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DOE OSTI2016

Crystal plasticity investigation of the microstructural factors influencing dislocation channeling in a model irradiated bcc material

We use a continuum crystal plasticity framework to study the effect of microstructure and mesoscopic factors on dislocation channeling and flow localization in an irradiated model bcc alloy. For simulated dislocation channeling characteristics we correlate the dislocation and defect densities in the substructure, local Schmid factor, and stress triaxiality, in terms of their temporal and spatial evolution. A metric is introduced to assess the propensity for localization and is correlated to the grain-level Schmid factor. We also found that localization generally takes place in grains with a local Schmid factor in the range 0.42 or higher. Surface slip step heights are computed at free surfaces and compared to relevant experiments.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Estimation of mass of compact object in H 1743-322 from 2010 and 2011 outbursts using TCAF solution and spectral index–QPO frequency correlation

The well-known black hole candidate (BHC) H 1743-322 exhibited temporal and spectral variabilities during several outbursts. The variation of the accretion rates and flow geometry that change on a daily basis during each of the outbursts can be very well understood using the recent implementation of the two-component advective flow solution of the viscous transonic flow equations as an additive table model in XSPEC. This has dramatically improved our understanding of accretion flow dynamics. Most interestingly, the solution allows us to treat the mass of the BHC as a free parameter and its mass could be estimated from spectral fits. In this paper, we fitted the data of two successive outbursts of H 1743-322 in 2010 and 2011 and studied the evolution of accretion flow parameters, such as two-component (Keplerian and sub-Keplerian) accretion rates, shock location (i.e., size of the Compton cloud), etc. We assume that the model normalization remains the same across the states in both these outbursts. We used this to estimate the mass of the black hole and found that it comes out in the range of 9.25--12.86 M{sub ⊙}. For the sake of comparison, we also estimated mass using the Photon index versus Quasi Periodic Oscillation frequency correlation method, which turns out to be 11.65±0.67 M{sub ⊙} using GRO J1655-40 as a reference source. Combining these two estimates, the most probable mass of the compact object becomes 11.21{sub −1.96}{sup +1.65} M{sub ⊙}.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Characterization of 6 Li-loaded pulse-shape-discriminating plastic scintillators

Lithium-loaded organic plastic scintillators combine sensitivity to γ rays with the ability to detect both fast and slow neutrons, making them valuable for applications in nuclear security and in basic nuclear and particle physics. The goal of this work is to characterize the neutron response of two custom lithium-loaded organic plastic scintillators developed at Lawrence Livermore National Laboratory. Both are ternary polystyrene-based formulations containing 1.5 wt.% 6 Li salts of isobutyric acid, but they differ in their primary and secondary dye compositions: one uses m-terphenyl as the primary fluor and with Exalite 404 as the wavelength shifter, whereas the other uses 2,5-diphenyloxazole (PPO) and 9,10-diphenyl-anthracene, respectively. The temporal response of the scintillators was measured via time-correlated single photon counting for γ-ray and neutron events. The proton light yield was measured using the double time-of-flight technique from 1.3 to 15 MeV at the 88-Inch Cyclotron at Lawrence Berkeley National Laboratory. For the slow neutron response, an AmBe source moderated with polyethylene was used, and the light output from the 6 Li(n,α)t reaction was characterized. Differences in ionization quenching and temporal response were observed between the two materials with the PPO-containing scintillator exhibiting higher ionization quenching. These results provide performance benchmarks that can guide the design and optimization of future lithium-loaded plastic scintillators for use in basic science and applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1997

Comparison of TOPEX/Poseidon Sea Level and Linear Model Results forced by Various Wind Products for the Tropical Pacific

