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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Chemical Hygiene Program

The Chemical Management Team is responsible for ensuring compliance with the OSHA Laboratory Standard. The program at Lewis Research Center (LeRC) evolved over many years to include training, developing Standard Operating Procedures (SOPS) for each laboratory process, coordinating with other safety and health organizations and teams at the Center, and issuing an SOP binder. The Chemical Hygiene Policy was first established for the Center. The Chemical Hygiene Plan was established and reviewed by technical, laboratory and management for viability and applicability to the Center. A risk assessment was conducted for each laboratory. The laboratories were prioritized by order of risk, higher risk taking priority. A Chemical Management Team staff member interviewed the lead researcher for each laboratory process to gather the information needed to develop the SOP for the process. A binder containing the Chemical Hygiene Plan, the SOP, a map of the laboratory identifying the personal protective equipment and best egress, and glove guides, as well as other guides for safety and health. Each laboratory process has been captured in the form of an SOP. The chemicals used in the procedure have been identified and the information is used to reduce the number of chemicals in the lab. The Chemical Hygiene Plan binder is used as a training tool for new employees. LeRC is in compliance with the OSHA Standard. The program was designed to comply with the OSHA standard. In the process, we have been able to assess the usage of chemicals in the laboratories, as well as reduce or relocate the chemicals being stored in the laboratory. Our researchers are trained on the hazards of the materials they work with and have a better understanding of the hazards of the process and what is needed to prevent any incident. From the SOP process, we have been able to reduce our chemical inventory, determine and implement better hygiene procedures and equipment in the laboratories, and provide specific training to our employees. As a result of this program, we are adding labeling to the laboratories for emergency responders and initiating a certified chemical user program.

Mayor, Antoinette C.↗
NASA NTRS1996

Progress Toward an Efficient and General CFD Tool for Propulsion Design/Analysis

The simulation of propulsive flows inherently involves chemical activity. Recent years have seen substantial strides made in the development of numerical schemes for reacting flowfields, in particular those involving finite-rate chemistry. However, finite-rate calculations are computationally intensive and require knowledge of the actual kinetics, which are not always known with sufficient accuracy. Alternatively, flow simulations based on the assumption of local chemical equilibrium are capable of obtaining physically reasonable results at far less computational cost. The present study summarizes the development of efficient numerical techniques for the simulation of flows in local chemical equilibrium, whereby a 'Black Box' chemical equilibrium solver is coupled to the usual gasdynamic equations. The generalization of the methods enables the modelling of any arbitrary mixture of thermally perfect gases, including air, combustion mixtures and plasmas. As demonstration of the potential of the methodologies, several solutions, involving reacting and perfect gas flows, will be presented. Included is a preliminary simulation of the SSME startup transient. Future enhancements to the proposed techniques will be discussed, including more efficient finite-rate and hybrid (partial equilibrium) schemes. The algorithms that have been developed and are being optimized provide for an efficient and general tool for the design and analysis of propulsion systems.

Cox, C. F.↗
DOE OSTI2025

Resonant inelastic X-ray scattering tools to count 5 $f$ electrons of actinides and probe bond covalency

The actinides possess a complex electronic structure, making their chemical and physical properties among the least understood in the periodic table. Advanced spectroscopic tools, able to obtain deep insights into the electronic structure and binding properties of the actinides, are highly desirable. Here, we introduce two sensitive spectroscopic tools: one determines the number of localized 5f electrons on an actinide atom, and another assesses the covalent character of actinide-ligand bonding. Both tools are based on the multiplet structure present in actinide M 4 edge core-to-core resonant inelastic X-ray scattering (CC-RIXS) maps. The spectral intensity of different many-body final-state multiplets directly depends on the local many-electron ground-state symmetry including the local 5 f spin configuration. By comparing U M 4 edge CC-RIXS data for 21 U, Np, Pu and Am compounds, we demonstrate the ability to compare the number of localized 5 f electrons and bond covalency across the actinide series.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

The preparation and characterization of chemically deuterium incorporated cotton fibers

