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Idealized Simulations of a Squall Line from the MC3E Field Campaign Applying Three Bin Microphysics Schemes: Dynamic and Thermodynamic Structure
The squall line event on May 20, 2011, during the Midlatitude Continental Convective Clouds (MC3E) field campaign has been simulated by three bin (spectral) microphysics schemes coupled into the Weather Research and Forecasting (WRF) model. Semi-idealized three-dimensional simulations driven by temperature and moisture profiles acquired by a radiosonde released in the pre-convection environment at 1200 UTC in Morris, Oklahoma show that each scheme produced a squall line with features broadly consistent with the observed storm characteristics. However, substantial differences in the details of the simulated dynamic and thermodynamic structure are evident. These differences are attributed to different algorithms and numerical representations of microphysical processes, assumptions of the hydrometeor processes and properties, especially ice particle mass, density, and terminal velocity relationships with size, and the resulting interactions between the microphysics, cold pool, and dynamics. This study shows that different bin microphysics schemes, designed to be conceptually more realistic and thus arguably more accurate than bulk microphysics schemes, still simulate a wide spread of microphysical, thermodynamic, and dynamic characteristics of a squall line, qualitatively similar to the spread of squall line characteristics using various bulk schemes. Future work may focus on improving the representation of ice particle properties in bin schemes to reduce this uncertainty and using the similar assumptions for all schemes to isolate the impact of physics from numerics.
Structural Interpretation of the Large Slowdown of Water Dynamics at Stacked Phospholipid Membranes for Decreasing Hydration Level: All-Atom Molecular Dynamics
Hydration water determines the stability and function of phospholipid membranes as well as the interaction of membranes with other molecules. Experiments and simulations have shown that water dynamics slows down dramatically as the hydration decreases, suggesting that the interfacial water that dominates the average dynamics at low hydration is slower than water away from the membrane. Here, based on all-atom molecular dynamics simulations, we provide an interpretation of the slowdown of interfacial water in terms of the structure and dynamics of water–water and water–lipid hydrogen bonds (HBs). We calculate the rotational and translational slowdown of the dynamics of water confined in stacked phospholipid membranes at different levels of hydration, from completely hydrated to poorly hydrated membranes. For all hydrations, we analyze the distribution of HBs and find that water–lipids HBs last longer than water–water HBs and that at low hydration most of the water is in the interior of the membrane. We also show that water–water HBs become more persistent as the hydration is lowered. We attribute this effect (i) to HBs between water molecules that form, in turn, persistent HBs with lipids; (ii) to the hindering of the H-bonding switching between water molecules due to the lower water density at the interface; and (iii) to the higher probability of water–lipid HBs as the hydration decreases. Lastly, our interpretation of the large dynamic slowdown in water under dehydration is potentially relevant in understanding membrane biophysics at different hydration levels.
Description of the Fission Process: Nuclear Models for Fission Dynamics
Nuclear fission is the splitting of a heavy nucleus into two or more fragments, a process that releases a substantial amount of energy. It is ubiquitous in modern applications, critical for national security, energy generation and reactor safeguards. Fission also plays an important role in understanding the astrophysical formation of elements in the universe. Eighty years after the discovery of the fission process, its theoretical understanding from first principles remains a great challenge. In this paper, we present promising new approaches to make more accurate predictions of fission observables.
Observation of femtosecond molecular dynamics via pump–probe gas phase x-ray scattering
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A Conformal Decomposition Finite Element Method for Dynamic Wetting Applications.
Abstract not provided.
Modifications to WRF's dynamical core to improve the treatment of moisture for large-eddy simulations: WRF DY-CORE MOISTURE TREATMENT
Yamaguchi and Feingold (2012) note that the cloud fields in their Weather Research and Forecasting (WRF) large-eddy simulations (LESs) of marine stratocumulus exhibit a strong sensitivity to time stepping choices. In this study, we reproduce and analyze this sensitivity issue using two stratocumulus cases, one marine and one continental. Results show that (1) the sensitivity is associated with spurious motions near the moisture jump between the boundary layer and the free atmosphere, and (2) these spurious motions appear to arise from neglecting small variations in water vapor mixing ratio (qv) in the pressure gradient calculation in the acoustic substepping portion of the integration procedure. We show that this issue is remedied in the WRF dynamical core by replacing the prognostic equation for the potential temperature θ with one for the moist potential temperature θm=θ(1+1.61qv), which allows consistent treatment of moisture in the calculation of pressure during the acoustic substeps. With this modification, the spurious motions and the sensitivity to the time stepping settings (i.e., the dynamic time step length and number of acoustic substeps) are eliminated in both of the example stratocumulus cases. This modification improves the applicability of WRF for LES applications, and possibly other models using similar dynamical core formulations, and also permits the use of longer time steps than in the original code.
