 records · Page 69

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DOE OSTI2020

Membrane Proteins Have Distinct Fast Internal Motion and Residual Conformational Entropy

Abstract The internal motions of integral membrane proteins have largely eluded comprehensive experimental characterization. Here the fast side‐chain dynamics of the α‐helical sensory rhodopsin II and the β‐barrel outer membrane protein W have been investigated in lipid bilayers and detergent micelles by solution NMR relaxation techniques. Despite their differing topologies, both proteins have a similar distribution of methyl‐bearing side‐chain motion that is largely independent of membrane mimetic. The methyl‐bearing side chains of both proteins are, on average, more dynamic in the ps–ns timescale than any soluble protein characterized to date. Accordingly, both proteins retain an extraordinary residual conformational entropy in the folded state, which provides a counterbalance to the absence of the hydrophobic effect. Furthermore, the high conformational entropy could greatly influence the thermodynamics underlying membrane‐protein functions, including ligand binding, allostery, and signaling.

O'Brien, Evan S.↗

DOE OSTI2021

Host population diversity as a driver of viral infection cycle in wild populations of green sulfur bacteria with long standing virus-host interactions

Abstract Temperate phages are viruses of bacteria that can establish two types of infection: a lysogenic infection in which the virus replicates with the host cell without producing virions, and a lytic infection where the host cell is eventually destroyed, and new virions are released. While both lytic and lysogenic infections are routinely observed in the environment, the ecological and evolutionary processes regulating these viral dynamics are still not well understood, especially for uncultivated virus-host pairs. Here, we characterized the long-term dynamics of uncultivated viruses infecting green sulfur bacteria (GSB) in a model freshwater lake (Trout Bog Lake, TBL). As no GSB virus has been formally described yet, we first used two complementary approaches to identify new GSB viruses from TBL; one in vitro based on flow cytometry cell sorting, the other in silico based on CRISPR spacer sequences. We then took advantage of existing TBL metagenomes covering the 2005–2018 period to examine the interactions between GSB and their viruses across years and seasons. From our data, GSB populations in TBL were constantly associated with at least 2-8 viruses each, including both lytic and temperate phages. The dominant GSB population in particular was consistently associated with two prophages with a nearly 100% infection rate for >10 years. We illustrate with a theoretical model that such an interaction can be stable given a low, but persistent, level of prophage induction in low-diversity host populations. Overall, our data suggest that lytic and lysogenic viruses can readily co-infect the same host population, and that host strain-level diversity might be an important factor controlling virus-host dynamics including lytic/lysogeny switch.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2011

Evolution dynamics of discrete-continuous light bullets

We experimentally and numerically investigate the propagation of light bullets (LBs) excited in two-dimensional fiber arrays. The combination of nonlinear self-frequency shift, wavelength dependence of the dispersion, and the interwaveguide coupling strength induce an adiabatic variation of the parameters of the LBs along their propagation paths, until they reach the limits of the regime of existence and decay. The relative strength of the various perturbative effects can partially be controlled by the array's geometry. The characterization of the LB dynamics is carried out by implementing a spatiotemporal, cross-correlating, and spectrally resolved imaging system with femtosecond resolution. The experimental results are in good agreement with the numerical data if higher-order nonlinear effects and the wavelength dependence of the dispersion and coupling are included. The observed wave packets are linked to the stationary solutions of the simplified nonlinear Schroedinger equation. Furthermore, the maximum possible range of existence of LBs in arrays of waveguides is discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Disentangling the Distant Stellar Halo Using K Giants in DESI Year 3 Data

