Search NASA⌕ Search

SEARCH · Search NASA

Results for “Imaging studies”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

X‑ray Coherent Diffractive Imaging of Large Helium Nanodroplets Doped with Small Molecules

We report the first X-ray coherent diffractive imaging experiment on molecule-doped helium nanodroplets. It complements previous work, where we reported single-shot X-ray coherent diffractive imaging studies of Xe dopant clusters formed in 4He and 3He droplets. These noble gas clusters were used to visualize the impact of rotational excitation of the droplets on the spatial distribution of atomic dopants within the droplets, and to study the differences and connections between quantum and classical droplet rotational motion. Here, we expand our studies to the molecular dopants CF4, CHF3, CH3CN, and SF6, imaged with 1.5 keV photons. We find multiple Bragg spots in the diffraction patterns of molecule-doped droplets with radii of approximately 600 nm, which provide evidence that molecules form elongated clusters with preferential alignment along the angular momentum axis of the 4He droplets, in agreement with our previous results on the aggregation of Xe clusters on quantum vortices. Real-space reconstructions of molecular dopant cluster density profiles are obtained for droplets with smaller radii of approximately 300 nm. The diffuse images suggest the formation of low-density, potentially porous, molecular clusters upon aggregation at T = 0.4 K in 4He droplets. In the normal fluid 3He droplets, molecules aggregate into loose clusters on the droplets' equator, similar to previous observations for Xe atoms. Time-of-flight mass spectra reveal that the doped helium nanodroplet moieties fragment extensively into constituent atomic ions, producing only a small fraction of molecular fragment ions. The findings are discussed in the context of previously proposed schemes to use He droplets as potential tamper materials for ultrafast X-ray imaging experiments.

Feinberg, AlexandraJ↗

Investigating the Theranostic Potential of Elementally Matched [ 43 Sc]Sc-PSMA-617 and [ 47 Sc]Sc-PSMA-617

The theranostic approach, which employs diagnostic radiopharmaceuticals to select patients who would benefit from targeted radiotherapy agents, has become an invaluable strategy for effective medical care. Scandium radionuclides offer the advantage of forming elementally matched and chemically identical diagnostic and therapeutic compounds, making them ideal candidates for this strategy. PSMA-617 is an established prostate-specific membrane antigen targeting agent and can be used as a proof of concept to investigate 43 Sc, the diagnostic nuclide, and 47 Sc, the therapeutic nuclide, as a theranostic pair. Methods: Cellular uptake, competitive binding assays, and internalization studies were carried out using LNCaP or PC-3 cell lines. [ 43 Sc]Sc-PSMA-617 was used in PET imaging studies in LNCaP or PC-3 tumor models, with time points ranging from 1–9 h. LNCaP tumor-bearing mice injected with [ 47 Sc]Sc-PSMA-617 were imaged using SPECT up to 48 h. A longitudinal study was carried out using LNCaP tumor-bearing mice imaged with [ 43 Sc]Sc-PSMA-617 prior to receiving a therapeutic dose of [ 47 Sc]Sc-PSMA-617. Results: 43 Sc and 47 Sc were incorporated into PSMA-617 at radiochemical yields of >99%. Cellular uptake studies demonstrated high uptake and specificity to PSMA receptors for [ 47 Sc]Sc-PSMA-617. In vivo PET studies showed specificity of [ 43 Sc]Sc-PSMA-617 while SPECT studies demonstrated tumor retention of [ 47 Sc]Sc-PSMA-617 up to 48 h. [ 47 Sc]Sc-PSMA-617 demonstrated therapeutic efficacy by delaying tumor growth and increasing survival rates from a single administered dose in xenograft models. More importantly, the PET results from [ 43 Sc]Sc-PSMA-617 PET were highly correlated with the therapeutic response from [ 47 Sc]Sc-PSMA-617, showing that 43 Sc PET data can predict therapeutic outcomes in individual animals from 47 Sc agents, even in animals sharing a genetic background and implanted with tumors from the same cell line. Conclusions: Two chemically identical, PSMA-targeting radioscandium pharmaceuticals demonstrated in vivo stability, specificity and retention in PSMA+ tumor models. A theranostic study showed that a higher 43 Sc PET SUVmean was strongly correlated to therapeutic response from the 47 Sc agent, demonstrating that 43 Sc and 47 Sc can be used as an elementally matched theranostic pair.

