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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 739 records · Page 41

Explicit correlation treatment of the potential energy surface of CO{sub 2} dimer

We present an extensive study of the four-dimensional potential energy surface (4D-PES) of the carbon dioxide dimer, (CO{sub 2}){sub 2}. This PES is developed over the set of intermolecular coordinates. The electronic computations are carried out at the explicitly correlated coupled cluster method with single, double, and perturbative triple excitations [CCSD(T)-F12] level of theory in connection with the augmented correlation-consistent aug-cc-pVTZ basis set. An analytic representation of the 4D-PES is derived. Our extensive calculations confirm that “Slipped Parallel” is the most stable form and that the T-shaped structure corresponds to a transition state. Later on, this PES is employed for the calculations of the vibrational energy levels of the dimer. Moreover, the temperature dependence of the dimer second virial coefficient and of the first spectral moment of rototranslational collision-induced absorption spectrum is derived. For both quantities, a good agreement is found between our values and the experimental data for a wide range of temperatures. This attests to the high quality of our PES. Generally, our PES and results can be used for modeling CO{sub 2} supercritical fluidity and examination of its role in planetary atmospheres. It can be also incorporated into dynamical computations of CO{sub 2} capture and sequestration. This allows deep understanding, at the microscopic level, of these processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Massively scalable workflows for quantum chemistry: BigChem and ChemCloud

Electronic structure theory, i.e., quantum chemistry, is the fundamental building block for many problems in computational chemistry. Here we present a new distributed computing framework (BigChem), which allows for an efficient solution of many quantum chemistry problems in parallel. BigChem is designed to be easily composable and leverages industry-standard middleware (e.g., Celery, RabbitMQ, and Redis) for distributed approaches to large scale problems. BigChem can harness any collection of worker nodes, including ones on cloud providers (such as AWS or Azure), local clusters, or supercomputer centers (and any mixture of these). BigChem builds upon MolSSI packages, such as QCEngine to standardize the operation of numerous computational chemistry programs, demonstrated here with Psi4, xtb, geomeTRIC, and TeraChem. BigChem delivers full utilization of compute resources at scale, offers a programable canvas for designing sophisticated quantum chemistry workflows, and is fault tolerant to node failures and network disruptions. We demonstrate linear scalability of BigChem running computational chemistry workloads on up to 125 GPUs. Finally, we present ChemCloud, a web API to BigChem and successor to TeraChem Cloud. ChemCloud delivers scalable and secure access to BigChem over the Internet.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A cloud computing approach to massively-parallel distributed stochastic optimization with application to geomechanical reservoir characterization

Many search strategies used to optimize parameters during hydrologic model calibration are inherently limited in that simulations must be performed sequentially in order for the algorithm to converge. As a result, the overall time required to reach a solution increases linearly with the number of steps necessary. In contrast, sampling strategies that attempt to approximate the posterior distribution of the parameters do not require the model simulations to be run in sequence and therefore invite the use of a massively parallel approach across heterogeneous computing environments. We apply a cloud computing methodology to this problem where a head node running on Amazon Web Services continuously produces candidate models that are distributed to arbitrary compute environments to run the simulation, in our case Clemson’s Palmetto cluster computer. Thus the time required to obtain a sufficient number of samples to produce an adequate approximation of the posterior distribution of the parameters is limited by the number of available compute sites. Monte Carlo sampling of the posterior space would be duplicative and inefficient, thus we combine Latin hypercube methods with genetic algorithms to ensure that no large regions of the parameter space are left unexplored, and that high probability regions are investigated thoroughly. We independently assess the fit to different types of data sets without the need to construct a single objective function. Sets of Pareto optimal models are particularly valuable when the quality and information content of data is poorly known or conceptual model errors exist in our simulation. We illustrate our approach for a problem where in situ strain data are used to calibrate the parameters of an oil reservoir in the Avant oil field in Oklahoma. We use well injection and shut-in to stress a deep (500m) confined formation, and observe the geomechanical response using borehole strainmeters installed in the shallow subsurface (30m). These data were then used to calibrate the poroelastic properties of the reservoir and caprock along with the geometry of an elliptic channel associated with the formation. Using our approach we are able to identify issues with model error as well as substantial tradeoffs that occur within the parameters.

