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At least 811 records · Page 45

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↗

Non percolative nature of the metal-insulator transition and persistence of local Jahn-Teller distortions in the rhombohedral regime of La 1-x Ca x MnO 3

Evolution of the average and local crystal structure of Ca-doped LaMnO 3 has been studied across the metal to insulator (MI) and the orthorhombic to rhombohedral (OR) structural phase transitions over a broad temperature range for two Ca concentrations (x = 0.18,0.22). Combined Rietveld and high real space resolution atomic pair distribution function (PDF) analysis of neutron total scattering data was carried out with aims of exploring the possibility of nanoscale phase separation (PS) in relation to MI transition, and charting the evolution of local Jahn-Teller (JT) distortion of MnO 6 octahedra across the OR transition at T S ~720 K. The study utilized explicit two-phase PDF structural modeling, revealing that away from T MI there is no evidence for nanoscale phase coexistence. The local JT distortions disappear abruptly upon crossing into the metallic regime both with doping and temperature, with only a small temperature-independent signature of quenched disorder being observable at low temperature as compared to CaMnO 3 . The results hence do not support the percolative scenario for the MI transition in La 1–x Ca x MnO 3 based on PS, and question its ubiquity in the manganites. In contrast to LaMnO 3 that exhibits long-range orbital correlations and sizable octahedral distortions at low temperature, the doped samples with compositions straddling the MI boundary exhibit correlations (in the insulating regime) limited to only ~1 nm with observably smaller distortions. In the x = 0.22 sample local JT distortions are found to persist across the OR transition and deep into the R phase (up to ~1050 K), where they are crystallographically prohibited. As a result, their magnitude and subnanometer spatial extent remain unchanged.

36 MATERIALS SCIENCE↗

Explainable Machine Learning for Functional Data

Black-box machine learning models are recognized as useful tools for prediction applications, but the algorithmic complexity of some models causes interpretation challenges. Explainability methods have been proposed to provide insight into these models, but there is little research focused on supervised modeling with functional data inputs. We argue that, especially in applications of high consequence, it is important to explicitly model the functional dependence in a black-box analysis to not obscure or misrepresent patterns in explanations. As such, we propose the V ariable importance E xplainable E lastic S hape A nalysis (VEESA) pipeline for training supervised machine learning models with functional inputs. The pipeline is an analysis process that includes the data preprocessing, modeling, and post-hoc explanations. The preprocessing is done using elastic functional principal components analysis, which accounts for vertical and horizontal variability in functional data and, ultimately, allows for explanations in the original data space that identify the important functional variability without bias due to correlated variables. Here, we demonstrate the pipeline on two high-consequence applications: explosives classification for national security and inkjet printer identification in forensic science. The applications exhibit the VEESA pipeline’s ability to provide an understanding of the characteristics of the functional data useful for prediction. Code for implementing the pipeline is available in the veesa R package (and supplemental python code).

Elastic Shape Analysis↗

Multifaceted Water Dynamics in Spherical Nanocages

We present here a new method to study position-dependent, anisotropic diffusion tensors inside spherically confined systems—a geometry that is common to many chemical nanoreactors. We use this method to elucidate the surprisingly rich solvent dynamics of confined water. The spatial variation of the strongly anisotropic diffusion predicted by the model agrees with the results of explicit molecular dynamics simulations. The same approach can be directly transferred to the transport of solutes to and from reaction sites located at nanoreactor interfaces. We complement our study by a detailed analysis of water hydrogen bond kinetics, which is intimately coupled to diffusion. Despite the inhomogeneity in structure and translational dynamics inside our nanocages, a single set of well-defined rate constants is sufficient to accurately describe the kinetics of hydrogen bond breaking and formation. We find that once system size effects have been eliminated, the residence times of water molecules inside the coordination shell of a hydrogen bond partner are well correlated to average diffusion constants obtained from the procedure above.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Biases to primordial non-Gaussianity measurements from CMB secondary anisotropies

