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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

The electron-impact promoted fragmentation of aurone epoxides.

The mass spectra of six aurone epoxides have been rationalized with the aid of high resolution mass spectrometry and metastable ion evidence. These compounds fragment in a well defined manner and mechanisms are proposed for the formation of their characteristic ions. Some similarity was observed between the mass spectra of 6-methoxyaurone epoxide (II), 4-hydroxy-7-methoxy-3-phenylcoumarin (VII) and 7-methoxyflavonol (IX). The possibility that VII and IX are intermediates in the fragmentation of epoxide II is discussed. Thermal rearrangement of aurone epoxide II was shown to yield the corresponding flavonol IX and coumarin VII.

Brady, B. A.↗
NASA NTRS1983

Biological particle analysis by mass spectrometry

An instrument that analyzes the chemical composition of biological particles in aerosol or hydrosol form was developed. Efforts were directed toward the acquisition of mass spectra from aerosols of biomolecules and bacteria. The filament ion source was installed on the particle analysis by mass spectrometry system. Modifications of the vacuum system improved the sensitivity of the mass spectrometer. After the modifications were incorporated, detailed mass spectra of simple compounds from the three major classes of biomolecules, proteins, nucleic acids, and carbohydrates were obtained. A method of generating bacterial aerosols was developed. The aerosols generated were collected and examined in the scanning electron microscope to insure that the bacteria delivered to the mass spectrometer were intact and free from debris.

Vilker, V. L.↗
NASA NTRS1973

Trace organic impurities in gaseous helium

A program to determine trace organic impurities present in helium has been initiated. The impurities were concentrated in a cryogenic trap to permit detection and identification by a gas chromatographic-mass spectrometric technique. Gaseous helium (GHe) exhibited 63 GC flame ionization response peaks. Relative GC peak heights and identifications of 25 major impurities by their mass spectra are given. As an aid to further investigation, identities are proposed for 16 other components, and their mass spectra are given.

Schehl, T. A.↗
NASA NTRS2016

Mapping of Spacecraft Atmosphere Monitor Signal to Major Constituent Abundances

The Spacecraft Atmosphere Monitor (S.A.M.) follows the JPL’s commitment to introduce and develop next-generation instrumentation concepts for sensing the air quality on manned space flights via continuous sampling, measuring, and reporting in 2s intervals on all gaseous pollutants. The S.A.M. will have two modes of operation: the Major Constituent Analysis (MCA) mode and the Trace Gas Analysis (TGA) mode. The MCA mode will report on molecular analytes such as CH4, H2O, N2, O2, Ar, and CO2 while the TGA mode will acquire minute amounts of volatile organic compounds. Both modes assess the composition of the ambient air with twenty full mass spectra per second giving rise to a substantial amount of data to be processed by a set of small footprint software stacks hosted by an on-board computer. Mass spectra will be accumulated as the number of counts recorded in a given mass-to-charge channel and converted into the absolute abundances of detected species using an efficient algorithm. The decomposition algorithm contains four units: peak identification, mass calibration, background and dead time correction, and an abundance analysis unit. The abundance analysis module identifies target species through their characteristic fragmentation patterns in the presence of molecular isobars, such as CO and N2. For example, in order to identify N2 analyte, the code will simultaneously monitor abundance ratios of the 14, 28 and 29 Th signals and will adapt to any instability caused by a decrease in ambient pressure or changes in humidity. This requirement becomes critical for instruments designed to monitor the near real-time quality of cabin air and promptly provide accurate feedbacks.

