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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Creation of an Acyltransferase Toolbox for Plant Biomass Engineering (Final Report)

The major goal of this project was to expand our understanding of acyl‐CoA ligases and BAHD acyltransferases and their utility in plant engineering. We combined bioinformatic analysis of genes and transcripts with functional fingerprinting of synthesized genes produced by JGI. Best candidates from this experimental pipeline were transferred into bioenergy plants to study their effects on lignin composition. We found combinations of ligase and transferase genes encoding enzymes with interesting catalytic specificities. Our work demonstrated the feasibility of use of acyl-CoA ligases and BAHD acyltransferases to alter the composition of plant cell walls without deleterious effects on the modified plant.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Understanding the optoelectronic properties of doped 2D organic-inorganic halide perovskite quantum wells: towards efficient ultrafast quantum well IR photodetectors

This project, titled “Understanding the optoelectronic properties of doped 2D organic-inorganic halide perovskite quantum wells: towards efficient quantum well IR photodetectors”, was funded by the U.S. Department of Energy to explore a new class of materials that could make future light-sensing technologies, such as infrared (IR) cameras and detectors more efficient, affordable, and widely available. The research focused on special layered materials called 2D halide perovskites, which are made up of alternating organic and inorganic layers only a few atoms thick. These materials can be tuned at the atomic level to absorb and emit light in precise ways, making them very attractive for use in optoelectronic devices. The main goal of the project was to understand how these perovskite materials absorb light and move electrical charges at very small scales. However, this is not an easy task. These materials often contain a mixture of different structures in the same film, and traditional tools like regular absorption or photoluminescence spectroscopy are not good at telling those structures apart. To solve this, the research team, led by Professor Luisa Whittaker-Brooks at the University of Utah developed a powerful method called electroabsorption spectroscopy. This technique uses electric fields to highlight the unique “fingerprints” of different excitons, which are tiny packets of energy formed when light hits the material. By using this method, the team could separate overlapping signals and learn exactly how the materials respond to light under different conditions, including changes in temperature, thickness, and chemical makeup.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Firmware Tampering Detection in Heavy-Duty Vehicles through J1939 CAN Analysis

Modern heavy-duty vehicles rely on complex networks of Electronic Control Units (ECUs) that communicate using the J1939 protocol. While this system makes it easier to update and configure vehicle components, it also opens the door to serious cybersecurity risks if not properly secured. This work investigates the potential for firmware tampering through the J1939 communication protocol, which enables ECU configuration and reprogramming over the Controller Area Network (CAN) bus. By monitoring CAN traffic during legitimate maintenance operations and reverse-engineering OEM diagnostic software, we identified common and proprietary J1939 message identifiers, authentication patterns, and vulnerabilities within Unified Diagnostic Services (UDS). These findings demonstrate that inadequate authentication mechanisms can allow malicious actors to alter ECU firmware or disable safety functions, posing severe operational and safety risks. Our analysis contributes to the development of vehicle intrusion detection systems capable of recognizing abnormal reprogramming activity and future firmware fingerprinting methods to verify software integrity across ECUs. This work highlights the importance of standardizing secure firmware authentication across manufacturers to strengthen cyber resilience in heavy-duty vehicle systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Metabolome patterns identify active dechlorination in bioaugmentation consortium SDC-9™

