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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Cancer cell membrane-coated rare earth doped nanoparticles for tumor surgery navigation in NIR-II imaging window

With the attractive characteristics of low toxicity, narrow emission spectra, long fluorescence lifetime, and no photobleaching, rare-earth doped nanoparticles (RENPs) have become promising imaging nanoplatforms in the second near-infrared window (NIR-II, 1000–1700 nm). Many studies have been devoted to different surface modification strategies of RENPs to achieve good NIR-II tumor imaging property. However, the tumor imaging efficiency of these approaches remains disappointing. Herein, two methods were pursued to modify RENPs with either polyethylene glycol (PEG) or cancer-cell-membrane to generate PEGylated-RENPs and cancer-cell-membrane camouflaged RENPs (CC-RENPs), respectively. Furthermore, this study demonstrated that cancer-cell-membrane coating of RENPs greatly improved tumor imaging performance in NIR-II window than PEG coating. Besides, CC-RENPs uptakes in liver and spleen significantly decreased. Importantly, CC-RENPs was found to be capable to aid us to pursue precise resection of the tumor. In conclusion, CC-RENPs are capable of targeting tumors and show high tumor NIR-II imaging quality. They are highly promising nanomaterials for future medical applications.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Contactless Position Measurement System for Remote Alignment of Highly Reflective Objects

The Contactless Position Measurement System (CPMS) permits automatic alignment of highly-reflecting components that cannot or should not be touched by human hands, such as those used in SRF cavities. CPMS also has application during maintenance of fusion reactors, when the components in the reactor are radioactive. The length of time for which humans can handle the components in order to carry out maintenance or repairs is limited. We would like to measure the relative positions of such objects so we can bring them into alignment with motorized stages, thus eliminating the need for human contact. The CPMS is a computer vision system that measures the location of highly reflective components to within a fraction of a millimeter by finding the edges of silhouette images. This is done by placing a uniform, infrared backlight behind the components, and viewing each component with two low-aberration, infrared cameras. Each of these stereoscopic cameras are located within a coordinate system we set up with reference platforms, light sources, and survey cameras distributed around the perimeter of the string assembly room, or fusion reactor. We obtain stereoscopic silhouette images of each component, and we use these to determine the position of the component within our string assembly coordinate system. The CPMS combines the silhouette images with knowledge of the dimensions of the objects to obtain the relative positions of components in its field of view. These position measurements then allow us to mechanically maneuver the components into contact. Once we know where they are, we can move the components to where they are supposed to be with motorized stages or other mechanical means, check they are in the right place, and bolt them together. In Phase I, we built a prototype infrared backlights and cameras, tested it, wrote an analysis program to fit the images. At a range of 50 cm, we are able to measure the relative positions of two stainless steel flanges with an accuracy of 150 μm rms. The next steps are to test the analysis program with motorized stages, build a full-size prototype, and implement it in an cleanroom with SRF cavity assembly. This can be done in a cost effective way given the materials with which the system is designed. As Open Source Instruments achieved more in Phase I than anticipated, despite not receiving a Phase II SBIR grant, we hope to move forward with product development and sales with a testing partner.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Identification of Metal Stresses in Arabidopsis thaliana Using Hyperspectral Reflectance Imaging

Industrial accidents, such as the Fukushima and Chernobyl disasters, release harmful chemicals into the environment, covering large geographical areas. Natural flora may serve as biological sensors for detecting metal contamination, such as cesium. Spectral detection of plant stresses typically employs a few select wavelengths and often cannot distinguish between different stress phenotypes. In this study, we apply hyperspectral reflectance imaging in the visible and near-infrared along with multivariate curve resolution (MCR) analysis to identify unique spectral signatures of three stresses in Arabidopsis thaliana : salt, copper, and cesium. While all stress conditions result in common stress physiology, hyperspectral reflectance imaging and MCR analysis produced unique spectral signatures that enabled classification of each stress. As the level of potassium was previously shown to affect cesium stress in plants, the response of A. thaliana to cesium stress under variable levels of potassium was also investigated. Increased levels of potassium reduced the spectral response of A. thaliana to cesium and prevented changes to chloroplast cellular organization. While metal stress mechanisms may vary under different environmental conditions, this study demonstrates that hyperspectral reflectance imaging with MCR analysis can distinguish metal stress phenotypes, providing the potential to detect metal contamination across large geographical areas.

