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Results for “dynamical correlation”

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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Anomalous spin polarization from turbulent color fields

Here we study the important, yet widely overlooked, role of gluons for spin transport with a connection to local parity violation in quark gluon plasmas. We employ the formalism of quantum kinetic theory to quarks in weakly coupled quantum chromodynamics to derive the source terms for quark spin polarization. These source terms involve parity-odd correlators of dynamically generated color fields in near-equilibrium quark gluon plasmas and give rise to locally fluctuating axial charge currents. Our results provide a possible explanation for the spin alignment of vector mesons measured in high-energy nuclear collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Emergent Z 2 Gauge Theories and Topological Excitations in Rydberg Atom Arrays

Strongly interacting arrays of Rydberg atoms provide versatile platforms for exploring exotic many-body phases and dynamics of correlated quantum systems. Motivated by recent experimental advances, we show that the combination of Rydberg interactions and appropriate lattice geometries naturally leads to emergent Z 2 gauge theories endowed with matter fields. Based on this mapping, we describe how Rydberg platforms could realize two distinct classes of topological Z 2 quantum spin liquids, which differ in their patterns of translational symmetry fractionalization. Additionally, we also discuss the natures of the fractionalized excitations of these Z 2 spin liquid states using both fermionic and bosonic parton theories and illustrate their rich interplay with proximate solid phases.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Superdiffusion from Nonabelian Symmetries in Nearly Integrable Systems

The Heisenberg spin chain is a canonical integrable model. As such, it features stable ballistically propagating quasiparticles, but spin transport is subballistic at any nonzero temperature: An initially localized spin fluctuation spreads in time t to a width t 2/3 . This exponent as well as the functional form of the dynamical spin correlation function suggest that spin transport is in the Kardar–Parisi–Zhang (KPZ) universality class. However, the full counting statistics of magnetization is manifestly incompatible with KPZ scaling. A simple two-mode hydrodynamic description, derivable from microscopic principles, captures both the KPZ scaling of the correlation function and the coarse features of the full counting statistics, but remains to be numerically validated. These results generalize to any integrable spin chain invariant under a continuous nonabelian symmetry and are surprisingly robust against moderately strong integrability-breaking perturbations that respect the nonabelian symmetry.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Noncollinear, inelastic four-wave mixing in the extreme ultraviolet

Driving four-wave mixing (FWM) processes with extreme ultraviolet (EUV) pulses could enable experimental approaches that have the potential to provide unique information on dynamics and correlations. In this work, we demonstrate inelastic FWM obtained by noncollinear mixing of two EUV pulses with different photon energies and an optical pulse in a diamond sample. This three-pulse interaction leads to the emission of an optical signal, propagating in the phase-matching direction and blue shifted by the photon energy difference of the two EUV pulses. The presented results demonstrate the feasibility of experiments such as the soft X-ray analogue of coherent anti-Stokes Raman scattering, so far only theoretically conceived [ Phys. Rev. Lett. 89 , 043001 ( 2002 ) PRLTAO 0031-9007 10.1103/PhysRevLett.89.043001 ], which can be further extended for studying vibrational and electronics dephasing in solid, liquid, or gaseous samples.

Mincigrucci, R. (ORCID:0000000163436256)↗
DOE OSTI2024

Elucidating Abnormal Grain Growth in Thermomagnetic Processed Materials with Transfer Learning and Reinforcement Learning

The goal of this research program is to establish the mechanism governing local grain boundary motion, which is needed to design and process desirable microstructures for better performance, by identifying the relative contributions of grain boundary (GB) energy and mobility to grain growth. Classical models for grain growth assume that the primary mechanism for reducing the total interfacial energy is area reduction and that GB restructuring is not significant. This assumption implies that grain growth is locally driven by curvature. However, recent experimental observations using new non-destructive 3D x-ray diffraction microscopy techniques (3D-XRM) reveal that classic descriptors (i.e., curvature, number of neighbors, grain size) do not predict real grain growth. Instead, local GB motion appears to be governed by its energy relative to its neighbors such that low-energy boundaries replace those of higher energy. However, simulations that incorporate GB energy anisotropy still fail to reproduce these observations. These discrepancies suggest that the common assumption for grain growth theory must be re-examined to predict and, thus, control microstructure evolution in real polycrystals. A significant challenge to testing this assumption is due to anisotropic GB mobility. Mobility may cause abnormal grain growth or affect the final grain shapes or growth rate but its true contributions are unknown because it is difficult to measure. For example, observations in Fe have found that grains associated with high energy and high mobility boundaries tend to experience abnormal grain growth, whereas abnormal grain growth is associated with low energy and high mobility boundaries in alumina. As mobility and energy both control GB motion, it is challenging to isolate the local driving forces necessary to test the common assumption that the primary mechanism is area reduction. The novelty of this work is the use of machine learning tools to capture GB mobility and energy from 3D-XRM measurements in polycrystals to test the common assumption used in grain growth models. Machine learning can capture high-order correlations in dynamic systems like those found in the evolving GB topology. The PIs have developed a physics-regularized interpretable machine learning microstructure evolution (PRIMME) model that accurately replicates the grain growth behavior of its trained data set.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Sextupole reduction via chaos suppression at NSLS-II

