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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Ribbon Synaptic Plasticity in Gravity Sensors of Rats Flown on Neurolab

Previous spaceflight experiments (Space Life Sciences-1 and -2 (SLS-1 and SLS-2)) first demonstrated the extraordinary ability of gravity sensor hair cells to change the number, kind, and distribution of connections (synapses) they make to other cells while in weightlessness. The number of synapses in hair cells in one part of the inner ear (the utricle) was markedly elevated on flight day 13 (FD13) of SLS-2. Unanswered questions, however, were whether these increases in synapses occur rapidly and whether they remain stable in weightlessness. The answers have implications for long-duration human space travel. If gravity sensors can adapt quickly, crews may be able to move easily between different gravity levels, since the sensors will adapt rapidly to weightlessness on the spacecraft and then back to Earth's gravity when the mission ends. This ability to adapt is also important for recovery from balance disorders. To further our understanding of this adaptive potential (a property called neuronal synaptic plasticity), the present Neurolab research was undertaken. Our experiment examined whether: (a) increases in synapses would remain stable throughout the flight, (b) changes in the number of synapses were uniform across different portions of the gravity sensors (the utricle and saccule), and (c) synaptic changes were similar for the different types of hair cells (Type I and Type II). Utricular and saccular maculae (the gravity-sensing portions of the inner ear) were collected in flight from rats on FD2 and FD14. Samples were also collected from control rats on the ground. Tissues were prepared for ultrastructural study. Hair cells and their ribbon synapses were examined in a transmission electron microscope. Synapses were counted in all hair cells in 50 consecutive sections that crossed the striolar zone. Results indicate that utricular hair cell synapses initially increased significantly in number in both types of hair cells by FD2. Counts declined by FD14, but the mean number of synapses in utricular Type II cells remained significantly higher than in the ground control rats. For saccular samples, synaptic number in Type I and Type II cells declined on FD2, but returned to near-baseline values by FD14. These findings indicate that: (a) synaptic plasticity occurs rapidly in weightlessness, and (b) synaptic changes are not identical for the two types of hair cells or for the two maculae.

Ross, Muriel D.↗
NASA NTRSDate not supplied

Risk-Based Methodology for the Determination of Hall Thruster Performance Specifications

This work adapts manufacturing and metrology industry standards to create a risk-based approach for the determination of electric propulsion performance specifications. The developed process is applied to 208 total thrust measurements acquired using three different NASA Hall Effect Rocket with Magnet Shielding (HERMeS) Technology Demonstration Unit (TDU) 12.5-kW Hall thrusters in three different test facilities in order to generate thrust specifications at the 300 V/6.25 kW, 400 V/8.33 kW, 500 V/10.42 kW, and 600 V/12.5 kW operating conditions. These thrust specifications are used to perform a set of sample acceptance tests to illustrate the importance of adding additional conservatism using a parameter known of the Test Accuracy Ratio in order to control the risk to the thruster producer and consumer from false rejection and acceptance of thruster units.

HERMeS↗
NASA NTRSDate not supplied

Risk-based Methodology for the Determination of Hall Thruster Performance Specifications

This work adapts manufacturing and metrology industry standards to create a risk-based approach for the determination of electric propulsion performance specifications. The developed process is applied to 208 total thrust measurements acquired using three different NASA Hall Effect Rocket with Magnet Shielding (HERMeS) Technology Demonstration Unit (TDU) 12.5-kW Hall thrusters in three different test facilities in order to generate thrust specifications at the 300 V/6.25 kW, 400 V/8.33 kW, 500 V/10.42 kW, and 600 V/12.5 kW operating conditions. These thrust specifications are used to perform a set of sample acceptance tests to illustrate the importance of adding additional conservatism using a parameter known of the Test Accuracy Ratio in order to control the risk to the thruster producer and consumer from false rejection and acceptance of thruster units.