multivariate curve resolution↗
DOE OSTI2021

NASA's surface biology and geology designated observable: A perspective on surface imaging algorithms

The 2017-2027 National Academies' Decadal Survey, Thriving on Our Changing Planet, recommended Surface Biology and Geology (SBG) as a "Designated Targeted Observable" (DO). The SBG DO is based on the need for capabilities to acquire global, high spatial resolution, visible to shortwave infrared (VSWIR; 380 - 2500 nm; ~30 m pixel resolution) hyperspectral (imaging spectroscopy) and multispectral midwave and thermal infrared (MWIR: 3-5 µm; TIR: 8-12 µm; ~60 m pixel resolution) measurements with sub-monthly temporal revisits over terrestrial, freshwater, and coastal marine habitats. To address the various mission design needs, an SBG Algorithms Working Group of multidisciplinary researchers has been formed to review and evaluate the algorithms applicable to the SBG DO across a wide range of Earth science disciplines, including terrestrial and aquatic ecology, atmospheric science, geology, and hydrology. Here, we summarize current state-of-the-practice VSWIR and TIR algorithms that use airborne or orbital spectral imaging observations to address the SBG DO priorities identified by the Decadal Survey: (i) terrestrial vegetation physiology, functional traits, and health; (ii) inland and coastal aquatic ecosystems physiology, functional traits, and health; (iii) snow and ice accumulation, melting, and albedo; (iv) active surface composition (eruptions, landslides, evolving landscapes, hazard risks); (v) effects of changing land use on surface energy, water, momentum, and carbon fluxes; and (vi) managing agriculture, natural habitats, water use/quality, and urban development. We review existing algorithms in the following categories: snow/ice, aquatic environments, geology, and terrestrial vegetation, and summarize the community-state-of-practice in each category. Finally, this effort synthesizes the findings of more than 130 scientists.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Handheld multi-sensor biometric imaging device and processing pipeline

A handheld biometric imaging device having an array of cameras configured to simultaneously capture face, iris and fingerprint biometrics of a subject. The device includes a plurality of visible-light cameras and a plurality of infrared-light cameras capable of being triggered simultaneously to obtain a plurality of images from which a 3D image of the light field can be constructed. The device includes a plurality of visible-light illuminators and a plurality of infrared-light illuminators that allow images of a subject to be captured under different lighting profiles. The device may include an onboard control system that is capable of reconstructing a face region, an iris region and a fingerprint region from the 3D light-field image, and then extract a corresponding face template, an iris template, and a fingerprint template from the respective reconstructed regions. The extracted face, iris, and fingerprint templates may be used for enrollment and/or comparison against a biometric-template database associated with one or more watchlists.

Bolme, David S.↗
DOE OSTI2021

Bright NIR‐II Photoluminescence in Rod‐Shaped Icosahedral Gold Nanoclusters

Abstract Fluorophores with high quantum yields, extended maximum emission wavelengths, and long photoluminescence (PL) lifetimes are still lacking for sensing and imaging applications in the second near‐infrared window (NIR‐II). In this work, a series of rod‐shaped icosahedral nanoclusters with bright NIR‐II PL, quantum yields up to ≈ 8%, and a peak emission wavelength of 1520 nm are reported. It is found that the bright NIR‐II emission arises from a previously ignored state with near‐zero oscillator strength in the ground‐state geometry and the central Au atom in the nanoclusters suppresses the non‐radiative transitions and enhances the overall PL efficiency. In addition, a framework is developed to analyze and relate the underlying transitions for the absorptions and the NIR‐II emissions in the Au nanoclusters based on the experimentally defined absorption coefficient. Overall, this work not only shows good performance of the rod‐shaped icosahedral series of Au nanoclusters as NIR‐II fluorophores, but also unravels the fundamental electronic transitions and atomic‐level structure‐property relations for the enhancement of the NIR‐II PL in gold nanoclusters. The framework developed here also provides a simple method to analyze the underlying electronic transitions in metal nanoclusters.