We revisit the nonlinear lattice design approach for the National Synchrotron Light Source II (NSLS-II) storage ring. By suppressing chaos, we identify alternative sextupole configurations to the original design, which relied on the conventional approach of simultaneously minimizing Resonance Driving Terms (RDTs) and Amplitude-Dependent Detuning (ADD). These alternatives achieve comparable performance while requiring fewer sextupoles. A detailed comparison of two representative solutions is presented and supported by experimental validation. Our results indicate that dynamic aperture correlates more strongly with global chaos than with individual RDTs, and that the importance of minimizing ADD may have been overstated in earlier design approach.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Inner-Shell Photodetachment of Na – Using R-Matrix Methods

Inner-shell photodetachment of Na – near the L-edge threshold was investigated using the R-matrix method. Significant structure was found in the cross section, and this structure is shown to be related to the complicated correlated electron dynamics endemic in negative ions. Comparison with experiment suggests that the absolute values of the measured cross section might be too small by a factor of two.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Review: Real-space analyses of local dynamics in liquid using X-ray scattering

In this review, we advocate describing the liquid dynamics using the Van Hove correlation function, a temporal and spatial correlation function. Recent progress in X-ray optics and X-ray sources makes it possible to carry out inelastic and quasi-elastic x-ray scattering whose spectra can be converted into the dynamic correlation function in real space. We describe the basic concept of the Van Hove correlation function, how it is obtained from the X-ray scattering spectra using synchrotron X-rays and X-ray free electron lasers, and the atomic dynamics in water and aqueous salt solution.

Shinohara, Yuya↗
DOE OSTI2025

Constraints on magnetism and correlations in RuO 2 from lattice dynamics and Mössbauer spectroscopy

We provide experimental evidence for the absence of a magnetic moment in bulk RuO 2 , a candidate altermagnetic material, by using a combination of Mössbauer spectroscopy, nuclear forward scattering, inelastic X-ray and neutron scattering, and density functional theory calculations. Using complementary Mössbauer and nuclear forward scattering, we determine the Ru magnetic hyperfine splitting to be negligible. Inelastic X-ray and neutron scattering-derived lattice dynamics of RuO 2 are compared to density functional theory calculations of varying flavors. Comparisons among theory with experiments indicate that electronic correlations, rather than magnetic order, are key in describing the lattice dynamics.

Mössbauer spectroscopy↗
DOE OSTI2021

Nanoscale dynamics during self-organized ion beam patterning of Si. I. Ar + bombardment

X-ray photon correlation spectroscopy (XPCS) is used to investigate the fluctuation dynamics during self- organized nanopatterning of silicon by Ar + bombardment at 65° polar angle. Rich structure is observed in the development of the correlation dynamics as seen in the evolving correlation time τ(q || ) and fluctuation relaxation exponent n(q || ). Furthermore, on length scales of the ripple structure, local structure becomes ever more long lived as coarsening progresses. In addition, τ (q || ) develops a peak on length scales corresponding to the ripple wavelength. As patterning progresses, correlation times become asymmetric between the positive and negative directions, suggesting the possibility of different dynamics on the slopes facing toward and away from the ion beam. Relaxation exponents show evolution from linear dynamics at early times to compressed exponential relaxation at low wave numbers and stretched exponential relaxation at high wave numbers. Compressed exponential behavior is reminiscent of stress relaxation processes observed in glasses.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Sequence Modulates Polypeptoid Hydration Water Structure and Dynamics

We use molecular dynamics simulations to investigate the effect of polypeptoid sequence on the structure and dynamics of its hydration waters. Polypeptoids provide an excellent platform to study small-molecule hydration in disordered polymers, as they can be precisely synthesized with a variety of sidechain chemistries. We examine water behavior near a set of peptoid oligomers in which the number and placement of nonpolar versus polar sidechains are systematically varied. To do this, we leverage a new computational workflow enabling accurate sampling of polypeptoid conformations. We find that the hydration waters are less dense, are more tetrahedral, and have slower dynamics compared to bulk water. The magnitude of these shifts increases with the number of nonpolar groups. Here, we also find that shifts in the water structure and dynamics are strongly correlated, suggesting that experimental insight into the dynamics of hydration water obtained by Overhauser dynamic nuclear polarization (ODNP) also contains information about water structural properties. We then demonstrate the ability of ODNP to probe site-specific dynamics of hydration water near these model peptoid systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dynamics of non-Gaussian fluctuations in model A

