Search NASA⌕ Search

SEARCH · Search NASA

Results for “Precursor Analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4

Verification of a Modeling Toolkit for the Design of Building Electrical Distribution Systems

DC electrical distribution systems offer many potential advantages over their AC counterparts. They can facilitate easier integration with distributed energy resources, improve system energy efficiency by eliminating AC/DC converters at end-use devices (e.g., laptop chargers), and reduce installation material, time, and cost. However, DC electrical distribution systems present additional design considerations, largely resulting from potentially greater magnitude and variation in cable losses. Modeling and simulation are rarely used to design such systems. However, the greater dependency of DC system energy efficiency on design choices such as distribution voltages, architecture, and integration of PV and BESS suggests that modeling and simulation may be required. Such system performance analysis is currently not a standard practice, in part due to limited availability and validation of capable software tools. This paper characterizes the accuracy of a Modelica-based Building Electrical Efficiency Analysis Model (BEEAM) toolkit, as a precursor for validating its use to perform system performance analysis and inform design decisions. The study builds upon previous verification research by characterizing complete systems comprised of commercially available equipment, and providing a more detailed analysis of simulation results. Five lighting systems with varying electrical distribution architectures were designed using market-available equipment, installed in a laboratory environment, modeled using BEEAM, and simulated using three Modelica integrated development environments (IDEs). Simulated and measured results were compared to characterize toolkit accuracy. Initial results revealed that simulated performance was mostly within ±5% of measured system-level and device-level performance. While simulation results were not found to be dependent on the IDE, some Modelica compiler interoperability issues were identified. Although the BEEAM toolkit showed promise for the targeted use case, further work is needed to determine whether the demonstrated 5% accuracy is sufficient for making real-world design decisions, and for BEEAM to advance from an interesting research tool to one that can impact real-world building projects.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Influence of Alkyne Precursor Structure on Carbon Nanotube Chiral Distribution: Data-Dense Analysis Across Multiple Catalyst Types

Carbon nanotubes (CNTs) are a desirable material in the field of optoelectronics and semiconductors due to electronic properties (e.g., bandgap) that are dependent upon their chirality, defined by their diameter and lattice angle. Unfortunately, industrial-scale syntheses have yet to realize growth of a single desired chirality and instead rely on postsynthetic separation techniques to refine a chiral mixture, which increases process complexity and cost. Here, we studied the influence of precursor structure on chiral distribution, using a series of terminal alkyne precursors (acetylene, methylacetylene, vinylacetylene, 1-butyne, two enantiomers of 3-butyn-2-ol and a racemic mixture thereof) to grow CNTs across five transition-metal catalysts (Fe, FeMo, and three proportions of CoMo). Multiwavelength Raman spectroscopy on 5,145 spots (5 catalysts, 7 precursors, 3 lasers, and 49 distinct substrate locations on each) determined that acetylene grew the smallest diameter CNTs, while vinylacetylene produced fewer subnanometer CNTs. Though precursor structure did not dictate a uniform chiral shift, it was shown to broaden or narrow chiral distribution, while catalyst structure played a dominant role. In conclusion, this is consistent with metal-precursor binding occurring through unsaturated bonds in the hydrocarbons via the alkyne polymerization mechanism.

Carbon nanotubes↗

Detection of CH 4 Hotspots from NASA’s GEOS Composition Analysis System

Recent research indicates that 8 to 12% of the global oil and gas production methane emissions could be attributed to ultra-emitters, which result in high concentration ‘hotspots’ near point sources. Identifying these emissions in near real time provides useful information to the policy makers and private industry, who are working to reduce their impact. To meet this need, scientists are increasingly analyzing satellite data from the TROPOspheric Monitoring Instrument (TROPOMI) instrument aboard ESA’s Sentinel 5-Precursor mission. While direct analysis of TROPOMI level 2 swath data has been successful in identifying some large emission events, identifying hotpots is challenging because of the imaging noise due to a variety of artifacts and limits in daily coverage. Here we explore possible methodologies to detect methane hotspots using a new, gap-filled, and temporally continuous methane product from NASA’s Goddard Earth Observing System (GEOS) Constituent Data Assimilation System (CoDAS), which assimilates column averaged methane mole fractions from the TROPOMI with capabilities to assimilate other remote sensing measurements. The CoDAS has been expanded from a heritage of stratospheric composition and carbon dioxide assimilation allowing for the support of regional modeling, validation with non-coincident operations, and merging variety of datasets. The current work mainly explores Observing System Simulation Experiments with methane GEOS simulations without assimilation to prepare the groundwork for further experiments with assimilated TROPOMI. First, known hotspots based on the known inventory are identified to demonstrate the capability of the system to point out emission hotspots. In the next step, a variety of machine learning techniques such as Self-Organizing Maps and Deep Learning are explored to automate detection of the plumes. Finally, a few approaches to quantify emissions from the identified hotspots are presented and are evaluated against the inventory. The effort is directed toward a future evaluation of the CoDAS based methane monitoring system’s ability to successfully detect and quantify hotspots.

