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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 703 records · Page 39

Character of intermolecular interaction in pyridine-argon complex: Ab initio potential energy surface, internal dynamics, and interrelations between SAPT energy components

The pyridine-Ar (PAr) van der Waals (vdW) complex is studied using a high level ab initio method. Its structure, binding energy, and intermolecular vibrational states are determined from the analytical potential energy surface constructed from interaction energy (IE) values computed at the coupled cluster level of theory with single, double, and perturbatively included triple excitations with the augmented correlation consistent polarized valence double-ζ (aug-cc-pVDZ) basis set complemented by midbond functions. The structure of the complex at its global minimum with Ar at a distance of 3.509 Å from the pyridine plane and shifted by 0.218 Å from the center of mass towards nitrogen agrees well with the corresponding equilibrium structure derived previously from the rotational spectrum of PAr. The PAr binding energy D{sub e} of 392 cm{sup −1} is close to that of 387 cm{sup −1} calculated earlier at the same ab initio level for the prototypical benzene-Ar (BAr) complex. However, under an extension of the basis set, D{sub e} for PAr becomes slightly lower than D{sub e} for BAr. The ab initio vdW vibrational energy levels allow us to estimate the reliability of the methods for the determination of the vdW fundamentals from the rotational spectra. To disclose the character of the intermolecular interaction in PAr, the symmetry-adapted perturbation theory (SAPT) is employed for the analysis of different physical contributions to IE. It is found that SAPT components of IE can be approximately expressed in the binding region by only two of them: the exchange repulsion and dispersion energy. The total induction effect is negligible. The interrelations between various SAPT components found for PAr are fulfilled for a few other complexes involving aromatic molecules and Ar or Ne, which indicates that they are valid for all rare gas (Rg) atoms and aromatics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Scaling NWChem with Efficient and Portable Asychronous Communication in MPI RMA

NWChem is one of the most widely used computational chemistry application suites for chemical and biological systems. Despite its vast success, the computational efficiency of NWChem is still low. This is especially true in higher accuracy methods such as the CCSD(T) coupled cluster method, where it currently achieves a mere 50% computational efficiency when run at large scales. In this paper, we demonstrate the most computationally efficient scaling of NWChem CCSD(T) to date, and use it to solve large water clusters. We use our recently proposed process-based asynchronous progress framework for MPI RMA, called Casper, to scale the computation on water clusters at near-100% computational efficiency on up to 12288 cores.

Si, Min↗

Experimental and Computational Analysis of the Solvent‐Dependent O 2 /Li + ‐O 2 − Redox Couple: Standard Potentials, Coupling Strength, and Implications for Lithium–Oxygen Batteries

Abstract Understanding and controlling the kinetics of O 2 reduction in the presence of Li + ‐containing aprotic solvents, to either Li + ‐O 2 − by one‐electron reduction or Li 2 O 2 by two‐electron reduction, is instrumental to enhance the discharge voltage and capacity of aprotic Li‐O 2 batteries. Standard potentials of O 2 /Li + ‐O 2 − and O 2 /O 2 − were experimentally measured and computed using a mixed cluster‐continuum model of ion solvation. Increasing combined solvation of Li + and O 2 − was found to lower the coupling of Li + ‐O 2 − and the difference between O 2 /Li + ‐O 2 − and O 2 /O 2 − potentials. The solvation energy of Li + trended with donor number (DN), and varied greater than that of O 2 − ions, which correlated with acceptor number (AN), explaining a previously reported correlation between Li + ‐O 2 − solubility and DN. These results highlight the importance of the interplay between ion–solvent and ion–ion interactions for manipulating the energetics of intermediate species produced in aprotic metal–oxygen batteries.