inversion, stochastic, geomechanics, poroelastic, ↗

Global Transformations for Legacy Parallel Applications via Structural Analysis and Rewriting

Performance and scalability optimization of large HPC applications is currently a labor-intensive, manual process with very low productivity. Major difficulties come from the disaggregated environment for HPC application development: the compiler is only involved in local decisions (core or multithreaded domain), while a library-based, communication-oriented programming model realizes whole-machine parallelism. Realizing any major global change in such a disaggregated environment is very difficult and involves changing large portions of the source code. We present semi-automated techniques, based on structural analysis and rewriting, for performing global transformations on an HPC application source code. We present two case studies using the Self-Consistent Field (SCF) standalone benchmark as well as the Coupled Cluster (CCSD) module (2.9 million lines of Fortran code), a key module of the NWChem computational chemistry application. We demonstrate how structural rewriting techniques can be used to automate transformations that affect multiple sections of the application's source code. We show that the transformations can be applied in a systematic fashion across the source code bases with minimal manual effort. These transformations improve the scalability of the SCF benchmark by more than two orders of magnitude and the performance of the full CCSD module by a factor of 4.0.

legacy parallel applications↗

Adsorption of Water on JSC-1A Lunar Simulant Samples

Remote sensing probes sent to the moon in the 1990s indicated that water may exist in areas such as the bottoms of deep, permanently shadowed craters at the lunar poles, buried under regolith. Water is of paramount importance for any lunar exploration and colonization project which would require self-sustainable systems. Therefore, investigating the interaction of water with lunar regolith is pertinent to future exploration. The lunar environment can be approximated in ultra-high vacuum systems such as those used in thermal desorption spectroscopy (TDS). Questions about water dissociation, surface wetting, degree of crystallization, details of water-ice transitions, and cluster formation kinetics can be addressed by TDS. Lunar regolith specimens collected during the Apollo missions are still available though precious, so testing with simulant is required before applying to use lunar regolith samples. Hence, we used for these studies JSC-1a, mostly an aluminosilicate glass and basaltic material containing substantial amounts of plagioclase, some olivine and traces of other minerals. Objectives of this project include: 1) Manufacturing samples using as little raw material as possible, allowing the use of surface chemistry and kinetics tools to determine the feasibility of parallel studies on regolith, and 2) Characterizing the adsorption kinetics of water on the regolith simulant. This has implications for the probability of finding water on the moon and, if present, for recovery techniques. For condensed water films, complex TDS data were obtained containing multiple features, which are related to subtle rearrangements of the water adlayer. Results from JSC-1a TDS studies indicate: 1) Water dissociation on JSC-1a at low exposures, with features detected at temperatures as high as 450 K and 2) The formation of 3D water clusters and a rather porous condensed water film. It appears plausible that the sub- m sized particles act as nucleation centers.

Goering, John↗

Non-equilibrium reaction and relaxation dynamics in a strongly interacting explicit solvent: F + CD{sub 3}CN treated with a parallel multi-state EVB model