HERMeS↗
NASA NTRS2017

Online Multi-Modal Learning and Adaptive Information Trajectory Planning for Autonomous Exploration

In robotic information gathering missions, scientists are typically interested in understanding variables which require proxy measurements from specialized sensor suites to estimate. However, energy and time constraints limit how often these sensors can be used in a mission. Robots are also equipped with cheaper to use navigation sensors such as cameras. In this paper, we explore a challenging planning problem in which a robot is required to learn about a scientific variable of interest in an initially unknown environment by planning informative paths and deciding when and where to use its sensors. To tackle this we present two innovations: a Bayesian generative model framework to automatically learn correlations between expensive science sensors and cheaper to use navigation sensors online, and a sampling based approach to plan for multiple sensors while handling long horizons and budget constraints. Our approach does not grow in complexity with data and is anytime making it highly applicable to field robotics. We tested our approach extensively in simulation and validated it with real data collected during the 2014 Mojave Volatiles Prospector Mission. Our planning algorithm performs statistically significantly better than myopic approaches and at least as well as a coverage-based algorithm in an initially unknown environment while having added advantages of being able to exploit prior knowledge and handle other intricacies of the real world without further algorithmic modifications.

learning↗
DOE OSTI2025

Fabrication of porous transport electrodes: Development of quantitative approach for quality control

This work focuses on porous transport electrodes (PTEs), which integrate the anodic catalyst with the adjacent Ti porous transport layer (PTL). Challenges in catalyst deposition on PTLs, particularly at low loadings, motivated this study to evaluate various fabrication methods and characterization approaches. This work investigated Pt-treated PTLs coated with Ir-based catalysts using several common methods, including airbrush coating, rod coating, ultrasonic spray coating, electrodeposition, and sputter deposition, with catalyst loadings ranging from 2.9 to 0.1 mg/cm 2 , providing the opportunity for comparisons across a large set of samples produced by different methods. Two widely accessible characterization techniques: X-ray computed tomography (XCT) and scanning electron microscopy energy dispersive X-ray spectroscopy (SEM-EDS) were explored. Initial evaluation of selected samples with XCT provided qualitative insights into catalyst distribution, however comprehensive quantitative analysis was limited. SEM-EDS enabled detailed information on the catalyst distribution both qualitatively and quantitatively using two metrics. Atomic and surface area % ratios of Pt:Ir and Ti:Ir revealed trends in catalyst loading and losses into the PTL pores, as well as evaluating the homogeneity of catalyst coatings. The analysis demonstrated that ultrasonic spray coating, electrodeposition, and sputter coating produced the most homogeneous coatings, with minimal catalyst losses observed for electrodeposition and sputter coating. By adapting common techniques with novel, standardized methodologies, this work establishes a universally applicable framework for cross-study comparison of PTEs. The SEM-EDS approach provides a practical, accessible tool for PTE characterization and contributes a reference dataset supporting both research development and rapid quality control.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A rapid thioacidolysis method for biomass lignin composition and tricin analysis

Abstract Background Biomass composition varies from plant to plant and greatly affects biomass utilization. Lignin is a heterogeneous phenolic polymer derived mainly from p -coumaryl, coniferyl, and sinapyl alcohols and makes up to 10–25% of lignocellulosic biomass. Recently, tricin, an O -methylated flavone, was identified as a lignin monomer in many grass species. Tricin may function as a nucleation site for lignification and is advocated as a novel target for lignin engineering to reduce lignin content and improve biomass digestibility in grasses. Thioacidolysis is an analytical method that can be adapted to analyze both lignin monomeric composition and tricin content in the lignin polymer. However, the original thioacidolysis procedure is complex, laborious, and time consuming, making it difficult to be adopted for large-scale screening in biomass research. In this study, a modified, rapid higher throughput thioacidolysis method was developed. Results In combination with gas chromatography–mass spectrometry (GC–MS) and liquid chromatography–mass spectrometry (LC–MS), the modified thioacidolysis method can be used to simultaneously characterize the lignin composition and tricin content using 2–5 mg of dry samples. The modified method eliminates the solvent extraction and drastically improves the throughput; 80 samples can be processed in one day per person. Our results indicate that there is no significant difference in the determination of lignin S/G ratio and tricin content between the original and modified methods. Conclusions A modified thioacidolysis protocol was established. The results demonstrate that the modified method can be used for rapid, high-throughput, and reliable lignin composition and tricin content analyses for screening transgenic plants for cell wall modifications or in large-scale genome-wide association studies (GWAS).

