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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

In Quest of a Ferromagnetic Insulator: Structure-Controlled Magnetism in Mg–Ti–O Thin Films

Ferromagnetic insulator thin films can convey information by spin waves, avoiding charge displacement and Eddy current losses. The sparsity of high-temperature insulating ferromagnetic materials hinders the development of spin-wave-based devices. Stoichiometric magnesium titanate, MgTiO 3 , has an electronic-energy-band structure in which all bands are either full or empty, being a paramagnetic insulator. The MgTiO 3 ilmenite consists of ordered octahedra and a cation network in which one-third of the octahedra are vacant, one-third host magnesium, and one-third titanium. By giving up these characteristics, a rich variety of different magnetic structures can be formed. Our experiments and electronic-energy-band-structure computations show that the magnetic and electric properties of Mg–Ti–O films can drastically be changed and controlled by Mg- and Ti-cation arrangement and abundancy in the octahedra. Insulating titanium- and semiconducting magnesium-rich films exhibited reversible magnetization up to elevated temperatures. The presence and origin of the insulating phase with reversible magnetization, assigned to ferromagnetic ordering, is not apparent. Here, the expectation, based on the well-established rules set by Goodenough and Kanamori, is paramagnetic or antiferromagnetic ordering. We show that ferro- and paramagnetic phases, possessing the same stoichiometry, can be obtained by merely rearranging the cations, thus allowing defect-free interfaces in multilayer structures.

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

Observation of Conformational Simplification upon N-methylation on Amino Acid Iodide Clusters

This work reports a surprising observation that methylation of glycine-iodide cluster leads to less conformations and spectroscopic simplicity. We used cryogenic “iodide-tagging” negative ion photoelectron spectroscopy (NIPES) to probe specific binding sites of three N-methylated glycine derivatives, i.e., N-methylglycine (sarcosine, Sar), N,N-dimethylglycine (Dmg), and N,N,N-trimethylglycine (glycine betaine, Bet). NIPES reveals a progressive spectral simplification of the iodide clusters with increasing methylation due to the presence of fewer contributing structures, a reduction in the number of NH and OH hydrogen bond donating sites, and an increase in the basicity of the amine. Low energy conformers and tautomers of each cluster are computationally identified, and those observed in the experiments are assigned based on excellent agreement between the NIPE spectra and theoretical simulations. Clusters with zwitterionic structures for Gly, Sar, and Dmg are found to be less stable than their canonical forms and do not contribute to the observed spectra. This work demonstrates the power of “iodide-tagging” NIPES in probing conformational and tautomeric structures of amino acid-iodide clusters and provides a molecular level understanding on the effect of methyl substitution on the active binding sites of amino acids.

Cao, Wenjin↗
DOE OSTI2018

Spin–Orbit Interactions Greatly Accelerate Nonradiative Dynamics in Lead Halide Perovskites

In this study, we study the role of spin–orbit coupling (SOC) in nonradiative relaxation of hot electrons and holes in methylammonium lead perovskite, MAPbI 3 . For this purpose, we have developed the nonadiabatic molecular dynamics method with two-component spinor wave functions that are solutions of the relativistic Kohn–Sham (KS) equations. We find that SOC enhances contributions of Pb(p x ) and Pb(p y ) orbitals to the conduction and valence bands. As a result, the KS orbitals become more sensitive to nuclear motions, leading to the increased nonadiabatic couplings. Consequently, SOC greatly speeds up the electron and hole relaxation, making the computed relaxation time scales consistent with available experiments. Furthermore, we suggest that the fast hot carrier relaxation facilitated by the SOC allows rapid transition into the long-lived triplet state that extends charge-carrier lifetime and helps achieve high-efficiency perovskite solar cells.

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

The Structure of Boron Monoxide

Boron monoxide (BO), prepared by the thermal condensation of tetrahydroxydiboron, was first reported in 1955; however, its structure could not be determined. With the recent attention on boron-based two-dimensional materials, such as borophene and hexagonal boron nitride, there is renewed interest in BO. A large number of stable BO structures have been computationally identified, but none are supported by experiments. The consensus is that the material likely forms a boroxine-based two-dimensional material. Herein, we apply advanced 11 B NMR experiments to determine the relative orientations of B(B)O 2 centers in BO. We find that the material is composed of D 2h -symmetric O 2 B–BO 2 units that organize to form larger B 4 O 2 rings. Further, powder diffraction experiments additionally reveal that these units organize to form two-dimensional layers with a random stacking pattern. This observation is in agreement with earlier density functional theory (DFT) studies that showed B 4 O 2 -based structures to be the most stable.