We describe a parallelized linear-scaling computational framework developed to implement arbitrarily large multi-state empirical valence bond (MS-EVB) calculations within CHARMM and TINKER. Forces are obtained using the Hellmann-Feynman relationship, giving continuous gradients, and good energy conservation. Utilizing multi-dimensional Gaussian coupling elements fit to explicitly correlated coupled cluster theory, we built a 64-state MS-EVB model designed to study the F + CD{sub 3}CN → DF + CD{sub 2}CN reaction in CD{sub 3}CN solvent (recently reported in Dunning et al. [Science 347(6221), 530 (2015)]). This approach allows us to build a reactive potential energy surface whose balanced accuracy and efficiency considerably surpass what we could achieve otherwise. We ran molecular dynamics simulations to examine a range of observables which follow in the wake of the reactive event: energy deposition in the nascent reaction products, vibrational relaxation rates of excited DF in CD{sub 3}CN solvent, equilibrium power spectra of DF in CD{sub 3}CN, and time dependent spectral shifts associated with relaxation of the nascent DF. Many of our results are in good agreement with time-resolved experimental observations, providing evidence for the accuracy of our MS-EVB framework in treating both the solute and solute/solvent interactions. The simulations provide additional insight into the dynamics at sub-picosecond time scales that are difficult to resolve experimentally. In particular, the simulations show that (immediately following deuterium abstraction) the nascent DF finds itself in a non-equilibrium regime in two different respects: (1) it is highly vibrationally excited, with ∼23 kcal mol{sup −1} localized in the stretch and (2) its post-reaction solvation environment, in which it is not yet hydrogen-bonded to CD{sub 3}CN solvent molecules, is intermediate between the non-interacting gas-phase limit and the solution-phase equilibrium limit. Vibrational relaxation of the nascent DF results in a spectral blue shift, while relaxation of the post-reaction solvation environment results in a red shift. These two competing effects mean that the post-reaction relaxation profile is distinct from what is observed when Franck-Condon vibrational excitation of DF occurs within a microsolvation environment initially at equilibrium. Our conclusions, along with the theoretical and parallel software framework presented in this paper, should be more broadly applicable to a range of complex reactive systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spatially Accelerated Winding Numbers for Curved Geometry

The generalized winding number (GWN) is a scalar field that supports robust containment queries on curved geometry, including non-watertight, overlapping, and nested boundary representations. While queries can be easily parallelized over samples, direct evaluation on parametric curves and surfaces remains costly for large and complex models. Fast, state-of-the-art GWN approaches leverage a spatial index to approximate the GWN, typically coupled with a Taylor expansion which approximates the GWN contribution for far clusters of geometric primitives. However, such methods operate only on discrete inputs such as triangle meshes and point clouds, and would introduce containment errors near boundaries if applied to curved input. We extend support for fast GWN evaluation over arbitrary collections of NURBS curves in 2D and trimmed NURBS patches in 3D via a Bounding Volume Hierarchy that stores efficiently precomputed moment data in the hierarchy nodes. When querying the hierarchy, approximations for far clusters are used alongside direct evaluation for nearby NURBS primitives, achieving sub-linear complexity while preserving the geometric features in the vicinity of the query point. Central to our performance improvements is an adaptive subdivision strategy for NURBS primitives during a preprocessing phase, creating better spatial partitions while retaining the same accuracy for containment decisions as a direct evaluation. We demonstrate the performance and accuracy of our approach across a large collection of 2D and 3D datasets.

Computer science↗

Predictive Modeling of Aging and Degradation of Materials in Extreme Environments.

In order to accurately describe defect accumulation in heterogeneous microstructures and under complex irradiation conditions, simulation methods are needed that can explicitly account for the effect of nonhomogeneous microstructures on damage accumulation. In this project, an advanced simulation tool called spatially resolved stochastic cluster dynamics (SRSCD) is developed for this purpose. The proposed approach relies on solving spatially resolved coupled rate equations of standard cluster dynamics methods in a kinetic Monte Carlo scheme. Large-scale simulations of radiation damage in polycrystalline materials are enabled through several improvements made to this method, including a pseudo-adaptive meshing scheme for cascade implantation and implementation of this method in a synchronous parallel kinetic Monte Carlo framework.