The goal of this paper is to compare TOPEX/Posaidon (T/P) sea level with sea level results from linear ocean model experiments forced by several different wind products for the tropical Pacific. During the period of this study (October 1992 - October 1995), available wind products include satellite winds from the ERS-1 scatterometer product of [HALP 97] and the passive microwave analysis of SSMI winds produced using the variational analysis method (VAM) of [ATLA 91]. In addition, atmospheric GCM winds from the NCEP reanalysis [KALN 96], ECMWF analysis [ECMW94], and the Goddard EOS-1 (GEOS-1) reanalysis experiment [SCHU 93] are available for comparison. The observed ship wind analysis of FSU [STRI 92] is also included in this study. The linear model of [CANE 84] is used as a transfer function to test the quality of each of these wind products for the tropical Pacific. The various wind products are judged by comparing the wind-forced model sea level results against the T/P sea level anomalies. Correlation and RMS difference maps show how well each wind product does in reproducing the T/P sea level signal. These results are summarized in a table showing area average correlations and RMS differences. The large-scale low-frequency temporal signal is reproduced by all of the wind products, However, significant differences exist in both amplitude and phase on regional scales. In general, the model results forced by satellite winds do a better job reproducing the T/P signal (i.e. have a higher average correlation and lower RMS difference) than the results forced by atmospheric model winds.

Hackert, Eric C.↗

DOE OSTI2016

Correlation between cationic lipid-based transfection and cell division

We evaluate the temporal relation between protein expression by cationic lipid-mediated transfection and cell division using time lapse fluorescence microscopy. Detailed image analysis provides new insights on the single cell level while simultaneously achieving appropriate statistics. Earlier evidence by less direct methods such as flow cytometry indicates a primary route for transfection involving nuclear envelope breakdown, but also suggests the existence of a pathway independent of mitosis. We confirm and quantify both mechanisms. We found the timing for successful transfection to be unexpectedly flexible, contrary to assertions of a narrow time window. Specifically, cells dividing more than 24 h after exposure to the transfection medium express the probed protein at a comparable level to cells in a mitotic state during or shortly after transfection. This finding can have a profound impact on the guidance and development of non-viral gene delivery materials. - Highlights: • Cationic lipid-based transfection supports protein expression without cell division. • Protein expression is unrelated to cell cycle status at the time of transfection. • Time-lapse imaging provides direct evaluation without statistical averaging. • Lipoplex dissociation is a likely target for improvement of transfection efficiency.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1990

Total-sky and clear-sky variability of outgoing longwave radiation and shortwave radiation and its relation to cloud fluctuation statistics

Correlation statistics are used to investigate some of the characteristic temporal and spatial scales of the day-to-day changes in cloudiness which tend to dominate the variance of outgoing LW radiation and SW radiation fields. The temporal decorrelation time of the radiation field as measured by the lag time required for the autocorrelation of a region to fall to 0.4 is about 12 hours in the midlatitude storm track. Decorrelation time approaches one to two days when the averaging area of the region is increased significantly. Decorrelation times are also longer in the equatorial and tropical regions. The short decorrelation times are a manifestation of the creation, breakup, and movement of cloud systems. Cross-correlation analysis of the radiation field in the midlatitude storm track region and the subtropical dry zone shows advection speeds that range from about 25 m/sec in the storm tracks to about 8 m/sec in the subtropical dry zone.

Bess, T. D.↗

NASA NTRS1992

Model-based vision for space applications

This paper describes a method for tracking moving image features by combining spatial and temporal edge information with model based feature information. The algorithm updates the two-dimensional position of object features by correlating predicted model features with current image data. The results of the correlation process are used to compute an updated model. The algorithm makes use of a high temporal sampling rate with respect to spatial changes of the image features and operates in a real-time multiprocessing environment. Preliminary results demonstrate successful tracking for image feature velocities between 1.1 and 4.5 pixels every image frame. This work has applications for docking, assembly, retrieval of floating objects and a host of other space-related tasks.

Chaconas, Karen↗

NASA NTRS1992

Spatial and temporal variations of the fluxes of carbon dioxide and sensible and latent heat over the FIFE site

Airborne measurements of flux densities of carbon dioxide CO2, sensible heat, and latent heat (H2O) obtained over the First ISLSCP Field Experiment (FIFE) site during three intensive field campaigns in 1987 and one in 1989 are examined to characterize the spatial and temporal variations of CO2 and energy transfer processes. These data were collected by the National Research Council Twin Otter using low-level flight patterns, all flown at constant pressure altitude during relatively clear days. The spatial variations are larger in 1989 than in 1987 and a higher correlation is observed between the fluxes and the surface features. The temporal patterns are easier to characterize with the relatively homogeneous situation of 1987. Functional relationships obtained between fluxes of CO2 and latent heat, CO2 fluxes and greenness index, latent heat fluxes and greenness index, and between sensible heat fluxes and surface air temperature differences are presented for one day in 1987 and one in 1989 as an example of the kind of information that can be obtained from grid flights at constant pressure altitude.