Biodistribution↗

A Prodrug Strategy to Conditionally Trap Therapeutic Payloads for Improved Tumor Retention

Altered extracellular proteolysis has been exploited to selectively activate therapeutics in diseases such as cancer; however, once activated, extracellular drugs can diffuse away, limiting efficacy. We address this challenge by coupling proteolytic activation with membrane tethering to retain drugs within diseased tissue. To accomplish this, we developed “restricted interaction peptides” (RIPs), a delivery platform that leverages elevated proteolytic activity to activate membrane-interacting peptides, localizing cargos near the site of proteolysis. We demonstrate that RIPs can deliver diverse therapeutic cargos, including cytotoxins and radioisotopes. As proof of concept, we engineered “FRIP,” a RIP designed for cleavage by fibroblast activation protein (FAP), an endoprotease upregulated in solid tumors and fibrosis. Efficient P4–P4’ substrate sequences were identified and incorporated into FRIPs. Cell-based studies showed that, upon activation, the peptide adhered to membranes rapidly internalized and successfully delivered therapeutic cargos. Consistent with this, FRIPs delivering MMAE inhibited proliferation in an FAP-dependent manner. Imaging studies confirmed tumor targeting with minimal uptake in normal tissues. Finally, FRIPs delivering MMAE or Cu-67 exhibited potent antitumor effects. These findings establish membrane tethering as a strategy to enhance drug retention.

60 APPLIED LIFE SCIENCES↗

Towards the Stable Chelation of Radioantimony(V) for Targeted Auger Theranostics

Abstract Antimony‐119 ( 119 Sb) is one of the most attractive Auger‐electron emitters identified to date, but it remains practically unexplored for targeted radiotherapy because no chelators have been identified to stably bind this metalloid in vivo. In a departure from current studies focused on chelator development for Sb(III), we explore the chelation chemistry of Sb(V) using the tris‐catecholate ligand TREN‐CAM. Through a combination of radiolabeling, spectroscopic, solid‐state, and computational studies, the radiochemistry and structural chemistry of TREN‐CAM with 1XX/nat Sb(V) were established. The resulting [ 1XX Sb]Sb–TREN‐CAM complex remained intact for several days in human serum, signifying high stability under biological conditions. Finally, the first in vivo single photon emission computed tomography and positron emission tomography imaging studies were carried out using 117 Sb, the diagnostic analogue of 119 Sb. These studies revealed marked differences in the uptake and distribution of activity in mice administered unchelated [ 117 Sb]Sb(OH) 6 – versus [ 117 Sb]Sb–TREN‐CAM, suggesting that 117 Sb is largely retained by TREN‐CAM over the time course of the study. Collectively, these findings demonstrate the most physiologically stable complex of no‐carrier‐added 1XX Sb yet reported, offering new promise for the clinical implementation of radioantimony in nuclear medicine. Our results also establish the feasibility of 117 Sb as an elementally matched partner to 119 Sb for theranostic applications.

Olson, Aeli P. [Department of Medical Physics Univ↗

Towards the Stable Chelation of Radioantimony(V) for Targeted Auger Theranostics

Antimony-119 ( 119 Sb) is one of the most attractive Auger-electron emitters identified to date, but it remains practically unexplored for targeted radiotherapy because no chelators have been identified to stably bind this metalloid in vivo. In a departure from current studies focused on chelator development for Sb(III), we explore the chelation chemistry of Sb(V) using the tris-catecholate ligand TREN-CAM. Through a combination of radiolabeling, spectroscopic, solid-state, and computational studies, the radiochemistry and structural chemistry of TREN-CAM with 1XX/nat Sb(V) were established. The resulting [ 1XX Sb]Sb–TREN-CAM complex remained intact for several days in human serum, signifying high stability under biological conditions. Finally, the first in vivo single photon emission computed tomography and positron emission tomography imaging studies were carried out using 117 Sb, the diagnostic analogue of 119 Sb. These studies revealed marked differences in the uptake and distribution of activity in mice administered unchelated [ 117 Sb]Sb(OH) 6 – versus [ 117 Sb]Sb–TREN-CAM, suggesting that 117 Sb is largely retained by TREN-CAM over the time course of the study. Collectively, these findings demonstrate the most physiologically stable complex of no-carrier-added 1XX Sb yet reported, offering new promise for the clinical implementation of radioantimony in nuclear medicine. In conclusion, our results also establish the feasibility of 117 Sb as an elementally matched partner to 119 Sb for theranostic applications.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Interactions of a Microdischarge with a Premixed Flame (Final Technical Report)

