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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Gapped-filtering for efficient Chebyshev expansion of the density projection operator

In this paper, we develop the gapped-filtering method, whereby a short Chebyshev expansion accurately represents the density-matrix operator. The method optimizes the Chebyshev coefficients to give the correct density matrix at all energies except within the gapped region where there are no eigenstates. Gapped filtering reduces the number of required terms in the Chebyshev expansion compared to traditional expansion methods, as long as one knows or can determine efficiently the HOMO and LUMO positions. The reduction is especially noticeable (factors of 2-3) when high accuracy is sought. To exemplify the method, we use gapped-filtering to increase the efficiency of stochastic-GW calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Achieving performance portability in Gaussian basis set density functional theory on accelerator based architectures in NWChemEx

The numerical integration of the exchange–correlation (XC) potential is one of the primary computational bottlenecks in Gaussian basis set Kohn–Sham density functional theory (KS-DFT). To achieve optimal performance and accuracy, care must be taken in this numerical integration to preserve local sparsity as to allow for near linear weak scaling with system size. This leads to an integration scheme with several performance critical kernels which must be hand optimized for each architecture of interest. As the set of available accelerator hardware goes more diverse, a key challenge for developers of KS-DFT software is to maintain performance portability across a wide range of computational architectures. In this article, we examine a modular software design pattern which decouples the implementation details of performance critical kernels from the expression of high-level algorithmic workflows in a device-agnostic language such as C++; thus allowing for developers to target existing and emerging accelerator hardware within a single code base. We consider the efficacy of such a design pattern in the numerical integration of the XC potential by demonstrating its ability to achieve performance portability across a set of accelerator architectures which are representative of those on current and future U.S. Department of Energy Leadership Computing Facilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Parsimonious Potential Energy Surface Expansions Using Dictionary Learning with Multipass Greedy Selection

Potential energy surfaces fit with basis set expansions have been shown to provide accurate representations of electronic energies and have enabled a variety of high-accuracy dynamics, kinetics, and spectroscopy applications. The number of terms in these expansions scales poorly with system size, a drawback that challenges their use for systems with more than similar to 10 atoms. A solution is presented here using dictionary learning. Subsets of the full set of conventional basis functions are optimized using a newly developed multipass greedy regression method inspired by forward and backward selection methods from the statistics, signal processing, and machine learning literatures. Here, the optimized representations have accuracies comparable to the full set but are 1 or more orders of magnitude smaller, and notably, the number of terms in the optimized multipass greedy expansions scales approximately linearly with the number of atoms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Metal–Organic Framework–Polyacrylonitrile Composite Beads for Xenon Capture

Mechanically robust forms of HKUST-1 metal-organic frameworks (MOFs) were fabricated by embedding the MOF in a passive polyacrylonitrile (PAN) matrix at different MOF loadings of 10–90 mass%. Here, the PAN is highly porous and acts as a scaffold that holds the active MOF adsorbent in place for Xe capture. Data presented herein show that the PAN matrix does not notably interfere with the Xe capture process where the Xe capacities scale somewhat linearly with the increase in MOF loading in the composites. Radiation testing of the composites under a gamma flux revealed that they are highly tolerant to these types of radiation fields.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Adaptive finite differencing in high accuracy electronic structure calculations

Abstract A multi-order Adaptive Finite Differencing (AFD) method is developed for the kinetic energy operator in real-space, grid-based electronic structure codes. It uses atomic pseudo orbitals produced by the corresponding pseudopotential codes to optimize the standard finite difference (SFD) operators for improved precision. Results are presented for a variety of test systems and Bravais lattice types, including the well-known Δ test for 71 elements in the periodic table, the Mott insulator NiO, and borax decahydrate, which contains covalent, ionic, and hydrogen bonds. The tests show that an 8th-order AFD operator leads to the same average Δ value as that achieved by plane-wave codes and is typically far more accurate and has a much lower computational cost than a 12th-order SFD operator. The scalability of real-space electronic calculations is demonstrated for a 2016-atom NiO cell, for which the computational time decreases nearly linearly when scaled from 18 to 144 CPU-GPU nodes.

