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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 sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, whole organism, behavior; tabular, imagery). Open Science is the concept that the more people have access to scientifically curated data, the more knowledge will be gained. This led NASA to start the development of GeneLab in 2015. GeneLab houses spaceflight and space-analog multi-omics datasets from plant, rodent, small animal, and microbial experiments. The success and knowledge gained from GeneLab led to a new alliance of NASA “Open Science Data Repositories” (OSDR), which include the Ames Life Sciences Data Archive (ALSDA) and the NASA Biological Institutional Scientific Collection (NBISC). Both are adopting the GeneLab data system, so data are more findable, accessible, interoperable, and reusable (FAIR). OSDR systems provide users the ability to upload, download, search, share, analyze, and visualize. Open Science also needs strong confidence in the data, which is gained through building science communities. With ~400 current members, GeneLab and ALSDA formed Analysis Working Groups (AWGs) to provide feedback on processing pipelines, metadata curation standards (for ‘omics and phenotypic-physiological-behavioral assays), and to collaborate in effectively reusing data. The AWG also led to the development of the Radiation Biology Ontology (RBO), ensuring radiation metadata are efficiently captured, connected, and interoperable. Feedback from the AWG provided design input toward the new single point-of-entry data submission portal for all investigators to submit, curate, and share their research data. Space biological data is now maximally open access, collected-curated with rich metadata, and formatted for interoperability to enable systems biology, meta-analysis, knowledge graphs, machine learning, modeling, and other reuse approaches. With potential for further federation of OSDR for data mining with traditional biological and medical databases (NIH, NCI, EBI, etc.), a new era for space biology has begun to support the knowledge discovery necessary for Lunar and Martian missions.

Ryan T Scott↗
DOE OSTI2024

Swift /UVOT discovery of Swift J221951−484240: a UV luminous ambiguous nuclear transient

We report the discovery of Swift J221951−484240 (hereafter: J221951), a luminous slow-evolving blue transient that was detected by the Neil Gehrels Swift Observatory Ultraviolet/Optical Telescope (Swift/UVOT) during the follow-up of gravitational wave alert S190930t, to which it is unrelated. Swift/UVOT photometry shows the UV spectral energy distribution of the transient to be well modelled by a slowly shrinking blackbody with an approximately constant temperature of T ∼ 2.5 × 10 4 K. At a redshift z = 0.5205, J221951 had a peak absolute magnitude of M u,AB = −23 mag, peak bolometric luminosity Lmax = 1.1 x 10 45 ergs -1 and a total radiated energy of E > 2.6 × 10 52 erg. The archival Wide-field Infrared Survey Explorer IR photometry shows a slow rise prior to a peak near the discovery date. Spectroscopic UV observations display broad absorption lines in N V and O VI, pointing towards an outflow at coronal temperatures. The lack of emission in the higher H α lines, N I and other neutral lines is consistent with a viewing angle close to the plane of the accretion or debris disc. The origin of J221951 cannot be determined with certainty but has properties consistent with a tidal disruption event and the turn-on of an active galactic nucleus.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Characterizing Defect Dynamics in Silicon Carbide Using Symmetry-Adapted Collective Variables and Machine Learning Interatomic Potentials

Silicon carbide (SiC) divacancies are attractive candidates for spin-defect qubits possessing long coherence times and optical addressability. The high activation barriers associated with SiC defect formation and motion pose challenges for their study by first-principles molecular dynamics. In this work, we develop and deploy machine learning interatomic potentials (MLIPs) to accelerate defect dynamics simulations while retaining ab initio accuracy. We employ an active learning strategy comprising symmetry-adapted collective variable discovery and enhanced sampling to compile configurationally diverse training data, calculation of energies and forces using density functional theory (DFT), and training of an E(3)-equivariant MLIP based on the Allegro model. Here, the trained MLIP reproduces DFT-level accuracy in defect transition activation free energy barriers, enables the efficient and stable simulation of multidefect 216-atom supercells, and permits an analysis of the temperature dependence of defect thermodynamic stability and formation/annihilation kinetics to propose an optimal annealing temperature to maximally stabilize VV divacancies.

Computer simulations↗
DOE OSTI2025

Automated Nanocrystal Synthesis: Lessons from 25 Years of Robots, Microfluidics, and Machine Learning

Here, this perspective highlights the evolution of techniques for automating the synthesis of colloidal nanocrystals. Over the past 25 years, microfluidic reactors and robotic workflows have been developed to enhance the reproducibility of nanocrystal synthesis, facilitate rapid screening of reaction conditions, optimize material properties, and perform multistep syntheses of high-quality nanoparticles with complex heterostructures. Modern automated systems are now valued for their ability to generate robust data sets for validating physical models, supporting chemical mechanisms, training machine learning models, and for directing autonomous experimentation. We discuss the early challenges and limitations of these technologies and present key lessons for effectively utilizing automated and ML-guided tools to accelerate nanocrystal discovery for the next 25 years.