09 BIOMASS FUELS↗
DOE OSTI2022

Global patterns of diversity and metabolism of microbial communities in deep-sea hydrothermal vent deposits

When deep-sea hydrothermal fluids mix with cold oxygenated fluids, minerals precipitate out of solution and form hydrothermal deposits. These actively venting deep-sea hydrothermal deposits support a rich diversity of thermophilic microorganisms which are involved in a range of carbon, sulfur, nitrogen, and hydrogen metabolisms. Global patterns of thermophilic microbial diversity in deep-sea hydrothermal ecosystems have illustrated the strong connectivity between geological processes and microbial colonization, but little is known about the genomic diversity and physiological potential of these novel taxa. Here we explore this genomic diversity in 42 metagenomes from four deep-sea hydrothermal vent fields and a deep-sea volcano collected from 2004 to 2018 and document their potential implications in biogeochemical cycles. Our dataset represents 3635 metagenome-assembled genomes encompassing 511 novel and recently identified genera from deep-sea hydrothermal settings. Some of the novel bacterial (107) and archaeal genera (30) that were recently reported from the deep-sea Brothers volcano were also detected at the deep-sea hydrothermal vent fields, while 99 bacterial and 54 archaeal genera were endemic to the deep-sea Brothers volcano deposits. We report some of the first examples of medium- (≥ 50% complete, ≤ 10% contaminated) to high-quality (> 90% complete, < 5% contaminated) MAGs from phyla and families never previously identified, or poorly sampled, from deep-sea hydrothermal environments. We greatly expand the novel diversity of Thermoproteia, Patescibacteria (Candidate Phyla Radiation, CPR), and Chloroflexota found at deep-sea hydrothermal vents and identify a small sampling of two potentially novel phyla, designated JALSQH01 and JALWCF01. Metabolic pathway analysis of metagenomes provides insights into the prevalent carbon, nitrogen, sulfur, and hydrogen metabolic processes across all sites and illustrates sulfur and nitrogen metabolic “handoffs” in community interactions. We confirm that Campylobacteria and Gammaproteobacteria occupy similar ecological guilds but their prevalence in a particular site is driven by shifts in the geochemical environment. Our study of globally distributed hydrothermal vent deposits provides a significant expansion of microbial genomic diversity associated with hydrothermal vent deposits and highlights the metabolic adaptation of taxonomic guilds. Collectively, our results illustrate the importance of comparative biodiversity studies in establishing patterns of shared phylogenetic diversity and physiological ecology, while providing many targets for enrichment and cultivation of novel and endemic taxa.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Ambient Ion Trapping and Separations for High Throughput Structurally Selective Material Deposition