Preparation of deuterium incorporated cellulose is a vital tool to investigate cellulose internal structure and to expand the application fields of cellulose materials. In this study, cellulosic cotton fibers with anti-rehydration (exchange-resistant) deuterium incorporated in cellulose were prepared by chemical hydrogen–deuterium exchange treatment. The chemical hydrogen–deuterium exchange process, along with exchange time, were characterized by nuclear magnetic resonance hydrogen spectroscopy (1H-NMR). The anti-rehydration deuterium incorporation was determined by Fourier Transform infrared spectroscopy (FTIR) and Stable Isotope Ratio Mass Spectrometer (IRSM). Here, the effect of the deuterium hydroxyl substitution on cotton fiber’s spectral data, microstructure, crystalline information, degree of polymerization, as well as it’s thermogravimetric analysis (charcoalization and combustion) are explored. Analysis of the chemical exchange process indicated that the hydrogen–deuterium exchange occurred preferentially in the amorphous cellulose component over the first several minutes. Deuterium exchange in the anti-rehydration crystalline phase took several hours. Increasing the treatment time, enhanced exchange-resistant deuterium incorporation to as high as about 60% of the cotton fibers’ cellulose hydroxyl groups was achieved. The characterization of FTIR, Fourier transform Raman (FT-Raman), and near-infrared spectra (NIR) all exhibited the deuterium spectral isotope effect on cellulose hydroxl groups. While, apart from the effect of reaction temperature, deuterium incorporation isotope effect did not affect the cellulose microstructure, crystalline index and the degree of polymerization properties. Furthermore, the thermogravimetric analysis of deuterated cotton fibers under N 2 and air atmosphere were both altered due to the thermodynamic isotope effect. These observations revealed the hydrogen–deuterium exchange treatment process and impacts on cellulose fiber properties, which helped us to better understand the cellulose internal structure and may facilitate the potential utilization of deuterated cellulosic materials.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Random forest models accurately classify synthetic opioids using high-dimensionality mass spectrometry datasets

Detection of novel threat agents presents several challenges, a principle one being the development of untargeted methods to screen an increasing number of threat chemicals whose exact structures are unknown. With the use of Machine Learning (ML) tools, we can guide the development of analytical methods for broad-spectrum detection of unbounded threat chemical families in complex mixtures. Toward this goal, we used nominal mass and high-resolution mass spectrometry data for hundreds of synthetic opioids and non-opioid compounds. We tested two ML techniques, logistic regression and random forest, to develop models towards a practical, implementable method for opioid detection. We found that of these tested ML methods, random forest models resulted in the highest validation accuracy (95+%) for both nominal mass and high-resolution classification of opioids versus non-opioids, with low false positive and false negative rates. The RF models were then used to successfully predict the classification of 10 compounds—five opioids and five non-opioids not part of the training and validation analysis. This application of ML is a critical step towards the development of field-deployable nominal mass spectrometers with ML-driven analyses for classification of emergent threats.

Chemistry↗
DOE OSTI2025

Random forest models accurately classify synthetic opioids using high-dimensionality mass spectrometry datasets

Detection of novel threat agents presents several challenges, a principle one being the development of untargeted methods to screen an increasing number of threat chemicals whose exact structures are unknown. With the use of Machine Learning (ML) tools, we can guide the development of analytical methods for broad-spectrum detection of unbounded threat chemical families in complex mixtures. Toward this goal, we used nominal mass and high-resolution mass spectrometry data for hundreds of synthetic opioids and non-opioid compounds. We tested two ML techniques, logistic regression and random forest, to develop models towards a practical, implementable method for opioid detection. We found that of these tested ML methods, random forest models resulted in the highest validation accuracy (95+%) for both nominal mass and high-resolution classification of opioids versus non-opioids, with low false positive and false negative rates. The RF models were then used to successfully predict the classification of 10 compounds—five opioids and five non-opioids not part of the training and validation analysis. This application of ML is a critical step towards the development of field-deployable nominal mass spectrometers with ML-driven analyses for classification of emergent threats.

