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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Experimental studies of the two-step scheme with an intense radioactive 132 Sn beam for next-generation production of very neutron-rich nuclei

The study of nuclei in the yet-unexplored, very neutron-rich, mid- to heavy-mass region of the nuclear chart, comprising perhaps half of all nuclei predicted to exist, is leading to new and/or upgraded facilities, as well as to research into the underlying production processes. In the present study, the usefulness of the two-step scheme, an alternate method to produce very neutron-rich nuclei, by a combination of an isotope-separation online (ISOL) system as a first step, and in-beam fragmentation of re-accelerated radioactive isotopes (RIs) as a second step, was investigated with a 132 Sn beam. In this work, very neutron-rich RIs around the neutron-rich neutron number N = 82 region were produced from the 278-MeV/nucleon 132 Sn beam impinging on a 5.97-mm Be target, and their production cross sections were measured. Yields were then estimated for the two-step scheme with the 132 Sn beam relative to the ones by a one-step scheme, in-flight fission of a 238 U beam, for 1-MW proton and 238 U beams at respective RI-beam facilities. This comparison suggests that the two-step scheme with the 132 Sn beam provides yields >40-times higher than those with the one-step scheme for the very neutron-rich N = 82 region. Moreover, by using various RI beams over the nuclear chart from ISOL, certain kinds of very neutron-rich RIs around the supernova r-process path can be produced with greater yields than by the one-step approach.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects

This is the conference paper accompanying an oral presentation “Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects” at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24 , 2024. Carbon capture and storage (CCS) technology is critical for mitigating climate change but requires effective subsurface reservoir management to ensure safe containment of injected CO2. Accurate predictions of reservoir pressure and saturation are essential for assessing long-term CCS performance. Traditional numerical simulations, while effective, are computationally intensive, time-consuming, and constrained by data discretization. Previous work has shown the effectiveness of MeshGraphNets (MGN), a graph-based machine learning framework, as an innovative alternative for predicting reservoir behavior. MGN leverages graph neural networks (GNNs) and mesh representations to model complex geological formations, offering superior adaptability across different discretizations and reservoir configurations. Classic MGN implementations utilize an autoregressive technique to predict future behavior based on current predictions, but this technique is hampered by error accumulation over time. To enhance the model accuracy in time-series predictions, this study implemented a multi-step rollout strategy that integrates autoregressive predictions during training to stabilize prediction of saturation over time. Using the Illinois Basin – Decatur Project (IBDP) dataset, comprising 100 simulations of CO2 injection, pressure, and saturation changes, the framework demonstrated its ability to learn spatial dependencies and temporal dynamics. With inputs including permeabilities, porosities, and injection rates, MGN accurately predicted CO2 plume evolution over time, even with limited training data. Moreover, the addition of a multi-step rollout procedure during training improved the ability of MGN to predict stably over time by ~15%. This research positions MGN, enhanced with multi-step rollout capabilities, as a robust and efficient tool for CCS applications. It advances the field by enabling precise, computationally efficient predictions of reservoir behavior, providing a foundation for the broader adoption of machine learning frameworks in CCS and other geoscience domains.

Holcomb, Paul↗
DOE OSTI2024

Rapid detection of mexX in Pseudomonas aeruginosa based on CRISPR-Cas13a coupled with recombinase polymerase amplification