Ultra-high performance liquid chromatography–high-resolution mass spectrometry (UPHLC–HRMS) is used to discover and monitor single or sets of biomarkers informing about metabolic processes of interest. The technique can detect 1000’s of molecules (i.e., metabolites) in a single instrument run and provide a measurement of the global metabolome, which could be a fingerprint of activity. Despite the power of this approach, technical challenges have hindered the effective use of metabolomics to interrogate microbial communities implicated in the removal of priority contaminants. Herein, our efforts to circumvent these challenges and apply this emerging systems biology technique to microbiomes relevant for contaminant biodegradation will be discussed. Chlorinated ethenes impact many contaminated sites, and detoxification can be achieved by organohalide-respiring bacteria, a process currently assessed by quantitative gene-centric tools (e.g., quantitative PCR). This laboratory study monitored the metabolome of the SDC-9™ bioaugmentation consortium during cis-1,2-dichloroethene (cDCE) conversion to vinyl chloride (VC) and nontoxic ethene. Untargeted metabolomics using an UHPLC-Orbitrap mass spectrometer and performed on SDC-9™ cultures at different stages of the reductive dechlorination process detected ~10,000 spectral features per sample arising from water-soluble molecules with both known and unknown structures. Multivariate statistical techniques including partial least squares-discriminate analysis (PLSDA) identified patterns of measurable spectral features (peak patterns) that correlated with dechlorination (in)activity, and ANOVA analyses identified 18 potential biomarkers for this process. Statistical clustering of samples with these 18 features identified dechlorination activity more reliably than clustering of samples based only on chlorinated ethene concentration and Dhc 16S rRNA gene abundance data, highlighting the potential value of metabolomic workflows as an innovative site assessment and bioremediation monitoring tool.

environmental monitoring↗
DOE OSTI2021

Structural Polymorphism of Chitin and Chitosan in Fungal Cell Walls From Solid-State NMR and Principal Component Analysis

Chitin is a major carbohydrate component of the fungal cell wall and a promising target for novel antifungal agents. However, it is technically challenging to characterize the structure of this polymer in native cell walls. Here, we recorded and compared 13 C chemical shifts of chitin using isotopically enriched cells of six Aspergillus, Rhizopus, and Candida strains, with data interpretation assisted by principal component analysis (PCA) and linear discriminant analysis (LDA) methods. The structure of chitin is found to be intrinsically heterogeneous, with peak multiplicity detected in each sample and distinct fingerprints observed across fungal species. Fungal chitin exhibits partial similarity to the model structures of α- and γ-allomorphs; therefore, chitin structure is not significantly affected by interactions with other cell wall components. Addition of antifungal drugs and salts did not significantly perturb the chemical shifts, revealing the structural resistance of chitin to external stress. In addition, the structure of the deacetylated form, chitosan, was found to resemble a relaxed two-fold helix conformation. This study provides high-resolution information on the structure of chitin and chitosan in their cellular contexts. The method is applicable to the analysis of other complex carbohydrates and polymer composites.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

What Polarimetric Weather Radars Offer to Cloud Modelers: Forward Radar Operators and Microphysical/Thermodynamic Retrievals

The utilization of polarimetric weather radars for optimizing cloud models is a next frontier of research. It is widely understood that inadequacies in microphysical parameterization schemes in numerical weather prediction (NWP) models is a primary cause of forecast uncertainties. Due to its ability to distinguish between hydrometeors with different microphysical habits and to identify “polarimetric fingerprints” of various microphysical processes, polarimetric radar emerges as a primary source of needed information. There are two approaches to leverage this information for NWP models: (1) radar microphysical and thermodynamic retrievals and (2) forward radar operators for converting the model outputs into the fields of polarimetric radar variables. In this paper, we will provide an overview of both. Polarimetric measurements can be combined with cloud models of varying complexity, including ones with bulk and spectral bin microphysics, as well as simplified Lagrangian models focused on a particular microphysical process. Combining polarimetric measurements with cloud modeling can reveal the impact of important microphysical agents such as aerosols or supercooled cloud water invisible to the radar on cloud and precipitation formation. Some pertinent results obtained from models with spectral bin microphysics, including the Hebrew University cloud model (HUCM) and 1D models of melting hail and snow coupled with the NSSL forward radar operator, are illustrated in the paper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Iron Bonding with Light Elements: Implications for Planetary Cores Beyond the Binary System