While ion mobility coupled to mass spectrometry (IMS/MS) has been increasingly adapted to biological analysis, the structural and molecular specificity offered by IMS/MS has untapped potential for creating novel materials (for energy, catalysis, biomolecular switches etc.) with rationally tailored properties by precisely controlling the chemical structure and composition of these materials. While electrochemical and catalytic properties of the bulk material are understood by mass-selective ion-soft-landing, different structures of one molecule can exhibit distinct properties from the bulk. Many biological phenomenon occur at interfaces and are highly structurally specific. IMS/MS offers means to separate molecules in a sample (which is first ionized and released to gas phase from the condensed phase) based on mass and structure. Species thus separated can potentially be deposited onto surfaces with molecular and structural specificity, to perform fundamental investigations for understanding critical interfacial phenomenon. Key performance metrics for IMS/MS analysis are resolution of separations and sensitivity. Recently developed Structures for Lossless Ion Manipulations (SLIM)4 enabled unprecedented resolution in IMS separations. In addition, high sensitivity was enabled in SLIM due to lossless confinement of ions using radio frequency fields. Thus, SLIM enabled extremely long path length separations (up to 0.1 km thus far) providing efficient separation of molecular ions never before achieved (e.g. isotopologues, D&L amino acids). While SLIM has unprecedented analytical separations power/utility, the use of SLIM platform for depositing mobility and mass selected molecular ions has two specific technological challenges: (a) Pulsed nature of IMS separations and their low duty cycle and (b) the need for a low vacuum of ~4 torr for lossless ion confinement. These limitations lead to long deposition times due to loss of ions generated from the sample. Enabling ion confinement at atmospheric pressure will be path-breaking contribution to the fundamental understanding of ion manipulations and separations and will also enable novel science currently precluded due to the inability of the present technologies to confine ions under ambient conditions. Traditionally used radio frequency fields are ineffective in confining ions at high pressures due to ion/neutral collisions. To address these, we propose to (a) develop methods for confining and manipulating ions for lossless IMS separations at atmospheric pressure enabling high sensitivity and throughput and (b) use the high specificity of IMS/MS and high throughput from ambient ion confinement to perform mobility and mass selective ion deposition at atmospheric pressure. Our goal is to enable the study of the fundamental properties of energy/catalysis materials and biomolecules. This project paves the way for high-throughput, mass and structure selective material deposition for highly specific surface creation/functionalization (discussed in Section 2 of the report). Further, the developments reported continue to push the boundaries of this process to ambient conditions (discussed in Section 3 of the report). We conclude with a list of specific intellectual property and publications which have been the outcome of this funded project.

36 MATERIALS SCIENCE↗
DOE OSTI2025

GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning

Large language models (LLMs) are increasingly adapted to downstream tasks via reinforcement learning (RL) methods like Group Relative Policy Optimization (GRPO), which often require thousands of rollouts to learn new tasks. We argue that the interpretable nature of language often provides a much richer learning medium for LLMs, compared to policy gradients derived from sparse, scalar rewards. To test this, we introduce GEPA (Genetic-Pareto), a prompt optimizer that thoroughly incorporates natural language reflection to learn high-level rules from trial and error. Given any AI system containing one or more LLM prompts, GEPA samples trajectories (e.g., reasoning, tool calls, and tool outputs) and reflects on them in natural language to diagnose problems, propose and test prompt updates, and combine complementary lessons from the Pareto frontier of its own attempts. As a result of GEPA's design, it can often turn even just a few rollouts into a large quality gain. Across six tasks, GEPA outperforms GRPO by 6% on average and by up to 20%, while using up to 35x fewer rollouts. GEPA also outperforms the leading prompt optimizer, MIPROv2, by over 10% (e.g., +12% accuracy on AIME-2025), and demonstrates promising results as an inference-time search strategy for code optimization. We release our code at https://github.com/gepa-ai/gepa.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2010

