Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Mass Spectrometry”

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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Experimental and Computational Evaluation of Lipidomic In-Source Fragmentation as a Result of Postionization with Matrix-Assisted Laser Desorption/Ionization

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can provide spatially resolved molecular information about a sample. Recently, a postionization approach (MALDI-2) has been commercially integrated with MALDI-MSI, allowing for bettered sensitivity and consequent improved spatial resolution. While advantages of MALDI-2 have previously been established, we demonstrate here statistically increased in-source fragmentation (ISF) results from postionization with a commercial instrument. Via lipid standard analyses, known MALDI ISF pathways (e.g., loss of trimethylamine) were statistically increased in MALDI-2 compared to MALDI-1 (65–172% increase in fragmentation). Gas phase molecular modeling with density functional theory estimated that the most-weighted virtual orbitals to excite within lipids involve ester and phosphate bonds. Protonated lipid excitation energies are furthermore red-shifted compared to those of other adduct types [e.g., 254 nm for protonated PC(16:0/18:1)] and approach the MALDI-2 laser energy (266 nm). Analysis of rat brain homogenate detected statistically more positive-ion mode peaks with MALDI-2 (1090) than that with MALDI-1 (719), where Kernel density estimations showed that the majority of this enhancement occurs with low m/z ions (i.e., m/z 75–500). Taken together with the lipid standard data, these observations may indicate ISF due to postionization. Finally, while artifact contributions from matrix blanks were also noted, both experimental and computational data sets suggest that the overall extent of ISF is statistically increased in MALDI-2 compared to MALDI-1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Discovery of a Ferromagnetic Nickel Chalcogenide Nanocluster Ni 3 S 3 H(PEt 3 ) 5

Atomically precise ligated nanoclusters (NC) are promising cluster-based materials with novel molecular architectures and tunable magnetic properties. Herein, the synthesis and characterization of a nickel sulfide NC Ni 3 S 3 H(PEt 3 ) 5 (PEt 3 = triethylphosphine) with distinct magnetic properties are reported. Magnetization measurements reveal its magnetic moment of 1.5 µ B in the solid phase, consistent with the existence of one unpaired electron predicted by density functional theory (DFT) calculations. Additionally, experimental measurements indicate the presence of ferromagnetic ordering within each Ni 3 S 3 H(PEt 3 ) 5 NC and strong coercivity at temperatures below 20 K. Ion mobility-mass spectrometry is employed in conjunction with DFT calculations and collision cross-section simulations to investigate the structure of the isolated Ni 3 S 3 H(PEt 3 ) 5 . Theoretical studies show that [Ni 3 S 3 H(PEt 3 ) 5 ] + has a planar Ni 3 S 3 core where three Ni atoms are arranged in a triangle with three bridging S atoms residing in the same plane. This structure is preserved in both solution and solid phases, which is confirmed by spectroscopic studies of Ni 3 S 3 H(PEt 3 ) 5 . Additionally, DFT calculations indicate that all spins at the Ni sites are aligned parallel, confirming the presence of ferromagnetic coupling. Overall, this study provides key insights into the structure and magnetic properties of Ni 3 S 3 H(PEt 3 ) 5 , which will facilitate the design of new NC-based magnetic materials.

Nickel sulfide nanocluster↗
DOE OSTI2023

Surface Water Disinfection Byproducts and Organic Matter Characterization Data Associated with: “Disinfection byproducts formed during drinking water treatment reveal an export control point for dissolved organic matter in a subalpine headwater stream”

