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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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NASA NTRSDate not supplied

Enhancing accessibility and usability of Algorithm Theoretical Basis Documents through the Algorithm Publication Tool

Effective communication of scientific theories is crucial for transforming raw instrument data into valuable Earth observation products. The NASA Earth science data community disseminates this knowledge through Algorithm Theoretical Basis Documents (ATBDs). Historically, these documents lacked a standardized format, were designed for human readability rather than machine interpretation, and were challenging to locate due to the absence of a centralized repository. The Algorithm Publication Tool (APT) transforms how ATBD content is presented, simplifying the processes of creating, updating, and locating these documents. APT offers authors the option to use its user-friendly cloud-based interface or standardized templates for ATBD development. The primary advantage of the interface is its capability to manage the entire ATBD creation process within a single environment, ensuring comprehensive tracking of all activities and facilitating user tasks. Conversely, the use of standardized ATBD templates allows users to create documents using familiar tools like Google Docs, Microsoft Word, or Overleaf for LaTeX. APT also provides a centralized repository, enabling easy search and discovery of published ATBDs. This presentation showcases APT's functionalities, illustrates its contributions to advancing open science, and highlights potential benefits for broader community adoption.

Bradley Baker↗
NASA NTRS1993

Discovery Venera surface: Atmosphere geochemistry experiments mission concept

The phenomenal increase in our understanding of Venus provided by the Magellan Mission has raised a series of focused, fundamental scientific questions about the geochemistry of the surface of Venus, the nature of the lower atmosphere, and the relationship of the lower atmosphere and surface. First, surface geochemical measurements from the Venera/Vega spacecraft showed that widely spaced regions of the venusian plains are made of basalts; thus basalts are significant and may be the only component of the venusian crust. But we lack information on the composition of several key elements of Venus geology: (1) Tessera terrain (which may be outcrops of continental-like non-basaltic crustal material) and steep-sided domes/festoons are promising candidates for non-basaltic geochemically evolved material. The composition of the lower part of the Venusian crust is unknown: however, ejecta from large venusian craters provides us with the possibility of sampling this material on the surface; (2) bulk chemistry (structure and dynamics) of the venusian atmosphere are known. The altitude profiles of water vapor content and minor admixtures relevant to redox conditions in the lower atmosphere (less than 20 km altitude) remain uncertain. Lack of that knowledge means that we do not understand the fine chemical structure of the main mass of the Venusian atmosphere; and (3) thermodynamic models predict that igneous materials on the surface of Venus should react with gases of the venusian atmosphere. But because the water vapor content and redox conditions in the lower atmosphere are not well known, we do not understand the nature of venusian weathering: oxidation, sulfatization, carbonatization, and hydration. The answers to these questions are critical to the understanding of Venus, the most Earth-like of the terrestrial planets.

Surkov, Yuri A.↗
DOE OSTI2025

Flow instabilities in helical-coil steam generators for small modular reactors: A review

Here, this study covers the research and discoveries in two-phase flow-boiling instabilities available in the literature—specifically for a helical-coil steam generator (HCSG), including experimental findings, theoretical research, computational models, and system code analyses—supporting research and development of representative small modular reactors (SMRs). Like other new and advanced reactor systems, water-cooled SMRs require experimental data from both integral and separate thermal-hydraulics test facilities for the verification and validation (V&V) of the computational models and computer codes in order to design and obtain regulatory approval. The complex dynamics of two-phase flow-boiling instabilities includes flow regimes physics phenomena, flow-channel geometries, heat-transfer behavior, and interactions among the solid–liquid-gas within the system boundary, all of which are pivotal for understanding the design and operational challenges of SMRs. This study focuses on identifying the relevant knowledge gaps on boiling instabilities—specifically for a HCSG—and provides insights about future research direction optimizing the transport of thermal energy, mass-flow rates, and boundary conditions that ensure the adequate heat-transfer performance, operational stability, and safety associated with SMR systems.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2026

