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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

High-speed real-time 3D shape measurement based on adaptive depth constraint

Stereo phase unwrapping (SPU) has been increasingly applied to high-speed real-time fringe projection profilometry (FPP) because it can retrieve the absolute phase or matching points in a stereo FPP system without projecting or acquiring additional fringe patterns. Based on a pre-defined measurement volume, artificial maximum/minimum phase maps can be created solely using geometric constraints of the FPP system, permitting phase unwrapping on a pixel-by-pixel basis. However, when high-frequency fringes are used, the phase ambiguities will increase which makes SPU unreliable. Several auxiliary techniques have been proposed to enhance the robustness of SPU, but their flexibility still needs to be improved. In this paper, we proposed an adaptive depth constraint (ADC) approach for high-speed real-time 3D shape measurement, where the measurement depth volume for geometric constraints is adaptively updated according to the current reconstructed geometry. By utilizing the spatio-temporal correlation of moving objects under measurement, a customized and tighter depth constraint can be defined, which helps enhance the robustness of SPU over a large measurement volume. Besides, two complementary techniques, including simplified left-right consistency check and feedback mechanism based on valid area, are introduced to further increase the robustness and flexibility of the ADC. Furthermore, experimental results demonstrate the success of our proposed SPU approach in recovering absolute 3D geometries of both simple and complicated objects with only three phase-shifted fringe images.

42 ENGINEERING↗
DOE OSTI2019

Conformational coupling by trans-phosphorylation in calcium calmodulin dependent kinase II

The calcium calmodulin-dependent protein kinase II (CaMKII) is a dodecameric holoenzyme important for encoding memory. Its activation, triggered by binding of calcium-calmodulin, persists autonomously after calmodulin dissociation. One (receiver) kinase captures and subsequently phosphorylates the regulatory domain peptide of a donor kinase forming a chained dimer as the first stage of autonomous activation. Protein dynamics simulations examined the conformational changes triggered by dimer formation and phosphorylation, aimed to provide a molecular rationale for human mutations that result in learning disabilities. Ensembles generated from X-ray crystal structures were characterized by network centrality and community analysis. Mutual information related collective motions to local fragment dynamics encoded with a structural alphabet. Implicit solvent tCONCOORD conformational ensembles revealed the dynamic architecture of inactive kinase domains was co-opted in the activated dimer but the network hub shifted from the nucleotide binding cleft to the captured peptide. Explicit solvent molecular dynamics (MD) showed nucleotide and substrate binding determinants formed coupled nodes in long-range signal relays between regulatory peptides in the dimer. Strain in the extended captured peptide was balanced by reduced flexibility of the receiver kinase C-lobe core. The relays were organized around a hydrophobic patch between the captured peptide and a key binding helix. The human mutations aligned along the relays. Thus, these mutations could disrupt the allosteric network alternatively, or in addition, to altered binding affinities. Non-binding protein sectors distant from the binding sites mediated the allosteric signalling; providing possible targets for inhibitor design. Phosphorylation of the peptide modulated the dielectric of its binding pocket to strengthen the patch, non-binding sectors, domain interface and temporal correlations between parallel relays. These results provide the molecular details underlying the reported positive kinase cooperativity to enrich the discussion on how autonomous activation by phosphorylation leads to long-term behavioural effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Image mapping for multiple charge state beams using a beam induced fluorescence profile monitors

Work continues on a minimally invasive, nitrogen fluorescence gas sheet at the Facility for Rare Isotope Beams (FRIB). A low density gas sheet may be used to observe the 2D transverse beam profile of high intensity, multiple charge state beams with minimal interference. Spatially and temporally correlated profiles are of particular interest in locations where there is significant charge state spread, such as the FRIB linac folding segments. A low-density gas sheet measurement system offers advantages for gas handling in nitrogen sensitive areas, however signal intensity is significantly lower than techniques using higher density gas sheets and jets. This work discusses measurement considerations for photon distributions generated by several spatially separated interaction points and design considerations for a high-sensitivity optics system for handling the expected low signal intensity.