The principal pathogen responsible for chronic urinary tract infections, immunocompromised hosts, and cystic fibrosis patients is Pseudomonas aeruginosa , which is difficult to eradicate. Due to the extensive use of antibiotics, multidrug-resistant P. aeruginosa has evolved, complicating clinical therapy. Therefore, a rapid and efficient approach for detecting P. aeruginosa strains and their resistance genes is necessary for early clinical diagnosis and appropriate treatment. This study combines recombinase polymerase amplification (RPA) and clustered regularly interspaced short palindromic repeats-association protein 13a (CRISPR-Cas13a) to establish a one-tube and two-step reaction systems for detecting the mexX gene in P. aeruginosa . The test times for one-tube and two-step RPA-Cas13a methods were 5 and 40 min (including a 30 min RPA amplification reaction), respectively. Both methods outperform Quantitative Real-time Polymerase Chain Reactions (qRT-PCR) and traditional PCR. The limit of detection (LoD) of P. aeruginosa genome in one-tube and two-step RPA-Cas13a is 10 aM and 1 aM, respectively. Meanwhile, the designed primers have a high specificity for P. aeruginosa mexX gene. These two methods were also verified with actual samples isolated from industrial settings and demonstrated great accuracy. Furthermore, the results of the two-step RPA-Cas13a assay could also be visualized using a commercial lateral flow dipstick with a LoD of 10 fM, which is a useful adjunt to the gold-standard qRT-PCR assay in field detection. Taken together, the procedure developed in this study using RPA and CRISPR-Cas13a provides a simple and fast way for detecting resistance genes.

Zhu, Xiao-Xuan↗
DOE OSTI2024

LightMAT - Pediction of Aluminum/Steel Joint Failure

Develop a predictive model of dissimilar metallic spot joints and their behavior during fracture; specifically, whether the joint fractures via interfacial fracture or button pull-out as a function of alloy, sheet thickness, faying interface microstructure, and thermal-mechanical treatment of the weld nugget and heat affected zone. Having the ability to model whether a given joint structure would fracture inter-facially or via button pullout will reduce development time and provide savings to vehicle design programs. This would provide a significant step function improvement in reducing the time-to-market for this multi-material, weight-saving technology.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Noise-induced stabilization of dynamical states with broken time-reversal symmetry

Under a high frequency drive, Josephson junctions demonstrate Shapiro steps of quantized voltage. These are dynamically stabilized states in which the phase across the junction locks to the external drive. We explore the stochastic switching between two symmetric steps at $\frac{hw}{2e}$ and –$\frac{hw}{2e}$. Surprisingly, the switching rate exhibits a pronounced nonmonotonicity as a function of temperature, violating the general expectation that transitions should become faster with temperature. As a result, we explain this behavior by realizing that the system retains memory of the dynamic state from which it is switching, thereby breaking the conventional simplifying assumptions about separations of timescales.

36 MATERIALS SCIENCE↗
DOE OSTI2026

The Art of Automation: Translating Electron Microscopy Workflows Into Automated Processes

Acquiring data using a scanning transmission electron microscope (STEM) is a complex, multi-step process. The intricacy of the process depends on the type of sample, composition of the material, desired results of the experiment, resolution requirement and other experimental factors. Each experiment presents unique complications, such as sample drift and contamination, that the microscopist must consider when acquiring data. All these challenges are handled fluidly and expertly by experienced microscopists, but to reach new levels of innovation in material development, including greater reproducibility, throughput, and precision, the automation of these workflows is essential. The initial phase of this work involved translating intuition-based workflows into discrete, programmable steps. Some common key stages in STEM workflows are the initial tuning, scanning the sample for areas of interest, and then acquiring the data. Each stage can be broken further into specific parameter adjustments, such as aberration correction and dwell time optimization, depending on the experiment. When deconstructing various experiments each step was assessed for automation feasibility based on the amount of real time operator decisions. There are steps that lend themselves to automation more readily than others, such as course focusing and sample screening, but there is potential for full automation of all stages with time. As an initial step, an automated montage routine was developed, allowing for the efficient acquisition of large portions of the sample without requiring continuous intervention from the operator. The automation of this small process of the procedure demonstrates the value of this capability. A major challenge in automation arises from discrepancies between commanded, reported and actual stage movements. Using systematic tests, stage movement was quantified. This error can be corrected algorithmically for more accurate workflows in the future. Expanding automation capabilities would result in larger, more efficient data acquisition which allows for more robust statistical analysis. Additionally, this work lays the groundwork for a closed loop system where machine learning algorithms would intake automatically acquired data and make real time decisions. By progressively automating this instrument, this work establishes the foundation for fully automated experimentation in transmission electron microscopy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Conjugate Multimode Heat Transfer Analysis of Cryogenic EXLO Manipulation

