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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

BCARS Simulated Phantom Dataset for Evaluation of Processing Pipelines

Broadband coherent anti-Stokes Raman scattering (BCARS) microscopy is a powerful label-free biological imaging technique, but the raw signal requires careful processing. The vibrationally resonant (Raman) fingerprint signal is usually small compared with instrumental noise sources and the nonresonant background (NRB) inherent in the BCARS signal. Fortunately, the NRB exhibits a systematic phase relationship with the coherent Raman response, acting as a heterodyne amplifier for the weak fingerprint signal. Due to this heterodyne effect, the Raman response can be recovered quantitatively and invariantly across different instruments, provided the NRB shape is known. Even with heterodyne amplification, the amplitudes of fingerprint signal components are often comparable to system noise. Singular value decomposition (SVD), which utilizes spatial information, is often employed for additional noise filtering. Consequently, finding optimal processing parameters to properly distinguish the NRB and Raman responses and suppress noise in the complex BCARS signal requires a reference system that realistically represents the spectral and spatial properties of BCARS signals obtained from biological samples. We present a digital tissue phantom that meets these criteria as a tool for testing candidate signal processing pipelines. The digital phantom is generated with simulated hyperspectral Raman images having system-specific noise and background characteristics. Here, we analyze phantom datasets with differing background and signal-to-noise conditions to evaluate their impact on the performance of multiple signal processing pipelines. Specifically, we investigate the application of a Butterworth filter-based routine to directly estimate the NRB from the BCARS signal. Additionally, we evaluate a Lorentzian wavelet transform as an alternative to the Hilbert transform for extracting the Raman spectrum from the BCARS signal. While we demonstrate this phantom for BCARS, it can be used for any spectroscopic Raman imaging approach.

Dixon, Jessica Z. [Georgia Institute of Technology↗
NASA NTRS1994

BIOME: An Ecosystem Remote Sensor Based on Imaging Interferometry

Until recent times, optical remote sensing of ecosystem properties from space has been limited to broad band multispectral scanners such as Landsat and AVHRR. While these sensor data can be used to derive important information about ecosystem parameters, they are very limited for measuring key biogeochemical cycling parameters such as the chemical content of plant canopies. Such parameters, for example the lignin and nitrogen contents, are potentially amenable to measurements by very high spectral resolution instruments using a spectroscopic approach. Airborne sensors based on grating imaging spectrometers gave the first promise of such potential but the recent decision not to deploy the space version has left the community without many alternatives. In the past few years, advancements in high performance deep well digital sensor arrays coupled with a patented design for a two-beam interferometer has produced an entirely new design for acquiring imaging spectroscopic data at the signal to noise levels necessary for quantitatively estimating chemical composition (1000:1 at 2 microns). This design has been assembled as a laboratory instrument and the principles demonstrated for acquiring remote scenes. An airborne instrument is in production and spaceborne sensors being proposed. The instrument is extremely promising because of its low cost, lower power requirements, very low weight, simplicity (no moving parts), and high performance. For these reasons, we have called it the first instrument optimized for ecosystem studies as part of a Biological Imaging and Observation Mission to Earth (BIOME).

Peterson, David L.↗
DOE OSTI2025

Enhanced upconversion and photoconductive nanocomposites of lanthanide-doped nanoparticles functionalized with low-vibrational-energy inorganic ligands

Upconverting nanoparticles (UCNPs) convert near-infrared (IR) light into higher-energy visible light, allowing them to be used in applications such as biological imaging, nano-thermometry, and photodetection. It is well known that the upconversion luminescent efficiency of UCNPs can be enhanced by using a host material with low phonon energies, but the use of low-vibrational-energy inorganic ligands and non-epitaxial shells has been relatively underexplored. Here, we investigate the functionalization of lanthanide-doped NaYF4 UCNPs with low-vibrational-energy Sn2S64- ligands. Raman spectroscopy and elemental mapping are employed to confirm the binding of Sn2S64- ligands to UCNPs. This binding enhances upconversion efficiencies up to a factor of 16, consistent with an increase in the luminescent lifetimes of the lanthanide ions. Annealing Sn2S64--capped UCNPs results in the formation of a nanocomposite comprised of UCNPs embedded within an interconnected matrix of SnS2, enabling each UCNP to be electrically accessible through the semiconducting SnS2 matrix. This facilitates the integration of UCNPs into electronic devices, which we demonstrate through the fabrication of a UCNP-SnS2 photodetector that detects UV and near-IR light. Our findings show the promise of using inorganic capping agents to enhance the properties of UCNPs while facilitating their integration into optoelectronic devices.

