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At least 325 records · Page 18

Microwave soft x-ray microscopy for nanoscale magnetization dynamics in the 5–10 GHz frequency range

We present a scanning transmission x-ray microscopy setup combined with a novel microwave synchronization scheme for studying high frequency magnetization dynamics at synchrotron light sources. The sensitivity necessary to detect small changes in the magnetization on short time scales and nanometer spatial dimensions is achieved by combining the excitation mechanism with single photon counting electronics that is locked to the synchrotron operation frequency. Our instrument is capable of creating direct images of dynamical phenomena in the 5-10 GHz range, with high spatial resolution. When used together with circularly polarized x-rays, the above capabilities can be combined to study magnetic phenomena at microwave frequencies, such as ferromagnetic resonance (FMR) and spin waves. We demonstrate the capabilities of our technique by presenting phase resolved images of a ∼6 GHz nanoscale spin wave generated by a spin torque oscillator, as well as the uniform ferromagnetic precession with ∼0.1° amplitude at ∼9 GHz in a micrometer-sized cobalt strip.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Molecular dynamics simulations of the structure and single-particle dynamics of mixtures of divalent salts and ionic liquids

We report a molecular dynamics study of the structure and single-particle dynamics of mixtures of a protic (ethylammonium nitrate) and an aprotic (1-butyl-3-methylimidazolium hexaflurophosphate [BMIM][PF{sub 6}]) room-temperature ionic liquids doped with magnesium and calcium salts with a common anion at 298.15 K and 1 atm. The solvation of these divalent cations in dense ionic environments is analyzed by means of apparent molar volumes of the mixtures, radial distribution functions, and coordination numbers. For the protic mixtures, the effect of salt concentration on the network of hydrogen bonds is also considered. Moreover, single-particle dynamics of the salt cations is studied by means of their velocity autocorrelation functions and vibrational densities of states, explicitly analyzing the influence of salt concentration, and cation charge and mass on these magnitudes. The effect of the valency of the salt cation on these properties is considered comparing the results with those for the corresponding mixtures with lithium salts. We found that the main structural and dynamic features of the local solvation of divalent cations in ionic liquids are similar to those of monovalent salts, with cations being localized in the polar nanoregions of the bulk mixture coordinated in monodentate and bidentate coordination modes by the [NO{sub 3}]{sup −} and [PF{sub 6}]{sup −} anions. However, stronger electrostatic correlations of these polar nanoregions than in mixtures with salts with monovalent cations are found. The vibrational modes of the ionic liquid (IL) are seen to be scarcely affected by the addition of the salt, and the effect of mass and charge on the vibrational densities of states of the dissolved cations is reported. Cation mass is seen to exert a deeper influence than charge on the low-frequency vibrational spectra, giving a red shift of the vibrational modes and a virtual suppression of the higher energy vibrational modes for the heavier Ca{sup 2+} cations. No qualitative difference with monovalent cations was found in what solvation is concerned, which suggests that no enhanced reduction of the mobility of these cations and their complexes in ILs respective to those of monovalent cations is to be expected.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Insight into the Li{sub 2}CO{sub 3}–K{sub 2}CO{sub 3} eutectic mixture from classical molecular dynamics: Thermodynamics, structure, and dynamics

We use molecular dynamics simulations to study the thermodynamics, structure, and dynamics of the Li{sub 2}CO{sub 3}–K{sub 2}CO{sub 3} (62:38 mol. %) eutectic mixture. We present a new classical non-polarizable force field for this molten salt mixture, optimized using experimental and first principles molecular dynamics simulations data as reference. This simple force field allows efficient molecular simulations of phenomena at long time scales. We use this optimized force field to describe the behavior of the eutectic mixture in the 900–1100 K temperature range, at pressures between 0 and 5 GPa. After studying the equation of state in these thermodynamic conditions, we present molecular insight into the structure and dynamics of the melt. In particular, we present an analysis of the temperature and pressure dependence of the eutectic mixture’s self-diffusion coefficients, viscosity, and ionic conductivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Maxwell–Stefan diffusion and dynamical correlation in molten LiF-KF: A molecular dynamics study