Abstract In this study, a conjugate radiation/conduction multimode heat transfer analysis of cryogenic focused ion beam (FIB) milling steps necessary for producing ex situ lift out specimens under cryogenic conditions (cryo-EXLO) is performed. Using finite volume for transient heat conduction and enclosure theory for radiation heat transfer, the analysis shows that as long as the specimen is attached or touching the FIB side wall trenches, the specimen will remain vitreous indefinitely, while actively cooled at liquid nitrogen (LN2) temperatures. To simulate the time needed to perform a transfer step to move the bulk sample containing the FIB-thinned specimen from the cryo-FIB to the cryo-EXLO cryostat, the LN2 temperature active cooling is turned off after steady-state conditions are reached and the specimen is monitored over time until the critical devitrification temperature is reached. Under these conditions, the sample will remain vitreous for >3 min, which is more than enough time needed to perform the cryo-transfer step from the FIB to the cryostat, which takes only ∼10 s. Cryo-transmission electron microscopy images of a manipulated cryo-EXLO yeast specimen prepared with cryo-FIB corroborates the heat transfer analysis.

Materials Science↗
DOE OSTI2021

Computational Complexity of Neuromorphic Algorithms

Neuromorphic computing has several characteristics that make it an extremely compelling computing paradigm for post Moore computation. Some of these characteristics include intrinsic parallelism, inherent scalability, collocated processing and memory, and event-driven computation. While these characteristics impart energy efficiency to neuromorphic systems, they do come with their own set of challenges. One of the biggest challenges in neuromorphic computing is to establish the theoretical underpinnings of the computational complexity of neuromorphic algorithms. In this paper, we take the first steps towards defining the space and time complexity of neuromorphic algorithms. Specifically, we describe a model of neuromorphic computation and state the assumptions that govern the computational complexity of neuromorphic algorithms. Next, we present a theoretical framework to define the computational complexity of a neuromorphic algorithm. We explicitly define what space and time complexities mean in the context of neuromorphic algorithms based on our model of neuromorphic computation. Finally, we leverage our approach and define the computational complexities of six neuromorphic algorithms: constant function, successor function, predecessor function, projection function, neuromorphic sorting algorithm and neighborhood subgraph extraction algorithm.

Date, Prasanna↗
DOE OSTI2023

The Fermilab Holometer: A program to measure Planck scale indeterminacy

We propose an experiment at Fermilab to study a conjectured effect called "holographic noise" that may arise from new Planck scale physics: the measured positions of bodies may wander randomly from ideal geodesics of classical relativity, in measurement-dependent directions, by about a Planck length per Planck time. The experiment will search for this holographic jitter in the relation of mass-energy and space-time by looking for correlated phase noise between two neighboring 40 meter interferometers. The goal of the experiment is to provide convincing evidence for or against the hypothesis that relative transverse positions of bodies display this particular new kind of quantum noise, whose power spectrum is independent of frequency and has a spectral density determined only by the Planck time. A positive result of the experiment would be a major step forward in understanding the emergence of space time and mass-energy from a unified theory of spacetime and quantum mechanics. A negative result will impact the macroscopic interpretation of unified theories.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Spatiotemporal Formation and Growth Kinetics of Polyelectrolyte Complex Micelles with Millisecond Resolution

