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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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All sources NASA NTRS DOE OSTI

DOE OSTI2025

Data-driven multi-element substitution of TiFe alloys for tunable thermodynamics and enhanced activation behaviour for hydrogen storage

Due to their high volumetric hydrogen storage capacity under moderate storage conditions, TiFe alloys have been widely investigated as candidates for practical solid-state hydrogen storage. Partially substituting Ti or Fe sites can improve the key characteristics of TiFe alloys, such as the first hydrogen absorption step (activation) and the equilibrium hydrogen pressure (thermodynamic properties). However, the selection of substitution elements has heavily relied on intuition and trial-and-error. Also, conventional substitution strategies have mainly focused on single-element substitution within the TiFe alloy, limiting the design space and tunability for target applications. Here, to address this limitation, we report a multi-element substitution strategy motivated by an efficient, data-driven machine learning (ML) approach combined with corroborating density functional theory (DFT) calculations. Our models successfully predict experimentally measured hydride stability in five selected alloys using only compositional descriptors. Most importantly, the multi-element substitution leads to enhanced activation properties compared to pure TiFe, achieving near room-temperature activation behaviour. This work provides a method for on-demand tuning of hydrogen storage and activation properties, which may have broad implications for data-driven discovery of energy storage materials.

Cho, YongJun [Korea Advanced Institute Science and↗

DOE OSTI2024

Methods for Causal Discovery

SAND2025-11742O Methods for Causal Discovery is a software tool that is used for causal discovery from data, including predicting and visualizing directed acyclic graphs from data using traditional machine learning techniques. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗

DOE OSTI2026

Quasars Acting as Strong Lenses Found in DESI DR1

Quasars acting as strong gravitational lenses offer a rare opportunity to probe the redshift evolution of scaling relations between supermassive black holes and their host galaxies, particularly the M$_{BH}$–M$_{host}$ relation. Using these powerful probes, the mass of the host galaxy can be precisely inferred from the Einstein radius θ$_{E}$. Using 812,118 quasars from DESI DR1 (0.03 ≤ z ≤ 1.8), we searched for quasars lensing higher-redshift galaxies by identifying background emission-line features in their spectra. To detect these rare systems, we trained a convolutional neural network (CNN) on mock lenses constructed from real DESI spectra of quasars and emission-line galaxies (ELGs), achieving a high classification performance (AUC = 0.99). We also trained a regression network to estimate the redshift of the background ELG. Applying this pipeline, we identified seven high-quality (Grade A) lens candidates, each exhibiting a strong [O II] doublet at a higher redshift than the foreground quasar; four candidates additionally show Hβ, [O III] λ4959, and [O III] λ5007 emission. These results significantly expand the sample of quasar lens candidates beyond the 12 identified and 3 confirmed in previous work and demonstrate the potential for scalable, data-driven discovery of quasars as strong lenses in upcoming spectroscopic surveys.

McArthur, Everett [Stanford U., Phys. Dept.; KIPAC↗

DOE OSTI2025

Enabling Early Transient Discovery in LSST via Difference Imaging with DECam

We present SLIDE, a pipeline that enables transient discovery in data from the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST), using archival images from the Dark Energy Camera as templates for difference imaging. We apply this pipeline to the recently released Data Preview 1 (DP1; the first public release of Rubin commissioning data) and search for transients in the resulting difference images. The image subtraction, photometry extraction, and transient detection are all performed on the Rubin Science Platform. We demonstrate that SLIDE effectively extracts clean photometry by circumventing poor or missing LSST templates. We identified 29 previously unreported transients, 12 of which would not have been detected based on the DP1 DiaObject catalog. SLIDE will be especially useful for transient analysis in the early years of LSST, when template coverage will be largely incomplete or when templates may be contaminated by transients present at the time of acquisition. We present multiband light curves for a sample of known transients, along with new transient candidates identified through our search. Finally, we discuss the prospects of applying this pipeline during the main LSST survey. Our pipeline is broadly applicable and will support studies of all transients with slowly evolving phases.

Dong, Yize 一泽董 [Harvard-Smithsonian Center for Ast↗

DOE OSTI2025

YeastWGD2025

Supplementary data for Discovery of additional ancient genome duplications in yeasts wgd_syn / - directory containing wgd syn output for all contiguous genomes [dataset] Tree - phylogeny [dataset]Duplications - duplication table from OrthoFinder output KOannotations - KEGG annotations used for enrichment analysis IPRannotations - InterPro annotations used for enrichment analysis DipodascalesOrthogroups - formatted orthogroup assignments for Dipodascales genes.fa and .gff3 files for each new genome assembly are also provided, those these are not required to replicate the analysis

Genomics↗

NASA NTRS1996

New observational facts about particle acceleration and transport during solar flares

Extensive hard X-ray (HXR)/gamma-ray (GR) observations of solar flares, performed during solar cycles 21 and 22 have led to important new discoveries. These data, combined with observations obtained in other parts of the electromagnetic spectrum (soft X-ray, Hard X-ray, optical, and radio) largley contributed to get a better understanding and to develop new ideas on particle acceleration and transport during solar flares. This review presents new observational facts relevant to hard X-ray/gamma-ray producing flares. Among these are the frequent presence of sub-second time structure in the hard X-ray emission, the variability in hard X-ray and radio spatial distributions during a flare and from flare to flare, the evidence for strong gamma-ray line emission from the Corona and the existence of extended phases of the gamma-ray emission lasting for several hours after the flare onset. This ensemble of observations indicates that particle acceleration takes place at different sites in a complex and dynamic magnetic field environment.