In this work our main objective is to compute Dynamical correlations, Onsager coefficients and Maxwell-Stefan (MS) diffusivities for molten salt LiF-KF mixture at various thermodynamic states through Green–Kubo formalism for the first time. The equilibrium molecular dynamics (MD) simulations were performed using BHM potential for LiF–KF mixture. The velocity autocorrelations functions involving Li ions reflect the endurance of cage dynamics or backscattering with temperature. The magnitude of Onsager coefficients for all pairs increases with increase in temperature. Interestingly most of the Onsager coefficients has almost maximum magnitude at the eutectic composition indicating the most dynamic character of the eutectic mixture. MS diffusivity hence diffusion for all ion pairs increases in the system with increasing temperature. Smooth variation of the diffusivity values denies any network formation in the mixture. Also, the striking feature is the noticeable concentration dependence of MS diffusivity between cation-cation pair, Đ{sub Li-K} which remains negative for most of the concentration range but changes sign to become positive for higher LiF concentration. The negative MS diffusivity is acceptable as it satisfies the non-negative entropy constraint governed by 2{sup nd} law of thermodynamics. This high diffusivity also vouches the candidature of molten salt as a coolant.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Insights into the structure and dynamics of K + ions at the muscovite–water interface from machine learning potential simulations

The surfaces of many minerals are covered by naturally occurring cations that become partially hydrated and can be replaced by hydronium or other cations when the surface is exposed to water or an aqueous solution. These ion exchange processes are relevant to various chemical and transport phenomena, yet elucidating their microscopic details is challenging for both experiments and simulations. Here, in this work, we make a first step in this direction by investigating the behavior of the native K + ions at the interface between neat water and the muscovite mica (001) surface with ab-initio -based machine learning molecular dynamics and enhanced sampling simulations. Our results show that the desorption of the surface K + ions in pure ion-free water has a significant free energy barrier irrespective of their local surface arrangement. In contrast, facile K + diffusion between mica’s ditrigonal cavities characterized by different Al/Si orderings is observed. This behavior suggests that the K + ions may favor a dynamic disordered surface arrangement rather than complete desorption when exposed to deionized water.

Ab-initio molecular dynamics↗

Dynamical Self-Assembly: Constrained phase separation and mesoscale dynamics in lipid membranes (Final Report)

This final technical report summarizes scientific and technical achievements derived through the the award, DE-FG02-04ER46173 [2013-2016, 2016-2017, and 2017-2018(NCE)], for the grant proposal titled, “Dynamical Self-Assembly: Constrained phase separation and mesoscale dynamics in lipid membranes.” The effort was organized into three major scientific aims: (1) characterize the mechanism of inter-layer coupling of laterally phase-separated domains in stacked lipid bilayers; (2) characterize curvature-dependent dynamic reorganization in membrane milieu; and (3) characterize real-time effects of mechanochemical perturbations on lateral phase separation membrane bilayers. The cumulative weight of the activities, including experimental research and collaborative modeling, disseminated through the publications listed above and presentations, has addressed two over-arching objectives: (a) to abstract a physical science based understanding of fundamental rules that determine dynamic self-assembly processes in lipid bilayer membranes - a versatile class of biologically inspired interfacial complex fluids and (b) to translate these physical principles into quantitative design rules for the development of new classes of membrane-based complex materials that exhibit complex, co-operative, and adaptive behavior.

36 MATERIALS SCIENCE↗

Mathematical Modeling of Microbial Community Dynamics: A Methodological Review

Microorganisms in nature form diverse communities that dynamically change in structure and function in response to environmental variations. As a complex adaptive system, microbial communities show higher-order properties that are not present in individual microbes, but arise from their interactions. Predictive mathematical models not only help to understand the underlying principles of the dynamics and emergent properties of natural and synthetic microbial communities, but also provide key knowledge required for engineering them. In this article, we provide an overview of mathematical tools that include not only current mainstream approaches, but also less traditional approaches that, in our opinion, can be potentially useful. We discuss a broad range of methods ranging from low-resolution supra-organismal to high-resolution individual-based modeling. Particularly, we highlight the integrative approaches that synergistically combine disparate methods. In conclusion, we provide our outlook for the key aspects that should be further developed to move microbial community modeling towards greater predictive power.

