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At least 649 records · Page 36

Oxygen evolution from olivine Mn 1– x M x PO 4 ( M =Fe,Ni,Al,Mg) delithiated cathode materials

Olivine LiMnPO 4 is a promising cathode material for Li-ion batteries. One drawback of this material is the propensity of its delithiated phase, MnPO 4 , to evolve oxygen gas above approximately 200 °C. During thermal runaway of cells, this oxygen gas can burn the electrolyte and other cell components and thereby jeopardize safety. Partial substitution of Mn with M = Fe, Ni, Al, or Mg has been used to improve the lithium intercalation kinetics of Li x MnPO 4 ; however, the effect of these substitutions on oxygen evolution is not fully documented. In this paper, we calculate phase diagrams and oxygen evolution diagrams for these Mn 1–x M x PO 4 delithiated cathode materials. To generate the phase diagrams, we use subregular solid-solution models and fit the energetic parameters of these models to density functional theory calculations of special quasirandom structures. The resulting thermodynamic models describe the effect of mixing on the initial temperature of oxygen evolution and on the cumulative amount of oxygen evolution at elevated temperatures. We find that addition of Fe increases the initial temperature and decreases the cumulative amount of oxygen evolution. Mn 0.5 Fe 0.5 PO 4 exhibits an initial temperature 50 °C higher than MnPO 4 and releases 70% less oxygen gas at 300 °C. Al is insoluble in MnPO 4 , so addition of Al has no affect on the initial temperature. However, Al addition does slightly decrease the amount of oxygen evolution due to an inactive AlPO 4 component. Mg and Ni both decrease the initial temperature of oxygen evolution, and therefore may worsen the safety of MnPO 4 .

25 ENERGY STORAGE↗

Redshift space clustering of galaxies and cold dark matter model

The distorting effect of peculiar velocities on the power speturm and correlation function of IRAS and optical galaxies is studied. The observed redshift space power spectra and correlation functions of IRAS and optical the galaxies over the entire range of scales are directly compared with the corresponding redshift space distributions using large-scale computer simulations of cold dark matter (CDM) models in order to study the distortion effect of peculiar velocities on the power spectrum and correlation function of the galaxies. It is found that the observed power spectrum of IRAS and optical galaxies is consistent with the spectrum of an Omega = 1 CDM model. The problems that such a model currently faces may be related more to the high value of Omega in the model than to the shape of the spectrum. A low-density CDM model is also investigated and found to be consistent with the data.

Bahcall, Neta A.↗

Optimization and supervised machine learning methods for fitting numerical physics models without derivatives

Here, we address the calibration of a computationally expensive nuclear physics model for which derivative information with respect to the fit parameters is not readily available. Of particular interest is the performance of optimization-based training algorithms when dozens, rather than millions or more, of training data are available and when the expense of the model places limitations on the number of concurrent model evaluations that can be performed. As a case study, we consider the Fayans energy density functional model, which has characteristics similar to many model fitting and calibration problems in nuclear physics. We analyze hyperparameter tuning considerations and variability associated with stochastic optimization algorithms and illustrate considerations for tuning in different computational settings.

97 MATHEMATICS AND COMPUTING↗

Temperature, density, and composition in the disturbed thermosphere from Esro 4 gas analyzer measurements - A global model

An analysis of density measurements of Ar, N2, O, and He made at 280 km with the gas analyzer aboard the polar-orbiting satellite Esro 4 has yielded a global model of the variations in temperature, density, and composition that occur in the disturbed thermosphere. In the model the increase of temperature over quiet conditions is a nonlinear function of the planetary geomagnetic index, its latitude profile being approximated by a fourth-power sin phi law, where phi is the 'invariant' magnetic latitude. A density wave proceeding from high latitudes is approximated by a fourth power cos phi law. A strong nonlinearity in the relation between the temperature variations and the variations in the height of the homopause explains a previously found behavioral difference in the variation of atomic oxygen during magnetic storms and during periods of sustained geomagnetic activity.