We present a sample of 88,959 K giants from Dark Energy Spectroscopic Instrument Milky Way Survey Year 3 data, which we use to characterize the chemo-dynamical properties of the stellar halo at Galactocentric distances of 12 to ∼100 kpc. Using HDBSCAN, we identify five prominent stellar halo substructures: Aleph, the Sagittarius stream, Gaia-Sausage-Enceladus (GSE), Cetus-Palca, and the Orphan–Chenab stream. We present the properties of each of these structures as they appear in our catalog, and examine how uncertainties on distance affect the characterization of substructure with this approach. We also examine regions associated with previously reported overdensities (such as the Virgo Overdensities and the Sagittarius spur) that we do not recover with HDBSCAN. The size and distance range of our catalog allows us to explore in detail the residual stellar halo, comprising stars that we do not associate with any substructure. We find that samples of ∼2000 outer halo stars with both highly prograde and highly retrograde angular momenta have similar metallicity distribution functions (MDFs), which do not resemble the MDFs of either GSE or Sagittarius. Both the prograde and retrograde residual halo MDFs are bimodal, with a metal-poor peak at [Fe/H] ∼ −2 and a metal-rich peak at [Fe/H] ∼ −1.3 (prograde) or −1.5 (retrograde). The MDF for lower-angular-momentum residual halo K giants does not show clear evidence for a metal-poor peak, and broadly resembles the MDF of GSE, even at much lower binding energies than GSE itself. We discuss possible interpretations of these findings for GSE accretion scenarios.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Water Dynamics of Superacid Aromatic Proton Exchange Membranes for Fuel Cell Applications

Proton exchange membranes (PEMs) with high conductivity are of critical importance for the development of fuel cells, electrolyzers, and other electrochemical technologies. In this research, poly(1,1,2,2-tetrafluoro-2-phenoxyethane-1-sulfonic acid) (PTPS) with an aromatic polymer main chain and a perfluorinated superacidic polymer side chain was synthesized. The water dynamics of PTPS were characterized across various length scales using a combination of Fourier-transform infrared spectroscopy (FTIR) and nuclear magnetic resonance (NMR) and compared with Nafion, a standard perfluorinated PEM, and sulfonated poly(ether sulfone) (SPES 40), an aromatic PEM without perfluorinated superacid side chains. The T 1 and T 2 relaxation times of water in the samples probed by NMR increase from SPES 40 to PTPS to Nafion, indicating that the local motion of the water molecules becomes faster. This trend corresponds well with the relative fraction of bulk-like water determined using FTIR. At larger length scales, the diffusion coefficient of water was characterized using pulsed-field gradient NMR (PFG-NMR). At a longer diffusion time (Δ = 100 ms), PTPS has a smaller diffusion coefficient compared with both Nafion and SPES 40, due to restricted diffusion, and this effect is also evident in the proton conductivity of the hydrated membranes. From this comparison, it is apparent that the aromatic backbone and side chain type greatly influence the water dynamics in PEMs at various length scales and the water dynamics significantly impact the bulk proton conductivity. These insights will lead to new designs for aromatic PEMs and help to identify bottlenecks in current materials.

25 ENERGY STORAGE↗

DOE OSTI2022

Ultrafast infrared nano-imaging of far-from-equilibrium carrier and vibrational dynamics

Ultrafast infrared nano-imaging has demonstrated access to ultrafast carrier dynamics on the nanoscale in semiconductor, correlated-electron, or polaritonic materials. However, mostly limited to short-lived transient states, the contrast obtained has remained insufficient to probe important long-lived excitations, which arise from many-body interactions induced by strong perturbation among carriers, lattice phonons, or molecular vibrations. Here, we demonstrate ultrafast infrared nano-imaging based on excitation modulation and sideband detection to characterize electron and vibration dynamics with nano- to micro-second lifetimes. As an exemplary application to quantum materials, in phase-resolved ultrafast nano-imaging of the photoinduced insulator-to-metal transition in vanadium dioxide, a distinct transient nano-domain behavior is quantified. In another application to lead halide perovskites, transient vibrational nano-FTIR spatially resolves the excited-state polaron-cation coupling underlying the photovoltaic response. These examples show how heterodyne pump-probe nano-spectroscopy with low-repetition excitation extends ultrafast infrared nano-imaging to probe elementary processes in quantum and molecular materials in space and time.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1996

Wetting Hysteresis at the Molecular Scale

The motion of a fluid-fluid-solid contact line on a rough surface is well known to display hysteresis in the contact angle vs. velocity relationship. In order to understand the phenomenon at a fundamental microscopic level, we have conducted molecular dynamics computer simulations of a Wilhelmy plate experiment in which a solid surface is dipped into a liquid bath, and the force-velocity characteristics are measured. We directly observe a systematic variation of force and contact angle with velocity, which is single-valued for the case of an atomically smooth solid surface. In the microscopically rough case, however, we find (as intuitively expected) an open hysteresis loop. Further characterization of the interface dynamics is in progress.