We have directly observed the in situ self-assembly kinetics of polyelectrolyte complex (PEC) micelles by synchrotron time-resolved small-angle X-ray scattering, equipped with a stopped-flow device that provides millisecond temporal resolution. A synthesized neutral-charged diblock polycation and homopolyanion that we have previously investigated as a model charge-matched, core-shell micelle system were selected for this work. The initial micellization of the oppositely charged polyelectrolytes was completed within the dead time of mixing of 100 ms, followed by micelle growth and equilibration up to several seconds. By combining the structural evolution of the radius of gyration (R-g) with complementary molecular dynamics simulations, we show how the self-assemblies evolve incrementally in size over time through a two-step kinetic process: first, oppositely charged polyelectrolyte chains pair to form nascent aggregates that immediately assemble into spherical micelles, and second, these PEC micelles grow into larger micellar entities. Furthermore, this work has determined one possible kinetic pathway for the initial formation of PEC micelles, which provides useful physical insights for increasing fundamental understanding self-assembly dynamics, driven by polyelectrolyte complexation that occurs on ultrafast time scales.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

STRIDES: automated uniform models for 30 quadruply imaged quasars

ABSTRACT Gravitational time delays provide a powerful one-step measurement of H0, independent of all other probes. One key ingredient in time-delay cosmography are high-accuracy lens models. Those are currently expensive to obtain, both, in terms of computing and investigator time (105–106 CPU hours and ∼0.5–1 yr, respectively). Major improvements in modelling speed are therefore necessary to exploit the large number of lenses that are forecast to be discovered over the current decade. In order to bypass this roadblock, we develop an automated modelling pipeline and apply it to a sample of 31 lens systems, observed by the Hubble Space Telescope in multiple bands. Our automated pipeline can derive models for 30/31 lenses with few hours of human time and <100 CPU hours of computing time for a typical system. For each lens, we provide measurements of key parameters and predictions of magnification as well as time delays for the multiple images. We characterize the cosmography-readiness of our models using the stability of differences in the Fermat potential (proportional to time delay) with respect to modelling choices. We find that for 10/30 lenses, our models are cosmography or nearly cosmography grade (<3 per cent and 3–5 per cent variations). For 6/30 lenses, the models are close to cosmography grade (5–10 per cent). These results utilize informative priors and will need to be confirmed by further analysis. However, they are also likely to improve by extending the pipeline modelling sequence and options. In conclusion, we show that uniform cosmography grade modelling of large strong lens samples is within reach.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Real-time simulation of asymmetry generation in fermion-bubble collisions

Motivated by the out-of-equilibrium dynamics during an early-Universe first-order phase transition, we perform real-time simulations of fermion-bubble scattering in 1 + 1 dimensions. This nonequilibrium process can generate a charge-conjugation C asymmetry outside the bubble wall, induced by the complex fermion mass profile. The resulting C asymmetry is the 1 + 1 -dimensional analog of the C P asymmetry in 3 + 1 dimensions, a key ingredient in baryon asymmetry generation at the electroweak scale. Using tensor network methods, we track the real-time evolution of the C asymmetry in the charge density as the fermion interacts with the bubble wall, a regime inaccessible to analytic calculations. We further introduce two observables to quantify the asymmetry in the asymptotic region where reflected particles are well separated from the scattering point: one based on the net charge outside the bubble wall, and the other on the spatial displacement between the reflected particle and antiparticle wave packets. Our study represents a first step toward nonperturbative, real-time computations of C P asymmetry in 3 + 1 dimensions for electroweak baryogenesis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

First observations from the Kr multi-monochromatic x-ray imager for time and spatially resolved diagnosis of hot implosion cores

This paper presents initial findings from the recently deployed Kr multi-monochromatic x-ray imager (Kr MMI) at the Omega laser facility. The experiment focuses on exploring implosion dynamics in exploding pusher capsules at three distinct initial gas fill densities. Utilizing time-gated and spatially integrated measurements, core size, electron temperature (Te), and electron densities (ne) are extracted through the analysis of the spectral region encompassing the Kr He α and its satellite lines. A comprehensive spectral database, incorporating atomic kinetics, spectroscopic-quality radiation transport, and Stark broadened line shapes, has been developed for rigorous data analysis. These measurements underscore the utility of the new Kr MMI instrument, which, combined with sophisticated analysis techniques, enables the diagnosis of plasma conditions at Te>2000 eV, thereby extending the capabilities beyond the prior Ar MMI design. This is an important stepping stone for achieving time-gated and space-resolved diagnostics of electron temperature, electron density, and heat transport in high temperature implosion cores.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Real-time gravitational replicas: formalism and a variational principle

