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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Accelerated Ion Irradiation for Emulation of In-reactor Radiation Damage

Reactor core materials in both fast reactors and LWRs granted life extension must withstand irradiation to high doses at high temperature. Ferritic-martensitic (F-M) alloys are attractive candidates for structural components and fuel cladding in fast and thermal reactors, and high chromium and high nickel-containing austenitic steels are potential replacement alloys for LWR core materials. To reach high doses, self-ion irradiation is conducted with simultaneous He injection into both F-M and austenitic alloys, accompanied by reactor irradiations conducted in the BOR-60 fast reactor to assess the capability of ion irradiation to emulate the evolution of microstructure and mechanical properties in reactor. Computational models for defect cluster evolution are being developed and benchmarked against experimental data to ultimately provide predictive capability for the response of both microstructure (loops, voids, precipitates, etc.), and mechanical properties (hardening, ductility, slip behavior) to irradiation. A research program is aimed at understanding how to emulate neutron irradiation using ion irradiation. Results to date have been focused on microstructure and properties of ion irradiated alloys T91, 800H and Fe21Ce32Ni. Data from single ion irradiations are thus far in good agreement with that expected based on previous ion and neutron irradiation data. Dual ion irradiations and neutron irradiated samples are being evaluated and these will be the focus of future work. (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2021

Workflows Community Summit: Tightening the Integration between Computing Facilities and Scientific Workflows

Scientific workflows are used almost universally across science domains for solving complex and largescale computing and data analysis problems. The importance of workflows is highlighted by the fact that they have underpinned some of the most significant discoveries of the past decades. Many of these workflows have significant computational, storage, and communication demands, and thus must execute on a range of large-scale computer systems, from local clusters to public clouds and upcoming exascale HPC platforms. Managing these executions is often a significant undertaking, requiring a sophisticated and versatile software infrastructure. Historically, infrastructures for workflow execution consisted of complex, integrated systems, developed in-house by workflow practitioners with strong dependencies on a range of legacy technologies—even including sets of ad hoc scripts. Due to the increasing need to support workflows, dedicated workflow systems were developed to provide abstractions for creating, executing, and adapting workflows conveniently and efficiently while ensuring portability. While these efforts are all worthwhile individually, there are now hundreds of independent workflow systems. These workflow systems are created and used by thousands of researchers and developers, leading to a rapidly growing corpus of workflows research publications. The resulting workflow system technology landscape is fragmented, which may present significant barriers for future workflow users due to many seemingly comparable, yet usually mutually incompatible, systems that exist. In order to tackle some of the challenges described above, the DOE-funded ExaWorks and NSF-funded WorkflowsRI projects have organized in 2021 a series of events entitled the “Workflows Community Summit”. The third edition of the “Workflows Community Summit” explored workflows challenges and opportunities from the perspective of computing centers and facilities. This third summit builds on two prior summits (https://workflowsri.org/summits) that (i) established a high level vision for workflows research; and (ii) explored technical approaches for realizing that vision. The third summit brought together a small group of facilities representatives with the aim to understand how workflows are currently being used at each facility, how facilities would like to interact with workflow developers and users, how workflows fit with facility roadmaps, and what opportunities there are for tighter integration between facilities and workflows. This report documents and organizes the wealth of information provided by the participants before, during, and after the summit.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Strong enhancement of surface diffusion by nonlinear surface acoustic waves

The phenomenon of acoustic activation of surface diffusion is investigated in a combined computational and experimental study. The ability of pulsed laser-generated surface acoustic waves (SAWs) to enhance the mobility of small atomic clusters is demonstrated by directly tracking, with fluorescence microscopy, individual Au 8 clusters moving on a (111) silicon substrate. In this work, a 19-fold increase in the effective diffusion coefficient is measured in room temperature experiments in the presence of SAWs generated by nanosecond pulse laser irradiation at a 100 Hz repetition rate. A strong enhancement of cluster mobility by SAWs is also observed in large-scale molecular dynamics simulations of surface diffusion of small atomic clusters. The analysis of the computational results demonstrates that the nonlinear sharpening of SAWs and the corresponding enrichment of the SAW spectra by high frequency harmonics which are capable of dynamic coupling to the cluster vibrations are responsible for the efficient acoustic activation of surface mobility in the simulations. The increase in the effective diffusion coefficient is proportional to the number of the SAW pulses passing through the diffusion region per unit time and a dramatic 4500-fold diffusion enhancement (corresponds to an equivalent temperature increase by ~10 3 K ) is predicted in the simulations for 15 GHz SAWs. The ability of SAWs to affect atomic-level surface processes has far-reaching implications for the design of new techniques where the acoustic energy serves as an effective substitution for thermal activation in applications where heating must be avoided or rapid switching of surface conditions is required.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

An Automated Thermochemistry Protocol Based on Explicitly Correlated Coupled-Cluster Theory: The Methyl and Ethyl Peroxy Families

An automated computational thermochemistry protocol based on explicitly correlated coupled-cluster theory was determined to produce highly accurate enthalpies of formation and atomization energies for small- to medium-sized molecular species (3–12 atoms). Each possible source of error was carefully examined, and the sizes of contributions to the total atomization enthalpies were used to generate uncertainty estimates. The protocol was first used to generate total atomization enthalpies for a family of four molecular species exhibiting a variety of charges, multiplicities, and electronic ground states. The new protocol was demonstrated to be in good agreement with the Active Thermochemical Tables database for the four species: the methyl peroxy radical, methoxyoxoniumylidene (methyl peroxy cation), methyl peroxy anion, and methyl hydroperoxide. Updating the Active Thermochemical Tables to include those results yielded significantly improved accuracy for the formation enthalpies of those species. The derived protocol was then used to predict formation enthalpies for the larger ethyl peroxy family of species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Determining Catalytically Relevant Surfaces through Coverage-Dependent Lattice Gas Models: Carbon Adsorption on Fe(100)