Trottel, G.↗

NASA NTRS2013

Fluid Vessel Quantity Using Non-invasive PZT Technology Flight Volume Measurements Under Zero G Analysis

The purpose of the project is to perform analysis of data using the Systems Engineering Educational Discovery (SEED) program data from 2011 and 2012 Fluid Vessel Quantity using Non-Invasive PZT Technology flight volume measurements under Zero G conditions (parabolic Plane flight data). Also experimental planning and lab work for future sub-orbital experiments to use the NASA PZT technology for fluid volume measurement. Along with conducting data analysis of flight data, I also did a variety of other tasks. I provided the lab with detailed technical drawings, experimented with 3d printers, made changes to the liquid nitrogen skid schematics, and learned how to weld. I also programmed microcontrollers to interact with various sensors and helped with other things going on around the lab.

Garofalo, Anthony A↗

NASA NTRS2013

Fluid Vessel Quantity using Non-Invasive PZT Technology Flight Volume Measurements Under Zero G Analysis

Garofalo, Anthony A.↗

NASA NTRS2013

Superorbital Periodic Modulation in Wind-Accretion High-Mass X-Ray Binaries from Swift Burst Alert Telescope Observations

We report the discovery using data from the Swift-Burst Alert Telescope (BAT) of superorbital modulation in the wind-accretion supergiant high-mass X-ray binaries 4U 1909+07 (= X 1908+075), IGR J16418−4532, and IGR J16479−4514. Together with already known superorbital periodicities in 2S 0114+650 and IGR J16493−4348, the systems exhibit a monotonic relationship between superorbital and orbital periods. These systems include both supergiant fast X-ray transients and classical supergiant systems, and have a range of inclination angles. This suggests an underlying physical mechanism which is connected to the orbital period. In addition to these sources with clear detections of superorbital periods, IGR J16393−4643 (= AX J16390.4−4642) is identified as a system that may have superorbital modulation due to the coincidence of low-amplitude peaks in power spectra derived from BAT, Rossi X-Ray Timing Explorer Proportional Counter Array, and International Gamma-Ray Astrophysics Laboratory light curves. 1E 1145.1−6141 may also be worthy of further attention due to the amount of low-frequency modulation of its light curve. However, we find that the presence of superorbital modulation is not a universal feature of wind-accretion supergiant X-ray binaries.

superorbital↗

NASA NTRS2014

Enhancement of Mutual Discovery, Search, and Access of Data for Users of NASA and GEOSS-Cataloged Data Systems

An ongoing NASA-funded Data Rods (time series) project has demonstrated the removal of a longstanding barrier to accessing NASA data (i.e., accessing archived time-step array data as point-time series) for selected variables of the North American and Global Land Data Assimilation Systems (NLDAS and GLDAS, respectively) and other NASA data sets. Data rods are pre-generated or generated on-the-fly (OTF), leveraging the NASA Simple Subset Wizard (SSW), a gateway to NASA data centers. Data rods Web services are accessible through the CUAHSI Hydrologic Information System (HIS) and the Goddard Earth Sciences Data and Information Services Center (GES DISC) but are not easily discoverable by users of other non-NASA data systems. An ongoing GEOSS Water Services project aims to develop a distributed, global registry of water data, map, and modeling services cataloged using the standards and procedures of the Open Geospatial Consortium and the World Meteorological Organization. Preliminary work has shown GEOSS can be leveraged to help provide access to data rods. A new NASA-funded project is extending this early work.

data access↗

NASA NTRS2014

Timing and Flux Evolution of the Galactic Center Magnetar SGR J1745-2900

We present the X-ray timing and spectral evolution of the Galactic Center magnetar SGR J1745-2900 (SGR*) for the first 4 months post-discovery using data obtained with the Nuclear Spectroscopic Telescope Array (NuSTAR) and Swift observatories. Our timing analysis reveals a large increase in the magnetar spin-down rate by a factor of 2.6 plus or minus 0.07 over our data span. We further show that the change in spin evolution was likely coincident with a bright X-ray burst observed in 2013 June by Swift, and if so, there was no accompanying discontinuity in the frequency. We find that the source 3 to 10 kiloelectronvolt flux has declined monotonically by a factor of approximately 2 over an 80-day period post-outburst accompanied by an approximately 20 percent decrease in the source's blackbody temperature, although there is evidence for both flux and kiloteslas having leveled off. We argue that the torque variations are likely to be magnetospheric in nature and will dominate over any dynamical signatures of orbital motion around Sgr A*.

