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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Stable Water Isotope Data for the East River Watershed, Colorado (2014-2025)

The stable water isotope data for the East River Watershed, Colorado, consists of delta2H (hydrogen) and delta18O (oxygen) values from samples collected at multiple, long-term monitoring sites including streams, groundwater wells, springs, and a precipitation collector used to establish a local meteoric water line (LMWL) for the watershed. These locations represent important and/or unique end-member locations for which stable isotope values can be diagnostic of the connection between precipitation inputs as snow and rain and riverine export. Such locations include drainages underline entirely or largely by shale bedrock, land covered dominated by conifers, aspens, or meadows, and drainages impacted by historic mining activity and the presence of naturally mineralized rock. Developing a long-term record of water isotope values from a diversity of environments is a critical component of quantifying the impacts of both climate change and discrete climate perturbations, such as drought, forest mortality, and wildfire, on water export. Such data may be combined with stream gaging stations co-located at each surface water monitoring site to relate seasonal variations in water export to their stable isotopic signature. Data for liquid water delta2H and delta18O values are reported in units of parts per thousand (per-mil; ‰). This data package contains (1) a zip file (isotope_data_2014-2025.zip) containing a total of 95 files: 96 data files of isotope data from across the Lawrence Berkeley National Laboratory (LBNL) Watershed Function Scientific Focus Area (SFA) which is reported in .csv files per location and a locations.csv (1 file) with latitude and longitude for each location; (2) a file-level metadata (v6_20260901_flmd.csv) file that lists each file contained in the dataset with associated metadata; and (3) a data dictionary (v6_20260901_dd.csv) file that contains terms/column_headers used throughout the files along with a definition, units, and data type. Missing values within the anion data files are noted as either "-9999" or "0.0" for not detectable (N.D.) data. There are a total of 43 locations containing isotope data. Update on 2022-06-10: versioned updates to this dataset was made along with these changes: (1) updated isotope data for all locations up to 2021-12-31 and (2) the addition of the file-level metadata (flmd.csv) and data dictionary (dd.csv) were added to comply with the File-Level Metadata Reporting Format. Update on 2022-09-09: Updates were made to reporting format specific files (file-level metadata and data dictionary) to correct swapped file names, add additional details on metadata descriptions on both files, add a header_row column to enable parsing, and add version number and date to file names (v2_20220909_flmd.csv and v2_20220909_dd.csv). Update on 2023-08-08: Updates were made to both the data files and reporting format specific files. New available anion data was added, up until 2023-03-13. The file level metadata and data dictionary files were updated to reflect the additional data added. Update on 2024-03-11: Updates were made to both the data files and reporting format specific files. New available anion data was added, up until 2024-02-19. Further, revisions to the data files were made to remove incorrect data points (from 1970 and 2001). The reporting format specific files were updated to reflect the additional data added. Update on 2025-05-15: Updates were made to both the data files and reporting format specific files. New available isotope data was added, up until the end of WY2024 (September 30, 2024). International Generic Sample Numbers (IGSNs), when registered, were added to the data files. The reporting format specific files were updated to reflect the additional data added. Update on 2026-09-01: Updates were made to both the data files and reporting format specific files. New available isotope data was added, up until the end of WY2025 (September 30, 2025).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

FREDA: A Web Application for the Processing, Analysis, and Visualization of Fourier‐Transform Mass Spectrometry Data