Briggs, E. L. (ORCID:0000000343983492)↗
DOE OSTI2022

Critical role of orbital hybridization in the Dzyaloshinskii-Moriya interaction of magnetic interfaces

Dzyaloshinskii-Moriya interaction (DMI), an interfacial spin-orbit coupling (ISOC)-related effect, has become foundational for spintronic research and magnetic memory and computing technologies. However, the underlying mechanism of DMI, including the quantitative role of ISOC, has remained a long-standing unsettled problem due to the great challenge in quantifying and widely tuning ISOC strength in a strong DMI material system. Here, we find that DMI, ISOC, and orbital hybridization at the model magnetic interface Au 1-x Pt x /Co can be quantified and tuned significantly at the same time through the composition of the Au 1-x Pt x , without varying the bulk SOC and the electronegativity. From this ability, we establish that the widespread expectation that DMI should scale in linear proportion to ISOC breaks down at the Au 1-x Pt x /Co interface where degree of orbital hybridization varies with the Au 1-x Pt x composition and that the unexpected DMI behaviors can be understood well by the critical role of orbital hybridization. Our study provides a quantitative frame for comprehensively understanding interfacial DMI of various magnetic interfaces and establishes orbital hybridization as a new degree of freedom for controlling DMI in high-performance chiral domain wall/skyrmion devices and ultrafast magnetic tunnel junctions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Electrocatalytic nitrate reduction on rhodium sulfide compared to Pt and Rh in the presence of chloride

Chloride poisoning is a serious problem for the electrocatalytic reduction of aqueous nitrate (NO 3 – ) and improved electrocatalysts are needed. Here we study the electrocatalytic activity of rhodium sulfide supported on carbon (Rh x S y /C) for the reduction of nitrate and compare it against Pt/C and Rh/C in the presence of chloride. Between 0.05–0.15 V vs. RHE, Rh x S y /C has a steady-state nitrate reduction current density in 1 M H 2 SO 4 + 1 M NaNO 3 that is 1.6–5.6 times greater than Rh/C (the most active metal electrocatalyst) and 10–24 times greater than Pt/C. Current densities are decreased by 37% for Rh x S y /C, 62% for Rh/C, and 40% for Pt/C at 0.1 V vs. RHE in the presence of 1 mM chloride. The decrease in nitrate reduction activity for Pt, Rh, and Rh x S y is due to the competitive adsorption of chloride and nitrate on the surface. Density functional theory (DFT) modeling predicts that chloride poisoning will persistently inhibit nitrate reduction on metals due to linear adsorbate scaling relations between nitrate and chloride. DFT calculations and microkinetic modeling of our experimental measurements predict that nitrate converts to nitrite via an H-assisted dissociation mechanism on Pt and direct nitrate dissociation on Rh and Rh x S y . Pristine Rh x S y (i.e., Rh 3 S 4 , Rh 2 S 3 , and Rh 17 S 15 ) terraces are predicted to be inactive toward nitrate reduction. In contrast, sulfur vacancies in Rh 3 S 4 terraces are predicted to be active for nitrate reduction, but also bind chloride strongly. Furthermore, sulfur-defected Rh 3 S 4 rationalize the experimentally observed high activity but moderate chloride poison-resistance of Rh x S y /C for nitrate reduction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

pyRMG: A framework for high-throughput, large-cell DFT calculations on supercomputers