Nanocrystals↗
DOE OSTI2025

Solvent Screening for Separation Processes Using Machine Learning and High-Throughput Technologies

As the chemical industry shifts toward sustainable practices, there is a growing initiative to replace conventional fossil-derived solvents with environmentally friendly alternatives such as ionic liquids (ILs) and deep eutectic solvents (DESs). Artificial intelligence (AI) plays a key role in the discovery and design of novel solvents and the development of green processes. This review explores the latest advancements in AI-assisted solvent screening with a specific focus on machine learning (ML) models for physicochemical property prediction and separation process design. Additionally, this paper highlights recent progress in the development of automated high-throughput (HT) platforms for solvent screening. Finally, this paper discusses the challenges and prospects of ML-driven HT strategies for green solvent design and optimization. To this end, this review provides key insights to advance solvent screening strategies for future chemical and separation processes.

Artificial intelligence↗
DOE OSTI2024

Short-Wave Infrared Upconverting Nanoparticles

Optical technologies enable real-time, noninvasive analysis of complex systems but are limited to discrete regions of the optical spectrum. While wavelengths in the short-wave infrared (SWIR) window (typically, 1700-3000 nm) should enable deep subsurface penetration and reduced photodamage, there are few luminescent probes that can be excited in this region. Here, we report the discovery of lanthanide-based upconverting nanoparticles (UCNPs) that efficiently convert 1740 or 1950 nm excitation to wavelengths compatible with conventional silicon detectors. Screening of Ln3+ ion combinations by differential rate equation modeling identifies Ho3+/Tm3+ or Tm3+ dopants with strong visible or NIR-I emission following SWIR excitation. Experimental upconverted photoluminescence excitation (U-PLE) spectra find that 10% Tm3+-doped NaYF4 core/shell UCNPs have the strongest 800 nm emission from SWIR wavelengths, while UCNPs with an added 2% or 10% Ho3+ show the strongest red emission when excited at 1740 or 1950 nm. Mechanistic modeling shows that addition of a low percentage of Ho3+ to Tm3+-doped UCNPs shifts their emission from 800 to 652 nm by acting as a hub of efficient SWIR energy acceptance and redistribution up to visible emission manifolds. Parallel experimental and computational analysis shows rate equation models are able to predict compositions for specific wavelengths of both excitation and emission. These SWIR-responsive probes open a new IR bioimaging window, and are responsive at wavelengths important for vision technologies.

Qi, Xiao↗
DOE OSTI2020

Chemically distinct regions of Venus’s atmosphere revealed by measured N 2 concentrations

A defining characteristic of the planet Venus is its thick, CO 2 -dominated atmosphere. Despite over 50 years of robotic exploration of Venus, including thirteen successful atmospheric probes and landers, our knowledge of N 2 , the second most abundant compound in the atmosphere, is highly uncertain. We report the first measurement of the nitrogen content of Venus’s atmosphere at altitudes between 60 and 100 km. Our result, 5.0 ± 0.4 v% N 2 , is 40% higher than the value of 3.5 v% N 2 reported for the lower atmosphere (<50 km altitude). Our discovery of altitude-dependent variations in the N 2 content of the atmosphere defies early expectations of homogeneous composition below 100 km (for example, see ref. 1), and necessitates complete chemical modelling to investigate chemical versus physical explanations for the enhanced N 2 in the upper atmosphere. Furthermore, the existence of chemically distinct lower and upper atmosphere regions complicates the use of remote sensing measurements of the upper atmosphere to infer the properties of the lower atmosphere and surface, an important lesson that also extends to the growing field of exoplanet astronomy.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Coexistence of ordered and disordered vacancies in tungsten diboride with a broken hexagonal symmetry