Kwabi, David G.↗

Experimental and Computational Analysis of the Solvent‐Dependent O 2 /Li + ‐O 2 − Redox Couple: Standard Potentials, Coupling Strength, and Implications for Lithium–Oxygen Batteries

Abstract Understanding and controlling the kinetics of O 2 reduction in the presence of Li + ‐containing aprotic solvents, to either Li + ‐O 2 − by one‐electron reduction or Li 2 O 2 by two‐electron reduction, is instrumental to enhance the discharge voltage and capacity of aprotic Li‐O 2 batteries. Standard potentials of O 2 /Li + ‐O 2 − and O 2 /O 2 − were experimentally measured and computed using a mixed cluster‐continuum model of ion solvation. Increasing combined solvation of Li + and O 2 − was found to lower the coupling of Li + ‐O 2 − and the difference between O 2 /Li + ‐O 2 − and O 2 /O 2 − potentials. The solvation energy of Li + trended with donor number (DN), and varied greater than that of O 2 − ions, which correlated with acceptor number (AN), explaining a previously reported correlation between Li + ‐O 2 − solubility and DN. These results highlight the importance of the interplay between ion–solvent and ion–ion interactions for manipulating the energetics of intermediate species produced in aprotic metal–oxygen batteries.

Kwabi, David G.↗

A cluster of results on amplituhedron tiles

Abstract The amplituhedron is a mathematical object which was introduced to provide a geometric origin of scattering amplitudes in $$\mathcal {N}=4$$ N = 4 super Yang–Mills theory. It generalizes cyclic polytopes and the positive Grassmannian and has a very rich combinatorics with connections to cluster algebras. In this article, we provide a series of results about tiles and tilings of the $$m=4$$ m = 4 amplituhedron. Firstly, we provide a full characterization of facets of BCFW tiles in terms of cluster variables for $$\text{ Gr}_{4,n}$$ Gr 4 , n . Secondly, we exhibit a tiling of the $$m=4$$ m = 4 amplituhedron which involves a tile which does not come from the BCFW recurrence—the spurion tile, which also satisfies all cluster properties. Finally, strengthening the connection with cluster algebras, we show that each standard BCFW tile is the positive part of a cluster variety, which allows us to compute the canonical form of each such tile explicitly in terms of cluster variables for $$\text{ Gr}_{4,n}$$ Gr 4 , n . This paper is a companion to our previous paper “Cluster algebras and tilings for the $$m=4$$ m = 4 amplituhedron.”

Physics↗

Meso-scale microstructural agglomerate quantification in boron carbide using X-ray microcomputed tomography

Highlights: • First known quantification of agglomerate defect distributions comprising of carbonaceous and aluminum nitride phases B{sub 4}C. • In-depth statistical analyses of the size, orientation, and morphology of the defects. • The determination of directional dependence of the hot-pressing direction on the agglomerate distributions. - Abstract: Failure in brittle materials is governed, in part, by the specific microstructure of that material, with heterogeneous microstructures generally leading to reduced mechanical properties and performance. In ceramics used for armor, an increase in compressive strength can be an indicator of improved ballistic performance. In hot-pressed boron carbide (B{sub 4}C) ceramic plates, failure has been attributed to carbonaceous flakes observed on the fracture surfaces of failed specimens. However, this current work shows agglomerates, in addition to the carbonaceous flakes, are present in this boron carbide. The density and distribution of these agglomerates are believed to influence the ballistic performance. Therefore, it is of interest to improve the quantification of meso-scale microstructural agglomerates so that strategies can be developed to mitigate them. This work is focused on the microstructural characterization of dumbbell-shaped compression specimens that were machined from a single tile of pressure-aided densification (PAD) B{sub 4}C, using high-resolution micro-computed tomography (microCT). Large clusters of non-B{sub 4}C agglomerates, up to 125 μm in diameter, were observed in addition to the typical smaller carbonaceous flakes and aluminum-based phases. Agglomerate size distribution, orientation, morphology, and spacing were quantified both parallel and perpendicular to the pressing direction. This defect quantification provides valuable information for a better understanding of the material microstructure which is a critical step in improving armor materials for the future.

36 MATERIALS SCIENCE↗

Simplifying computational workflows with the Multiscale Atomic Zeolite Simulation Environment (MAZE)

Zeolites, an important class of 3-dimensional nanoporous materials, have been widely explored for a variety of applications including gas storage, separations, and catalysis. As the properties of these aluminosilicate materials depend on a number of factors (e.g., framework topology, Si/Al ratio, extra-framework cations etc.), detailed experiments (e.g., catalytic properties, adsorption capacities etc.) are often limited to only a handful of materials. Computational methods have played an important role in (1) providing molecular level insights to rationalize experimental observations, and (2) screening large libraries of zeolites to identify promising candidates for experimental synthesis and validation. Different levels of theory and computational chemistry codes are necessary to describe the range of relevant phenomena such as adsorption (e.g., grand canonical Monte Carlo), diffusion (e.g., molecular dynamics), and chemical reactions (e.g., density functional theory). Manipulation of atomic structures, handling of input files, and developing robust workflows becomes quite cumbersome. To mitigate these challenges, we describe the development of the Multiscale Atomic Zeolite Simulation Environment (MAZE) – a Python package that simplifies zeolite-specific calculation workflows by providing a user-friendly interface for systematically manipulating zeolite structures