Radiation Exposure Alters Expression of Metabolic Enzyme Genes In Mice

Most pharmaceuticals are metabolized by the liver. The health of the liver, especially the rate of its metabolic enzymes, determines the concentration of circulating drugs as well as the duration of their efficacy. Because of the importance of the liver in drug metabolism it is important to understand the effects of spaceflight on the enzymes of the liver. Exposure to cosmic radiation is one aspect of spaceflight that can be modeled in ground experiments. This study is an effort to examine the effects of adaptive mechanisms that may be triggered by early exposure to low radiation doses. Using procedures approved by the JSC Animal Care & Use Committee, C57 male mice were exposed to Cs-137 in groups: controls, low dose (50 mGy), high dose (6Gy) and a fourth group that received both radiation doses separated by 24 hours. Animals were anesthetized and sacrificed 4 hours after their last radiation exposure. Livers were removed immediately and flash-frozen in liquid nitrogen. Tissue was homogenized, RNA extracted and purified (Absolutely RNA, Agilent). Quality of RNA samples was evaluated (Agilent Bioanalyzer 2100). Complementary DNA was prepared from high-quality RNA samples, and used to run RT-qPCR screening arrays for DNA Repair and Drug Metabolism (SuperArray, SABiosciences/Qiagen; BioRad Cfx96 qPCR System). Of 91 drug metabolism genes examined, expression of 7 was altered by at least one treatment condition. Genes that had elevated expression include those that metabolize promethazine and steroids (4-8-fold), many that reduce oxidation products, and one that reduces heavy metal exposure (greater than 200-fold). Of the 91 DNA repair and general metabolism genes examined, expression of 14 was altered by at least one treatment condition. These gene expression changes are likely homeostatic and could lead to development of new radioprotective countermeasures.

Wotring, Virginia E.↗
DOE OSTI2026

NanoPSD: A software for automatic detection of Nano-Particle Shape Distribution in electron microscopy images

Accurate quantification of the size and morphology of nanoparticles from electron microscopy (EM) images is essential to understand growth mechanisms, surface reactivity, and functional behavior in nanoscale materials. Manual analysis remains slow, subjective, and difficult to reproduce in large datasets. We introduce NanoPSD (Nano-Particle Shape Distribution), an open-source and fully automated framework for quantitative particle detection and morphology analysis from EM images. NanoPSD integrates adaptive contrast enhancement, polarity-agnostic scale-bar detection, Optical Character Recognition (OCR)-based calibration, and classical segmentation via Otsu thresholding with morphological refinement. Particle contours are used to extract geometric descriptors, including equivalent circular diameter, aspect ratio, circularity, and solidity, enabling automated classification into spherical, rod-like, and aggregate morphologies. The framework supports both single-image and batch processing, generating publication-quality visualizations, LaTeX-ready tables, and structured comma-separated values (CSV) datasets. As a demonstration, we applied NanoPSD to plasma-synthesized nanoparticle samples diagnosed via transmission electron microscopy (TEM). The code produced statistically robust size and morphology distributions spanning a few to tens of nanometers with minimal user supervision. The pipeline demonstrates high reproducibility and scalability, processing large image collections with consistent calibration and output formatting. Its modular design enables seamless integration of future deep-learning-based segmentation models, providing a pathway toward intelligent, data-driven electron microscopy analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Engineered bone marrow as a clinically relevant ex vivo model for primary bone cancer research and drug screening

Osteosarcoma (OS) is the most common primary malignant bone cancer in children and adolescents. While numerous other cancers now have promising therapeutic advances, treatment options for OS have remained unchanged since the advent of standard chemotherapeutics and offer less than a 25% 5-y survival rate for those with metastatic disease. This dearth of clinical progress underscores a lack of understanding of OS progression and necessitates the study of this disease in an innovative system. Here, we adapt a previously described engineered bone marrow (eBM) construct for use as a three-dimensional platform to study how microenvironmental and immune factors affect OS tumor progression. We form eBM by implanting acellular bone-forming materials in mice and explanting the cellularized constructs after 8 wk for study. We interrogate the influence of the anatomical implantation site on eBM tissue quality, test ex vivo stability under normoxic (5% O 2 ) and standard (21% O 2 ) culture conditions, culture OS cells within these constructs, and compare them to human OS samples. We show that eBM stably recapitulates the composition of native bone marrow. OS cells exhibit differential behavior dependent on metastatic potential when cultured in eBM, thus mimicking in vivo conditions. Furthermore, we highlight the clinical applicability of eBM as a drug-screening platform through doxorubicin treatment and show that eBM confers a protective effect on OS cells that parallel clinical responses. Combined, this work presents eBM as a cellular construct that mimics the complex bone marrow environment that is useful for mechanistic bone cancer research and drug screening.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Development of Automated Atom Probe Tomography capability to study the influence of applied voltage and laser power on the final apparent composition of the analyzed specimen

