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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Tracking oxygen vacancy migration in memristor devices using operando hard X-ray photoelectron spectroscopy

Fabrication of ultrathin (sub-2 nm) oxide semiconductor memristors poses the fundamental challenge of achieving oxide growth with atomic precision in terms of electronic structure and defect formation. Recently, ultrathin memristors consisting of bilayers of mixed Al 2 O 3 and MgO atomic layers were fabricated using an in vacuo atomic layer deposition process. This approach offers a unique platform for precise atomic control of oxygen vacancies in the device in which the vacancies are introduced by placing MgO atomic layers between pristine Al 2 O 3 layers. In this work, we present a systematic operando Hard X-ray PhotoElectron Spectroscopy (HAXPES) study of the switching of such memristors, combined with complementary current-voltage and capacitance-voltage (C-V) measurements. We used a memristor stack of Al 2 O 3 /MgO atomic layers, with the MgO-containing oxide deposited on the bottom Al metal electrode and a pure Al 2 O 3 layer below the top Pd electrode. HAXPES analysis shows a substantial change in the chemical shift of the Aluminum oxide when switching between the ”OFF” and ”ON” states indicative of a redistribution of oxygen vacancies in the device active layer. Interestingly, subsequent switching to the OFF state shows hysteretic behavior indicating the retention of some oxygen vacancies in the top Al 2 O 3 layer. This vacancy retention can be correlated with the stochastic behavior of the switching voltage observed in these devices. C–V measurements show a clear frequency-dependent response in the OFF state, consistent with enhanced polarization and vacancy trapping at low frequencies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

miss-SNF: a multimodal patient similarity network integration approach to handle completely missing data sources

Abstract Motivation Precision medicine leverages patient-specific multimodal data to improve prevention, diagnosis, prognosis, and treatment of diseases. Advancing precision medicine requires the non-trivial integration of complex, heterogeneous, and potentially high-dimensional data sources, such as multi-omics and clinical data. In the literature, several approaches have been proposed to manage missing data, but are usually limited to the recovery of subsets of features for a subset of patients. A largely overlooked problem is the integration of multiple sources of data when one or more of them are completely missing for a subset of patients, a relatively common condition in clinical practice. Results We propose miss-Similarity Network Fusion (miss-SNF), a novel general-purpose data integration approach designed to manage completely missing data in the context of patient similarity networks. miss-SNF integrates incomplete unimodal patient similarity networks by leveraging a non-linear message-passing strategy borrowed from the SNF algorithm. miss-SNF is able to recover missing patient similarities and is “task agnostic”, in the sense that can integrate partial data for both unsupervised and supervised prediction tasks. Experimental analyses on nine cancer datasets from The Cancer Genome Atlas (TCGA) demonstrate that miss-SNF achieves state-of-the-art results in recovering similarities and in identifying patients subgroups enriched in clinically relevant variables and having differential survival. Moreover, amputation experiments show that miss-SNF supervised prediction of cancer clinical outcomes and Alzheimer’s disease diagnosis with completely missing data achieves results comparable to those obtained when all the data are available. Availability and implementation miss-SNF code, implemented in R, is available at https://github.com/AnacletoLAB/missSNF.

Biochemistry & Molecular Biology↗
DOE OSTI2024

Enhanced material identification via momentum-integrated muon scattering tomography

Cosmic ray muons, originating from interactions in the upper atmosphere, possess high energy and unique penetrative capabilities suitable for non-traditional radiographic inspection. This study explores their application in various fields such as nuclear fuel cask monitoring, nuclear reactor imaging, and archaeology, leveraging the principle of multiple Coulomb scattering for imaging dense materials. While muon scattering tomography has shown promise, accurately measuring muon momentum remains challenging. This research introduces the Momentum Integrated Point-of-Closest Approach (mPoCA) algorithm, integrating muon momentum data into the traditional Point-of-Closest Approach (PoCA) framework. Utilizing the Cherenkov muon spectrometer, renowned for precise muon momentum estimation, the mPoCA algorithm offers a novel imaging approach. Simulations conducted with GEANT4 evaluate the mPoCA algorithm’s performance against the standard PoCA method, demonstrating superior image resolution and enhanced material identification capabilities, particularly in distinguishing materials like uranium and lead. These findings underscore the potential of the mPoCA algorithm for advancing muon scattering tomography applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A multimodal and integrated approach to interrogate human kidney biopsies with rigor and reproducibility: guidelines from the Kidney Precision Medicine Project

