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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
DOE OSTI2025

The role of the droplet interface in controlling the multiphase oxidation of thiosulfate by ozone

Predicting reaction kinetics in aqueous microdroplets, including aerosols and cloud droplets, is challenging due to the probability that the underlying reaction mechanism can occur both at the surface and in the interior of the droplet. Additionally, few studies directly measure the surface activities of doubly charged anions, despite their prevalence in the atmosphere. Here, deep-UV second harmonic generation spectroscopy is used to probe surface affinities of the doubly charged anions thiosulfate, sulfate, and sulfite, key species in the thiosulfate ozonation reaction mechanism. Thiosulfate has an appreciable surface affinity with a measured Gibbs free energy of adsorption of -7.3 ± 2.5 kJ mol -1 in neutral solution, while sulfate and sulfite exhibit negligible surface propensity. The Gibbs free energy is combined with data from liquid flat jet ambient pressure X-ray photoelectron spectroscopy to constrain the concentration of thiosulfate at the surface in our model. Stochastic kinetic simulations leveraging these novel measurements show that the primary reaction between thiosulfate and ozone occurs at the interface and in the bulk, with the contribution of the interface decreasing from ~65% at pH 5 to ~45% at pH 13. Additionally, sulfate, the major product of thiosulfate ozonation and an important species in atmospheric processes, can be produced by two different pathways at pH 5, one with a contribution from the interface of >70% and the other occurring predominantly in the bulk (>98%). The observations in this work have implications for mining wastewater remediation, atmospheric chemistry, and understanding other complex reaction mechanisms in multiphase environments. Future interfacial or microdroplet/aerosol chemistry studies should carefully consider the role of both surface and bulk chemistry.

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

Solvent-dependent complex reaction pathways of bromoform revealed by time-resolved X-ray solution scattering and X-ray transient absorption spectroscopy

The photochemical reaction pathways of CHBr3 in solution were unveiled using two complementary X-ray techniques, time-resolved X-ray solution scattering (TRXSS) and X-ray transient absorption spectroscopy, in a wide temporal range from 100 ps to tens of microseconds. By performing comparative measurements in protic (methanol) and aprotic (methylcyclohexane) solvents, we found that the reaction pathways depend significantly on the solvent properties. In methanol, the major photoproducts are CH3OCHBr2 and HBr generated by rapid solvolysis of iso-CHBr2-Br, an isomer of CHBr3. In contrast, in methylcyclohexane, iso-CHBr2-Br returns to CHBr3 without solvolysis. In both solvents, the formation of CHBr2 and Br is a competing reaction channel. From the structural analysis of TRXSS data, we determined the structures of key intermediate species, CH3OCHBr2 and iso-CHBr2-Br in methanol and methylcyclohexane, respectively, which are consistent with the structures from density functional theory calculations.

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

Enthalpies of formation for Criegee intermediates: A correlation energy convergence study

Criegee intermediates, formed from the ozonolysis of alkenes, are known to have a role in atmospheric chemistry, including the modulation of the oxidizing capacity of the troposphere. Although studies have been conducted since their discovery, the synthesis of these species in the laboratory has ushered in a new wave of investigations of these structures, both theoretically and experimentally. In some of these theoretical studies, high-order corrections for correlation energy are included to account for the mid multi-reference character found in these systems. Many of these studies include a focus on kinetics; therefore, the calculated energies should be accurate (<1 kcal/mol in error). In this research, we compute the enthalpies of formation for a small set of Criegee intermediates, including higher-order coupled cluster corrections for correlation energy up to coupled cluster with perturbative quintuple excitations. The enthalpies of formation for formaldehyde oxide, anti-acetaldehyde oxide, syn-acetaldehyde oxide, and acetone oxide are presented at 0 K as 26.5, 15.6, 12.2, and 0.1 kcal mol−1, respectively. Additionally, we do not recommend the coupled cluster with perturbative quadruple excitations [CCSDT(Q)] energy correction, as it is approximately twice as large as that of the coupled cluster with full quadruple excitations (CCSDTQ). Half of the CCSDT(Q) energy correction may be included as a reliable, cost-effective estimation of CCSDTQ energies for Criegee intermediates.