Nikolic, D.↗
DOE OSTI2023

HypoRiPPAtlas as an Atlas of hypothetical natural products for mass spectrometry database search

Abstract Recent analyses of public microbial genomes have found over a million biosynthetic gene clusters, the natural products of the majority of which remain unknown. Additionally, GNPS harbors billions of mass spectra of natural products without known structures and biosynthetic genes. We bridge the gap between large-scale genome mining and mass spectral datasets for natural product discovery by developing HypoRiPPAtlas, an Atlas of hypothetical natural product structures, which is ready-to-use for in silico database search of tandem mass spectra. HypoRiPPAtlas is constructed by mining genomes using seq2ripp, a machine-learning tool for the prediction of ribosomally synthesized and post-translationally modified peptides (RiPPs). In HypoRiPPAtlas, we identify RiPPs in microbes and plants. HypoRiPPAtlas could be extended to other natural product classes in the future by implementing corresponding biosynthetic logic. This study paves the way for large-scale explorations of biosynthetic pathways and chemical structures of microbial and plant RiPP classes.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1971

Electron-impact promoted fragmentation of alkyl-n-/1-phenylethyl/-carbamates of primary, secondary and tertiary alcohols.

The mass spectra of twenty alkyl carbamates derived from primary, secondary, and tertiary alcohols are investigated, using deuterium labeling and high-resolution mass spectrometry. Several of the primary and secondary alcohol derivatives are found to yield an ion formally equivalent to the product ion of a McLafferty rearrangement. Deuterium labeling, however, revealed a lack, in these carbamate derivatives, of the usual site specificity associated with the McLafferty rearrangement. A double hydrogen rearrangement process was observed in the mass spectra of several carbamates derived from tertiary alcohols.

Pereira, W. E.↗
DOE OSTI2025

ChemEcho v1.0

ChemEcho is a tool that converts tandem mass spectra into embeddings used to build machine learning (ML) models with fully explainable predictions. It provides an API for transforming raw tandem mass spectral data into embeddings, along with functions for training and validating ML models. Additionally, it includes utilities for retrieving and cleaning training data. ChemEcho is broadly applicable in ML pipelines that use tandem mass spectra for a variety of tasks, such as chemical classification or bioactivity mining. While there are existing methods to generate embeddings from fragmentation data, ChemEcho's approach ensures that predictions remain interpretable, enabling experts to evaluate results and generate hypotheses about the underlying data.

Harwood, Thomas [Lawrence Berkeley National Labora↗
NASA NTRS1976

Mass spectrometry of aerospace materials

Mass spectrometry is used for chemical analysis of aerospace materials and contaminants. Years of analytical aerospace experience have resulted in the development of specialized techniques of sampling and analysis which are required in order to optimize results. This work has resulted in the evolution of a hybrid method of indexing mass spectra which include both the largest peaks and the structurally significant peaks in a concise format. With this system, a library of mass spectra of aerospace materials was assembled, including the materials responsible for 80 to 90 percent of the contamination problems at Goddard Space Flight Center during the past several years.

Colony, J. A.↗
NASA NTRS2009

Synthesis, Characterization, and Processing of Copper, Indium, and Gallium Dithiocarbamates for Energy Conversion Applications

Ten dithiocarbamate complexes of indium(III) and gallium(III) have been prepared and characterized by elemental analysis, infrared spectra and melting point. Each complex was decomposed thermally and its decomposition products separated and identified with the combination of gas chromatography/mass spectrometry. Their potential utility as photovoltaic materials precursors was assessed. Bis(dibenzyldithiocarbamato)- and bis(diethyldithiocarbamato)copper(II), Cu(S2CN(CH2C6H5)2)2 and Cu(S2CN(C2H5)2)2 respectively, have also been examined for their suitability as precursors for copper sulfides for the fabrication of photovoltaic materials. Each complex was decomposed thermally and the products analyzed by GC/MS, TGA and FTIR. The dibenzyl derivative complex decomposed at a lower temperature (225-320 C) to yield CuS as the product. The diethyl derivative complex decomposed at a higher temperature (260-325 C) to yield Cu2S. No Cu containing fragments were noted in the mass spectra. Unusual recombination fragments were observed in the mass spectra of the diethyl derivative. Tris(bis(phenylmethyl)carbamodithioato-S,S'), commonly referred to as tris(N,N-dibenzyldithiocarbamato)indium(III), In(S2CNBz2)3, was synthesized and characterized by single crystal X-ray crystallography. The compound crystallizes in the triclinic space group P1(bar) with two molecules per unit cell. The material was further characterized using a novel analytical system employing the combined powers of thermogravimetric analysis, gas chromatography/mass spectrometry, and Fourier transform infrared (FT-IR) spectroscopy to investigate its potential use as a precursor for the chemical vapor deposition (CVD) of thin film materials for photovoltaic applications. Upon heating, the material thermally decomposes to release CS2 and benzyl moieties in to the gas phase, resulting in bulk In2S3. Preliminary spray CVD experiments indicate that In(S2CNBz2)3 decomposed on a Cu substrate reacts to produce stoichiometric CuInS2 films.

