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At least 1,585 records · Page 88

Molecular structure determination: Equilibrium structure of pyrimidine (m-C 4 H 4 N 2 ) from rotational spectroscopy (reSE) and high-level ab initio calculation (re) agree within the uncertainty of experimental measurement

The pure rotational spectrum of pyrimidine (m-C 4 H 4 N 2 ), the meta-substituted dinitrogen analog of benzene, has been studied in the millimeter-wave region from 235 GHz to 360 GHz. The rotational spectrum of the ground vibrational state has been assigned and fit to yield accurate rotational and distortion constants. Over 1700 distinct transitions were identified for the normal isotopologue in its ground vibrational state and least-squares fit to a partial sextic S-reduced Hamiltonian. Transitions for all four singly substituted 13 C and 15 N isotopologues were observed at natural abundance and were likewise fit. Deuterium-enriched samples of pyrimidine were synthesized, giving access to all eleven possible deuterium-substituted isotopologues, ten of which were previously unreported. Experimental values of rotational constants and computed values of vibration–rotation interaction constants and electron-mass corrections were used to determine semi-experimental equilibrium structures (r e SE ) of pyrimidine. The r e SE structure obtained using coupled-cluster with single, double, and perturbative triple excitations [CCSD(T)] corrections shows exceptional agreement with the re structure computed at the CCSD(T)/cc-pCV5Z level (≤0.0002 Å in bond distance and ≤0.03° in bond angle). Of the various computational methods examined, CCSD(T)/cc-pCV5Z is the only method for which the computed value of each geometric parameter lies within the statistical experimental uncertainty (2σ) of the corresponding semi-experimental coordinate. The exceptionally high accuracy and precision of the structure determination is a consequence of the large number of isotopologues measured, the precision and extent of the experimental frequency measurements, and the sophisticated theoretical treatment of the effects of vibration–rotation coupling and electron mass. Taken together, these demanding experimental and computational studies establish the capabilities of modern structural analysis for a prototypical monocyclic aromatic compound.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Small Al clusters. I - The effect of basis set and correlation on the geometry of small Al clusters

A detailed study is presented of the basis set requirements and effects of correlation on the geometry and structure of small Al(n) clusters n = 2, 4, and 13. An effective core potential (ECP) is developed from the Huzinaga basis which accurately reproduces the all-electron results. It is found that depolarization functions are very important in computing the bond length, and that the bond contraction obtained is about as large for a 13-atom cluster as for the Al(4) rhombus structure. With d functions on each center in Al(13), a bond distance shorter than the bulk is obtained, as expected. The inclusion of correlation in Al(4) is found to be less important than the addition of polarization functions for determining the bond length, but increases substantially the calculated atomization energy. These calibration calculations allow an accurate treatment for Al(n) clusters to be designed.

Bauschlicher, Charles W., Jr.↗

Latent code-based fusion: A Volterra neural network approach

We propose a deep structure encoder using Volterra Neural Networks (VNNs) to seek a latent representation of multi-modal data whose features are jointly captured by a union of subspaces. The so-called self-representation embedding of the latent codes leads to a simplified fusion which is driven by a similarly constructed decoding. The Volterra Filter architecture achieved reduction in parameter complexity is primarily due to controlled non-linearities being introduced by the higher-order convolutions in lieu of generalized activation functions. Experimental results on two different datasets have shown a significant improvement in the clustering performance for VNNs auto-encoder over conventional Convolutional Neural Networks (CNNs) auto-encoder. In addition, we also show that the proposed approach demonstrates a much-improved sample complexity over CNN-based auto-encoder with a robust classification performance.

97 MATHEMATICS AND COMPUTING↗

Stability and mobility of tungsten clusters on tungsten (110) surface: Ab initio and atomistic simulations

Quantifying the surface transport properties of tungsten (W) is of prime importance to understand the formation of nano-fuzz in fusion plasma-facing conditions. The stability and mobility of W adatom clusters (W n , n = 2-9) on the W(110) surface has been investigated by computer simulations, including ab initio calculations using density functional theory (DFT) and molecular statics (MS) simulations with multiple W interatomic potentials. The DFT results demonstrate that the sequential binding energy generally increases with number of W adatoms, except for the 5 th and 7 th W adatoms. The most common elemental migration steps of W n (n>2) clusters are observed to consist of monomer and dimer hops, while larger W n clusters can also diffuse by dissociation and recombination of smaller clusters. The threshold migration energy of W 9 is the highest, then followed by W 8 , W 4 , and W 6 , while W 3 , W 5 , and W 7 have similar migration energies. Compared to DFT, each interatomic potential evaluated overestimates the binding energies of W n clusters. Additionally, the embedded-atom potential developed by Juslin and Wirth adequately predicts the threshold migration energy of W n (n>2) clusters, although it predicts different underlying migration mechanisms. The results show that interaction mechanism between W adatoms controls the stability and mobility of W n clusters on the W(110) surface.

