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All sources NASA NTRS DOE OSTI

DOE OSTI2023

Data Archive and Portal (DAP) Platform for Solid Phase Processing Technologies

The scale and speed of data generated by modern scientific experiments have constantly challenged the research community to store, curate, manage and optimally use it to drive scientific discoveries. In this work, we have developed a data archive and portal (DAP) platform including analytics capabilities to collect, curate, and manage data and metadata stream for solid phase processing (SPP) techniques. We successfully hosted around ~347K files of data related to processing parameters, microscopic images, and spectroscopic data related to solid phase processing. The DAP platform for SPP will establish an enduring capability to support machine learning and grow collaboration at the intersection of materials science and data science.

36 MATERIALS SCIENCE↗

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 OSTI2019

An integrated meta-omics approach reveals substrates involved in synergistic interactions in a bisphenol A (BPA)-degrading microbial community

BACKGROUND:Understanding microbial interactions in engineering bioprocesses is important to enhance and optimize performance outcomes and requires dissection of the multi-layer complexities of microbial communities. However, unraveling microbial interactions as well as substrates involved in complex microbial communities is a challenging task. Here, we demonstrate an integrated approach of metagenomics, metatranscriptomics, and targeted metabolite analysis to identify the substrates involved in interspecies interactions from a potential cross-feeding model community-bisphenol A (BPA)-biodegrading community, aiming to establish an identification method of microbial interactions in engineering or environmental bioprocesses. RESULTS:The community-level BPA-metabolic pathway was constructed using integrated metagenomics and targeted metabolite analyses. The dynamics of active functions and metabolism of major community members were identified using metagenomic and metatranscriptomic analyses in concert. Correlating the community BPA biodegradation performance to the individual bacterial activities enabled the discovery of substrates involved in a synergistic interaction of cross-feeding between BPA-degrading Sphingonomas species and intermediate users, Pseudomonas sp. and Pusillimonas sp. This proposed synergistic interaction was confirmed by the co-culture of a Sphingonomas sp. and Pseudomonas sp. isolates, which demonstrated enhanced BPA biodegradation compared to the isolate of Sphingonomas sp. alone. CONCLUSION:The three types of integrated meta-omics analyses effectively revealed the metabolic capability at both community-wide and individual bacterial levels. The correlation between these two levels revealed the hidden connection between apparent overall community performance and the contributions of individual community members and their interactions in a BPA-degrading microbial community. In addition, we demonstrated that using integrated multi-omics in conjunction with culture-based confirmation approach is effective to elucidate the microbial interactions affecting the performance outcome. We foresee this approach would contribute the future application and operation of environmental bioprocesses on a knowledge-based control.

59 BASIC BIOLOGICAL SCIENCES↗

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↗

DOE OSTI2020

Emerging materials intelligence ecosystems propelled by machine learning

We report that the age of cognitive computing and artificial intelligence (AI) is just dawning. Inspired by its successes and promises, several AI ecosystems are blossoming, many of them within the domain of materials science and engineering. These materials intelligence ecosystems are being shaped by several independent developments. Machine learning (ML) algorithms and extant materials data are utilized to create surrogate models of materials properties and performance predictions. Materials data repositories, which fuel such surrogate model development, are mushrooming. Automated data and knowledge capture from the literature (to populate data repositories) using natural language processing approaches is being explored. The design of materials that meet target property requirements and of synthesis steps to create target materials appear to be within reach, either by closed-loop active-learning strategies or by inverting the prediction pipeline using advanced generative algorithms. AI and ML concepts are also transforming the computational and physical laboratory infrastructural landscapes used to create materials data in the first place. Surrogate models that can outstrip physics-based simulations (on which they are trained) by several orders of magnitude in speed while preserving accuracy are being actively developed. Automation, autonomy and guided high-throughput techniques are imparting enormous efficiencies and eliminating redundancies in materials synthesis and characterization. The integration of the various parts of the burgeoning ML landscape may lead to materials-savvy digital assistants and to a human-machine partnership that could enable dramatic efficiencies, accelerated discoveries and increased productivity. Here, we review these emergent materials intelligence ecosystems and discuss the imminent challenges and opportunities. The materials research landscape is being transformed by the infusion of approaches based on machine learning. This Review discusses the emerging materials intelligence ecosystems and the potential of human-machine partnerships for fast and efficient virtual materials screening, development and discovery.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Stop Codon Reassignment in the Wild