Nikolay Balashov↗

Multi-device study of temporal characteristics of magnetohydrodynamic modes initiating disruptions

Disruptions in tokamaks are often preceded by magnetohydrodynamic (MHD) instabilities that can rotate or become locked to the wall. Measurements from magnetic diagnostics in the presence of MHD mode precursors to disruptions can yield potentially valuable input to the plasma control system, with a view to disruption avoidance, prediction and mitigation. This report presents an exploratory analysis of the growth of MHD modes and corresponding time scales on the basis of magnetic measurements in multiple tokamaks. To this end, a database was compiled using disruptive discharges from COMPASS, ASDEX Upgrade, DIII-D and JET, manually classified according to disruption root cause, and characterized by a great diversity of operational conditions and mode dynamics. The typical time during which a mode can be detected using saddle coils and the duration of the locked mode phase in the database both extend over several orders of magnitude, but generally the time scales increase with plasma size. Several additional factors are discussed that can influence these durations, including the disruption root cause. A scaling law for the locked phase duration was estimated, yielding predictions toward ITER of the order of hundreds of milliseconds or even seconds. In addition, a scaling law for the mode amplitude at the disruption onset, proposed earlier by de Vries et al. (2016), is applied to the database, and its predictive capabilities are assessed. Despite significant uncertainty on the predictions from both scaling laws, encouraging trends are observed of the fraction of disruptions that may be detected with sufficient warning time to allow mitigation or even avoidance, based solely on observations of MHD mode dynamics. When combined with similar analysis of measurements from diagnostics that are sensitive to other disruption precursors, our analysis methods and results may contribute to the reliability, robustness and generalization of disruption warning schemes for ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Vapor-Phase Heteroatom Incorporation into Semiconductive Molecular-Scale Magic-Size Clusters

Magic-size metal chalcogenide clusters of molecular size exhibit well-defined structure and unique properties that might be further expanded with the incorporation or substitution of a second metal. Here, we report the postmodification of magic-size clusters synthesized in polymer thin films via exposure to volatile metal organic precursors commonly utilized for atomic layer deposition. Exposure of In 6 S 6 (CH 3 ) 6 clusters to dimethylcadmium results in exposure-dependent incorporation of Cd 2+ , which extends the optical absorbance of the clusters into the visible spectrum. The mechanism for Cd 2+ incorporation is consistent with Cd 2+ replacement of In 3+ that includes methyl ligand removal to maintain charge neutrality. Even for clusters embedded in a polymer matrix, ligand loss leads to sintering and transformation into larger nanoscale aggregates with zinc blende-type structure. The extent of Cd incorporation can be modulated by varying the process temperature and volatile metal organic exposure as well as the choice of volatile metal organic precursor. A computational thermodynamic analysis of heteroatom incorporation for several metals and chemistries reveals that both the stability of the substituted cluster and the favorability of reaction byproducts jointly determine the favorability of cation incorporation.

atomic layer deposition↗

Synthesis of multifilament silicon carbide fibers by chemical vapor deposition

A process for development of clean silicon carbide fiber with a small diameter and high reliability is presented. An experimental evaluation of operating conditions for SiC fibers of good mechanical properties and devising an efficient technique which will prevent welding together of individual filaments are discussed. The thermodynamic analysis of a different precursor system was analyzed vigorously. Thermodynamically optimum conditions for stoichiometric SiC deposit were obtained.

