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DOE OSTI2024

Ventenata dubia projected to expand in the western United States despite future novel conditions

Abstract Distributions of both native and invasive species are expected to shift under future climate. Species distribution models (SDMs) are often used to explore future habitats, but sources of uncertainty including novel climate conditions may reduce the reliability of future projections. We explore the potential spread of the invasive annual grass ventenata ( Ventenata dubia ) in the western United States under both current and future climate scenarios using boosted regression tree models and 30 global climate models (GCMs). We quantify novel climate conditions, prediction variability arising from both the SDMs and GCMs, and the agreement among GCMs. Results demonstrate that currently suitable habitat is concentrated inside the invaded range of the northwest, but substantial habitat exists outside the invaded range in the Southern Rockies and southwestern US mountains. Future suitability projections vary greatly among GCMs, but GCMs commonly projected decreased suitability in the invaded range and increased suitability along higher elevations of interior mountainous areas. Climate novelty did not appear to undermine the prediction reliability in many cases where the climate–species relationship was fully represented by the occurrence data. GCM‐derived variability resulting from variation in future cool season precipitation and temperature seasonality was greatest in the Rocky Mountains. SDM‐derived variability was higher in currently suitable habitat, and few GCMs projections agreed that these areas would contain future suitable habitat. However, while prediction variability was high, many GCM projections agreed that parts of the Rocky, Wasatch, and Uinta Mountains would contain highly suitable habitat in the future. As disturbances in the interior mountains occur in coming decades, reducing some natural barriers to invasion, land managers, and conservationists will need to monitor for ventenata in post‐disturbance environments. Changes to invasion potential may not play out for several decades, but results related to current potential may have applications for early detection and rapid response planning.

Environmental Sciences & Ecology↗

DOE OSTI2025

Template‐Directed Growth of Palladium Nanoparticles in Holey Single‐Layer Graphene for High‐Performance Room‐Temperature Hydrogen Sensing

Holey graphene (HG), formed by introducing nanoscale perforations into graphene sheets, combines the structural advantages of continuous sp 2 conjugation with the beneficial effects of high surface area and enhanced chemical reactivity associated with nanoscopic holes. Conventional HG fabrication methods often rely on harsh oxidative treatments that compromise graphene's intrinsic electronic properties by disrupting its sp 2 conjugation. A new approach is introduced to fabricate HG directly from single-layer graphene (SLG), using two-dimensional covalent organic frameworks (COFs) as a template followed by controlled oxygen plasma etching. This method preserves the integrity of the SLG's sp 2 network while producing well-defined holes with an average diameter of 2.7 nm. These hole edges act as reactive sites that facilitate the confined, autoreductive growth of palladium nanoparticles (PdNPs) without external reducing agents. The confined hole geometry prevents NP agglomeration and ensures a uniform size distribution. The resulting Pd@HG hybrid exhibits exceptional chemiresistive hydrogen sensing characteristics, including ultrahigh sensitivity, low detection limits, rapid response and recovery, and long-term stability under both dry and humid conditions. Mechanistic investigations reveal a two-step sensing process involving surface redox interactions and hydrogen absorption into the PdNP lattices. This strategy presents a scalable platform for integrating metal NPs within conductive carbon frameworks for advanced sensing applications.

chemical vapor deposition↗

DOE OSTI2025

Proton emission in ultraperipheral Pb-Pb collisions at $\sqrt{𝑠_{𝑁⁢𝑁}}$ = 5.02 TeV

The first measurements of proton emission accompanied by neutron emission in the electromagnetic dissociation (EMD) of 208 Pb nuclei in the ALICE experiment at the Large Hadron Collider are presented. The EMD protons and neutrons emitted at very forward rapidities are detected by the proton and neutron zero degree calorimeters of the ALICE experiment. The emission cross sections of zero, one, two, and three protons accompanied by at least one neutron were measured in ultraperipheral 208 Pb − 208 Pb collisions at a center-of-mass energy per nucleon pair $\sqrt{𝑠_{𝑁⁢𝑁}}$ = 5.02TeV. The 0p and 3p cross sections are described by the RELDIS model within their measurement uncertainties, while the 1p and 2p cross sections are underestimated by the model by 17–25%. According to this model, these 0p, 1p, 2p, and 3p cross sections are associated, respectively, with the production of various isotopes of Pb, Tl, Hg, and Au in the EMD of 208 Pb . The cross sections of the emission of a single proton accompanied by the emission of one, two, or three neutrons in EMD were also measured. The data are significantly overestimated by the RELDIS model, which predicts that the (1p,1n), (1p,2n), and (1p,3n) cross sections are very similar to the cross sections for the production of the thallium isotopes 206,205,204 Tl.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Dynamic STEM-EELS for single-atom and defect measurement during electron beam transformations