Since the discovery of the genetic code and protein translation mechanisms (1), a limited number of variations of the standard assignment between unique base triplets (codons) and their encoded amino acids and translational stop signals have been found in bacteria and phages (2-3). Given the apparent ubiquity of the canonical genetic code, the design of genomically recoded organisms with non-canonical codes has been suggested as a means to prevent horizontal gene transfer between laboratory and environmental organisms (4). It is also predicted that genomically recoded organisms are immune to infection by viruses, under the assumption that phages and their hosts must share a common genetic code (5). This paradigm is supported by the observation of increased resistance of genomically recoded bacteria to phages with a canonical code (4). Despite these assumptions and accompanying lines of evidence, it remains unclear whether differential and non-canonical codon usage represents an absolute barrier to phage infection and genetic exchange between organisms. Our knowledge of the diversity of genetic codes and their use by viruses and their hosts is primarily derived from the analysis of cultivated organisms. Advances in single-cell sequencing and metagenome assembly technologies have enabled the reconstruction of genomes of uncultivated bacterial and archaeal lineages (6). These initial findings suggest that large scale systematic studies of uncultivated microorganisms and viruses may reveal the extent and modes of divergence from the canonical genetic code operating in nature. To explore alternative genetic codes, we carried out a systematic analysis of stop codon reassignments from the canonical TAG amber, TGA opal, and TAA ochre codons in assembled metagenomes from environmental and host-associated samples, single-cell genomes of uncultivated bacteria and archaea, and a collection of phage sequences

09 BIOMASS FUELS↗

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.↗

DOE OSTI2023

Engineering custom morpho- and chemotypes of Populus for sustainable production of biofuels, bioproducts, and biomaterials

Humans have been modifying plant traits for thousands of years, first through selection (i.e., domestication) then modern breeding, and in the last 30 years, through biotechnology. These modifications have resulted in increased yield, more efficient agronomic practices, and enhanced quality traits. Precision knowledge of gene regulation and function through high-resolution single-cell omics technologies, coupled with the ability to engineer plant genomes at the DNA sequence, chromatin accessibility, and gene expression levels, can enable engineering of complex and complementary traits at the biosystem level. Populus spp., the primary genetic model system for woody perennials, are among the fastest growing trees in temperate zones and are important for both carbon sequestration and global carbon cycling. Ample genomic and transcriptomic resources for poplar are available including emerging single-cell omics datasets. To expand use of poplar outside of valorization of woody biomass, chassis with novel morphotypes in which stem branching and tree height are modified can be fabricated thereby leading to trees with altered leaf to wood ratios. These morphotypes can then be engineered into customized chemotypes that produce high value biofuels, bioproducts, and biomaterials not only in specific organs but also in a cell-type-specific manner. For example, the recent discovery of triterpene production in poplar leaf trichomes can be exploited using cell-type specific regulatory sequences to synthesize high value terpenes such as the jet fuel precursor bisabolene specifically in the trichomes. By spatially and temporally controlling expression, not only can pools of abundant precursors be exploited but engineered molecules can be sequestered in discrete cell structures in the leaf. The structural diversity of the hemicellulose xylan is a barrier to fully utilizing lignocellulose in biomaterial production and by leveraging cell-type-specific omics data, cell wall composition can be modified in a tailored and targeted specific manner to generate poplar wood with novel chemical features that are amenable for processing or advanced manufacturing. Precision engineering poplar as a multi-purpose sustainable feedstock highlights how genome engineering can be used to re-imagine a crop species.