Arasteh, Kourosh [Lawrence Livermore National Labo↗
DOE OSTI2026

Characterizing the impact of water uptake on light absorption by aerosol particles

Absorbing aerosols (AA) have an important impact on the global radiation budget. The composition and properties of AA can vary substantially throughout the atmosphere, depending on the particle source and the influence of chemical aging. Uncertainties associated with the radiative effects of AA remain substantial. A key contributor to this uncertainty is understanding the extent to which water uptake alters absorption by AA particles and how this depends on particle composition. We have used new and existing experimental tools to systematically characterize the relationship(s) between AA chemical and physical characteristics, relative humidity, and mixing of AA with other aerosol components through a combination of laboratory and field measurements. We have developed fundamental understanding through laboratory experiments that will enable interpretation of field observations at DOE ARM sites and facilitate process-based improvements in the simulation of absorption by carbonaceous aerosols in climate models. In the laboratory experiments we have considered a variety of different AA types, including fullerene soot (a surrogate for refractory black carbon, or BC) and nigrosine (a surrogate for partially soluble brown carbon, or BrC). By examining a range of AA types we will develop insight into how the chemical and physical properties of AA particles (e.g. whether they are refractory or soluble) impact the influence of water uptake on absorption. These AA particles will also be mixed—both internally and externally—with compounds having a wide range of hygroscopic properties to establish how the impact of water uptake on absorption will vary with photochemical processing. These laboratory observations have been compared with commonly used theoretical models, enabling development of empirical models that will facilitate improved representation of absorption by AA particles in regional and global climate models. Overall, our study has contributed to the mission of the Atmospheric System Research program by quantifying how interactions between aerosols and radiation depend on relative humidity. Through this, our work will improve understanding and model representation of aerosol processes as they affect the Earth’s radiation budget.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

Planetary Defense: Options for Deflection of Near Earth Objects

In FY 2002 a team of engineers and scientists at MSFC conducted a preliminary investigation of the options for deflecting a Near Earth Object (NEO) fiom a collision course with the earth. A general discussion of the current threat facing the earth from NEO s is outlined. A suite of tools were developed to model inbound and outbound trajectories, propulsive options, and assessment of threat. Propulsive options considered included; staged chemical, nuclear ablation and deflagration, mass driver and solar sail concepts. Trajectory tools plotted the outbound course to intercept the NE0 and the deflection requirements to cause the inbound NE0 to miss the earth. Threat assessment tools estimated the number of lives saved over a given time frame by deploying a system capable of deflecting an NE0 of a certain size and velocity. All of these tools were integrated into a routine to find the most effective vehicle for a given mission mass and mission time. Discussion of desired future efforts is given. This work was funded under the Revolutionary Aerospace Systems Concepts activity from NASA HQ.

Adams, Robert B.↗
DOE OSTI2024

Long-Term High-Temperature High-Pressure Cable for Geothermal Logging Tools

Downhole logging tools are commonly used to characterize multi-thousand-foot geothermal wells. The elevated temperatures, pressures, and harsh chemical environments present significant challenges for the long-term operation of these tools, especially when real-time data transmission to the surface is required via data cable lines. Teflon-based single or multi-conductor cables with grease-filled cable heads are typically used for downhole tools. However, over extended periods of operation, the gr

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Production of Gaseous Olefins from Syngas over a Cobalt-HZSM-5 Catalyst

Light olefins (C2–C5) are high-value platform chemicals used to produce plastics, lubricants, coating material, and surfactants, and can be intermediates to produce transportation fuels. In this study we report on the development of a Co-based catalyst for direct conversion of fossil as well as biomass derived syngas into light olefins that enables high conversion and olefin/paraffin (O/P) product ratio, minimal selectivity to CO2 (<?1%) and wax formation (C14+ selectivity?<?1%). Over a Co/HZSM-5 bi-functional catalyst 38% CO conversion with C2–C5 olefin selectivity of 48%, and O/P ratio of 4.0 was achieved at 240 °C, 17 bar, and 1.5 L/(g–h). In addition to a gaseous olefin-rich stream a C6–C13 mixed olefin/paraffin liquid byproduct was also produced with 25% selectivity. Both Co loading and the HZSM-5 acidity levels were optimized to maintain the balance between the hydrogenation and the cracking activity to generate high levels of C2–C4 olefins. A suite of catalyst characterization tools were used to correlate the physical and chemical property of the catalyst to the performance of the catalyst towards syngas conversion and C2–C4 olefin selectivity.