Jin, Wei↗

NASA NTRS1989

Computational chaos in massively parallel neural networks

A fundamental issue which directly impacts the scalability of current theoretical neural network models to massively parallel embodiments, in both software as well as hardware, is the inherent and unavoidable concurrent asynchronicity of emerging fine-grained computational ensembles and the possible emergence of chaotic manifestations. Previous analyses attributed dynamical instability to the topology of the interconnection matrix, to parasitic components or to propagation delays. However, researchers have observed the existence of emergent computational chaos in a concurrently asynchronous framework, independent of the network topology. Researcher present a methodology enabling the effective asynchronous operation of large-scale neural networks. Necessary and sufficient conditions guaranteeing concurrent asynchronous convergence are established in terms of contracting operators. Lyapunov exponents are computed formally to characterize the underlying nonlinear dynamics. Simulation results are presented to illustrate network convergence to the correct results, even in the presence of large delays.

Barhen, Jacob↗

NASA NTRSDate not supplied

CFD Predictions of Fluctuating Pressure Environments on NASA’s SLS Ascent Unsteady Aerodynamics Wind Tunnel Test

This paper details work that is being conducted on predicting fluctuating pressure environments on NASA launch vehicles using computational fluid dynamics (CFD). The accurate characterization of these aeroacoustics environments is necessary in the analysis of vehicle structural health and aerodynamic performance and in the vehicle design process. High-fidelity simulations of the unsteady flow over NASA’s SLS Ascent Unsteady Aerodynamics wind tunnel Test (AUAT) using the hybrid Reynolds-averaged Navier-Stokes (RANS)-large eddy simulations (LES) methodologies in Mississippi States’ Loci/CHEM solver are presented. The two available methods, Nelson-Nichols and dynamic hybrid RANS-LES (DHRL), are compared head-to-head on identical grids at two Mach numbers. At the high-subsonic Mach number, locally supersonic flow expanding over a shoulder induces a separation-reattachment system that is predicted poorly by the Nelson-Nichols method due to an under-prediction in unsteady content. The DHRL solution predicts the spatial extent and frequency domain response of this system well but under-predicts the peak noise levels due to a delay in the RANS-to-LES transition. At the low-supersonic Mach number, compression corner dynamics dominate the unsteady flow. While the Nelson Nichols solution captures this phenomenon well, another solution on a refined grid indicates that some model stress depletion is occurring. The DHRL solution again performs well at this Mach number and matches the wind tunnel data fairly closely, but perhaps most impressively, is fairly agnostic to increasing grid resolution. The findings in this paper are expected to be generally applicable and will be used to guide the prediction of aeroacoustics environments of other NASA launch vehicles.

CFD↗

DOE OSTI2021

Defect-Driven Oxide Transformations and the Electrochemical Interphase

The redox reaction pathway is crucial to the sustainable production of the fuels and chemicals required for a carbon-neutral society. Our society is becoming increasingly dependent on devices using batteries and electrolyzers, all of which rely on a series of redox reactions. The overall properties of oxide materials make them very well suited for such electrochemical and catalytic applications due to their associated cationic redox properties and the static site-adsorbate interactions. As these technologies have matured, it has become apparent that defect-driven redox reactions, defect-coupled diffusion, and structural transformations that are both time- and rate-dependent are also critical materials processes. This change in focus, considering not only redox properties but also more complex, dynamic behaviors, represents a new research frontier in the molecular sciences as they are strongly linked to device operation and degradation and lie at the heart of various phenomena that take place at electrochemical interfaces. Fundamental studies of the structural, electronic, and chemical transformation mechanisms are key to the advancement of materials and technological innovations that could be implemented in various electrochemical systems. In this Account, we focus on recent studies and advances in characterizing and understanding the dynamic redox evolution and structural transformations that take place in model perovskites and layered oxides under reactive conditions and correlate them with degradation mechanisms and operations in electrolyzers and batteries. We show that the dynamic evolution of oxygen vacancies and cationic migration in the surface or bulk occurs at the solid-liquid interface, using a combination of different synchrotron-based Xray spectroscopies and scattering probes. Detailed redox-structure-reactivity correlation studies show how defects and diffusion processes can be tailored to drive various physical and chemical transformations in electrolyzers and batteries. We also highlight a strong correlation between oxygen redox reactivity and structural reorganization in both model thin films and particles, helping to bridge the gap between fundamental studies of the reaction mechanism and device applications. Finally, on the basis of these findings, we discuss strategies to probe and tune the redox reactivity and structural stability of the redox-active oxide interphase toward devising efficient pathways for energy and chemical harvesting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Magnetic excitations, nonclassicality, and quantum wake spin dynamics in the Hubbard chain