Pan, Jia-Ahn↗
DOE OSTI2024

Towards Autonomous Experiments by Connecting High Performance Microscopy with High Performance Computing

The digitization of controls, data, and analysis in microscopy is bringing the idea of autonomous microscopes closer to reality than ever before. Automated transmission electron microscopy (TEM) is already fairly routine for some experiments the only require simple repetitive tasks such as imaging biological macromolecules for single particle cryoEM [1], tilt series for electron tomography [2], and movies for crystallography [3]. The vast majority of TEM experiments are conducted completely by human operators who choose the regions of interest, optimize experimental parameters, and make decisions about data quality visually during an experiment. The field is still a long way from having completely autonomous TEMs that can adapt to sample difficulties and tune experimental parameters based on data quality and desired experimental outcomes. Part of the issue is the lack of capability for feeding information learned from on-line, live data analysis back into the on-going experiment [4]. Furthermore, this presentation will discuss current capabilities for large scale data reduction and analysis using high performance computing (i.e. supercomputing) and progress towards developing a true feed-back loop that places data analysis and theory in the experimental loop.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Third-order photon correlations extract single-nanocrystal multiexciton properties in solution

Colloidal semiconductor nanocrystals are considered promising materials for high-flux optical applications, including lasing, light-emitting diodes, biological imaging, and quantum optics. In high-flux applications, multiexcitons can significantly contribute to emission, influencing its brightness, spectral purity, and kinetics. As a result, understanding and controlling multiexciton emission in colloidal nanocrystal materials is of the utmost importance. In the past, single-nanocrystal photon correlation methods have been applied to understand biexciton and triexciton efficiencies, lifetimes, and spectra. While powerful, such methods suffer from user selection bias and require stable emission from single nanocrystals. To compensate for this shortcoming, second-order correlation methods were developed to extract sample-averaged biexciton properties from a solution of nanocrystals. Until now, however, the analogous third-order solution photon correlation methods remained unexplored. In this work, we present a pair of third-order photon correlation techniques to obtain the sample-averaged single-nanocrystal triexciton quantum yield and lifetime in a solution-phase experiment. These techniques derive from the relationship between the Poisson probability of nanocrystal photon absorption and the intrinsic probability of nanocrystal photon emission. We validate the theoretical background of these techniques by creating a numerical model to simulate the diffusion and emission of many nanocrystals in solution. Our simulations confirm that the average triexciton quantum yield and triexciton lifetime can be extracted from a solution of nanocrystals. These techniques will enable researchers to gain a better understanding of the fundamental multiexciton properties of colloidal nanocrystals.

Horowitz, Jonah R. [Massachusetts Institute of Tec↗
DOE OSTI2024

Functionalization of nitrogen vacancy-containing nanodiamonds with a metal-organic framework for quantum sensing applications

Nitrogen vacancy (NV)-containing nanodiamonds (NDs) are an important material in applications such as biological imaging, catalysis, and, in particular, quantum sensing. Careful manipulation of the surface coating on NV NDs is essential for both enhancing quantum sensor performance and for tuning selectivity towards specific sensing targets. Here, we demonstrate a simple synthetic approach for functionalizing NV NDs with the zeolitic imidazole framework-8 (ZIF-8) metal–organic framework (MOF), providing a well-ordered, porous scaffold for immobilizing target analytes near the NV ND surface. The composites were structurally characterized by x-ray diffraction, electron microscopy, and X-ray photoelectron spectroscopy, and these results were all consistent with NV NDs fully encapsulated by ZIF-8. Critically, the luminescent properties of the NV NDs, which are vital for quantum sensing experiments such as optically detected magnetic resonance (ODMR), are unchanged by the MOF coating. Moreover, spin relaxometry experiments indicate that the ZIF-8 coating significantly enhances the NV ND spin longitudinal relaxation time T1, a critical quantum parameter for sensing applications. Given the tremendous structural diversity of MOFs, the NV ND@MOF composites are an exciting material class with exciting implications for the development of high-performance quantum sensors.

Crawford, Scott↗
NASA NTRS2000

Process of changing the refractive index of a composite containing a polymer and a compound having large dipole moment and polarizability and applications thereof

Fused ring bridge, ring locked dyes that form thermally stable photorfractive compositions. The fused ring bridge structures are .pi.-conjugated bonds in benzene-, naphthalene- or anthracene-derived fused ring systems that connect donor and acceptor groups. The donor and acceptor groups contribute to a high molecular dipole moment and linear polarizability anisotropy. The polarization characteristics of the dye molecules are stabilized since the bonds in the fused ring bridge are not susceptible to rotation, reducing the opportunity for photoisomerization. The dyes are compatible with polymeric compositions, including thermoplastics. The dyes are electrically neutral but have charge transport, electronic and orientational properties such that upon illumination of a composition containing the dye, the dye facilitates refractive index modulation and a photorefractive effect that can be utilized advantageously in numerous applications such as in optical quality devices and biological imaging.

