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At least 1,423 records · Page 79

Vortex-sheet modeling of hydrodynamic instabilities produced by an oblique shock interacting with a perturbed interface in the HED regime

In this work, we consider hydrodynamic instabilities produced by the interaction of an oblique shock with a perturbed material interface under high-energy-density (HED) conditions. During this interaction, a baroclinic torque is generated along the interface due to the misalignment between the density and pressure gradients, thus leading to perturbation growth. Our objective is to understand the competition between the impulsive acceleration due to the normal component of the shock velocity, which drives the Richtmyer–Meshkov instability, and the shear flow across the interface due to the tangential component of the shock velocity, which drives the Kelvin–Helmholtz instability, as well as its relation to perturbation growth. Since the vorticity resulting from the shock-interface interaction is confined to the interface, we describe the perturbation growth using a two-dimensional vortex-sheet model. We demonstrate the ability of the vortex-sheet model to reproduce roll-up dynamics for non-zero Atwood numbers by comparing to past laser-driven HED experiments. We determine the dependence of the interface dynamics on the tilt angle and propose a time scaling for the perturbation growth at early time. Eventually, this scaling will serve as a platform for the design of future experiments. This study is the first attempt to incorporate into a vortex-sheet model the time-dependent interface decompression and the deceleration (as well as the corresponding Rayleigh–Taylor instability) arising from laser turn-off.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Improved accuracy and transferability of molecular-orbital-based machine learning: Organics, transition-metal complexes, non-covalent interactions, and transition states

We report molecular-orbital-based machine learning (MOB-ML) provides a general framework for the prediction of accurate correlation energies at the cost of obtaining molecular orbitals. The application of Nesbet’s theorem makes it possible to recast a typical extrapolation task, training on correlation energies for small molecules and predicting correlation energies for large molecules, into an interpolation task based on the properties of orbital pairs. We demonstrate the importance of preserving physical constraints, including invariance conditions and size consistency, when generating the input for the machine learning model. Numerical improvements are demonstrated for different datasets covering total and relative energies for thermally accessible organic and transition-metal containing molecules, non-covalent interactions, and transition-state energies. MOB-ML requires training data from only 1% of the QM7b-T dataset (i.e., only 70 organic molecules with seven and fewer heavy atoms) to predict the total energy of the remaining 99% of this dataset with sub-kcal/mol accuracy. This MOB-ML model is significantly more accurate than other methods when transferred to a dataset comprising of 13 heavy atom molecules, exhibiting no loss of accuracy on a size intensive (i.e., per-electron) basis. It is shown that MOB-ML also works well for extrapolating to transition-state structures, predicting the barrier region for malonaldehyde intramolecular proton-transfer to within 0.35 kcal/mol when only trained on reactant/product-like structures. Finally, the use of the Gaussian process variance enables an active learning strategy for extending the MOB-ML model to new regions of chemical space with minimal effort. We demonstrate this active learning strategy by extending a QM7b-T model to describe non-covalent interactions in the protein backbone–backbone interaction dataset to an accuracy of 0.28 kcal/mol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phonon gas model for thermal conductivity of dense, strongly interacting liquids

Developing predictive thermal property models for liquids based on microscopic principles has been elusive. The difficulty is that liquids have gas-like and solid-like attributes that are at odds when considering the frameworks of microscopic models: Models for gases are simple due to randomness and low density, whereas models for crystalline solids rely on symmetry and long-range order for easier calculation. The short-range order in liquids does, however, provide structure to neighboring molecules similar to amorphous solids, and there have been recent advances indicating that collective vibrational modes store heat in liquids. Models combining Debye approximations from solid-state physics and Frenkel’s theory of liquids can accurately predict the heat capacity of liquids. Phonon-like dispersions in liquids have also been widely observed in neutron scattering experiments. These developments motivate us to propose a model where high-frequency vibrational modes, which travel at the speed of sound and have a mean free path on the order of the average intermolecular distance, conduct heat in liquids. We use this liquid phonon gas model to calculate the thermal conductivity of liquids with varying intermolecular interaction energies from strongest to weakest—Coulomb, hydrogen-bonding, Keesom, and London dispersion energy. Generally, the model is more accurate as the intermolecular interaction energy and density of liquids increase. The calculated thermal conductivity of Coulombic-bound molten sodium nitrate and hydrogen-bonded water is within 1.46% and 2.98% of the experimentally measured values, respectively, across their entire temperature ranges. Further modal analysis of the velocity and the mean free path of collective vibrations could establish the liquid phonon gas model as an accurate model for weakly interacting liquids as well.