This dataset is associated with the publication “Disinfection byproducts formed during drinking water treatment reveal an export control point for dissolved organic matter in a subalpine headwater stream” published in Water Research X (Leonard et al. 2022; https://doi.org/10.1016/j.wroa.2022.100144). The associated study analyzed temporal trends from the Town of Crested Butte water treatment facility and synoptic sampling at Coal Creek in Crested Butte, Colorado, US. This work demonstrates how drinking water quality archives combined with synoptic sampling and targeted analyses can be used to identify and understand export control points for dissolved organic matter. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) metadata and international geo-sample number (IGSN) mapping file; (4) dissolved organic carbon (DOC), ultraviolet absorbance at 254 nanometers (UV254), total nitrogen (TN), and specific ultraviolet absorbance (SUVA) data; (5) disinfection bioproduct formation potential (DBP-FP) data; (6) readme; (7) methods codes; (8) water collection protocol; (9) folder of high resolution characterization of organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory); and (10) folder of excitation emissions matrix (EEM) spectra. The FTICR folder contains a file of DOC (measured as non-purgeable organic carbon; NPOC) used for FTICR sample preparation. The FTICR folder also contains three subfolders: one subfolder containing the raw .xml data files, one containing the processed data, and the other containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .dat, .R, .ref, or .xml

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A lipidomics platform to analyze the fatty acid compositions of non-polar and polar lipid molecular species from plant tissues: Examples from developing seeds and seedlings of pennycress (Thlaspi arvense)

The lipidome comprises the total content of molecular species of each lipid class, and is measured using the analytical techniques of lipidomics. Many liquid chromatography-mass spectrometry (LC-MS) methods have previously been described to characterize the lipidome. However, many lipidomic approaches may not fully uncover the subtleties of lipid molecular species, such as the full fatty acid (FA) composition of certain lipid classes. Here, we describe a stepwise targeted lipidomics approach to characterize the polar and non-polar lipid classes using complementary LC-MS methods. Our “polar” method measures 260 molecular species across 12 polar lipid classes, and is performed using hydrophilic interaction chromatography (HILIC) on a NH2 column to separate lipid classes by their headgroup. Our “non-polar” method measures 254 molecular species across three non-polar lipid classes, separating molecular species on their FA characteristics by reverse phase (RP) chromatography on a C30 column. Five different extraction methods were compared, with an MTBE-based extraction chosen for the final lipidomics workflow. A state-of-the-art strategy to determine and relatively quantify the FA composition of triacylglycerols is also described. This lipidomics workflow was applied to developing, mature, and germinated pennycress seeds/seedlings and found unexpected changes among several lipid molecular species. During development, diacylglycerols predominantly contained long chain length FAs, which contrasted with the very long chain FAs of triacylglycerols in mature seeds. Potential metabolic explanations are discussed. The lack of very long chain fatty acids in diacylglycerols of germinating seeds may indicate very long chain FAs, such as erucic acid, are preferentially channeled into beta-oxidation for energy production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Aggregation Methods for Quantifying PTM and Structural Changes in Bottom-Up Proteomics

Bottom-up proteomic workflows rely on sequential preprocessing steps, commonly including peptide-to-protein aggregation (“roll-up”), to enhance data reliability and interpretability. While roll-up is effective for protein-centered analyses, it may be suboptimal for applications focused on post-translational modifications (PTMs) or protein structural changes, such as limited proteolysis–mass spectrometry (LiP-MS). Here, we investigate how different roll-up strategies influence site-level quantification in PTM differential analysis. Moreover, we introduce a novel site-centric roll-up approach tailored for LiP-MS, which quantifies proteolytic fragments rather than solely tryptic peptides. We benchmark these methods through simulation studies, comparing their sensitivity and specificity in detecting structural and PTM-driven changes. We found that the median and mean roll-up methods outperform the sum method in both PTM and LiP proteomics, and site-level quantification in LiP outperforms peptide-level quantification. Our findings offer the first systematic, data-driven guidance for selecting roll-up techniques in site-level proteomic analyses, with implications for both PTM-focused and structural proteomics studies.

aggregation↗
DOE OSTI2021

Benzo[a]pyrene (BaP) metabolites predominant in human plasma following escalating oral micro-dosing with [ 14 C]-BaP