Unveiling the Mechanism of Mn Dissolution Through a Dynamic Cathode‐Electrolyte Interphase on LiMn2O4
Abstract Understanding the formation and evolution of the cathode‐electrolyte interphase (CEI), which forms at the interface between the cathode and electrolyte, is crucial for revealing degradation mechanisms in cathode materials, especially for developing strategies to stabilize the interphase in the strongly oxidizing conditions that evolve at high operating voltages in next‐generation Li‐ion batteries. However, The present understanding of the CEI is challenged by its complex and dynamic nature. In this work, near‐edge X‐ray absorption fine structure spectroscopy, electrochemical characterization, and reactive molecular dynamics simulations are combined to reveal a mechanism for CEI formation and evolution above model LiMn 2 O 4 (LMO) thin‐film electrodes in contact with conventional carbonate‐based electrolytes. It is found that Mn dissolution from LMO can be understood in terms of repetitive Mn 3 O 4 formation and dissolution behavior during cycling, which is closely connected to electrolyte decomposition and a key aspect of the CEI formation and growth. The behavior of the CEI in this model system offers detailed insight into the dynamic chemistry of the interphase, underscoring the important role of electrolyte composition and cathode surface structure in interphase degradation.
Comparative Study of Clustering Techniques for Real-Time Dynamic Model Reduction
Dynamic model reduction in power systems is necessary for improving computational efficiency. Traditional model reduction using linearized models or offline analysis would not be adequate to capture power system dynamic behaviors, especially the new mix of intermittent generation and intelligent consumption makes the power system more dynamic and non-linear. Real time dynamic model reduction emerges as an important need. This paper explores the use of clustering techniques to analyze real-time phasor measurements to determine generator groups and representative generators for dynamic model reduction. Two clustering techniques – graph clustering and evolutionary clustering – are studied in this paper. Various implementations of these techniques are compared and also compared with a previously developed Singular Value Decomposition (SVD)-based dynamic model reduction approach. Various methods exhibit different levels of accuracy when comparing the reduced model simulation against the original model. But some of them are consistently accurate. From this comparative perspective, this paper provides a good reference point for practical implementations.
Influence of Surface Oxidation on Ion Dynamics and Capacitance in Porous and Nonporous Carbon Electrodes
We investigate the influence of surface chemistry and ion confinement on capacitance and electrosorption dynamics of room-temperature ionic liquids (RTILs) in supercapacitors. Using air oxidation and vacuum annealing, we produced defunctionalized and oxygen-rich surfaces of carbide-derived carbons (CDCs) and graphene nanoplatelets (GNPs). While oxidized surfaces of porous CDCs improve capacitance and rate handling abilities of ions, defunctionalized nonporous GNPs improve charge storage densities on planar electrodes. Quasi-elastic neutron scattering (QENS) and inelastic neutron scattering (INS) probed the structure, dynamics, and orientation of RTIL ions confined in divergently functionalized pores. Oxidized, ionophilic surfaces draw ions closer to pore surfaces and enhance potential-driven ion transport during electrosorption. Molecular dynamics (MD) simulations corroborated experimental data and demonstrated the significance of surface functional groups on ion orientations, accumulation densities, and capacitance.