This study presents the development and implementation of an autonomous Bayesian optimization (BO) framework for controlling and optimizing experimental parameters in Atom Probe Tomography (APT). Using commercial silicon needle samples as a benchmark system, we demonstrate that BO can efficiently navigate the complex parameter space of voltage and laser power to achieve target charge state ratios (specifically Si + /(Si + +Si 2+ )) with minimal experimental evaluations. Our implementation integrates Gaussian Process modeling with the CAMECA atom probe control framework, enabling autonomous adjustment of experimental conditions in real-time. Results show that the algorithm successfully converges to target ratios under different scenarios: maintaining a reference ratio, increasing the ratio (favoring Si 1+ ), and decreasing the ratio (favoring Si 2+ ). The system adapts to specimen evolution during analysis, compensating for changes in apex geometry while maintaining optimization targets. This work establishes a proof of concept for AI-driven optimization in APT, addressing the traditional challenges of manual parameter tuning and paving the way for applications to more complex materials where compositional accuracy is critical.

36 MATERIALS SCIENCE↗
NASA NTRS1972

Seventeen Ketogenic steroids excretion in crewmen in a 90-day manned test of an advanced regenerative life support system

Seventeen KGS (17-Ketogenic steroids) and Na/K were determined in 19 urine specimens collected by each of 4 crewmen during the 90-day test. The specimens represented 10% aliquots of 24-hour collections stored frozen onboard the simulator until passthrough. Electrolytes were analyzed immediately after sample passthrough while the steroids were determined post-test on aliquots of the original sample held at 203 K. Steroid data was corrected for body weight and also for analytical variation in the laboratory urine pool control. Long-term nonspecific responses to low-level stress appear to be reflected by the individual and group mean 17-KGS excretion patterns. The first 39 and the last 20 days of the test were significantly different--and presumably more stressful to the crew--than the period from days 39 to 67. Reduction of adrenocortical function during the mid-test phase is attributed to either an adaptation to chronic or intermittent stress or was the result of an actual reduction in the operational demands of the test during this time. Most remarkable of the metabolic findings is the prevalance of high Na/K ratios and an abrupt peak on day 74 for all 4 crewmen.

Myers, D. J.↗
NASA NTRS2009

Developing Dual Polarization Applications For 45th Weather Squadron's (45 WS) New Weather Radar: A Cooperative Project With The National Space Science and Technology Center (NSSTC)

A new weather radar is being acquired for use in support of America s space program at Cape Canaveral Air Force Station, NASA Kennedy Space Center, and Patrick AFB on the east coast of central Florida. This new radar includes dual polarization capability, which has not been available to 45 WS previously. The 45 WS has teamed with NSSTC with funding from NASA Marshall Spaceflight Flight Center to improve their use of this new dual polarization capability when it is implemented operationally. The project goals include developing a temperature profile adaptive scan strategy, developing training materials, and developing forecast techniques and tools using dual polarization products. The temperature profile adaptive scan strategy will provide the scan angles that provide the optimal compromise between volume scan rate, vertical resolution, phenomena detection, data quality, and reduced cone-of-silence for the 45 WS mission. The mission requirements include outstanding detection of low level boundaries for thunderstorm prediction, excellent vertical resolution in the atmosphere electrification layer between 0 C and -20 C for lightning forecasting and Lightning Launch Commit Criteria evaluation, good detection of anvil clouds for Lightning Launch Commit Criteria evaluation, reduced cone-of-silence, fast volume scans, and many samples per pulse for good data quality. The training materials will emphasize the appropriate applications most important to the 45 WS mission. These include forecasting the onset and cessation of lightning, forecasting convective winds, and hopefully the inference of electrical fields in clouds. The training materials will focus on annotated radar imagery based on products available to the 45 WS. Other examples will include time sequenced radar products without annotation to simulate radar operations. This will reinforce the forecast concepts and also allow testing of the forecasters. The new dual polarization techniques and tools will focus on the appropriate applications for the 45 WS mission. These include forecasting the onset of lightning, the cessation of lightning, convective winds, and hopefully the inference of electrical fields in clouds. This presentation will report on the results achieved so far in the project.