ABSTRACT Our view of the last-scattering surface in the cosmic microwave background (CMB) is obscured by secondary anisotropies, sourced by scattering, extragalactic emission, and gravitational processes between recombination and observation. Whilst it is established that non-Gaussianity from the correlation between the integrated-Sachs–Wolfe (ISW) effect and gravitational lensing can significantly bias primordial non-Gaussianity (PNG) searches, recent work by Hill suggests that other combinations of secondary anisotropies can also produce significant biases. Building on that work, we use the WebSky and Sehgal et al. simulations to perform an extensive examination of possible biases to PNG measurements for the local, equilateral and orthogonal shapes. For a Planck-like CMB experiment, without foreground cleaning, we find significant biases from cosmic infrared background (CIB)-lensing and thermal Sunyaev–Zel’dovich (tSZ)-lensing bispectra for the local and orthogonal templates, and from CIB and tSZ bispectra for the equilateral template. For future experiments, such as the Simons Observatory, biases from correlations between the ISW effect and the tSZ and CIB will also become important. Finally, we investigate the effectiveness of foreground-cleaning techniques to suppress these biases. We find that the majority of these biases are effectively suppressed by the internal-linear combination method with a total bias below the $1\, \sigma$ statistical error for both experiments. However, the small total bias arises from the cancellation of several $1\, \sigma$ biases for Planck-like experiments and $2\, \sigma$ biases for SO-like. As this cancellation is likely sensitive to the modelling, to ensure robustness against these biases, we recommend that explicit removal methods should be used.

Astronomy & Astrophysics↗

Estimation of heat transfer coefficients for biomass particles by direct numerical simulation using microstructured particle models in the Laminar regime

Here, direct numerical simulation of convective heat transfer from hot gas to isolated biomass particle models with realistic morphology and explicit microstructure was performed over a range of conditions with laminar flow of hot gas (500 degrees C). Steady-state results demonstrated that convective interfacial heat transfer is dependent on the wood species. The computed heat transfer coefficients were shown to vary between the pine and aspen models by nearly 20%. These differences are attributed to the species-specific variations in the exterior surface morphology of the biomass particles. We also quantify variations in heat transfer experienced by the particle when positioned in different orientations with respect to the direction of fluid flow. These results are compared to previously reported heat transfer coefficient correlations in the range of 0.1 < Pr < 1.5 and 10 < Re < 500. Comparison of these simulation results to correlations commonly used in the literature (Gunn, Ranz-Marshall, and Bird-Stewart-Lightfoot) shows that the Ranz-Marshall (sphere) correlation gave the closest h values to our steady-state simulations for both wood species, though no existing correlation was within 20% of both species at all conditions studied. In general, this work exemplifies the fact that all biomass feedstocks are not created equal, and that their species-specific characteristics must be appreciated in order to facilitate accurate simulations of conversion processes.

09 BIOMASS FUELS↗

A stochastic extension of the explicit algebraic subgrid-scale models

The explicit algebraic subgrid-scale (SGS) stress model (EASM) of Marstorp et al. [“Explicit algebraic subgrid stress models with application to rotating channel flow,” J. Fluid Mech. 639, 403–432 (2009)] and explicit algebraic SGS scalar flux model (EASFM) of Rasam et al. [“An explicit algebraic model for the subgrid-scale passive scalar flux,” J. Fluid Mech. 721, 541–577 (2013)] are extended with stochastic terms based on the Langevin equation formalism for the subgrid-scales by Marstorp et al. [“A stochastic subgrid model with application to turbulent flow and scalar mixing,” Phys. Fluids 19, 035107 (2007)]. The EASM and EASFM are nonlinear mixed and tensor eddy-diffusivity models, which improve large eddy simulation (LES) predictions of the mean flow, Reynolds stresses, and scalar fluxes of wall-bounded flows compared to isotropic eddy-viscosity and eddy-diffusivity SGS models, especially at coarse resolutions. The purpose of the stochastic extension of the explicit algebraic SGS models is to further improve the characteristics of the kinetic energy and scalar variance SGS dissipation, which are key quantities that govern the small-scale mixing and dispersion dynamics. LES of turbulent channel flow with passive scalar transport shows that the stochastic terms enhance SGS dissipation statistics such as length scale, variance, and probability density functions and introduce a significant amount of backscatter of energy from the subgrid to the resolved scales without causing numerical stability problems. The improvements in the SGS dissipation predictions in turn enhances the predicted resolved statistics such as the mean scalar, scalar fluxes, Reynolds stresses, and correlation lengths. Moreover, the nonalignment between the SGS stress and resolved strain-rate tensors predicted by the EASM with stochastic extension is in much closer agreement with direct numerical simulation data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Solvation of furfural at metal–water interfaces: Implications for aqueous phase hydrogenation reactions