Accelerator Physics↗
DOE OSTI2016

Fundamental Mechanisms of Roughening and Smoothing During Thin Film Deposition

In this research program, we have explored the fundamental limits for thin film deposition in both crystalline and amorphous (i.e. non-crystalline) materials systems. For vacuum-based physical deposition processes such as sputter deposition, the background gas pressure of the inert gas (usually argon) used as the process gas has been found to be a key variable. Both a roughness transition and stress transition as a function of pressure have been linked to a common mechanism involving collisions of energetic particles from the deposition source with the process inert gas. As energetic particles collide with gas molecules in the deposition process they lose their energy rapidly if the pressure (and background gas density) is above a critical value. Both roughness and stress limit important properties of thin films for applications. In the area of epitaxial growth we have also discovered a related effect; there is a critical pressure below which highly crystalline layers grow in a layer-by-layer mode. This effect is also though to be due to energetic particle thermalization and scattering. Several other important effects such as the observation of coalescence dominated growth has been observed. This mode can be likened to the behavior of two-dimensional water droplets on the hood of a car during a rain storm; as the droplets grow and touch each other they tend to coalesce rapidly into new larger circular puddles, and this process proceeds exponentially as larger puddles overtake smaller ones and also merge with other large puddles. This discovery will enable more accurate simulations and modeling of epitaxial growth processes. We have also observed that epitaxial films undergo a roughening transition as a function of thickness, which is attributed to strain induced by the crystalline lattice mismatch with the substrate crystal. In addition, we have studied another physical deposition process called pulsed laser deposition. It differs from sputter deposition due to the pulsed nature of the deposition where particles arrive at the growth surface in an interval of a few microseconds. We have observed effects such as transient formation of two dimensional islands on elemental crystalline surfaces. Pulsed deposition may also lead to non-equilibrium phases in some cases, such as the observation anomalously high tetragonality for ferroelectric thin films. All of the results described above feature in-situ synchrotron X-ray scattering as the main experimental method, which has become an indispensable technique for observing the kinetics of structures forming in real-time. We have also investigated in-situ coherent X-ray scattering and have developed methods to characterize temporal correlations that are not possible to observe with low-coherence X-rays. A high profile result of this work is a new technique to monitor defect propagation velocities in thin films. This has practical significance since defects limit the properties of thin films and it is desirable to understand their properties and origin in order to control them for practical applications. More broadly, amorphous thin films and multilayers have applications in optical devices, including mirrors and filters. Epitaxial thin films and multilayers have applications in electronic devices such as ferroelectric multilayers for non-volatile data storage, and thermoelectric nanostructures for energy conversion. Our progress in this project points the way for improved deposition methods and for improved simulation and modeling of thin film deposition processes for nanoscale control of materials with novel applications in these areas.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Sensor network based solar forecasting using a local vector autoregressive ridge framework

The significant improvements and falling costs of photovoltaic (PV) technology make solar energy a promising resource, yet the cloud induced variability of surface solar irradiance inhibits its effective use in grid-tied PV generation. Short-term irradiance forecasting, especially on the minute scale, is critically important for grid system stability and auxiliary power source management. Compared to the trending sky imaging devices, irradiance sensors are inexpensive and easy to deploy but related forecasting methods have not been well researched. The prominent challenge of applying classic time series models on a network of irradiance sensors is to address their varying spatio-temporal correlations due to local changes in cloud conditions. We propose a local vector autoregressive framework with ridge regularization to forecast irradiance without explicitly determining the wind field or cloud movement. By using local training data, our learned forecast model is adaptive to local cloud conditions and by using regularization, we overcome the risk of overfitting from the limited training data. Our systematic experimental results showed an average of 19.7% RMSE and 20.2% MAE improvement over the benchmark Persistent Model for 1-5 minute forecasts on a comprehensive 25-day dataset.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Inferring Organizational Structure from Behavior

In this project, we researched new techniques for detecting hidden networks of individuals and institutions by introducing the use of temporal correlations among behaviors, leveraging both information sources and metadata. We validated the algorithms using the Wikipedia edit history. The rapid increase in crowd-sourced applications like Wikipedia is providing a rich set of data with both a record of behaviors and a set of direct interactions among individuals. Data sets with network ground truth are needed to develop and validate models, before applying them to national security settings where content and meta-data alone are available.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