Benzo[a]pyrene (BaP) is formed by incomplete combustion of organic materials (petroleum, coal, tobacco, etc.). BaP is designated by the International Agency for Research on Cancer as a group 1 known human carcinogen; a classification supported by numerous studies in preclinical models and epidemiology studies of exposed populations. Risk assessment relies on toxicokinetic and cancer studies in rodents at doses 5–6 orders of magnitude greater than average human uptake. Using a dose–response design at environmentally relevant concentrations, this study follows uptake, metabolism, and elimination of [ 14 C]-BaP in human plasma by employing UPLC - accelerator mass spectrometry (UPLC-AMS). Volunteers were administered 25, 50, 100, and 250 ng (2.7–27 nCi) of [ 14 C]-BaP (with interceding minimum 3-week washout periods) with quantification of parent [ 14 C]-BaP and metabolites in plasma measured over 48 h. [ 14 C]-BaP median T max was 30 min with C max and area under the curve (AUC) approximating dose-dependency. Marked inter-individual variability in plasma pharmacokinetics following a 250 ng dose was seen with 7 volunteers as measured by the C max (8.99 ± 7.08 ng × mL -1 ) and AUC0-48hr (68.6 ± 64.0 fg × hr -1 × mL -1 ). Approximately 3–6% of the [ 14 C] recovered (AUC 0-48 hr ) was parent compound, demonstrating extensive metabolism following oral dosing. Metabolite profiles showed that, even at the earliest time-point (30 min), a substantial percentage of [ 14 C] in plasma was polar BaP metabolites. The best fit modeling approach identified non-compartmental apparent volume of distribution of BaP as significantly increasing as a function of dose (p = 0.004). Bay region tetrols and dihydrodiols predominated, suggesting not only was there extensive first pass metabolism but also potentially bioactivation. AMS enables the study of environmental carcinogens in humans with de minimus risk, allowing for important testing and validation of physiologically based pharmacokinetic models derived from animal data, risk assessment, and the interpretation of data from high-risk occupationally exposed populations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Open access repository-scale propagated nearest neighbor suspect spectral library for untargeted metabolomics

Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of MS/MS spectra originating from published untargeted metabolomics experiments. Entries in this library, or “suspects,” were derived from unannotated spectra that could be linked in a molecular network to an annotated spectrum. Annotations were propagated to unknowns based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimer’s brain phenotype. The nearest neighbor suspect spectral library is openly available for download or for data analysis through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Low-Temperature Non-Oxidative Coupling of Methane on Atomically Dispersed Titanium–Aluminum–Boron Nanopowder

Nonoxidative coupling of methane represents a long-standing challenge in heterogeneous catalysis, as it requires activation of the carbon–hydrogen (C–H) bond, controlled carbon–carbon (C–C) bond formation, and effective hydrogen management without relying on oxidants. Here, we report a low-temperature C–H activation and nonoxidative C–C coupling of methane over atomically dispersed titanium–aluminum–boron nanopowder (Ti–Al–B NP) utilizing a catalytic microreactor coupled to synchrotron single-photon photoionization reflectron time-of-flight mass spectrometry. The soft-ionization, in situ probing method detects the nascent reaction products and radical intermediates under operando conditions, including methyl radical, C2 hydrocarbons, and molecular hydrogen. Methane activation is initiated at 800 K, approximately 700 K below the gas-phase decomposition threshold, leading predominantly to ethylene formation with selectivity reaching up to 78% among the C–C coupled products. Electronic structure calculations on model Ti–Al–B clusters elucidate a cooperative catalytic mechanism in which titanium enables methane adsorption and C–H activation, boron acts as a reversible hydrogen reservoir, and aluminum stabilizes methylene intermediates, thereby facilitating selective C–C coupling and dehydrogenation. These findings establish a distinct catalyst architecture for nonoxidative methane coupling based on earth abundant elements alternative to expensive platinum and other noble metal-containing conventional catalysts and provide molecular-level design principles for controlling dehydrogenation and subsequent C–C bond formation in challenging light alkane conversions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows

Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carry out a community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluate the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observe that variability at the peptide level is predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappear at the protein group level. While differences are observed for predicted community composition, similar functional profiles are obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A variant of the MenB strain of Synechocystis sp. PCC 6803 disrupts a stress response pathway allowing DMPBQ to occupy the A 1 sites of photosystem I

Phylloquinone (PhQ) plays a unique role in photosynthesis as the A1A and A1B intermediates in light-driven electron transfer in Photosystem I (PSI). When PhQ biosynthesis is inhibited by deletion of the menB gene in the cyanobacterium Synechocystis sp. PCC 6803, previous studies have shown that plastoquinone-9 (PQ-9) occupies the A 1 sites. However, a recent cryo-electron microscopy structure of a strain of ΔmenB from the year 2023 revealed an unusual quinone in the A 1 sites with a benzoquinone headgroup similar to PQ-9 and a phytyl tail similar to PhQ. Here, we investigate its biosynthesis and binding properties. Mass spectrometry confirms that PSI from the 2023 ΔmenB strain contains 2,3-dimethyl-5-phytyl-1,4-benzoquinone (DMPBQ), while PSI from the original strain contains PQ-9. Whole genome sequencing reveals that a mutation in slr1737 (tocopherol cyclase) leads to the accumulation of DMPBQ, an intermediate in the tocopherol biosynthetic pathway. Transient optical and electron paramagnetic resonance spectroscopy studies show that when DMPBQ occupies the A 1 sites, it does not exchange with exogenously supplied PhQ in contrast to PQ-9, which exchanges readily. We propose that the slr1737 mutation in the 2023 ΔmenB strain is a likely candidate for the source of the phenotype. This new strain has sacrificed tocopherol synthesis, the absence of which is known to have no effect on growth under low stress conditions, resulting in incorporation of DMPBQ in the A 1 sites. The tighter binding and function of DMPBQ likely allow this ΔmenB strain to outcompete its peers under optimal growth conditions and thus dominate the population.

2,3-dimethyl-5-phytyl-1,4-benzoquinone↗
DOE OSTI2022

Abundance of Major Cell Wall Components in Natural Variants and Pedigrees of Populus trichocarpa

The rapid analysis of biopolymers including lignin and sugars in lignocellulosic biomass cell walls is essential for the analysis of the large sample populations needed for identifying heritable genetic variation in biomass feedstocks for biofuels and bioproducts. In this study, we reported the analysis of cell wall lignin content, syringyl/guaiacyl (S/G) ratio, as well as glucose and xylose content by high-throughput pyrolysis-molecular beam mass spectrometry (py-MBMS) for >3,600 samples derived from hundreds of accessions of Populus trichocarpa from natural populations, as well as pedigrees constructed from 14 parents (7 × 7). Partial Least Squares (PLS) regression models were built from the samples of known sugar composition previously determined by hydrolysis followed by nuclear magnetic resonance (NMR) analysis. Key spectral features positively correlated with glucose content consisted of m/z 126, 98, and 69, among others, deriving from pyrolyzates such as hydroxymethylfurfural, maltol, and other sugar-derived species. Xylose content positively correlated primarily with many lignin-derived ions and to a lesser degree with m/z 114, deriving from a lactone produced from xylose pyrolysis. Models were capable of predicting glucose and xylose contents with an average error of less than 4%, and accuracy was significantly improved over previously used methods. The differences in the models constructed from the two sample sets varied in training sample number, but the genetic and compositional uniformity of the pedigree set could be a potential driver in the slightly better performance of that model in comparison with the natural variants. Broad-sense heritability of glucose and xylose composition using these data was 0.32 and 0.34, respectively. In summary, we have demonstrated the use of a single high-throughput method to predict sugar and lignin composition in thousands of poplar samples to estimate the heritability and phenotypic plasticity of traits necessary to develop optimized feedstocks for bioenergy applications.