Here, we have quantified the C–C lateral interactions on Fe(100) using a density functional theory (DFT)-parameterized lattice gas cluster expansion (LG CE) model trained using 265 unique configurations spanning a C coverage from 0 to 1 monolayer (ML). Our LG CE model shows high predictive accuracy with a leave-multiple-out cross-validation score of 10.2 and 16.6 meV/site for systems with and without the top two layers of Fe atoms fixed, respectively. Electronic ground-state structures identified from the lattice gas model (including the structures at 0 and 1 monolayers) were further used to generate ab initio phase diagrams under a range of temperatures and pressures. At low temperatures (<400 K), we found that the 1.0 monolayer structure is dominant, whereas at higher temperatures (>500 K), the 0.88 ML structure is most likely to form on the Fe surface. Interestingly, our model identified a c (2 × 2) ordered structure at 1/2 ML, which correlates well with previous DFT studies for carbon adsorption on iron surfaces and matches with the experimentally observed low-energy electron diffraction structure. Overall, the DFT-parameterized energies for the C/Fe system including effects of coverage and configurational space can further help in developing multiscale models for various heterogeneous reactions involving C–C and C–Fe interactions.

08 HYDROGEN↗
DOE OSTI2022

Folding Coarse-Grained Oligomer Models with PyRosetta

Non-biological foldamers are a promising class of macromolecules that share similarities to classical biopolymers such as proteins and nucleic acids. Currently, designing novel foldamers is a non-trivial process, often involving many iterations of trial synthesis and characterization until folded structures are observed. In this work, we aim to tackle these foldamer design challenges using computational modeling techniques. We developed CG PyRosetta, an extension to the popular protein folding python package, PyRosetta, which introduces coarse-grained (CG) residues into PyRosetta, enabling the folding of toy CG foldamer models. Although these models are simplified, they can help explore overarching physical hypotheses about how oligomers can form. Through systematic variation of CG parameters in these models, we can investigate various folding hypotheses at the CG scale to inform the design process of new foldamer chemistries. In this study, we demonstrate CG PyRosetta’s ability to identify minimum energy structures with a diverse structural search over a range of simple models, as well as two hypothesis-driven parameter scans investigating the effects of side-chain size and internal backbone angle on secondary structures. We are able to identify several types of secondary structures from single- and double-helices to sheet-like and knot-like structures. Here, we show how side-chain size and backbone bond angle both play an important role in the structure and energetics of these toy models. Optimal side-chain sizes promote favorable packing of side chains, while specific backbone bond angles influence the specific helix type found in folded structures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units

Atomic structure prediction and associated property calculations are the bedrock of chemical physics. Since high-fidelity ab initio modeling techniques for computing the structure and properties can be prohibitively expensive, this motivates the development of machine-learning (ML) models that make these predictions more efficiently. Training graph neural networks over large atomistic databases introduces unique computational challenges such as the need to process millions of small graphs with variable size and support communication patterns that are distinct from learning over large graphs such as social networks. We demonstrate a novel hardware-software co-design approach to scale up the training of atomistic graph neural networks (GNN) for structure and property prediction. First, to eliminate redundant computation and memory associated with alternative padding techniques and to improve throughput via minimizing communication, we formulate the effective coalescing of the batches of variable-size atomistic graphs as the bin packing problem and introduce a hardware-agnostic algorithm to pack these batches. In addition, we propose hardware-specific optimizations including a planner and vectorization for the gather-scatter operations targeted for Graphcore’s Intelligence Processing Unit (IPU), as well as model-specific optimizations such as merged communication collectives and optimized softplus. Putting these all together, we demonstrate the effectiveness of the proposed co-design approach by providing an implementation of a well-established atomistic GNN on the Graphcore IPUs. We evaluate the training performance on multiple atomistic graph databases with varying degrees of graph counts, sizes and sparsity. Here, we demonstrate that such a co-design approach can reduce the training time of atomistic GNNs and can improve the performance by up to 1.5× compared to the baseline implementation of the model on the IPUs. Additionally, we compare our IPU implementation with a Nvidia GPU-based implementation and show that our atomistic GNN implementation on the IPUs can run 1.8× faster on average compared to the execution time on the GPUs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

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↗
DOE OSTI2015

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↗
DOE OSTI2014

Oak Ridge Institutional Cluster Autotune Test Drive Report

The Oak Ridge Institutional Cluster (OIC) provides general purpose computational resources for the ORNL staff to run computation heavy jobs that are larger than desktop applications but do not quite require the scale and power of the Oak Ridge Leadership Computing Facility (OLCF). This report details the efforts made and conclusions derived in performing a short test drive of the cluster resources on Phase 5 of the OIC. EnergyPlus was used in the analysis as a candidate user program and the overall software environment was evaluated against anticipated challenges experienced with resources such as the shared memory-Nautilus (JICS) and Titan (OLCF). The OIC performed within reason and was found to be acceptable in the context of running EnergyPlus simulations. The number of cores per node and the availability of scratch space per node allow non-traditional desktop focused applications to leverage parallel ensemble execution. Although only individual runs of EnergyPlus were executed, the software environment on the OIC appeared suitable to run ensemble simulations with some modifications to the Autotune workflow. From a standpoint of general usability, the system supports common Linux libraries, compilers, standard job scheduling software (Torque/Moab), and the OpenMPI library (the only MPI library) for MPI communications. The file system is a Panasas file system which literature indicates to be an efficient file system.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

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.↗
DOE OSTI2016

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.↗
DOE OSTI2024

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↗
DOE OSTI2018

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↗
DOE OSTI2021

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↗