In this project we introduced an experimental platform that facilitates the study of the two-way interaction of plasma and flame, and the exploration of the impact of the spatial location of the discharge on its kinetics, in a controlled environment. The experimental platform is a mesoscale CH4/air premixed flame burner that also acts as a dielectric barrier discharge (DBD) operated by nanosecond pulsed voltage. A unique feature of this setup is that the DBD utilizes transparent electrodes, made of Indium Tin Oxide (ITO), to unlock optical access along the line-of-sight parallel to the dominant electric field. This platform is suitable to study both the forward problem (impact of plasma-on-flame), which manifests itself as a modified flame speed as well as flame wrinkling; and the backward problem (impact of flame-on-plasma), which includes plasma regime transitions, between microdischarges and uniform modes, driven by the flame passage. Prior work at MIT has focused on electrical measurements and direct imaging studies of the plasma-flame interaction through the ITO electrode. This project, which was awarded experimental runtime at the Low-temperature Plasma Research Facility (PRF) at Sandia National Laboratories, quantifies the flame-plasma interaction through temporally resolved measurement of key radicals (oxygen atom, O) produced by the nanosecond repetitively pused discharge (NRPD) in an individual microdischarge, using two-photon absorption laser-induced fluorescence (TALIF).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Invariant discovery of features across multiple length scales: Applications in microscopy and autonomous materials characterization

Physical imaging is a foundational characterization method in areas from condensed matter physics and chemistry to astronomy and spans length scales from atomic to universe. Images encapsulate crucial data regarding atomic bonding, materials microstructures, and dynamic phenomena such as microstructural evolution and turbulence, among other phenomena. The challenge lies in effectively extracting and interpreting this information. Variational Autoencoders (VAEs) have emerged as powerful tools for identifying the underlying factors of variation in image data, providing a systematic approach to distilling meaningful patterns from complex data sets. However, a significant hurdle in their application is the definition and selection of appropriate descriptors reflecting local structures. Here, we introduce the scale-invariant VAE approach (SI-VAE) based on the progressive training of the VAE with the descriptors sampled at different length scales. The SI-VAE allows the discovery of the length scale-dependent factors of variation in the system. Here, we illustrate this approach using the ferroelectric domain images and generalize it to the movies of the electron-beam induced phenomena in graphene and topography evolution across combinatorial libraries. This approach can further be used to initialize the decision making in automated experiments including structure–property discovery and can be applied across a broad range of imaging methods. This approach is universal and can be applied to any spatially resolved data including both experimental imaging studies and simulations, and can be particularly useful for exploration of phenomena such as turbulence and scale-invariant transformation fronts.

36 MATERIALS SCIENCE↗

Visualizing energy transfer between redox-active colloids

Redox-active colloids (RACs) represent a novel class of energy carriers that exchange electrical energy upon contact. Understanding contact-mediated electron transfer dynamics in RACs offers insights into physical contact events in colloidal suspensions and enables quantification of electrical energy transport in nonconjugated polymers. Redox-based electron transport was directly observed in monolayers of micron-sized RACs containing ethyl-viologen side groups via fluorescence microscopy through an unexpected nonlinear electrofluorochromism that is quantitatively coupled to the redox state of the colloid. Via imaging studies, using this electrofluorochromism, the apparent charge transfer diffusion coefficient D CT of the RAC was easily determined. The visualization of energy transport within suspensions of redox-active colloids was also demonstrated. Our work elucidates fundamental mechanisms of energy transport in colloidal systems, informs the development of next-generation redox flow batteries, and may inspire new designs of smart active soft matter including conductive polymers for applications ranging from electrochemical sensors and organic electronics to colloidal robotics.