19-LW-045 Full Length Final Report. Molecular Mechanisms of Bacterial Pathogenesis: Waging the Arms Race with Superbugs

As the current global pandemic makes abundantly clear, we need a better understanding of infectious disease to safeguard human health, the economy and global security. Modern omics techniques hold the promise of providing a comprehensive understanding of the molecular mechanisms of life, including causes of pathogenesis from infectious disease at the molecular level, but we there is a serious gap in annotation of gene function. For as much as half of the genes and gene products encoded in genomes the molecular and/or cellular function is unknown or only partially understood. Recent innovations in fluorescence microscopy for live cell imaging and genetic engineering make it possible to determine the temporal correlation between molecular events, such as a gene being expressed due to host-pathogen interaction, and cellular events, such as bacterial invasion of immune cells. This is turn allows us to gain new insight as to the molecular and cellular role of individual genes and will enable the discovery and validation of new molecular mechanisms essential for infectious disease. Knowing the molecular mechanisms of disease processes will provide new therapeutic targets or novel countermeasure strategies. We aimed to develop a lattice light sheet fluorescence microscope as a unique resource at LLNL for long time course live cell imaging experiments; to develop the reagents and cell lines needed to monitor molecular events during the course pathogenic bacteria infecting mammalian immune cells; and to demonstrate that we could capture molecular events during an infection. We fully commissioned the LLNL lattice light sheet microscope and conducted initial proof of principle imaging experiments on mammalian immune cells and pathogenic bacteria. It is clear from the experience gained that long time course live cell imaging has tremendous potential to help elucidate molecular mechanisms of host-pathogen interactions and to help annotate gene function, which would establish a basis for new countermeasures. It is also clear that if live cell imaging is to realize its full potential new data processing and analysis tools will need to be developed to facilitate analysis of molecular events within cells; new sample chambers and stages could facilitate studies with a wider range of cell and tissue types; and alternative molecular tagging methods need to be explored to enable more facile engineering of cells labeled with molecular specificity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Cryogenic Platforms at Fermilab: Recent Results and Outlook

The Cosmic Quantum group at Fermilab operates three cryogenic facilities dedicated to the development and calibration of superconducting low-threshold detectors and qubits. One of which (LOUD) is located at the surface, while the other two (NEXUS and QUIET) are located 100 m underground enabling low-background device characterization and rare event searches. Recently, we have demonstrated world-leading resolution in the quasiparticle channel for kinetic inductance phonon-mediated detectors as well as the lowest rate of spatially- and temporally- correlated errors ( charge jumps ) in superconducting qubit chips. We have additionally made significant progress in expanding the suite of tools for simulating signal production and readout of these devices. In this talk, I will review these recent results, discuss some nascent projects focused on enhancing sensitivity of these detectors to sub-GeV dark matter, and highlight activities in these facilities over the next year.

Temples, Dylan J.↗
DOE OSTI2026

TLS characterization using multilevel decay of a fixed-frequency transmon

Transmon qubits are a cornerstone of superconducting quantum computing platforms, yet their coherence times often exhibit temporal fluctuations that degrade processor performance. These variations are commonly attributed to shifts in the resonance frequencies of individual two-level systems (TLSs) near the qubit transition. In this study, we monitor the lifetimes of multiple energy levels of a fixed-frequency transmon and examine their temporal correlations. Our measurements reveal that one or more TLSs—detuned by more than 100 MHz from the qubit transition—can still significantly influence coherence. The proposed method provides a powerful tool for TLS spectroscopy without the need to tune the transmon frequency, either via a flux-tunable inductor or AC-Stark shifts.