Jacchia, L. G.↗

A comparison of two algorithms for simulating collisionless systems

Two completely different simulation algorithms are compared by applying them to the same stellar dynamical problems: one is a self-consistent field (SCF) method for solving Poisson's equation and the other is a phase-space method for integrating the collisionless Boltzmann equation. We consider simulations of spherical stellar systems which are initially far from equilibrium and relax to their final states by gravitational collapse. The initial conditions consist of either uniform-density spheres or nonequilibrium models having Plummer density profiles, in which velocity dispersions are assigned according to given virial ratios. If a few tens of radial expansion terms with hundreds of thousands of particles are used in the SCF code, excellent agreement is found between the results it generates and those obtained with the phase-space solver, provided that a sufficiently large number of grid cells are employed with the latter. These findings imply that for simulating collisionless systmes over many dynamical times, the SCF approach based on sampling phase space is competitive with the approach treating phase space as a continuous fluid. The results of our tests make it possible to estimate the number of particles and basis functions required in situations like those modeled. Limitations of the SCF method and the choice of an optimal set of basis functions are also discussed.

Hozumi, Shunsuke↗

Analytical Modeling and Test Correlation of Variable Density Multilayer Insulation for Cryogenic Storage

A unique foam/multilayer insulation (MLI) combination concept for orbital cryogenic storage was experimentally evaluated using a large-scale hydrogen tank. The foam substrate insulates for ground-hold periods and enables a gaseous nitrogen purge as opposed to helium. The MLI, designed for an on-orbit storage period for 45 days, includes several unique features including a variable layer density and larger but fewer perforations for venting during ascent to orbit. Test results with liquid hydrogen indicated that the MLI weight or tank heat leak is reduced by about half in comparison with standard MLI. The focus of this effort is on analytical modeling of the variable density MLI (VD-MLI) on-orbit performance. The foam/VD-MLI model is considered to have five segments. The first segment represents the optional foam layer. The second, third, and fourth segments represent three different MLI layer densities. The last segment is an environmental boundary or shroud that surrounds the last MLI layer. Two approaches are considered: a variable density MLI modeled layer by layer and a semiempirical model or "modified Lockheed equation." Results from the two models were very comparable and were within 5-8 percent of the measured data at the 300 K boundary condition.

Hastings, L. J.↗

Mind the gap: the power of combining photometric surveys with intensity mapping

The long wavelength modes lost to bright foregrounds in the interferometric 21-cm surveys can partially be recovered using a forward modeling approach that exploits the non-linear coupling between small and large scales induced by gravitational evolution. In this work, we build upon this approach by considering how adding external galaxy distribution data can help to fill in these modes. We consider supplementing the 21-cm data at two different redshifts with a spectroscopic sample (good radial resolution but low number density) loosely modeled on DESI-ELG at z=1 and a photometric sample (high number density but poor radial resolution) similar to LSST sample at z=1 and z=4 respectively. We find that both the galaxy samples are able to reconstruct the largest modes better than only using 21-cm data, with the spectroscopic sample performing significantly better than the photometric sample despite much lower number density. Here, we demonstrate the synergies between surveys by showing that the primordial initial density field is reconstructed better with the combination of surveys than using either of them individually. Methodologically, we also explore the importance of smoothing the density field when using bias models to forward model these tracers for reconstruction.