Chemistry↗
DOE OSTI2024

Deprotonated sulfamic acid and its homodimers: Does sulfamic acid adopt zwitterion during cluster growth?

Here we present a joint experimental and computational study on the geometric and electronic structures of deprotonated sulfamic acid (SA) clusters [(SA) n –H] – (n = 1, 2) employing negative ion photoelectron spectroscopy and high-level ab initio calculations. The photoelectron spectra provide the vertical/adiabatic detachment energy (VDE/ADE) of the sulfamate anion (SM – ) H 2 N•SO 3 – at 4.85 ± 0.05 and 4.58 ± 0.08 eV, respectively, and the VDE and ADE of the SM – •SA dimer at 6.41 ± 0.05 and 5.87 ± 0.08 eV, respectively. The significantly increased electron binding energies of the dimer confirm the enhanced electronic stability upon the addition of one SA molecule. The CCSD(T)-predicted VDEs/ADEs agree excellently with the experimental data, confirming the identified structures as the most stable ones. Two types of dimer isomers possessing different hydrogen bonding (HB) motifs are identified, corresponding to SM – binding to a zwitterionic SA (SM – •SA z ) and a canonical SA (SM – •SA c ), respectively. Two N–H$\cdots$O HBs and one superior O–H$\cdots$O HB are formed in the lowest-lying SM – •SA c , while SM – •SA z has three moderate N–H$\cdots$O HBs, with the former being 4.71 kcal/mol more stable. Further theoretical analyses reveal that the binding strength advantage of SM – •SA c over SM – •SA z arises from its significant contributions of orbital interactions between fragments, illustrating that sulfamate strongly interacts with its parent SA acid and preferably chooses the canonical SA in the subsequent cluster formations. Given the prominent presence of SA, this study provides the first evidence that the canonical dimer model of sulfamic acid should exist as a superior configuration during cluster growth.

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

An investigation of aqueous ammonium nitrate aerosols with soft X-ray spectroscopy

Aqueous aerosols are important in atmospheric chemistry, drug delivery, and human health. X-ray photoelectron spectroscopy (XPS), a surface-sensitive technique and near-edge X-ray absorption fine structure (NEXAFS) spectroscopy which informs on the bulk, is deployed to study the solvation of ammonium nitrate (NH 4 NO 3 ). Aerosolised solutions of NH 4 NO 3 were introduced into a photoelectron spectrometer via an aerodynamic lens, and interrogated with soft X-ray photons, the resulting electrons were imaged via velocity map imaging. Density functional theory calculations were performed to compare with the measured binding energies of NH 4 + and NO 3 - solvated in water. The results reveal that the nitrate anion has a slight propensity for the surface, while both ammonium and nitrate ions are present in equal measure in the bulk.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Characterizing and quantifying uncertainty in projections of climate change impacts on air quality

Climate change can aggravate air pollution, with important public health and environmental consequences. While major sources of uncertainty in climate change projections - greenhouse gas (GHG) emissions scenario, model response, and internal variability - have been investigated extensively, their propagation to estimates of air quality impacts has not been systematically assessed. Here, we compare these uncertainties using a coupled modeling framework that includes a human activity model, an Earth system model of intermediate complexity, and a global atmospheric chemistry model. Uncertainties in projections of U.S. air quality under 21st century climate change are quantified based on a climate-chemistry ensemble that includes multiple initializations, representations of climate sensitivity, and climate policy scenarios, under constant air pollution emissions. We find that climate-related uncertainties are comparable at mid-century, making it difficult to distinguish the impact of variations in GHG emissions on ozone and particulate matter pollution. While GHG emissions scenario eventually becomes the dominant uncertainty based on the scenarios considered, all sources of uncertainty are significant through the end of the century. The results provide insights into intrinsically different uncertainties in projections of air pollution impacts and the potential for large ensembles to better capture them.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Intelligent Electrochemical Sensors for Precise Identification of Volatile Organic Compounds Enabled by Neural Network Analysis