Towards a self-driving trigger at the LHC: adaptive response in real time

Real-time data filtering and selection—or trigger—systems at high-throughput scientific facilities such as the experiments at the Large Hadron Collider must process extremely high-rate data streams under stringent bandwidth, latency, and storage constraints. Yet these systems are typically designed as static, hand-tuned menus of selection criteria grounded in prior knowledge and simulation. In this work, we further explore the concept of a self-driving trigger, an autonomous data-filtering framework that reallocates resources and adjusts thresholds dynamically in real-time to optimize signal efficiency, rate stability, and computational cost as instrumentation and environmental conditions evolve. We introduce a benchmark ecosystem to emulate realistic collider scenarios and demonstrate real-time optimization of a menu including canonical energy sum triggers as well as modern anomaly-detection algorithms that target non-standard event topologies using machine learning. Using simulated data streams and publicly available collision data from the Compact Muon Solenoid experiment, we demonstrate the capability to dynamically and automatically optimize trigger performance under specific cost objectives without manual retuning. Our adaptive strategy shifts trigger design from static menus with heuristic tuning to intelligent, automated, data-driven control, unlocking greater flexibility and discovery potential in future high-energy physics analyses.

Emami, Shaghayegh [Michigan U.] (ORCID:00090007589↗
DOE OSTI2024

Durable and High-Performance SOECs Based on Proton Conductors for Hydrogen Production

Proton-conducting solid oxide electrolysis cells (P-SOECs) are a promising technology for cost-effective and efficient production of green hydrogen. Breakthroughs in materials development, optimization of cell structure, and achievement of high performance and durability are essential to significantly increase the commercial competitiveness of these technologies. The main objective of this project is to gain scientific knowledge for the rational design, fabrication, and demonstration of a robust, highly efficient, and low-cost SOEC technology based on a proton-conducting electrolyte membrane for hydrogen production. We focused on better understanding the degradation mechanisms of proton-conducting electrolytes, air electrodes, and catalyst materials under electrolysis mode to develop an effective strategy for rationalizing new materials that are vital for enhancing cell performance and durability. The scope includes enhancing the performance and durability of the electrolyte and electrode materials under realistic operating conditions, developing highly active and robust catalysts to minimize electrode losses while improving tolerance to contaminant poisoning, revealing the mechanism of enhanced activity and stability of the catalyst, and understanding the underlying degradation mechanisms. In addition, various characterization techniques were employed to gain a fundamental understanding of the materials’ behavior and their impact on cell performance, providing vital information to guide materials discovery and cell design. After defect chemistry engineering, the optimized donor and acceptor co-doped electrolytes BaMo/W 0.03 Ce 0.71 Yb 0.26 O 3-δ (BM/W03) showed substantially improved chemical stability against high concentrations of CO 2 and H 2 O compared to the state-of-the-art electrolyte (BaZr 0.1 Ce 0.7 Y 0.1 Yb 0.1 O 3-δ , BZCYYb1711) while maintaining comparable ionic conductivity and ionic transference number. To bypass the inherent trade-off between conductivity and chemical stability, we fabricated a bi-layer electrolyte composed of BZCYYb1711 coated with a highly-stable thin layer of BaHf 0.83 Yb 0.17 O 3-δ (BHYb). This bi-layer electrolyte displayed excellent chemical stability against high concentration CO 2 ; there was no detectable formation of BaCO 3 after exposure to 97% CO 2 (with 3% H 2 O) at 500 °C for 1000 hours and the rate of degradation in resistance was about 0.4% per 1,000 hours (kh). In contrast, the same BZCYYb1711 electrolyte without a BHYb coating degraded significantly under the same testing conditions; the degradation rate was increased to 5.1%/kh. In addition, a triple conducting air electrode Ba 0.9 Pr 0.1 Hf 0.1 Y0.1Co 0.8 O 3-δ (BPHYC) was developed by heavily doping transition metal ions into a proton-conducting material. This air electrode material, composed of 3 distinct phases, exhibits superior electrocatalytic activity due to the synergistic effect from the three component phases. Moreover, an active and durable catalyst, La 2 Ni 0.5 Fe 0.5 O 4+δ (LNF), was developed, showing excellent catalytic activity and contaminant tolerance, with a degradation rate of only 0.49%/kh when exposed to high concentrations of steam and Cr. Finally, single cells were constructed from the best electrolytes, electrodes, and catalyst coatings developed in this project. These cells demonstrated superior high current density at a given cell voltage, high roundtrip efficiency, and remarkable durability (up to 1000 hours of operation).