Light element alloying in iron is required to explain density deficit and seismic wave velocities in Earth’s core. However, the light element composition of the Earth’s core seems hard to constrain as nearly all light element alloying would reduce the density and sound velocity (elastic moduli). The alloying light elements include oxidizing elements like oxygen and sulfur and reducing elements like hydrogen and carbon, yet their chemical effects in the alloy system are less discussed. Moreover, Fe-X-ray Absorption Near Edge Structure (Fe-XANES) fingerprints have been studied for silicate materials with ferrous and ferric ions, while not many X-ray absorption spectroscopy (XAS) studies have focused on iron alloys, especially at high pressures. To investigate the bonding nature of iron alloys in planetary interiors, we presented X-ray absorption spectroscopy of iron–nitrogen and iron–carbon alloys at high pressures up to 50 GPa. Together with existing literature on iron–carbon, –hydrogen alloys, we analyzed their edge positions and found no significant difference in the degree of oxidation among these alloys. Pressure effects on edge positions were also found negligible. Our theoretical simulation of the valence state of iron, alloyed with S, C, O, N, and P also showed nearly unchanged behavior under pressures up to 300 GPa. This finding indicates that the high pressure bonding of iron alloyed with light elements closely resembles bonding at the ambient conditions. We suggest that the chemical properties of light elements constrain which ones can coexist within iron alloys.

Advanced Photon Source↗
DOE OSTI2026

Transient Catalytic Reaction Analysis Through Signal Defragmentation

The Temporal Analysis of Products (TAP) pulse response technique provides valuable insights into catalytic function and reaction kinetics. However, complex fragmentation patterns in the TAP mass spectrometry signals can complicate precise quantification, particularly when analyzing transient gas flux data typical of TAP experiments. This work demonstrates a standard defragmentation method that deconvolves transient TAP signals while maintaining the temporal resolution of the experiment. First, the integrals of calibration gas fluxes are used to determine the fingerprint fragmentation pattern and construct a fragmentation matrix. This matrix is then used to defragment experimental flux data at each recorded time point via a non-negative least squares regression. The effectiveness of this method is demonstrated using virtual data and control experiments with a TAP reactor system. The defragmentation is then applied to the more complex propane dehydrogenation reaction on a chromia/alumina catalyst, which can contain up to ten significant gas species in the reactor outlet. Initial propane pulsing reveals an induction period during which propane is fully oxidized to CO2, followed by partial reduction to CO. Afterwards, there is a transition in chemistries towards coking and propylene production. Our example illustrates a practical method for the accurate determination of the time-dependent reactant/product concentrations and rates for a thorough analysis of the propane dehydrogenation kinetics. This approach can be broadly applied to any transient mass spectrometry experiment for a better understanding of catalyst-reaction dynamics.

36 - MATERIALS SCIENCE↗
DOE OSTI2023

Bovine Rectoanal Junction In Vitro Organ Culture Model System to Study Shiga Toxin-Producing Escherichia coli Adherence

Studies evaluating the interactions between Shiga toxin-producing Escherichia coli O157:H7 (O157) and the bovine recto–anal junction (RAJ) have been limited to either in vitro analyses of bacteria, cells, or nucleic acids at the RAJ, providing limited information. Alternatively, expensive in vivo studies in animals have been conducted. Therefore, our objective was to develop a comprehensive in vitro organ culture system of the RAJ (RAJ-IVOC) that accurately represents all cell types present in the RAJ. This system would enable studies that yield results similar to those observed in vivo. Pieces of RAJ tissue, obtained from unrelated cattle necropsies, were assembled and subjected to various tests in order to determine the optimal conditions for assaying bacterial adherence in a viable IVOC. O157 strain EDL933 and E. coli K12 with known adherence differences were used to standardize the RAJ-IVOC adherence assay. Tissue integrity was assessed using cell viability, structural cell markers, and histopathology, while the adherence of bacteria was evaluated via microscopy and culture methods. DNA fingerprinting verified the recovered bacteria against the inoculum. When the RAJ-IVOC was assembled in Dulbecco’s Modified Eagle Medium, maintained at a temperature of 39 °C with 5% CO 2 and gentle shaking for a duration of 3–4 h, it successfully preserved tissue integrity and reproduced the expected adherence phenotype of the bacteria being tested. The RAJ-IVOC model system provides a convenient method to pre-screen multiple bacteria-RAJ interactions prior to in vivo experiments, thereby reducing animal usage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Characterization of Levan Fructan Produced by a Gluconobacter japonicus Strain Isolated from a Sugarcane Processing Facility