36 MATERIALS SCIENCE↗

Implementation of analytic gradients for CCSD and EOM-CCSD using Cholesky decomposition of the electron-repulsion integrals and their derivatives: Theory and benchmarks

We present a general formulation of analytic nuclear gradients for the coupled-cluster with single and double substitution (CCSD) and equation-of-motion (EOM) CCSD energies computed using Cholesky decomposition (CD) representations of the electron repulsion integrals. By rewriting the correlated energy and response equations such that the storage of the largest four-index intermediates is eliminated, CD leads to a significant reduction in disk storage requirements, reduced I/O penalties, and an improved parallel performance. CD thus extends the scope of the systems that can be treated by (EOM-)CCSD methods, although analytic gradients in the framework of CD are needed to extend the applicability of (EOM-)CCSD methods in the context of geometry optimizations. This paper presents a formulation of analytic (EOM-)CCSD gradient within the CD framework and reports on the salient details of the corresponding implementation. The accuracy and the capabilities of analytic CD-based (EOM-)CCSD gradients are illustrated by benchmark calculations and several illustrative examples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Paradeisos: A perfect hashing algorithm for many-body eigenvalue problems

Here, we describe an essentially perfect hashing algorithm for calculating the position of an element in an ordered list, appropriate for the construction and manipulation of many-body Hamiltonian, sparse matrices. Each element of the list corresponds to an integer value whose binary representation reflects the occupation of single-particle basis states for each element in the many-body Hilbert space. The algorithm replaces conventional methods, such as binary search, for locating the elements of the ordered list, eliminating the need to store the integer representation for each element, without increasing the computational complexity. Combined with the “checkerboard” decomposition of the Hamiltonian matrix for distribution over parallel computing environments, this leads to a substantial savings in aggregate memory. While the algorithm can be applied broadly to many-body, correlated problems, we demonstrate its utility in reducing total memory consumption for a series of fermionic single-band Hubbard model calculations on small clusters with progressively larger Hilbert space dimension.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Molecular dynamics study of primary damage in the near-surface region in nickel

In this work, we carried out a large-scale molecular dynamics (MD) simulation to elucidate the effect of the free surface on the defect production of displacement cascades in pure nickel. These MD simulations were performed both in the bulk and near-surface regions with primary knock-on atom (PKA) energies of E PKA = 1, 5, or 10 keV and at temperatures T = 300, 425, or 525 K. Additionally, for every (T, E PKA ), near-surface cascade simulations were performed as a function of depth. In the near-surface simulations, assuming isotropic neutron fluence, the PKAs were initiated in random directions, including toward and parallel to the free surface. For both the near-surface and bulk cascades, the effect of E PKA and T on the defect production is similar. In both cases, the defect production increases with E PKA , but the temperature has minimal effect. However, the production and clustering of vacancies are higher for near-surface cascades, and they decrease with increasing depth. In contrast, the production and clustering of self-interstitial atoms are lower and increase with depth. Eventually, the production and clustering of both defect types approach bulk cascade-like behavior, and the depth at which this occurs increases with E PKA , but is independent of temperature.

36 MATERIALS SCIENCE↗

Electronic structure and magnetic properties of FeWO{sub 4} nanocrystals synthesized by the microwave-hydrothermal method

This communication reports that FeWO{sub 4} nanocrystals were successfully synthesized by the microwave-hydrothermal method at 443 K for 1 h. The structure and shape of these nanocrystals were characterized by X-ray diffraction, Rietveld refinement, and transmission electron microscopy. The experimental results and first principles calculations were combined to explain the electronic structure and magnetic properties. Experimental data were obtained by magnetization measurements for different applied magnetic fields. Theoretical calculations revealed that magnetic properties of FeWO{sub 4} nanocrystals can be assigned to two magnetic orderings with parallel or antiparallel spins in adjacent chains. These factors are crucial to understanding of competition between ferro- and antiferromagnetic behavior. Highlights: Black-Right-Pointing-Pointer Monophasic FeWO{sub 4} nanocrystals were synthesized by the microwave-hydrothermal method. Black-Right-Pointing-Pointer Rietveld refinement and clusters model for monoclinic structure Black-Right-Pointing-Pointer Magnetic properties of FeWO{sub 4} nanocrystals at different temperatures.