08 HYDROGEN↗
NASA NTRS2011

Fermi/GBM Results of Magnetars

Magnetars are magnetically powered rotating neutron stars with extreme magnetic fields (over 10(exp 14) Gauss). They were discovered in the X- and gamma-rays where they predominantly emit their radiation. Very few sources (roughly 18) have been found since their discovery in 1987. NASA's Fermi Gamma-ray Space Telescope was launched June 11,2009; since then the Fermi Gamma-ray Burst Monitor (GBM) recorded emission from four magnetar sources. Two of these were brand new sources, SGR J0501 +4516, discovered with Swift and extensively monitored with Swift and GBM, SGR J0418+5729, discovered with GBM and the Interplanetary Network (IPN). A third was SGR Jl550-5418, a source originally classified as an Anomalous X-ray Pulsar (AXP IEI547.0-5408), but exhibiting a very prolific outburst with over 400 events recorded in January 2009. In my talk I will give a short history of magnetars and describe how this, once relatively esoteric field, has emerged as a link between several astrophysical areas including Gamma-Ray Bursts. Finally, I will describe the exciting new results of Fermi in this field and the current status of our knowledge of the magnetar population properties and magnetic fields.

Kouveliotou, chryssa↗
NASA NTRS1992

Bias correction factors for near-Earth asteroids

Knowledge of the population size and physical characteristics (albedo, size, and rotation rate) of near-Earth asteroids (NEA's) is biased by observational selection effects which are functions of the population's intrinsic properties and the size of the telescope, detector sensitivity, and search strategy used. The NEA population is modeled in terms of orbital and physical elements: a, e, i, omega, Omega, M, albedo, and diameter, and an asteroid search program is simulated using actual telescope pointings of right ascension, declination, date, and time. The position of each object in the model population is calculated at the date and time of each telescope pointing. The program tests to see if that object is within the field of view (FOV = 8.75 degrees) of the telescope and above the limiting magnitude (V = +1.65) of the film. The effect of the starting population on the outcome of the simulation's discoveries is compared to the actual discoveries in order to define a most probable starting population.

Benedix, Gretchen K.↗
NASA NTRS2011

The Extreme Case of Magnetars

Magnetars are magnetically powered rotating neutron stars with extreme magnetic fields (over 10(exp 14) Gauss). They were discovered in the X- and gamma-rays where they predominantly emit their radiation. Very few sources (roughly 18) have been found since their discovery in 1987. NASA's Fermi Gamma-ray Space Telescope was launched June 11, 2009; since then the Fermi Gamma-ray Burst Monitor (GBM) recorded emission from four magnetar sources. Two of these were brand new sources, SGR J0501+4516, discovered with Swift and extensively monitored with Swift and GBM, SGR J0418+5729, discovered with GBM and the Interplanetary Network (IPN). A third was SGR J1550-5418, a source originally classified as an Anomalous X-ray Pulsar (AXP 1E1547.0-5408), but exhibiting a very prolific outburst with over 400 events recorded in January 2009. In my talk I will give a short history of magnetars and describe how this, once relatively esoteric field, has emerged as a link between several astrophysical areas including Gamma-Ray Bursts. Finally, I will describe the exciting new results of Fermi in this field and the current status of our knowledge of the magnetar population properties and magnetic fields.

Kouveliotou, Chryssa↗
DOE OSTI2025

Accelerated data-driven materials science with the Materials Project

The Materials Project was launched formally in 2011 to drive materials discovery forwards through high-throughput computation and open data. More than a decade later, the Materials Project has become an indispensable tool used by more than 600,000 materials researchers around the world. This Perspective describes how the Materials Project, as a data platform and a software ecosystem, has helped to shape research in data-driven materials science. We cover how sustainable software and computational methods have accelerated materials design while becoming more open source and collaborative in nature. Next, we present cases where the Materials Project was used to understand and discover functional materials. We then describe our efforts to meet the needs of an expanding user base, through technical infrastructure updates ranging from data architecture and cloud resources to interactive web applications. Finally, we discuss opportunities to better aid the research community, with the vision that more accessible and easy-to-understand materials data will result in democratized materials knowledge and an increasingly collaborative community.