Song, Hyun-Seob↗

An Approach to Dynamic Human Reliability Analysis using EMRALD Dynamic Risk Assessment Tool

Research for dynamic human reliability analysis (HRA) (a.k.a., simulation-based or computation-based HRA) has been required, as many researchers have emphasized the importance of dynamic approaches to probabilistic safety assessment (PSA). This study proposes the PRocedure-based Investigation Method of EMRALD Risk Assessment – Human Reliability Analysis (PRIMERA-HRA) method, which is an approach to dynamic HRA using the Event Modeling Risk Assessment using Linked Diagram (EMRALD) software developed by Idaho National Laboratory (INL). In this study, how to model human actions using the software and evaluate the error probabilities is suggested. The applicability of this approach will be also investigated through an extended loss of AC power (ELAP) scenario. Then, major insights from this dynamic HRA approach against the static one will be discussed in the paper.

99 GENERAL AND MISCELLANEOUS↗

An Approach to Dynamic Human Reliability Analysis Using the EMRALD Dynamic Risk Assessment Tool

There is a need for research into dynamic human reliability analysis (HRA) (i.e., simulation- or computation-based HRA), as many researchers have emphasized the importance of applying dynamic approaches to probabilistic safety assessments (PSAs). This study proposes the Procedure-based Investigation Method of EMRALD Risk Assessment – Human Reliability Analysis (PRIMERA-HRA), a dynamic HRA approach based on the Event Modeling Risk Assessment Using Linked Diagram (EMRALD) software developed by Idaho National Laboratory (INL). This study suggests how this software can be used to model human actions and evaluate error probabilities. The applicability of this approach is also be investigated in light of an extended loss of AC power (ELAP) scenario. This paper then discusses the major insights derived by comparing this dynamic HRA approach against the static one.

99 GENERAL AND MISCELLANEOUS↗

Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape: Modeling Archive

This modeling archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025). This archive contains model input files and outputs from landscape-scale simulations conducted using ELM, the land model component of the Department of Energy’s Energy Exascale Earth System Model (E3SM), at the Council NGEE Arctic field site (Council Road mile marker 71) on Alaska’s Seward Peninsula. Input data and model output from two sets of ELM simulations are provided. The first set of simulations were conducted with the two default ELM Arctic plant functional types (PFTs; broadleaf deciduous boreal shrub and a C3 grass) and the second set of simulations were conducted with a set of nine Arctic-specific PFTs including nonvascular mosses and lichens, graminoids, forbs, evergreen dwarf shrubs, three height classes of deciduous shrubs (dwarf, low, and low to tall), and deciduous alder shrubs (Sulman et al., 2021). Parameter names and major parameter changes in the Arctic-specific PFT configuration are described in Sulman et al. (2021) and archived in the Sulman et al. (2021) dataset (see below). Simulations were spatially explicit, covering an approximately 6.4X3.3 km domain at the Council site with a spatial resolution of 100 m for a total of 2,112 simulated grid cells under each ELM PFT configuration. The modeling archive contains meteorological forcing (seven *.nc files and one *.txt file), a domain definition file (one *.nc files), land surface configuration files (two *.nc files), parameter files (two *.nc files), annual ELM output files spanning 1980-2014 (68 *.nc files), and a User’s Guide (*pdf file). Additional information on the provided files is in the “Modeling Archive Contents” section of the User’s Guide. Model outputs are aggregated to the column scale (i.e. PFT-specific outputs are not provided here).

Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗

PyCCE: A python package for custer correlation expansion simulations of spin qubit dynamics.