This study introduces the integration of dynamic computer vision–enabled imaging with electron energy loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM). This approach involves real-time discovery and analysis of atomic structures as they form, allowing us to observe the evolution of material properties at the atomic level, capturing transient states traditional techniques often miss. Rapid object detection and action system enhances the efficiency and accuracy of STEM-EELS by autonomously identifying and targeting only areas of interest. This machine learning (ML)–based approach differs from classical ML in that it must be executed on the fly, not using static data. We apply this technology to V-doped MoS 2 , uncovering insights into defect formation and evolution under electron beam exposure. This approach opens uncharted avenues for exploring and characterizing materials in dynamic states, offering a pathway to increase our understanding of dynamic phenomena in materials under thermal, chemical, and beam stimuli.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Offshore-onshore record of Last Glacial Maximum–to–present grounding line retreat at Pine Island Glacier, Antarctica

Pine Island Glacier, West Antarctica, is the largest Antarctic contributor to global sea-level rise and is vulnerable to rapid retreat, yet our knowledge of its deglacial history since the Last Glacial Maximum is based largely on marine sediments that record a retreat history ending in the early Holocene. Using a suite of 10 Be exposure ages from onshore glacial deposits directly adjacent to Pine Island Glacier, we show that this major glacier thinned rapidly in the early to mid-Holocene. Our results indicate that Pine Island Glacier was at least 690 m thicker than present prior to ca. 8 ka. We infer that the rapid thinning detected at the site farthest downstream records the arrival and stabilization of the retreating grounding line at that site by 8–6 ka. By combining our exposure ages and the marine record, we extend knowledge of Pine Island Glacier retreat both spatially and temporally: to 50 km from the modern grounding line and to the mid-Holocene, providing a data set that is important for future numerical ice-sheet model validation.

58 GEOSCIENCES↗

DOE OSTI2022

Image Analysis for Rapid Assessment and Quality-Based Sorting of Corn Stover

Imaging in the visible spectrum is a low-cost tool that can be readily deployed for in-field or over-belt monitoring of biomass quality for bio-refining operations. Rapid image analysis coupled with innovative preprocessing may reduce the impacts of feedstock variability through identification of contaminants or other material attributes to guide selective sorting and quality management. Image analysis was employed to evaluate the quality of corn stover in red-green-blue (RGB) chromatic space. This study used controlled, bench-scale imaging as a proof-of-concept for rapid quality assessment of corn stover based on variations in material attributes, including chemical and physical attributes, that relate to biological degradation and soil contamination. Additionally, logistic regression-based classification algorithms were used to develop a method for biomass screening as a function of biological degradation or soil contamination. This study demonstrated the use of image analysis to extract features from RGB color space to investigate variations in critical material attributes from chemical composition of corn stover. Fourier transform infrared (FT-IR) suggested a correlation between red band intensity and biological degradation, while detailed surface texture analysis was found to distinguish among variations in ash. These insights offer promise for development of a rapid screening tool that could be deployed by farmers for in-field assessment of biomass quality or biorefinery operators for in-line sorting and process optimization.

09 BIOMASS FUELS↗

NASA NTRS1989

The Exosat spectral survey of AGN

Results are presented from Exosat observations of 48 hard X-ray selected Seyfert-type active galactic nuclei (AGN). These include all 30 of the emission line AGN in the Piccinotti (1981) sample. Combining Exosat LE and ME data has yielded X-ray spectra over the broad energy range 0.1-10 keV. Spectra in the about 2-10 keV range are found to be well described by a simple power law, with a narrow distribution of spectral indices across the sample about a mean energy index alpha = 0.70. Exosat has also revealed a substantial number of sources with complex soft X-ray spectra. Evidence that soft emission components occur in many Seyferts, together with detection of rapid variability in the soft component, provides a quantitative support for an accretion disk model for AGN. Approximately half of the present sample of AGN show low-energy absorption attributable to substantial cold matter within the host galaxy. A few cases show evidence for column variability and reduced low-energy opacity (by photo-ionization). These results and the observed rarity of intrinsic absorption in the higher luminosity sources suggest the absorbing matter lies close to the central continuum source.