09 BIOMASS FUELS↗
DOE OSTI2024

Molecular shifts in dissolved organic matter along a burn severity continuum for common land cover types in the Pacific Northwest, USA

Increasing wildfire severity is of growing concern in the western United States, with consequences for the production, composition, and mobilization of dissolved organic matter (DOM) from terrestrial to aquatic systems. Our current understanding of wildfire impacted DOM (often termed pyrogenic DOM) composition is largely built from temperature-based studies that can be difficult to extrapolate to field conditions, which are often defined by ‘burn severity’, or the post-wildfire impact observed at a site. Thus, burn severity can encapsulate a broader range of fire and environmental conditions not exclusive to temperature. Biogeochemical studies that describe DOM along burn severity continuums remain limited but are needed to better link DOM composition with field conditions post-fire. Here, in this study, we addressed this need with an experimental open air burn simulation that generated chars from vegetation representative of major land cover types in the western United States. The chars were leached to simulate DOM mobilization potential. The DOM composition was characterized by ultra-high resolution mass spectrometry (HR-MS) and UV/VIS absorbance and fluorescence. Our results indicated that the shifts of DOM production and composition along a burn-severity gradient depends on the land cover type that was burned, with the degree of change dependent on the composition of the starting parent vegetation material. Fluorescence signatures indicated a strong convergence across land cover types to more aromatic DOM with increasing severity, while HR-MS indicated an increase in the production of aromatic nitrogen containing DOM with increasing severity. Results from this study enhance our ability to describe DOM composition in a framework that can be more directly related with field and remote-sensing based metrics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Information theory and machine learning illuminate large‐scale metabolomic responses of Brachypodium distachyon to environmental change

SUMMARY Plant responses to environmental change are mediated via changes in cellular metabolomes. However, <5% of signals obtained from liquid chromatography tandem mass spectrometry (LC‐MS/MS) can be identified, limiting our understanding of how metabolomes change under biotic/abiotic stress. To address this challenge, we performed untargeted LC‐MS/MS of leaves, roots, and other organs of Brachypodium distachyon (Poaceae) under 17 organ–condition combinations, including copper deficiency, heat stress, low phosphate, and arbuscular mycorrhizal symbiosis. We found that both leaf and root metabolomes were significantly affected by the growth medium. Leaf metabolomes were more diverse than root metabolomes, but the latter were more specialized and more responsive to environmental change. We found that 1 week of copper deficiency shielded the root, but not the leaf metabolome, from perturbation due to heat stress. Machine learning (ML)‐based analysis annotated approximately 81% of the fragmented peaks versus approximately 6% using spectral matches alone. We performed one of the most extensive validations of ML‐based peak annotations in plants using thousands of authentic standards, and analyzed approximately 37% of the annotated peaks based on these assessments. Analyzing responsiveness of each predicted metabolite class to environmental change revealed significant perturbations of glycerophospholipids, sphingolipids, and flavonoids. Co‐accumulation analysis further identified condition‐specific biomarkers. To make these results accessible, we developed a visualization platform on the Bio‐Analytic Resource for Plant Biology website ( https://bar.utoronto.ca/efp_brachypodium_metabolites/cgi‐bin/efpWeb.cgi ), where perturbed metabolite classes can be readily visualized. Overall, our study illustrates how emerging chemoinformatic methods can be applied to reveal novel insights into the dynamic plant metabolome and stress adaptation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Queen bees offload pesticide burden to eggs when social buffering is overwhelmed