Li, Qi↗
DOE OSTI2024

The SRG/eROSITA All-Sky Survey: Optical identification and properties of galaxy clusters and groups in the western galactic hemisphere

The first SRG/eROSITA All-Sky Survey (eRASS1) provides the largest intracluster medium-selected galaxy cluster and group catalog covering the western Galactic hemisphere. Compared to samples selected purely on X-ray extent, the sample purity can be enhanced by identifying cluster candidates using optical and near-infrared data from the DESI Legacy Imaging Surveys. Using the red-sequence-based cluster findereROMaPPer, we measured individual photometric properties (redshiftz λ , richnessλ, optical center, and BCG position) for 12000 eRASS1 clusters over a sky area of 13 116 deg 2 , augmented by 247 cases identified by matching the candidates with known clusters from the literature. The median redshift of the identified eRASS1 sample isz= 0.31, with 10% of the clusters atz> 0.72. The photometric redshifts have an accuracy ofδz/(1 +z) ≲ 0.005 for 0.05 specand velocity dispersionσ) were measured a posteriori for a subsample of 3210 and 1499 eRASS1 clusters, respectively, using an extensive compilation of spectroscopic redshifts of galaxies from the literature. We infer that the primary eRASS1 sample has a purity of 86% and optical completeness >95% forz> 0.05. For these and further quality assessments of the eRASS1 identified catalog, we applied our identification method to a collection of galaxy cluster catalogs in the literature, as well as blindly on the full Legacy Surveys covering 24069 deg 2 . Using a combination of these cluster samples, we investigated the velocity dispersion-richness relation, finding that it scales with richness as log(λ norm ) = 2.401 × log(σ) − 5.074 with an intrinsic scatter ofδ in = 0.10 ± 0.01 dex. The primary product of our work is the identified eRASS1 cluster catalog with high purity and a well-defined X-ray selection process, opening the path for precise cosmological analyses presented in companion papers.

Astronomy & Astrophysics↗
DOE OSTI2025

Imaging transient molecular configurations in UV-excited diiodomethane

Femtosecond structural dynamics of diiodomethane (CH 2 I 2 ) triggered by ultraviolet (UV) photoabsorption at 290 and 330 nm are studied using time-resolved coincident Coulomb explosion imaging driven by a near-infrared probe pulse. Here, we map the dominant single-photon process, the cleavage of the carbon–iodine bond producing rotationally excited CH 2 I radical, identify the contributions of the three-body (CH 2 + I + I) dissociation and molecular iodine formation channels, which are primarily driven by the absorption of more than one UV photon, and demonstrate the existence of a weak reaction pathway involving the formation of short-lived transient species resembling iso-CH 2 I 2 -like geometries with a slightly shorter I–I separation compared to the ground-state CH 2 I 2 . These transient molecular configurations, which can be separated from the other channels by applying a set of conditions on the correlated momenta of three ionic fragments, are formed within ∼100 fs after the initial photoexcitation and decay within the next 100 fs.

Atomic and molecular processes↗
DOE OSTI2023

NIR fluorescence lifetime macroscopic imaging with a novel time-gated SPAD camera

SwissSPAD3 is the latest of a family of widefield time-gated SPAD imagers developed for fluorescence lifetime imaging (FLI) applications. Its distinctive features are (i) the ability to define shorter gates than its predecessors (width W < 1 ns), (ii) support for laser repetition rates up to at least 80 MHz and (iii) a dual-gate architecture providing an effective duty cycle of 100%. We present widefield macroscopic FLI measurements of short lifetime NIR dyes, analyzed using the phasor approach. Furthermore, the results are compared with those previously obtained with SwissSPAD2 and to theoretical predictions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Chiral plasmonic metasurface absorbers in the mid-infrared wavelength range