This work is the first step in a two-part investigation of real-time replica wormholes. Here we study the associated real-time gravitational path integral and construct the variational principle that will define its saddle-points. We also describe the general structure of the resulting real-time replica wormhole saddles, setting the stage for construction of explicit examples. These saddles necessarily involve complex metrics, and thus are accessed by deforming the original real contour of integration. However, the construction of these saddles need not rely on analytic continuation, and our formulation can be used even in the presence of non-analytic boundary-sources. Furthermore, at least for replica- and CPT-symmetric saddles we show that the metrics may be taken to be real in regions spacelike separated from a so-called ‘splitting surface’. This feature is an important hallmark of unitarity in a field theory dual.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Influence of silicon infiltration conditions on microstructure and mechanical properties in binder jet 3D printed SiC

Atmosphere, temperature, and hold time were varied for silicon infiltrated binder jet 3D printed SiC preforms. A two-step infiltration process optimized infiltration. The first step at 1450 °C under vacuum facilitated improved wetting. The second step at elevated temperature in argon advanced infiltration while suppressing vaporization. Variation of the second-step temperature (1550–1750 °C) and hold time revealed that 1550 °C for 1 h in argon following initial vacuum treatment yielded the highest silicon uptake ratio (∼96 %) with minimal residual porosity and strengths of 150–180 MPa. Flexural strength was either stable or improved with elevated temperatures up to 1000°C. In contrast, higher temperatures or extended hold times led to increased silicon vaporization and pores. The optimized process was applied to formulations with extra carbon to enhance SiC content and interconnectedness through reaction bonding, which corresponded to increased flexural strength. These findings provide guidance for silicon infiltration in additively manufactured SiC.

Yoon, Bola [ORNL] (ORCID:0000000260875373)↗
DOE OSTI2026

Exploring Approaches for Accelerated Mass Spectrometric Detection of Fluorochemicals from Aqueous Solutions Using Indirect, Adsorbent-Facilitated Desorption Ionization

There is a growing need for rapid, low-cost analytical tools to screen water supplies for persistent contaminants. Due to their ubiquitous presence in the environment and their detrimental effects on human health, there is a public interest in widespread testing for perfluoroalkyl substances (PFAS). However, the most common methods for PFAS analysis can be time-intensive, requiring a preconcentration step followed by liquid chromatography–mass spectrometry (LC–MS), and are cost-prohibitive for most members of the public. To address these challenges, this study explores a novel method for rapid analysis of aqueous analytes by concentrating analytes on solid adsorbents and detecting them using mass spectrometric analysis via desorption ionization directly from the adsorbent surface. We demonstrate this general approach of indirect solution analysis (ISA) with desorption electrospray ionization (ISA-DESI) and laser desorption ionization (ISA-LDI). Various adsorbent materials were screened, including commercial mesoporous carbons, alumina, and metal–organic frameworks (MOFs). Using ISA-DESI, we consistently detect concentrations as low as 5–100 parts per trillion (ppt) for perfluorooctanoic acid (PFOA) and 10–100 ppt for perfluoroundecanoic acid (PFUnDA). This approach enables rapid detection in under 5 min, making it suitable for applications requiring trace detection with fast response times. We further demonstrate the use of ISA-DESI on a range of environmentally relevant contaminants. Advantages of this indirect solution analysis approach include simplified sample preparation, accelerated analysis, and low cost with readily available materials, making it a promising tool to accelerate mass spectrometric PFAS detection for identifying contaminated sites, performing laboratory studies, and monitoring industrial waste streams.

