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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Development of high throughput and in vitro assays for analyzing RNA modifications

Modifications on RNAs play major roles in their stability, translation, and enzymatic activity. Despite its importance, the current techniques are insufficient to study the structure and function of RNA modifications. Indeed, the National Academies of Science, Engineering and Medicine indicate that developing new tools and further study the function of RNA modifications is strategically a high priority for advancing science in the coming years (https://www.nationalacademies.org/our-work/toward-sequencing-and-mapping-of-rna-modifications). RNA modifications occur in all domains of life controlling processes such as RNA turnover, translation regulation, cellular defenses and bioproduction. Our preliminary data indicated that the insulin mRNA might get ADP-ribosylated by the ADP-ribosyltransferase PARP12. RNA ADP-ribosylation has been described in Escherichia coli. Combined to the fact that ADP-ribosyltransferase (PARP) genes are conserved throughout evolution we hypothesize that this modification might play essential roles in cells. Therefore, we proposed to develop sequencing techniques and in vitro enzymatic assays to identify and validate ADP-ribosylation motifs and sites. Here we report the development of RNA-seq and qPCR assays to identify ADP-ribosylated RNAs, in addition to a nicotinamide adenosine dinucleotide (NAD – ADP-ribosylation donor) consumption assay and an enzyme-linked immunosorbent assay (ELISA) to measure ADP-ribosyltransferase activity. Testing these assays with the insulin mRNA confirmed that this transcript is ADP-ribosylated. These assays will not only enable studying the function of ADP-ribosylation but can be easily adapted for studying other RNA modifications. This will open opportunities to study RNA modifications in different model systems from bacteria to viruses to plants, bringing insights into their cellular functions and the possibility of targeting them for biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1991

High throughput narrowband 83.4 nm self-filtering camera

Photometric imaging of ionospheric/magnetospheric O II emission at 83.4 nm is a primary objective for mapping the distribution of O(+) ions. However, instrumental sensitivity has been a major barrier to realizing this goal. We report an instrumental design employing a low focal ratio three-mirror camera where the reflecting surfaces act as both narrowband reflection filters at 83.4 nm and as a high quality imaging system. The design includes coatings with reflectances that are relatively insensitive to the angle of incidence of light. The peak reflectance per mirror is more than 60 percent at 83.4 nm with the average reflectance for out-of-band wavelengths of less than 5 percent. The net reflective transmission for the three mirrors is greater than 20 percent with 6.8 nm bandwidth and 0.01 percent maximum transmittance for out-of-band wavelengths. The transmittance at 30.4 nm is 0.03 percent at 58.4 nm 0.05 percent, and at 121.6 nm 0.004 percent. When used with an open microchannel plate detector, contamination by H Ly-alpha is essentially eliminated. With this spectral purity and effective elimination of major contributors to background contamination noise, a signal-to-noise ratio (excluding detector noise) of 10 is achievable for a 0.01 R signal in 8.8 seconds for the full 6 deg field-of-view.

Zukic, Muamer↗
DOE OSTI2026

Scalable High-Throughput Open-Air Spray-Plasma Manufacturing of Solid-State Lithium Batteries

This final technical report presents a comprehensive analysis of a novel plasma-based in-line manufacturing process for large-area, LLZO-separator-based, solid-state lithium-ion batteries, demonstrating both technical feasibility and economic advantages over conventional vacuum deposition methods. The technical validation shows that spray-deposition with plasma curing achieves comparable electrode and separator quality to vacuum techniques while enabling continuous processing of components and industrially relevant film areas. Critical material interfaces maintain low porosity and high ionic conductivities, which confirm the process's ability to overcome the primary limitation of conventional methods - the trade-off between deposition quality and economically-viable production scale.