36 MATERIALS SCIENCE↗

Benchmark Theoretical Study of the π–π Binding Energy in the Benzene Dimer

We establish a new estimate for the binding energy between two benzene molecules in the parallel-displaced (PD) conformation by systematically converging (i) the intra- and intermolecular geometry at the minimum, (ii) the expansion of the orbital basis set, and (iii) the level of electron correlation. The calculations were performed at the second-order Møller–Plesset perturbation (MP2) and the coupled cluster including singles, doubles, and a perturbative estimate of triples replacement [CCSD(T)] levels of electronic structure theory. At both levels of theory, by including results corrected for basis set superposition error (BSSE), we have estimated the complete basis set (CBS) limit by employing the family of Dunning’s correlation-consistent polarized valence basis sets. The largest MP2 calculation was performed with the cc-pV6Z basis set (2772 basis functions), whereas the largest CCSD(T) calculation was with the cc-pV5Z basis set (1752 basis functions). The cluster geometries were optimized with basis sets up to quadruple-ζ quality, observing that both its intra- and intermolecular parts have practically converged with the triple-ζ quality sets. The use of converged geometries was found to play an important role for obtaining accurate estimates for the CBS limits. Our results demonstrate that the binding energies with the families of the plain (cc-pVnZ) and augmented (aug-cc-pVnZ) sets converge [within <0.01 kcal/mol for MP2 and <0.15 kcal/mol for CCSD(T)] to the same CBS limit. In addition, the average of the uncorrected and BSSE-corrected binding energies was found to converge to the same CBS limit much faster than either of the two constituents (uncorrected or BSSE-corrected binding energies). Due to the fact that the family of augmented basis sets (especially for the larger sets) causes serious linear dependency problems, the plain basis sets (for which no linear dependencies were found) are deemed as a more efficient and straightforward path for obtaining an accurate CBS limit. We considered extrapolations of the uncorrected (ΔE) and BSSE-corrected (ΔE cp ) binding energies, their average value (ΔE ave ), as well as the average of the latter over the plain and augmented sets (Δ~E ave ) with the cardinal number of the basis set n. Our best estimate of the CCSD(T)/CBS limit for the π–π binding energy in the PD benzene dimer is D e = -2.65 ± 0.02 kcal/mol. The best CCSD(T)/cc-pV5Z calculated value is -2.62 kcal/mol, just 0.03 kcal/mol away from the CBS limit. For comparison, the MP2/CBS limit estimate is -5.00 ± 0.01 kcal/mol, demonstrating a 90% overbinding with respect to CCSD(T). Finally, the spin-component-scaled (SCS) MP2 variant was found to closely reproduce the CCSD(T) results for each basis set, while scaled opposite spin (SOS) MP2 yielded results that are too low when compared to CCSD(T).

Environmental Molecular Sciences Laboratory↗

Adsorption of silver dimer on graphene - A DFT study

We performed a systematic density functional theory (DFT) study of the adsorption of silver dimer (Ag{sub 2}) on graphene using SIESTA (Spanish Initiative for Electronic Simulations with Thousands of Atoms) package, in the generalized gradient approximation (GGA). The adsorption energy, geometry, and charge transfer of Ag2-graphene system are calculated. The minimum energy configuration for a silver dimer is parallel to the graphene sheet with its two atoms directly above the centre of carbon-carbon bond. The negligible charge transfer between the dimer and the surface is also indicative of a weak bond. The methodology demonstrated in this paper may be applied to larger silver clusters on graphene sheet.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Optimization of Composite Cloud Service Processing with Virtual Machines