As an important member of transition-metal borides, tungsten diboride (i.e., WB 2+𝑥 ) contains complex atomic vacancies with the originally assigned hexagonal symmetries, exhibiting many fascinating properties such as superconductivity and superior hardness. However, due to the difficulties in exploring atomic vacancies of transition-metal borides, the actual structure and composition of WB 2+𝑥 have been long-standing unsettled issues, which have impeded in-depth understanding of its structural stability and origins of such extraordinary properties. Here, we report a systematic investigation of the crystal structure of high-pressure synthesized WB 2+𝑥 samples by combination of state-of-the-art diffraction techniques and microstructural observations, leading to the discovery of an unusual coexistence of both the ordered and disordered atomic vacancies in WB 2+𝑥 with a broken hexagonal symmetry that can be well described by a dual-phase model involving hP12-W 0.70 ⁢B 1.73 and P1-W 0.75⁢ B 1.64 . Superposition of thin sample layers with disordered vacancies along the [001] or [110] direction is revealed to produce ordered vacancies, rationalizing the observed size-dependent symmetry breaking. In conclusion, these findings not only provide solid foundations for studying the phase stability and properties of this boride but also give powerful insights into how the intricate atomic vacancies can influence crystal structures of transition-metal borides.

high pressure↗
DOE OSTI2024

Prospects for exotic h → 4 τ decays in single and di-Higgs boson production at the LHC and future hadron colliders

We study the prospects for observing exotic decays of the Standard Model Higgs boson h into light beyond the Standard Model scalars a with mass m a ≲ m h / 2 in the single Higgs and Higgs pair production channels at the high luminosity run of the Large Hadron Collider (HL-LHC). Discovery prospects for single Higgs production in the gluon-gluon fusion and vector boson fusion modes with the Higgs boson decaying via the exotic mode h → a a → 4 τ are analyzed at the HL-LHC. The projected sensitivity for exotic Higgs decays in the nonresonant Higgs pair production channel p p → h h → ( h → b b ¯ ) ( h → a a → 4 τ ) → 2 b 4 τ at the HL-LHC and a future s = 100 TeV hadron collider (FCC-hh) are also estimated. Furthermore, we study HL-LHC’s potential reach for the Higgs-strahlung process in the 2 b 4 τ channel, taking into account the contamination from nonresonant Higgs pair production. Finally, the potential reach for resonant Higgs pair production in the 2 b 4 τ channel at the HL-LHC is also explored for several choices of { m H , m a } . Our studies suggest that significant improvements over existing bounds are achievable in several production channels, motivating new dedicated searches for h → a a → 4 τ at the HL-LHC and future colliders. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
NASA NTRS2007

High-Energy Emission from Rotation-Powered Pulsars

Thirty-five years after the discovery of rotation-powered pulsars, we still do not understand their pulsed emission at any wavelength. In the last few years there have been some fundamental developments in acceleration and emission models. I will review both the basic physics of the models as well as the latest developments in understanding the high-energy emission of rotation-powered pulsars. Special and general relativistic effects play important roles in pulsar emission, from inertial frame-dragging near the stellar surface to aberration, time-of-flight and retardation of the magnetic field near the light cylinder. Understanding how these effects determine what we observe at different wavelengths is critical to unraveling the emission physics. Fortunately two new gamma-ray telescopes, AGILE and GLAST, with launches expected this year will detect many new gamma-ray pulsars and test the predictions of these models with unprecedented sensitivity and energy resolution for gamma-rays in the range of 30 MeV to 300 GeV.

Harding, Alice K.↗
NASA NTRS2012

Gravity Wave Variances and Propagation Derived from AIRS Radiances

As the first gravity wave (GW) climatology study using nadir-viewing infrared sounders, 50 Atmospheric Infrared Sounder (AIRS) radiance channels are selected to estimate GW variances at pressure levels between 2-100 hPa. The GW variance for each scan in the cross-track direction is derived from radiance perturbations in the scan, independently of adjacent scans along the orbit. Since the scanning swaths are perpendicular to the satellite orbits, which are inclined meridionally at most latitudes, the zonal component of GW propagation can be inferred by differencing the variances derived between the westmost and the eastmost viewing angles. Consistent with previous GW studies using various satellite instruments, monthly mean AIRS variance shows large enhancements over meridionally oriented mountain ranges as well as some islands at winter hemisphere high latitudes. Enhanced wave activities are also found above tropical deep convective regions. GWs prefer to propagate westward above mountain ranges, and eastward above deep convection. AIRS 90 field-of-views (FOVs), ranging from +48 deg. to −48 deg. off nadir, can detect large-amplitude GWs with a phase velocity propagating preferentially at steep angles (e.g., those from orographic and convective sources). The annual cycle dominates the GW variances and the preferred propagation directions for all latitudes. Indication of a weak two-year variation in the tropics is found, which is presumably related to the Quasi-biennial oscillation (QBO). AIRS geometry makes its out-tracks capable of detecting GWs with vertical wavelengths substantially shorter than the thickness of instrument weighting functions. The novel discovery of AIRS capability of observing shallow inertia GWs will expand the potential of satellite GW remote sensing and provide further constraints on the GW drag parameterization schemes in the general circulation models (GCMs).