Metal–water interfaces are central to understanding aqueous-phase heterogeneous catalytic processes. However, the explicit modeling of the interface is still challenging as it necessitates extensive sampling of the interfaces’ degrees of freedom. Herein, we use ab initio molecular dynamics (AIMD) simulations to study the adsorption of furfural, a platform biomass chemical on several catalytically relevant metal–water interfaces (Pt, Rh, Pd, Cu, and Au) at low coverages. We find that furfural adsorption is destabilized on all the metal–water interfaces compared to the metal–gas interfaces considered in this work. This destabilization is a result of the energetic penalty associated with the displacement of water molecules near the surface upon adsorption of furfural, further evidenced by a linear correlation between solvation energy and the change in surface water coverage. To predict solvation energies without the need for computationally expensive AIMD simulations, we demonstrate OH binding energy as a good descriptor to estimate the solvation energies of furfural. Using microkinetic modeling, we further explain the origin of the activity for furfural hydrogenation on intrinsically strong-binding metals under aqueous conditions, i.e., the endothermic solvation energies for furfural adsorption prevent surface poisoning. In conclusion, our work sheds light on the development of active aqueous-phase catalytic systems via rationally tuning the solvation energies of reaction intermediates.

aqueous-phase hydrogenation↗

Dark matter from anomaly cancellation at the LHC

We discuss a class of theories that predict a fermionic dark matter candidate from gauge anomaly cancellation. As an explicit example, we study the predictions in theories where the global symmetry associated with baryon number is promoted to a local gauge symmetry. In this context, the symmetry-breaking scale has to be below the multi-TeV scale in order to be in agreement with the cosmological constraints on the dark matter relic density. The new physical “Cucuyo” Higgs boson in the theory has very interesting properties, decaying mainly into two photons in the low mass region, and mainly into dark matter in the intermediate mass region. We study the most important signatures at the Large Hadron Collider, evaluating the experimental bounds. We discuss the correlation between the dark matter relic density, direct detection, and collider constraints. We find that these theories are still viable and are susceptible to being probed in current, and future high-luminosity, running. Published by the American Physical Society 2024

Butterworth, Jon (ORCID:0000000259055394)↗

Estimation of Snow Mass Information via Assimilation of C-Band Synthetic Aperture Radar Backscatter Observations Into an Advanced and Surface Model

This study assimilated Sentinel-1 C-band backscatter observations over snow-covered terrain into the Noah-Multiparameterization land surface model using support vector machine (SVM) regression and an ensemble Kalman filter to improve the modeled terrestrial snow mass estimates. The data assimilation (DA) experiment was conducted across Western Colorado from September 2016 to August 2017. As part of the DA experiments, the impact of a rule-based update was evaluated by comparing snow water equivalent (SWE) estimates via DA (with [ DAv1 ] and without [ DAv2 ] the rule-based update) against SNOTEL SWE measurements. Results confirmed that rule-based update helped minimize SVM controllability issues, and in turn, improved the accuracy of SWE estimates relative to both open loop (OL) and DAv2 . Comparison of SWE estimates from Sentinel-1 DAv1 against SNOTEL SWE revealed that 75% of stations showed improvements in bias and correlation coefficient relative to the OL. Assimilated SWE estimates also showed statistical improvements during both the snow accumulation and snow ablation periods. However, unbiased root mean square error showed a slight increase during the snow ablation period due to the large variability in the electromagnetic response of C-band backscatter over deep and/or wet snow. Improvement of the SWE estimates also resulted in improving river discharge estimates compared to in situ measurements. River discharge using Sentinel-1 DAv1 improved the Nash–Sutcliffe efficiency at all available stations. These results suggest that physically constrained SVM can serve as an efficient observation operator for snow mass DA through explicit consideration of the first-order C-band scattering mechanisms over different terrestrial snow conditions.