Turner, T. J.↗

NASA NTRS1990

Two arm robot path planning in a static environment using polytopes and string stretching

The two arm robot path planning problem has been analyzed and reduced into components to be simplified. This thesis examines one component in which two Puma-560 robot arms are simultaneously holding a single object. The problem is to find a path between two points around obstacles which is relatively fast and minimizes the distance. The thesis involves creating a structure on which to form an advanced path planning algorithm which could ideally find the optimum path. An actual path planning method is implemented which is simple though effective in most common situations. Given the limits of computer technology, a 'good' path is currently found. Objects in the workspace are modeled with polytopes. These are used because they can be used for rapid collision detection and still provide a representation which is adequate for path planning.

Schima, Francis J., III↗

NASA NTRS1999

Glacier and Ice Shelves Studies Using Satellite SAR Interferometry

Satellite radar interferometry is a powerful technique to measure the surface velocity and topography of glacier ice. On ice shelves, a quadruple difference technique separates tidal motion from the steady creep flow deformation of ice. The results provide a wealth of information about glacier grounding lines , mass fluxes, stability, elastic properties of ice, and tidal regime. The grounding line, which is where the glacier detaches from its bed and becomes afloat, is detected with a precision of a few tens of meters. Combining this information with satellite radar altimetry makes it possible to measure glacier discharge into the ocean and state of mass balance with greater precision than ever before, and in turn provide a significant revision of past estimates of mass balance of the Greenland and Antarctic Ice Sheets. Analysis of creep rates on floating ice permits an estimation of basal melting at the ice shelf underside. The results reveal that the action of ocean water in sub-ice-shelf cavities has been largely underestimated by oceanographic models and is the dominant mode of mass release to the ocean from an ice shelf. Precise mapping of grounding line positions also permits the detection of grounding line migration, which is a fine indicator of glacier change, independent of our knowledge of snow accumulation and ice melting. This technique has been successfully used to detect the rapid retreat of Pine Island Glacier, the largest ice stream in West Antarctica. Finally, tidal motion of ice shelves measured interferometrically provides a modern, synoptic view of the physical processes which govern the formation of tabular icebergs in the Antarctic.

Rignot, Eric↗

NASA NTRS1999

Subsurface Microsensors for Assisted Recertification of TPS (SmarTPS)

Commercialization of a competitive reusable launch vehicle (RLV) is a primary goal for both NASA and the U.S. aerospace industry. To expedite achievement of this goal, the Bantam-X Technology Program is funding development of innovative technologies to lower costs for access to space. Ground operations is one area where significant cost reduction is required. For the Shuttle fleet, ground operations account for over 80% of the life cycle costs, and TPS recertification accounts for 27% of the operation costs ($4.5M per flight). Bantam Task TPS-7, Subsurface Microsensors for Assisted Recertification of TPS (SmarTPS), is a joint effort between NASA centers and industry partners to develop rapid remote detection and scanning technology for inspection of TPS and detection of subsurface defects. This short paper will provide a general overview of the SmarTPS concept.

Pallix, Joan B.↗

NASA NTRS2004

Deployment of a Fast-GCMS System to Measure C2 to C5 Carbonyls, Methanol and Ethanol Aboard Aircraft

Through funding of this proposal, a fast response gas chromatograph/mass spectrometer (FGCMS) instrument to measure less than or equal to C4 carbonyl compounds and methanol was developed for the NASA GTE TRACE-P (Global Tropospheric Experiment, Transport And Chemical Evolution Over The Pacific) mission. The system consists of four major components: sample inlet, preconcentration system, gas chromatograph (GC), and detector. The preconcentration system is a custom-built cryogen-conservative system. The GC is a compact, custom-built unit that can be temperature programmed and rapidly cooled. Detection is accomplished with an Agilent Technologies 5973 mass spectrometer. The FGCMS instrument provides positive identification because the compounds are chromatographically separated and mass selected. During TRACE-P, a sample was analyzed every 5 minutes. The FGCMS limit of detection was between 5 and 75 pptv, depending on the compound. The entire instrument package is contained in a standard NASA instrument rack (106 cm x 61 cm x 135 cm), consumes less than 1200 watts and is fully automated with LabViEW 6i. Methods were developed or producing highly accurate gas phase standards for the target compounds and for testing the system in the presence of potential interferents. This report presents data on these tests and on the general overall performance of the system in the laboratory and aboard the DC-8 aircraft during the mission. Vertical profiles for acetaldehyde, methanol, acetone, propanal, methyl ethyl ketone, and butanal from FGCMS data collected over the entire mission are also presented.