Chiral metamaterials in the mid-infrared wavelength range have tremendous potential for studying thermal emission manipulation and molecular vibration sensing. In this work, we present one type of chiral plasmonic metasurface absorber with high circular dichroism (CD) in absorption of more than 0.56 across the mid-infrared wavelength range of 5-5.5 mu m. The demonstrated chiral metasurface absorbers exhibit a maximum chiral absorption of 0.87 and a maximum CD in absorption of around 0.60. By adjusting the geometric parameters of the unit cell structure of the metasurface, the chiral absorption peak can be shifted to different wavelengths. Due to the strong chiroptical response, the thermal analysis of the designed chiral metasurface absorber further shows the large temperature difference between the left-handed and right-handed circularly polarized light. The demonstrated results can be utilized in various applications such as molecular detection, mid-infrared filter, thermal emission, and chiral imaging.

42 ENGINEERING↗
DOE OSTI2020

Deep Learning for Land Cover Classification Using Only a Few Bands

There is an emerging interest in using hyperspectral data for land cover classification. The motivation behind using hyperspectral data is the notion that increasing the number of narrowband spectral channels would provide richer spectral information and thus help improve the land cover classification performance. Although hyperspectral data with hundreds of channels provide detailed spectral signatures, the curse of dimensionality might lead to degradation in the land cover classification performance. Moreover, in some practical applications, hyperspectral data may not be available due to cost, data storage, or bandwidth issues, and RGB and near infrared (NIR) could be the only image bands available for land cover classification. Light detection and ranging (LiDAR) data is another type of data to assist land cover classification especially if the land covers of interest have different heights. In this paper, we examined the performance of two Convolutional Neural Network (CNN)-based deep learning algorithms for land cover classification using only four bands (RGB+NIR) and five bands (RGB+NIR+LiDAR), where these limited number of image bands were augmented using Extended Multi-attribute Profiles (EMAP). The deep learning algorithms were applied to a well-known dataset used in the 2013 IEEE Geoscience and Remote Sensing Society (GRSS) Data Fusion Contest. With EMAP augmentation, the two deep learning algorithms were observed to achieve better land cover classification performance using only four bands as compared to that using all 144 hyperspectral bands.

58 GEOSCIENCES↗
DOE OSTI2020

The Feasibility of Directly Imaging Nearby Cold Jovian Planets with MIRI/JWST

The upcoming launch of the James Webb Space Telescope (JWST) will dramatically increase our understanding of exoplanets, particularly through direct imaging. Microlensing and radial velocity surveys indicate that some M dwarfs host long-period giant planets. Some of these planets will likely be just a few parsecs away and a few astronomical units from their host stars, a parameter space that cannot be probed by existing high-contrast imagers. We studied whether the coronagraphs on the Mid-infrared Instrument on JWST can detect Jovian-type planets around nearby M dwarfs. For a sample of 27 very nearby M dwarfs, we simulated a sample of Saturn–Jupiter-mass planets with three atmospheric configurations and three orbital separations, observed in three different filters. We found that the f1550c 15.5 μm filter is best suited for detecting Jupiter-like planets. Jupiter-like planets with patchy cloud cover, 2 au from their star, are detectable at 15.5 μm around 14 stars in our sample, while Jupiters with clearer atmospheres are detectable around all stars in the sample. Saturns were most detectable at 10.65 and 11.4 μm (f1065c and f1140c filters), but only with cloud-free atmospheres and within 3 pc (six stars). Surveying all 27 stars would take <170 hr of JWST integration time, or just a few hours for a shorter survey of the most favorable targets. There is one potentially detectable known planet in our sample: GJ 832 b. Observations aimed at detecting this planet should occur in 2024–2026, when the planet is maximally separated from the star.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Phase-resolving spin-wave microscopy using infrared strobe light