36 MATERIALS SCIENCE↗

Parallel and Distributed Computational Fluid Dynamics: Experimental Results and Challenges

This paper describes several results of parallel and distributed computing using a large scale production flow solver program. A coarse grained parallelization based on clustering of discretization grids combined with partitioning of large grids for load balancing is presented. An assessment is given of its performance on distributed and distributed-shared memory platforms using large scale scientific problems. An experiment with this solver, adapted to a Wide Area Network execution environment is presented. We also give a comparative performance assessment of computation and communication times on both the tightly and loosely-coupled machines.

Djomehri, Mohammad Jahed↗

Continuous Security and Configuration Monitoring of HPC Clusters

Continuous security and configuration monitoring of information systems has been a time consuming and laborious task for system administrators at the High Performance Computing (HPC) center. Prior to this project, system administrators had to manually check the settings of thousands of nodes, which required a significant number of hours rendering the old process ineffective and inefficient. This paper explains the application of Splunk Enterprise, a software agent, and a reporting tool in the development of a user application interface to track and report on critical system updates and security compliance status of HPC Clusters. In conjunction with other configuration management systems, the reporting tool is to provide continuous situational awareness to system administrators of the compliance state of information systems. Our approach consisted of the development, testing, and deployment of an agent to collect any arbitrary information across a massively distributed computing center, and organize that information into a human-readable format. Using Splunk Enterprise, this raw data was then gathered into a central repository and indexed for search, analysis, and correlation. Following acquisition and accumulation, the reporting tool generated and presented actionable information by filtering the data according to command line parameters passed at run time. Preliminary data showed results for over six thousand nodes. Further research and expansion of this tool could lead to the development of a series of agents to gather and report critical system parameters. However, in order to make use of the flexibility and resourcefulness of the reporting tool the agent must conform to specifications set forth in this paper. This project has simplified the way system administrators gather, analyze, and report on the configuration and security state of HPC clusters, maintaining ongoing situational awareness. Rather than querying each cluster independently, compliance checking can be managed from one central location.

97 MATHEMATICS AND COMPUTING↗

Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package

This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange-correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear-electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an "open teamware" model and an increasingly modular design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Scalable Multiprocessor for High-Speed Computing in Space

A report discusses the continuing development of a scalable multiprocessor computing system for hard real-time applications aboard a spacecraft. "Hard realtime applications" signifies applications, like real-time radar signal processing, in which the data to be processed are generated at "hundreds" of pulses per second, each pulse "requiring" millions of arithmetic operations. In these applications, the digital processors must be tightly integrated with analog instrumentation (e.g., radar equipment), and data input/output must be synchronized with analog instrumentation, controlled to within fractions of a microsecond. The scalable multiprocessor is a cluster of identical commercial-off-the-shelf generic DSP (digital-signal-processing) computers plus generic interface circuits, including analog-to-digital converters, all controlled by software. The processors are computers interconnected by high-speed serial links. Performance can be increased by adding hardware modules and correspondingly modifying the software. Work is distributed among the processors in a parallel or pipeline fashion by means of a flexible master/slave control and timing scheme. Each processor operates under its own local clock; synchronization is achieved by broadcasting master time signals to all the processors, which compute offsets between the master clock and their local clocks.

Lux, James↗

Evaluation of advanced automatic PET segmentation methods using nonspherical thin-wall inserts