Jongmin Park↗

Cumulants of multiple conserved charges and global conservation laws

We analyze the behavior of cumulants of conserved charges in a subvolume of a thermal system with exact global conservation laws by extending a recently developed subensemble acceptance method (SAM) to multiple conserved charges. Explicit expressions for all diagonal and off-diagonal cumulants up to sixth order that relate them to the grand canonical susceptibilities are obtained. The derivation is presented for an arbitrary equation of state with an arbitrary number of different conserved charges. The global conservation effects cancel out in any ratio of two second order cumulants, in any ratio of two third order cumulants, as well as in a ratio of strongly intensive measures Σ and Δ involving any two conserved charges, making all these quantities particularly suitable for theory-to-experiment comparisons in heavy-ion collisions. We also show that the same cancellation occurs in correlators of a conserved charge, like the electric charge, with any non-conserved quantity such as net proton or net kaon number. The main results of the SAM are illustrated in the framework of the hadron resonance gas model. We also elucidate how net-proton and net-Λ fluctuations are affected by conservation of electric charge and strangeness in addition to baryon number.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Avoiding ergodicity problems in lattice discretizations of the Hubbard model

The Hubbard model arises naturally when electron-electron interactions are added to the tight-binding descriptions of many condensed matter systems. For instance, the two-dimensional Hubbard model on the honeycomb lattice is central to the ab initio description of the electronic structure of carbon nanomaterials, such as graphene. Such low-dimensional Hubbard models are advantageously studied with Markov chain Monte Carlo methods, such as hybrid Monte Carlo (HMC). HMC is the standard algorithm of the lattice gauge theory community, as it is well suited to theories of dynamical fermions. As HMC performs continuous, global updates of the lattice degrees of freedom, it provides superior scaling with system size relative to local updating methods. A potential drawback of HMC is its susceptibility to ergodicity problems due to so-called exceptional configurations, for which the fermion operator cannot be inverted. Recently, ergodicity problems were found in some formulations of HMC simulations of the Hubbard model. Here, we address this issue directly and clarify under what conditions ergodicity is maintained or violated in HMC simulations of the Hubbard model. We study different lattice formulations of the fermion operator and provide explicit, representative calculations for small systems, often comparing to exact results. Here, we show that a fermion operator can be found which is both computationally convenient and free of ergodicity problems.

First-principles calculations↗

Revisiting Understanding of Electrochemical CO 2 Reduction on Cu(111): Competing Proton-Coupled Electron Transfer Reaction Mechanisms Revealed by Embedded Correlated Wavefunction Theory

Copper (Cu) electrodes, as the most efficacious of CO 2 reduction reaction (CO 2 RR) electrocatalysts, serve as prototypes for determining and validating reaction mechanisms associated with electrochemical CO 2 reduction to hydrocarbons. As in situ electrochemical mechanism determination by experiments is still out of reach, such mechanistic analysis typically is conducted using density functional theory (DFT). The semilocal exchange-correlation (XC) approximations most often used to model such catalysis unfortunately engender a basic error: predicting the wrong adsorption site for CO (a key CO 2 RR intermediate) on the most ubiquitous facet of Cu, namely, Cu(111). This longstanding inconsistency casts lingering doubt on previous DFT predictions of the attendant CO 2 RR kinetics. Here, we apply embedded correlated wavefunction (ECW) theory, which corrects XC functional error, to study the CO 2 RR on Cu(111) via both surface hydride (*H) transfer and proton-coupled electron transfer (PCET). We predict that adsorbed CO (*CO) reduces almost equally to two intermediates, namely, hydroxymethylidyne (*COH) and formyl (*CHO) at –0.9 V vs the RHE. In contrast, semilocal DFT approximations predict a strong preference for *COH. With increasing applied potential, the dominance of *COH (formed via potential-independent surface *H transfer) diminishes, switching to the competitive formation of both *CHO and *COH (both formed via potential-dependent PCET). Furthermore, our results also demonstrate the importance of including explicitly modeled solvent molecules in predicting electron-transfer barriers and reveal the pitfalls of overreliance on simple surface *H transfer models of reduction reactions.

30 DIRECT ENERGY CONVERSION↗

High strain-rate compression behavior of polymeric rod and plate Kelvin lattice structures