09 BIOMASS FUELS↗

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 OSTI2017

K-Ras(G12D)-selective inhibitory peptides generated by random peptide T7 phage display technology

Amino-acid mutations of Gly{sup 12} (e.g. G12D, G12V, G12C) of V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (K-Ras), the most promising drug target in cancer therapy, are major growth drivers in various cancers. Although over 30 years have passed since the discovery of these mutations in most cancer patients, effective mutated K-Ras inhibitors have not been marketed. Here, we report novel and selective inhibitory peptides to K-Ras(G12D). We screened random peptide libraries displayed on T7 phage against purified recombinant K-Ras(G12D), with thorough subtraction of phages bound to wild-type K-Ras, and obtained KRpep-2 (Ac-RRCPLYISYDPVCRR-NH{sub 2}) as a consensus sequence. KRpep-2 showed more than 10-fold binding- and inhibition-selectivity to K-Ras(G12D), both in SPR analysis and GDP/GTP exchange enzyme assay. K{sub D} and IC{sub 50} values were 51 and 8.9 nM, respectively. After subsequent sequence optimization, we successfully generated KRpep-2d (Ac-RRRRCPLYISYDPVCRRRR-NH{sub 2}) that inhibited enzyme activity of K-Ras(G12D) with IC{sub 50} = 1.6 nM and significantly suppressed ERK-phosphorylation, downstream of K-Ras(G12D), along with A427 cancer cell proliferation at 30 μM peptide concentration. To our knowledge, this is the first report of a K-Ras(G12D)-selective inhibitor, contributing to the development and study of K-Ras(G12D)-targeting drugs. - Highlights: • The first K-Ras(G12D)-selective inhibitory peptides were generated. • These peptides showed more than 10-fold binding- and inhibition-selectivity to K-Ras(G12D) in compared to wild type K-Ras. • The peptide KRpep-2d suppressed downstream signal of K-Ras(G12D) and cell proliferations of cancer cell line A427.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Efficient Removal of Per- and Polyfluoroalkyl Substances from Water with Zirconium-Based Metal–Organic Frameworks

Per- and polyfluoroalkyl substances (PFASs) are an emerging class of contaminants raising increased levels of concern due to their toxic, bioaccumulative, and persistent nature. Current solutions for removing PFAS from contaminated water rely on adsorption-based methods where commonly used sorbents, for example, activated carbons and ion-exchange resins, exhibit low adsorption capacity and a long equilibration time. Motivated by the generally deficient performance of these current materials, this work addresses the need for the discovery of advanced sorbents for high capacity and efficient PFAS removal. The zirconium-based metal–organic framework (MOF) NU-1000 was characterized for the adsorption of three perfluorosulfonic acids (PFSAs, C4–C8) and six perfluorinated carboxylic acids (PFCAs, C1–C9) from aqueous solutions. Here, the results indicate that NU-1000 exhibits outstanding adsorption capacities of 400–620 mg/g for PFSAs and 201–604 mg/g for PFCAs coupled with ultrafast adsorption kinetics featuring equilibrium times of <1 min. Complementary density functional theory calculations reveal that the PFAS@MOF adsorption mechanism is dominated by a combination of hydrogen bonding, electrostatic, and hydrophobic non-covalent PFAS–MOF interactions. Excellent regeneration and reusability characteristics were found, particularly nearly quantitative removal and recovery rates of NU-1000 after five consecutive adsoption and desorption cycles of PFAS. Additional adsorption testing using PFAS-contaminated groundwater samples obtained from U.S. Air Force bases revealed impressive PFAS removal rates of 75–98% within 10 min regardless of the presence of co-contaminants. To the best of our knowledge, the suite of herein presented PFAS sorption characteristics—capacity, kinetics, regeneration, and reusability—significantly outperforms other current sorbents, rendering NU-1000 as a promising platform for the rapid and effective removal of PFAS from aqueous media.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Designing workflows for materials characterization

Experimental science is enabled by the combination of synthesis, imaging, and functional characterization organized into evolving discovery loop. Synthesis of new material is typically followed by a set of characterization steps aiming to provide feedback for optimization or discover fundamental mechanisms. However, the sequence of synthesis and characterization methods and their interpretation, or research workflow, has traditionally been driven by human intuition and is highly domain specific. Here, we explore concepts of scientific workflows that emerge at the interface between theory, characterization, and imaging. In this study, we discuss the criteria by which these workflows can be constructed for special cases of multiresolution structural imaging and functional characterization, as a part of more general material synthesis workflows. Some considerations for theory–experiment workflows are provided. We further pose that the emergence of user facilities and cloud labs disrupts the classical progression from ideation, orchestration, and execution stages of workflow development. To accelerate this transition, we propose the framework for workflow design, including universal hyperlanguages describing laboratory operation, ontological domain matching, reward functions and their integration between domains, and policy development for workflow optimization. These tools will enable knowledge-based workflow optimization; enable lateral instrumental networks, sequential and parallel orchestration of characterization between dissimilar facilities; and empower distributed research.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Discovery of high-affinity BCL6-binding peptide and its structure-activity relationship