The volatile organic compounds (VOCs) in a wide spectrum of categories were identified as biomarkers in aquatic environments, playing an important role in marine and freshwater ecology and global atmospheric chemistry. VOCs released from biofuel have also attracted increasing attention. Although the importance has been recognized, the portable detection and analysis methods of VOC in aquatic systems have not yet been well developed and understood. Here, in this work, we innovatively proposed an intelligent electrochemical sensing approach to classify and quantify VOCs in solution. Utilizing the cyclic voltammetry (CV) method with an ionic liquid (IL)-based electrolyte, we analyzed 50 μL samples of various VOC analytes, including acetic acid (AC), acetone, dimethylformamide (DMF), dimethyl sulfoxide (DMSO), ethanol, formaldehyde, formic acid, methanol, methyl formate (MF), toluene, and a formaldehyde-methanol mixture, along with deionized water (DI water). The generated voltammograms were subsequently analyzed using our uniquely designed and optimized 1-D convolutional neural network (1D-CNN). This deep-learning algorithm achieved a 99.09% accuracy in VOC classification validated through fivefold cross-validation and demonstrated an impressive 94.4% test accuracy for methanol detection within a 10 μL error range. For quantification, the system accurately categorized methanol volumes ranging from 0 to 50 μL in 10 μL increments, achieving a 98.18% accuracy. A notable linear correlation (R2 = 95.56%) was found between max current density at the oxidation peak and methanol volume, with the limit of detection (LOD) at 9.3 μL. Such a sensing method exhibits potential for portability, high accuracy, and generalization in the classification and quantification, ultimately reshaping the realm of VOC analysis in solution.

42 ENGINEERING↗
DOE OSTI2021

NACHOS, a CubeSat-based high-resolution UV-Visible hyperspectral imager for remote sensing of trace gases: system overview and science objectives

Here, the Nano-satellite Atmospheric Chemistry Hyperspectral Observation System (NACHOS) is a high-throughput (f/2.9), high spectral resolution (~1.3 nm optical resolution, 0.6 nm sampling) Offner-design hyperspectral imager operating in the 300-500 nm spectral region. The 1.5U instrument payload (1U optical system, 0.5U electronics module) is hosted by a 1.5U LANL-designed CubeSat bus to comprise a 3U complete satellite. Spectroscopically similar to NASA’s Ozone Monitoring Instrument (OMI), which provides wide-field global mapping of ozone and other gases at coarse spatial resolution, NACHOS fills the complementary niche of targeted measurements at much higher spatial resolution. With 350 across-track spatial pixels and a 15-degree across-track field of view, NACHOS will provide spectral imaging at roughly 0.4 km per pixel from 500 km altitude. NACHOS incorporates highly streamlined gas-retrieval algorithms for rapid onboard processing, alleviating the need to routinely downlink massive hyperspectral data cubes. We will discuss the instrument design, challenges in achieving mechanical robustness to launch vibration in such a compact instrument, the onboard calibration system, and gas-retrieval data downlink strategy. We will also discuss potential science missions, including monitoring of NO 2 as an easily detected proxy for anthropogenic fossil-fuel greenhouse gases, monitoring lowlevel SO 2 degassing at pre-eruptive volcanoes, H 2 CO from wildfires, and characterization of aerosols. The long-term vision is for a many-satellite constellation that could provide both high spatial resolution and frequent revisits for selected targets of interest. As an initial technology demonstration of this vision, the NACHOS project is currently slated to launch two CubeSats in early 2022.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Cloud–Aerosol–Turbulence Interactions: Science Priorities and Concepts for a Large-Scale Laboratory Facility

The purpose of this meeting summary, therefore, is to outline the range of scientific questions, and the facility concepts that were explored.We began the workshop with a series of overview talks to highlight scientific questions that could be investigated in a large-scale aerosol-cloud-turbulence laboratory facility. Topics included warm and mixed-phase cloud microphysics, aerosol and cloud chemistry, atmospheric turbulence, radiative transfer, cloud/aerosol instrumentation, and remote sensing. There was ample time for questions and discussion following each overview presentation. We also broke into groups for several hours at various points to enable more active discussion among all participants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Coupling of high-resolution mass spectrometer and photosynthesis system for comprehensive leaf volatile metabolite profiling