Roy, Tanay [Fermilab] (ORCID:000000019442862X)↗
DOE OSTI2026

TLS characterization using multilevel decay of a fixed-frequency transmon

Transmon qubits are a cornerstone of superconducting quantum computing platforms, yet their coherence times often exhibit temporal fluctuations that degrade processor performance. These variations are commonly attributed to shifts in the resonance frequencies of individual two-level systems (TLSs) near the qubit transition. In this study, we monitor the lifetimes of multiple energy levels of a fixed-frequency transmon and examine their temporal correlations. Our measurements reveal that one or more TLSs—detuned by more than 100 MHz from the qubit transition—can still significantly influence coherence. The proposed method provides a powerful tool for TLS spectroscopy without the need to tune the transmon frequency, either via a flux-tunable inductor or AC-Stark shifts.

Roy, Tanay [Fermilab] (ORCID:000000019442862X)↗
DOE OSTI2022

Intracardiac Electrical Imaging using the 12-lead ECG: A Machine Learning Approach using Synthetic Data

Current state-of-the-art techniques for non-invasive imaging of cardiac electrical phenomena require voltage recordings from dozens of different torso locations and anatomical models built from expensive medical diagnostic imaging procedures. Here this study aimed to assess if recent machine learning advances could alternatively reconstruct electroanatomical maps at clinically relevant resolutions using only the standard 12-lead electrocardiogram (ECG) as input. To that end, a computational study was conducted to generate a dataset of over 16000 detailed cardiac simulations, which was then used to train neural network (NN) architectures designed to exploit both spatial and temporal correlations in the ECG signal. Analysis over a validation set showed average errors in activation map reconstruction below 1.7 msec over 75 intracardiac locations. Furthermore, phenotypical patterns of activation and the morphology of the activation potential were correctly reconstructed. The approach offers opportunities to stratify patients non-invasively, both retrospectively and prospectively, using metrics otherwise only available through invasive clinical procedures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Heterogeneous Multi-Domain Dataset Synthesis to Facilitate Privacy and Risk Assessments in Smart City IoT

The emergence of the Smart Cities paradigm and the rapid expansion and integration of Internet of Things (IoT) technologies within this context have created unprecedented opportunities for high-resolution behavioral analytics, urban optimization, and context-aware services. However, this same proliferation intensifies privacy risks, particularly those arising from cross-modal data linkage across heterogeneous sensing platforms. To address these challenges, this paper introduces a comprehensive, statistically grounded framework for generating synthetic, multimodal IoT datasets tailored to Smart City research. The framework produces behaviorally plausible synthetic data suitable for preliminary privacy risk assessment and as a benchmark for future re-identification studies, as well as for evaluating algorithms in mobility modeling, urban informatics, and privacy-enhancing technologies. As part of our approach, we formalize probabilistic methods for synthesizing three heterogeneous and operationally relevant data streams—cellular mobility traces, payment terminal transaction logs, and Smart Retail nutrition records—capturing the behaviors of a large number of synthetically generated urban residents over a 12-week period. The framework integrates spatially explicit merchant selection using K-Dimensional (KD)-tree nearest-neighbor algorithms, temporally correlated anchor-based mobility simulation reflective of daily urban rhythms, and dietary-constraint filtering to preserve ecological validity in consumption patterns. In total, the system generates approximately 116 million mobility pings, 5.4 million transactions, and 1.9 million itemized purchases, yielding a reproducible benchmark for evaluating multimodal analytics, privacy-preserving computation, and secure IoT data-sharing protocols. To show the validity of this dataset, the underlying distributions of these residents were successfully validated against reported distributions in published research. We present preliminary uniqueness and cross-modal linkage indicators; comprehensive re-identification benchmarking against specific attack algorithms is planned as future work. This framework can be easily adapted to various scenarios of interest in Smart Cities and other IoT applications. By aligning methodological rigor with the operational needs of Smart City ecosystems, this work fills critical gaps in synthetic data generation for privacy-sensitive domains, including intelligent transportation systems, urban health informatics, and next-generation digital commerce infrastructures.

