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At least 145 records · Page 8

Prediction of potential pseudo-symmetry issues in the indexing of electron backscatter diffraction patterns

A new methodology to predict potential pseudo-symmetric or systematically mis-indexed orientations for an arbitrary crystal structure is presented. The method leverages the recently proposed spherical indexing algorithm to index electron backscatter diffraction patterns. Potential pseudo-symmetric orientations are interpreted as secondary peaks in the autocorrelation of the Kikuchi sphere. The generality of the method is illustrated using a number of crystal systems, ranging from nickel, where no significant pseudo-symmetric issues are expected, to SrTiO 3 , with mild occurrence of such issues, to the olivine series, γ-TiAl and U-6%Nb systems, where the traditional Hough method systematically mis-indexes the pseudo-symmetric variants. Here, the method predicts the severity of potential pseudo-symmetric matches and ranks all variants using a normalized autocorrelation coefficient.

36 MATERIALS SCIENCE↗

Quantifying the uncertainty introduced by discretization and time-averaging in two-fluid model predictions

The two-fluid model (TFM) has become a tool for the design and troubleshooting of industrial fluidized bed reactors. To use TFM for scale up with confidence, the uncertainty in its predictions must be quantified. Here, we study two sources of uncertainty: discretization and time-averaging. First, we show that successive grid refinement may not yield grid-independent transient quantities, including cross-section–averaged quantities. Successive grid refinement would yield grid-independent time-averaged quantities on sufficiently fine grids. A Richardson extrapolation can then be used to estimate the discretization error, and the grid convergence index gives an estimate of the uncertainty. Richardson extrapolation may not work for industrial-scale simulations that use coarse grids. We present an alternative method for coarse grids and assess its ability to estimate the discretization error. Second, we assess two methods (autocorrelation and binning) and find that the autocorrelation method is more reliable for estimating the uncertainty introduced by time-averaging TFM data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Dynamics of High Molecular Weight Cylindrical and Lamellar Block Copolymers with X‐ray Photon Correlation Spectroscopy

Here, the structure and dynamics of polystyrene (PS)-b-poly(ethylene oxide) block copolymers (BCPs) are studied. The BCPs exhibit microphase-separated cylindrical and lamellar morphologies. Structural dynamics are measured with X-ray photon correlation spectroscopy in the small-angle regime. Morphologies and domain sizes are evaluated using small-angle X-ray scattering (SAXS), scanning electron microscopy, and atomic force microscopy. Different solvent processing conditions are investigated. Grain sizes evaluated using SAXS are found to depend on processing only for the rubbery majority BCP. The structural relaxation times are examined as a function of PS volume fraction, temperature, morphology, and structural sizes. Well above the glass transition temperature (T g ) of PS, all samples exhibit stretched autocorrelation decays and diffusive dynamics. Near T g of PS, the dynamics of all samples are anomalous with compressed autocorrelation decays and hyperdiffusive dynamics. This transition occurs at 153 °C or 1.13 T g of PS. In the diffusive regime (at high temperature), structural relaxation times are dependent on the processing method. Near PS T g (at low temperature), structural relaxation times scale with the PS volume fraction. Structural relaxation times do not correlate with grain size, indicating that the out-of-equilibrium state of PS dominates the structural dynamics of these strongly phase-segregated BCPs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Recalibration of missing low-frequency variability and trends in the North Atlantic Oscillation

Abstract Multi-decadal trends in the wintertime North Atlantic Oscillation (NAO) are under-represented by coupled general circulation models (CGCMs), consistent with a lack of autocorrelation in their NAO index series. This study proposes and tests two simple “reddening” approaches for correcting this problem in simulated indices based on simple one parameter short-term (AR; Auto-Regressive order 1) and long-term (FD; Fractional-Difference) time series filters. Using CGCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6), the FD filter successfully improves the autocorrelation structure of the NAO, and in turn the simulation of extreme trends, while the AR filter is less successful. The 1963–1993 NAO trend is the maximum 31-year trend in the historical period. Raw CGCMs underestimate the likelihood of this trend by a factor of ten but this discrepancy is corrected after reddening. CMIP6 future projections show that long-term (2024–2094) NAO ensemble mean trends systematically increase with the magnitude of radiative forcing: -2.4 to 3.5 hPa/century for low-to-high forcing after reddening (more than double the range using raw output). The related likelihood of future maximum 31year trends comparable to 1963–1993 ranges from 3 to 7% whereas none of these CMIP6 projections simulate this without reddening. Near-term projections of the next 31 years (2024–2054) are less sensitive than long term trends to the future scenario, showing weak-to-no forced trend. However, reddening increases the ensemble range by 74% (to +/-1 standard deviation/decade), which could increase/decrease regional climate change signals in the Northern Hemisphere by magnitudes that are underestimated when using raw CGCM output.