Confinement Effects on Host Chain Dynamics in Polymer Nanocomposite Thin Films
Incorporating nanoparticles (NPs) within a polymer host to create polymer nanocomposites (PNCs) while having the effect of increasing the functionality (e.g., sensing, energy conversion) of these materials influences other properties. One challenge is to understand the effects of nanoparticles on the viscosity of nanoscale thick polymer films. A new mechanism that contributes to an enhancement of the viscosity of nanoscale thick polymer/nanoparticle films is identified. We show that while the viscosities of neat homopolymer poly(2-vinylpyridine) (P2VP) films as thin as 50 nm remained the same as the bulk, polymer/nanoparticle films containing P2VP brush-coated gold NPs, spaced 50 nm apart, exhibited unprecedented increases in viscosities of over an order of magnitude. For thicker films or more widely separated NPs, the chain dynamics and viscosities were comparable to the bulk values. These results - NP proximities and suppression of their dynamics - suggest a new mechanism by which the viscosities of polymeric liquids could be controlled for nanoscale applications.
Dispersal, habitat filtering, and eco-evolutionary dynamics as drivers of local and global wetland viral biogeography
Abstract Wetlands store 20–30% of the world’s soil carbon, and identifying the microbial controls on these carbon reserves is essential to predicting feedbacks to climate change. Although viral infections likely play important roles in wetland ecosystem dynamics, we lack a basic understanding of wetland viral ecology. Here 63 viral size-fraction metagenomes (viromes) and paired total metagenomes were generated from three time points in 2021 at seven fresh- and saltwater wetlands in the California Bodega Marine Reserve. We recovered 12,826 viral population genomic sequences (vOTUs), only 4.4% of which were detected at the same field site two years prior, indicating a small degree of population stability or recurrence. Viral communities differed most significantly among the seven wetland sites and were also structured by habitat (plant community composition and salinity). Read mapping to a new version of our reference database, PIGEONv2.0 (515,763 vOTUs), revealed 196 vOTUs present over large geographic distances, often reflecting shared habitat characteristics. Wetland vOTU microdiversity was significantly lower locally than globally and lower within than between time points, indicating greater divergence with increasing spatiotemporal distance. Viruses tended to have broad predicted host ranges via CRISPR spacer linkages to metagenome-assembled genomes, and increased SNP frequencies in CRISPR-targeted major tail protein genes suggest potential viral eco-evolutionary dynamics in response to both immune targeting and changes in host cell receptors involved in viral attachment. Together, these results highlight the importance of dispersal, environmental selection, and eco-evolutionary dynamics as drivers of local and global wetland viral biogeography.
Dynamic mode decomposition of nonequilibrium electron-phonon dynamics: accelerating the first-principles real-time Boltzmann equation
Abstract Nonequilibrium dynamics governed by electron–phonon ( e -ph) interactions plays a key role in electronic devices and spectroscopies and is central to understanding electronic excitations in materials. The real-time Boltzmann transport equation (rt-BTE) with collision processes computed from first principles can describe the coupled dynamics of electrons and atomic vibrations (phonons). Yet, a bottleneck of these simulations is the calculation of e –ph scattering integrals on dense momentum grids at each time step. Here we show a data-driven approach based on dynamic mode decomposition (DMD) that can accelerate the time propagation of the rt-BTE and identify dominant electronic processes. We apply this approach to two case studies, high-field charge transport and ultrafast excited electron relaxation. In both cases, simulating only a short time window of ~10% of the dynamics suffices to predict the dynamics from initial excitation to steady state using DMD extrapolation. Analysis of the momentum-space modes extracted from DMD sheds light on the microscopic mechanisms governing electron relaxation to a steady state or equilibrium. The combination of accuracy and efficiency makes our DMD-based method a valuable tool for investigating ultrafast dynamics in a wide range of materials.