IoT↗
DOE OSTI2026

Monitoring of Liquid Metal Reactor Heater Zones with Recurrent Neural Network Learning of Temperature Time Series

Advanced high-temperature fluid reactors (ARs), such as sodium fast reactors (SFRs) and molten salt cooled reactors (MSCRs) utilize high-temperature fluids at ambient pressure. To melt the fluid during reactor startup and prevent fluid freezing during cooldown, the thermal–hydraulic systems of such ARs include heater zones consisting of specific heaters with controllers, temperature sensors, and thermal insulation. The failure of heater zones due to insulation material degradation or improper installation, resulting in parasitic heat losses, can lead to fluid freezing. The detection of faults using a heat-transfer model is difficult because of a lack of knowledge of the experimental details. Data-driven machine learning of heater zone temperature time series offers a viable alternative. In this study, we benchmarked the performance of recurrent neural networks (RNNs) in an analysis of heat-up transient temperature time series of heater zones installed on a liquid sodium vessel. The RNN models include long short-term memory (LSTM) and gated recurrent unit (GRU) networks, as well as their bi-directional variants, BiLSTM and BiGRU. Anomalous temperature points were designated using a percentile-based threshold applied to residual fluctuations in the detrended temperature time series. Additionally, the impact of the exponentially weighted moving average (EWMA) method on detection accuracy was examined. The RNN models’ performance was assessed using precision, recall, and F 1 score metrics. Results demonstrated that RNN models effectively detect anomalies in temperature time series with the best models for each heater zone achieving F 1 scores of over 93%. To explain the variations in RNN model performance across different heater zones, we used Kullback–Leibler (KL) divergence to quantify the relative entropy between training and testing data, and the Detrended Fluctuation Analysis (DFA) to assess long-range temporal correlations. For datasets with strong long-range correlations and minimal relative entropy between training and testing data, GRU is the best-performing model. When the data exhibits weaker long-term correlations and a significant relative entropy between training and testing distributions, BiGRU shows the best performance. For the data sets with intermediate values of both KL divergence and DFA, the best performance is obtained with LSTM and BiLSTM, respectively.

gated recurrent unit↗
DOE OSTI2016

NEW SUNS IN THE COSMOS. III. MULTIFRACTAL SIGNATURE ANALYSIS

In the present paper, we investigate the multifractality signatures in hourly time series extracted from the CoRoT spacecraft database. Our analysis is intended to highlight the possibility that astrophysical time series can be members of a particular class of complex and dynamic processes, which require several photometric variability diagnostics to characterize their structural and topological properties. To achieve this goal, we search for contributions due to a nonlinear temporal correlation and effects caused by heavier tails than the Gaussian distribution, using a detrending moving average algorithm for one-dimensional multifractal signals (MFDMA). We observe that the correlation structure is the main source of multifractality, while heavy-tailed distribution plays a minor role in generating the multifractal effects. Our work also reveals that the rotation period of stars is inherently scaled by the degree of multifractality. As a result, analyzing the multifractal degree of the referred series, we uncover an evolution of multifractality from shorter to larger periods.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The Statistics of Radio Astronomical Polarimetry: Disjoint, Superposed, and Composite Samples

A statistical framework is presented for the study of the orthogonally polarized modes of radio pulsar emission via the covariances between the Stokes parameters. To accommodate the typically heavy-tailed distributions of single-pulse radio flux density, the fourth-order joint cumulants of the electric field are used to describe the superposition of modes with arbitrary probability distributions. The framework is used to consider the distinction between superposed and disjoint modes, with particular attention to the effects of integration over finite samples. If the interval over which the polarization state is estimated is longer than the timescale for switching between two or more disjoint modes of emission, then the modes are unresolved by the instrument. The resulting composite sample mean exhibits properties that have been attributed to mode superposition, such as depolarization. Because the distinction between disjoint modes and a composite sample of unresolved disjoint modes depends on the temporal resolution of the observing instrumentation, the arguments in favor of superposed modes of pulsar emission are revisited, and observational evidence for disjoint modes is described. In principle, the four-dimensional covariance matrix that describes the distribution of sample mean Stokes parameters can be used to distinguish between disjoint modes, superposed modes, and a composite sample of unresolved disjoint modes. More comprehensive and conclusive interpretation of the covariance matrix requires more detailed consideration of various relevant phenomena, including temporally correlated subpulse modulation (e.g., jitter), statistical dependence between modes (e.g., covariant intensities and partial coherence), and multipath propagation effects (e.g., scintillation and scattering).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