Comprehensive and spatially mapped molecular atlases of organs at a cellular level are a critical resource to gain insights into pathogenic mechanisms and personalized therapies for diseases. The Kidney Precision Medicine Project (KPMP) is an endeavor to generate three-dimensional (3-D) molecular atlases of healthy and diseased kidney biopsies by using multiple state-of-the-art omics and imaging technologies across several institutions. Obtaining rigorous and reproducible results from disparate methods and at different sites to interrogate biomolecules at a single-cell level or in 3-D space is a significant challenge that can be a futile exercise if not well controlled. Here we describe a “follow the tissue” pipeline for generating a reliable and authentic single-cell/region 3-D molecular atlas of human adult kidney. Our approach emphasizes quality assurance, quality control, validation, and harmonization across different omics and imaging technologies from sample procurement, processing, storage, shipping to data generation, analysis, and sharing. We established benchmarks for quality control, rigor, reproducibility, and feasibility across multiple technologies through a pilot experiment using common source tissue that was processed and analyzed at different institutions and different technologies. A peer review system was established to critically review quality control measures and the reproducibility of data generated by each technology before their being approved to interrogate clinical biopsy specimens. The process established economizes the use of valuable biopsy tissue for multiomics and imaging analysis with stringent quality control to ensure rigor and reproducibility of results and serves as a model for precision medicine projects across laboratories, institutions and consortia.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Solving high-dimensional partial integral differential equations: The finite expression method

Partial integro-differential equations (PIDEs) have broad applications in the sciences, from electro-magnetism to options pricing. Here, in this paper, we introduce a new finite expression method (FEX) to solve PIDEs. This approach builds upon the original FEX and its inherent advantages with new advances: 1) A novel method of parameter grouping is proposed to reduce the number of coefficients in high-dimensional function approximation; 2) A Taylor series approximation method is implemented to significantly improve the computational efficiency and accuracy of the evaluation of the integral terms of PIDEs. The new FEX based method, denoted FEX-PG to indicate the addition of the parameter grouping (PG) step to the algorithm, provides both high accuracy and interpretable numerical solutions, with the outcome being an explicit equation that facilitates intuitive understanding of the underlying solution structures. These features are often absent in traditional methods, such as finite element methods (FEM) and finite difference methods, as well as in deep learning-based approaches. To benchmark our method against recent advances, we apply the new FEX-PG to solve benchmark PIDEs in the literature. In high-dimensional settings, FEX-PG exhibits strong and robust performance, achieving relative errors on the order of single precision machine epsilon, significantly outperforming existing approaches based on neural networks.

Combinatorial optimization↗
DOE OSTI2021

Improved control of atomic layering in perovskite-related homologous series

Homologous series are layered phases that can have a range of stoichiometries depending on an index n. Examples of perovskite-related homologous series include (ABO 3 )nAO Ruddlesden–Popper phases and (Bi 2 O 2 ) (A n-1 B n O 3n+1 ) Aurivillius phases. It is challenging to precisely control n because other members of the homologous series have similar stoichiometry and a phase with the desired n is degenerate in energy with syntactic intergrowths among similar n values; this challenge is amplified as n increases. To improve the ability to synthesize a targeted phase with precise control of the atomic layering, we apply the x-ray diffraction (XRD) approach developed for superlattices of III–V semiconductors to measure minute deviations from the ideal structure so that they can be quantitatively eradicated in subsequent films. We demonstrate the precision of this approach by improving the growth of known Ruddlesden–Popper phases and ultimately, by synthesizing an unprecedented n = 20 Ruddlesden–Popper phase, (ATiO 3 ) 20 AO where the A-site occupancy is Ba 0.6 Sr 0.4 . We demonstrate the generality of this method by applying it to Aurivillius phases and the Bi 2 Sr 2 Ca n–1 Cu n O 2n+4 series of high-temperature superconducting phases.