The need for sensitively and reliably probing magnetization dynamics has been increasing in various contexts such as studying novel hybrid magnonic systems, in which the spin dynamics strongly and coherently couple to other excitations, including microwave photons, light photons, or phonons. Recent advances in quantum magnonics also highlight the need for employing the magnon phase as quantum state variable, which is to be detected and mapped out with high precision in on-chip micro- and nanoscale magnonic devices. Here, in this study, we demonstrate a facile optical technique that can directly perform concurrent spectroscopic and imaging functionalities with spatial and phase resolutions, using infrared strobe light operating at 1550-nm wavelength. To showcase the methodology, we spectroscopically studied the phaseresolved spin dynamics in a bilayer of Permalloy and yttrium iron garnet Y 3 Fe 5 O 12 (YIG), and spatially imaged the backward-volume spin-wave modes of YIG in the dipolar spin-wave regime. Using the strobe light probe, the detected precessional phase contrast can be directly used to construct the map of the spin wave's wave front, in the continuous-wave regime of spin-wave propagation and in the stationary state, without needing any optical reference path. By selecting the applied field, frequency, and detection phase, the spin-wave images can be made sensitive to the precession amplitude and phase. Our results demonstrate that infrared optical strobe light can serve as a versatile platform for magneto-optical probing of magnetization dynamics, with potential implications in investigating hybrid magnonic systems.

Xiong, Yuzan [University of North Carolina, Chapel↗
DOE OSTI2021

Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics

Mounting evidence indicates dryland ecosystems play an important role in driving the interannual variability and trend of the terrestrial carbon sink. Nevertheless, our understanding of the seasonal dynamics of dryland ecosystem carbon uptake through photosynthesis [gross primary productivity (GPP)] remains relatively limited due in part to the limited availability of long-term data and unique challenges associated with satellite remote sensing across dryland ecosystems. Here, we comprehensively evaluated longstanding and emerging satellite vegetation proxies in their ability to capture seasonal dryland GPP dynamics. Specifically, we evaluated: 1) reflectance-based proxies normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), near infrared reflectance index (NIR v ), and kernel NDVI (kNDVI) from the MODerate resolution Imaging Spectroradiometer (MODIS); and 2) newly available physiologically-based proxy solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI). As a performance benchmark, we used GPP estimates from a robust network of 21 western United States eddy covariance tower sites that span representative gradients in dryland ecosystem climate and functional composition. We found that NIR v and SIF were the best performing GPP proxies and captured complementary aspects of seasonal GPP dynamics across dryland ecosystem types. NIR v offered better performance than the other proxies across relatively low-productivity, sparsely non-evergreen vegetated sites (R 2 = 0.59 ± 0.13); whereas SIF best captured seasonal dynamics across relatively high-productivity sites, including evergreen-dominated sites (R 2 = 0.74 ± 0.07). Notably, across grass-dominated sites, all reflectance-based proxies (NDVI, SAVI, NIRv and kNDVI) showed significant seasonal bias (hysteresis) that strengthened with the total fraction of woody vegetation cover, likely due to seasonal patterns in woody vegetation reflectance that are unrelated to or decoupled from GPP. In conclusion, future efforts to fully integrate the complementary strengths of NIR v and SIF could significantly improve our understanding and representation of dryland GPP dynamics in satellite-based models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Above the Energy Gap Law: Heavy Chalcogenide Substitution in NIR II-Emissive Diradicaloid Qubits

Near-infrared (NIR, 700–1700 nm)- and telecom (∼1260–1625 nm)-emissive molecules are good candidates for biological imaging and quantum sensing applications, respectively; however, bright low energy emission is rare due to exponentially increasing nonradiative decay rates in these regions, a phenomenon known as the energy gap law. Recent literature has emphasized the importance of minimizing skeletal modes to prevent increased nonradiative decay rates, but most organic lumiphores in these regions utilize large, conjugated scaffolds containing many C═C modes. Here we report a compact, telecom-emissive scaffold, tetrathiafulvalene-2,3,6,7-tetraselenate, or TTFts, that displays remarkable air, water, and acid stability, exhibits record quantum yields and brightness values, and retains quantum coherence under ambient conditions. These properties are enabled through methodical selenium substitution, which bathochromically shifts emission while shifting skeletal vibrations to lower energies. This new scaffold validates heavy heteroatom substitution strategies and establishes a new class of bright telecom emitters and robust qubits.

biological imaging↗
DOE OSTI2024

Software For Automated Leak Detection Using Infrared Camera

This code can read in videos or images in either a batch or real-time format. Videos are broken up into frames, and the frames are processed using an optical flow algorithm to decipher movement between adjacent frames. This adherent movement is ran through a convolutional neural network that automatically classifies the contents of the video. Additional content inside the code aids with noisy images and removal of nuisance movement.