Qu, Alan Subing [Univ. of Illinois at Urbana-Champ↗

High-Throughput Computing: Case Study of Medical Image Processing Applications

HPC is designed for large-scale simulations using monolithic codes of tightly coupled processes highly optimized to deliver decreased time to solution. Medical image processing is not a traditional field of HPC. Similar to AI applications, medical image processing parses large datasets, typically multiple times, to support a variety of studies for classification, diagnosis or monitoring purposes. The convergence of AI, HPC and Big Data encouraged more fields using image processing to transition to HPC. However, not all applications benefit from the same optimizations. In this paper we focus on high throughput medical image processing applications that analyze a huge dataset of small MRI images and that require HPC systems to decrease the time of parsing the entire dataset and not individual MRIs. We show in this research the performance of running SLANT, an image processing application for a whole brain segmentation, on large-scale systems and highlight performance limitations. We present optimizations prioritizing throughput that exhibit a 3.5x speed-up on the Summit Supercomputer that can be used as a baseline for building a high-throughput execution framework for other HPC systems.

Predescu, Maria↗

Quantum ghost imaging microscopy depth-of-field study

Quantum ghost imaging approaches have been proposed to enhance biological microscopy, for example, using 2D visible detectors to provide IR images or providing additional dimensions of spatial or spectral information. Toward the goal of making such imaging schemes practical, we compare image quality and depth-of-field between traditional images and ghost images at the same excitation levels. We measure how image quality and depth-of-field depend on the parameters of the entangled light produced using type-I spontaneous parametric down-conversion (SPDC). We use a pair of time-synchronized, photon-timing single-photon avalanche diode (SPAD) array detectors to capture two distinct microscope imaging paths simultaneously on a photon-pair-by-photon-pair basis: one in a traditional imaging pathway and the other a quantum ghost imaging pathway. We calculate the depth-of-field, resolution, contrast, and signal-to-noise ratio (SNR) through the parameter space of a β-Barium Borate (BBO) type-I bulk non-linear crystal length and angle. Our results provide a basis for choosing parameters for quantum ghost imaging with type-I SPDC sources.

47 OTHER INSTRUMENTATION↗

Harnessing Machine Learning and Data Fusion for Accurate Undocumented Well Identification in Satellite Images

This study utilizes satellite data to detect undocumented oil and gas wells, which pose significant environmental concerns, including greenhouse gas emissions. Three key findings emerge from the study. Firstly, the problem of imbalanced data is addressed by recommending oversampling techniques like Rotation–GaussianBlur–Solarization data augmentation (RGS), the Synthetic Minority Over-Sampling Technique (SMOTE), or ADASYN (an extension of SMOTE) over undersampling techniques. The performance of borderline SMOTE is less effective than that of the rest of the oversampling techniques, as its performance relies heavily on the quality and distribution of data near the decision boundary. Secondly, incorporating pre-trained models trained on large-scale datasets enhances the models’ generalization ability, with models trained on one county’s dataset demonstrating high overall accuracy, recall, and F1 scores that can be extended to other areas. This transferability of models allows for wider application. Lastly, including persistent homology (PH) as an additional input improves performance for in-distribution testing but may affect the model’s generalization for out-of-distribution testing. A careful consideration of PH’s impact on overall performance and generalizability is recommended. Overall, this study provides a robust approach to identifying undocumented oil and gas wells, contributing to the acceleration of a net-zero economy and supporting environmental sustainability efforts.

SMOTE↗

NETL RDE Image Classification Dataset 2025 - 14 Classes

Dataset including high-speed down-axis RDE images used for updated image classification study. This dataset includes 180,000 images with 14 classifications: 1CW, 1CCW, 2CW, 2CCW, 3CW, 3CCW, Deflagration, 4CW, 4CCW, 5CW, and 5CCW. Images are cropped to center annulus, and resized to 301x301 pixels. Images are filtered using the AFRL Beta correction factor.