Maddi, Balakrishna↗
DOE OSTI2021

Deep Learning Coordinate-Free Quantum Chemistry

Computing quantum chemical properties of small molecules and polymers can provide insights valuable to physicists, chemists and biologists when designing new materials, catalysts, biological probes and drugs. Deep learning can compute quantum chemical properties accurately in a fraction of the time required by commonly used methods such as density functional theory (DFT). However, many of these deep learning architectures require energy minimized molecular geometries as input, which is also computationally expensive, and decreasing the reproducibility and throughput of these methods. In this study, we demonstrate that accurate quantum chemical computations can be performed without optimized geometries by operating in the coordinate-free domain using deep learning on graph encodings. Furthermore, we also find that the choice of graph-encoding architecture substantially affects the performance of these methods. The Wave architecture outperforms graph convolution architectures, particularly on complex molecules. Furthermore, the structures of these graph encoding architectures provide an opportunity to probe an important, outstanding question in quantum mechanics: What types of quantum chemical properties can be represented by local-variable models? We find that Wave, a local-variable model, is more accurately calculates quantum chemical properties. Graph convolutional architectures require global variables, and are not as effective as as Wave. We anticipate that coordinate-free, deep-learning models of quantum chemistry will become valuable tools in chemistry and biology, enabling researchers to rapidly screen chemical databases or identify new molecules using automated, de-novo design algorithms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Feature-agnostic metabolomics for determining effective subcytotoxic doses of common pesticides in human cells

Although classical molecular biology assays can provide a measure of cellular response to chemical challenges, they rely on a single biological phenomenon to infer a broader measure of cellular metabolic response. These methods do not always afford the necessary sensitivity to answer questions of subcytotoxic effects, nor do they work for all cell types. Likewise, boutique assays such as cardiomyocyte beat rate may indirectly measure cellular metabolic response, but they too, are limited to measuring a specific biological phenomenon and are often limited to a single cell type. For these reasons, toxicological researchers need new approaches to determine metabolic changes across various doses in differing cell types, especially within the low-dose regime. Here, the data collected herein demonstrate that LC-MS/MS-based untargeted metabolomics with a feature-agnostic view of the data, combined with a suite of statistical methods including an adapted environmental threshold analysis, provides a versatile, robust, and holistic approach to directly monitoring the overall cellular metabolomic response to pesticides. When employing this method in investigating two different cell types, human cardiomyocytes and neurons, this approach revealed separate subcytotoxic metabolomic responses at doses of 0.1 and 1 µM of chlorpyrifos and carbaryl. These findings suggest that this agnostic approach to untargeted metabolomics can provide a new tool for determining effective dose by metabolomics of chemical challenges, such as pesticides, in a direct measurement of metabolomic response that is not cell type-specific or observable using traditional assays.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Fundamental Studies of Soiling and Cementation of PV Cover Glass Materials: Addressing Reliability with Advanced X-ray Scattering/Spectroscopy and First Principles Modeling (Final Technical Report)

Accumulation of soils and other particulate matter on the front cover glass of solar photovoltaic (PV) modules results in transmission losses that detrimentally affect the power output of PV installations. The conventional solution to this problem is manual abrasive scrubbing of modules, which entails significant water usage and manpower. To further combat this issue, there is a concerted effort within the PV industry to develop anti-soiling (AS) coatings to mitigate power losses due to soiling of PV modules, which can exceed 35% in some cases. However, relatively little is known about the fundamental physical and chemical mechanisms that enable anti-soiling behavior. In this project, a combination of advanced X-ray analysis tools and first principles computational modeling has employed to understand the physical and chemical interactions between environmental soils and PV cover glass materials. The specific objectives were: 1) investigate soiling interactions and cementation behavior of relevant PV materials, including bare glass, conventional antireflective (AR) coatings, and a commercial AS coating, using a library of representative particulate soils, and 2) utilize first principles computational spectroscopy modeling to interpret the experimental X-ray spectroscopy measurements and determine the detailed surface chemistry changes that occur on these surfaces in the presence of soiling and cementation.