During raw sugarcane processing, a significant portion of lost sucrose is attributable to microbial degradation. Sucrose consumption by many bacteria is also linked to the production of exopolysaccharides (EPS) such as dextrans and fructans. These resulting EPS cause operational challenges during raw sugar manufacturing. Here, we report the characterization of EPS from a fructan-forming Gluconobacter japonicus bacterium that we previously isolated from a Louisiana sugarcane factory. The genome sequencing revealed the presence of two encoded levansucrase genes, lsrA and lsrB. One levansucrase, LsrB, was detected in the secreted protein fraction of G. japonicus LASM12 by QTOF LC-MS. The spotting assays indicated that G. japonicus produces EPS using sucrose and raffinose as substrates. The G. japonicus EPS correlated with levan fructan commercial standards by 1H-NMR, and with the characteristic carbohydrate fingerprint region for FTIR spectra, confirming that the G. japonicus EPS is levan fructan. The glycosyl composition and glycosyl linkage analysis revealed a linear β-2,6-fructofuranosyl polysaccharide with occasional (5.7%) β-2,1-fructofuranosyl branches. The gel permeation chromatography of the levan fructan EPS showed two main peaks at 4.5 kDa and 8 kDa and a very minor peak at 500 kDa. G. japonicus was identified as a producer of levan fructan. These findings will be useful for future studies aimed at evaluating the impact of levan fructans on sugar crop processing, which have been historically underestimated in industry.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

HPTLC Analysis and Chemical Composition of Selected Melaleuca Essential Oils

Tea tree oil (TTO) is a volatile essential oil obtained by distillation, mainly from the Australian native plant Melaleuca alternifolia (Maiden & Betche) Cheel (Myrtaceae). In this study, a comparative analysis of the chemical constituents of seven tea tree oils (M. alternifolia) and four other Melaleuca spp. oils (M. cajuputi, (M Ca ), two chemotypes of M. quinquenervia, (M Ne and M Ni ), and M. ericifolia (M Ro )) was carried out using gas chromatography–mass spectrometry (GC-MS) and high-performance thin-layer chromatography (HPTLC). Among the seven TTOs, terpinen-4-ol (37.66–44.28%), γ-terpinene (16.42–20.75%), α-terpinene (3.47–12.62%), α-terpineol (3.11–4.66%), and terpinolene (2.75–4.19%) were the most abundant compounds. On the other hand, the most abundant compounds of the other Melaleuca oils varied, such as 1,8-cineole (64.63%) in M Ca oil, (E)-nerolidol (48.40%) and linalool (33.30%) in M Ne oil, 1,8-cineole (52.20%) in M Ni oil, and linalool (38.19%) and 1,8-cineole (27.57%) in M Ro oil. HPTLC fingerprinting of Melaleuca oils enabled the discrimination of TTO oils from other Melaleuca spp. oils. Variation was observed in the profile of the R f values among EOs. The present study shows that HPTLC is one of the best ways to identify and evaluate the quality control in authenticating TTOs, other Melaleuca EOs, or EOs from other species within the Myrtaceae.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Optimization of Molecular Methods for Detecting Duckweed-Associated Bacteria

The bacterial colonization dynamics of plants can differ between phylogenetically similar bacterial strains and in the context of complex bacterial communities. Quantitative methods that can resolve closely related bacteria within complex communities can lead to a better understanding of plant–microbe interactions. However, current methods often lack the specificity to differentiate phylogenetically similar bacterial strains. In this study, we describe molecular strategies to study duckweed–associated bacteria. We first systematically optimized a bead-beating protocol to co-isolate nucleic acids simultaneously from duckweed and bacteria. We then developed a generic fingerprinting assay to detect bacteria present in duckweed samples. To detect specific duckweed–bacterium associations, we developed a genomics-based computational pipeline to generate bacterial strain-specific primers. These strain-specific primers differentiated bacterial strains from the same genus and enabled the detection of specific duckweed–bacterium associations present in a community context. Moreover, we used these strain-specific primers to quantify the bacterial colonization of duckweed by normalization to a plant reference gene and revealed differences in colonization levels between strains from the same genus. Lastly, confocal microscopy of inoculated duckweed further supported our PCR results and showed bacterial colonization of the duckweed root–frond interface and root interior. The molecular methods introduced in this work should enable the tracking and quantification of specific plant-microbe associations within plant-microbial communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Tropical Red Macroalgae Cultivation with a Focus on Compositional Analysis