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

Storm Surge Modeling as an Application of Local Time-Stepping in MPAS-Ocean

This paper presents the first practical application of local time-stepping (LTS) schemes in the Model for Prediction Across Scales-Ocean (MPAS-O). We use LTS schemes in a single-layer, global ocean model that predicts the storm surge around the eastern coast of the United States during Hurricane Sandy. The variable-resolution meshes used are of unprecedentedly high resolution in MPAS-O, containing cells as small as 125 m wide in Delaware Bay. It is shown that a particular, third-order LTS scheme (LTS3) produces sea-surface height solutions that are of comparable quality to solutions produced by the classical four-stage, fourth-order Runge-Kutta method (RK4) with a uniform time step on the same meshes. Furthermore, LTS3 is up to 35% faster in the best cases considered, where the number of cells using the coarse time-step relative to those using the fine time-step is as low as 1:1. This shows that LTS schemes are viable for use in MPAS-O with the added benefit of substantially less computational cost. The results of these performance experiments inform us of the requirements for efficient mesh design and configuration of LTS regions for LTS schemes. In particular, we see that for LTS to be efficient on a given mesh, it is important to have enough cells using the coarse time-step relative to those using the fine time-step, typically at least 1:5 to see an increase in performance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Inversion symmetry and bulk Rashba effect in methylammonium lead iodide perovskite single crystals

Methylammonium lead iodide perovskite (MAPbI 3 ) exhibits long charge carrier lifetimes that are linked to its high efficiency in solar cells. Yet, the mechanisms governing these unusual carrier dynamics are not completely understood. A leading hypothesis-disproved in this work-is that a large, static bulk Rashba effect slows down carrier recombination. Here, using second harmonic generation rotational anisotropy measurements on MAPbI 3 crystals, we demonstrate that the bulk structure of tetragonal MAPbI 3 is centrosymmetric with I4/ mcm space group. Our calculations show that a significant Rashba splitting in the bandstructure requires a non-centrosymmetric lead iodide framework, and that incorrect structural relaxations are responsible for the previously predicted large Rashba effect. The small Rashba splitting allows us to compute effective masses in excellent agreement with experiment. Here, our findings rule out the presence of a large static Rashba effect in bulk MAPbI 3 , and our measurements find no evidence of dynamic Rashba effects.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ising meson spectroscopy on a noisy digital quantum simulator

Abstract Quantum simulation has the potential to be an indispensable technique for the investigation of non-perturbative phenomena in strongly-interacting quantum field theories (QFTs). In the modern quantum era, with Noisy Intermediate Scale Quantum (NISQ) simulators widely available and larger-scale quantum machines on the horizon, it is natural to ask: what non-perturbative QFT problems can be solved with the existing quantum hardware? We show that existing noisy quantum machines can be used to analyze the energy spectrum of several strongly-interacting 1+1D QFTs, which exhibit non-perturbative effects like ‘quark confinement’ and ‘false vacuum decay’. We perform quench experiments on IBM’s quantum simulators to compute the energy spectrum of 1+1D quantum Ising model with a longitudinal field. Our results demonstrate that digital quantum simulation in the NISQ era has the potential to be a viable alternative to numerical techniques such as density matrix renormalization group or the truncated conformal space methods for analyzing QFTs.

Science & Technology - Other Topics↗
DOE OSTI2023

Boundaries of quantum supremacy via random circuit sampling

Abstract Google’s quantum supremacy experiment heralded a transition point where quantum computers can evaluate a computational task, random circuit sampling, faster than classical supercomputers. We examine the constraints on the region of quantum advantage for quantum circuits with a larger number of qubits and gates than experimentally implemented. At near-term gate fidelities, we demonstrate that quantum supremacy is limited to circuits with a qubit count and circuit depth of a few hundred. Larger circuits encounter two distinct boundaries: a return of a classical advantage and practically infeasible quantum runtimes. Decreasing error rates cause the region of a quantum advantage to grow rapidly. At error rates required for early implementations of the surface code, the largest circuit size within the quantum supremacy regime coincides approximately with the smallest circuit size needed to implement error correction. Thus, the boundaries of quantum supremacy may fortuitously coincide with the advent of scalable, error-corrected quantum computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Conditioned quantum-assisted deep generative surrogate for particle-calorimeter interactions