Walker, CodyM. [Idaho National Laboratory (INL), I↗
DOE OSTI2020

Keck/NIRC2 L’-band Imaging of Jovian-mass Accreting Protoplanets around PDS 70

We present L’-band imaging of the PDS 70 planetary system with Keck/NIRC2 using the new infrared pyramid wave front sensor. We detected both PDS 70 b and c in our images, as well as the front rim of the circumstellar disk. After subtracting off a model of the disk, we measured the astrometry and photometry of both planets. Placing priors based on the dynamics of the system, we estimated PDS 70 b to have a semimajor axis of 20{sub −4}{sup +3} au and PDS 70 c to have a semimajor axis of 34{sub −6}{sup +12} au (95% credible interval). We fit the spectral energy distribution (SED) of both planets. For PDS 70 b, we were able to place better constraints on the red half of its SED than previous studies and inferred the radius of the photosphere to be 2–3 R {sub Jup}. The SED of PDS 70 c is less well constrained, with a range of total luminosities spanning an order of magnitude. With our inferred radii and luminosities, we used evolutionary models of accreting protoplanets to derive a mass of PDS 70 b between 2 and 4 M {sub Jup} and a mean mass accretion rate between 3 × 10{sup −7} and 8 × 10{sup −7} M {sub Jup}/yr. For PDS 70 c, we computed a mass between 1 and 3 M {sub Jup} and mean mass accretion rate between 1 × 10{sup −7} and 5 × 10{sup −7} M {sub Jup}/yr. The mass accretion rates imply dust accretion timescales short enough to hide strong molecular absorption features in both planets’ SEDs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Leveraging hyperspectral phenotyping for accurate, non-destructive prediction of metabolite profiles in poplar under drought stress

Accurately predicting drought tolerance in woody perennial bioenergy crops is critical for sustainable biomass production under fluctuating precipitation. Hyperspectral imaging (HSI) in the visible-near-infrared (VNIR) and shortwave-infrared (SWIR) ranges offers a promising approach for predicting plant biochemical traits, yet its application in metabolite profiling remains underexplored. We integrated VNIR+SWIR HSI with untargeted metabolomics to investigate drought-induced metabolic shifts in Populus leaves from eight Populus genotypes. Metabolite profiling identified 127 compounds, with 73 showing significant drought responses spanning amino acids (AA), carbohydrates (CHO), phenolic glycosides (PG), organic acids (OA), fatty acids and alcohols (FA), terpenes (T), phenolic metabolites (P), and unclassified metabolites. Spectral analysis revealed consistently higher reflectance across VNIR and SWIR wavelengths in drought-stressed plants, corresponding with increased accumulation of AA and reduced CHO and PG levels. Least absolute shrinkage and selection operator (LASSO) regression modeling identified robust spectral predictors of metabolite concentrations, associating VNIR wavelengths (500–700 nm) predominantly with AA and P, whereas SWIR wavelengths (1680–1700 nm) reliably predicted CHO, OA, and T. Several stable spectral-metabolite associations persisted across the two watering regimes (drought vs. well-watered), highlighting their potential as spectral biomarkers for non-destructive stress monitoring. Minimal genotype-specific variation suggests that observed spectral and metabolic responses were driven primarily by environmental factors, likely reflecting limited genetic diversity among the commercial Populus genotypes examined. This work establishes VNIR+SWIR hyperspectral imaging as a powerful, non-destructive phenotyping tool for precision monitoring and targeted improvement of drought resilience in bioenergy crops.

Biochemical trait prediction↗