IRIS , Hinode , SDO , and RHESSI Observations of a White Light Flare Produced Directly by Non-thermal Electrons

An X1.6 flare occurred in active region AR 12192 on 2014 October 22 at 14:02 UT and was observed by Hinode , IRIS , SDO , and RHESSI . We analyze a bright kernel that produces a white light (WL) flare with continuum enhancement and a hard X-ray (HXR) peak. Taking advantage of the spectroscopic observations of IRIS and Hinode /EIS, we measure the temporal variation of the plasma properties in the bright kernel in the chromosphere and corona. We find that explosive evaporation was observed when the WL emission occurred, even though the intensity enhancement in hotter lines is quite weak. The temporal correlation of the WL emission, HXR peak, and evaporation flows indicates that the WL emission was produced by accelerated electrons. To understand the WL emission process, we calculated the energy flux deposited by non-thermal electrons (observed by RHESSI ) and compared it to the dissipated energy estimated from a chromospheric line (Mg ii triplet) observed by IRIS . The deposited energy flux from the non-thermal electrons is about (3–7.7) × 10{sup 10} erg cm{sup −2} s{sup −1} for a given low-energy cutoff of 30–40 keV, assuming the thick-target model. The energy flux estimated from the changes in temperature in the chromosphere measured using the Mg ii subordinate line is about (4.6–6.7) × 10{sup 9} erg cm{sup −2} s{sup −1}: ∼6%–22% of the deposited energy. This comparison of estimated energy fluxes implies that the continuum enhancement was directly produced by the non-thermal electrons.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Triggering Process of the X1.0 Three-ribbon Flare in the Great Active Region NOAA 12192

The solar magnetic field in a flare-producing active region (AR) is much more complicated than theoretical models, which assume a very simple magnetic field structure. The X1.0 flare, which occurred in AR 12192 on 2014 October 25, showed a complicated three-ribbon structure. To clarify the trigger process of the flare and to evaluate the applicability of a simple theoretical model, we analyzed the data from Hinode /Solar Optical Telescope and the Solar Dynamics Observatory /Helioseismic and Magnetic Imager, Atmospheric Imaging Assembly. We investigated the spatio-temporal correlation between the magnetic field structures, especially the non-potentiality of the horizontal field, and the bright structures in the solar atmosphere. As a result, we determined that the western side of the positive polarity, which is intruding on a negative polarity region, is the location where the flare was triggered. This is due to the fact that the sign of the magnetic shear in that region was opposite that of the major shear of the AR, and the significant brightenings were observed over the polarity inversion line (PIL) in that region before flare onset. These features are consistent with the recently proposed flare-trigger model that suggests that small reversed shear (RS) magnetic disturbances can trigger solar flares. Moreover, we found that the RS field was located slightly off the flaring PIL, contrary to the theoretical prediction. We discuss the possibility of an extension of the RS model based on an extra numerical simulation. Our result suggests that the RS field has a certain flexibility for displacement from a highly sheared PIL, and that the RS field triggers more flares than we expected.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

New Evidence for a Coronal Mass Ejection-driven High Frequency Type II Burst near the Sun

We report observations of the high frequency type II radio burst (≈430–30 MHz) that occurred in the solar corona on 2015 November 4. The drift rate of the burst, estimated close to the start frequency of its fundamental component (≈215 MHz), is unusually high (≈2 MHz s{sup −1}). Our analysis shows that the estimated speed of the magnetohydrodynamic shock driver of the burst varies with time. The peak speed and acceleration are very large, ≈2450 km s{sup −1} and ≈17 km s{sup −2}, respectively. There is spatio-temporal correlation between the type II burst and the associated coronal mass ejection (CME) in the whitelight and extreme-ultraviolet images. The time profile of the shock speed and the light curve of the associated soft X-ray flare correlate well. These results indicate that in the present case, (i) the magnetohydrodynamic shock responsible for the high frequency coronal type II burst is driven by the CME and (ii) the time profile of the type II burst shock speed represents the near-Sun kinematics of the CME.

79 ASTRONOMY AND ASTROPHYSICS↗