36 MATERIALS SCIENCE↗
NASA NTRS1976

A study to determine the characteristic shapes of helicopter visual approach profiles

On previous helicopter instrument approach studies, pilot comments frequently indicated that the deceleration profiles were characterized by 'unnatural cues', and it was found that the pilots were comparing the motion and attitude cues with those obtained during visual approaches. Prior to this study, the characteristic shape of visual approach profiles had not been formally documented. Over 200 visual approaches were flown using different helicopter types, test subjects, and initial conditions, and the altitude and groundspeed profiles were measured by a precision tracking radar. The data from each approach were then processed, and the characteristic shape of the altitude, groundspeed, and deceleration profiles was determined for each set of initial conditions. These flight data were processed further using graphical analysis techniques and parameterization, which, in turn, led to developing closed-form equations that accurately describe the characteristic groundspeed and deceleration profiles. Results from this study can be used to select instrument approach profiles, to develop instrument approach control laws, and to define the corresponding hardware requirements.

Moen, G. C.↗
NASA NTRS2011

LIDAR-Aided Inertial Navigation with Extended Kalman Filtering for Pinpoint Landing

In support of NASA s Autonomous Landing and Hazard Avoidance Technology (ALHAT) project, an extended Kalman filter routine has been developed for estimating the position, velocity, and attitude of a spacecraft during the landing phase of a planetary mission. The proposed filter combines measurements of acceleration and angular velocity from an inertial measurement unit (IMU) with range and Doppler velocity observations from an onboard light detection and ranging (LIDAR) system. These high-precision LIDAR measurements of distance to the ground and approach velocity will enable both robotic and manned vehicles to land safely and precisely at scientifically interesting sites. The filter has been extensively tested using a lunar landing simulation and shown to improve navigation over flat surfaces or rough terrain. Experimental results from a helicopter flight test performed at NASA Dryden in August 2008 demonstrate that LIDAR can be employed to significantly improve navigation based exclusively on IMU integration.

Busnardo, David M.↗
DOE OSTI2021

The Swan: Data-driven Inference of Stellar Surface Gravities for Cool Stars from Photometric Light Curves

Stellar light curves are well known to encode physical stellar properties. Precise, automated, and computationally inexpensive methods to derive physical parameters from light curves are needed to cope with the large influx of these data from space-based missions such as Kepler and TESS. Here we present a new methodology that we call “The Swan,” a fast, generalizable, and effective approach for deriving stellar surface gravity (logg) for main-sequence, subgiant, and red giant stars from Kepler light curves using local linear regression on the full frequency content of Kepler long-cadence power spectra. With this inexpensive data-driven approach, we recover logg to a precision of ~0.02 dex for 13,822 stars with seismic logg values between 0.2 and 4.4 dex and ~0.11 dex for 4646 stars with Gaia-derived logg values between 2.3 and 4.6 dex. We further develop a signal-to-noise metric and find that granulation is difficult to detect in many cool main-sequence stars (T {sub eff} ≲ 5500 K), in particular K dwarfs. By combining our logg measurements with Gaia radii, we derive empirical masses for 4646 subgiant and main-sequence stars with a median precision of ~7%. Finally, we demonstrate that our method can be used to recover logg to a similar mean absolute deviation precision for a TESS baseline of 27 days. Our methodology can be readily applied to photometric time series observations to infer stellar surface gravities to high precision across evolutionary states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

The two-point correlation function covariance with fewer mocks

We present FITCOV an approach for accurate estimation of the covariance of two-point correlation functions that requires fewer mocks than the standard mock-based covariance. This can be achieved by dividing a set of mocks into jackknife regions and fitting the correction term first introduced in Mohammad & Percival (2022), such that the mean of the jackknife covariances corresponds to the one from the mocks. This extends the model beyond the shot-noise limited regime, allowing it to be used for denser samples of galaxies. We test the performance of our fitted jackknife approach, both in terms of accuracy and precision, using lognormal mocks with varying densities and approximate EZmocks mimicking the Dark Energy Spectroscopic Instrument LRG and ELG samples in the redshift range of z = [0.8, 1.1]. We find that the Mohammad–Percival correction produces a bias in the two-point correlation function covariance matrix that grows with number density and that our fitted jackknife approach does not. We also study the effect of the covariance on the uncertainty of cosmological parameters by performing a full-shape analysis. We demonstrate that our fitted jackknife approach based on 25 mocks can recover unbiased and as precise cosmological parameters as the ones obtained from a covariance matrix based on 1000 or 1500 mocks, while the Mohammad–Percival correction produces uncertainties that are twice as large.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1994