97 MATHEMATICS AND COMPUTING↗

DONKEY: A Flexible and Accurate Algorithm for Clustering

We propose an accurate clustering algorithm suitable for the varied and multidimensional data sets that correspond to temporal snapshots from on-the-fly nonadiabatic trajectory-based simulations of photoexcited dynamics. The algorithm approximates the underlying probability density function using variable kernel density estimation, with local maxima corresponding to cluster centers. Each data point is then assigned to one of the maxima by employing a maximization procedure. Finally, clusters artificially separated by minor fluctuations in the probability density are merged. The algorithm does not require parameter tuning, which ensures flexibility and reduces the risk of bias. It is tested on several synthetic data sets, where it consistently outperforms conventional clustering algorithms. As a final example, the algorithm is applied to the excited dynamics of the norbornadiene ⇌ quadricyclane (C 7 H 8 ) molecular photoswitch, demonstrating how distinct reaction pathways can be identified.

algorithms↗

LeaPP: Learning Pathways to Polymorphs through Machine Learning Analysis of Atomic Trajectories

Understanding the mechanisms underlying crystal nucleation and growth is crucial for many technological applications. Due to the short length and time scales involved, crystal nucleation is often studied using molecular simulations. Most existing approaches to extract the nucleation mechanism from simulations focus on the analysis of static snapshots of the configurations, potentially overlooking subtle local fluctuations and the history of the particles involved in the formation of solid nuclei. Here, in this work, we propose a novel methodology called LeaPP that categorizes nucleation trajectories based on the temporal information of their constituent particles. We leverage the time evolution of the local environment of the crystallizing particles to encapsulate the relationship between the structure and dynamics and distinguish between different evolving particle paths. Identification of the distinct particle paths further enables characterizing the nucleation trajectories into different pathways. Collectively, LeaPP provides a more nuanced understanding of nucleation through an unsupervised approach with lesser dependence on traditional order parameters. Furthermore, the pathways identified by LeaPP are predictive of the resulting polymorph. We demonstrate LeaPP on three different systems─Lennard-Jones-like particles, Ni 3 Al, and water on surfaces. The general methodology underlying LeaPP─considering the time evolution of the building blocks─applies to a wide range of self-assembly problems.

36 MATERIALS SCIENCE↗

Determining Atomistic SAXS Models of Tri-Ubiquitin Chains from Bayesian Analysis of Accelerated Molecular Dynamics Simulations

Small-angle X-ray scattering (SAXS) has become an increasingly popular technique for characterizing the solution ensemble of flexible biomolecules. However, data resulting from SAXS is typically low-dimensional and is therefore difficult to interpret without additional structural knowledge. In theory, molecular dynamics (MD) trajectories can provide this information, but conventional simulations rarely sample the complete ensemble. Here, we demonstrate that accelerated MD simulations can be used to produce higher quality models in shorter time scales than standard simulations, and we present an iterative Bayesian Monte Carlo method that is able to identify multistate ensembles without overfitting. This methodology is applied to several ubiquitin trimers to demonstrate the effect of linkage type on the solution states of the signaling protein. Here, we observe that the linkage site directly affects the solution flexibility of the trimer and theorize that this difference in plasticity contributes to their disparate roles in vivo.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