Desjardins, R. L.↗

DOE OSTI2017

Stochastic goal-oriented error estimation with memory

We propose a stochastic dual-weighted error estimator for the viscous shallow-water equation with boundaries. For this purpose, previous work on memory-less stochastic dual-weighted error estimation is extended by incorporating memory effects. The memory is introduced by describing the local truncation error as a sum of time-correlated random variables. The random variables itself represent the temporal fluctuations in local truncation errors and are estimated from high-resolution information at near-initial times. The resulting error estimator is evaluated experimentally in two classical ocean-type experiments, the Munk gyre and the flow around an island. In these experiments, the stochastic process is adapted locally to the respective dynamical flow regime. Our stochastic dual-weighted error estimator is shown to provide meaningful error bounds for a range of physically relevant goals. We prove, as well as show numerically, that our approach can be interpreted as a linearized stochastic-physics ensemble.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Theory and modeling of molecular modes in the NMR relaxation of fluids

Traditional theories of the nuclear magnetic resonance (NMR) autocorrelation function for intra-molecular dipole pairs assume a single-exponential decay, yet the calculated autocorrelation of realistic systems displays a rich, multi-exponential behavior, resulting in anomalous NMR relaxation dispersion (i.e., frequency dependence). We develop an approach to model and interpret the multi-exponential intra-molecular autocorrelation using simple, physical models within a rigorous statistical mechanical development that encompasses both rotational diffusion and translational diffusion in the same framework. Here, we recast the problem of evaluating the autocorrelation in terms of averaging over a diffusion propagator whose evolution is described by a Fokker–Planck equation. The time-independent part admits an eigenfunction expansion, allowing us to write the propagator as a sum over modes. Each mode has a spatial part that depends on the specified eigenfunction and a temporal part that depends on the corresponding eigenvalue (i.e., correlation time) with a simple, exponential decay. The spatial part is a probability distribution of the dipole pair, analogous to the stationary states of a quantum harmonic oscillator. Drawing inspiration from the idea of inherent structures in liquids, we interpret each of the spatial contributions as a specific molecular mode. These modes can be used to model and predict the NMR dipole–dipole relaxation dispersion of fluids by incorporating phenomena on the molecular level. We validate our statistical mechanical description of the distribution in molecular modes with molecular dynamics simulations interpreted without any relaxation models or adjustable parameters: the most important poles in the Padé–Laplace transform of the simulated autocorrelation agree with the eigenvalues predicted by the theory

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

High-fidelity dimer excitations using quantum hardware

The quantum simulation of entangled spin systems can play a central role in quantum magnetic materials discovery. Additionally, the simulation of spectroscopic signatures, such as the dynamical structure factor accessed in inelastic neutron scattering (INS), necessitates a long timescale for circuit evolution. This is because the energy resolution is directly related to the time over which the circuit could be meaningfully evolved. However, canonical Trotterization requires deep circuits precluding such long-time evolution—even for a small number of qubits. Here, in this study, we demonstrate “direct” resource efficient fast-forwarding (REFF) measurements with short-depth circuits that can be used to capture longer time dynamics of spin Hamiltonians. We showcase the results of the dynamics of a quantum spin dimer, the basic quantum unit of emergent many-body spin systems, whose density of states we simulate accurately. The long temporal evolution and measurement of the two-spin correlation functions enable the calculation of the dynamical structure factor S⁡(Q = 0, ω) measured in the neutron scattering cross-section. We exhibit the clarity of the triplet gap and the triplet splitting of the quantum dimer with class-leading fidelity that enables comparison to experimental neutron data. Our results on current circuit hardware outline an important workflow to predict and benchmark against the outputs of INS experiments of quantum magnets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Benchmarking Information Scrambling

Information scrambling refers to the rapid spreading of initially localized information over an entire system, via the generation of global entanglement. This effect is usually detected by measuring a temporal decay of the out-of-time order correlators. However, in experiments, decays of these correlators suffer from fake positive signals from various sources, e.g., decoherence due to inevitable couplings to the environment, or errors that cause mismatches between the purported forward and backward evolutions. Here, in this Letter, we provide a simple and robust approach to single out the effect of genuine scrambling. This allows us to benchmark the scrambling process by quantifying the degree of the scrambling from the noisy backgrounds. We also demonstrate our protocol with simulations on IBM cloud-based quantum computers.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics With Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis

Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.