Roeder, W.P.↗
NASA NTRS2016

Trajectories for Flyby Sample Return at Saturn's Moons

Ballistic trajectories are computed which would enable a sample return mission to Titan or Enceladus without capturing, descending, or landing. The low-cost mission concept utilizes a free return trajectory that also involves a close flyby of the moon. This work extends the concept, and related trajectory analysis methodology, previously applied to a Europa mission. Specifically, a broad search algorithm is employed to systematically locate potentially feasible itineraries over an entire Saturn period. High-quality approximate solutions are then optimized to be continuous using high-fidelity dynamics. Techniques and software from the Europa analysis, were readily adapted and able to find numerous mission enabling trajectories. A direct mission to Titan is possible with flight time under 16 years and Earth-relative speeds below 11.0 km/sec. The VEEGA option is shown to substantially reduce launch C3, but flight times exceed 21 years. Unfortunately, an Enceladus mission requires a flight time of 25 years or more, and incurs fairly high relative speeds. Nevertheless, an optimized reference mission is computed.

Jones, Drew Ryan↗
NASA NTRS2019

A Laser Heterodyne Radiometer for Sampling Plumes of Icy Moons

We propose to develop an instrument capable of passively sampling plumes in icy moon environments for the components needed for life and habitability. The compact, low-mass and power, orbital instrument would be an occultation-viewing laser heterodyne radiometer (LHR) that collects sunlight passing through the plumes of icy moons to measure abundancies of key trace gases such as water vapor, methane, ethane, carbon dioxide, and their isotopes. Laser heterodyne radiometers are based on radio receiver technology and have been applied to measurements of trace gases in Earth and planetary atmospheres since the 1960s. Our team has recently adapted this technology into a 4U (20cm x 20cm x 10cm) CubeSat instrument to measure carbon dioxide, methane and water vapor in the Earth's atmosphere (launching on Virgin Orbit in 2019) and have the experience to develop this into a compact science payload to monitor gases emerging from icy moons of Saturn and Jupiter.

laser heterodyne radiometer (LHR)↗
NASA NTRSDate not supplied

Machine-Learning-Based Adaptive Thinning of CrIS Radiances to Improve Global Tropical Cyclone Analysis and Forecasts

This work is focused on optimizing the assimilation of hyperspectral infrared (IR) radiances from the Cross-track Infrared Sounder (CrIS) with the goal of improving the representation of tropical cyclones (TCs) in global analyses and forecasts. Current operational assimilation systems rely on subsampling IR radiances on a regular thinning grid. A new and improved adaptive methodology based on machine learning (ML) recognizes TCs from geostationary satellite imagery and is implemented in the Goddard Earth Observing System (GEOS) model and data assimilation framework. The ML methodology is extensively trained on existing TC data sets and creates for each TC a dynamic mask, based on the evolving shape and life cycle of that specific event. Once a TC mask is created, a switch is then activated in the data assimilation system to alter the thinning, ingesting more CrIS radiances within the moving mask, thus increasing the TC sampling. After the TC dissipates, the assimilation of CrIS radiances reverts to normal data density. Results of TC segmentation provided by a state-of-the-art generative machine learning model known as the Denoising Diffusion Probabilistic Model (DDPM) are compared to the previously used U-Net model. The new approach surpasses the performance of the previously developed one. The methodology is applied to both clear-sky and cloud-cleared radiances. Benefits from the latter methodology, particularly in improving the structure of TCs and the intensity forecasts, are presented.

Oreste Reale↗