By leveraging virtual machine (VM) technology, we optimize cloud system performance based on refined resource allocation, in processing user requests with composite services. Our contribution is three-fold. (1) We devise a VM resource allocation scheme with a minimized processing overhead for task execution. (2) We comprehensively investigate the best-suited task scheduling policy with different design parameters. (3) We also explore the best-suited resource sharing scheme with adjusted divisible resource fractions on running tasks in terms of Proportional-share model (PSM), which can be split into absolute mode (called AAPSM) and relative mode (RAPSM). We implement a prototype system over a cluster environment deployed with 56 real VM instances, and summarized valuable experience from our evaluation. As the system runs in short supply, lightest workload first (LWF) is mostly recommended because it can minimize the overall response extension ratio (RER) for both sequential-mode tasks and parallel-mode tasks. In a competitive situation with over-commitment of resources, the best one is combining LWF with both AAPSM and RAPSM. It outperforms other solutions in the competitive situation, by 16 + % w.r.t. the worst-case response time and by 7.4 + % w.r.t. the fairness.

cloud resource allocation↗

Role of Many-Body Effects in Describing Low-Lying Excited States of pi-Conjugated Chromophores: High-Level Equation-of-Motion Coupled-Cluster Studies of Fused Porphyrin Systems

The unusual photophysical properties of the pi-conjugated chrompohores makes them potential building blocks of various molecular devices. In particular, significant narrowing of the HOMO-LUMO gaps can be observed as an effect of functionalization chromophores with polycyclic aromatic hydrocabrons (PAHs). In this paper we present equation-of-motion coupled cluster calculations for vertical excitation energies of several functionalized forms of porphyrins. The results of free-base porphyrin (FBP) clearly demonstrate significant differences between functionalization of FBP with one- (anthracene) and two-dimensional (coronene) structures. We also compare the EOMCC results with the experimentally available results for the anthracene fused zinc porphyrin. The impact of various-type correlation effects is illustrated on several benchmark models where the comparison with the experiment is possible. In particular, we demonstrate that for all excited states considered in this paper, all of them being dominated by single excitations, the inclusion of triply excited configurations is crucial for attaining qualitative agreement with the experiment. We also demonstrate the parallel performance of the most computationally intensive part of the completely renormalized EOMCCSD(T) approach (CR-EOMCCSD(T)) across 120,000 cores.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

First-principles assessment of hole transport in pure and Li-doped NiO

Alloying nickel oxide (NiO) with lithium oxide (Li 2 O) at high Li concentrations may reduce NiO's band gap and expand its use as a light absorber in photocatalytic and tandem dye-sensitized solar cell technologies. In this work, we evaluate the viability of this alloy as a p-type hole transport material. We use embedded cluster models, along with unrestricted Hartree–Fock and complete active space self-consistent field theories, to study the impact of alloying on polaronic transport of holes. Our calculated energy barrier for hole transfer in undoped NiO is in excellent agreement with the experimental value of ~0.1 eV. We predict that hole transport in NiO is anisotropic and mostly confined parallel to the (111) ferromagnetic planes. Applying the same model to Li-doped NiO indicates that isolated Li ions do not introduce free holes into NiO samples. However, free holes can be created in the homogeneous Li 0.125 Ni 0.875 O alloy, in which the Li concentration is very high. Our kinetic Monte Carlo calculations show that hole mobility in this alloy is lower than in undoped NiO. However, the additional free holes and the predicted lower band gap of Li 0.125 Ni 0.875 O should increase hole conductivity compared to NiO upon alloy formation. Therefore, Li 0.125 Ni 0.875 O alloys have potential for use as a hole transporter, as well as a sunlight absorber, in a variety of solar energy applications.

25 ENERGY STORAGE↗

Strong correlation of atomic thermal motion in the first coordination shell of a Cu-Zr metallic glass

We demonstrate a strong correlation of atomic thermal motions in the first coordination shell of Cu{sub 50}Zr{sub 50} metallic glass using molecular dynamics simulations, which explains directly the small thermal expansion coefficient calculated by the first maxima of pair correlation functions. The vibrational anisotropy in the glass is found to be even higher than in crystalline copper. The parallel-perpendicular anisotropy gradually decreases upon heating. The anisotropy in Zr-Zr is the strongest bonds among all the interatomic bonds, which is also very stable near the glass transition at 700 K. Structurally, the anisotropy can be correlated to Cu-centered (0 2 8 1) clusters.

36 MATERIALS SCIENCE↗