The high-resolution measurement capability of Fourier-transform mass spectrometry (FT-MS) has made it a necessity for exploring the molecular composition of complex organic mixtures, like soil, plant, aquatic, and petroleum samples. This demand has driven a need for informatics tools to explore and analyze FT-MS data in a robust and reproducible manner. FREDA is an interactive web application developed to enable spectrometrists to format, process, and explore their FT-MS data without the need for statistical programming expertise. FREDA was built to explore outputs from a molecular identification tool, like CoreMS, and provide a suite of methods to filter data, compute chemical properties of peaks, statistically compare samples and groups of samples, conduct exploratory data analysis, and download the results with a report detailing all steps conducted. To demonstrate the utility of FREDA, an example analysis was conducted using FT-MS data from a soil microbiology study of samples collected in two different soil depths at the Sphagnum bog forest north of Grand Rapids, Minnesota. Differences between the two depths are observed using Kendrick, Gibbs free energy, and van Krevelen plots. G-tests are used to quantify a significant difference between the groups. All analyses and plotting are conducted using only the FREDA application. FREDA is an open-source and readily available web application that allows users to explore and make statistically valid conclusions about their FT-MS data. The application is available online (https://map.emsl.pnnl.gov/app/freda) with a tutorial web series (https://youtu.be/k5HLE2kNSBY?si=yB6sGoyvzxrFf5MP) and freely accessible code on Github (https://github.com/EMSL-Computing/FREDA).

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Electron and photon efficiencies in LHC Run 2 with the ATLAS experiment

Precision measurements of electron reconstruction, identification, and isolation efficiencies and photon identification efficiencies are presented. They use the full Run 2 data sample collected by the ATLAS experiment in pp collisions at a centre-of-mass energy of 13 TeV during the years 2015–2018, corresponding to an integrated luminosity of 139 fb -1 . The measured electron identification efficiencies have uncertainties that are around 30%–50% smaller than the previous Run 2 results due to an improved methodology and the inclusion of more data. A better pile-up subtraction method leads to electron isolation efficiencies that are more independent of the amount of pile-up activity. Updated photon identification efficiencies are also presented, using the full Run 2 data. When compared to the previous measurement, a 30%–40% smaller uncertainty is observed on the photon identification efficiencies, thanks to the increased amount of available data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Measurement of the Υ(1S), Υ(2S), and Υ(3S) differential cross sections in pp collisions at $\sqrt{s}=13.6$ TeV

The production cross sections of the Υ(1S), Υ(2S), and Υ(3S) mesons are measured in proton-proton collisions at $\sqrt{s}=13.6$ TeV, using a data sample collected in 2022 by the CMS experiment and corresponding to an integrated luminosity of 37.4 fb −1 . The measurement is performed in the μ + μ − decay channels, differentially as a function of transverse momentum in the 20–200 GeV range, in the |y| < 0.6 and 0.6 < |y| < 1.2 rapidity intervals.

Hadron-Hadron Scattering↗
DOE OSTI2025

Measurements of the branching fractions of ${\Xi }_{c}^{+}\to {\Sigma }^{+}{K}_{S}^{0}$, ${\Xi }_{c}^{+}\to {\Xi }^{0}{\pi }^{+}$, and ${\Xi }_{c}^{+}\to {\Xi }^{0}{K}+$ at Belle and Belle II