Duraj, S. A.↗
DOE OSTI2020

A robust clustering algorithm for analysis of composition-dependent organic aerosol thermal desorption measurements

Abstract. One of the challenges of understanding atmospheric organic aerosol (OA) particles stems from its complex composition. Mass spectrometry is commonly used to characterize the compositional variability of OA. Clustering of a mass spectral dataset helps identify components that exhibit similar behavior or have similar properties, facilitating understanding of sources and processes that govern compositional variability. Here, we developed an algorithm for clustering mass spectra, the noise-sorted scanning clustering (NSSC), appropriate for application to thermal desorption measurements of collected OA particles from the Filter Inlet for Gases and AEROsols coupled to a chemical ionization mass spectrometer (FIGAERO-CIMS). NSSC, which extends the common density-based special clustering of applications with noise (DBSCAN) algorithm, provides a robust, reproducible analysis of the FIGAERO temperature-dependent mass spectral data. The NSSC allows for the determination of thermal profiles for compositionally distinct clusters of mass spectra, increasing the accessibility and enhancing the interpretation of FIGAERO data. Applications of NSSC to several laboratory biogenic secondary organic aerosol (BSOA) systems demonstrate the ability of NSSC to distinguish different types of thermal behaviors for the components comprising the particles along with the relative mass contributions and chemical properties (e.g., average molecular formula) of each mass spectral cluster. For each of the systems examined, more than 80 % of the total mass is clustered into 9–13 mass spectral clusters. Comparison of the average thermograms of the mass spectral clusters between systems indicates some commonality in terms of the thermal properties of different BSOA, although with some system-specific behavior. Application of NSSC to sets of experiments in which one experimental parameter, such as the concentration of NO, is varied demonstrates the potential for mass spectral clustering to elucidate the chemical factors that drive changes in the thermal properties of OA particles. Further quantitative interpretation of the thermograms of the mass spectral clusters will allow for a more comprehensive understanding of the thermochemical properties of OA particles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Array-Based Machine Learning for Functional Group Detection in Electron Ionization Mass Spectrometry

Mass spectrometry is a ubiquitous technique capable of complex chemical analysis. The fragmentation patterns that appear in mass spectrometry are an excellent target for artificial intelligence methods to automate and expedite the analysis of data to identify targets such as functional groups. To develop this approach, we trained models on electron ionization (a reproducible hard fragmentation technique) mass spectra so that not only the final model accuracies but also the reasoning behind model assignments could be evaluated. The convolutional neural network (CNN) models were trained on 2D images of the spectra using transfer learning of Inception V3, and the logistic regression models were trained using array-based data and Scikit Learn implementation in Python. Our training dataset consisted of 21,166 mass spectra from the United States’ National Institute of Standards and Technology (NIST) Webbook. The data was used to train models to identify functional groups, both specific (e.g., amines, esters) and generalized classifications (aromatics, oxygen-containing functional groups, and nitrogen-containing functional groups). We found that the highest final accuracies on identifying new data were observed using logistic regression rather than transfer learning on CNN models. It was also determined that the mass range most beneficial for functional group analysis is 0–100 m/z. We also found success in correctly identifying functional groups of example molecules selected from both the NIST database and experimental data. Beyond functional group analysis, we also have developed a methodology to identify impactful fragments for the accurate detection of the models’ targets. The results demonstrate a potential pathway for analyzing and screening substantial amounts of mass spectral data.