Explainable AI↗

DOE OSTI2016

MO-FG-BRA-09: Towards an Optimal Breath-Holding Procedure for Radiotherapy: Differences in Organ Motion During Inhalation and Exhalation Breath-Holds

Purpose: Breath-holding (BH) is often used to reduce organ motion during radiotherapy. The aim of this study was to determine the differences in pancreatic and diaphragmatic motion during BH between inhalation and exhalation BHs with variable lung volumes and to investigate whether motion increases/decreases during BH. Methods: Sixteen healthy volunteers were asked to perform four different 60-second BHs, from fully inflated to fully deflated lungs (i.e. lung volumes of: 100%, ∼70%, ∼30% and 0% of inspiratory capacity) three times (total of 192 BHs). During each BH, we obtained single-slice (coronal) magnetic-resonance scans with spatial resolution 0.93×0.93×8.0 mm3 and temporal resolution 0.6 s. We used 2-dimensional image correlation to obtain the motion of pancreatic head and diaphragm during BH. Motion magnitude in inferior-superior direction was obtained by determining the maximum displacement during BH. Results: Pancreatic and diaphragmatic drifts occurred during BH and were mostly in the superior direction. We observed significantly smaller pancreatic and diaphragmatic motion magnitudes in inferior-superior direction during exhalation BHs (BH{sub 30%} and BH{sub 0%}) compared to inhalation BHs (BH{sub 100%} and BH{sub 70%}). The mean motion magnitudes of the pancreatic head were 7.0, 6.5, 4.4 and 4.2 mm during BH{sub 100%}, BH{sub 70%}, BH{sub 30%} and BH{sub 0%}, respectively, and mean BH durations were 59.9, 59.1, 59.0 and 52.7 s. For the diaphragm, mean motion magnitudes were 9.8, 9.0, 5.6 and 4.3 mm, respectively. When considering 30-second BHs, as often used in the clinic, the motion was most pronounced during the first 10 s and excluding these from the analysis (yielding an effective BH period of 20 s) significantly reduced (P≤0.002) organ motion. Conclusion: Organ motion was significantly smaller during exhalation BHs compared to inhalation BHs. Also, motion was largest at the start of BH. Hence, waiting for 10 s may significantly decrease motion of the pancreas and diaphragm during treatment.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Ultrafast correlated charge and lattice motion in a hybrid metal halide perovskite

Hybrid organic-inorganic halide perovskites have shown remarkable optoelectronic properties, exhibiting an impressive tolerance to defects believed to originate from correlated motion of charge carriers and the polar lattice forming large polarons. Few experimental techniques are capable of directly probing these correlations, requiring simultaneous sub–millielectron volt energy and femtosecond temporal resolution after absorption of a photon. Here, we use time-resolved multi-THz spectroscopy, sensitive to the internal excitations of the polaron, to temporally and energetically resolve the coherent coupling of charges to longitudinal optical phonons in single-crystal CH 3 NH 3 PbI 3 (MAPI). We observe room temperature intraband quantum beats arising from the coherent displacement of charge from the coupled phonon cloud. Our measurements provide strong evidence for the existence of polarons in MAPI at room temperature, suggesting that electron/hole-phonon coupling is a defining aspect of the hybrid metal-halide perovskites contributing to the protection from scattering and enhanced carrier lifetimes that define their usefulness in devices.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Data and scripts associated with the manuscript "Encoding Diel Hysteresis and the Birch Effect in Dryland Soil Respiration Models through Knowledge-Guided Deep Learning"