Using 983.0 fb −1 and 427.9 fb −1 data samples collected with the Belle and Belle II detectors at the KEKB and SuperKEKB asymmetric energy e + e − colliders, respectively, we present studies of the Cabibbo-favored ${\Xi }_{c}^{+}$ decays ${\Xi }_{c}^{+}\to {\Sigma }^{+}{K}_{S}^{0}$ and ${\Xi }_{c}^{+}\to {\Xi }^{0}{\pi }^{+}$, and the singly Cabibbo-suppressed decay ${\Xi }_{c}^{+}\to {\Xi }^{0}{K}^{+}$. The ratios of branching fractions of ${\Xi }_{c}^{+}\to {\Sigma }^{+}{K}_{S}^{0}$ and ${\Xi }_{c}^{+}\to {\Xi }^{0}{K}^{+}$ relative to that of ${\Xi }_{c}^{+}\to {\Xi }^{-}{\pi }^{+}{\pi }^{+}$ are measured for the first time, while the ratio $\mathcal{B}({\Xi }_{c}^{+}\to {\Xi }^{0}{\pi }^{+})/\mathcal{B}({\Xi }_{c}^{+}\to {\Xi }^{-}{\pi }^{+}{\pi }^{+})$ is also determined and improved by an order of magnitude in precision. The measured branching fraction ratios are $\begin{array}{c}\frac{\mathcal{B}\left({\Xi }_{c}^{+}\to {\Sigma }^{+}{K}_{S}^{0}\right)}{\mathcal{B}\left({\Xi }_{c}^{+}\to {\Xi }^{-}{\pi }^{+}{\pi }^{+}\right)}=0.067\pm 0.007\pm 0.003,\\ \frac{\mathcal{B}\left({\Xi }_{c}^{+}\to {\Xi }^{0}{\pi }^{+}\right)}{\mathcal{B}\left({\Xi }_{c}^{+}\to {\Xi }^{-}{\pi }^{+}{\pi }^{+}\right)}=0.251\pm 0.005\pm 0.010,\\ \frac{\mathcal{B}\left({\Xi }_{c}^{+}\to {\Xi }^{0}{K}^{+}\right)}{\mathcal{B}\left({\Xi }_{c}^{+}\to {\Xi }^{-}{\pi }^{+}{\pi }^{+}\right)}=0.017\pm 0.003\pm 0.001.\end{array}$ Additionally, the ratio $\mathcal{B}({\Xi }_{c}^{+}\to {\Xi }^{0}{K}^{+})/\mathcal{B}({\Xi }_{c}^{+}\to {\Xi }^{0}{\pi }^{+})$ is measured to be 0.068 ± 0.010 ± 0.004. Here, the first and second uncertainties are statistical and systematic, respectively. Multiplying the ratios by the branching fraction of the normalization mode, $\mathcal{B}({\Xi }_{c}^{+}\to {\Xi }^{-}{\pi }^{+}{\pi }^{+})=(2.9\pm 1.3)%$, we obtain the following absolute branching fractions $\begin{array}{c}\mathcal{B}({\Xi }_{c}^{+}\to {\Sigma }^{+}{K}_{S}^{0})=(0.194\pm 0.021\pm 0.009\pm 0.087)\text{%},\\ \mathcal{B}({\Xi }_{c}^{+}\to {\Xi }^{0}{\pi }^{+})=(0.728\pm 0.014\pm 0.027\pm 0.326)\text{%},\\ \mathcal{B}({\Xi }_{c}^{+}\to {\Xi }^{0}{K}^{+})=(0.049\pm 0.007\pm 0.003\pm 0.022)\text{%},\end{array}$ where the third uncertainties are from $\mathcal{B}({\Xi }_{c}^{+}\to {\Xi }^{-}{\pi }^{+}{\pi }^{+})$.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Measurement of beauty-quark production in pp collisions at $\sqrt{s}$ = 13 TeV via non-prompt D mesons

The p T -diferential production cross sections of non-prompt D 0 , D + , and D$^+_s$ at a centre-of-mass energy $\sqrt{s}$ = 13 TeV. The measurements are performed at midrapidity, |y| < 0.5, with the data sample collected by ALICE from 2016 to 2018. The results are in agreement with predictions from several perturbative QCD calculations. The fragmentation fraction of beauty quarks to strange mesons divided by the one to non-strange mesons, $f_s$/($f_u$ +$f_d$), is found to be 0.114 ± 0.016 (stat.) ± 0.006 (syst.) ± 0.003 (BR) ± 0.003 (extrap.). This value is compatible with previous measurements at lower centre-of-mass energies and in diferent collision systems in agreement with the assumption of universality of fragmentation functions. In addition, the dependence of the non-prompt D meson production on the centre of-mass energy is investigated by comparing the results obtained at $\sqrt{s}$ = 5.02 and 13 TeV, showing a hardening of the non-prompt D-meson p T -diferential production cross section at higher $\sqrt{s}$. Finally, the $b\overline{b}$ production cross section per unit of rapidity at midrapidity is calculated from the non-prompt D 0 , D + , D$^+_s$, and $Λ^+_c$ hadron measurements, obtaining dσ/dy = 75.2 ± 3.2 (stat.) ± 5.2 (syst.)$^{+12.3}_{-3.2}$ (extrap.) µb.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A Comparative Metagenomic Analysis of Specified Microorganisms in Groundwater for Non-Sterilized Pharmaceutical Products