25 ENERGY STORAGE↗
NASA NTRS2011

High-Throughput Processes and Structural Characterization of Single-Nanotube Based Devices for 3D Electronics

We have developed manufacturable approaches to form single, vertically aligned carbon nanotubes, where the tubes are centered precisely, and placed within a few hundred nm of 1-1.5 micron deep trenches. These wafer-scale approaches were enabled by chemically amplified resists and inductively coupled Cryo-etchers to form the 3D nanoscale architectures. The tube growth was performed using dc plasmaenhanced chemical vapor deposition (PECVD), and the materials used for the pre-fabricated 3D architectures were chemically and structurally compatible with the high temperature (700 C) PECVD synthesis of our tubes, in an ammonia and acetylene ambient. The TEM analysis of our tubes revealed graphitic basal planes inclined to the central or fiber axis, with cone angles up to 30 deg. for the particular growth conditions used. In addition, bending tests performed using a custom nanoindentor, suggest that the tubes are well adhered to the Si substrate. Tube characteristics were also engineered to some extent, by adjusting growth parameters, such as Ni catalyst thickness, pressure and plasma power during growth.

top-down fabrication↗
NASA NTRS2001

A Compact X-Ray System for Support of High Throughput Crystallography

Standard x-ray systems for crystallography rely on massive generators coupled with optics that guide X-ray beams onto the crystal sample. Optics for single-crystal diffractometry include total reflection mirrors, polycapillary optics or graded multilayer monochromators. The benefit of using polycapillary optic is that it can collect x-rays over tile greatest solid angle, and thus most efficiently, utilize the greatest portion of X-rays emitted from the Source, The x-ray generator has to have a small anode spot, and thus its size and power requirements can be substantially reduced We present the design and results from the first high flux x-ray system for crystallography that combine's a microfocus X-ray generator (40microns FWHM Spot size at a power of 45 W) and a collimating, polycapillary optic. Diffraction data collected from small test crystals with cell dimensions up to 160A (lysozyme and thaumatin) are of high quality. For example, diffraction data collected from a lysozyme crystal at RT yielded R=5.0% for data extending to 1.70A. We compare these results with measurements taken from standard crystallographic systems. Our current microfocus X-ray diffraction system is attractive for supporting crystal growth research in the standard crystallography laboratory as well as in remote, automated crystal growth laboratory. Its small volume, light-weight, and low power requirements are sufficient to have it installed in unique environments, i.e.. on-board International Space Station.

Ciszak, Ewa↗
NASA NTRSDate not supplied

SPIKE-Dx : A Low-Power High-Throughput Fault Diagnostics Tool using Spiking Neural Networks for Constrained Systems

Diagnostic systems are important for many aerospace systems, which are severely limited in available power, like cubesats or UAVs. Therefore, traditional diagnostics systems cannot be used due to their substantial footprint and constraints. In this paper, we present our very low power diagnostic tool SPIKE-DX to monitor critical systems with constrained computational and energy resources. This is made possible through spiking neural networks (SNNs), which are executable within optimized simulation environments and further implemented on on cutting-edge neuromorphic hardware. Based upon FMEA (Failure Mode and Effect Analysis) framework, Diagnostic Bayesian Networks (DBNs) can be constructed that provide powerful means for diagnostic reasoning. In this paper, we describe such DBNs and a method to automatically translate the DBN into highly structured networks of spiking neurons for execution in SPIKE-DX.

Spiking Neural Networks↗
DOE OSTI2024

Hyperspectral Reflectance-Based High Throughput Phenotyping to Assess Water-Use Efficiency in Cotton