Meteorology & Atmospheric Sciences↗

A Bayesian approach to calibrating hydrogen flame kinetics using many experiments and parameters

First-principles Markov Chain Monte Carlo sampling is used to investigate uncertainty quantification and uncertainty propagation in parameters describing hydrogen kinetics. Specifically, we sample the posterior distribution for thirty-one parameters focusing on the H 2 O 2 and HO 2 reactions resulting from conditioning on ninety-one experiments. Established literature values are used for the remaining parameters in the mechanism as well as other thermodynamic and transport data needed to specify fluid properties. The samples are computed using an affine invariant sampler starting with broad, noninformative priors. Autocorrelation analysis shows that O(1M) samples are sufficient to obtain a reasonable sampling of the posterior. The resulting distribution identifies strong positive and negative correlations and several non-Gaussian characteristics. Using samples drawn from the posterior, we investigate the impact of parameter uncertainty on the prediction of two more complex flames: a 2D premixed flame kernel and the ignition of a hydrogen jet issuing into a heated chamber. The former represents a combustion regime similar to the target experiments used to calibrate the mechanism and the latter represents a different combustion regime. For the premixed flame, the net amount of product after a given time interval has a standard deviation of less than 2% whereas the standard deviation of the ignition time for the jet is more than 10%. The samples used for these studies are posted online. These results indicate the degree to which parameters consistent with the target experiments constrain predicted behavior in different combustion regimes. Finally, this process provides a framework for both identifying reactions for further study from candidate mechanisms as well as combining uncertainty quantification and propagation to, ultimately, tie uncertainty in laboratory flame experiments to uncertainty in end-use numerical predictions of more complicated scenarios.

97 MATHEMATICS AND COMPUTING↗

Imaging Fluorescence-Correlation Spectroscopy for Measuring Fast Surface Diffusion at Liquid/Solid Interfaces

The development of techniques to probe interfacial molecular transport is important for understanding and optimizing surface-based analytical methods including surface-enhanced spectroscopies, biological assays, and chemical separations. Single-molecule-fluorescence imaging and tracking has been used to measure lateral diffusion rates of fluorescent molecules at surfaces, but the technique is limited to the study of slower diffusion, where molecules must remain relatively stationary during acquisition of an image in order to build up sufficient intensity in a spot to detect and localize the molecule. Although faster time resolution can be achieved by fluorescence-correlation spectroscopy (FCS), where intensity fluctuations in a small spot are related to the motions of molecules on the surface, long-lived adsorption events arising from surface inhomogeneity can overwhelm the correlation measurement and mask the surface diffusion of the moving population. Here, we exploit a combination of these two techniques, imaging-FCS, for measurement of fast interfacial transport at a model chromatographic surface. This is accomplished by rapid imaging of the surface using an electron-multiplied-charged-coupled-device (CCD) camera, while limiting the acquisition to a small area on the camera to allow fast framing rates. The total intensity from the sampled region is autocorrelated to determine surface diffusion rates of molecules with millisecond time resolution. Here, the technique allows electronic control over the acquisition region, which can be used to avoid strong adsorption sites and thus minimize their contribution to the measured autocorrelation decay and to vary the acquisition area to resolve surface diffusion from adsorption and desorption kinetics. As proof of concept, imaging-FCS was used to measure surface diffusion rates, interfacial populations, and adsorption–desorption rates of 1,1'-dioctadecyl-3,3,3'3'-tetramethylindocarbocyanine (DiI) on planar C18- and C1-modified surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coarse-grained modeling of polyethylene melts: Effect on dynamics