Horton, Matthew K↗
DOE OSTI2024

The Most Distant H i Galaxies Discovered by the 500 m Dish FAST

Abstract Neutral hydrogen (Hi) is the primary component of the cool interstellar medium (ISM) and is the reservoir of fuel for star formation. Owing to the sensitivity of existing radio telescopes, our understanding of the evolution of the ISM in galaxies remains limited, as it is based on only a few hundred galaxies detected in Hibeyond the local Universe. With the high sensitivity of the Five-hundred-meter Aperture Spherical radio Telescope (FAST), we carried out a blind Hisearch, the FAST Ultra-Deep Survey, which extends to redshifts up to 0.42 and a sensitivity of 50μJy beam −1 . Here, we report the first discovery of six galaxies in Hi atz> 0.38. For these galaxies, the FAST angular resolution of ∼4′ corresponds to a mean linear size of ∼ 1.3 h 70 − 1 Mpc. These galaxies are among the most distant Hiemission detections known, with one having the most massive Hicontent ( 10 10.93 ± 0.04 h 70 − 2 M ⊙ ). Using recent data from the DESI survey and new observations with the Hale, Big Telescope Alt-azimuth, and Keck telescopes, optical counterparts are detected for all galaxies within the 3σpositional uncertainty ( 0.5 h 70 − 1 Mpc) and 200 km s −1 in recession velocity. Assuming that the dominant source of Hiis the identified optical counterpart, we find evidence of evolution in the Hicontent of galaxies over the last 4.2 Gyr. Our new high-redshift Higalaxy sample provides the opportunity to better investigate the evolution of cool gas in galaxies. A larger sample size in the future will allow us to refine our knowledge of the formation and evolution of galaxies.

Astronomy & Astrophysics↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth independence and autonomy of mission operations. Here we present an overview of AI/ML architecture to support deep space mission goals, developed with leaders in the field. First, we focus on the fundamental biological research that supports our understanding of physiological responses to spaceflight, and we describe current efforts to support AI/ML research including data standardization and data engineering through maximally open and FAIR (findable, accessible, interoperable, reusable) databases and the generation of AI-ready datasets for reuse and analysis. We also discuss remote data management frameworks for research data as well as environmental and health data that are generated during deep space missions. We highlight several research projects that leverage data standardization and management for fundamental biological discovery to uncover the complex effects of space travel on living systems. Next, we provide an overview of cutting-edge AI/ML approaches that can be integrated to support remote monitoring and analysis during deep space missions, including generative models and large language models to learn the underlying biomedical patterns and predict outcomes or answer questions during off world medical scenarios. We also describe current AI/ML methods to support this research and monitoring through automated cloud-based labs which enable limited human intervention and closed-loop experimentation in remote settings. These labs could support mission autonomy by analyzing environmental data streams, and would be facilitated through in situ analytics capabilities to avoid sending large raw data files through low bandwidth communications. Finally, in the context of deep space missions with limited communications or access to medical advice from Earth, we describe a solution for integrated, real-time mission biomonitoring across hierarchical levels from continuous environmental monitoring, to wearables and point-of-care devices, to molecular and physiological monitoring. We introduce a precision space health system that will ensure that the future of space health is predictive, preventative, participatory and personalized.

artificial intelligence↗
NASA NTRS1991

Heterogeneous processes: Laboratory, field, and modeling studies

The efficiencies of chemical families such as ClO(x) and NO(x) for altering the total abundance and distribution of stratospheric ozone are controlled by a partitioning between reactive (active) and nonreactive (reservoir) compounds within each family. Gas phase thermodynamics, photochemistry, and kinetics would dictate, for example, that only about 1 percent of the chlorine resident in the lower stratosphere would be in the form of active Cl or ClO, the remainder existing in the reservoir compounds HCl and ClONO2. The consistency of this picture was recently challenged by the recognition that important chemical transformations take place on polar regions: the Airborne Antarctic Ozone Experiment (AAOE) and the Airborne Arctic Stratospheric Expedition (AASA). Following the discovery of the Antarctic ozone hole, Solomon et al. suggested that the heterogeneous chemical reaction: ClONO2(g)+HCl(s) yields Cl2(g)+HNO3(s) could play a key role in converting chlorine from inactive forms into a species (Cl2) that would rapidly dissociate in sunlight to liberate atomic chlorine and initiate ozone depletion. The symbols (s) and (g) denote solid phase, or adsorbed onto a solid surface, and gas phase, respectively, and represent the approach by which such a reaction is modeled rather than the microscopic details of the reaction. The reaction was expected to be most important at altitudes where PSC's were most prevalent (10 to 25 km), thereby extending the altitude range over which chlorine compounds can efficiently destroy ozone from the 35 to 45 km region (where concentrations of active chlorine are usually highest) to lower altitudes where the ozone concentration is at its peak. This chapter will briefly review the current state of knowledge of heterogeneous processes in the stratosphere, emphasizing those results obtained since the World Meteorological Organization (WMO) conference. Sections are included on laboratory investigations of heterogeneous reactions, the characteristics and climatology of PSC's, stratospheric sulfate aerosols, and evidence of heterogeneous chemical processing.