Purpose: The use of positron emission tomography (PET) within radiotherapy treatment planning requires the availability of reliable and accurate segmentation tools. PET automatic segmentation (PET-AS) methods have been recommended for the delineation of tumors, but there is still a lack of thorough validation and cross-comparison of such methods using clinically relevant data. In particular, studies validating PET segmentation tools mainly use phantoms with thick plastic walls inserts of simple spherical geometry and have not specifically investigated the effect of the target object geometry on the delineation accuracy. Our work therefore aimed at generating clinically realistic data using nonspherical thin-wall plastic inserts, for the evaluation and comparison of a set of eight promising PET-AS approaches. Methods: Sixteen nonspherical inserts were manufactured with a plastic wall of 0.18 mm and scanned within a custom plastic phantom. These included ellipsoids and toroids derived with different volumes, as well as tubes, pear- and drop-shaped inserts with different aspect ratios. A set of six spheres of volumes ranging from 0.5 to 102 ml was used for a baseline study. A selection of eight PET-AS methods, written in house, was applied to the images obtained. The methods represented promising segmentation approaches such as adaptive iterative thresholding, region-growing, clustering and gradient-based schemes. The delineation accuracy was measured in terms of overlap with the computed tomography reference contour, using the dice similarity coefficient (DSC), and error in dimensions. Results: The delineation accuracy was lower for nonspherical inserts than for spheres of the same volume in 88% cases. Slice-by-slice gradient-based methods, showed particularly lower DSC for tori (DSC < 0.5), caused by a failure to recover the object geometry. The region-growing method reached high levels of accuracy for most inserts (DSC > 0.76 except for tori) but showed the largest errors in the recovery of pears and drops dimensions (higher than 10% and 30% of the true length, respectively). Large errors were visible for one of the gradient-based contouring methods when delineating drop-shaped inserts. Low DSC due to systematic underestimation of the volumes was observed for our fuzzy clustering method when using nonspherical inserts. The adaptive iterative thresholding method produced the highest DSC score on our nonspherical dataset (DSC > 0.83, except for tori) and showed robustness to the insert geometry. Conclusions: This study investigated the accuracy of eight PET-AS methods for the delineation of objects with a range of nonspherical geometries. The authors’ results confirmed the robustness of some segmentation approaches, but also showed the weaknesses of some of the other methods implemented, which were not observed with spherical inserts. This work therefore highlights the importance of using a variety of thin-wall inserts with complex geometries for the validation of PET-AS methods and provided useful information for further development of the methods tested.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Avoiding Excess Computation in Asynchronous Evolutionary Algorithms

Asynchronous evolutionary algorithms are becoming increasingly popular as a means of making full use of many processors while solving computationally expensive search and optimization problems. These algorithms excel at keeping large clusters fully utilized, but may sometimes inefficiently sample an excess of fast-evaluating solutions at the expense of higher-quality, slow-evaluating ones. We introduce a steady-state parent selection strategy, SWEET (“Selection whilE EvaluaTing”), that sometimes selects individuals that are still being evaluated and allows them to reproduce early. This gives slow-evaluating individuals that have higher fitnesses an increased ability to multiply in the population. We find that SWEET appears effective in simulated take-over time analysis, but that its benefit is confined mostly to early in the run, and our preliminary study on an autonomous vehicle controller problem that involves tuning a spiking neural network proves inconclusive.

Scott, Eric↗

SHAPER: can you hear the shape of a jet?

The identification of interesting substructures within jets is an important tool for searching for new physics and probing the Standard Model at colliders. Many of these substructure tools have previously been shown to take the form of optimal transport problems, in particular the Energy Mover’s Distance (EMD). In this work, we show that the EMD is in fact the natural structure for comparing collider events, which accounts for its recent success in understanding event and jet substructure. We then present a Shape Hunting Algorithm using Parameterized Energy Reconstruction (SHAPER), which is a general framework for defining and computing shape-based observables. SHAPER generalizes N-jettiness from point clusters to any extended, parametrizable shape. This is accomplished by efficiently minimizing the EMD between events and parameterized manifolds of energy flows representing idealized shapes, implemented using the dual-potential Sinkhorn approximation of the Wasserstein metric. We show how the geometric language of observables as manifolds can be used to define novel observables with built-in infrared-and-collinear safety. We demonstrate the efficacy of the SHAPER framework by performing empirical jet substructure studies using several examples of new shape-based observables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Cluster truncated Wigner approximation in strongly interacting systems