To create carbon efficient sources of bioenergy feedstocks and feedstuff for aquaculture and terrestrial livestock, it is critical to develop and commercialize the most efficient seaweed cultivation approach with a sustainable nutrient input supply. Here, we present data for a novel, onshore tropical macroalgae cultivation system, based on influent deep seawater as the nutrient and carbon sources. Two red algal species were selected, Agardhiella subulata and Halymenia hawaiiana, as the basis for growth optimization. Highest productivity in small-scale cultivation was demonstrated with A. subulata in the 10% deep seawater (64.7 µg N L−1) treatment, growing at up to 26% specific growth rate day−1 with highest yields observed at 247.5 g m−2 day−1 fresh weight. The highest yields for H. hawaiiana were measured with the addition of 10% deep seawater up to 8.8% specific growth rate day−1 and yields at 63.3 g fresh weight m−2 day−1 equivalent. Biomass should be culled weekly or biweekly to avoid density limitations, which likely contributed to a decrease in SGR over time. With a measured 30–40% carbon content of the ash-free dry weight (20–30% of the dry weight) biomass, this translates to an almost 1:1 CO2 capture to biomass ratio. The compositional fingerprint of the high carbohydrate content of both Agardhiella and Halymenia makes for an attractive feedstock for downstream biorefinery applications. By focusing on scaling and optimizing seaweed farming technologies for large-scale onshore farms, the opportunities for yield potential, adaptability to cultivation conditions, and meeting global sustainability goals through novel, carbon-negative biomass sources such as seaweed can be realized.

09 BIOMASS FUELS↗
DOE OSTI2020

Gamma Rays from Kilonova: A Potential Probe of r-process Nucleosynthesis

The mergers of compact binaries with at least one neutron star component are the potential leading sites of the production and ejection of r-process elements. Discoveries of galactic binary pulsars, short gamma-ray bursts, and gravitational-wave detections have all been constraining the rate of these events, while the gravitational wave plus broadband electromagnetic coverage of binary neutron star merger (GW170817) has also placed constraints on the properties (mass and composition) of the merger ejecta. But uncertainties and ambiguities in modeling the optical and infrared emission make it difficult to definitively measure the distribution of heavy isotopes in these mergers. In contrast, gamma rays emitted in the decay of these neutron-rich ejecta may provide a more direct measurement of the yields. We calculate the gamma production in remnants of neutron star mergers, considering two epochs: a kilonova epoch, lasting about two weeks, and a much later epoch of tens and hundreds of thousands of years after the merger. For the kilonova epoch, when the expanding ejecta is still only partially transparent to gamma radiation, we use 3D radiative transport simulations to produce the spectra. Futhermore, we show that the gamma-ray spectra associated with beta- and alpha-decay provide a fingerprint of the ejecta properties and, for a sufficiently nearby remnant, may be detectable, even for old remnants. We compare our gamma spectra with the potential detection limits of next generation detectors, including the Lunar Occultation Explorer (LOX), the All-sky Medium Energy Gamma-ray Observatory (AMEGO), and the Compton Spectrometer and Imager (COSI). We show that fission models can be discriminated via the presence of short-lived fission fragments in the remnant spectra.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Neutrino-driven Outflows and the Elemental Abundance Patterns of Very Metal-poor Stars

Abstract The elemental abundances between strontium and silver ( Z = 38–47) observed in the atmospheres of very metal-poor stars in the Galaxy may contain the fingerprint of the weak r -process and ν p -process occurring in early core-collapse supernovae explosions. In this work, we combine various astrophysical conditions based on a steady-state model to cover the richness of the supernova ejecta in terms of entropy, expansion timescale, and electron fraction. The calculated abundances based on different combinations of conditions are compared with stellar observations, with the aim of constraining supernova ejecta conditions. We find that some conditions of the neutrino-driven outflows consistently reproduce the observed abundances of our sample. In addition, from the successful combinations, the neutron-rich trajectories better reproduce the observed abundances of Sr–Zr ( Z = 38–40), while the proton-rich ones, Mo–Pd ( Z = 42–47).