Time transfer using geostationary satellites: Implementation of a Kalman filter

Since 1988, various experiments have shown that the TV signals transmitted by direct TV satellites may easily be used to perform time transfers at the level of a few tens of nanoseconds, the main source of error being the uncertainty on the satellite position. We first present the two methods used in our experiment to reduce the effects of the satellite residual motion: the first one consists in estimating the longitude variations of the satellite and then using this information to improve other measurements. This allows reducing the uncertainty to values between 9 and 50 nanoseconds according to the position of the involved stations. In the second method we determine the satellite position by using the data collected by three calibrated stations. Time transfer between each of these stations and a fourth one has been shown to be achievable at the precision level of ten nanoseconds. A new approach based on the use of a Kalman filter is proposed in order to take into account the dynamics of the geostationary satellite. The precisions on orbital elements and clock differences and rates determination given by the first simulated applications of the Kalman filter are presented and compared to those obtained by the other methods.

Meyer, F.↗
NASA NTRS1999

Detection of O VII Lambda 1522 in IUE Spectra of Planetary Nebula Nuclei and Other Hot Stars

We present the first detection of O VII lambda 1522 emission or absorption from archival IUE spectra in 14 planetary nebula nuclei and three PG 1159-type stars. The n = 5 approaching 6 transition of O VII was determined by Kruk & Werner and observed by them in the spectrum of the very hot PG 1159-type star H1504+65 from data obtained with the Hopkins Ultraviolet Telescope (HUT). Emission-line fluxes or absorption equivalent widths as well as radial velocities for the program stars are presented. The precise rest wavelength for the 5 approaching 6 transition requires further investigation.

Feibelman, Walter A.↗
NASA NTRSDate not supplied

Fast and Precise Trajectory Simulation for Entry, Descent, and Landing Using A Multi-Model Monte Carlo Approach

Predicting landing radius and other quantities of interest (QoI) for entry, descent, and landing (EDL) applications requires a viable uncertainty propagation method for quantifying the impact of uncertainties in wind pattern variations, atmospheric uncertainties, etc. While standard MC simulation is the defacto standard for providing robust and unbiased predictions,it is often infeasible for expensive, high-fidelity EDL models. Low-fidelity models are commonly constructed to replace the high-fidelity model in MC simulation for computational speedup,but at the expense of accuracy and unbiasedness. Emerging multi-model MC methods are bridging this gap by combining predictions from two or more models of varying fidelity and computational cost for efficient and unbiased uncertainty propagation. This work explores the use of multi-model MC for increasing the speed and precision of trajectory simulation for EDL. It is shown that combining a high-fidelity EDL model with low-fidelity models (e.g,data-driven, reduced physics) yields substantial computational speedup versus standard MCwith only the high-fidelity model. Moreover, the unbiasedness of multi-model MC predictions is highlighted by showing increased accuracy versus an approach that leverages a low-fidelity surrogate model alone.

James E. Warner↗
DOE OSTI2022

Throughput-Oriented and Accuracy-Aware DNN Training with BFloat16 on GPU

Deep Neural Networks (DNNs) have transformed the field of artificial intelligence and achieved extraordinary success in many areas. The training of DNNs is commonly compute and memory-intensive, which has resulted in several optimizations in the training phase. Among them, reduced precision is a typical and widely used technique to accelerate DNN training and reduce memory requirements. However, applying a widely adopted reduced precision format such as Float16 to all involved operations in DNN training is not optimal as the use of Float16 in some operations can hurt model accuracy. Meanwhile, additional optimizations including loss scaling and autocast techniques can mitigate the accuracy loss but lead to inherent overhead and inadequate use of reduced precision. In this work, we leverage another reduced precision format, BFloat16, and introduce a throughput-oriented and accuracy-aware approach to maximize the performance potential of DNN training. Since the high throughput provided by BFloat16 format is accompanied by low precision of the floating-point representation, this approach achieves high throughput by using BFloat16 on all DNN operations and avoids the accuracy loss through a customized accuracy-aware normalization. Results show that our approach outperforms the state-of-the-art mixed-precision training by 1.21x on an NVIDIA A100 GPU.