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

Ultrafast dynamics of fluorene initiated by highly intense laser fields

Here, we present an investigation of the ultrafast dynamics of the polycyclic aromatic hydrocarbon fluorene initiated by an intense femtosecond near-infrared laser pulse (810 nm) and probed by a weak visible pulse (405 nm). Using a multichannel detection scheme (mass spectra, electron and ion velocity-map imaging), we provide a full disentanglement of the complex dynamics of the vibronically excited parent molecule, its excited ionic states, and fragments. We observed various channels resulting from the strong-field ionization regime. In particular, we observed the formation of the unstable tetracation of fluorene, above-threshold ionization features in the photoelectron spectra, and evidence of ubiquitous secondary fragmentation. We produced a global fit of all observed time-dependent photoelectron and photoion channels. This global fit includes four parent ions extracted from the mass spectra, 15 kinetic-energy-resolved ionic fragments extracted from ion velocity map imaging, and five photoelectron channels obtained from electron velocity map imaging. The fit allowed for the extraction of 60 lifetimes of various metastable photoinduced intermediates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Study of Excited Cascade Baryons and Preliminary Cross-Sections for Ξ(1530) Using Data from the GlueX Experiment

The spectra of predicted particles from elementary quark models (CQMs) are expansive, accurate for the low-lying spectra, but incomplete. The GlueX experiment at Jefferson Lab is a vehicle to study medium energy photoproduction of hadronic states. The primary goal of the GlueX collaboration is to study Quantum Chromodynamics (QCD, also known as the strong nuclear force) and the nature of quark confinement. The GlueX collaboration uses a polarized photon beam incident on a liquid hydrogen target (LH 2 ) to investigate the aftermath of photon-proton interactions. The cascade baryons, denoted by Ξ, are defined by having two, second-generation, strange quarks with an additional first-generation light quark (u or d). Experimentally, few cascades have been discovered, which is the antithesis of what most models expect. The cascades have some favorable attributes but are difficult to detect because the production cross sections are small and direct production is unlikely. Fortunately, in the 12 GeV era of the GlueX experiment, there is sufficient energy, beam time and data analysis tools for the detection of excited cascade states and their properties. From the reaction γ p →Κ + Κ + Ξ - π 0 , the invariant mass spectra of Ξ - π 0 system was surveyed for new possible resonances. The invariant mass spectrum has a strong Ξ(1530) signal with other smaller resonances throughout the spectrum. Preliminary cross sections for the Ξ(1530) that was photoproduced from the proton are presented at energies never before explored. While the Ξ(1530) couples almost exclusively to the Ξπ channel, there is an easily identifiable Ξ(1690) signal decaying Ξπ. Through the use of a simultaneous fitting routing of the Ξ*- mass spectra, I was able to observe the Ξ(1690) decaying to the KΛ, as well as to the Ξ - π 0 branch. With additional statistics, a measurement of the branching ratio should be possible. Lastly, a partial wave analysis (PWA) was completed to verify that the total angular momentum of Ξ(1530) is J = 3/2 and consistent with having positive parity. Additionally, there is evidence of a potentially interesting feature slightly above the mass of the Ξ(1530) that should be more fully explored as new GlueX data becomes available.

Sumner, Brandon↗
NASA NTRS1986

Composition of comet Halley dust particles from Giotto observations

Mass spectra of cometary dust particles measured by the PIA dust particle analyzer aboard the Giotto spacecraft show some unexpected and striking features. First, small particles below 10 to the -14th g are much more abundant than anticipated by models. Second, most of the particles are rich in light elements such as H, C, N, and O, suggesting the validity of models that describe the cometary dust as including organic material. Third, the light elements specifically seem to have a low ratio of mass to volume. Three examples of original mass spectra showing typical compositions are given; these have been measured, and are compared with a computer-simulated mass spectrum.