Cotton is a pivotal global commodity underscored by its economic value and widespread use. In the face of climate change, breeding resilient cultivars for variable environmental conditions becomes increasingly essential. However, the process of phenotyping, crucial to breeding programs, is often viewed as a bottleneck due to the inefficiency of traditional, low-throughput methods. To address this limitation, this study utilizes hyperspectral remote sensing, a promising tool for assessing crucial crop traits across forty cotton varieties. The results from this study demonstrated the effectiveness of four vegetation indices (VIs) in evaluating these varieties for water-use efficiency (WUE). The prediction accuracy for WUE through VIs such as the simple ratio water index (SRWI) and normalized difference water index (NDWI) was higher (up to R2 = 0.66), enabling better detection of phenotypic variations (p < 0.05) among the varieties compared to physiological-related traits (from R2 = 0.21 to R2 = 0.42), with high repeatability and a low RMSE. These VIs also showed high Pearson correlations with WUE (up to r = 0.81) and yield-related traits (up to r = 0.63). We also selected high-performing varieties based on the VIs, WUE, and fiber quality traits. This study demonstrated that the hyperspectral-based proximal sensing approach helps rapidly assess the in-season performance of varieties for imperative traits and aids in precise breeding decisions.

Agriculture↗
NASA NTRS2024

Demonstration of Portable X-ray Fluorescence Spectroscopy for High-Throughput In-Situ Quantification of Surface Lunar Dust for Testing and Future Surface Missions

In this paper, we present a new method of quantification for surface concentrations of lunar dust and lunar simulant for use and deployment for development testing and potential eventual use for verification and development testing and lunar surface missions. This technique demonstrates the use of portable X-ray fluorescence spectroscopy (pXRF) to quantify lunar dust loading on surfaces using an adaption of existing pXRF techniques. This paper shows the background in current methodologies for quantification of lunar dust in tests as well as current and potential future techniques for lunar surface missions, as well as current applications of commercial off-the-shelf (COTS) pXRF technology. The methodology for adapting current pXRF techniques is presented, followed by a demonstration of this new method on a variety of materials related to spaceflight or lunar surface missions. This technique shows high fidelity for immediate utilization as well as a demonstration of high potential for future surface missions.

Spectroscopy↗
DOE OSTI2026

Innovating High Throughput Hydrogen Stations: Cooperative Research and Development Final Report, CRADA Number CRD-18-00773

Hydrogen stations today serve the emerging market of light duty fuel cell vehicles, primarily in California with over 30 public retail locations. There has been a steady increase in the number of stations open and hydrogen dispensed, especially in the last two years. From 2015 to 2016, the annual amount of hydrogen dispensed increased from 27,400 kg to 109,200 kg, a nearly fourfold increase in just one year. One station dispensed nearly 12,000 kg in the second quarter of 2017. Despite the significant progress, gaps exist between current infrastructure capabilities and future requirements. For example, fuel cell vehicle applications such as buses, medium-duty, and heavy-duty trucks will gain market share and this must be considered as future customers at hydrogen stations. The expected number of light duty fuel cell vehicles in California alone are expected to grow from approximately 4,000 to over 13,000 by 2020, and 37,000 by 2023. To serve the multiple mobile fuel cell technologies and increased demand, hydrogen stations will have to increase output, decrease cost, and improve reliability. To address these challenges, the project team will demonstrate a hydrogen-focused integrated renewable energy production, storage, and transportation fuel distribution/retailing system. The proposed R&D tasks address key challenges related to light duty station/component reliability and development and validation of high flow rate system models for new applications like medium and heavy-duty truck fueling.

08 HYDROGEN↗
DOE OSTI2026

PlantCV v4: Image analysis software for high‐throughput plant phenotyping

PlantCV is an open-source Python project aimed at developing tools to address a range of image-based, plant phenotyping questions. PlantCV has been used for more than 10 years to automate trait collection from image data, and the newest release, PlantCV version 4, continues to lower the barrier to entry for users without substantial coding experience through extensive example use-case tutorials and simplified installation. In addition to usability, we document added functionality since the release of PlantCV v2, including support for more image types such as fluorescence, thermal, and hyperspectral data. Finally, we describe the development of a new subpackage focused on morphological trait measurements like leaf angle, and demonstrate its utility as compared to more manual methods of data collection.

Schuhl, Haley [Donald Danforth Plant Science Cente↗