Bays, Nathan Robert [Sandia National Laboratories ↗
DOE OSTI2022

MEUMAPPS (C++ Version)

Many materials, metal alloys in particular, have features on the on micrometer or nanometer scale that have a large impact on the properties of the material. These features are known as the microstructure of the material. Understanding why and how the microstructure forms in a material is of fundamental scientific interest as well as of significant technological interest. The capability to predict microstructure evolution in a material allows the intentional design of microstructures and hence the intentional design of material properties. The phase-field method is one of the leading methods for predicting microstructure evolution. One of the most significant problems for phase-field models is their computational expense. Even limited phase-field simulations can easily require thousands of CPU core-hours to complete, which significantly limits their use. This code provides both a general framework for creating scalable, GPU-accelerated phase-field model applications as well as several applications themselves. The code is capable of using hundreds of GPUs efficiently, which greatly reduces the time required to perform simulations. The code is written with an emphasis on performance portability, that is the ability for the code to run efficiently on a number of different computing architectures without modification of the source code. The performance portability of this code is primarily enabled through the use of two libraries, Kokkos (performance portable data structures and execution patterns) and heFFTe (performance portable distributed 3D fast Fourier transforms). The code consists of a core library, applications, and tests. The core library includes shared functionality between applications. This includes interfaces with fast Fourier transform (FFT) libraries such as heFFTe, data structures based on Kokkos, file input and output capabilities, and a solver for infinitesimal strain mechanical equilibrium problems. Five applications are included in the code. The flagship application is the MEUMAPPS-SS application, which implements the Kim-Kim-Suzuki phase-field model for precipitation for an arbitrary number of phases and components in a metal alloy. Five simpler applications are also included that solve the Eshelby inclusion problem, Allen-Cahn equation, the coupled Allen-Cahn and diffusion equations, and the Cahn-Hilliard equation. The code includes two applications to solve the Cahn-Hilliard equation, one with constant-step-size first-order time integration and the second with adaptive high-order time integration.

DeWitt, Stephen [Oak Ridge National Lab. (ORNL), O↗
DOE OSTI2023

Structural dynamics of a thermally silent triiron( II ) spin crossover defect grid complex

The structural evolution of spin crossover (SCO) complexes during their spin transition at equilibrium and out-of-equilibrium conditions needs to be understood to enable their successful utilisation in displays, actuators and memory components. In this study, diffraction techniques were employed to study the structural changes accompanying the temperature increase and the light irradiation of a defect [2 × 2] triiron(II) metallogrid of the form [Fe II 3 L H 2 (HL H ) 2 ](BF 4 ) 4 ·4MeCN (FE3), L H = 3,5-bis{6-(2,2'-bipyridyl)}pyrazole. Although a multi-temperature crystallographic investigation on single crystals evidenced that the compound does not exhibit a thermal spin transition, the structural analysis of the defect grid suggests that the flexibility of the grid, provided by a metal-devoid vertex, leads to interesting characteristics that can be used for intermolecular cooperativity in related thermally responsive systems. Time-resolved photocrystallography results reveal that upon excitation with a ps laser pulse, the defect grid shows the first two steps of the out-of-equilibrium process, namely the photoinduced and elastic steps, occurring at the ps and ns time scales, respectively. Similar to a previously reported [2 × 2] tetrairon(II) metallogrid, FE3 exhibits a local distortion of the entire grid during the photoinduced step and a long-range distortion of the lattice during the elastic step. Although the lifetime of the pure photoinduced high spin (HS) state is longer in the tetranuclear grid than in the defect grid, suggesting that the global nuclearity plays a crucial role for the lifetime of the photoinduced species, the influence of the co-crystalising solvent on the lifetime of the photoinduced HS state remains unknown. This study sheds light on the out-of-equilibrium dynamics of a thermally silent defect triiron SCO metallogrid.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