The distinctive viscoelastic behavior of polymers results from a coupled interplay of motion on multiple length and time scales. Capturing the broad time and length scales of polymer motion remains a challenge. Using polyethylene (PE) as a model macromolecule, we construct coarse-grained (CG) models of PE with three to six methyl groups per CG bead and probe two critical aspects of the technique: pressure corrections required after iterative Boltzmann inversion (IBI) to generate CG potentials that match the pressure of reference fully atomistic melt simulations and the transferability of CG potentials across temperatures. While IBI produces nonbonded pair potentials that give excellent agreement between the atomistic and CG pair correlation functions, the resulting pressure for the CG models is large compared with the pressure of the atomistic system. We find that correcting the potential to match the reference pressure leads to nonbonded interactions with much deeper minima and slightly smaller effective bead diameter. However, simulations with potentials generated by IBI and pressure-corrected IBI result in similar mean-square displacements (MSDs) and stress autocorrelation functions G( t ) for PE melts. While the time rescaling factor required to match CG and atomistic models is the same for pressure- and non-pressure-corrected CG models, it strongly depends on temperature. Furthermore, transferability was investigated by comparing the MSDs and stress autocorrelation functions for potentials developed at different temperatures.

36 MATERIALS SCIENCE↗

Shear-Induced Conformations of Salt-Free Polyelectrolytes in Semidilute Solutions

Here, we present coarse-grained molecular dynamics simulations of salt-free polyelectrolyte chains in semidilute solutions under simple shear flow, with full hydrodynamic interactions and explicit dipolar solvent. At equilibrium, chain orientation statistics follow a pseudo-Voigt distribution, and the structural correlation length and chain end-to-end vector autocorrelation function exhibit scaling behavior consistent with theoretical predictions for polyelectrolytes. Under shear, chains transition from coiled to stretched states and the end-to-end vector autocorrelation function reveals oscillatory dynamics at high Weissenberg numbers. Analysis of the gyration tensor and shear strain distributions identified three distinct chain populations with directional alignment along and against the shear gradient. Compared with their neutral polymer counterparts, polyelectrolytes exhibit stronger shear thinning and enhanced chain alignment under the same Weissenberg number, which is attributed to electrostatic interactions and shear-induced counterion release. These findings provide molecular insight into the distinct flow response of charged polymers and have implications for tailoring the rheological properties of polyelectrolyte-based materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identifying Key Environmental Factors Explaining Temporal Patterns of DOC Export From Watersheds in the Conterminous United States

The export of dissolved organic carbon (DOC) from a watershed is a key component of the terrestrial biosphere carbon cycle. There is a need to improve our understanding of how and by how much various environmental factors are driving the temporal patterns of DOC export in order to accurately model and evaluate terrestrial carbon storage and fluxes. In this synthesis, we compiled observational data sets from 14 watersheds in the conterminous United States spanning the time period from 1981 to 2017. We used these data sets to examine the relative impacts of various climate, atmospheric deposition, and land cover factors on the temporal patterns of DOC export across watersheds of different sizes and landscape conditions, as well as the time-series autocorrelation of DOC export. Overall, our results suggest that the dominant factor on an annual scale was the amount of precipitation, which had a positive correlation with DOC export from a watershed. Overall increasing nitrogen deposition was coincident with increasing DOC export, and increasing sulfur deposition was coincident with declining DOC export. The seasonal pattern of DOC export was strongly regulated by air temperature, the long-term trend was negatively influenced by increasing sulfur deposition, and no obvious autocorrelation was detected in DOC export. In addition, higher rates of DOC export were positively correlated with greater area of wetlands within a watershed, but was not found to be strongly related to any of the other land cover types.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of a Stochastic Mixing Scheme in the Deep Convective Gray Zone Using a Tropical Oceanic Deep Convection Case Study

Abstract A stochastic horizontal subgrid‐scale mixing scheme is evaluated in ensemble simulations of a tropical oceanic deep convection case using a horizontal grid spacing (Δ h ) of 3 km. The stochastic scheme, which perturbs the horizontal mixing coefficient according to a prescribed spatiotemporal autocorrelation scale, is found to generally increase mesoscale organization and convective intensity relative to a non‐stochastic control simulation. Perturbations applied at relatively short autocorrelation scales induce differences relative to the control that are more systematic than those from perturbations applied at relatively long scales that yield more variable outcomes. A simulation with mixing enhanced by a constant factor of 4 significantly increases mesoscale organization and convective intensity, while turning off horizontal subgrid‐scale mixing decreases both. Total rainfall is modulated by a combination of mesoscale organization, areal coverage of convection, and convective intensity. The stochastic simulations tend to behave more similarly to the constant enhanced mixing simulation owing to greater impacts from enhanced mixing as compared to reduced mixing. The impacts of stochastic mixing are robust, ascertained by comparing the stochastic mixing ensembles with a non‐stochastic mixing ensemble that has grid‐scale noise added to the initial thermodynamic field. Compared to radar observations and a higher resolution Δ h = 1 km simulation, stochastic mixing seemingly degrades the simulation performance. These results imply that stochastic mixing produces non‐negligible impacts on convective system properties and evolution but does not lead to an improved representation of convective cloud characteristics in the case studied here.