We present a general method by which linear quantum Hamiltonian dynamics with exponentially many degrees of freedom is replaced by approximate classical nonlinear dynamics with the number of degrees of freedom (phase space dimensionality) scaling polynomially in the system size. This method is based on generalization of the truncated Wigner approximation (TWA) to a higher dimensional phase space, where phase space variables are associated with a complete set of quantum operators spanning finite size clusters. The method becomes asymptotically exact with increasing cluster size. The crucial feature of TWA is fluctuating initial conditions, which we approximate by a Gaussian distribution. We show that such fluctuations dramatically increase accuracy of TWA over traditional cluster mean-field approximations. In this way we can treat on equal footing quantum and thermal fluctuations as well as compute entanglement and various equal and non-equal time correlation functions. The main limitation of the method is exponential scaling of the phase space dimensionality with the cluster size, which can be significantly reduced by using the language of Schwinger bosons and can likely be further reduced by truncating the local Hilbert space variables. We demonstrate the power of this method analyzing dynamics in various spin chains with and without disorder and show that we can capture such phenomena as long time hydrodynamic relaxation, many-body localization and the ballistic spread of entanglement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Accurate modeling and reconstruction of three-dimensional percolating filamentary microstructures from two-dimensional micrographs via dilation-erosion method

Heterogeneous materials are ubiquitous in nature and synthetic situations and have a wide range of important engineering applications. Accurate modeling and reconstructing three-dimensional (3D) microstructure of topologically complex materials from limited morphological information such as a two-dimensional (2D) micrograph is crucial to the assessment and prediction of effective material properties and performance under extreme conditions. Here, we extend a recently developed dilation–erosion method and employ the Yeong–Torquato stochastic reconstruction procedure to model and generate 3D austenitic–ferritic cast duplex stainless steel microstructure containing percolating filamentary ferrite phase from 2D optical micrographs of the material sample. Specifically, the ferrite phase is dilated to produce a modified target 2D microstructure and the resulting 3D reconstruction is eroded to recover the percolating ferrite filaments. The dilation–erosion reconstruction is compared with the actual 3D microstructure, obtained from serial sectioning (polishing), as well as the standard stochastic reconstructions incorporating topological connectedness information. The fact that the former can achieve the same level of accuracy as the latter suggests that the dilation–erosion procedure is tantamount to incorporating appreciably more topological and geometrical information into the reconstruction while being much more computationally efficient. - Highlights: • Spatial correlation functions used to characterize filamentary ferrite phase • Clustering information assessed from 3D experimental structure via serial sectioning • Stochastic reconstruction used to generate 3D virtual structure 2D micrograph • Dilation–erosion method to improve accuracy of 3D reconstruction.

36 MATERIALS SCIENCE↗

Fe Protein-Independent Substrate Reduction by Nitrogenase MoFe Protein Variants

The reduction of substrates catalyzed by nitrogenase normally requires nucleotide-dependent Fe protein delivery of electrons to the MoFe protein, which contains the active site FeMo-cofactor. Here, it is reported that independent substitution of three amino acids (ß-98Tyr→His, α-64Tyr→His, and ß-99Phe→His) located between the P cluster and FeMo-cofactor within the MoFe protein endows it with the ability to reduce protons to H2, azide to ammonia, and hydrazine to ammonia without the need for Fe protein or ATP. Instead, electrons can be provided by the low potential reductant polyaminocarboxylate ligated Eu(II) (Em -1.1 to -0.84 V vs NHE). The crystal structure of the ß-98Tyr→His variant MoFe protein was determined, revealing only small changes near the amino acid substitution that affect the solvent structure and immediate vicinity between the P cluster and the FeMo-cofactor, with no global conformational changes observed. Computational normal mode analysis on the nitrogenase complex reveal coupling in the motions of the Fe protein and the region of the MoFe protein with these three amino acids, which suggests a possible mechanism for how Fe protein might communicate deep within the MoFe protein subtle changes that profoundly affect intramolecular electron transfer and substrate reduction. This work was supported by a grant from the National Science Foundation (MCB-1330807) to JWP and LCS. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences (DE-SC0010687 and DE-SC0010834 to LCS and DRD) and the Division of Chemical Sciences, Geosciences, and Bio-Sciences (SR). The coordinates for the ß-98His MoFe protein were deposited with the Protein Data Bank (PDB 4XPI).

Danyal, Karamatullah↗

Fission and fusion scenarios for magnetic microswimmer clusters

Fission and fusion processes of particle clusters occur in many areas of physics and chemistry from subnuclear to astronomic length scales. Here we study fission and fusion of magnetic microswimmer clusters as governed by their hydrodynamic and dipolar interactions. Rich scenarios are found that depend crucially on whether the swimmer is a pusher or a puller. In particular a linear magnetic chain of pullers is stable while a pusher chain shows a cascade of fission (or disassembly) processes as the self-propulsion velocity is increased. Contrarily, magnetic ring clusters show fission for any type of swimmer. Moreover, we find a plethora of possible fusion (or assembly) scenarios if a single swimmer collides with a ringlike cluster and two rings spontaneously collide. Lastly, our predictions are obtained by computer simulations and verifiable in experiments on active colloidal Janus particles and magnetotactic bacteria.