Poole, Lamont R.↗
NASA NTRS2012

Kennedy Space Center

Among 2011's many accomplishments, we safely retired the Space Shuttle Program after 30 incredible years; completed the International Space Station and are taking steps to enable it to reach its full potential as a multi-purpose laboratory; and helped to expand scientific knowledge with missions like Aquarius, GRAIL, and the Mars Science Laboratory. Responding to national budget challenges, we are prioritizing critical capabilities and divesting ourselves of assets no longer needed for NASA's future exploration programs. Since these facilities do not have to be maintained or demolished, the government saves money. At the same time, our commercial partners save money because they do not have to build new facilities. It is a win-win for everyone. Moving forward, 2012 will be even more historically significant as we celebrate the 50th Anniversary of Kennedy Space Center. In the coming year, KSC will facilitate commercial transportation to low-Earth orbit and support the evolution of the Space Launch System and Orion crew vehicle as they ready for exploration missions, which will shape how human beings view the universe. While NASA's Vision is to lead scientific and technological advances in aeronautics and space for a Nation on the frontier of discovery KSC's vision is to be the world's preeminent launch complex for government and commercial space access, enabling the world to explore and work in space. KSC's Mission is to safely manage, develop, integrate, and sustain space systems through partnerships that enable innovative, diverse access to space and inspires the Nation's future explorers.

Griffin, Amanda↗
DOE OSTI2025

Accurate and uncertainty-aware multi-task prediction of HEA properties using prior-guided deep Gaussian processes

Surrogate modeling techniques have become indispensable in accelerating the discovery and optimization of high-entropy alloys (HEAs), especially when integrating computational predictions with sparse experimental observations. This study systematically evaluates the training and testing performance of four prominent surrogate models—conventional Gaussian processes (cGP), Deep Gaussian processes (DGP), encoder-decoder neural networks for multi-output regression and eXtreme Gradient Boosting (XGBoost)—applied to a hybrid dataset of experimental and computational properties of the 8-component HEA system Al-Co-Cr-Cu-Fe-Mn-Ni-V. We specifically assess their capabilities in predicting correlated material properties, including yield strength, hardness, modulus, ultimate tensile strength, elongation, and average hardness under dynamic/quasi-static conditions, alongside auxiliary computational properties. The comparison highlights the strengths of hierarchical deep modeling approaches in handling heteroscedastic, heterotopic, and incomplete data commonly encountered in materials science. Our findings illustrate that combined surrogate models such as DGPs infused with machine-learned priors outperform other surrogates by effectively capturing inter-property correlations and by assimilating prior knowledge. This enhanced predictive accuracy positions the combined surrogate models as powerful tools for robust and data-efficient materials design.

36 MATERIALS SCIENCE↗
NASA NTRS2008

Preparing Cassini Uplink Operations for Extended Mission

The Cassini-Huygens Mission to Saturn and Titan, a joint venture between the National Aeronautics and Space Administration, the European Space Agency, and the Italian Space Agency, is conducting a four-year, prime mission exploring the Saturnian system, including its atmosphere, rings, magnetosphere, moons and icy satellites. Launched in 1997, Cassini began its prime mission in 2004. Cassini is now preparing for a new era, a two-year extended mission to revisit many of the highlights and new discoveries made during the prime mission. Because of the light time delay from Earth to Saturn, and the time needed to coordinate the complicated science and engineering activities that take place on the spacecraft, commanding on Cassini is done in approximately 40-day intervals known as sequences. The Cassini Uplink Operations team is responsible for the final development and validation of the pointing profile and instrument and spacecraft commands that are contained in a sequence. During this final analysis prior to uplink to the spacecraft, thorough and exact evaluation is necessary to ensure there are no mistakes during commanding. In order to perform this evaluation, complete and refined processes and procedures are fundamental. The Uplink Operations team is also responsible for anomaly response during sequence execution, a process in which critical decisions often are made in real-time. Recent anomalies on other spacecraft missions have highlighted two major risks in the operations process: (1) personnel turnover and the retirement of critical knowledge and (2) aging, outdated operations procedures. If other missions are a good barometer, the Cassini extended mission will be presented with a high personnel turnover of the Cassini flight team, which could lead to a loss of expertise that has been essential to the success of the prime mission. In order to prepare the Cassini Uplink Operations Team for this possibility and to continue to develop and operate safe science and engineering sequences, a review and major update of the current documentation and operations procedures was needed. This paper will address the changes made to extended mission sequence generation processes primarily due to new restrictions in spacecraft operating capability and lessons learned from prime mission. In addition, it will address the state of the prime mission operations procedures, the philosophy changes and updates that were made to those procedures in response to process improvement, and the validation of those new procedures through the training of current and new personnel. And lastly, it will address the lessons learned throughout prime mission and how the Uplink Operations team chose to incorporate those lessons into the working documentation and team knowledge. This incorporation was necessary to facilitate the success of the extended mission with potentially all new personnel at some point prior to the end of the mission.