54 ENVIRONMENTAL SCIENCES↗

Emission from quantum-dot high-β microcavities: transition from spontaneous emission to lasing and the effects of superradiant emitter coupling

Measured and calculated results are presented for the emission properties of a new class of emitters operating in the cavity quantum electrodynamics regime. The structures are based on high-finesse GaAs/AlAs micropillar cavities, each with an active medium consisting of a layer of InGaAs quantum dots (QDs) and the distinguishing feature of having a substantial fraction of spontaneous emission channeled into one cavity mode (high β-factor). This paper demonstrates that the usual criterion for lasing with a conventional (low β-factor) cavity, that is, a sharp non-linearity in the input–output curve accompanied by noticeable linewidth narrowing, has to be reinforced by the equal-time second-order photon autocorrelation function to confirm lasing. The article also shows that the equal-time second-order photon autocorrelation function is useful for recognizing superradiance, a manifestation of the correlations possible in high-β microcavities operating with QDs. In terms of consolidating the collected data and identifying the physics underlying laser action, both theory and experiment suggest a sole dependence on intracavity photon number. Evidence for this assertion comes from all our measured and calculated data on emission coherence and fluctuation, for devices ranging from light-emitting diodes (LEDs) and cavity-enhanced LEDs to lasers, lying on the same two curves: one for linewidth narrowing versus intracavity photon number and the other for g( 2 )(0) versus intracavity photon number.

36 MATERIALS SCIENCE↗

Machine learning assisted quantum super-resolution microscopy

One of the main characteristics of optical imaging systems is spatial resolution, which is restricted by the diffraction limit to approximately half the wavelength of the incident light. Along with the recently developed classical super-resolution techniques, which aim at breaking the diffraction limit in classical systems, there is a class of quantum super-resolution techniques which leverage the non-classical nature of the optical signals radiated by quantum emitters, the so-called antibunching super-resolution microscopy. This approach can ensure a factor of $\sqrt{n}$ improvement in the spatial resolution by measuring the n -th order autocorrelation function. The main bottleneck of the antibunching super-resolution microscopy is the time-consuming acquisition of multi-photon event histograms. We present a machine learning-assisted approach for the realization of rapid antibunching super-resolution imaging and demonstrate 12 times speed-up compared to conventional, fitting-based autocorrelation measurements. The developed framework paves the way to the practical realization of scalable quantum super-resolution imaging devices that can be compatible with various types of quantum emitters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Thermodynamics, dynamics, and structure of supercritical water at extreme conditions

Molecular dynamics (MD) simulations to understand the thermodynamic, dynamic, and structural changes in supercritical water across the Frenkel line and the melting line have been performed. The two-phase thermodynamic model [J. Phys. Chem. B(2010), 114(24), 8191-8198] and the velocity autocorrelation functions are used to locate the Frenkel line and to calculate the thermodynamic and dynamic properties. The Frenkel lines obtained from the two-phase thermodynamic model and the velocity autocorrelation criterion do not agree with each other. Structural characteristics and the translational diffusion dynamics of water suggest that this inconsistency could arise from the two oscillatory modes in water, which are associated with the bending of hydrogen bonds and intermolecular collisions inside the first coordination shell. Finally, the overall results lead us to conclude that the universality of the Frenkel line as a dynamic crossover line from rigid to nonrigid fluids is preserved in water.