Partial dynamical symmetry versus quasi dynamical symmetry examination within a quantum chaos analyses of spectral data for even–even nuclei
Statistical analyses of the spectral distributions of rotational bands in 51 deformed prolate even–even nuclei in the 152 ≤ A ≤ 250 mass region $R_{{4_{1}^{ + } /2_{1}^{ + } }} \ge 3.00$ are examined in terms of nearest neighbor spacing distributions. Specifically, the focus is on data for 0 + , 2 + , and 4 + energy levels of the ground, gamma, and beta bands. The chaotic behavior of the gamma band, especially the position of the $2_{\gamma }^{ + }$ band-head compared to other levels and bands, is clear. The levels are analyzed within the framework of two models, namely, a SU(3)-partial dynamical symmetry Hamiltonian and a SU(3) two-coupled quasi-dynamical symmetry Hamiltonian, with results that are further analyzed using random matrix theory. The partial and quasi dynamics both yield outcomes that are in reasonable agreement with the known experimental results. However, due to the degeneracy of the beta and gamma bands within the simplest SU(3) picture, the theory cannot be used to describe the fluctuation properties of excited bands. By changing relative weights of the different terms in the partial and quasi dynamical Hamiltonians, results are obtained that show more GOE-like statistics in the partial dynamical formalism as the strength of the pairing term is increased. Also, in the quasi-dynamical symmetry limit, more correlations are found because of the stronger couplings.
Kinetically-constrained ring-polymer molecular dynamics for non-adiabatic chemistries involving solvent and donor–acceptor dynamical effects
We investigate the performance of the recently developed kinetically-constrained ring polymer molecular dynamics (KC-RPMD) method for the description of model condensed-phase electron transfer (ET) reactions in which solvent and donor–acceptor dynamics play an important role. Comparison of KC-RPMD with results from Golden-Rule rate theories and numerically exact quantum dynamics calculations demonstrates that KC-RPMD accurately captures the combination of electronic- and nuclear-dynamical effects throughout the Marcus (intermediate solvent friction) and Zusman (large solvent friction) regimes of ET. It is also demonstrated that KC-RPMD accurately describes systems in which the magnitude of the diabatic coupling depends on the position of a dynamical donor–acceptor mode. In addition to these successes, however, we present an unsurprising failure of KC-RPMD to capture the enhancement of the ET rate in the low solvent friction regime associated with nuclear coherence effects. In this analysis, we re-visit several aspects of the original KC-RPMD formulation, including the form of the kinetic constraint and the choice of the mass of the auxiliary electronic variable. In particular, we introduce a Langevin bath for the auxiliary electronic variable to correct for its unphysically low coupling with the nuclear degrees of freedom. This work demonstrates that the KC-RPMD method is well suited for the direct simulation of non-adiabatic donor–acceptor chemistries associated with many complex systems, including those for which solvent dynamics plays an important role in the reaction mechanism.
Hybrid approach for estimating dynamic states of synchronous generators
Accurate and robust estimation of dynamic states is essential for monitoring and controlling a power grid. To achieve higher accuracy and robustness, this paper proposes a hybrid estimation approach to estimate the dynamic states of synchronous generators using multiple models, classified into a set of local models and a wide-area model. The proposed estimation approach, first, estimates dynamic states using the extended Kalman filter (EKF) based on a local model and a wide-area model. Then, at each time step, probability indexes, which quantify the likelihood of both local and wide-area models, are determined using hypothesis testing based on measurements innovations. Finally, using the weighted fix approach, the states estimated from the local and wide-area models are combined based on their probability indexes. Simulation studies using the two-area four-machine system shows that the proposed approach can improve estimation accuracy and increase robustness against model errors.
Quantum dynamics of hydrogen atoms on graphene. II. Sticking
Following our recent system-bath modeling of the interaction between a hydrogen atom and a graphene surface [Bonfanti et al., J. Chem. Phys. 143, 124703 (2015)], we present the results of converged quantum scattering calculations on the activated sticking dynamics. The focus of this study is the collinear scattering on a surface at zero temperature, which is treated with high-dimensional wavepacket propagations with the multi-configuration time-dependent Hartree method. At low collision energies, barrier-crossing dominates the sticking and any projectile that overcomes the barrier gets trapped in the chemisorption well. However, at high collision energies, energy transfer to the surface is a limiting factor, and fast H atoms hardly dissipate their excess energy and stick on the surface. As a consequence, the sticking coefficient is maximum (∼0.65) at an energy which is about one and half larger than the barrier height. Comparison of the results with classical and quasi-classical calculations shows that quantum fluctuations of the lattice play a primary role in the dynamics. A simple impulsive model describing the collision of a classical projectile with a quantum surface is developed which reproduces the quantum results remarkably well for all but the lowest energies, thereby capturing the essential physics of the activated sticking dynamics investigated.