Exascale computing delivers the raw power to simulate ever larger and more chemically realistic systems, but realizing this potential requires codes that can efficiently use thousands of processors. Our real-space multigrid (RMG) density functional theory (DFT) code’s grid-decomposition approach scales nearly linearly with the number of graphics processing units (GPUs), even for simulations exceeding thousands of atoms. This scalability makes RMG a compelling tool for high-throughput DFT studies of materials that would otherwise be bottlenecked in other codes (for example, by global fast Fourier transforms in plane-wave DFT). However, the limited workflow infrastructure for RMG has thus far constrained its adoption to a small user community. In this work, we present pyRMG, a Python package designed to streamline the setup and execution of RMG DFT calculations. Built on the pymatgen and ASE (Atomic Simulation Environment) computational materials science Python packages, pyRMG automates input generation and convergence checking, and it integrates with modern job schedulers (e.g., Flux) on leadership-class platforms such as Frontier and Perlmutter. Here, we demonstrate pyRMG for a high-throughput study of strain effects in 2D 2L-Bi 2 Se 3 /2L-NbSe 2 heterostructures, which offers chemical insights into this system and shows that RMG-based workflows can converge with limited user intervention.

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

Analysing the effects of heating and gas puffing in Proto-MPEX helicon and auxiliary heated plasmas

The Material Plasma Exposure Experiment (MPEX) is being constructed at Oak Ridge National Laboratory to investigate critical fusion reactor issues, such as plasma–material interactions (PMIs) under reactor-relevant conditions and time scales. The linear device Proto-MPEX was used as a test bed to address anticipated research and development issues associated with heating scenarios and establish the physics basis for MPEX. The SOLPS-ITER code suite has been applied to understand plasma and neutral transport in Proto-MPEX and to increase confidence in predictive simulations for MPEX. Coupling between COMSOL and SOLPS is performed to implement a 2D electron heating profile of the helicon source. The simulations show reasonable agreement with the experimental data for plasma with helicon and auxiliary electron cyclotron heating (ECH). Both Bohm and constant diffusion (D$_\perp$: 0.5 m 2 s –1 and $\chi_\perp$: 1 m 2 s –1 ) simulations show similar levels of agreement with respect to the sparse experimental data available, assuming a few per cent impurity concentration. ECH significantly increases the target electron temperature, however, the target electron density is reduced compared to helicon-only heated plasmas due to an increase in flow velocity and radial losses. The simulations show that further increasing the ECH power results in an increase in the target electron density due to increased recycling flux and ionization. The results indicate that ECH significantly enhances the target heat flux, with ECH power of 50 kW increasing the target heat flux from 0.4 to 17 MW m –2 . It is found that a small amount of gas puffing (GP) near the target plate can further increase the target heat fluxes at the higher ECH power cases, but the target heat flux is reduced at higher GP conditions due to a significant reduction in electron temperature via radiation. ECH and GP scenarios can generate a higher target flux, facilitating improved PMI studies with more reactor-relevant plasma conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

nf-core/proteinfamilies: a scalable pipeline for the generation of protein families

The growth of metagenomics-derived amino acid sequence data has transformed our understanding of protein function, microbial diversity, and evolutionary relationships. However, the vast majority of these proteins remain functionally uncharacterized. Grouping the millions of such uncharacterized sequences with the few experimentally characterized ones allows the transfer of annotations, while the inspection of conserved residues with multiple sequence alignments can provide clues to function, even in the absence of existing functional information. To address the challenges associated with this data surge and the need to group sequences, we present a scalable, open-source, parametrizable Nextflow pipeline (nf-core/proteinfamilies) that generates nascent protein families or assigns new proteins to existing families. The computational benchmarks demonstrated that resource usage scales approximately linearly with input size, and the biological benchmarks showed that the generated protein families closely resemble manually curated families in widely used databases.