Background Leaf-level biogenic volatile organic compounds (BVOCs) emissions represent a major source of organic gases in the atmosphere, influencing both climate and air quality. These emissions are strongly driven by environmental perturbations, which affect individual plant- to ecosystem-level processes. Uncovering all the BVOCs and understanding how their emissions respond to altered environmental conditions provide critical insights into vegetation-driven changes in atmospheric chemistry. We developed a tandem instrumentation setup that integrates a proton transfer reaction time-of-flight mass spectrometer (PTR-ToF-MS) with parts-per-trillion detection limits and a photosynthetic infrared gas exchange system for the untargeted survey of all the BVOCs. This novel system enables simultaneous, real-time monitoring of BVOC emissions and photosynthetic parameters at the leaf level, offering new opportunities to disentangle the physiological and environmental drivers of VOC release. Furthermore, we established the VOC Analysis and Processing Optimization Resource (VAPOR), an open-access software tool designed for rapid data post-processing and the analysis of the variability of hundreds of BVOCs. We assessed the performance of the tandem system under varying background conditions, using standard gas mixtures and a range of environmental factors. Results Blank emissions were substantially lower for major BVOCs (e.g., isoprene) compared to those observed in plant emissions. Despite this, the observation of background-level VOCs highlights the importance of routinely acquiring and accounting for blank measurements in analyses using the coupled instrumentation. Introduction of known VOC concentrations to the system demonstrated a linear response across different compounds with varying molecular compositions, indicating minimal gas loss regardless of chemical moieties within the coupled instrumentation. We applied the optimized system to investigate the physiological mechanisms driving BVOC emissions across different genotypes of poplar and pennycress. The high mass resolution capabilities of the PTR-ToF-MS, coupled with comprehensive VAPOR-driven data analysis, enabled the identification of several important BVOCs, including methanol and methanethiol; these BVOCs displayed substantial variation across pennycress genotypes and showed concentrations ~ 100–350% higher than the blank. Moreover, isoprene emissions varied significantly among poplar genotypes grown in different potting media. Conclusions Tandem instrumentation offers a powerful tool for profiling volatile molecular markers and elucidating their genetic and environmental underpinnings. This approach enhances our ability to predict BVOC emissions in response to genotype by environmental interactions and contributes to a deeper understanding of vegetation responses to environmental changes.

Biogenic volatile organic compounds↗
DOE OSTI2021

Data from: Learning coagulation processes with combinatorially-invariant neural networks

This dataset contains all the necessary information to recreate the study presented in the paper entitled "Learning coagulation processes with combinatorially-invariant neural networks". This consists of (1) the aggregated output files used for machine learning, (2) the machine learning codes used to learn the presented models, (3) the PartMC model source code that was used to generate the simulation data and (4) the Python scripts used construct the scenario library for training and testing simulations. This data was used to investigate a method (combinatorally-invariant neural network) for learning the aerosol process of coagulation. This data may be useful for application of other methods.

Atmospheric chemistry↗
DOE OSTI2026

Data for The impact of aerosol mixing state on immersion freezing: Insights from classical nucleation theory and particle-resolved simulations

This dataset contains the values directly shown in the figures of the article "The impact of aerosol mixing state on immersion freezing: Insights from classical nucleation theory and particle-resolved simulations". This article is in preparation for submission to the journal Atmospheric Chemistry and Physics. The dataset consists of 12 NetCDF files processed from the raw output of the PartMC model. It does not include the theoretical values of frozen fraction, which can be computed using the equations provided in the paper. *New in V2: adding data for a newly included figure (INP_spectrum.nc), removing files that are no longer used in the revised manuscript figures (e.g., UNC_A_ratio=0.9_Dp=0.1.nc, UNC_A_ratio=0.9_Dp=10.0.nc, UNC_A_ratio=0.1_Dp=0.1.nc, and UNC_A_ratio=0.1_Dp=10.0.nc), and updating README.pdf accordingly.