In pharmaceutical manufacturing, ensuring product safety involves the detection and identification of microorganisms with human pathogenic potential, including Burkholderia cepacia complex (BCC), Escherichia coli, Pseudomonas aeruginosa, Salmonella enterica, Staphylococcus aureus, Clostridium sporogenes, Candida albicans, and Mycoplasma spp., some of which may be missed or not identified by traditional culture-dependent methods. In this study, we employed a metagenomic approach to detect these taxa, avoiding the limitations of conventional cultivation methods. We assessed the groundwater microbiome’s taxonomic and functional features from samples collected at two locations in the spring and summer. All datasets comprised 436–557 genera with Proteobacteria, Bacteroidota, Firmicutes, Actinobacteria, and Cyanobacteria accounting for > 95% of microbial DNA sequences. The aforementioned species constituted less than 18.3% of relative abundance. Escherichia and Salmonella were mainly detected in Hot Springs, relative to Jefferson, while Clostridium and Pseudomonas were mainly found in Jefferson relative to Hot Springs. Multidrug resistance efflux pumps and BlaR1 family regulatory sensor-transducer disambiguation dominated in Hot Springs and in Jefferson. These initial results provide insight into the detection of specified microorganisms and could constitute a framework for the establishment of comprehensive metagenomic analysis for the microbiological evaluation of pharmaceutical-grade water and other non-sterile pharmaceutical products, ensuring public safety.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Performance of the LHCb muon detector in Run 3

In Run 3 of the LHC, the instantaneous luminosity at the LHCb interaction point has been increased by a factor of five, from to $\mathscr{L}$ = 4 x 10 32 cm -2 s -2 to $\mathscr{L}$ = 2 x 10 33 cm -2 s -1 . Several hardware interventions, including a complete overhaul of the readout electronics, have been carried out on the muon detector. The muon identification algorithms in the software trigger were improved with the aim of ensuring Run 2 performance under a higher particle rate. The operation and calibration of the upgraded muon detector are presented. The muon detection efficiency and muon identification performance are evaluated on data calibration samples collected during the year 2024. A muon identification efficiency above 90% with sub-percent hadron misidentification probability is achieved by exploiting the pattern of hits in the muon detector.

Gaseous detectors↗
DOE OSTI2024

Measurement of the polarizations of prompt and non-prompt J/ψ and ψ ( 2S ) mesons produced in pp collisions at s = 13 TeV

The polarizations of prompt and non-prompt Image 2 and ψ ( 2S ) mesons are measured in proton-proton collisions at s = 13 TeV, using data samples collected by the CMS experiment in 2017 and 2018, corresponding to a total integrated luminosity of 103.3 fb − 1 . Based on the analysis of the dimuon decay angular distributions in the helicity frame, the polar anisotropy, λ ϑ , is measured as a function of the transverse momentum, p T , of the charmonium states, in the 25–120 and 20–100 GeV ranges for the Image 2 and ψ ( 2S ) , respectively. The non-prompt polarizations agree with predictions based on the hypothesis that, for p T ≳ 25 GeV , the non-prompt Image 2 and ψ ( 2S ) are predominantly produced in two-body B meson decays. The prompt results clearly exclude strong transverse polarizations, even for p T exceeding 30 times the Image 2 mass, where λ ϑ tends to an asymptotic value around 0.3. Taken together with previous measurements, by CMS and LHCb at s = 7 TeV, the prompt polarizations show a significant variation with p T , at low p T .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Probing late-stage hadronic interactions at high baryon density via $K^{⁎0}$ production in the RHIC beam energy scan program