36 MATERIALS SCIENCE↗

Static dipole polarizabilities of polyacenes using self-interaction-corrected density functional approximations

Density functional approximations are known to significantly overestimate the polarizabilities of long chain-like molecules. We study the static electric dipole polarizabilities and the vertical ionization potentials of polyacenes from benzene to pentacene using the Fermi-L\"owdin orbital based self-interaction corrected (FLOSIC) density functional method. The orbital-by-orbital self-interaction correction corrects for the overestimation tendency of density functional approximations. The polarizabilities calculated with FLOSIC-DFA are however overly corrected. We also tested the recently developed locally-scaled self-interaction correction (LSIC) method on the polyacenes. The local-scaling method applies full SIC in the one-electron regions and restores the proper behavior of the SIC exchange-correlation functionals in the uniform density limit. The results show that LSIC removes the overcorrection tendency of the FLOSIC-DFA and produces results that are in excellent agreement with reference CCSD values. The vertical ionization potentials with LSIC also show good agreement with available experimental values.

74 ATOMIC AND MOLECULAR PHYSICS↗

Role of transferred graphene on atomic interaction of GaAs for remote epitaxy

Remote epitaxy is a recently discovered type of epitaxy, wherein single-crystalline thin films can be grown on graphene-coated substrates following the crystallinity of the substrate via remote interaction through graphene. Although remote epitaxy provides a pathway to form freestanding membranes by controlled exfoliation of grown film at the graphene interface, implementing remote epitaxy is not straightforward because atomically precise control of interface is required. Here, we unveil the role of the graphene–substrate interface on the remote epitaxy of GaAs by investigating the interface at the atomic scale. By comparing remote epitaxy on wet-transferred and dry-transferred graphene, we show that interfacial oxide layer formed at the graphene–substrate interface hinders remote interaction through graphene when wet-transferred graphene is employed, which is confirmed by an increase of interatomic distance through graphene and also by the formation of polycrystalline films on graphene. On the other hand, when dry-transferred graphene is employed, the interface is free of native oxide, and single-crystalline remote epitaxial films are formed on graphene, with the interatomic distance between the epilayer and the substrate matching with the theoretically predicted value. The first atomic layer of the grown film on graphene is vertically aligned with the top layer of the substrate with these atoms having different polarities, substantiating the remote interaction of adatoms with the substrate through graphene. These results directly show the impact of interface properties formed by different graphene transfer methods on remote epitaxy.

36 MATERIALS SCIENCE↗

The role of H–H interactions and impurities on the structure and energetics of H/Pd(111)

Understanding hydrogen incorporation into palladium requires detailed knowledge of surface and subsurface structure and atomic interactions as surface hydrogen is being embedded. Using density functional theory (DFT), we examine the energies of hydrogen layers of varying coverage adsorbed on Pd(111). Here we find that H–H and H–Pd interactions promote the formation of the well-known ($\sqrt{3}$ x $\sqrt{3}$) phases but also favor an unreported (3 × 3) phase at high H coverages for which we present experimental evidence. We relate the stability of isolated H vacancies of the (3 × 3) phase to the need of H 2 molecules to access bare Pd before they can dissociate. Following higher hydrogen dosage, we observe initial steps of hydride formation, starting with small clusters of subsurface hydrogen. The interaction between H and Pd is complicated by the persistent presence of carbon at the surface. X-ray photoelectron spectroscopy experiments show that trace amounts of carbon, emerging from the Pd bulk despite many surface cleaning cycles, become mobile enough to repopulate the C-depleted surface at temperatures above 200 K. When exposed to hydrogen, these surface carbon atoms react to form benzene, as evidenced by scanning tunneling microscopy observations interpreted with DFT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A review of tidal energy—Resource, feedbacks, and environmental interactions