Stars: magnetic field↗

NASA NTRS2019

NASA Earthdata Knowledge Base

Prototype work for connecting together the main elements of Earth Observation knowledge and context in a way that is: machine-readable, human-usable and curatable. Using the latest in graph technologies and cloud managed services.

earth data↗

NASA NTRSDate not supplied

Creating a knowledge graph to connect scientific publications and datasets for improving discovery of GES DISC’s data and services

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) archives and distributes to the public hundreds of Earth Science data collections. These collections are used in research, resulting in thousands of scientific papers published each year. As new users come to GES DISC for the data, it is important for them to understand how these data were used in the prior research. For this we are creating the Knowledge Graph that connects research paper citation and the data collection metadata. The relationships created in the graph have potential for the Web applications that utilize this information to directly connect the paper research to the GES DISC datasets and services. We will demonstrate these relationships using the Web application prototype.

Nathaniel Ross Crosby↗

NASA NTRSDate not supplied

NASA’s Unsteady Pressure-Sensitive Paint Research and Operational Capability Developments

To address challenges in the field of unsteady aerodynamics, NASA has developed a new state-of-the-art capability called Unsteady Pressure-Sensitive Paint (uPSP). It has been developed as an operational surface-pressure measurement capability for deployment in NASA’s AETC ground test facilities. Offering unprecedented spatiotemporal resolution, uPSP is an extremely powerful tool for investigating unsteady separated flows. To accelerate scientific discovery, uPSP data is to be processed and distributed as rapidly as it is acquired. Several demonstrations of the technology collected valuable data that has been used to develop data products, a robust processing pipeline, and other computational capabilities. A collection of papers documents the most recent research and development work on the uPSP technology and capability. This paper summarizes the current state of this effort at NASA.

Pressure-Sensitive Paint↗

NASA NTRSDate not supplied

The Science Discovery Engine: An Open Science Success Story

NASA is committed to building an inclusive open science community over the next decade and is championing the new Open-Source Science Initiative (OSSI) to foster that community. The OSSI is made up of a number of activities including the development of an empowering cyberinfrastructure to accelerate the time to actionable science. One component of the OSSI cyberinfrastructure is the Science Discovery Engine (SDE). The goal of the SDE is to enable the discovery of data, software and documentation across the five SMD divisions including Astrophysics, Biological and Physical Sciences, Earth Science, Heliophysics and Planetary Science. The SDE increases accessibility to the wealth of NASA’s open science data and information. In this presentation, we will present our collaborative work to date to build the SDE and our vision for empowering open source science in the future.

Kaylin Bugbee↗

NASA NTRSDate not supplied

NASA’s Unsteady Pressure-Sensitive Paint Research and Operational Capability Developments

To address challenges in the field of unsteady aerodynamics, NASA has developed a new stateof-the-art capability called Unsteady Pressure-Sensitive Paint (uPSP). It has been developed as an operational surface-pressure measurement capability for deployment in NASA’s AETC ground test facilities. Offering unprecedented spatiotemporal resolution, uPSP is an extremely powerful tool for investigating unsteady separated flows. To accelerate scientific discovery, uPSP data is to be processed and distributed as rapidly as it is acquired. Several demonstrations of the technology collected valuable data that has been used to develop data products, a robust processing pipeline, and other computational capabilities. A collection of papers documents the most recent research and development work on the uPSP technology and capability. This paper summarizes the current state of this effort at NASA.

Pressure-Sensitive Paint↗

NASA NTRSDate not supplied

SBIR Space Weather R2O2R Technology Development and Commercial Applications

The Small Business Innovation Research (SBIR) Program provides U.S. small businesses of 500 or fewer employees with the opportunity for early-stage funding for research and development. Through NASA's Science Mission Directorate, the SBIR subtopic S14.01 Space Weather Research-to-Operations-to-Research (R2O2R) Technology Development and Commercial Applications supports high-priority space weather needs as outlined in the National Space Weather Strategy and Action Plan (NSWSAP). There are four focus areas for which solutions are sought; these will be discussed (in no priority order): 1) space-weather forecasting technologies, techniques, and applications, 2) commercial and decision-making applications for space weather technologies, 3) space weather advanced data-driven discovery techniques, and 4) space-weather instrumentation.

Space weather↗

DOE OSTI2025

Understanding and Estimating Error Propagation in Neural Networks for Scientific Data Analysis

Neural networks are increasingly integrated into scientific discovery, where input data reduction and model quantization play a key role in accelerating inference. However, understanding and mitigating the impact of these techniques on output error is critical for ensuring reliable results, particularly in tasks demanding high numerical precision. This paper introduces a comprehensive framework for optimizing neural network inference in scientific computing by combining data reduction and weight quantization while maintaining error-controlled outcomes. We develop theoretical analyses to bound error propagation under these reductions and propose a framework that balances computational performance with error constraints. Evaluation on real-world learning-based combustion simulations and satellite image classification demonstrates that our derived error bounds accurately predict observed errors while enabling significant computational speedup under our framework. This work highlights the potential for further leveraging advancements in modern lossy compression algorithms and hardware accelerators that support lower-precision formats.

He, Weiming [New Jersey Institute of Technology]↗