AIRS↗
NASA NTRS2015

Characterizing Young Giant Planets with the Gemini Planet Imager: An Iterative Approach to Planet Characterization

After discovery, the first task of exoplanet science is characterization. However experience has shown that the limited spectral range and resolution of most directly imaged exoplanet data requires an iterative approach to spectral modeling. Simple, brown dwarf-like models, must first be tested to ascertain if they are both adequate to reproduce the available data and consistent with additional constraints, including the age of the system and available limits on the planet's mass and luminosity, if any. When agreement is lacking, progressively more complex solutions must be considered, including non-solar composition, partial cloudiness, and disequilibrium chemistry. Such additional complexity must be balanced against an understanding of the limitations of the atmospheric models themselves. For example while great strides have been made in improving the opacities of important molecules, particularly NH3 and CH4, at high temperatures, much more work is needed to understand the opacity of atomic Na and K. The highly pressure broadened fundamental band of Na and K in the optical stretches into the near-infrared, strongly influencing the spectral shape of Y and J spectral bands. Discerning gravity and atmospheric composition is difficult, if not impossible, without both good atomic opacities as well as an excellent understanding of the relevant atmospheric chemistry. I will present examples of the iterative process of directly imaged exoplanet characterization as applied to both known and potentially newly discovered exoplanets with a focus on constraints provided by GPI spectra. If a new GPI planet is lacking, as a case study I will discuss HR 8799 c and d will explain why some solutions, such as spatially inhomogeneous cloudiness, introduce their own additional layers of complexity. If spectra of new planets from GPI are available I will explain the modeling process in the context of understanding these new worlds.

exoplanets↗
NASA NTRS2018

Convergent Aeronautics Solutions Project

NASA is committed to transforming our aviation system to best meet demands and opportunities of the future. With a vision of safe, efficient, flexible, and environmentally sustainable air transportation, the NASA Aeronautics Research Mission Directorate is conducting research and development to address future needs of the aviation community, the Nation, and the world. While our NASA Aeronautics vision and strategy reaches into the next 25 years and beyond, we recognize that our vision and strategy must be responsive to new discoveries and emerging markets. For this reason, we are empowering our research community to redefine the future of aviation by dreaming up convergent/transformative ideas and studying if those ideas are possible. By modeling the new NASA Aeronautics' Convergent Aeronautics Solutions (CAS) Project after the venture capital community, we created opportunities for teams of intrapreneurs to mature their ideas into concepts through rapid feasibility studies. The CAS Project expects teams to consider the complexities and potential benefits of multi-disciplinary solutions and to leverage technology advances from outside the field of aeronautics. We also expect teams to explore their concepts in a rapid, iterative manner that allows them to learn and adjust their research approach. Within a year or two, teams are responsible for reporting on the feasibility of their concept. The findings inform NASA Aeronautics strategic planning and further investment. This presentation will give an overview of CAS.

Transformative↗
NASA NTRS2020

Global Airborne Sampling Reveals a Previously Unobserved Dimethyl Sulfide Oxidation Mechanism in the Marine Atmosphere

Dimethyl sulfide (DMS), emitted from the oceans, is the most abundant biological source of sulfur to the marine atmosphere. Atmospheric DMS is oxidized to condensable products that form secondary aerosols that affect Earth’s radiative balance by scattering solar radiation and serving as cloud condensation nuclei. We report the atmospheric discovery of a previously unquantified DMS oxidation product, hydroperoxymethyl thioformate (HPMTF, HOOCH2SCHO), identified through global-scale airborne observations that demonstrate it to be a major reservoir of marine sulfur. Observationally constrained model results show that more than 30% of oceanic DMS emitted to the atmosphere forms HPMTF. Coincident particle measurements suggest a strong link between HPMTF concentration and new particle formation and growth. Analyses of these observations show that HPMTF chemistry must be included in atmospheric models to improve representation of key linkages between the biogeochemistry of the ocean, marine aerosol formation and growth, and their combined effects on climate.