Nextflow↗
DOE OSTI2026

Linear complexity

We present factorization and solution phases for a new linear complexity direct solver designed for concurrent batch operations on fine-grained parallel architectures, for matrices amenable to hierarchical representation. We focus on the strong-admissibility-based $\mathscr{H}^{2}$ format, where strong recursive skeletonization factorization compresses remote interactions. We build upon previous implementations of $\mathscr{H}^{2}$ matrix construction for efficient factorization and solution algorithm design, which are illustrated graphically in stepwise detail. The algorithms are ‘blackbox’ in the sense that the only inputs are the matrix and right-hand side, without analytical or geometrical information about the origin of the system. We demonstrate linear complexity scaling in both time and memory on four representative families of dense matrices up to one million in size. Parallel scaling up to 16 threads is enabled by a multi-level matrix graph coloring and avoidance of dynamic memory allocations thanks to prefix-sum memory management. An experimental backward error analysis is included. We break down the timings of different phases, identify phases that are memory-bandwidth limited, and discuss alternatives for phases that may be sensitive to the trend to employ lower precisions for performance.

Boukaram, Wajih↗
DOE OSTI2021

Hidden strange metallic state in underdoped electron-doped cuprates

The low-temperature linear-in-T resistivity of “strange metals,” such as the metallic state of the cuprate high-temperature superconductors, has long been thought to be associated with a quantum critical point. However, recent transport studies of the cuprates have found this behavior persists over a finite range of overdoping. Here, in this work, we report magnetoresistance and Hall effect results for electron-doped films of the cuprate superconductor La 2-x ⁢ Ce x CuO 4 (LCCO) for temperatures from 0.7 to 45 K and magnetic fields up to 65 T. For x = 0.12 and 0.13, just below the Fermi surface reconstruction (FSR) at x = 0.14, the normal state in-plane resistivity exhibits a well-known upturn at low temperature. Our new results show that this resistivity upturn is eliminated at high magnetic field and the resistivity becomes linear-in-temperature from ~40 K down to 0.7 K. The magnitude of the linear coefficient scales with Tc and doping, as found previously for dopings above the FSR. This striking observation suggests that the strange metal is not confined to a single “critical point” in the phase diagram, but rather is a robust universal feature of the metallic ground state of the cuprates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Efficient numerical method for evaluating normal and anomalous time-domain equilibrium Green's functions in inhomogeneous systems

In this work we develop EPOCH (equilibrium propagator by orthogonal polynomial chain), a computationally efficient method to calculate the time-dependent equilibrium Green's functions, including the anomalous Green's functions of superconductors, to capture the time evolution in large inhomogeneous systems. The EPOCH method generalizes the Chebyshev wave-packet propagation method from quantum chemistry and efficiently incorporates the Fermi-Dirac statistics that is needed for equilibrium quantum condensed matter systems. The computational cost of EPOCH scales only linearly in the system degrees of freedom, generating an extremely efficient algorithm also for very large systems. We demonstrate the power of the EPOCH method by calculating the time evolution of an excitation near a superconductor–normal metal interface in two and three dimensions, capturing transmission as well as normal and Andreev reflections.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Kinetic study of strong shock waves in fully ionized plasmas

Fully kinetic simulations are used in this work to study strong shock waves in fully ionized plasmas for charge state 𝑍 ranging from 1 to 18. The ion stress tensor amplitude agrees well with classical predictions within the compression layer; however, its spatial structure is noticeably shaped by nonlocal transport effects. The electron stress tensor remains significantly smaller than that of the ions for all values of 𝑍 considered. Ion overheating in the compression layer is observed to scale approximately linearly with 𝑍. Both findings diverge from hydrodynamic models based on classical electron stress formulations. In conclusion, the electrons exhibit strong nonlocal behavior in the compression layer, with Knudsen numbers approaching unity for 𝑍 ≥ 6.