First-Principles Simulations of CuCl in High-Temperature Water Vapor

Experimental data suggest that the solubility of copper in high-temperature water vapor is controlled by the formation of hydrated clusters of the form CuCl(H 2 O) n , where the average number of water molecules in the cluster generally increases with increasing density [Migdisov, A. A.; et al. Geochim. Cosmochim. Acta2014, 129, 33–53]. However, the precise nature of these clusters is difficult to probe experimentally. Moreover, there are some discrepancies between experimental estimates of average cluster size and prior simulation work [Mei, Y. Geofluids2018, 2018, 4279124]. Here, we have performed first-principles Monte Carlo (MC) and molecular dynamics (MD) simulations to explore these clusters in finer detail. We find that molecular dynamics is not the most appropriate technique for studying aggregation in vapor phases, even at relatively high temperatures. Specifically, our MD simulations exhibit substantial problems in adequately sampling the equilibrium cluster size distribution. In contrast, MC simulations with specialized cluster moves are able to accurately sample the phase space of hydrogen-bonding vapors. At all densities, we find a stable, slightly distorted linear H 2 O–Cu–Cl structure, which is in agreement with the earlier simulations, surrounded by a variable number of water molecules. The surrounding water molecules do not form a well-defined second solvation shell but rather a loose network of hydrogen-bonded water with molecular CuCl on the outside edge of the water cluster. We also find a broad distribution of hydration numbers, especially at higher densities. In contrast to previous simulation work but in agreement with experimental data, we find that the average hydration number substantially increases with increasing density. Moreover, the value of the hydration number depends on the choice of cluster definition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Crystal Nucleation Kinetics and Mechanism: Influence of Interaction Potential

Modulating liquid-to-solid transitions and the resulting crystalline structure for tailored properties is much desired. Colloidal systems are exemplary to this end, but the fundamental knowledge gaps in relating the influence of intermolecular interactions to crystallization behavior continue to hinder progress. In this study, we address this knowledge gap by studying nucleation and growth in systems with modified Lennard-Jones potential. Specifically, we study the commonly used 12-6 potential and a softer 7-6 potential. The thermodynamic state point for the study is chosen such that both systems are investigated at the same level of supercooling and pressure. Under these conditions, we find that the nucleation rate for both systems is comparable. Interestingly, the nucleation pathways and resulting crystal structures are different. In the 12-6 system, nucleation and growth occur predominantly through the FCC structure. Softening the potential alters the critical nucleus composition and introduces two distinct nucleation pathways. One pathway predominantly leads to the nucleus with a body-centered cubic (BCC) structure, while the other favors the face-centered cubic (FCC) arrangement. Our study illustrates that polymorph selection can be achieved through modifications to intermolecular interactions without impacting nucleation kinetics. The results have significant implications in designing approaches for polymorph selection and modulating self-assembly mechanisms.

36 MATERIALS SCIENCE↗

Reagent-Triggered Isomerization of Fluxional Cluster Catalyst via Dynamic Coupling

Metallic cluster catalysts have many thermodynamically accessible isomers with diverse active sites and low reaction barriers, and lately a strong hypothesis emerged that the many catalyst states collectively drive the catalysis. Furthermore, it remained a hypothesis that catalyst isomerization is actually kinetically feasible under the current reaction conditions. Using high-temperature dynamics simulations and sampling, a range of orientations, and vibrational energy distributions, we probe how thermal effects and molecular events affect cluster catalyst dynamics. We show that even such a delicate affair as the dissociation or scattering of a methane molecule on the heavy and thus slow Pt 13 cluster triggers substantial isomerization of the catalyst, far beyond thermal at 700 K. A kinetic coupling between the methane activity and cluster catalyst dynamics is observed. In return, the thermal dynamics of the cluster affects the methane reaction and scattering probabilities. Hence, molecular events at the surfaces of fluxional cluster catalysts should facilitate the population of an ensemble of catalyst states under the current reaction conditions, with implications for available active sites, reaction mechanisms, and apparent rates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Formation of Exotic Networks of Water Clusters in Helium Droplets Facilitated by the Presence of Neon Atoms

Water clusters are formed in helium droplets via the sequential capture of monomers. One or two neon atoms are added to each droplet prior to the addition of water. The infrared spectrum of the droplet ensemble reveals several signatures of polar, water tetramer clusters having dipole moments between 2D and 3D. Comparison with ab initio computations supports the assignment of the cluster networks to noncyclic “3+1” clusters, which are ~5.3 kcal/mol less stable than the global minimum nonpolar cyclic tetramer. The (H2O)3Ne + H2O ring insertion barrier is sufficiently large, such that evaporative helium cooling is capable of kinetically quenching the nonequilibrium tetramer system prior to its rearrangement to the lower energy cyclic species. To this end, the reported process results in the formation of exotic water cluster networks that are either higher in energy than the most stable gas-phase analogs or not even stable in the gas phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