Marder, Seth R.↗
NASA NTRS2002

Thermally stable molecules with large dipole moments and polarizabilities and applications thereof

Disclosed are fused ring bridge, ring-locked dyes that form thermally stable photorefractive compositions. The fused ring bridge structures are .pi.-conjugated bonds in benzene-, naphthalene- or anthracene-derived fused ring systems that connect donor and acceptor groups. The donor and acceptor groups contribute to a high molecular dipole moment and linear polarizability anisotropy. The polarization characteristics of the dye molecules are stabilized since the bonds in the fused ring bridge are not susceptible to rotation, reducing the opportunity for photoisomerization. The dyes are compatible with polymeric compositions, including thermoplastics. The dyes are electrically neutral but have charge transport, electronic and orientational properties such that upon illumination of a composition containing the dye, the dye facilitates refractive index modulation and a photorefractive effect that can be utilized advantageously in numerous applications such as in optical quality devices and biological imaging.

Marder, Seth R.↗
NASA NTRS2010

Development of a Solar Array Drive Assembly for CubeSat

Small satellites and in particular CubeSats, have increasingly become more viable as platforms for payloads typically requiring much larger bus structures. As advances in technology make payloads and instruments for space missions smaller, lighter and more power efficient, a niche market is emerging from the university community to perform rapidly developed, low-cost missions on very small spacecraft - micro, nano, and picosatellites. In just the last few years, imaging, biological and new technology demonstration missions have been either proposed or have flown using variations of the CubeSat structure as a basis. As these missions have become more complex, and the CubeSat standard has increased in both size (number of cubes) and mass, available power has become an issue. Body-mounted solar cells provide a minimal amount of power; deployable arrays improve on that baseline but are still limited. To truly achieve maximum power, deployed tracked arrays are necessary. To this end, Honeybee Robotics Spacecraft Mechanisms Corporation, along with MMA of Nederland Colorado, has developed a solar array drive assembly (SADA) and deployable solar arrays specifically for CubeSat missions. In this paper, we discuss the development of the SADA.

Passaretti, Mike↗
DOE OSTI2024

Simulation Study of High-Precision Characterization of MeV Electron Interactions for Advanced Nano-Imaging of Thick Biological Samples and Microchips

The resolution of a mega-electron-volt scanning transmission electron microscope (MeV-STEM) is primarily governed by the properties of the incident electron beam and angular broadening effects that occur within thick biological samples and microchips. A precise understanding and mitigation of these constraints require detailed knowledge of beam emittance, aberrations in the STEM column optics, and energy-dependent elastic and inelastic critical angles of the materials being examined. This simulation study proposes a standardized experimental framework for comprehensively assessing beam intensity, divergence, and size at the sample exit. This framework aims to characterize electron-sample interactions, reconcile discrepancies among analytical models, and validate Monte Carlo (MC) simulations for enhanced predictive accuracy. Our numerical findings demonstrate that precise measurements of these parameters, especially angular broadening, are not only feasible but also essential for optimizing imaging resolution in thick biological samples and microchips. By utilizing an electron source with minimal emittance and tailored beam characteristics, along with amorphous ice and silicon samples as biological proxies and microchip materials, this research seeks to optimize electron beam energy by focusing on parameters to improve the resolution in MeV-STEM/TEM. This optimization is particularly crucial for in situ imaging of thick biological samples and for examining microchip defects with nanometer resolutions. Our ultimate goal is to develop a comprehensive mapping of the minimum electron energy required to achieve a nanoscale resolution, taking into account variations in sample thickness, composition, and imaging mode.