74 ATOMIC AND MOLECULAR PHYSICS↗

Clustering of CODEX clusters

The clustering of galaxy clusters links the spatial nonuniformity of dark matter halos to the growth of the primordial spectrum of perturbations. The amplitude of the clustering signal is widely used to estimate the halo mass of astrophysical objects. The advent of cluster mass calibrations enables using clustering in cosmological studies. Aims. We analyze the autocorrelation function of a large contiguous sample of galaxy clusters, the Constrain Dark Energy with X-ray (CODEX) sample, in which we take particular care of cluster definition. These clusters were X-ray selected using the ROentgen SATellite All-Sky Survey and then identified as galaxy clusters using the code redMaPPer run on the photometry of the Sloan Digital Sky Survey. We develop methods for precisely accounting for the sample selection effects on the clustering and demonstrate their robustness using numerical simulations. Methods. Using the clean CODEX sample, which was obtained by applying a redshift-dependent richness selection, we computed the two-point autocorrelation function of galaxy clusters in the 0.1 < z < 0.3 and 0.3 < z < 0.5 redshift bins. We compared the bias in the measured correlation function with values obtained in numerical simulations using a similar cluster mass range. Results. By fitting a power law, we measured a correlation length r 0 = 18.7 ± 1.1 and slope γ = 1.98 ± 0.14 for the correlation function in the full redshift range. By fixing the other cosmological parameters to their nine-year Wilkinson Microwave Anisotropy Probe values, we reproduced the observed shape of the correlation function under the following cosmological conditions: Ω m0 = $0.22_{-0.03}^{+0.04}$ and S 8 = σ 8 (Ω m0 /0.3)0.5 = $0.85_{-0.08}^{+0.10}$ with estimated additional systematic errors of σ Ω m0 = 0.02 and σS 8 = 0.20. We illustrate the complementarity of clustering constraints by combining them with CODEX cosmological constraints based on the X-ray luminosity function, deriving Ωm = 0.25 ± 0.01 and σ 8 = $0.81_{-0.02}^{+0.01}$ with an estimated additional systematic error of σ Ω m0 = 0.07 and σ σ8 = 0.04. The mass calibration and statistical quality of the mass tracers are the dominant source of uncertainty.

79 ASTRONOMY AND ASTROPHYSICS↗

Lattice thermal conductivity of UO{sub 2} using ab-initio and classical molecular dynamics

We applied the non-equilibrium ab-initio molecular dynamics and predict the lattice thermal conductivity of the pristine uranium dioxide for up to 2000 K. We also use the equilibrium classical molecular dynamics and heat-current autocorrelation decay theory to decompose the lattice thermal conductivity into acoustic and optical components. The predicted optical phonon transport is temperature independent and small, while the acoustic component follows the Slack relation and is in good agreement with the limited single-crystal experimental results. Considering the phonon grain-boundary and pore scatterings, the effective lattice thermal conductivity is reduced, and we show it is in general agreement with the sintered-powder experimental results. The charge and photon thermal conductivities are also addressed, and we find small roles for electron, surface polaron, and photon in the defect-free structures and for temperatures below 1500 K.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Damping constant estimation in magnetoresistive readers

The damping constant is a key design parameter in magnetic reader design. Its value can be derived from bulk or sheet film ferromagnetic resonance (FMR) line width. However, dynamics of nanodevices is usually defined by presence of non-uniform modes. It triggers new damping mechanisms and produces stronger damping than expected from traditional FMR. This work proposes a device-level technique for damping evaluation, based on time-domain analysis of thermally excited stochastic oscillations. The signal is collected using a high bandwidth oscilloscope, by direct probing of a biased reader. Recorded waveforms may contain different noise signals, but free layer FMR is usually a dominating one. The autocorrelation function is a reflection of the damped oscillation curve, averaging out stochastic contributions. The damped oscillator formula is fitted to autocorrelation data, producing resonance frequency and damping constant values. Restricting lag range allows for mitigation of the impact of other phenomena (e.g., reader instability) on the damping constant. For a micromagnetically modeled reader, the technique proves to be much more accurate than the stochastic FMR line width approach. Application to actual reader waveforms yields a damping constant of ∼0.03.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Magnetohydrodynamic turbulence: Observation and experiment

We provide a tutorial on the paradigms and tools of magnetohydrodynamic (MHD) turbulence. The principal paradigm is that of a turbulent cascade from large scales to small, resulting in power law behavior for the frequency power spectrum for magnetic fluctuations E{sub B}(f). We will describe five useful statistical tools for MHD turbulence in the time domain: the temporal autocorrelation function, the frequency power spectrum, the probability distribution function of temporal increments, the temporal structure function, and the permutation entropy. Each of these tools will be illustrated with an example taken from MHD fluctuations in the solar wind. A single dataset from the Wind satellite will be used to illustrate all five temporal statistical tools.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