Physics - Plasma physics↗
DOE OSTI2025

Tailoring spectral properties for entangled photon generation

The linear intensity scaling of entangled two-photon absorption (ETPA) offers a fundamental mechanism to enable nonlinear optical spectroscopy and microscopy under a substantially lower excitation power than is currently feasible. However, the long data acquisition time and low signal-to-noise ratio in reported ETPA-based spectroscopic and microscopic studies prevent its widespread application. To gain the full potential of this novel quantum light approach, it is essential to optimize entangled photon generation for significantly enhanced ETPA responses. Here, we report a new quantum light source by combining entangled photon generation with free-space femtosecond pump-pulse shaping. Here, through measurements of singles and coincidence counts by varying the patterns applied to a spatial light modulator to control the spectral widths of the pump pulses, we reveal strong dependence of the singles and coincidence count rates as well as their ratios on the spectral widths of pump pulses. An optimal spectral width for the highest ratios between the coincidence photon and the signal or idler photon count rates is also determined. Identification of such optimal spectral widths for entangled photon generation in the presence of postgeneration spectral selection makes this quantum light source a promising choice for ETPA-based spectroscopy and imaging.

Photon pairs & parametric down-conversion↗
DOE OSTI2023

TomocuPy – efficient GPU-based tomographic reconstruction with asynchronous data processing

Fast 3D data analysis and steering of a tomographic experiment by changing environmental conditions or acquisition parameters require fast, close to real-time, 3D reconstruction of large data volumes. Here a performance-optimized TomocuPy package is presented as a GPU alternative to the commonly used central processing unit (CPU) based TomoPy package for tomographic reconstruction. TomocuPy utilizes modern hardware capabilities to organize a 3D asynchronous reconstruction involving parallel read/write operations with storage drives, CPU–GPU data transfers, and GPU computations. In the asynchronous reconstruction, all the operations are timely overlapped to almost fully hide all data management time. Since most cameras work with less than 16-bit digital output, the memory usage and processing speed are furthermore optimized by using 16-bit floating-point arithmetic. As a result, 3D reconstruction with TomocuPy became 20–30 times faster than its multi-threaded CPU equivalent. Full reconstruction (including read/write operations and methods initialization) of a 2048 3 tomographic volume takes less than 7 s on a single Nvidia Tesla A100 and PCIe 4.0 NVMe SSD, and scales almost linearly increasing the data size. To simplify operation at synchrotron beamlines, TomocuPy provides an easy-to-use command-line interface. Efficacy of the package was demonstrated during a tomographic experiment on gas-hydrate formation in porous samples, where a steering option was implemented as a lens-changing mechanism for zooming to regions of interest.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Sparse Approximate Multifrontal Factorization with Butterfly Compression for High-Frequency Wave Equations

In this work, we present a fast and approximate multifrontal solver for large-scale sparse linear systems arising from finite-difference, finite-volume or finite-element discretization of high-frequency wave equations. The proposed solver leverages the butterfly algorithm and its hierarchical matrix extension for compressing and factorizing large frontal matrices via graph-distance guided entry evaluation or randomized matrix-vector multiplication-based schemes. Complexity analysis and numerical experiments demonstrate $\mathcal{O}(N\log^2 N)$ computation and $\mathcal{O}(N)$ memory complexity when applied to an $N\times N$ sparse system arising from 3D high-frequency Helmholtz and Maxwell problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Optimal Experimental Design for Inverse Problems in the Presence of Observation Correlations

Optimal experimental design (OED) is the general formalism of sensor placement and decisions on the data collection strategy for engineered or natural experiments. This problem is prevalent in many critical fields such as battery design, numerical weather prediction, geosciences, environmental and urban studies. State-of-the-art computational methods for experimental design do not accommodate correlation structure in observational errors produced by many expensive-to-operate devices such as X-ray machines, radars, and satellites. Discarding evident data correlations leads to biased results, higher expenses, and waste of valuable resources. We present a general formulation of the OED formalism for model-constrained large-scale Bayesian linear inverse problems, where measurement errors are generally correlated. The proposed approach utilizes the Hadamard product of matrices to formulate the weighted-likelihood, and is valid for both finite as well as infinite-dimensional Bayesian inverse problems. Extensive numerical experiments are carried out for empirical verification of the proposed approach using an advection-diffusion model, where the objective is to optimally place a small set of sensors, under a limited budget, to predict the concentration of a contaminant in a closed and bounded domain.

Correlated observations↗