36 MATERIALS SCIENCE↗

Many-body entanglement in solid-state emitters

The preparation and control of quantum states lie at the heart of quantum information science. Recent advances in solid-state quantum emitters (QEs) and nanophotonics have transformed the landscape of quantum photonic technologies, enabling scalable generation of quantum states of light and matter. A new frontier in solid-state quantum photonics is the engineering of many-body interactions between QEs and photons to achieve robust coherence and controllable many-body entanglement. These entangled states, including photonic graph and cluster states, superradiant emission and emergent quantum phases, are promising for quantum computation, sensing and simulation. However, intrinsic inhomogeneities and decoherence in solid-state platforms pose considerable challenges in realizing such complex entangled states. This Review provides an overview of fundamental many-body interactions and dynamics at the light–matter interfaces of solid-state QEs and discusses recent advances in mitigating decoherence and harnessing robust many-body coherence.

36 MATERIALS SCIENCE↗

Hydrogen evolution from water through metal sulfide reactions

Transition metal sulfides play an important catalytic role in many chemical reactions. In this work, we have conducted a careful computational study of the structures, electronic states, and reactivity of metal sulfide cluster anions M{sub 2}S{sub X}{sup −} (M = Mo and W, X = 4–6) using density functional theory. Detailed structural analysis shows that these metal sulfide anions have ground state isomers with two bridging sulfide bonds, notably different in some cases from the corresponding oxides with the same stoichiometry. The chemical reactivity of these metal sulfide anions with water has also been carried out. After a thorough search on the reactive potential energy surface, we propose several competitive, energetically favorable, reaction pathways that lead to the evolution of hydrogen. Selectivity in the initial water addition and subsequent hydrogen migration are found to be the key steps in all the proposed reaction channels. Initial adsorption of water is most favored involving a terminal metal sulfur bond in Mo{sub 2}S{sub 4}{sup −} isomers whereas the most preferred orientation for water addition involves a bridging metal sulfur bond in the case of W{sub 2}S{sub 4}{sup −} and M{sub 2}S{sub 5}{sup −} isomers. In all the lowest energy H{sub 2} elimination steps, the interacting hydrogen atoms involve a metal hydride and a metal hydroxide (or thiol) group. We have also observed a higher energy reaction channel where the interacting hydrogen atoms in the H{sub 2} elimination step involve a thiol (–SH) and a hydroxyl (–OH) group. For all the reaction pathways, the Mo sulfide reactions involve a higher barrier than the corresponding W analogues. We observe for both metals that reactions of M{sub 2}S{sub 4}{sup −} and M{sub 2}S{sub 5}{sup −} clusters with water to liberate H{sub 2} are exothermic and involve modest free energy barriers. However, the reaction of water with M{sub 2}S{sub 6}{sup −} is highly endothermic with a considerable barrier due to saturation of the local bonding environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Distributions of methyl group rotational barriers in polycrystalline organic solids

We bring together solid state {sup 1}H spin-lattice relaxation rate measurements, scanning electron microscopy, single crystal X-ray diffraction, and electronic structure calculations for two methyl substituted organic compounds to investigate methyl group (CH{sub 3}) rotational dynamics in the solid state. Methyl group rotational barrier heights are computed using electronic structure calculations, both in isolated molecules and in molecular clusters mimicking a perfect single crystal environment. The calculations are performed on suitable clusters built from the X-ray diffraction studies. These calculations allow for an estimate of the intramolecular and the intermolecular contributions to the barrier heights. The {sup 1}H relaxation measurements, on the other hand, are performed with polycrystalline samples which have been investigated with scanning electron microscopy. The {sup 1}H relaxation measurements are best fitted with a distribution of activation energies for methyl group rotation and we propose, based on the scanning electron microscopy images, that this distribution arises from molecules near crystallite surfaces or near other crystal imperfections (vacancies, dislocations, etc.). An activation energy characterizing this distribution is compared with a barrier height determined from the electronic structure calculations and a consistent model for methyl group rotation is developed. The compounds are 1,6-dimethylphenanthrene and 1,8-dimethylphenanthrene and the methyl group barriers being discussed and compared are in the 2–12 kJ mol{sup −1} range.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