79 ASTRONOMY AND ASTROPHYSICS↗

SUNBIRD : a simulation-based model for full-shape density-split clustering

Combining galaxy clustering information from regions of different environmental densities can help break cosmological parameter degeneracies and access non-Gaussian information from the density field that is not readily captured by the standard two-point correlation function (2PCF) analyses. However, modelling these density-dependent statistics down to the non-linear regime has so far remained challenging. We present a simulation-based model that is able to capture the cosmological dependence of the full shape of the density-split clustering (DSC) statistics down to intra-halo scales. Our models are based on neural-network emulators that are trained on high-fidelity mock galaxy catalogues within an extended-ΛCDM framework, incorporating the effects of redshift-space, Alcock–Paczynski distortions, and models of the halo–galaxy connection. Our models reach sub-percent level accuracy down to $1 \, h^{-1}\text{Mpc}$ and are robust against different choices of galaxy–halo connection modelling. When combined with the galaxy 2PCF, DSC can tighten the constraints on ω cdm , σ 8 , and n s by factors of 2.9, 1.9, and 2.1, respectively, compared to a 2PCF-only analysis. DSC additionally puts strong constraints on environment-based assembly bias parameters.

79 ASTRONOMY AND ASTROPHYSICS↗

Fluid-kinetic modeling of a high power density radio frequency inductively coupled positive hydrogen ion source

High power density radio-frequency (RF) inductively coupled positive ion sources are attractive candidates for next-generation neutral beam injection (NBI) systems, where higher injected power and longer pulse lengths are desired without sacrificing source reliability. Operating at absorbed power densities of order $\gt 1~\mathrm{W\,cm}^{-3}$ places these sources in a regime with stronger gas heating, higher dissociation, and non-Maxwellian electron energy distributions. The Large Uniform Plasma for Ionizing Neutrals (LUPIN) is an RF inductively coupled plasma source designed to explore this high power density regime and to provide guidance for a positive ion source upgrade for the DIII-D NBI system. LUPIN is designed to operate at up to 20 kW of RF power at 2 MHz, coupling energy through a cylindrical quartz vessel to achieve target ion current densities of $2100\,\mathrm{A\,m}^{-2}$ . This paper presents fluid-kinetic modeling of LUPIN using the hybrid plasma equipment model where electrons are treated kinetically, and the simulations reveal that electron energy distribution function transitions from nearly Maxwellian in the core to bi-Maxwellian towards the edge. Parametric simulations investigate the effects of RF power, gas pressure, and frequency on plasma density, ion flux, and uniformity. Parametric sweeps reveal that increasing power shifts the primary ionization channel from molecular to atomic with diminishing flux gains due to skin-depth contraction and gas rarefaction. Higher frequency localizes heating and increases $\mathrm{H}_2^+$ and $\mathrm{H}_3^+$ delivery to the grid, while elevated pressure boosts ionization yet hinders ion transport due to increase in collisionality.

inductively coupled plasma↗

TensorBNN: Bayesian inference for neural networks using TensorFlow

We report that TensorBNN is a new package based on TensorFlow that implements Bayesian inference for modern neural network models. The posterior density of neural network model parameters is represented as a point cloud sampled using Hamiltonian Monte Carlo. The TensorBNN package leverages TensorFlow's architecture and its ability to use modern graphics processing units in both the training and prediction stages.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Modified Energy Span Analysis Reveals Heterogeneous Catalytic Kinetics

Mechanistic modeling is a cornerstone of catalyst development generally conducted with microkinetic models or density functional theory-based energy profiles. We extend the energy span model of homogeneous catalysis to heterogeneous systems by introducing the modified energy span analysis (MESA) model by implementing collision theory and gas-phase concentration effects. We determine analytically turnover frequencies, coverages, rate-determining steps, apparent activation energies, and reaction orders in agreement with microkinetic and kinetic Monte Carlo simulations. The model applies to discrete catalyst state systems, including single-atom catalysts, homogeneous systems, and microporous materials. A generalizable rate expression is derived for reactor modeling or mechanistic insights from solely experimentally measured reaction orders. Here, we illustrate MESA on three published mechanisms and reveal unexpected phenomena absent in traditional energy span profiles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Dynamics Simulations of Supercritical Carbon Dioxide and Water using TraPPE and SWM4-NDP Force Fields