B cell lymphoma 6 (BCL6) is a transcriptional repressor that interacts with its corepressors BcoR and SMRT. Since this protein-protein interaction (PPI) induces activation and differentiation of B lymphocytes, BCL6 has been an attractive drug target for potential autoimmune disease treatments. Here we report a novel BCL6 inhibitory peptide, F1324 (Ac-LWYTDIRMSWRVP-OH), which we discovered using phage display technology; we also discuss this peptide's structure-activity relationship (SAR). For BCL6(5-129) binding, K{sub D} and IC{sub 50} values of F1324 were 0.57 nM and 1 nM according to the results of an SPR analysis and cell-free ELISA assay, respectively. In contrast, BcoR(Arg498-514Pro) and SMRT(Leu1422-Arg1438) exhibited relatively weak micromole-order binding to BCL6. Furthermore, Fusion protein AcGFP-F1324 transiently expressed in HEK293T cells inhibited intracellular PPI in cell-based M2H assay. By examination of the truncation and fragmentation of F1324, the C-terminal sequence WRVP, which is similar to the BcoR(509-512) sequence WVVP, was identified as being critical for BCL6 binding. In addition, subsequent single-crystal X-ray diffraction analysis of F1324/BCL6(5-129) complex revealed that the high affinity of F1324 was caused by effective interaction of its side chains while its main chain structure was similar to that of BcoR(Arg498-514Pro). To our knowledge, F1324 is the strongest BCL6-binding peptide yet reported. - Highlights: • F1324 was discovered as 5000-times higher affinity peptide to BCL6 than that of BcoR(R498-P514). • X-ray crystal structure analysis revealed the binding mode. • To our knowledge, F1324 is the strongest BCL6-binding and -inhibition peptide so far.

60 APPLIED LIFE SCIENCES↗

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↗

DOE OSTI2020

Novel Microbial Based Enzymatic CO 2 Fixation Mechanisms

The broad, long term goal of the research is to provide insight into the mechanism of novel carboxylation reactions catalyzed by enzymes involved in bacterial alkene, ketone, and epoxide metabolism. Novel convergent pathways in the model microorganism Xanthobacter autotrophicus have been described in which epoxides produced by alkene oxidation and ketones produced by the oxidation of alcohols are further carboxylated and utilized in energy yielding pathways. Both alkene/epoxide and alcohol/ketone pathways involve distinct carboxylases with unique molecular properties and cofactor requirements that represent alternative mechanisms of CO 2 fixation. The main focus and aims of this project is to provide structural basis for the mechanistic understanding of the reactions catalyzed by 2-ketopropyl coenzyme M oxidoreductase / carboxylase and acetone carboxylase, the terminal steps in the convergent pathways of alkene/epoxide and alcohol ketone metabolism in X. autotrophicus strain Py2. Interestingly, coenzyme M (CoM), the simplest known organic coenzyme, has been shown to have a central role in the pathway of alkene/epoxide carboxylation. Prior to this discovery CoM was thought only to be involved in methanogenesis in archaea. In addition to the carboxylation mechanisms, we are examining the enzymology of the biosynthesis of CoM in bacteria and we have already determined that it is biochemically distinct from that of CoM synthesized by methanogens. The proposed studies will reveal new and unique insights into CO 2 fixation pathways and carboxylation chemistry. We are utilizing a multidisciplinary approach involving kinetic studies, site-specific amino acid substitution studies, and the determination of high-resolution structures of enzymes in the presence of substrate analogs and mechanism base inhibitors to ascertain information concerning the biochemical mechanisms of enzyme catalyzed reactions. Within the context of the mission of the Department of Energy and the core activities of the Energy Biosciences, the results obtained in the study will reveal new insights into these novel carboxylation reactions and will provide the basis for the comparison of the mechanism of these interesting enzymes to other well-characterized biological mechanisms for CO 2 fixation and carboxylation. Knowledge concerning the mechanism of these enzymes provides the basis for an increased fundamental understanding of carboxylation chemistry that could contribute to future mechanisms for CO 2 capture and fixation and, in turn, to mitigating the effects of increasing concentrations of CO 2 on global climate change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Conversion of CO 2 into Commercial Materials Using Carbon Feedstocks