Particle collisions at accelerators like the Large Hadron Collider (LHC), recorded by experiments such as ATLAS and CMS, enable precise standard model measurements and searches for new phenomena. Simulating these collisions significantly influences experiment design and analysis but incurs immense computational costs, projected at millions of CPU-years annually during the high luminosity LHC (HL-LHC) phase. Currently, simulating a single event with Geant4 consumes around 1000 CPU seconds, with calorimeter simulations especially demanding. To address this, we propose a conditioned quantum-assisted generative model, integrating a conditioned variational autoencoder (VAE) and a conditioned restricted Boltzmann machine (RBM). Our RBM architecture is tailored for D-Wave’s Pegasus-structured advantage quantum annealer for sampling, leveraging the flux bias for conditioning. This approach combines classical RBMs as universal approximators for discrete distributions with quantum annealing’s speed and scalability. We also introduce an adaptive method for efficiently estimating effective inverse temperature, and validate our framework on Dataset 2 of CaloChallenge.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Pitfalls in parameters: practical process development in chemical vapor processing of SiC

Vapor processing of high-value materials, such as silicon carbide (SiC), is of interest for many industries, including aerospace and energy production. Chemical vapor infiltration (CVI) of additively manufactured components is an especially attractive manufacturing process currently in development. Here, a novel development workflow is demonstrated with the H 2 –CH 3 SiCl 3 gas system for SiC to accelerate the process optimization of CVI SiC. A combination of calculated thermodynamics and high-throughput experimental chemical vapor deposition (CVD) coatings substantially reduced the experiments required with slow CVI processes. The computational results accurately predicted changes in the thermodynamic conditions tested, while CVD coatings – characterized by Raman spectroscopy – addressed changes in kinetic parameters. This workflow is also applicable to other vapor-processing systems, such as pyrolytic carbon, ZrC, or Si 3 N 4 .

Lamm, Benjamin W. [Oak Ridge National Laboratory (↗
DOE OSTI2019

Design of a Do-It-Yourself Geiger-Muller Counter With Smartphone Mapping Application

Legacy Geiger-Muller (GM) survey meters recovered from fallout shelters have been used by several nuclear scientific societies as part of high school outreach programs. A donated antique instrument helps teachers demonstrate radiological principles, but fails to develop student's electronics skills, generate excitement for nuclear careers, or provide individuals with their own devices to explore the radioactive planet. A simple, affordable GM survey meter built by each student would increase direct engagement while providing hands-on experience with circuit-building, soldering, and computer programming. The inclusion of an affordable single-board computer as a component in the survey meter would enable students to tackle more various computer science and electronics projects, thereby potentially recruiting more students into technology and engineering. This paper details the challenges faced by an interdisciplinary undergraduate team designing an easy-to-assemble smart GM survey meter. Their iterative research, design, and testing process included modification to a basic circuit to enable use of different tube types, component cost reduction, application development, and data communication. The ultimate product of the team's efforts, a survey meter with affordable components and a smartphone application capable of creating radiation maps, is detailed in full.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Improving noisy free-energy measurements by adding more noise

Estimating free-energy differences using nonequilibrium work relations, such as the Jarzynski equality, is hindered by poor convergence when work fluctuations are large. For systems governed by overdamped Langevin dynamics, we propose the counterintuitive approach of adding noise in order to increase the precision of such calculations. Here, by introducing additional stochastic fluctuations to the system and rescaling its potential energy accordingly, we leave the thermodynamics of the system unchanged while increasing its relaxation rate. For a given time-dependent protocol this modification reduces the dissipated reduced work, leading to more accurate free-energy estimates. The method is designed to be used in experiment, and we illustrate its operation using computer simulations applied to two model systems. However, the regime of applicability of this strategy is likely limited, because it requires control of the system's potential energy in a way that is feasible in only a few experimental settings.