This package contains the data and scripts used in "Encoding Diel Hysteresis and the Birch Effect in Dryland Soil Respiration Models through Knowledge-Guided Deep Learning" (Jiang et al., 2022). The data.zip file contains the flux tower and automated chamber observations used for developing the deep learning model for modeling soil respiration. The scripts.zip file contains the Jupyter notebooks and python scripts for preprocessing the data, training the deep learning models, and postprocessing the results. The src.zip contains the source code for training the deep learning model, performing mutual information analysis, and plotting functions. The trained_models.zip contains multiple folders used for hosting the trained deep-learning models and the associated soil respiration predictions. The whole process is performed using python. We include the REAMD.md to document the python package requirements.Soil respiration in dryland ecosystems is challenging to model due to its complex interactions with environmental drivers. Knowledge-guided deep learning provides a much more effective means of accurately representing these complex interactions than traditional Q10-based models. Mutual information analysis revealed that future soil temperature shares more information with soil respiration than past soil temperature, consistent with their clockwise diel hysteresis. We explicitly encoded diel hysteresis, soil drying, and soil rewetting effects on soil respiration dynamics in a newly designed Long Short Term Memory (LSTM) model. The model takes both past and future environmental drivers as inputs to predict soil respiration. The new LSTM model substantially outperformed three Q10-based models and the Community Land Model when reproducing the observed soil respiration dynamics in a semi-arid ecosystem. The new LSTM model clearly demonstrated its superiority for temporally extrapolating soil respiration dynamics, such that the resulting correlation with observational data is up to 0.7 while the correlations of both Q10-based models and the Community Land Model (CLM) are less than 0.4. Our results underscore the high potential for knowledge-guided deep learning to replace Q10-based soil respiration modules in Earth system models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Encoding Diel Hysteresis and the Birch Effect in Dryland Soil Respiration Models through Knowledge-Guided Deep Learning

Soil respiration in dryland ecosystems is challenging to model due to its complex interactions with environmental drivers. Knowledge-guided deep learning provides a much more effective means of accurately representing these complex interactions than traditional Q10-based models. Mutual information analysis revealed that future soil temperature shares more information with soil respiration than past soil temperature, consistent with their clockwise diel hysteresis. We explicitly encoded diel hysteresis, soil drying, and soil rewetting effects on soil respiration dynamics in a newly designed Long Short Term Memory (LSTM) model. The model takes both past and future environmental drivers as inputs to predict soil respiration. The new LSTM model substantially outperformed three Q10-based models and the Community Land Model when reproducing the observed soil respiration dynamics in a semi-arid ecosystem. The new LSTM model clearly demonstrated its superiority for temporally extrapolating soil respiration dynamics, such that the resulting correlation with observational data is up to 0.7 while the correlations of the Q10-based models and the Community Land Model (CLM) are less than 0.4. Our results underscore the high potential for knowledge-guided deep learning to replace Q10-based soil respiration modules in Earth system models.

Jiang, Peishi↗

DOE OSTI2015

Asymmetric projections of the arcuate fasciculus to the temporal cortex underlie lateralized language function in the human brain

The arcuate fasciculus (AF) in the human brain has asymmetric structural properties. However, the topographic organization of the asymmetric AF projections to the cortex and its relevance to cortical function remain unclear. Here we mapped the posterior projections of the human AF in the inferior parietal and lateral temporal cortices using surface-based structural connectivity analysis based on diffusion MRI and investigated their hemispheric differences. We then performed the cross-modal comparison with functional connectivity based on resting-state functional MRI (fMRI) and task-related cortical activation based on fMRI using a semantic classification task of single words. Structural connectivity analysis showed that the left AF connecting to Broca's area predominantly projected in the lateral temporal cortex extending from the posterior superior temporal gyrus to the mid part of the superior temporal sulcus and the middle temporal gyrus, whereas the right AF connecting to the right homolog of Broca's area predominantly projected to the inferior parietal cortex extending from the mid part of the supramarginal gyrus to the anterior part of the angular gyrus. The left-lateralized projection regions of the AF in the left temporal cortex had asymmetric functional connectivity with Broca's area, indicating structure-function concordance through the AF. During the language task, left-lateralized cortical activation was observed. Among them, the brain responses in the temporal cortex and Broca's area that were connected through the left-lateralized AF pathway were specifically correlated across subjects. These results suggest that the human left AF, which structurally and functionally connects the mid temporal cortex and Broca's area in asymmetrical fashion, coordinates the cortical activity in these remote cortices during a semantic decision task. As a result, the unique feature of the left AF is discussed in the context of the human capacity for language.

59 BASIC BIOLOGICAL SCIENCES↗