The increased levels of carbon dioxide (CO 2 ) emissions due to the combustion of fossil fuels and the consequential impact on global climate change have made CO 2 capture, storage, and utilization a significant area of focus for current research. In most electrochemical CO 2 applications, water is used as a proton donor due to its high availability and mobility and use as a polar solvent. Additionally, supercritical CO 2 is a promising avenue for electrochemical applications due to its unique chemical and physical properties. Consequently, understanding the interactions between water and supercritical CO 2 is of great importance for future electrochemical applications. Molecular dynamics (MD) simulation is a powerful tool that enables atomistic-resolution dynamics of molecular systems, which can complement and guide future experimental investigations. This study employed atomistic MD to study the cosolubilities, codiffusivities, and structure of supercritical CO 2 and water systems, with a polarizable water model (SWM4-NDP) and a nonpolarizable CO 2 model (TraPPE). Additionally, ab initio MD simulations were used to better understand how atomistic polarizable/nonpolarizable models compare to explicit modeling of electron densities. The polarizable water model exhibited substantial improvement in water-associated properties. In conclusion, we anticipate the development of a compatible polarizable CO 2 model to yield similar improvement, providing a pathway for realizing novel high-pressure electrochemical systems.

25 ENERGY STORAGE↗

Phase Transition of H 2 in Subnanometer Pores Observed at 75 K

In this paper, we report a phase transition in H 2 adsorbed in a locally graphitic Saran carbon with subnanometer pores 0.5–0.65 nm in width, in which two layers of hydrogen can just barely squeeze, provided they pack tightly. The phase transition is observed at 75 K, temperatures far higher than other systems in which an adsorbent is known to increase phase transition temperatures: for instance, H 2 melts at 14 K in the bulk, but at 20 K on graphite because the solid H 2 is stabilized by the surface structure. Here we observe a transition at 75 K and 77–200 bar: from a low-temperature, low-density phase to a high-temperature, higher density phase. We model the low-density phase as a monolayer commensurate solid composed mostly of para-H 2 (the ground nuclear spin state, S = 0) and the high-density phase as an orientationally ordered bilayer commensurate solid composed mostly of ortho-H 2 (S = 1). We attribute the increase in density with temperature to the fact that the oblong ortho-H 2 can pack more densely. The transition is observed using two experiments. The high-density phase is associated with an increase in neutron backscatter by a factor of 7.0 ± 0.1. Normally, hydrogen produces no backscatter (scattering angle >90°). This backscatter appears along with a discontinuous increase in the excitation mass from 1.2 amu to 21.0 ± 2.3 amu, which we associate with collective nuclear spin excitations in the orientationally ordered phase. Film densities were measured using hydrogen adsorption. Finally, no phase transition was observed in H 2 adsorbed in control activated carbon materials.

36 MATERIALS SCIENCE↗

A generalized approach to x-ray data modeling for high-energy-density plasma experiments

Accurate understanding of x-ray diagnostics is crucial for both interpreting high-energy-density experiments and testing simulations through quantitative comparisons. X-ray diagnostic models are complex. Past treatments of individual x-ray diagnostics on a case-by-case basis have hindered universal diagnostic understanding. Here, in this study, we derive a general formula for modeling the absolute response of non-focusing x-ray diagnostics, such as x-ray imagers, one-dimensional space-resolved spectrometers, and x-ray power diagnostics. The present model is useful for both data modeling and data processing. It naturally accounts for the x-ray crystal broadening. The new model verifies that standard approaches for a crystal response can be good approximations, but they can underestimate the total reflectivity and overestimate spectral resolving power by more than a factor of 2 in some cases near reflectivity edge features. We also find that a frequently used, simplified-crystal-response approximation for processing spectral data can introduce an absolute error of more than an order of magnitude and the relative spectral radiance error of a factor of 3. The present model is derived with straightforward geometric arguments. It is more general and is recommended for developing a unified picture and providing consistent treatment over multiple x-ray diagnostics. Such consistency is crucial for reliable multi-objective data analyses.