DMS gas-phase oxidation product↗
DOE OSTI2022

Report of the Snowmass 2021 Topical Group on Lattice Gauge Theory

Lattice gauge theory continues to be a powerful theoretical and computational approach to simulating strongly interacting quantum field theories, whose applications permeate almost all disciplines of modern-day research in High-Energy Physics. Whether it is to enable precision quark- and lepton-flavor physics, to uncover signals of new physics in nucleons and nuclei, to elucidate hadron structure and spectrum, to serve as a numerical laboratory to reach beyond the Standard Model, or to invent and improve state-of-the-art computational paradigms, the lattice-gauge-theory program is in a prime position to impact the course of developments and enhance discovery potential of a vibrant experimental program in High-Energy Physics over the coming decade. This projection is based on abundant successful results that have emerged using lattice gauge theory over the years: on continued improvement in theoretical frameworks and algorithmic suits; on the forthcoming transition into the exascale era of high-performance computing; and on a skillful, dedicated, and organized community of lattice gauge theorists in the U.S. and worldwide. The prospects of this effort in pushing the frontiers of research in High-Energy Physics have recently been studied within the U.S. decadal Particle Physics Planning Exercise (Snowmass 2021), and the conclusions are summarized in this Topical Report.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRSDate not supplied

Enabling Biological Discovery Through Biospecimen Sharing: The Nasa Biological Institutional Scientific Collection

Understanding biological impacts from spaceflight hazards and the subsequent development of countermeasures are a high priority to enable humanity to venture back to the Moon, and then to Mars and beyond. Experiments have been conducted with model organisms flown to space and analogous investigations terrestrially, to identify biological mechanistic impacts from spaceflight hazards and to develop mitigation countermeasures, thus contributing towards basic and applied science goals. However, sending organisms into space is a costly endeavor. To maximize scientific return, all biospecimens not required by spaceflight-relevant Principal Investigators are harvested, preserved, and archived in the NASA Biological Institutional Scientific Collection (NBISC). Biospecimens are collected and preserved according to well-established standard operating procedures to maintain scientific quality and are available on-request by the international scientific community. NBISC currently stores over 32,000 biospecimens from Shuttle, International Space Station, and ground-based space analog investigations. Tissue sharing has resulted in at least 33 publications since 2011 and 51 requests since 2016. Many requests for NBISC biospecimens come from first-time investigators who subsequently submit grants as their point-of-entry into the field of spaceflight biology and health. The NBISC biorepository is part of the NASA ‘Open Science for Life in Space’ collaborative group of projects, which includes NASA Genelab, the Space Biology Program’s Biospecimen Sharing Program, Physical Sciences Informatics, and the Ames Life Sciences Data Archive. NBISC biospecimens have been awarded to NASA Genelab, who then generated various open access science ‘omics datasets through the GeneLab Sample Processing laboratory, with resulting data widely used for biological study. Other NBISC biospecimen awards have led to studies on fecal microbiome analysis, DNA damage analysis using single-cell DNA sequencing, enzymatic-pathway identification involved in spaceflight muscle atrophy, and characterization of ocular morphological changes. Of note, NBISC is expanded to include a new Space Microbial Culture Collection (SMCC) for the collection, identification, documentation, long-term preservation, and distribution of space-related microbial isolates.

Biospecimens↗
DOE OSTI2021

Cortical proteins may provide motor resilience in older adults

Motor resilience proteins may be a high value therapeutic target that offset the negative effects of pathologies on motor function. This study sought to identify cortical proteins associated with motor decline unexplained by brain pathologies that provide motor resilience. We studied 1226 older decedents with annual motor testing, postmortem brain pathologies and quantified 226 proteotypic peptides in prefrontal cortex. Twenty peptides remained associated with motor decline in models controlling for ten brain pathologies (FDR < 0.05). Higher levels of nine peptides and lower levels of eleven peptides were related to slower decline. A higher motor resilience protein score based on averaging the levels of all 20 peptides was related to slower motor decline, less severe parkinsonism and lower odds of mobility disability before death. Cortical proteins may provide motor resilience. Targeting these proteins in further drug discovery may yield novel interventions to maintain motor function in old age.

Buchman, Aron↗
NASA NTRSDate not supplied

Data Science and the Knowledge Discovery Adventure

This talk will cover the important steps involved in the data science and knowledge discovery process: • Initial fact gathering (interview domain experts, review reports, articles, state-of-the-art) • Identify the problem (prediction, classification, statistical analysis, etc.) • Survey supporting data sources • Understand the data (numerical, categorical, text, sampling rate, data quality issues, etc.) • Selecting relevant features and sources • Acquire the data (set up agreements with the data stewards, APIs to download, etc.) • Merge data sources (temporal, spatial, common key, other ontologies...) • Feature Engineering (non linear domain knowledge or physics-based relationships) • Build data processing pipeline (may need to tap into data stream, develop parallel processing algorithm, federated learning etc.) • Build model and test (tune hyper-parameters, cross validation.) • Analyze/Validate results (do the results make sense. Does it answer the original question). • Deploy/Publish (Monitor and assess benefits)

Data science↗