Whitelam, Stephen [Lawrence Berkeley National Labo↗
DOE OSTI2020

Efficient I/O for Neural Network Training with Compressed Data

FanStore is a shared object store that enables efficient and scalable neural network training on supercomputers. By providing a global cache layer on node-local burst buffers using a compressed representation, it significantly enhances the processing capability of deep learning (DL) applications on existing hardware. In addition, FanStore allows POSIX-compliant file access to the compressed data in user space. We investigate the tradeoff between runtime overhead and data compression ratio using real-world datasets and applications, and propose a compressor selection algorithm to maximize storage capacity given performance constraints. We consider both asynchronous (i.e., with prefetching) and synchronous I/O strategies, and propose mechanisms for selecting compressors for both approaches. Using FanStore, the same storage hardware can host 2-13x more data for example applications without significant runtime overhead. Empirically, our experiments show that FanStore scales to 512 compute nodes with near linear performance scalability.

Zhang, Zhao↗
DOE OSTI2026

From Reproducible Edge–Cloud Experimentation to Real-World Practice: The E2Clab Experience

Reproducibility is already difficult in distributed systems; on the computing continuum, it becomes substantially harder. Applications that span sensing devices, edge and fog resources, and cloud platforms must be evaluated across heterogeneous hardware, variable network conditions, cross-layer orchestration decisions, and long-running workflow lifecycles. We use E2Clab as a case study to examine these challenges and their implications for experimental methodology. We explain why reproducible experimentation is harder on the continuum, then revisit E2Clab as an initial response based on explicit modeling of infrastructure, workflow lifecycle, and artifacts. Lastly, we discuss how its evolution toward more realistic application settings can be understood through the lens of Translational Computer Science. We argue that reproducible continuum experimentation requires methods that are rigorous enough for research while remaining adaptable to real-world practice.

42 ENGINEERING↗
DOE OSTI2018

LADR: low-cost application-level detector for reducing silent output corruptions

Applications running on future high performance computing (HPC) systems are more likely to experience transient faults due to technology scaling trends with respect to higher circuit density, smaller transistor size and near-threshold voltage (NTV) operations. A transient fault could corrupt application state without warning, possibly leading to incorrect application output. Such errors are called silent data corruptions (SDCs). In this paper, we present LADR, a low-cost application-level SDC detector for scientific applications. LADR protects scientific applications from SDCs by watching for data anomalies in their state variables (those of scientific interest). It employs compile-time data-flow analysis to minimize the number of monitored variables, thereby reducing runtime and memory overheads while maintaining a high level of fault coverage with low false positive rates. We evaluated LADR with 4 scientific workloads and results show that LADR achieved < 80% fault coverage with only ∼ 3% runtime overheads and ∼ 1% memory overheads. As compared to prior state-of-the-art anomaly-based detection methods, SDC achieved comparable or improved fault coverage, but reduced runtime overheads by 21% ∼ 75%, and memory overheads by 35% ∼ 55% for the evaluated workloads. We believe that such an approach with low memory and runtime overheads coupled with attractive detection precision makes LADR a viable approach for assuring the correct output from large-scale high performance simulations.

Chen, Chao↗
DOE OSTI2022

AutodiDAQt v1.1.0

AutodiDAQt automates and simplifies writing data acquisition software for spectroscopy and microscopy. After defining only how to communicate with instruments and hardware, autodiDAQt generates user interfaces for long running acquisition applications, handlings data collation and retention, and provides remote communication to analysis computers. This reduces the time to get experiments running from months to hours and increases reliability for scientific experiments. AutodiDAQt metaprograms from instrument drivers directly, where possible.

Stansbury, Conrad↗
DOE OSTI2023

EPiC-GAN: Equivariant point cloud generation for particle jets

With the vast data-collecting capabilities of current and future high-energy collider experiments, there is an increasing demand for computationally efficient simulations. Generative machine learning models enable fast event generation, yet so far these approaches are largely constrained to fixed data structures and rigid detector geometries. In this paper, we introduce EPiC-GAN - equivariant point cloud generative adversarial network - which can produce point clouds of variable multiplicity. This flexible framework is based on deep sets and is well suited for simulating sprays of particles called jets. The generator and discriminator utilize multiple EPiC layers with an interpretable global latent vector. Crucially, the EPiC layers do not rely on pairwise information sharing between particles, which leads to a significant speed-up over graph- and transformer-based approaches with more complex relation diagrams. We demonstrate that EPiC-GAN scales well to large particle multiplicities and achieves high generation fidelity on benchmark jet generation tasks.

Buhmann, Erik↗