Honey bee colonies pollinate about one-third of the world’s food crops, and their rapid decline directly threatens agricultural productivity and ecosystem stability. Understanding how colony-level social defenses influence pesticide fate and the circumstances under which they fail is therefore a crucial question in pollinator biology. We used biological accelerator mass spectrometry (BioAMS), a sensitive radiotracer technique, to track the movement of a model pesticide through a small honey bee colony under laboratory conditions. We tested the hypothesis that social buffering protects honey bees from toxic accumulation and that this protection can be overcome, leading to maternal offloading of the pesticide to developing eggs. Consistent with this hypothesis, our results identified three key mechanisms governing chemical movement within a social insect colony: (1) worker bees initially decrease dietary pesticide levels by 95% through diet filtering and deposition in honeycombs, though this declines to 86% by day 10; (2) queen bees maintain markedly lower pesticide levels than workers but, over time, they accumulate the pesticide in their ovaries and transfer it into developing eggs, revealing a previously undocumented protective mechanism in reproductive individuals; and (3) the presence of a queen bee shifts colony-wide chemical distribution by concentrating worker exposure and increasing pesticide deposition in wax. Our findings show that honey bee colonies function as integrated detoxification networks, in which chemical fate depends on complex social behaviors and caste-specific physiology. When social buffering is overwhelmed, reproductive queens may survive by transferring their chemical burden to their offspring.

Biological and medical sciences↗
DOE OSTI2025

Uranium particle age dating, aggregation, and model age best estimators

We present important aspects of uranium particle age dating by Large-Geometry Secondary Ion Mass Spectrometry (LG-SIMS) that can introduce bias and increase model age uncertainties, especially for small, young, and/or low-enriched particles. This metrology is important for applications related to International Nuclear Safeguards. We explore influential factors related to model age estimation, including the effects of evolving surface chemistry on inter-element measurements of particles (e.g., Th and U), detector background, and aggregation methods using simulated and actual particle samples. We introduce a new model age estimator, called “mid68”, that supplements 95% confidence intervals, providing a “best estimate” and uncertainty about the most likely age. The mid68 estimator can be calculated using the Feldman and Cousins method or Bayesian methods and provides a value with a symmetric uncertainty that can be used for calculations and approximate aggregation of processed model age values when the raw data and correction factors are not available. For particles yielding low 230 Th counts amidst nonzero detector background, their underlying model age probability distributions are asymmetric, so the mid68 estimator provides additional robust information regarding the underlying model age likelihood. This study provides a comprehensive and timely examination of critical aspects of uranium particle age dating as more laboratories establish particle chronometry capabilities.

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

Temporal Study 2021-2022: Sample-Based Surface Water Chemistry and Organic Matter Characterization across Watersheds in the Yakima River Basin, Washington, USA (v3)

This dataset supports a broader study examining the drivers of temporal variability in sediment respiration rates in the Yakima River Basin. The dataset provides geochemistry and organic matter characterization data generated from samples collected at weekly or bi-weekly intervals at six sites across the Yakima River Basin in Washington, USA. Related sensor data will be published separately and can be used to link sediment respiration rates to biogeochemical processing rates. The data package was originally published in November 2022. It was updated in November 2023 (v2; modified files) and April 2025 (new and modified files). See the change history section in readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved inorganic carbon (DIC), dissolved organic carbon (DOC; reported as non-purgeable organic carbon; NPOC), total nitrogen (TN), total suspended solids (TSS), and ions; (5) averaged values from water chemistry data; (6) surface water sampling protocol; (7) sensor protocol; (8) readme; (9) methods codes; (10) international generic sample number (IGSN) mapping file; and (11) folder of high resolution characterization of organic via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). This folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected our data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Modeling–Experiment–Theory Analysis of Reactions Initiated from Cl + Methyl Formate