In this project, our research focused on developing reaction chemistry that would support using carbon as a reductant for CO 2 utilization that would permit CO 2 consumption on a scale that would match or exceed anthropomorphic CO 2 generation for energy production from fossil fuels. Armed with the knowledge that reactions attempting to produce compounds with an energy content greater than CO 2 would be thermodynamically challenged and/or require significant amounts of energy, we developed a potential process that utilized a solid carbon source and recycled the carbon to effectively provide infinite time for the carbon to react. During testing of different carbon sources, we found a wide range of reaction rates. Biomass-derived samples had the most reactivity and coals and petcoke had the lowest. Because we had anticipated this challenge, we recognized that a catalyst would be necessary to improve reaction rates and conversion. From the data analysis of carbon samples, we recognized that alkali metals improved the reaction rate. Through parametric testing of catalyst formulations we were able to increase the reaction rate with petcoke by a factor of >70. Our efforts to identify the reaction mechanism to assist in improving the catalyst formulation demonstrated that the catalyst was catalyzing the extraction of oxygen from CO 2 and using this extracted oxygen to oxidize carbon. This was a significant discovery in that if we could modify the catalyst formulation to permit controlled the oxidation, we would have a very power selective oxidation process. With selective oxidation, CO 2 utilization could be effective used as one of the process steps in making many of the large volume commodity chemicals that support our modern lifestyles. The key challenges for incorporating these functionalities into the catalyst formulation were to make the oxidation selective and lower the temperature required for catalytic activity. We identified four catalyst families that had the potential to meet these challenges. Initial screening of the catalyst families did show that the reduction/oxidation activity did occur at lower temperatures and that these catalysts were able to cause carbon chain growth as well as C—C cleavage. A preliminary techno-economic feasibility of using petcoke/catalyst to produce a CO-rich syngas product was completed and showed significant economic promise. Testing of the different catalyst families demonstrated that Catalyst A was able to stably produce 5 sccm of ethylene/gram of catalyst at 900°C for one hour. For dry methane reforming, our Catalyst 4 was able to achieve production rates of > 10 sccm of CO and > 3 sccm of H2 per gram of catalyst at 600°C and 350 psig. Based on these developments, the potential for CO 2 utilization in the production of large volume commodity chemicals is very promising.

10 SYNTHETIC FUELS↗

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↗

NASA NTRS1997

New Dust Features Observed with ISO

This paper will review our current knowledge of circumstellar and interstellar dust with the emphasis on infrared spectroscopy with ISO. Objects embedded in or located behind molecular clouds show a wealth of absorption features due to simple molecules in an icy mantle. The SWS on ISO has provided us, for the first time, with complete 3-45 um spectra which allow an inventory of interstellar ice. Among the species identified are H2O, CH3OH, CH4, CO2, CO, and OCS. These species are formed through simple reactions among gas phase species accreted on grain surfaces, possibly modified by FUV photolysis and warm-up (ie., outgassing). The implications of the observations for our understanding of these processes will be reviewed. The IR spectra of many UV bright objects are dominated by strong emission features at 3.3, 6.2, 7.7, and 11.3 micrometers. These are generally attributed to Polycyclic Aromatic Hydrocarbons (PAHs) molecules. The observational evidence will be reviewed. The emphasis will be on recent data which show widespread spectral variations, particularly among protoplanetary and planetary nebulae, and their implications. One of the most exciting, recent discoveries on interstellar and circumstellar dust has been the detection of spectral structure due to crystalline olivine and enstatite in a variety of objects surrounded by circumstellar silicates. These spectra will be reviewed and circumstellar silicate mineralogy will be discussed.

Tielens, Alexander G. G. M.↗