Aerosol mixing state↗
DOE OSTI2024

Precision Gas System Isotope Analyzer (PGSISO) Instrument Handbook

The PGSISO is a combination of several systems in series; (1) gas processing components that pressurize and prevent liquid water entering the sample stream, and (2) the Spectronus FTIR spectrometer, which measures continuous CO 2 , 12 CO 2 , 13 CO 2 , CH 4 , CO, N 2 O, and H 2 O. The Spectronus analyzer has been developed by the Centre for Atmospheric Chemistry at the University of Wollongong, Australia, and manufactured by Ecotech Pty Ltd, headquartered in Melbourne, Australia.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Comprehensive Chemical Fingerprinting by Multidimensional GC and Supervised Machine Learning

This project leverages advances in machine learning based data analysis techniques and untargeted omic analytical methods to progress nuclear nonproliferation technologies beyond current capabilities. The developed approaches can be used to identify and detect complex chemical fingerprints of facilities of interest. These techniques have been developed for fields such as metabolomics and genomics but have not been applied to nuclear nonproliferation applications. Adaptation of these techniques for volatile organic compound analysis has far reaching application within the scientific community including environmental chemistry, atmospheric physics, and climate sciences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Comprehensive Chemical Fingerprinting by Multidimensional GC and Supervised Machine Learning

This project leveraged advances in machine learning based data analysis techniques and untargeted analytical methods for organic analysis to progress nuclear nonproliferation technologies beyond current capabilities. The developed approaches can be used to detect and identify complex chemical fingerprints of facilities of interest. These techniques have been developed for fields such as metabolomics and genomics but have not been applied to nuclear nonproliferation applications. Adaptation of these techniques for volatile organic compound analysis has far reaching application within the scientific community including environmental chemistry, atmospheric physics, and climate sciences.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Characterizing the contribution of bioaerosols diversity from complex aerosol particle samples.

Current global change scenarios expect to significantly increase the contribution of pollen to the total organic aerosol budget. In addition, pollen can burst into smaller fragments that are highly efficient as cloud condensation nuclei. However, current climate models still do not incorporate the effects of these particles due to detection and quantification challenges in complex aerosol mixtures. Chemical biomarkers (i.e. fructose) have commonly been used to trace pollen but this approximation can generate false positive results given the large number of shared compounds between different bioaerosols. A previous pilot EMSL experiment performed on pure pollen samples suggested that using a set of metabolites as a fingerprint of bioaerosols could serve to substantially increase detection accuracy over single biomarker approaches. In this proposal we developed novel bioinformatic strategies to characterize and quantify complex pollen mixtures present in the atmosphere. For that, we used diverse machine learning algorithms to analyze metabolic fingerprints from complex mixtures of different pollen acquired with high-resolution mass spectrometry (Orbitrap Q-Exactive). Our preliminary results demonstrated the potential to accurately discern and identify at specific relative abundances different pollen species in complex mixtures. Our research will lead to a significant advancement in the atmospheric chemistry and provide much needed data to improve the accuracy of climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Interactions between land use, fires, and dust as drivers of global climate change (Final Technical Report)

This award to UC Irvine and Cornell University led to the publication of 18 papers, three of which are highly cited. According to ISI Web of Science, the body of work from this grant has been cited over 476 times by May 2025. Several additional publications remain in review. This grant contributed to several significant science advances, including an improved understanding of the influence of fire aerosols on global photosynthesis (Xu et al., 2021), dust-driven teleconnections between Africa and South America (Li et al., 2021), the role of fire aerosols in triggering phytoplankton blooms in the Arctic (Ardyna et al., 2022), and wildfire responses to heat waves (Li et al., in review). Several other studies are being written up for publication, and will acknowledge funding support. These efforts include an analysis in which the magnitude of tropical fire emissions from land use change is constrained by comparing E3SMv3 simulations with atmospheric observations. This work has revealed that carbon cycle model estimates of land use change may considerably overestimate the global tropical deforestation flux. The project also contributed to several technical advances, including a new process-based and scale-aware desert dust emission scheme for global climate models (Leung et al., 2023), an improved representation of dust and its influence on radiation in E3SM (Feng et al., 2022), an improved representation of the dust parameterization in the Community Earth System Model (Li et al., 2022), and an improved coupling of wildfires with atmospheric chemistry in E3SM v3.

58 GEOSCIENCES↗
DOE OSTI2024

NETL Mobile Emissions Laboratory

This presentation was given (virtually) at the workshop on Atmospheric Chemistry and Dispersion Modelling of Non-CO2 Emissions from Carbon Capture at the National Carbon Capture Center on November 21, 2024. The presentation describes capabilities of NETL's new mobile emissions laboratory trailer.

air emissions↗