Dataset↗

NETL RDE Image Classification Dataset 2020 - 10 Classes

Dataset including high-speed down-axis RDE images used for updated image classification study. This dataset includes 100,000 images with 10 classifications: 1CW, 1CCW, 2CW, 2CCW, 3CW, 3CCW, and Deflagration. Images are cropped to center annulus, and resized to 301x301 pixels. Images are filtered using the AFRL Beta correction factor.

AS↗

Initial Split Disk Mechanical Testing Studies with a Digital Image Correlator

Nuclear graphite plays a pivotal role in the advanced reactor program. Consequently, developing a viable method to measure and evaluate small samples is essential. The Digital Image Correlation (DIC) technique allows for the examination of much smaller components in real-time applications, particularly concerning reactor capsule design and placement within the reactor. These samples become crucial for understanding the behavior of nuclear graphite before and after radiation exposure. They serve as a means to analyze changes and effectively measure the mechanical strength properties, which may or may not alter following irradiation.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Forward modeling fluctuations in the DESI LRGs target sample using image simulations

We use the forward modeling pipeline, Obiwan, to study the imaging systematics of the Luminous Red Galaxies (LRGs) targeted by the Dark Energy Spectroscopic Instrument (DESI). Imaging systematics refers to the false fluctuation of galaxy densities due to varying observing conditions and astrophysical foregrounds corresponding to the imaging surveys from which DESI LRG target galaxies are selected. We update the Obiwan pipeline, which we previously developed to simulate the optical images used to target DESI data, to further simulate WISE images in the infrared. This addition allows simulating the DESI LRGs sample, which utilizes WISE data in the target selection. Deep DESI imaging data combined with a method to account for biases in their shapes is used to define a truth sample of potential LRG targets. We inject these data evenly throughout the DESI Legacy Imaging Survey footprint at declinations between -30 and 32.375 degrees. We simulate a total of 15 million galaxies to obtain a simulated LRG sample (Obiwan LRGs) that predicts the variations in target density due to imaging properties. We find that the simulations predict the trends with depth observed in the data, including how they depend on the intrinsic brightness of the galaxies. We observe that faint LRGs are the main contributing source of the imaging systematics trend induced by depth. We also find significant trends in the data against Galactic extinction that are not predicted by Obiwan. These trends depend strongly on the particular map of Galactic extinction chosen to test against, implying systematic contamination in the Galactic extinction maps is a likely root cause (e.g., Cosmic-Infrared Background, dust temperature correction). We additionally observe a morphological change of the DESI LRGs population evidenced by a correlation between OII emission line average intensity and the size of the z-band PSF. This effect most likely results from uncertainties in background subtraction. The detailed findings we present should be used to guide any observational systematics mitigation treatment for the clustering of the DESI LRGs sample.

79 ASTRONOMY AND ASTROPHYSICS↗

Toward memory-efficient melt pool monitoring: a classification framework using event-based imaging and sparse sensing technique

Vision sensors like CMOS and CCD cameras are often used for in-process monitoring of melt pools in laser-based additive and welding processes, but they require transferring large amounts of data and computational processing resources. Event-based neuromorphic imagery, on the other hand, detects only the change in pixel intensity, thus potentially reducing the data amount and latency. With an event imager, this study develops a framework for melt pool condition classification, including image construction, time scale selection, optimal pixel selection, and sparse classification, to achieve a highly memory-efficient scheme. These are based on sparse sensing techniques with singular value decomposition (SVD) and QR pivoting, the two fundamental matrix transformations for linear dimensionality reduction. The framework is then validated by classifying a controlled experiment by exciting various mode shapes of liquid gallium pools of varying depths (3, 6, and 8 mm). At 200 pixels, the classifier can reach overall accuracy of 75%, while at 2000 pixels (0.013% of the total possible pixels), the accuracy is nearly 90% (89.86%). At the same number of pixels, random selection can only achieve 46% and 67%, respectively. The memory savings of the sparsely sampled event data compared to a conventional imager is about 500 times. In addition to performance, implementation and limitations of the framework are also discussed.

42 ENGINEERING↗