Recent work has demonstrated that quantum Fisher information (QFI), a witness of multipartite entanglement, and magnetic Van Hove correlations G(r,t), a probe of local real-space real-time spin dynamics, can be successfully extracted from inelastic neutron scattering on spin systems through accurate measurements of the dynamical spin structure factor S(k,ω). In this work, we apply theoretically these ideas to the half-filled Hubbard chain with nearest-neighbor hopping, away from the strong-coupling limit. This model has nontrivial redistribution of spectral weight in S(k,ω) going from the noninteracting limit (U = 0) to strong coupling (U→∞), where it reduces to the Heisenberg quantum spin chain. We use the density matrix renormalization group to find S(k,ω), from which QFI is then calculated. We find that QFI grows with U. With realistic energy resolution it becomes capable of witnessing bipartite entanglement above U=2.5 (in units of the hopping), where it also changes slope. This point is also proximate to slope changes of the bandwidth W(U) and the half-chain von Neumann entanglement entropy. We compute G(r,t) by Fourier transforming S(k,ω). The results indicate a crossover in the short-time short-distance dynamics at low U characterized by ferromagnetic light-cone wavefronts, to a Heisenberg-type behavior at large U featuring antiferromagnetic light cones and spatially period-doubled antiferromagnetism. We find this crossover has largely been completed by U=3. Our results thus provide evidence that, in several aspects, the strong-coupling limit of the Hubbard chain is reached qualitatively already at a relatively modest interaction strength. We discuss experimental candidates for observing the G(r,t) dynamics found at low U.

1-dimensional systems↗

NASA NTRS2002

Vestibular convergence patterns in vestibular nuclei neurons of alert primates

Sensory signal convergence is a fundamental and important aspect of brain function. Such convergence may often involve complex multidimensional interactions as those proposed for the processing of otolith and semicircular canal (SCC) information for the detection of translational head movements and the effective discrimination from physically congruent gravity signals. In the present study, we have examined the responses of primate rostral vestibular nuclei (VN) neurons that do not exhibit any eye movement-related activity using 0.5-Hz translational and three-dimensional (3D) rotational motion. Three distinct neural populations were identified. Approximately one-fourth of the cells exclusively encoded rotational movements (canal-only neurons) and were unresponsive to translation. The canal-only central neurons encoded head rotation in SCC coordinates, exhibited little orthogonal canal convergence, and were characterized with significantly higher sensitivities to rotation as compared to primary SCC afferents. Another fourth of the neurons modulated their firing rates during translation (otolith-only cells). During rotations, these neurons only responded when the axis of rotation was earth-horizontal and the head was changing orientation relative to gravity. The remaining one-half of VN neurons were sensitive to both rotations and translations (otolith + canal neurons). Unlike primary otolith afferents, however, central neurons often exhibited significant spatiotemporal (noncosine) tuning properties and a wide variety of response dynamics to translation. To characterize the pattern of SCC inputs to otolith + canal neurons, their rotational maximum sensitivity vectors were computed using exclusively responses during earth-vertical axis rotations (EVA). Maximum sensitivity vectors were distributed throughout the 3D space, suggesting strong convergence from multiple SCCs. These neurons were also tested with earth-horizontal axis rotations (EHA), which would activate both vertical canals and otolith organs. However, the recorded responses could not be predicted from a linear combination of EVA rotational and translational responses. In contrast, one-third of the neurons responded similarly during EVA and EHA rotations, although a significant response modulation was present during translation. Thus this subpopulation of otolith + canal cells, which included neurons with either high- or low-pass dynamics to translation, appear to selectively ignore the component of otolith-selective activation that is due to changes in the orientation of the head relative to gravity. Thus contrary to primary otolith afferents and otolith-only central neurons that respond equivalently to tilts relative to gravity and translational movements, approximately one-third of the otolith + canal cells seem to encode a true estimate of the translational component of the imposed passive head and body movement.