Kissel, J.↗
DOE OSTI2024

TBS FROST Data from 2023 at SGP C1

The FROST provides chemical analysis of four time-resolved sorbent samples on a LECO GCxGC Bench Time of Flight Mass Spectrometer, using a Gerstel MPS Thermal Desorption System. Samples collected via FROST can be analyzed on one of two Sandia National Laboratories' instruments. One instrument will provide ultra-high mass spectrometer resolution (up to four decimal points or m/z data) and can be used for identification of true unknowns. Data can include suspected formulas of species not included in any current mass spectra database. This instrument also has a low limit of detection of known species (tens of femtogram range). The second instrument can provide an order of magnitude lower limits of detection (into the single-digit femtogram range) for known species currently in mass spectra databases. This system is also more resilient to environmental samples that contain higher levels of moisture.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

DEIMoS: An Open-Source Tool for Processing High-Dimensional Mass Spectrometry Data

We present DEIMoS: Data Extraction for Integrated Multidimensional Spectrometry, a Python application programming interface and command-line tool for high-dimensional mass spectrometry data analysis workflows, offering ease of development and access to efficient algorithmic implementations. Functionality includes feature detection, feature alignment, collision cross section calibration, isotope detection, and MS/MS spectral deconvolution, with the output comprising detected features aligned across study samples and characterized by mass, CCS, tandem mass spectra, and isotopic signature. Notably, DEIMoS operates on N-dimensional data, largely agnostic to acquisition instrumentation: algorithm implementations utilize all dimensions simultaneously to (i) offer greater separation between features, improving detection sensitivity, (ii) increase alignment/feature matching confidence among datasets, and (iii) mitigate convolution artifacts in tandem mass spectra. We demonstrate DEIMoS with LC-IMS-MS/MS data, demonstrating the advantages of a multidimensional approach in each data processing step.

Colby, Sean M↗
DOE OSTI2024

Chemical properties and single-particle mixing state of soot aerosol in Houston during the TRACER campaign

Abstract. A high-resolution soot particle aerosol mass spectrometer (SP-AMS) was used to selectively measure refractory black carbon (rBC) and its associated coating material using both the ensemble size-resolved mass spectral mode and the event trigger single particle (ETSP) mode in Houston, Texas, in summer 2022. This study was conducted as part of the Department of Energy Atmospheric Radiation Measurement (ARM) program's TRacking Aerosol Convection interactions ExpeRiment (TRACER) field campaign. The study revealed an average (±1σ) rBC concentration of 103 ± 176 ng m−3. Additionally, the coatings on the BC particles were primarily composed of organics (59 %; 219 ± 260 ng m−3) and sulfate (26 %; 94 ± 55 ng m−3). Positive matrix factorization (PMF) analysis of the ensemble mass spectra of BC-containing particles resolved four distinct types of soot aerosol, including an oxidized organic aerosol (OOABC,PMF) factor associated with processed primary organic aerosol, an inorganic sulfate factor (SO4,BC,PMF), an oxidized rBC factor (O-BCPMF), and a mixed mineral dust–biomass burning aerosol factor with significant contribution from potassium (K-BBBC,PMF). Additionally, K-means clustering analysis of the single-particle mass spectra identified eight different clusters, including soot particles enriched in hydrocarbon-like organic aerosol (HOABC,ETSP), sulfate (SO4,BC,ETSP), two types of rBC, OOA (OOABC,ETSP), chloride (ClBC,ETSP), and nitrate (NO3,BC,ETSP). The single-particle measurements demonstrate substantial variation in BC coating thickness with coating-to-rBC mass ratios ranging from 0.1 to 100. The mixing state index (χ), which denotes the degree of homogeneity of the soot aerosol, varied from 4 % to 94 % with a median of 40 %, indicating that the aerosol population lies in between internal and external mixing but has large temporal and source type variability. In addition, a significant fraction of BC-containing particles, a majority enriched with oxidized organics and sulfate, exhibit sufficiently high κ values and diameters conducive to activation as cloud nuclei under atmospherically relevant supersaturation conditions. This finding bears significance in comprehending the aging processes of rBC-containing particles and their activation into cloud droplets. Our analysis highlights the complex nature of soot aerosol and underscores the need to comprehend its variability across different environments for accurate assessment of climate change.

54 ENVIRONMENTAL SCIENCES↗