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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
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 OSTI2016

Rapid sample classification using an open port sampling interface coupled with liquid introduction atmospheric pressure ionization mass spectrometry

An “Open Access”-like mass spectrometric platform to fully utilize the simplicity of the manual open port sampling interface for rapid characterization of unprocessed samples by liquid introduction atmospheric pressure ionization mass spectrometry has been lacking. The in-house developed integrated software with a simple, small and relatively low-cost mass spectrometry system introduced here fills this void. Software was developed to operate the mass spectrometer, to collect and process mass spectrometric data files, to build a database and to classify samples using such a database. These tasks were accomplished via the vendorprovided software libraries. Sample classification based on spectral comparison utilized the spectral contrast angle method. As a result, using the developed software platform near real-time sample classification is exemplified using a series of commercially available blue ink rollerball pens and vegetable oils. In the case of the inks, full scan positive and negative ion ESI mass spectra were both used for database generation and sample classification. For the vegetable oils, full scan positive ion mode APCI mass spectra were recorded. The overall accuracy of the employed spectral contrast angle statistical model was 95.3% and 98% in case of the inks and oils, respectively, using leave-one-out cross-validation. In conclusion, this work illustrates that an open port sampling interface/mass spectrometer combination, with appropriate instrument control and data processing software, is a viable direct liquid extraction sampling and analysis system suitable for the non-expert user and near real-time sample classification via database matching.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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 OSTI2019

UV–Vis Photodissociation Action Spectroscopy on Thermo LTQ-XL ETD and Bruker amaZon Ion Trap Mass Spectrometers: a Practical Guide

We report automated procedures for multiple tandem mass spectra acquisition allowing UV–Vis photodissociation action spectroscopy measurements of ions and radicals. The procedures were developed for two commercial ion trap mass spectrometers and applied to collision-induced and electron–transfer dissociation tandem mass spectrometry modes of ion generation. .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Search for dark matter and supersymmetry in the vector boson fusion topology in proton-proton collisions at CMS

A search for pair production of dark matter candidates and supersymmetry (SUSY) production with two jets in vector-boson fusion (VBF) topology is presented using data collected by the Compact Muon Solenoid (CMS) detector in proton-proton collisions at the Large Hadron Collider (LHC). Final states with no leptons are expected in pair production of dark matter particles or scalar quarks in SUSY compressed mass-spectra scenarios. Final states with low-energy leptons are expected in the production of charginos and neutralinos in SUSY compressed mass-spectra scenarios. Results for both zero and two lepton final states at 8 TeV are presented with brief prospects at 13 TeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
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 OSTI2017

Improved identification of primary biological aerosol particles using single-particle mass spectrometry

Measurements of primary biological aerosol particles (PBAP), especially at altitudes relevant to cloud formation, are scarce. Single-particle mass spectrometry (SPMS) has been used to probe aerosol chemical composition from ground and aircraft for over 20 years. Here we develop a method for identifying bioaerosols (PBAP and particles containing fragments of PBAP as part of an internal mixture) using SPMS. We show that identification of bioaerosol using SPMS is complicated because phosphorus-bearing mineral dust and phosphorus-rich combustion by-products such as fly ash produce mass spectra with peaks similar to those typically used as markers for bioaerosol. We have developed a methodology to differentiate and identify bioaerosol using machine learning statistical techniques applied to mass spectra of known particle types. This improved method provides far fewer false positives compared to approaches reported in the literature. The new method was then applied to two sets of ambient data collected at Storm Peak Laboratory and a forested site in Central Valley, California to show that 0.04–2 % of particles in the 200–3000 nm aerodynamic diameter range were identified as bioaerosol. In addition, 36–56 % of particles identified as biological also contained spectral features consistent with mineral dust, suggesting internal dust–biological mixtures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Formation of Carbon Dioxide Attached Fragment Ions in the Fragmentation of Deprotonated Tolfenpyrad and Tebufenpyrad

The in-source collision-induced dissociation (CID) and MS/MS mass spectra of deprotonated tolfenpyrad and tebufenpyrad both showed an unusual fragment ion at m/z 187, but its fragmentation pattern and structure could not be explained by logical neutral losses. Accurate mass measurement indicated that the mass difference between this fragment ion and the dominant fragment ion at m/z 143 equaled to a carbon dioxide (CO{sub 2}) molecule. The isolation of the fragment ion m/z 143 in the mass analyzer could spontaneously give rise to the ion m/z 187. The Gibbs free energy of carbon dioxide addition to deprotonated pyrazole ion was significantly negative from the computational results. According to these results, we derived a proposal for the formation and structure of the ion m/z 187, which was an attachment of molecular carbon dioxide to the fragment ion m/z 143 to produce a carboxylate anion. The trace carbon dioxide was speculated to be derived from the residual atmosphere or collision gas in the instrument. This study is valuable for the qualitative and quantitative mass spectrometry analysis of pesticides containing the pyrazole functional group. .

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

Clusters of Monoisotopic Elements for Calibration in (TOF) Mass Spectrometry

Precise calibration in TOF MS requires suitable and reliable standards, which are not always available for high masses. We evaluated inorganic clusters of the monoisotopic elements gold and phosphorus (Au{sub n}{sup +}/Au{sub n}{sup -} and P{sub n}{sup +}/P{sub n}{sup -}) as an alternative to peptides or proteins for the external and internal calibration of mass spectra in various experimental and instrumental scenarios. Monoisotopic gold or phosphorus clusters can be easily generated in situ from suitable precursors by laser desorption/ionization (LDI) or matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). Their use offers numerous advantages, including simplicity of preparation, biological inertness, and exact mass determination even at lower mass resolution. We used citrate-stabilized gold nanoparticles to generate gold calibration clusters, and red phosphorus powder to generate phosphorus clusters. Both elements can be added to samples to perform internal calibration up to mass-to-charge (m/z) 10–15,000 without significantly interfering with the analyte. We demonstrated the use of the gold and phosphorous clusters in the MS analysis of complex biological samples, including microbial standards and total extracts of mouse embryonic fibroblasts. We believe that clusters of monoisotopic elements could be used as generally applicable calibrants for complex biological samples. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
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 OSTI2018

Multivariate Analysis of MALDI Imaging Mass Spectrometry Data of Mixtures of Single Pollen Grains

Mixtures of pollen grains of three different species (Corylus avellana, Alnus cordata, and Pinus sylvestris) were investigated by matrix-assisted laser desorption/ionization time-of-flight imaging mass spectrometry (MALDI-TOF imaging MS). The amount of pollen grains was reduced stepwise from > 10 to single pollen grains. For sample pretreatment, we modified a previously applied approach, where any additional extraction steps were omitted. Our results show that characteristic pollen MALDI mass spectra can be obtained from a single pollen grain, which is the prerequisite for a reliable pollen classification in practical applications. MALDI imaging of laterally resolved pollen grains provides additional information by reducing the complexity of the MS spectra of mixtures, where frequently peak discrimination is observed. Combined with multivariate statistical analyses, such as principal component analysis (PCA), our approach offers the chance for a fast and reliable identification of individual pollen grains by mass spectrometry. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