Non-NASA Center↗

DOE OSTI2018

Theory of time-resolved Raman scattering in correlated systems: Ultrafast engineering of spin dynamics and detection of thermalization

Ultrafast characterization and control of many-body interactions and elementary excitations are critical to understanding and manipulating emergent phenomena in strongly correlated systems. In particular, spin interaction plays an important role in unconventional superconductivity, but efficient tools for probing spin dynamics, especially out of equilibrium, are still lacking. To address this question, we develop a theory for nonresonant time-resolved Raman scattering, which can be a generic and powerful tool for nonequilibrium studies. We also use exact diagonalization to simulate the pump-probe dynamics of correlated electrons in the square-lattice single-band Hubbard model. Different ultrafast processes are shown to exist in the time-resolved Raman spectra and dominate under different pump conditions. For high-frequency and off-resonance pumps, we show that the Floquet theory works well in capturing the softening of bimagnon excitation. By comparing the Stokes and anti-Stokes spectra, we also show that effective heating dominates at small pump fluences, while a coherent many-body effect starts to take over at larger pump amplitudes and frequencies on resonance to the Mott gap. In conclusion, time-resolved Raman scattering thereby provides the platform to explore different ultrafast processes and design material properties out of equilibrium.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Interface microstructure effects on dynamic failure behavior of layered Cu/Ta microstructures

Abstract Structural metallic materials with interfaces of immiscible materials provide opportunities to design and tailor the microstructures for desired mechanical behavior. Metallic microstructures with plasticity contributors of the FCC and BCC phases show significant promise for damage-tolerant applications due to their enhanced strengths and thermal stability. A fundamental understanding of the dynamic failure behavior is needed to design and tailor these microstructures with desired mechanical responses under extreme environments. This study uses molecular dynamics (MD) simulations to characterize plasticity contributors for various interface microstructures and the damage evolution behavior of FCC/BCC laminate microstructures. This study uses six model Cu/Ta interface systems with different orientation relationships that are as- created, and pre-deformed to understand the modifications in the plasticity contributions and the void nucleation/evolution behavior. The results suggest that pre-existing misfit dislocations and loading orientations (perpendicular to and parallel to the interface) affect the activation of primary and secondary slip systems. The dynamic strengths are observed to correlate with the energy of the interfaces, with the strengths being highest for low-energy interfaces and lowest for high-energy interfaces. However, the presence of pre-deformation of these interface microstructures affects not only the dynamic strength of the microstructures but also the correlation with interface energy.

42 ENGINEERING↗

DOE OSTI2026

Intermediate time sub-diffusion and stress relaxation in ring polymer melts

The slow dynamics of non-concatenated ring melts remains a frontier problem in polymer science with implications for many soft material environments including cellular biophysics. Here, in this work, we report large-scale simulations of model ring melts that analyze the monomer and center-of-mass (CM) mean square displacements (MSD) and stress relaxation function on intermediate time and length scales. The degree of dynamical slowing down is characterized by the maximally sub-diffusive fractional time scaling exponents. The data span an exceptionally wide range of ring degrees of polymerization and stiffnesses and are not successfully organized based on the classic measure linear chain entanglement, N/N e . Rather, we find that the crossover degree of polymerization, N D , based on ring macromolecular caging that successfully allows master curves to be constructed for the long-time CM self-diffusion constant also collapses these temporal dynamic scaling exponents. Different properties display different exponents and exhibit one or two regimes of linear variation with the logarithm of N D / N . A distinct crossover of the CM-MSD and stress relaxation exponents emerges at sufficiently large N or stiffness that is not found for the monomer MSD, indicating a novel form of dynamic decoupling. This crossover aligns with the predicted critical degree of polymerization for transitioning from a weak to strong caging regime, indicative of activated transport. The latter may reflect the emergence of an intermolecular collective contribution to stress in analogy with dense soft colloidal matter. Suggestions are made for future theoretical work to address the rich patterns of behavior discovered.