The ocean contains a variety of renewable energy resources, little of which has been exploited. Here, we review both tidal range and tidal stream energy, with a focus on the resource, feedbacks, and environmental interactions. The review covers a wide range of timescales of relevance to tidal energy, from fortnightly (spring-neap) and semi-diurnal variability, down to array, and device-scale turbulence. When simulating the regional tidal energy resource, and to assess environmental impacts, it is necessary to account for feedbacks between the tidal array and the resource itself. We critically review various methods for simulating energy extraction, from insights gained through theoretical studies of “tidal fences” in idealized channels, to realistic three-dimensional model studies with complex geometry and arrays of turbines represented by momentum sinks and additional turbulence due to the presence of rotors and support structures. We discuss how variability can be reduced by developing multiple (aggregated) sites with a consideration of the enhanced phase diversity offered by exploiting less energetic tidal currents. This leads to future research questions that have not yet been explored in depth at first-generation tidal sites in relatively sheltered channels (e.g., the interaction of waves with currents). Such enhanced understanding of real sea conditions, including the effects of wind and waves, leads to our other identified primary future research direction—reduced uncertainties in turbulence predictions, including the development of realistic models that simulate the interaction between ambient turbulence and the turbulence resulting from multiple wakes, and changes to system-wide hydrodynamics, water quality, and sedimentation.

Environmental impacts↗

An incompressible Eulerian method for fluid–structure interaction with mixed soft and rigid solids

Here, we present a general simulation approach for incompressible fluid–structure interactions in a fully Eulerian framework using the reference map technique. The approach is suitable for modeling one or more rigid or finitely deformable objects or soft objects with rigid components interacting with the fluid and with each other. It is also extended to control the kinematics of structures in fluids. The model is based on our previous Eulerian fluid–soft solver [Rycroft et al., “Reference map technique for incompressible fluid–structure interaction,” J. Fluid Mech. 898, A9 (2020)] and generalized to rigid structures by constraining the deformation-rate tensor in a projection framework. Several numerical examples are presented to illustrate the capability of the method.

42 ENGINEERING↗

Peculiarities of planar shockwave interaction with air–water interface and solid target

We present the results of the research on underwater electrical explosion of planar copper wire arrays, accompanied by the generation of a planar shock, using the synchrotron-based phase-contrast radiography imaging capabilities of the ID19 beamline at the European Synchrotron Radiation Facility. It is shown that the interaction of a strong shock with an air–water interface leads to additional acceleration of the wire expansion due to a rarefaction wave along with the emergence of micro-jets. In the case of a target placed above the array, we observed the formation of a cavity between the array and the target due to the interaction of two rarefaction waves. Furthermore, the results of two-dimensional hydrodynamic simulations of the wire explosion and the interaction of the generated shock with the water–air and water-target interfaces showed good agreement with experimental results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Mean-field theory for the structure of strongly interacting active liquids

Active systems, which are driven out of equilibrium by local non-conservative forces, exhibit unique behaviors and structures with potential utility for the design of novel materials. An important and difficult challenge along the path toward this goal is to precisely predict how the structure of active systems is modified as their driving forces push them out of equilibrium. Here, we use tools from liquid-state theories to approach this challenge for a classic minimal active matter model. First, we construct a nonequilibrium mean-field framework that can predict the structure of systems of weakly interacting particles. Second, motivated by equilibrium solvation theories, we modify this theory to extend it with surprisingly high accuracy to systems of strongly interacting particles, distinguishing it from most existing similarly tractable approaches. Furthermore, our results provide insight into spatial organization in strongly interacting out-of-equilibrium systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pressure–strain interaction. II. Decomposition in magnetic field-aligned coordinates

In weakly collisional and collisionless magnetized plasmas, the pressure–strain interaction describes the rate of conversion between bulk flow and thermal energy density. In this study, we derive an analytical expression for the pressure–strain interaction in a coordinate system with an axis aligned with the local magnetic field. The result is eight groups of terms corresponding to different physical mechanisms that can contribute to the pressure–strain interaction. We provide a physical description of each term. Here, the results are immediately of interest to weakly collisional and collisionless magnetized plasmas and the fundamental processes that happen therein, including magnetic reconnection, magnetized plasma turbulence, and collisionless shocks. The terms in the field-aligned coordinate decomposition are likely accessible to measurement with satellite observations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Spin-crossover complexes: Self-interaction correction vs density correction

Complexes containing a transition metal atom with a 3d 4 –3d 7 electron configuration typically have two low-lying, high-spin (HS) and low-spin (LS) states. The adiabatic energy difference between these states, known as the spin-crossover energy, is small enough to pose a challenge even for electronic structure methods that are well known for their accuracy and reliability. In this work, we analyze the quality of electronic structure approximations for spin-crossover energies of iron complexes with four different ligands by comparing energies from self-consistent and post-self-consistent calculations for methods based on the random phase approximation and the Fermi–Löwdin self-interaction correction. Considering that Hartree–Fock densities were found by Song et al., J. Chem. Theory Comput. 14, 2304 (2018), to eliminate the density error to a large extent, and that the Hartree–Fock method and the Perdew–Zunger-type self-interaction correction share some physics, we compare the densities obtained with these methods to learn their resemblance. Here, we find that evaluating non-empirical exchange-correlation energy functionals on the corresponding self-interaction-corrected densities can mitigate the strong density errors and improves the accuracy of the adiabatic energy differences between HS and LS states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In situ x-ray absorption investigations of a heterogenized molecular catalyst and its interaction with a carbon nanotube support