Revankar, Vithal↗

Precursor reaction pathway leading to BiFeO 3 formation: insights from text-mining and chemical reaction network analyses

BiFeO 3 (BFO) is a next-generation non-toxic multiferroic material with applications in sensors, memory devices, and spintronics, where its crystallinity and crystal structure directly influence its functional properties. Designing sol–gel syntheses that result in phase-pure BFO remains a challenge due to the complex interactions between metal complexes in the precursor solution. Here, we combine text-mined data and chemical reaction network (CRN) analysis to obtain novel insight into BFO sol–gel precursor chemistry. We perform text-mining analysis of 340 synthesis recipes with the emphasis on phase-pure BFO and identify trends in the use of precursor materials, including that nitrates are the preferred metal salts, 2-methoxyethanol (2 ME) is the dominant solvent, and adding citric acid as a chelating agent frequently leads to phase-pure BFO. Our CRN analysis reveals that the thermodynamically favored reaction mechanism between bismuth nitrate and 2ME interaction involves partial solvation followed by dimerization, contradicting assumptions in previous literature. We suggest that further oligomerization, facilitated by nitrite ion bridging, is critical for achieving the pure BFO phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling MTS pyrolysis and SiC deposition kinetics using principal component analysis and neural networks

Accurate chemical kinetics modeling is crucial for improving the efficiency of chemical processing and synthesis of ceramic matrix composites. Detailed kinetic models are computationally expensive due to the large number of transported chemical species, while the simplified physics-based models, such as single-step global mechanisms, are efficient but often overlook key chemical intermediates and pathways. Recent deep learning approaches promise accurate and cost-effective models. Yet, they require additional closures for the transported nonlinear latent variables, complicating integration with existing solvers. In this work, we develop a hybrid linear—nonlinear reduced model for silicon carbide deposition from methyltrichlorosilane precursor by combining principal component analysis (PCA) and autoencoder (AE) neural network (NN) approaches. PCA is used to identify a smaller set of linear transport variables, enabling direct reuse of conventional transport solvers. NNs then reconstruct the full chemical state from these reduced variables. We demonstrate the method on a chemical vapor deposition reactor—comprising a gas-phase pyrolysis plug flow reactor and a heterogeneous surface reactor—over a wide range of temperatures, pressures, and residence times. Our PCA–AE model achieves high accuracy with only five transported scalars, achieving an eightfold cost reduction compared to detailed mechanisms, in both a priori (using data from the test set only) and a posteriori (coupled with a differential equation solver). In conclusion, notable errors arise primarily near training domain boundaries and for long residence times, indicating the need for domain shift indicators and better long-horizon predictions in future reduced chemistry model development.

autoencoder neural networks↗

The role of precursor decomposition in the formation of samarium doped ceria nanoparticles via solid-state microwave synthesis

The impact on the final morphology of ceria (CeO 2 ) nanoparticles made from different precursors (commercial: cerium acetate/nitrate) and in house: cerium tri(methylsilyl)amide (Ce-TMSA)) via a microwave solid state reaction has been determined. In all instances, powder X-ray diffraction indicated that the cubic fluorite CeO 2 phase (PDF# 04–004-9150, with the space group Fm-3 m) had formed. Scanning electron microscopy (SEM) images revealed spherical nanoparticles were produced from the Ce-TMSA precursor. The commercial acetate and nitrate precursors produced particles with irregular morphology. The roles of the precursor decomposition and binding energy in the synthesis of the nanocrystals with various morphologies, as well as a possible growth mechanism, were evaluated based on experimental and computational data. The formation of spherical shaped nanoparticles was determined to be due to the preferential single-step decomposition of the Ce-TMSA as well as the low activation energy to overcome decomposition. Due to the complicated decomposition of the commercial precursors and high activation energy the resulting particles adopted an irregular morphology. Highly uniform samarium doped ceria (Sm x Ce 1-x O 2-δ ) nanospheres were also synthesized from Ce-TMSA and samarium tri(methylsilyl)amide (Sm-TMSA). The effects of reaction time and temperature, on the final morphology were observed through SEM. The rapid single-step decomposition of TMSA-based precursors as observed through thermogravimetric analysis (TGA) and confirmed through the calculation of potential energy surfaces and binding energies from density functional theory (DFT) calculations, indicated that nanoparticle formation follows LaMer’s classical nucleation theory.

36 MATERIALS SCIENCE↗

Contribution of Speciated Monoterpenes to Secondary Aerosol in the Eastern North Atlantic