14 SOLAR ENERGY↗
DOE OSTI2023

RB-TnSeq identifies genetic targets for improved tolerance of Pseudomonas putida towards compounds relevant to lignin conversion

We report lignin-derived mixtures intended for bioconversion commonly contain high concentrations of aromatic acids, aliphatic acids, and salts. The inherent toxicity of these chemicals places a significant bottleneck upon the effective use of microbial systems for the valorization of these mixtures. Pseudomonas putida KT2440 can tolerate stressful quantities of several lignin-related compounds, making this bacterium a promising host for converting these chemicals to valuable bioproducts. Nonetheless, further increasing P. putida tolerance to chemicals in lignin-rich substrates has the potential to improve bioprocess performance. Accordingly, we employed random barcoded transposon insertion sequencing (RB-TnSeq) to reveal genetic determinants in P. putida KT2440 that influence stress outcomes during exposure to representative constituents found in lignin-rich process streams. The fitness information obtained from the RB-TnSeq experiments informed engineering of strains via deletion or constitutive expression of several genes. Namely, ΔgacAS, ΔfleQ, ΔlapAB, ΔttgR::P tac :ttgABC, Ptac:PP_1150:PP_1152, ..delta..relA, and ΔPP_1430 mutants showed growth improvement in the presence of single compounds, and some also exhibited greater tolerance when grown using a complex chemical mixture representative of a lignin-rich chemical stream. Overall, this work demonstrates the successful implementation of a genome-scale screening tool for the identification of genes influencing stress tolerance against notable compounds within lignin-enriched chemical streams, and the genetic targets identified herein offer promising engineering targets for improving feedstock tolerance in lignin valorization strains of P. putida KT2440.

09 BIOMASS FUELS↗
DOE OSTI2023

Plan for a Data Base Approach to Evaluating LWR Plant Integration with Hydrogen and Industrial Facilities

The purpose of this report is to provide an outline and scope of a database tool that could be used to identify the most beneficial locations to site a hydrogen, chemical facility or other industrial facility that would be powered by nuclear energy. This energy may be in the form of electricity produced by the plant, heat in the form of steam or both. In addition, this siting tool should consider factors such as economics, geography, industries, residences, geological hydrogen storage, and key infrastructure. The infrastructure to be considered could include pipelines or other storage and transportation facilities to carry the created products from the production facility to the end user. Also considered should be infrastructure that could deliver needed chemicals or gasses to allow the production of desired products such as ammonia or biofuels. This data base tool should allow a screening study of all U.S. nuclear plants to identify opportunities and barriers to creating hydrogen hubs around nuclear power plants. For this effort, it has been decided that the Siting Tool for Advanced Nuclear Development (STAND) would be used to conduct this screening study which is a follow-on research project to this present effort. Currently, plans are being developed to modify the STAND tool to provide the capability necessary to perform screening of each US commercial nuclear plant to identify the best locations to site hydrogen or chemical production facilities. Many features of the current STAND tool will be employed to meet this objective, but additional infrastructure data (such as the location of pipelines) may need to be added to allow these locations to be fully vetted. In addition, new analysis capabilities may need to be added so economic considerations can be understood

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Indium segregation in Gd 5 (Si, Ge) 4 magnetocaloric materials