Motivated by the experimental search for the QCD critical point, we perform simulations of a stochastic field theory with purely relaxational dynamics (model A). We verify the expected dynamic scaling of correlation functions. Using a finite size scaling analysis, we obtain the dynamic critical exponent z = 2.026(56). We investigate time dependent correlation functions of higher moments M n (t) of the order parameter M(t) for n = 1, 2, 3, 4. We obtain dynamic scaling with the same critical exponent z for all n, but the relaxation constant depends on n. We also study the relaxation of M n (t) after a quench, where the simulation is initialized in the high temperature phase, and the dynamics is studied at the critical temperature T c . Finally, we find that the evolution does not follow simple scaling with the dynamic exponent z, and that it involves an early time rise followed by late stage relaxation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

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↗
DOE OSTI2022

MSASGCN : Multi-Head Self-Attention Spatiotemporal Graph Convolutional Network for Traffic Flow Forecasting

Traffic flow forecasting is an essential task of an intelligent transportation system (ITS), closely related to intelligent transportation management and resource scheduling. Dynamic spatial-temporal dependencies in traffic data make traffic flow forecasting to be a challenging task. Most existing research cannot model dynamic spatial and temporal correlations to achieve well-forecasting performance. The multi-head self-attention mechanism is a valuable method to capture dynamic spatial-temporal correlations, and combining it with graph convolutional networks is a promising solution. Therefore, we propose a multi-head self-attention spatiotemporal graph convolutional network (MSASGCN) model. It can effectively capture local correlations and potential global correlations of spatial structures, can handle dynamic evolution of the road network, and, in the time dimension, can effectively capture dynamic temporal correlations. Experiments on two real datasets verify the stability of our proposed model, obtaining a better prediction performance than the baseline algorithms. The correlation metrics get significantly reduced compared with traditional time series prediction methods and deep learning methods without using graph neural networks, according to MAE and RMSE results. Compared with advanced traffic flow forecasting methods, our model also has a performance improvement and a more stable prediction performance. We also discuss some problems and challenges in traffic forecasting.

Cao, Yang↗
DOE OSTI2026

Rotational memory function of SPC/E water

Memory effects are essential for the dynamics of condensed materials and are responsible for non-exponential relaxation of correlation functions of dynamic variables through the memory function. Memory functions of dipole rotations for water have never been calculated directly from molecular dynamics simulations. We present here calculations of memory functions for single-dipole rotations and for the overall dipole moment of the sample for SPC/E water. The normalized memory functions for single-particle and collective dipole dynamics turn out to be nearly identical. This result validates theories of dielectric spectroscopy in terms of single-particle time correlation functions and the connection between the collective and single-particle relaxation times through the Kirkwood factor. The dielectric function in this formalism contains no new dynamic information that does not exist in the single-dipole correlation function. A short memory time, ≲1 fs, justifies the use of the mathematics of rotational diffusion to describe the dynamics of a single molecular dipole moment in bulk water. Here, an analytical equation for the rotational memory time is derived.

Asthagiri, Dilipkumar N. [Oak Ridge National Labor↗
DOE OSTI2021

Probing the interplay between lattice dynamics and short-range magnetic correlations in CuGeO 3 with femtosecond RIXS

Investigations of magnetically ordered phases on the femtosecond timescale have provided significant insights into the influence of charge and lattice degrees of freedom on the magnetic sub-system. However, short-range magnetic correlations occurring in the absence of long-range order, for example in spin-frustrated systems, are inaccessible to many ultrafast techniques. Here, we show how time-resolved resonant inelastic X-ray scattering (trRIXS) is capable of probing such short-ranged magnetic dynamics in a charge-transfer insulator through the detection of a Zhang–Rice singlet exciton. Utilizing trRIXS measurements at the O K-edge, and in combination with model calculations, we probe the short-range spin correlations in the frustrated spin chain material CuGeO 3 following photo-excitation, revealing a strong coupling between the local lattice and spin sub-systems.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Toward Decoding the Relationship between Domain Structure and Functionality in Ferroelectrics via Hidden Latent Variables

Polarization switching mechanisms in ferroelectric materials are fundamentally linked to local domain structure and the presence of the structural defects, which both can act as nucleation and pinning centers and create local electrostatic and mechanical depolarization fields affecting wall dynamics. However, the general correlative mechanisms between domain structure and polarization dynamics are only weakly explored, precluding insight into the associated physical mechanisms. In this work, the correlation between local domain structures and switching behavior in ferroelectric materials is explored using convolutional encoder–decoder networks, enabling image to spectral (im2spec) and spectral to image (spec2im) translations via encoding of latent variables. The latter reflect the assumption that the relationship between domain structure and polarization switching is parsimonious, i.e., is based upon a small number of local mechanisms. The analysis of latent variables distributions and their real-space representations provides insight into the predictability of the local switching behavior and hence associated physical mechanisms. We further pose that the regions where these correlative relationships are violated, i.e., predictability of the polarization dynamics from domain structure is reduced, represent the obvious target for detailed studies, e.g., in the context of automated experiments. This approach provides a workflow to establish the presence of correlation between local spectral responses and local structure and can be universally applied to spectral imaging techniques such as piezoresponse force microscopy (PFM), scanning tunneling microscopy (STM) and spectroscopy, and electron energy loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM).

36 MATERIALS SCIENCE↗