Apel, Eric C.↗

NASA NTRS2010

NASA Tech Briefs, December 2010

Topics include: Coherent Frequency Reference System for the NASA Deep Space Network; Diamond Heat-Spreader for Submillimeter-Wave Frequency Multipliers; 180-GHz I-Q Second Harmonic Resistive Mixer MMIC; Ultra-Low-Noise W-Band MMIC Detector Modules; 338-GHz Semiconductor Amplifier Module; Power Amplifier Module with 734-mW Continuous Wave Output Power; Multiple Differential-Amplifier MMICs Embedded in Waveguides; Rapid Corner Detection Using FPGAs; Special Component Designs for Differential-Amplifier MMICs; Multi-Stage System for Automatic Target Recognition; Single-Receiver GPS Phase Bias Resolution; Ultra-Wideband Angle-of-Arrival Tracking Systems; Update on Waveguide-Embedded Differential MMIC Amplifiers; Automation Framework for Flight Dynamics Products Generation; Product Operations Status Summary Metrics; Mars Terrain Generation; Application-Controlled Parallel Asynchronous Input/Output Utility; Planetary Image Geometry Library; Propulsion Design With Freeform Fabrication (PDFF); Economical Fabrication of Thick-Section Ceramic Matrix Composites; Process for Making a Noble Metal on Tin Oxide Catalyst; Stacked Corrugated Horn Rings; Refinements in an Mg/MgH2/H2O-Based Hydrogen Generator; Continuous/Batch Mg/MgH2/H2O-Based Hydrogen Generator; Strain System for the Motion Base Shuttle Mission Simulator; Ko Displacement Theory for Structural Shape Predictions; Pyrotechnic Actuator for Retracting Tubes Between MSL Subsystems; Surface-Enhanced X-Ray Fluorescence; Infrared Sensor on Unmanned Aircraft Transmits Time-Critical Wildfire Data; and Slopes To Prevent Trapping of Bubbles in Microfluidic Channels.

Source record↗

NASA NTRS2014

Microbiological Quality and Food Safety of Plants Grown on ISS Project

The goal of this project is to select and advance methods to enable real-time sampling, microbiological analysis, and sanitation of crops grown on the International Space Station (ISS). These methods would validate the microbiological quality of crops grown for consumption to ensure safe and palatable fresh foods. This would be achieved through the development / advancement of microbiological sample collection, rapid pathogen detection and effective sanitation methods that are compatible with a microgravity environment.

Technology Portfolio System↗

NASA NTRS2018

Discovery of Pulsation Dropout and Turn-on During the High State of the Accreting X-Ray Pulsar LMC X-4

Two Nuclear Spectroscopic Telescope Array (NuSTAR) observations of the luminous X-ray pulsar LMC X-4 in2015 October and November captured several bright accretion flares from this source, which has a long history of stable pulse and superorbital behavior. We present a timing analysis of these data in which we detect a rapid pulse "turn-on" in association with the accretion flares, during which the source reaches super-Eddington luminosities.Pulsations, which are normally seen from this source, are found to only occur for approximately one hour before and during the bright flares. Beyond one hour before and after the flares, we find pulsations to be weak or nonexistent, with fractional rms amplitudes of less than 0.05. At the onset of the flare, the pulse profiles exhibit a phase shift of 0.25 cycles that could be associated with a change in the emission geometry. This increase in pulse strength occurring well before the flare cannot be explained by the propeller effect, and potentially offers a connection between the magnetic properties of pulsars that accrete close to their Eddington limits and ultraluminous X-ray pulsars.

Brumback, Mckinley C.↗

NASA NTRS2021

Colorado Ecological Forecasting: Monitoring Post-fire Cheatgrass (Bromus tectorum) Distribution to Inform Management Planning

Cheatgrass (Bromus tectorum) is a species of concern across the western United States as it has the potential to outcompete native plant species, reduce biodiversity, and diminish nutrient availability for ungulates. Furthermore, because cheatgrass can quickly dominate disturbed landscapes it has the potential to exacerbate wildfire risk by increasing fuel loads. In 2020, the Cameron Peak fire burned more than 200,000 acres on the Arapaho and Roosevelt National Forests in Colorado. These issues are of imminent concern for our partners at the Forest Service (USFS), as they are tasked with wildfire risk and invasive species mitigation. Disturbances such as wildfires can substantially increase the rate and extent of cheatgrass spread. Current cheatgrass mitigation methods rely on field crews to physically locate cheatgrass on the landscape, which takes time, money, and extensive manpower. Here, we developed two Random Forest models within the Software for Assisted Habitat Modeling (SAHM) using remote sensing predictors derived from Sentinel-2 MultiSpectral Instrument (MSI) and Shuttle Radar Topography Mission (SRTM). The first model identified suitable cheatgrass habitat while the other detected cheatgrass presence during the 2021 growing season. Topographic variables were found to be the most important in driving the habitat suitability model. Cheatgrass detection was also found to be possible within a short timespan with limited imagery surrounding a phenological shift of the plant. Maps produced from these models provide natural resource managers the ability to implement early detection and rapid response to prevent the spread of cheatgrass to new locations.