PyCCE, an open-source Python library for simulating the dynamics of spin qubits in a spin bath, is presented using the cluster-correlation expansion (CCE) method. PyCCE includes modules to generate realistic spin baths, employing coupling parameters computed from first principles with electronic structure codes, and enables the user to run simulations with either the conventional or generalized CCE method. Three use cases of the Python library are illustrated: the calculation of the Hahn-echo coherence time of the nitrogen-vacancy in diamond; the calculation of the coherence time of the basal divacancy in silicon carbide at avoided crossings; and the calculation for magnetic field orientation-dependent dynamics of a shallow donor in silicon. The complete documentation, downloadable tutorials, and installation instructions are available at https://pycce.readthedocs.io/en/latest/.

coherence↗

Nanoconfinement Inside Molecular Metal Oxide Clusters: Dynamics and Modified Encapsulation Behavior

Abstract Encapsulation behavior, as well as the presence of internal catalytically active sites, has been spurring the applications of a 3 nm hollow spherical metal oxide cluster {Mo 132 } as an encapsulation host and a nanoreactor. Due to its well‐defined and tunable cluster structures, and nanoscaled internal void space comparable to the volumes of small molecules, this cluster provides a good model to study the dynamics of materials under nanoconfinement. Neutron scattering studies suggest that bulky internal ligands inside the cluster show slower and limited dynamics compared to their counterparts in the bulk state, revealing the rigid nature of the skeleton of the internal ligands. NMR studies indicate that the rigid internal ligands that partially cover the interfacial pore on the molybdenum oxide shells are able to block some large guest molecules from going inside the capsule cluster, which provides a convincing protocol for size‐selective encapsulation and separation.

Wang, Zhe↗

Different dynamics and pathway of disulfide bonds reduction of two human defensins, a molecular dynamics simulation study

Human defensins are a class of antimicrobial peptides that are crucial components of the innate immune system. Both human α defensin type 5 (HD5) and human β defensin type 3 (hBD-3) have 6 cysteine residues which form 3 pairs of disulfide bonds in oxidizing condition. Disulfide bond linking is important to the protein structure stabilization, and the disulfide bond linking and breaking order have been shown to influence protein function. In this project, microsecond long molecular dynamics simulations were performed to study the structure and dynamics of HD5 and hBD-3 wildtype and analogs which have all 3 disulfide bonds released in reducing condition. The structure of hBD-3 was found to be more dynamic and flexible than HD5, based on RMSD, RMSF, and radius of gyration calculations. The disulfide bridge breaking order of HD5 and hBD-3 in reducing condition was predicted by two kinds of methods, which gave consistent results. It was found that the disulfide bonds breaking pathways for HD5 and hBD-3 are very different. The breaking of disulfide bonds can influence the dimer interface by making the dimer structure less stable for both kinds of defensin. In order to understand the difference in dynamics and disulfide bond breaking pathway, hydrophilic and hydrophobic accessible surface areas (ASA), buried surface area between cysteine pairs, entropy of cysteine pairs, and internal energy were calculated. Comparing to the wildtype, hBD-3 analog is more hydrophobic, while HD5 is more hydrophilic. For hBD-3, the disulfide breaking is mainly entropy driven, while other factors such as the solvation effects may take the major role in controlling HD5 disulfide breaking pathway. Proteins 2017; 85:665–681. © 2016 Wiley Periodicals, Inc.

Biochemistry & Molecular Biology↗

A Comparison of Reduced Order Modeling Techniques Used in Dynamic Substructuring [PowerPoint]

Experimental dynamic substructuring is a means whereby a mathematical model for a substructure can be obtained experimentally and then coupled to a model for the rest of the assembly to predict the response. Recently, various methods have been proposed that use a transmission simulator to overcome sensitivity to measurement errors and to exercise the interface between the substructures; including the Craig-Bampton, Dual Craig-Bampton, and Craig-Mayes methods. This work compares the advantages and disadvantages of these reduced order modeling strategies for two dynamic substructuring problems. The methods are first used on an analytical beam model to validate the methodologies. Then they are used to obtain an experimental model for structure consisting of a cylinder with several components inside connected to the outside case by foam with uncertain properties. This represents an exceedingly difficult structure to model and so experimental substructuring could be an attractive way to obtain a model of the system.