36 MATERIALS SCIENCE↗
NASA NTRS2023

Surface Biology and Geology Imaging Spectrometer: A Case Study to Optimize the Mission Design Using Intrinsic Dimensionality

The information content that can be derived from spectroscopic imagery tends to increase with finer ground sampling distance, finer spectral sampling, more frequent revisit, and higher signal-to-noise ratios (SNRs). However, these parameters are not independent, and it is thus impossible to design a space-borne imaging spectrometer to maximize all of them simultaneously. We present an instrument model and simulation environment that enable us to find the optimal combination of these four mission design parameters, using intrinsic dimensionality (ID) as the metric. ID is the size of the signal subspace – the maximum degrees of freedom when noise can be disregarded – and is a metric that is independent of any one particular algorithm or application area. This study is important for upcoming missions such as NASA's Earth System Observatory mission to study the Earth's Surface Biology and Geology (SBG), which will comprise a visible to shortwave infrared spectrometer in addition to a multi-channel thermal radiometer on a separate platform. When evaluating a desert site and a tropical forested site, we find that spectral resolution drives information content, with a significant drop in normalized ID (15–45% decrease) when simulating 15 nm spectral sampling as opposed to 10 nm spectral sampling. However, there was some variation between sites, with the forested site benefiting from 5 nm spectral sampling, whereas the desert site had poorer results at this resolution, due to the impact on noise. At 10 nm spectral sampling, ground sampling distances in the range 30–50 m provided the optimal balance between spatial resolution and SNR, although more frequent revisit, potentially by combining data from multiple missions, would maximize total information content.

Mission design↗
DOE OSTI2025

Time-resolved detectors for quantum ghost imaging

Quantum ghost imaging is a method that utilizes the correlated detection of two photons to generate an image. One photon is detected by an imaging sensor and the other by a single-element bucket detector. The selection of the imaging sensor and its capabilities relative to the bucket detector impact the quality of the ghost images. This work examines a SPAD array and a photocathode detector as imaging sensors for quantum ghost imaging. We discuss how to achieve optimal images using these two technologies. We also demonstrate that these devices are able to generate ghost images at 1Hz frame rates, expanding the technique to biologically relevant time scales.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Missing Wedge Completion via Unsupervised Learning with Coordinate Networks

Cryogenic electron tomography (cryoET) is a powerful tool in structural biology, enabling detailed 3D imaging of biological specimens at a resolution of nanometers. Despite its potential, cryoET faces challenges such as the missing wedge problem, which limits reconstruction quality due to incomplete data collection angles. Recently, supervised deep learning methods leveraging convolutional neural networks (CNNs) have considerably addressed this issue; however, their pretraining requirements render them susceptible to inaccuracies and artifacts, particularly when representative training data is scarce. To overcome these limitations, we introduce a proof-of-concept unsupervised learning approach using coordinate networks (CNs) that optimizes network weights directly against input projections. This eliminates the need for pretraining, reducing reconstruction runtime by 3–20× compared to supervised methods. Our in silico results show improved shape completion and reduction of missing wedge artifacts, assessed through several voxel-based image quality metrics in real space and a novel directional Fourier Shell Correlation (FSC) metric. Our study illuminates benefits and considerations of both supervised and unsupervised approaches, guiding the development of improved reconstruction strategies.

42 ENGINEERING↗
NASA NTRSDate not supplied

Enabling Space Biological Knowledge Discovery Through Image and Video Data Sharing

Increased biomedical risks and challenges associated with deep space missions and experiments (cis-Lunar, Mars transit/surface) require new knowledge discovery and development of novel ecosystems. Supporting distant and long-duration missions and experiments requires biological data (from yeast, microbes, fruit flies, C. elegans, plants, crops, rodents, humans) be findable, accessible, interoperable, reusable (FAIR), and maximally open-access. As data-intensive, bioinformatic, meta-analytical, and computer-assisted approaches continue to be a centerpiece of modern research, the NASA Biological and Physical Sciences division is expanding its Open Science capabilities beyond NASA GeneLab. The NASA Ames Life Sciences Data Archive (ALSDA) is a repository which is responsible for collecting and access to space biological imagery and video, alongside tabular and environmental data. In this presentation, we will discuss strategies dealing with archiving, curating, and accessibility of images from very distinct imaging modalities (e.g., micro-computed tomography, magnetic resonance imaging, photographic images of plants, fluorescence microscopy, behavioral videos, etc.). There are two main challenges: 1. Open-source data storage and 2. Metadata related to the imagery-video. Both have been solved by leveraging two existing open-source systems. For data storage, ALSDA is utilizing components through the Open Microscopy Environment (OME), which can read most imaging proprietary formats and display on a web interface complex multidimensional images (Z stack, multi-channel, temporal, spectral). Most technical metadata from imaging modalities are captured seamlessly. For metadata capturing experimental details, ALSDA (like GeneLab) uses the ISA-Tab specification which relies on the ISA data model to order and classify metadata. The ISA data model uses a tree structure with three files to capture the metadata: The top layer is the Investigations file, the second layer is the Study file(s), and the last layer is the Assay file(s). We believe such an approach may be useful for other types of image research data from other investigators in the AGU community.