A highly active heterogenized molecular CO 2 reduction catalyst on a conductive carbon support is investigated to identify if its improved catalytic activity can be attributed to strong electronic interactions between catalyst and support. The molecular structure and electronic character of a [Re +1 (tBu-bpy)(CO) 3 Cl] (tBu-bpy = 4,4'-tert-butyl-2,2'-bipyridine) catalyst deposited on multiwalled carbon nanotubes are characterized using Re L 3 -edge x-ray absorption spectroscopy under electrochemical conditions and compared to the homogeneous catalyst. The Re oxidation state is characterized from the near-edge absorption region, while structural changes of the catalyst are assessed from the extended x-ray absorption fine structure under reducing conditions. Chloride ligand dissociation and a Re-centered reduction are both observed under applied reducing potential. The results confirm weak coupling of [Re(tBu-bpy)(CO) 3 Cl] with the support, since the supported catalyst exhibits the same oxidation changes as the homogeneous case. However, these results do not preclude strong interactions between a reduced catalyst intermediate and the support, preliminarily investigated here using quantum mechanical calculations. Thus, our results suggest that complicated linkage schemes and strong electronic interactions with the initial catalyst species are not required to improve the activity of heterogenized molecular catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Self-consistent implementation of locally scaled self-interaction-correction method

Recently proposed local self-interaction correction (LSIC) method is a one-electron self-interaction-correction (SIC) method that uses an iso-orbital indicator to apply the SIC at each point in space by scaling the exchange–correlation and Coulomb energy densities. The LSIC method is exact for the one-electron densities, also recovers the uniform electron gas limit of the uncorrected density functional approximation, and reduces to the well-known Perdew–Zunger SIC (PZSIC) method as a special case. This article presents the self-consistent implementation of the LSIC method using the ratio of Weizsäcker and Kohn–Sham kinetic energy densities as an iso-orbital indicator. The atomic forces as well as the forces on the Fermi-Löwdin orbitals are also implemented for the LSIC energy functional. Results show that LSIC with the simplest local spin density functional predicts atomization energies of the AE6 dataset better than some of the most widely used generalized-gradient-approximation (GGA) functional and barrier heights of the BH6 database better than some of the most widely used hybrid functionals. The LSIC method [a mean absolute error (MAE) of 0.008 Å] predicts bond lengths of a small set of molecules better than the PZSIC-LSDA (MAE 0.042 Å) and LSDA (0.011 Å). Furthermore, this work shows that accurate results can be obtained from the simplest density functional by removing the self-interaction-errors using an appropriately designed SIC method.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Causal interaction in high frequency turbulence at the biosphere–atmosphere interface: Structural behavior

High-frequency (e.g., 10 Hz) eddy covariance measurements are typically used to estimate fluxes at the land–atmosphere interface at timescales of 15–60 min. These multivariate data contain information about the interdependency at high frequency between the interacting variables such as wind, humidity, temperature, and CO 2⁠ . We use data at 10 Hz from an eddy covariance instrument located at 25 m above agricultural land in the Midwestern US, which offers an opportunity to move beyond the traditional spectral analyses to explore causal dependency among variables. In this study, we quantify the structure of inter-dependencies of interacting variables at high frequency represented by a directed acyclic graph (DAG). We compare DAGs to investigate changes in structural differences in causal interactions. We then apply a distance-based classification and -means clustering approach to identify the evolution of the causal structure represented by a DAG. Our method selects an unbiased number of clusters of similar structures and characterizes the similarities and differences between them. We explore a range of dynamic behavior using data from a clear sky day and during a solar eclipse in 2017. Our results show well-defined clusters of similar causal dependencies as the system evolves. Furthermore, our approach provides a methodological framework to understand how causal dependence in turbulence manifests in high-frequency data when represented through a DAG.