A precision measurement of the $K^{⁎0}$ meson yield is reported in Au+Au collisions at $\sqrt{s_{NN}}$ = 7.7, 11.5, 14.6, 19.6, and 27 GeV using the high-statistics data sample collected by the STAR experiment during the Beam Energy Scan II (BES-II) program at RHIC. The transeverse momentum (p T )-integrated yield ratios $\large{(}K^{⁎0} + \overline{K^{⁎0}}\large{)}/(K^+ + K^{-})$ in central collisions show a suppression relative to peripheral collisions at the (1.7–3.6) σ level, while a thermal model without final-stage rescattering overpredicts this ratio with a deviation of (6.9–8.2) σ. These results indicate a loss of the measured $K^{⁎0}$ signal in central collisions due to re-scattering of its hadronic decay products in the hadronic phase. The p T -integrated yield of charged kaons exhibits an approximate scaling with charged-particle multiplicity, independent of collision energy and system size. A similar trend is observed for the short-lived $K^{⁎0}$ resonance, although significant deviations emerge at lower energies. At BES energies, the $K^{⁎0}/K$ ratio shows stronger suppression than at the highest RHIC and LHC energies within a given multiplicity bin, particularly in central and mid-central collisions. This behavior is consistent with changes in the effective hadronic interaction cross section and is supported by transport model calculations, which indicate dominant meson–baryon interactions at lower energies and meson–meson interactions at higher energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Functionalized Porous Polymer Networks as High-Performance PFAS Adsorbents

Toxic per- and polyfluoroalkyl substances (PFAS) are now found in nearly every water source on the planet. Exposure to these molecules can have negative health consequences, but the low concentration of PFAS relative to other solutes in water makes their removal challenging. Adsorbents offer a promising treatment route, but often exhibit low selectivities and removal capacities, as well as slow kinetics. The performance in these metrics can be improved by chemically optimizing PFAS binding sites and maximizing PFAS-adsorbent interactions. To explore how to achieve this, a porous polymer network solid (PPN-6, also known as PAF-1) was postsynthetically modified with various chemical moieties capable of leveraging unique combinations of electrostatic, hydrogen-bonding, hydrophobic, and fluorophilic interactions with PFAS molecules. Batch adsorption experiments and computational studies revealed that electrostatic and hydrogen-bonding interactions drive short-chain PFAS adsorption, while hydrophobic and fluorophilic interactions improve long-chain PFAS adsorption. In complex water matrices, a combination of electrostatic and fluorophilic interactions led to the greatest total PFAS removal. The best-performing material, functionalized with a fluorinated alkylammonium (PPN-6-FNDMB), selectively adsorbs PFAS with high capacity (up to 4.0 mmol/g) and rapid kinetics (equilibrium reached in <30 s). Furthermore, PPN-6-FNDMB outperforms several commercial adsorbents, achieving near-complete removal of 21 different PFAS from a groundwater sample collected at a US Air Force base. The PFAS could subsequently be desorbed from PPN-6-FNDMB, concentrating them by a factor of over 50 times. The recycled PPN-6-FNDMB could then be reused with minimal losses in long-chain PFAS adsorption capacity over four cycles.