Extension of laboratory results suggests that monoterpenes, a subset of marine biogenic volatile organic compounds, might play a competitive role in secondary aerosol formation in the remote marine atmosphere, where the oxidation of dimethyl sulfide has traditionally been thought to dominate. However, the current assessment of the role of monoterpenes in secondary aerosol formation in the remote marine atmosphere is limited by the scarcity of speciated monoterpene measurements and the complete absence of collocated measurements of particle chemical composition and monoterpene speciation. Here, in this paper, we present measurements of gas-phase volatile organic compounds, with particular focus on speciated monoterpenes, and commensurate measurements of aerosol chemical composition in the Eastern North Atlantic. The average monoterpene concentration in periods of marine air was 14 ± 10 ppt, and the dominant isomer was β-pinene (46 ± 10%), with other contributions from α-pinene, limonene, and β-ocimene. The total monoterpene concentration in marine air was greater than that of isoprene by a factor of 3.9 on average, in contrast to prior research and potentially due to the large β-pinene contribution. Monoterpenes were significantly smaller in concentration than dimethyl sulfide, which was also highlighted by the substantial contribution of sulfate to non-refractory submicron aerosol. The mean and interquartile range of the sulfate to organic aerosol mass ratio in clean marine air were 2.7 (0.7–3.4). Finally, a simple box model analysis showed that the BVOC precursors, dimethyl sulfide, methanethiol, monoterpenes, and isoprene, could sustain the measured sulfate to organic aerosol ratio in clean marine air.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Diagnostic studies of the HxOy-NzOy-O3 photochemical system using data from NASA GTE field expeditions

Spring 1084 GTE CITE-1 flight data from the field exercise was obtained from a GTE Data Archive Tape. Chemical and supporting meteorological data taken over the Pacific Ocean was statistically and diagnostically analyzed to identify the key processes affecting the concentrations of ozone and its chemical precursors in the region. The analysis was completed. The analysis of the GTE CITE-2 data is being performed in collaboration with Dr. D.D. Davis and other GTE scientists. Initial results of the analysis were presented and work begun on the paper describing the results.

Chameides, William L.↗

Atmospheric Transport and Photochemistry of Ozone Over Central Southern Africa During the Southern Africa Fire-Atmosphere Research Initiative

Vertically integrated back and forward trajectories for the 300-200, 700-500 and surface-800 hPa levels are calculated using Pretoria as point of origin for the Southern Africa Fire-Atmosphere Research Initiative (SAFARI) period September-October 1992. The transport fields are then combined to show both horizontal and vertical transport of air to and from Pretoria at the different levels. Air transport patterns in the vertical are linked to the occurrence of absolutely stable layers which are also evident in the 16 ozonesonde profiles recorded at Pretoria during SAFARI. The coherence of the stratification based on dynamical and ozone analysis permits the use of mean ozone profiles with air volume fluxes to interpret the ozone in terms of photochemistry and transport within stable layers. Extensive recirculation across the meridional plane at Pretoria implies that advection of ozone is slow and that photochemistry is responsible for the observed vertical structure over central southern Africa in September and October 1992. Requisite ozone formation rates are supported by model analysis of ozone and ozone precursors measured from SAFARI and Transport and Atmospheric Research Chemistry near the Equator-Atlantic aircraft.

Tyson, P. D.↗

The Instability of Monolayer-Thick PbSe on VSe 2

Two-dimensional monolayers derived from 3D bulk structures remain a relatively unexplored class of materials because of the challenge of stabilizing non-epitaxial interfaces. Here, we report an unusual reconstruction during the deposition of precursors when targeting the synthesis of heterostructures with an odd number of PbSe monolayers. Multilayer elemental precursors of Pb|Se + V|Se were deposited to have correct number of atoms to form [(PbSe) 1+δ ] q (VSe 2 ) 1 where q is the number of PbSe monolayers in the heterostructure. Structural analysis of the self-assembled precursor via xray reflectivity, x-ray diffraction, and HAADF-STEM suggests three different behaviors upon deposition. Precursors with q 7 and even values of q have the targeted nanoarchitectures after deposition which are maintained as the products are selfassembled through a near diffusionless process. Significant lateral surface diffusion occurred during deposition of precursors with q = 1, 3, and 5 resulting in the precursor having a different nanoarchitecture than targeted. Additional perpendicular long range diffusion occurs during self-assembly of these precursors resulting in different final products than targeted. DFT calculations of PbSe blocks show that the odd numbered layers are less stable than even numbered layers, which suggests an energetic driving force for the observed rearrangement. This work highlights the importance of understanding the reaction mechanism when attempting to prepare 2D layers of constituents with bulk 3D structures.

36 MATERIALS SCIENCE↗

Single crystal purification reduces trace impurities in halide perovskite precursors, alters perovskite thin film performance, and improves phase stability

Impurities present in commercially available halide perovskite precursors are known to affect photovoltaic performance. Here, we employ bulk single crystal growth of FAPbI 3 using solvent orthogonality induced crystallization (SONIC) to remove a broad set of extrinsic impurities from commercially available halide perovskite precursors, as verified by detailed chemical analysis. Following SONIC purification, FAPbI 3 films made from PbI 2 of originally low purity (99%) and high purity (99.99%) show improved phase purity and stability under light and heat relative to films made from raw precursors or precursors purified via retrograde powder crystallization (RPC) in 2-methoxyethanol, a method commonly utilized in recent reports of the highest-efficiency perovskite solar cells. In conclusion, single-crystal purification of precursors improves film stability under operational stressors, and the large enhancements in material purity provide a cleaner slate for improved isolation of compositional and additive effects on perovskite phase stability.