Astronomy & Astrophysics↗
DOE OSTI2022

Evaluating cloud liquid detection against Cloudnet using cloud radar Doppler spectra in a pre-trained artificial neural network

Detection of liquid-containing cloud layers in thick mixed-phase clouds or multi-layer cloud situations from ground-based remote-sensing instruments still poses observational challenges, yet improvements are crucial since the existence of multi-layer liquid layers in mixed-phase cloud situations influences cloud radiative effects, cloud lifetime, and precipitation formation processes. Hydrometeor target classifications such as from Cloudnet that require a lidar signal for the classification of liquid are limited to the maximum height of lidar signal penetration and thus often lead to underestimations of liquid-containing cloud layers. Here we evaluate the Cloudnet liquid detection against the approach of Luke et al. (2010) which extracts morphological features in cloud-penetrating cloud radar Doppler spectra measurements in an artificial neural network (ANN) approach to classify liquid beyond full lidar signal attenuation based on the simulation of the two lidar parameters particle backscatter coefficient and particle depolarization ratio. We show that the ANN of Luke et al. (2010) which was trained under Arctic conditions can successfully be applied to observations at the mid-latitudes obtained during the 7-week-long ACCEPT field experiment in Cabauw, the Netherlands, in 2014. In a sensitivity study covering the whole duration of the ACCEPT campaign, different liquid-detection thresholds for ANN-predicted lidar variables are applied and evaluated against the Cloudnet target classification. Independent validation of the liquid mask from the standard Cloudnet target classification against the ANN-based technique is realized by comparisons to observations of microwave radiometer liquid-water path, ceilometer liquid-layer base altitude, and radiosonde relative humidity. In addition, a case-study comparison against the cloud feature mask detected by the space-borne lidar aboard the CALIPSO satellite is presented. Three conclusions were drawn from the investigation. First, it was found that the threshold selection criteria of liquid-related lidar backscatter and depolarization alone control the liquid detection considerably. Second, all threshold values used in the ANN framework were found to outperform the Cloudnet target classification for deep or multi-layer cloud situations where the lidar signal is fully attenuated within low liquid layers and the cloud radar is able to detect the microphysical fingerprint of liquid in higher cloud layers. Third, if lidar data are available, Cloudnet is at least as good as the ANN. The times when Cloudnet outperforms the ANN in liquid detections are often associated with situations where cloud dynamics smear the imprint of cloud microphysics on the radar Doppler spectra.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Enhancing characterization of organic nitrogen components in aerosols and droplets using high-resolution aerosol mass spectrometry