54 ENVIRONMENTAL SCIENCES↗

Causal interaction in high frequency turbulence at the biosphere–atmosphere interface: Structure–function coupling

At the biosphere–atmosphere interface, nonlinear interdependencies among components of an ecohydrological complex system can be inferred using multivariate high frequency time series observations. Information flow among these interacting variables allows us to represent the causal dependencies in the form of a directed acyclic graph (DAG). Here, we use high frequency multivariate data at 10 Hz from an eddy covariance instrument located at 25 m above agricultural land in the Midwestern US to quantify the evolutionary dynamics of this complex system using a sequence of DAGs by examining the structural dependency of information flow and the associated functional response. We investigate whether functional differences correspond to structural differences or if there are no functional variations despite the structural differences. We base our analysis on the hypothesis that causal dependencies are instigated through information flow, and the resulting interactions sustain the dynamics and its functionality. To test our hypothesis, we build upon causal structure analysis in the companion paper to characterize the information flow in similarly clustered DAGs from 3-min non-overlapping contiguous windows in the observational data. We characterize functionality as the nature of interactions as discerned through redundant, unique, and synergistic components of information flow. Through this analysis, we find that in turbulence at the biosphere–atmosphere interface, the variables that control the dynamic character of the atmosphere as well as the thermodynamics are driven by non-local conditions, while the scalar transport associated with CO and H 2 O is mainly driven by short-term local conditions.

58 GEOSCIENCES↗

Spin-state gaps and self-interaction-corrected density functional approximations: Octahedral Fe(II) complexes as case study

Accurate prediction of a spin-state energy difference is crucial for understanding the spin crossover phenomena and is very challenging for density functional approximations, especially for local and semi-local approximations due to delocalization errors. Here, we investigate the effect of the self-interaction error removal from the local spin density approximation (LSDA) and Perdew–Burke–Ernzerhof generalized gradient approximation on the spin-state gaps of Fe(II) complexes with various ligands using recently developed locally scaled self-interaction correction (LSIC) by Zope et al. [J. Chem. Phys. 151, 214108 (2019)]. The LSIC method is exact for one-electron density, recovers the uniform electron gas limit of the underlying functional, and approaches the well-known Perdew–Zunger self-interaction correction (PZSIC) as a particular case when the scaling factor is set to unity. Our results, when compared with reference diffusion Monte Carlo results, show that the PZSIC method significantly overestimates spin-state gaps favoring low spin states for all ligands and does not improve upon density functional approximations. The perturbative LSIC-LSDA using PZSIC densities significantly improves the gaps with a mean absolute error of 0.51 eV but slightly overcorrects for the stronger CO ligands. Finally, the quasi-self-consistent LSIC-LSDA, such as coupled-cluster single double and perturbative triple [CCSD(T)], gives a correct sign of spin-state gaps for all ligands with a mean absolute error of 0.56 eV, comparable to that of CCSD(T) (0.49 eV).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electronic structure theory on modeling short-range noncovalent interactions between amino acids

While short-range noncovalent interactions (NCIs) are proving to be of importance in many chemical and biological systems, these atypical bindings happen within the so-called van der Waals envelope and pose an enormous challenge for current computational methods. We introduce SNCIAA, a database of 723 benchmark interaction energies of short-range noncovalent interactions between neutral/charged amino acids originated from protein x-ray crystal structures at the “gold standard” coupled-cluster with singles, doubles, and perturbative triples/complete basis set [CCSD(T)/CBS] level of theory with a mean absolute binding uncertainty less than 0.1 kcal/mol. Subsequently, a systematic assessment of commonly used computational methods, such as the second-order Møller−Plesset theory (MP2), density functional theory (DFT), symmetry-adapted perturbation theory (SAPT), composite electronic-structure methods, semiempirical approaches, and the physical-based potentials with machine learning (IPML) on SNCIAA is carried out. It is shown that the inclusion of dispersion corrections is essential even though these dimers are dominated by electrostatics, such as hydrogen bondings and salt bridges. Overall, MP2, ωB97M-V, and B3LYP+D4 turned out to be the most reliable methods for the description of short-range NCIs even in strongly attractive/repulsive complexes. SAPT is also recommended in describing short-range NCIs only if the δMP2 correction has been included. The good performance of IPML for dimers at close-equilibrium and long-range conditions is not transferable to the short-range. We expect that SNCIAA will assist the development/improvement/validation of computational methods, such as DFT, force-fields, and ML models, in describing NCIs across entire potential energy surfaces (short-, intermediate-, and long-range NCIs) on the same footing.

Chemistry↗