Pezoulas, Ethan R↗
DOE OSTI2024

Prediction of Distributed River Sediment Respiration Rates Using Community-Generated Data and Machine Learning

River sediment microbial respiration is a key indicator of ecosystem functioning and the biogeochemical fluxes across this critical zone link surface and subsurface waters. As such, there is tremendous interest in measuring and mapping these respiration rates. Respiration observations are expensive and labor intensive; there is limited data available to the community. An open science, collaborative initiative is collecting samples for respiration rate analysis and multi-scale metadata; this evolving data set is being used for making machine learning (ML) predictions at unsampled sites to help inform continued community engagement. However, it is a challenge to find an optimum configuration for ML models to work with this feature-rich (i.e., 100+ possible input variables) data set. Here, we present results from a two-tiered approach to managing the analysis of this complex data set: (a) a stacked ensemble of models that automatically optimizes hyperparameters and manages the training of many models and (b) feature permutation importance to detect the most important features in the models. The major elements of this workflow are modular, portable, open, and cloud-based thus making this implementation a potential template for other applications. The models developed here predict that sediment organic matter chemistry is one of the most important features for predicting sediment respiration rate. Other larger-scale, important features fall into the categories of climatic, ecological, geological, and fluvial settings. Leveraging these larger-scale features to generate data-driven estimates of river sediment respiration rates reveals spatially consistent but heterogeneous patterns across the river network of the Columbia River Basin.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Development and flight-testing of modular autonomous cultivation systems for biological plastics upcycling aboard the ISS

Cultivation of microorganisms in space has enormous potential to enable in-situ resource utilization (ISRU) Here, we develop an autonomous payload with fully programmable serial passaging and sample preservation, termed the Modular Open Biological Platform (MOBP), and flight-test the MOBP aboard the International Space Station (ISS) by conducting enzymatic and microbial plastics upcycling experiments. The MOBP is a compact, modular bioreactor system that allows for sustained microbial growth via automated media transfers, such as those for sample collection and storage for terrestrial analyses, and precise data monitoring from integrated sensors. The MOBP was flight-tested with two experiments designed to evaluate biological upcycling of the plastic poly(ethylene terephthalate) (PET). The bioproduct βKA can be polymerized into a nylon-6,6 analog with improved properties for use in the production of a variety of materials. We posit the MOBP will aid in democratizing the execution of synthetic biology in spaceflight towards enabling ISRU.

09 BIOMASS FUELS↗
DOE OSTI2024

Coassembly and binning of a twenty-year metagenomic time-series from Lake Mendota

Abstract The North Temperate Lakes Long-Term Ecological Research (NTL-LTER) program has been extensively used to improve understanding of how aquatic ecosystems respond to environmental stressors, climate fluctuations, and human activities. Here, we report on the metagenomes of samples collected between 2000 and 2019 from Lake Mendota, a freshwater eutrophic lake within the NTL-LTER site. We utilized the distributed metagenome assembler MetaHipMer to coassemble over 10 terabases (Tbp) of data from 471 individual Illumina-sequenced metagenomes. A total of 95,523,664 contigs were assembled and binned to generate 1,894 non-redundant metagenome-assembled genomes (MAGs) with ≥50% completeness and ≤10% contamination. Phylogenomic analysis revealed that the MAGs were nearly exclusively bacterial, dominated by Pseudomonadota (Proteobacteria, N = 623) and Bacteroidota (N = 321). Nine eukaryotic MAGs were identified by eukCC with six assigned to the phylum Chlorophyta. Additionally, 6,350 high-quality viral sequences were identified by geNomad with the majority classified in the phylum Uroviricota. This expansive coassembled metagenomic dataset provides an unprecedented foundation to advance understanding of microbial communities in freshwater ecosystems and explore temporal ecosystem dynamics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Heavy metal imprints in Antarctic snow from research and tourism

Antarctica, long regarded as one of the last pristine environments on Earth, is increasingly affected by human activity. As tourism surges and scientific operations expand, air pollution from local emissions is raising new environmental concerns. Here, in this study, we analyze surface snow samples collected along a ~2,000 km transect, from the South Shetland Islands (62°S) to the Ellsworth Mountains (79°S), to map the geochemical fingerprints of aerosol deposition. We identify distinct spatial patterns shaped by crustal, marine, biogenic, and anthropogenic sources. Notably, we detect heavy metal imprints in the snow chemistry of the northern Antarctic Peninsula, where major research stations are concentrated and marine tourism traffic is most intense. Our findings shed light on the extent of the impacts from energy-intensive local activities in Antarctica, underscoring the need for enhanced environmental monitoring and sustainable management strategies in this fragile region.