imaging↗
NASA NTRSDate not supplied

Enabling Space Biological Knowledge Discovery Through Image and Video Data Sharing

Increased biomedical risks associated with deep space crewed missions (cis-Lunar, Mars transit/surface) require development of health countermeasures, novel ecosystem support, risk modeling, and fundamental space biological knowledge discovery. Molecular-omics, physiological-phenotypic-behavioral, and environmental-radiation telemetry data from space biological and health studies are needed for reuse by scientists to address these tasks. The data as well as space-relevant biospecimens are being made more findable, accessible, interoperable, and reusable through NASA’s Open Science Data Repository (OSDR). This new OSDR umbrella grouping includes NASA GeneLab, the NASA Ames Life Sciences Data Archive (ALSDA), and the NASA Biological Institutional Scientific Collection. The OSDR system design appropriately handles metadata and processed-tabular results from ALSDA studies collected from space experiments. But raw and processed ALSDA bioimage and video datasets require an expansion of OSDR’s data architecture to handle ingestion, curation, and egress. The academic-industry bioimaging field saw a scientific renaissance in the past several years through leveraging open-source software, international collaborations, machine learning, and other open science/programming approaches. As crewed missions and more biological experiments are on the deep space horizon, OSDR is embracing data stewardship through listening to feedback from subject matter experts and designing an expanded architecture which is appropriate for NASA’s goals to enable analysis and reuse of bioimaging and video data for the public science community.Discovery Through Image and Video Data Sharing

space biology↗
NASA NTRS2001

Phase sensitive x-ray diffraction imaging of defects in biological macromolecular crystals

Conventional x-ray diffraction topography is currently used to map defects in the bulk of protein crystals, but the lack of sufficient contrast is frequently a limiting factor. We experimentally demonstrate that this barrier can be circumvented using a method that combines phase sensitive and diffraction imaging principles. Details of defects revealed in tetragonal lysozyme and cubic ferritin crystals are presented and discussed. The approach enabling the detection of the phase changes of diffracted x rays should prove to be useful in the study of defect structures in a broad range of biological macromolecular crystals.

Muramidase/chemistry↗
NASA NTRS2002

Phase Sensitive X-Ray Diffraction Imaging of Defects in Biological Macromolecular Crystals

Characterization of defects and/or disorder in biological macromolecular crystals presents much greater challenges than in conventional small-molecule crystals. The lack of sufficient contrast of defects is often a limiting factor in x-ray diffraction topography of protein crystals. This has seriously hampered efforts to understand mechanisms and origins of formation of imperfections, and the role of defects as essential entities in the bulk of macromolecular crystals. In this report, we employ a phase sensitive x-ray diffraction imaging approach for augmenting the contrast of defects in protein crystals.

Hu, Z. W.↗
DOE OSTI2024

Three Photon Excited Image Scanning Microscopy for in-Depth Super-Resolution Studies of Biological Samples

Multiphoton laser scanning microscopy is a powerful tool for deep imaging of thick biological samples. Image scanning microscopy (ISM) has demonstrated significant improvements in the signal-to-noise ratio in confocal laser scanning microscopy, while at the same time improving upon the effectively attainable resolution. Two-photon excitation (2PE), combined with ISM, has been shown to allow for deep tissue imaging with enhanced resolution compared to 2PE microscopy. Three-photon excitation (3PE) has enabled record imaging depth and contrast for multiphoton imaging, due to the superior suppression of out-of-focus signal generation. In this paper, we demonstrate super-resolution 3PE ISM. This is achieved using a single-photon avalanche detector array, and 1040-nm pulses for 3PE of blue fluorescence. This method enables subdiffraction limited resolution imaging of biological samples stained with blue fluorescent markers, such as mouse myocardial and spinal cord tissues stained with 4 ′ , 6 -diamidino-2-phenylindole. Deconvolution improves the resolving power further and allows for imaging with better than λ / 8 resolution with respect to the 3PE wavelength λ . With the ISM pixel reassignment procedure, we demonstrate a resolution enhancement of ∼ 1.6 laterally, compared to the resolution attained using a photomultiplier tube in a non-descanned detection arrangement, and a factor of ∼ 1.8 enhancement in axial resolution. The experimentally measured three-dimensional point spread function volume is shrunk ∼ 4.4 -fold, which is close to the theoretically expected enhancement. Published by the American Physical Society 2024

47 OTHER INSTRUMENTATION↗