97 MATHEMATICS AND COMPUTING↗

High-order fully implicit solver for all-speed fluid dynamics: AUSM ride from nearly incompressible variable-density flows to shock dynamics

We introduce a novel Newton–Krylov (NK)-based fully implicit algorithm for solving fluid flows in a wide range of flow conditions—from variable density nearly incompressible to supersonic shock dynamics. The key enabling feature of our all-speed solver is the ability to efficiently solve conservation laws by choosing a set of independent variables that produce a well-conditioned Jacobian matrix for the linear iterations of the global nonlinear iterative solver. In particular, instead of choosing to discretize the conservative variables (density, momentum, total energy), which is traditionally used in Eulerian high-speed compressible fluid dynamics, we demonstrate superior performance by discretizing the primitive variables—pressure–velocity–temperature in the very low-Mach flow limits or density–velocity–temperature/entropy in the shock dynamics range. Moreover, our method allows us to avoid direct inversion of the mass matrix in discrete time derivatives, which is usually an additional source for stiffness, especially pronounced when going to very high-order schemes with non-orthogonal basis functions. Here, we show robust solutions obtained for discontinuous finite element discretization up to seventh-order accuracy. Another important aspect of the solution algorithm is the Advection Upstream Splitting Method (AUSM), adopted to compute numerical fluxes within our reconstructed discontinuous Galerkin (rDG) spatial discretization scheme. The use of the low-Mach modification of the hyperbolic flux operator is found to be necessary for enabling robust simulations of very stiff liquids and metals for Mach numbers below M=10 -5 , which is well known to be very computationally challenging for compressible solvers. We demonstrate that our fully implicit rDG-NK solver with the AUSM + -up flux treatment produces efficient and high-resolution numerical solutions at all speeds, ranging from vanishing Mach numbers to transonic and supersonic, without substantial modifications of the solution procedures. (At high speed, we add limiting and use a simpler preconditioning of the Krylov solver.) Numerical examples include nearly incompressible constant-property flow past a backward-facing step with heat transfer, low-Mach variable-property channel flow of water at supercritical state, phase change and melt pool dynamics for laser spot welding and selective laser melting in additive manufacturing, and Mach 3 flow in a wind tunnel with a step.

97 MATHEMATICS AND COMPUTING↗

Virtual diffraction simulations using the quasi-coarse-grained dynamics method to understand and interpret plasticity contributions during in situ shock experiments

The dynamic deformation response of metallic materials has contributions from dislocations, deformation twinning, and plastic deformation. The current state-of-art techniques can detail the complex mechanistic history of deformation modes under shock loading in real-time using in situ X-ray diffraction (XRD). However, the capability of these experiments to unravel plasticity contributions is challenging due to limitations in interpreting results and the lack of validation from atomistic simulations. Molecular dynamics (MD) simulations can successfully capture various deformation modes in metals and complement experiments using simulated diffractograms at various stages of evolution. However, the difference in length and time scales of MD simulations and experiments is a substantial obstacle in completing and interpreting in situ diffractograms. Therefore, the existing modeling methods require various approximations to model defect evolution and interaction at the mesoscales. However, while using approximations to correlate the peak broadening behavior to the density of dislocations or the shifts/splitting due to the presence of twins, the interpretations of the plasticity contributions from diffractograms are non-trivial, especially when multiple modes of deformation may be operating. This viewpoint discusses combining a mesoscale modeling method called quasi-coarse-grained dynamics and virtual XRD to characterize the plasticity contributions in BCC metals from slip, twinning, and phase transformation behavior. Furthermore, the combined approach shows promise in bridging the mesoscale gap between the capabilities of atomic-scale simulations and in situ experiments to characterize the dynamic deformation of materials.

36 MATERIALS SCIENCE↗

Nonequilibrium Dynamical Mean-Field Theory for the Charge-Density-Wave Phase of the Falicov-Kimball Model

Nonequilibrium dynamical mean-field theory (DMFT) is developed for the case of the charge-density-wave ordered phase. We consider the spinless Falicov-Kimball model which can be solved exactly. This strongly correlated system is then placed in an uniform external dc electric field. We present a complete derivation for nonequilibrium dynamical mean-field theory Green’s functions defined on the Keldysh-Schwinger time contour. Here, we also discuss numerical issues involved in solving the coupled equations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