14 SOLAR ENERGY↗

Evaluation of Volatile Species in Green Monopropellant Project

NASA is interested in green monopropellants to replace hydrazine in reaction control systems (RCSs). Some current NASA programs require reduced vapor pressure and low toxicity monopropellant (green) and superior performance (specific impulse and density) formulations. Earlier vapor phase studies of a candidate green monopropellant at the NASA White Sands Test Facility (WSTF) showed the presence of a volatile species that warranted further investigation. The purpose of this study was to further characterize the volatile species and to evaluate it. The evaluation was with respect to whether the volatile species was an impurity or how it is formed, and to use that information to examine whether its presence as an impurity can be eliminated during formulation. The evaluation also considered whether formation of the volatile impurity could be prevented while not compromising the propellant. To reduce variables associated with evaluation of the propellant formulation as a whole, a precursor to one of the individual components in the propellant formulation was subjected to a NASA Standard 6001B Flammability, Off-gassing, and Compatibility Requirements and Test Procedures "Determination of Off-gassed Products (Test 7)". Testing took place in the NASA WSTF Molecular Desorption and Analysis Laboratory. One gram of the precursor was placed in a flask within a specimen container. After thermal conditioning for 72 +/- 1 h at 50 +/- 3 deg C (122 +/- 5 deg F), the atmosphere inside the specimen container was analyzed for off-gassed compounds by cryotrap gas chromatography-mass spectrometry (GC-MS) and fixed sample loop GC-flame ionization detection (GC-FID). The specimen container used was glass to minimize potential catalytic surfaces. The identification of compounds was difficult due to the complexity of the vapor phase concentrations and overlapping chromatographic peaks and mass spectra. However, eleven compounds were specifically identified and five compounds or classes of compounds were reported as unidentified. Quantitation of most of the compounds, including unidentified compounds, was as methane. Quantitating compounds or classes of compounds that were detected but for which specific calibration is not established as methane is in accordance with the Test 7 standard protocol. The thermal decomposition temperature of the precursor was significantly higher than the test temperature. Based on thermal decomposition temperature and on an examination of the structure and chemistry of the identified volatile species, the presence of the volatile species appears to be chemically reasonable with respect to the propellant formulation and is at this time attributed to impurities. Further examination of the overall propellant formulation process (including the individual components' synthesis processes) and process quality control (including purity of reagents and possible decomposition reactions) is indicated.

Greene, Benjamin↗

Diversification of multipotential postmitotic mouse retinal ganglion cell precursors into discrete types

The genesis of broad neuronal classes from multipotential neural progenitor cells has been extensively studied, but less is known about the diversification of a single neuronal class into multiple types. We used single-cell RNA-seq to study how newly born (postmitotic) mouse retinal ganglion cell (RGC) precursors diversify into ~45 discrete types. Computational analysis provides evidence that RGC transcriptomic type identity is not specified at mitotic exit, but acquired by gradual, asynchronous restriction of postmitotic multipotential precursors. Some types are not identifiable until a week after they are generated. Immature RGCs may be specified to project ipsilaterally or contralaterally to the rest of the brain before their type identity emerges. Optimal transport inference identifies groups of RGC precursors with largely nonoverlapping fates, distinguished by selectively expressed transcription factors that could act as fate determinants. Our study provides a framework for investigating the molecular diversification of discrete types within a neuronal class.

59 BASIC BIOLOGICAL SCIENCES↗

Enantiomeric Excesses of Acid Labile Amino Acid Precursors of the Murchison Meteorite

Amino acids present in carbonaceous chondrite are extracted in water in part as free compounds and in approximately equal part as acid labile precursors. On the assumption that they would be free of contamination, the precursors of two Murchison amino acids that have terrestrial occurrence, alanine and glutamic acid, have been targeted for analysis of their enantiomeric ratios. Pyroglutamic acid, the precursor of glutamic acid, was found with an L-enantiomeric excess comparable to that of the free acid, while alanine's precursor, N-acetyl alanine, appears approximately racemic. Also alpha-imino propioacetic acid, a proposed end product of alanine synthesis in the meteorite, was analyzed and found racemic.

Pizzarello, Sandra↗