Abstract. This study aims to enhance the understanding and application of the Aerodyne high-resolution aerosol mass spectrometer (HR-AMS) for the comprehensive characterization of organic nitrogen (ON) compounds in aerosol particles and atmospheric droplets. To achieve this goal, we analyzed 75 N-containing organic compounds, representing a diverse range of ambient non-organonitrate ON (NOON) types, including amines, amides, amino acids, N heterocycles, protein, and humic acids. Our results show that NOON compounds can produce significant levels of NHx+ and NOx+ ion fragments, which are typically recognized as ions representative of inorganic nitrogen species. We also identified the presence of CH2N+ at m/z = 28.0187, an ion fragment rarely quantified in ambient datasets due to substantial interference from N2+. As a result, the utilization of an updated calibration factor of 0.79 is necessary for accurate NOON quantification via the HR-AMS. We also assessed the relative ionization efficiencies (RIEs) for various NOON species and found that the average RIE for NOON compounds (1.52 ± 0.58) aligns with the commonly used default value of 1.40 for organic aerosol. Moreover, through a careful examination of the HR-AMS mass spectral features of various NOON types, we propose fingerprint ion series that can aid the NOON speciation analysis. For instance, the presence of CnH2n+2N+ ions is closely linked with amines, with CH4N+ indicating primary amines, C2H6N+ suggesting secondary amines, and C3H8N+ representing tertiary amines. CnH2nNO+ ions (especially for n values of 1–4) are very likely derived from amides. The co-existence of three ions, C2H4NO2+, C2H3NO+, and CH4NO+, serves as an indicator for the presence of amino acids. Additionally, the presence of CxHyN2+ ions indicates the occurrence of 2N-heterocyclic compounds. Notably, an elevated abundance of NH4+ is a distinct signature for amines and amino acids, as inorganic ammonium salts produce only negligible amounts of NH4+ in the HR-AMS. Finally, we quantified the NOON contents in submicron particles (PM1) and fog water in Fresno, California, and PM1 in New York City (NYC). Our results revealed the substantial presence of amino compounds in both Fresno and NYC aerosols, whereas concurrently collected fog water in Fresno contained a broader range of NOON species, including N-containing aromatic heterocycle (e.g., imidazoles) and amides. These findings highlight the significant potential of employing the widespread HR-AMS measurements of ambient aerosols and droplets to enhance our understanding of the sources, transformation processes, and environmental impacts associated with NOON compounds in the atmosphere.

Ge, Xinlei (ORCID:0000000195316478)↗
DOE OSTI2024

Enhancing characterization of organic nitrogen components in aerosols and droplets using high-resolution aerosol mass spectrometry

This study aims to enhance the understanding and application of the Aerodyne high-resolution aerosol mass spectrometer (HR-AMS) for comprehensive characterization of organic nitrogen (ON) compounds in aerosol particles and atmospheric droplets. To achieve this, we analyzed seventy-five N-containing organic compounds, representing a diverse range of ambient ON types, including amines, amides, amino acids, N-heterocycles, protein, and humic acids. Our results show that ON compounds can produce significant levels of NH x + and NO x + ion fragments, which are typically recognized as ions representative of inorganic nitrogen species. We also discovered the presence of CH 2 N + at m/z = 28.0187, an ion fragment that is rarely quantified in ambient datasets due to substantial interference from air-related N 2 + . As a result, we determined that an updated calibration factor of 0.79 is necessary to accurately quantify ON content using aerosol mass spectrometry. We also assessed the relative ionization efficiencies (RIEs) for different ON species and found that the average RIE of ON compounds (1.52 ± 0.58) aligns with the commonly used default value of 1.40 for organic aerosol (OA). Moreover, through a careful examination of the HR-AMS mass spectral features of various ON types, we propose fingerprint ion series that can aid the ON speciation analysis. The presence of C n H 2n+2 N + ions is closely linked with amines, with CH 4 N + indicating primary amines, C 2 H 6 N + suggesting secondary amines, and C 3 H 8 N + representing tertiary amines. C n H 2n NO + ions (especially for n values of 1–4) are very likely derived from amides. The co-existence of three ions, C 2 H 4 NO 2 + , C 2 H 3 NO + , and CH 4 NO + , serves as an indicator for the presence of amino acids. Additionally, the presence of C x H y N 2 + ions indicates the occurrence of 2N-heterocyclic compounds. Notably, an elevated abundance of NH 4 + is a distinct signature for amines and amino acids, as inorganic ammonium salts produce only negligible amounts of NH 4 + in HR-AMS. Finally, we quantified the ON contents in submicron particles (PM 1 ) and fog waters in Fresno, California and PM 1 in New York City (NYC). Our results revealed the substantial presence of amino compounds in both Fresno and NYC aerosols, whereas concurrently collected fog waters contained a broader range of ON species, including N-containing aromatic heterocycle (e.g., imidazoles) and amides. These findings highlight the significant potential of employing the widespread HR-AMS measurements of ambient aerosols and droplets to enhance our understanding of the sources, transformation processes, and environmental impacts associated with ON compounds in the atmosphere.

54 ENVIRONMENTAL SCIENCES↗