DEVELOP Tech Paper↗

NASA NTRS2021

DDOTI Observations of Gravitational-Wave Sources Discovered in O3

We present optical follow-up observations with the Deca-Degree Optical Transient Imager (DDOTI) telescope of gravitational-wave (GW) events detected during the Advanced LIGO and Advanced Virgo O3 observing run. DDOTI is capable of responding to an alert in a few minutes, has an instantaneous field of about 69 deg2, and obtains 10σ upper limits of wlim = 18.5–20.5 AB mag in 1000 s of exposure, depending on the conditions. We observed 54 per cent (26 out of 48) of the unretracted GW alerts and did not find any electromagnetic counterparts. We compare our upper limits to various possible counterparts: the kilonova AT 2017gfo, models of radioactive- and magnetar-powered kilonovae, short gamma-ray burst afterglows, and active galactic nucleus (AGN) flares. Although the large positional uncertainties of GW sources do not allow us to place strong constraints during O3, DDOTI observations of well-localized GW events in O4 and beyond could meaningfully constrain models of compact binary mergers. We show that DDOTI is able to detect kilonovae similar to AT 2017gfo up to about 200 Mpc and magnetar-powered kilonovae up to 1 Gpc. We calculate that nearby (≲200 Mpc) afterglows have a high chance (≈70 per cent) to be detected by rapid (≲3 h) DDOTI observations if observed on-axis, whereas off-axis afterglows are unlikely to be seen. Finally, we suggest that long-term monitoring of massive BBH events with DDOTI could confirm or rule out late AGN flares associated with these events.

gravitational waves↗

DOE OSTI2020

Redox-Based Electrochemical Affinity Sensor for Detection of Aqueous Pertechnetate Anion

Rapid, selective, in-situ detection of TcO4- in multicomponent matrices consisting of interfering anions such as the ubiquitous NO3- and Cl- or the isostructural and isoelectronic CrO42- is challenging. Present sensors mostly lack the selectivity to exclude these interferences, or the sensitivity to meet the detection limits that are lower than the drinking water standards across the globe. This work presents an affinity based electrochemical sensor for TcO4- detection that relies on selective reductive precipitation of aqueous TcO4- induced by a capture probe immobilized on an electrode platform. This results in a direct decrease of the electron transfer current, the magnitude of the decrease being proportional to the amount of TcO4- added. Using this approach, we were able to achieve a detection limit of 1x10-10 M, which is lower than the drinking water standard of 5.2x10-10 M set by United States Environmental Protection Agency. Our proposed approach also allowed us to detect TcO4- from a multicomponent groundwater sample obtained from a well at the Hanford site in Washington (well 299-W19-36) that also contained NO3- , Cl- and CrO42-, without discernably affecting the detection limits.

Chatterjee, Sayandev↗

DOE OSTI2026

SimLBR: Learning to Detect Fake Images by Learning to Detect Real Images

The rapid advancement of generative models has made the detection of AI-generated images a critical challenge for both research and society. Recent works have shown that most state-of-the-art fake image detection methods overfit to their training data and catastrophically fail when evaluated on curated hard test sets with strong distribution shifts. In this work, we argue that it is more principled to learn a tight decision boundary around the real image distribution and treat the fake category as a sink class. To this end, we propose SimLBR, a simple and efficient framework for fake image detection with Latent Blending Regularization (LBR). Our method significantly improves cross-generator generalization, achieving up to +24.85% accuracy and +69.62% recall on the challenging Chameleon benchmark. SimLBR is also highly efficient, training orders of magnitude faster than existing approaches. Furthermore, we emphasize the need for reliability-oriented evaluation in fake image detection, introducing risk-adjusted metrics and worst-case estimates to better assess model robustness. All the code and models are availabe at: https://github.com/mvrl/SimLBR

Dhakal, Aayush [Washington University, St. Louis]↗