The compressive high strain-rate behavior of polymeric Kelvin lattice structures with rod-based or plate-based unit cells was investigated through experimental techniques and finite element simulations. Polymeric lattice structures with 5x5x5 unit cell geometries were manufactured on the millimeter scale using vat polymerization additive manufacturing and tested at low (0.001/s) and high (1000/s) strain-rates. High strain-rate experiments were performed and validated for a viscoelastic split-Hopkinson (Kolsky) pressure bar system (SHPB) coupled with high-speed imaging and digital image correlation (DIC). Experimental results at both low and high strain-rates show the formation of a localized deformation band which was more prevalent in low relative density specimens and low strain-rate experiments. Strain-rate effects of lattice specimens strongly correlate with effects of the base polymer material; both bulk polymer and lattice specimen demonstrated strain-rate hardening, strain-rate stiffening, and decreased fracture strain under dynamic loading. Results show mechanical failure properties and energy absorption depended strongly on the relative density of the lattice specimen and exhibited distinct scaling between relative density and geometry type (rod, plate) and loading rate. High relative density plate-lattices demonstrated inferior mechanical properties to rod-lattices; however, there exists a critical relative density for a given mechanical property (17%- 28%) below which plate-lattices outperform rod-lattices of similar mass. As a result, high strain-rate explicit finite element simulations were performed and showed good agreement with the mechanical failure trends and deformation modes observed in the experiments.

36 MATERIALS SCIENCE↗

Photometric Analyses of Saturn’s Small Moons: Aegaeon, Methone, and Pallene Are Dark; Helene and Calypso Are Bright

We examine the surface brightnesses of Saturn’s smaller satellites using a photometric model that explicitly accounts for their elongated shapes and thus facilitates comparisons among different moons. Analyses of Cassini imaging data with this model reveal that the moons Aegaeon, Methone, and Pallene are darker than one would expect given trends previously observed among the nearby mid-sized satellites. On the other hand, the trojan moons Calypso and Helene have substantially brighter surfaces than their co-orbital companions Tethys and Dione. These observations are inconsistent with the moons’ surface brightnesses being entirely controlled by the local flux of E-ring particles, and therefore strongly imply that other phenomena are affecting their surface properties. The darkness of Aegaeon, Methone, and Pallene is correlated with the fluxes of high-energy protons, implying that high-energy radiation is responsible for darkening these small moons. Meanwhile, Prometheus and Pandora appear to be brightened by their interactions with the nearby dusty F ring, implying that enhanced dust fluxes are most likely responsible for Calypso’s and Helene’s excess brightness. However, there are no obvious structures in the E ring that would preferentially brighten these two moons, so there must either be something subtle in the E-ring particles’ orbital properties that leads to asymmetries in the relevant fluxes, or something happened recently to temporarily increase these moons’ brightnesses.

79 ASTRONOMY AND ASTROPHYSICS↗

Origin of parameter degeneracy and molecular shape relationships in geometric-flow calculations of solvation free energies

Implicit solvent models are important tools for calculating solvation free energies for chemical and biophysical studies since they require fewer computational resources but can achieve accuracy comparable to that of explicit-solvent models. In past papers, geometric flow-based solvation models have been established for solvation analysis of small and large compounds. In the present work, the use of realistic experiment-based parameter choices for the geometric flow models is studied. We find that the experimental parameters of solvent internal pressure p = 172 MPa and surface tension γ = 72 mN/m produce solvation free energies within 1 RT of the global minimum root-mean-squared deviation from experimental data over the expanded set. Our results demonstrate that experimental values can be used for geometric flow solvent model parameters, thus eliminating the need for additional parameterization. We also examine the correlations between optimal values of p and γ which are strongly anti-correlated. Geometric analysis of the small molecule test set shows that these results are inter-connected with an approximately linear relationship between area and volume in the range of molecular sizes spanned by the data set. In spite of this considerable degeneracy between the surface tension and pressure terms in the model, both terms are important for the broader applicability of the model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigating the magnetovolume effect in isotropic body-centered-cubic iron using spin-lattice dynamics simulations

The understanding of the magnetovolume effect lacks explicit consideration of spin-lattice coupling at the atomic level, despite abundant theoretical and experimental studies throughout the years. This research gap is filled by the recently developed spin-lattice dynamics technique implemented in this study, which investigates the magnetovolume effect of isotropic body-centered-cubic (BCC) iron, a topic that has previously been subject to macroscopic analysis only. This approach demonstrates the magnetic anomaly followed by the volumetric changes associated with the effect, each characterized by the corresponding field-induced inflection temperature. The temperature of the heat capacity peaks is useful in determining the temperature for retarding the atomic volume increase. Moreover, this work shows the correlation between the effects of temperature and field strength in determining the equilibrium atomic volume of a ferromagnetic material under a magnetic field.

36 MATERIALS SCIENCE↗