Maxwell, Jennifer L.↗
NASA NTRS2011

Lessons Learned for Planning and Estimating Operations Support Requirements

Operations (phase E) costs are typically small compared to the spacecraft development and test costs. This, combined with the long lead time for realizing operations costs, can lead projects to focus on hardware development schedules and costs, de-emphasizing estimation of operations support requirements during proposal, early design, and replan cost exercises. The Discovery and New Frontiers (D&NF) programs comprise small, cost-capped missions supporting scientific exploration of the solar system. Even moderate yearly underestimates of the operations costs can present significant LCC impacts for deep space missions with long operational durations, and any LCC growth can directly impact the programs ability to fund new missions. The D&NF Program Office at Marshall Space Flight Center recently studied cost overruns for 7 D&NF missions related to phase C/D development of operational capabilities and phase E mission operations. The goal was to identify the underlying causes for the overruns and develop practical mitigations to assist the D&NF projects in identifying potential operations risks and controlling the associated impacts to operations development and execution costs. The study found that the drivers behind these overruns include overly optimistic assumptions regarding the savings resulting from the use of heritage technology, late development of operations requirements, inadequate planning for sustaining engineering and the special requirements of long duration missions (e.g., knowledge retention and hardware/software refresh), and delayed completion of ground system development work. This presentation summarizes the study and the results, providing a set of lessons NASA can use to improve early estimation and validation of operations costs.

Newhouse, Marilyn↗
DOE OSTI2025

Causal Directions Matter: How Environmental Factors Drive Convective Cloud Detrainment Heights

This study investigates how environmental factors influence the level of maximum detrainment (LMD) in deep convective clouds. Through a novel application of the Linear Non‐Gaussian Acyclic Model (LiNGAM), we discover causal structures between environmental variables and LMD, observed at six tropical sites operated by the Atmospheric Radiation Measurement (ARM) user facility. LiNGAM effectively identifies causal directions among variables of interest, revealing robust relationships such as those among the lifting condensation level (LCL), level of free convection (LFC), and convective inhibition (CIN), aligning with prior knowledge. Relative humidity is shown to directly influence LMD; however, this relationship exhibits strong nonlinearity and becomes difficult to detect when the contrast between oceanic and continental environments is excluded from the analysis. This study highlights the importance of establishing causal relationships before performing statistical inference.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Impregnation of Catalytic Metals in Single-Walled Carbon Nanotubes for Toxic Gas Conversion in Life Support System

Carbon nanotubes (CNTs) possess extraordinary properties such as high surface area, ordered chemical structure that allows functionalization, larger pore volume, and very narrow pore size distribution that have attracted considerable research attention from around the world since their discovery in 1991. The development and characterization of an original and innovative approach for the control and elimination of gaseous toxins using single walled carbon nanotubes (SWNTs) promise superior performance over conventional approaches due to the ability to direct the selective uptake of gaseous species based on their controlled pore size, increased adsorptive capacity due to their increased surface area and the effectiveness of carbon nanotubes as catalyst supports for gaseous conversion. We present our recent investigation of using SWNTs as catalytic supporting materials to impregnate metals, such as rhodium (Rh), palladium (Pd) and other catalysts. A protocol has been developed to oxidize the SWNTs first and then impregnate the Rh in aqueous rhodium chloride solution, according to unique surface properties of SWNTs. The Rh has been successfully impregnated in SWNTs. The Rh-SWNTs have been characterized by various techniques, such as TGA, XPS, TEM, and FTIR. The project is funded by a NASA Research Announcement Grant to find applications of single walled nanocarbons in eliminating toxic gas Contaminant in life support system. This knowledge will be utilized in the development of a prototype SWNT KO, gas purification system that would represent a significant step in the development of high efficiency systems capable of selectively removing specific gaseous for use in regenerative life support system for human exploration missions.

Li, Jing↗