Methyl formate (MF; CH 3 OCHO) is the smallest representative of esters, which are common components of biodiesel. The present study characterizes the thermal dissociation kinetics of the radicals formed by H atom abstraction from MF—CH 3 OCO and CH 2 OCHO—through a combination of modeling, experiment, and theory. For the experimental effort, excimer laser photolysis of Cl 2 was used as a source of Cl atoms to initiate reactions with MF in the gas phase. Time-resolved species profiles of MF, Cl 2 , HCl, CO 2 , CH 3 , CH 3 Cl, CH 2 O, and CH 2 ClOCHO were measured and quantified using photoionization mass spectrometry at temperatures of 400–750 K and 10 Torr. The experimental data were simulated using a kinetic model, which was informed by ab initio-based theoretical kinetics calculations and included chlorine chemistry and secondary reactions of radical decomposition products. Here, we calculated the rate coefficients for the H-abstraction reactions Cl + MF → HCl + CH 3 OCO (R1a) and Cl + MF → HCl + CH 2 OCHO (R1b): k 1a,theory = 6.71 × 10 –15 ·T 1.14 ·exp(—606/T) cm 3 /molecule·s; k 1b,theory = 4.67 × 10 –18 ·T 2.21 ·exp(—245/T) cm 3 /molecule·s over T = 200–2000 K. Electronic structure calculations indicate that the barriers to CH 3 OCO and CH 2 OCHO dissociation are 13.7 and 31.6 kcal/mol and lead to CH 3 + CO 2 (R3) and CH 2 O + HCO (R5), respectively. The master equation-based theoretical rate coefficients are k 3,theory (P = ∞) = 2.94 × 10 9 ·T 1.21 ·exp(—6209/T) s –1 and k 5,theory (P = ∞) = 8.45 × 10 8 ·T 1.39 ·exp(—15132/T) s –1 over T = 300–1500 K. The calculated branching fractions into R1a and R1b and the rate coefficient for R5 were validated by modeling of the experimental species time profiles and found to be in excellent agreement with theory. Additionally, we found that the bimolecular reactions CH 2 OCHO + Cl, CH 2 OCHO + Cl 2 , and CH 3 + Cl 2 were critical to accurately model the experimental data and constrain the kinetics of MF-radicals. Inclusion of the kinetic parameters determined in this study showed a significant impact on combustion simulations of larger methyl esters, which are considered as biodiesel surrogates.

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

Availability and reactivity of N 2 ( v ) for NH 3 synthesis by plasma catalysis

Production of vibrationally excited N 2 (N 2 (v)) in atmospheric pressure nonthermal plasma and loss of N 2 (v) by gas-phase reactions and reactions on catalytic surfaces are analyzed to examine the role of N 2 (v) in NH 3 formation by plasma catalysis. Vibrational state-to-state kinetic models complemented with molecular beam mass spectrometry (MBMS) measurements demonstrate that N 2 (v> 0) is produced with densities 100× greater than the density of N radicals by a radiofrequency atmospheric pressure plasma jet. The experimentally measured loss of N 2 (v) corresponds with a state-to-state kinetic model that describes loss of N 2 (v) by surface-mediated vibrational relaxation without consideration of reactions that convert N 2 (v) to NH 3 over the catalyst surface. Rate constants for vibrational relaxation of N 2 (v) on catalyst surfaces exceed upper bounds on proposed rate constants for NH 3 formation reactions from N 2 (v) over Fe when v < 9, Ni when v < 18, and Ag when v < 39, which indicates that only higher vibrational levels can possibly contribute to catalytic NH 3 formation faster than they undergo vibrational relaxation on the surface. Densities of N 2 (v> 8), vibrational levels that can possibly react over Fe to form NH 3 faster than they undergo vibrational relaxation, are less than or similar to N densities at the inlet of the catalyst bed and measured NH 3 formation for the investigated conditions in this work, while densities of N 2 (v> 17) and N 2 (v> 38) are orders of magnitude below the N density at the inlet of the catalyst bed and the measured NH 3 formation. The loss of N 2 (v) by vibrational relaxation on the surface limits the ability of N 2 (v) to contribute to catalytic NH 3 formation and explains why N 2 (v) does not produce NH 3 in quantities that are comparable to NH 3 formation from N even though N 2 (v > 0) is more abundantly produced by the plasma.

state-to-state kinetic modeling↗