Anomalous diffusion↗

DOE OSTI2016

Lipidic cubic phase injector is a viable crystal delivery system for time-resolved serial crystallography

Serial femtosecond crystallography (SFX) using X-ray free-electron laser sources is an emerging method with considerable potential for time-resolved pump-probe experiments. Here we present a lipidic cubic phase SFX structure of the light-driven proton pump bacteriorhodopsin (bR) to 2.3 Å resolution and a method to investigate protein dynamics with modest sample requirement. Time-resolved SFX (TR-SFX) with a pump-probe delay of 1 ms yields difference Fourier maps compatible with the dark to M state transition of bR. Importantly, the method is very sample efficient and reduces sample consumption to about 1 mg per collected time point. Accumulation of M intermediate within the crystal lattice is confirmed by time-resolved visible absorption spectroscopy. Furthermore, this study provides an important step towards characterizing the complete photocycle dynamics of retinal proteins and demonstrates the feasibility of a sample efficient viscous medium jet for TR-SFX.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1982

A simple criterion for determining the dynamical stability of three-body systems

Coplanar, prograde three-body systems (TBS) are discussed, emphasizing the specification of general criteria for determining whether such systems are dynamically stable. It is shown that the Graziani-Black (1981) criteria provide a quantitatively accurate characterization of the onset of dynamic instability for values of the dimensionless mass ranging from one millionth to one million. Harrington's (1977) general criterion and the Graziani-Black criterion are compared with results from analytic work that spans a 12-orders-of-magnitude variation in the mass ratios of the TBS components. Comparison of the Graziani-Black criteria with data for eight well-studied triple-star systems indicates that the observed lower limit for the ratio of periastron distance of the tertiary orbit to the semimajor axis of the binary orbit is due to dynamical instability rather than to cosmogonic processes.

Black, D. C.↗

DOE OSTI2021

“Thought I’d Share First” and Other Conspiracy Theory Tweets from the COVID-19 Infodemic: Exploratory Study

Background: The COVID-19 outbreak has left many people isolated within their homes; these people are turning to social media for news and social connection, which leaves them vulnerable to believing and sharing misinformation. Health-related misinformation threatens adherence to public health messaging, and monitoring its spread on social media is critical to understanding the evolution of ideas that have potentially negative public health impacts. Objective: The aim of this study is to use Twitter data to explore methods to characterize and classify four COVID-19 conspiracy theories and to provide context for each of these conspiracy theories through the first 5 months of the pandemic. Methods: We began with a corpus of COVID-19 tweets (approximately 120 million) spanning late January to early May 2020. We first filtered tweets using regular expressions (n=1.8 million) and used random forest classification models to identify tweets related to four conspiracy theories. Our classified data sets were then used in downstream sentiment analysis and dynamic topic modeling to characterize the linguistic features of COVID-19 conspiracy theories as they evolve over time. Results: Analysis using model-labeled data was beneficial for increasing the proportion of data matching misinformation indicators. Random forest classifier metrics varied across the four conspiracy theories considered (F1 scores between 0.347 and 0.857); this performance increased as the given conspiracy theory was more narrowly defined. We showed that misinformation tweets demonstrate more negative sentiment when compared to non-misinformation tweets and that theories evolve over time, incorporating details from unrelated conspiracy theories as well as real-world events. Conclusions: Although we focus here on health-related misinformation, this combination of approaches is not specific to public health and is valuable for characterizing misinformation in general, which is an important first step in creating targeted messaging to counteract its spread. Initial messaging should aim to preempt generalized misinformation before it becomes widespread, while later messaging will

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