Chemical substitution is one of the most efficient tools to tune and optimize magnetic and magnetocaloric properties of the giant magnetocaloric materials. In particular, Indium substitutions could be useful both for tuning properties of these interesting intermetallic materials and to unveil their local-scale behavior across the magnetostructural transition via hyperfine techniques. Hence, in order to investigate the effect of Indium additions on the crystal structure, micro-structure, magnetic and magnetocaloric properties, a series of In-containing samples derived from the base Gd 5 Si 1.2 Ge 2.8 stoichiometry were prepared. Here, the major findings are that while In is insoluble in the 5:4 phase, it will instead promote the emergence of the impurity 5:3 phase and segregates into this phase. Hence, In leads to major crystallographic changes, which enhance atomic disorder and disrupt the Si to Ge ratio in the 5:4 phase. Subsequently, a higher 5:4 unit cell volume and a lower magnetic ordering temperature are found in the In-substituted samples. Finally, the magnetocaloric properties of the In-substituted samples reveal a detrimental effect on the maximum magnetic entropy change.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Nondestructive geochemical characterization of fossil hominin taphonomy and burial history

To date, only three Homo habilis specimens have been discovered that have associated craniodental and postcranial elements, providing a limited fossil record of the ontogeny and morphology of early members of the genus Homo. Recently, a nearly complete dentition, likely attributable to H. habilis, was discovered and excavated from early Pleistocene-age fluvial-lacustrine sediments of the upper Burgi Member of the Koobi Fora Formation at site F25787 in Area 13, near Ileret, Kenya. On the surface less than 15 m away, at site F25966, postcranial elements were found, which, if from the same individual as the nearby dentition, would represent the fourth associated craniodental and postcranial assemblage of this species. We developed a geochemical taphonomic history of these ca. 2 Ma hominin fossils using nondestructive X-ray based microanalytical tools (synchrotron and benchtop X-ray fluorescence chemical imaging and micro- and nano-computed tomography volumetric reconstruction), bulk analyses of sediments and paleosols at the excavation sites, and sedimentologic and stratigraphic observations. We integrate the chemical and physical taphonomic histories to test whether teeth (excavated in situ) and postcranial bones (eroded onto the outcrop surface) derive from a single individual. Minor differences in taphonomic history are attributable to the different biomineral properties of the dental and osseous components and to differences in physical damage during early post-mortem scavenging, dispersal, and burial in adjacent depositional settings. Microscale geochemical mapping enabled the temporal ordination of chemical and physical events in the specimens’ chemical taphonomic histories. Specifically, authigenic Fe- and K-bearing clays and Y, U, and Sr uptake occurred in post-burial fractures in bones and were also incorporated pervasively throughout dentin in teeth. Barite mineralization occurred along the latest fractures in both materials, and as a coating on tooth roots. The stratigraphic, taphonomic, and geochemical evidence supports the interpretation that the hominin fossils represent a single individual. Finally, successful application of these nondestructive sample characterization methods demonstrates capabilities for thorough interrogation of the taphonomic histories of other potential hominin fossil associations, enabling more robust and accurate palaeontologic constraints using those relationships.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Understanding and Controlling the Performance-Limiting Steps of Catalyst-Modified Semiconductors

Understanding and controlling factors that restrict the rates of fuel-forming reactions are essential to designing effective catalyst-modified semiconductors for applications in solar-to-fuel technologies. Herein, we describe GaAs semiconductors featuring a polymeric coating that contains cobaloxime-type catalysts for photoelectrochemically powering hydrogen production. The activities of these electrodes (limiting current densities >20 mA cm –2 under 1-sun illumination) enable identification of fundamental performance-limiting bottlenecks encountered at relatively high rates of fuel formation. Experiments conducted under varying bias potential, pH, illumination intensity, and scan rate reveal two distinct mechanisms of photoelectrochemical hydrogen production. At relatively low polarization and pH, the limiting photoactivity is independent of illumination conditions and is attributed to a mechanism involving reduction of substrate protons. At relatively high polarization or pH, the limiting photoactivity shows a linear response to increasing photon flux and is attributed to a mechanism involving reduction of substrate water. Furthermore, this work illustrates the complex interplay between transport of photons, electrons, and chemical substrates in photoelectrosynthetic reactions and highlights diagnostic tools for better understanding these processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