Nagayama, Taisuke↗

Gapless spin liquid and pair density wave of the Hubbard model on three-leg triangular cylinders

We study the ground state properties of the Hubbard model on three-leg triangular cylinders using large-scale density-matrix renormalization group simulations. At half-filling, we identify an intermediate gapless spin liquid phase, which has one gapless spin mode and algebraic spin–spin correlations but exponential decay scalar chiral–chiral correlations, between a metallic phase at weak coupling and Mott insulating dimer phase at strong interaction. Upon light doping the gapless spin liquid, the system exhibits power-law charge-density-wave (CDW) correlations but short-range single-particle, spin–spin, and chiral–chiral correlations. Similar to CDW correlations, the superconducting correlations also decay in power-law but oscillate in sign as a function of distance, which is consistent with the striped pair-density wave. When further doping the gapless spin liquid phase or doping the dimer order phase, another phase takes over, which has similar CDW correlations but all other correlations decay exponentially.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Structure and screening in molecular and metallic hydrogen at high pressure

A variational wavefunction is used to express the (spin restricted) Hartree-Fock energy as reciprocal lattice sums for static lattice FCC monatomic hydrogen and diatomic Pa3 molecular hydrogen. In the monatomic phase the hydrogenic orbital range closely parallels the inverse Thomas-Fermi wavevector; the corresponding energy E has a minimum of -0.929 Ryd/electron at r sub s = 1.67. For the diatomic phase E(r sub s) is similar, but the constituent energies, screening, and bond length reflect a qualitative change in the nature of the solid at r sub s = 2.8. This change is interpreted in terms of a transition from protons as structural units (at high density) to weakly interacting models (at low density). Insensitivity of the total energy to a rapid fall in the bond length suggests association with the rotational transition where the rapid molecular orientations characteristic of high pressures disappear and the molecules rotate freely at low pressure.

Wood, D. M.↗

Silicon chemistry in interstellar clouds

A new model of interstellar silicon chemistry is presented that explains the lack of SiO detections in cold clouds and contains an exponential temperature dependence for the SiO abundance. A key aspect of the model is the sensitivity of SiO production by neutral silicon reactions to density and temperature, which arises from the dependence of the rate coefficients on the population of the excited fine-structure levels of the silicon atom. As part of the explanation of the lack of SiO detections at low temperatures and densities, the model also emphasizes the small efficiencies of the production routes and the correspondingly long times needed to reach equilibrium. Measurements of the abundance of SiO, in conjunction with theory, can provide information on the physical properties of interstellar clouds such as the abundance of oxygen bearing molecules and the depletion of interstellar silicon.

Langer, William D.↗

Modeled Seasonal Variations of Firn Density Induced by Steady State Surface Air Temperature Cycle

Seasonal variations of firn density in ice-sheet firn layers have been attributed to variations in deposition processes or other processes within the upper firn. A recent high-resolution (mm scale) density profile, measured along a 181 m core from Antarctica, showed small-scale density variations with a clear seasonal cycle that apparently was not-related to seasonal variations in deposition or known near-surface processes (Gerland and others 1999). A recent model of surface elevation changes (Zwally and Li, submitted) produced a seasonal variation in firn densification, and explained the seasonal surface elevation changes observed by satellite radar altimeters. In this study, we apply our 1-D time-dependent numerical model of firn densification that includes a temperature-dependent formulation of firn densification based on laboratory measurements of grain growth. The model is driven by a steady-state seasonal surface temperature and a constant accumulation rate appropriate for the measured Antarctic ice core. The modeled seasonal variations in firn density show that the layers of snow deposited during spring to mid-summer with the highest temperature history compress to the highest density, and the layers deposited during later summer to autumn with the lowest temperature history compress to the lowest density. The initial amplitude of the seasonal difference of about 0.13 reduces to about 0.09 in five years and asymptotically to 0.92 at depth, which is consistent with the core measurements.

Jun, Li↗