Xie, Zhen↗
DOE OSTI2025

High-efficiency frost and ice control via sensing-assisted nanovibrational slippery surfaces

Frost and ice accretions on surfaces pose persistent challenges across numerous industrial, residential and transportation systems. While various removal strategies exist, they often suffer from limited effectiveness or high energy consumption, such as frosting delay, ice crack generation, and Joule heating. Here, in this work, we report a novel integrated approach combining vibrational quasi-liquid surface (QLS) and capacitive sensing for efficient condensate, frost, and ice management. Compared to Joule heating, our approach does not rely on complete melting and evaporation for removal, resulting in 68% and 95% energy savings for frost and ice removal, respectively. Our QLS coating significantly reduces surface retention forces, achieving 91% and 87% less residual mass compared to hydrophilic surfaces for frost and ice removal through surface nanovibration, respectively. The integrated capacitive sensor provides real-time detection of different phase states, enabling on-demand removal in precise timeframes. This sensor-assisted approach showed 3.8 times lower energy consumption compared to conventional Joule heating for defrosting. This synergistic integration of surface engineering, nanovibration, and intelligent sensing represents a significant advancement in phase change processes, offering an energy-efficient solution for frost and ice mitigation in energy-intensive systems.

Shen, Yuchen [Univ. of Texas at Dallas, Richardson↗
NASA NTRS1991

Back Azimuth Guidance In Departures And Missed Approaches

Report describes studies conducted with pilots in flight simulator to examine use of front azimuth and back azimuth functions of microwave landing system (MLS) during precise departures immediately after takeoffs and during missed approaches. Studies provided data to determine optimum back azimuth signal sensitivity to establish operationally acceptable limits and procedures for use of back azimuth guidance, and to determine optimum technique for switching from front azimuth to back azimuth guidance.

Scott, Barry C.↗
NASA NTRS1998

New AFM Techniques for Investigating Molecular Growth Mechanisms of Protein Crystals

Atomic Force Microscopy (AFM) has emerged as a powerful technique for investigating protein crystal growth. Earlier AFM studies were among the first to demonstrate that these crystals grew by dislocation and 2D nucleation growth mechanisms [1]. These investigations were restricted to the micron range where only surface features, such as dislocation hillocks and 2D islands are visible. Most AFM instruments can scan at higher resolutions and have the potential to resolve individual protein molecules at nanometer ranges. Such scans are essential for determining the molecular packing arrangements on crystal faces and for probing the growth process at the molecular level. However, at this resolution the AFM tip influences the image produced, with the resulting image being a convolution of the tip shape and the surface morphology [2]. In most studies this problem is resolved by deconvoluting the image to obtain the true surface morphology. Although deconvolution routines work reasonably well for simple one- dimensional shapes, for complex surfaces this approach does not produce accurate results. In this study we devised a new approach which takes advantage of the precise molecular order of crystal surfaces, combined with the knowledge of individual molecular shapes from the crystallographic data of the protein and the AFM tip shape. This information is used to construct expected theoretical AFM images by convoluting the tip shape with the constructed crystal surface shape for a given surface packing arrangement. By comparing the images from actual AFM scans with the constructed ones for different possible surface packing arrangements, the correct packing arrangement can be conclusively determined. This approach was used in this study to determine the correct one from two possible packing arrangements on (I 10) faces of tetragonal lysozyme crystals. Another novel AFM technique was also devised to measure the dimension of individual growth units of the crystal faces. Measuring these units was not attempted before and most studies have assumed that the growth unit consisted of individual protein molecules. The linescan mode of AFM instruments allows the crystal surface to be scanned along a single line. By scanning across a growth step an image showing the motion of the step is obtained. Normally such an image shows a straight line for continuous and constant step velocity. In this study by increasing the scan rate and by decreasing the step velocity (by decreasing the supersaturation), we were able to capture images of individual growth events, shown by jump discontinuities in the step line. By suitable integration of the image the growth unit dimension in the scanned direction can be obtained. Since multiple units can be involved in the growth process it is necessary to collect a statistically relevant sample before drawing conclusions about the growth mechanism. This technique was successfully employed to obtain the dimensions of growth units for the (110) face, showing that they consisted of various aggregates corresponding to the 43 helices in the crystal structure.

Li, Huayu↗
NASA NTRS1979

Sampling for area estimation: A comparison of full-frame sampling with the sample segment approach

The effect of sampling on the accuracy (precision and bias) of crop area estimates made from classifications of LANDSAT MSS data was investigated. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plants. Four sampling schemes involving different numbers of samples and different size sampling units were evaluated. The precision of the wheat area estimates increased as the segment size decreased and the number of segments was increased. Although the average bias associated with the various sampling schemes was not significantly different, the maximum absolute bias was directly related to sampling unit size.

Hixson, M. M.↗