Cordero, Raúl R. [Univ. of Groningen, Leeuwarden (↗
DOE OSTI2026

Single-particle chemical analysis reveals organic-rich detonation soot products

The detonation of high explosives produces a wide variety of particulate matter (PM) with distinct properties, not all of which are traditionally studied for chemical composition, formation processes, and forensic applications. We report particle-resolved measurements of Composition B detonation soot using soot particle aerosol mass spectrometry (SP-AMS), identifying carbonaceous species and metals not previously characterized on a single-particle basis. Results are combined with scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDS) to enhance source-dependent signatures. Black carbon, including graphitic carbon and detonation nanodiamonds, contributed 50.5-71.4% of PM 2.5 mass, while 22.5-43.4% was non-refractory organic carbon, a previously overlooked component that exhibited a complex and varying composition. Detonations were performed with and without PMMA confinement and under steady and overdriven conditions. Distinct particles enriched with polycyclic aromatic hydrocarbons (PAHs) were observed in experiments utilizing confinement, with quantities dependent on manufacturing method. SEM-EDS validated SP-AMS findings of metals internally mixed with carbonaceous species and extended the particle size range to 100 µm. This work makes detecting non-refractory organics using single-particle techniques more feasible for detonation forensics and understanding high-energy soot formation. While this analysis uses offline sample collection, SP-AMS could be deployed for in-situ measurements of detonation PM 2.5 transported in the atmosphere.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Amazonian fog harbors viable microbes

Fog formation over tropical forests remains poorly characterized, despite its potential role in bioaerosol dispersion and ecosystem processes. Here, we analyzed fog samples collected at the Amazon Tall Tower Observatory using flow cytometry and culture-based techniques to characterize viable microbial communities. Microbial cell concentrations varied over an order of magnitude across 13 fog events, reaching up to 8 × 104 cells per ml of fog water. Flow cytometry consistently detected metabolically active cells, while culturing and mass spectrometry-based identification yielded eight viable bacterial species and seven fungal taxa. The bacteria Serratia marcescens, Ralstonia pickettii and Sphingomonas paucimobilis exhibited seasonal variations in prevalence. The fungal species identified were primarily mesophilic saprophytes and endophytes, commonly associated with soil and plant surfaces. Our findings indicate that fog harbors viable microbes, including Serratia marcescens and Ralstonia pickettii, which may imply a relevance of fog for microbial dispersal, colonization and nutrient cycling in the Amazon rainforest.

Godoi, Ricardo H. (ORCID:0000000247744870)↗
DOE OSTI2024

Characterizing chemical abundance ratios in extremely metal-poor star-forming galaxies in DESI EDR

We present a search for galaxies in the local Universe with extremely low oxygen abundance, that is, more than 25 times lower than solar, which corresponds to 12 + log(O/H) < 7.3. To determine the oxygen abundance, we apply the directT e method for objects where the [O III]λ4363 line is detected. We identified 21 extremely metal-poor galaxies in the early data release of the Dark Energy Spectroscopic Instrument (DESI EDR), for some of which we also derived N/O, Ne/O, Ar/O, and S/O ratios. We find that many DESI galaxies with extremely low oxygen abundance exhibit a higher N/O ratio in comparison to the reference low-metallicity sample collected from the literature. We suggest that the elevation in N/O ratio may be explained by a contamination with metal-rich gas caused by gas inflow or a merger event. Moreover, contrary to some recent studies, we find that Ar/O and S/O ratios are enhanced as well, while the Ne/O ratio does not show such elevation. One of the galaxies, J0713+5608, has a remarkably low oxygen abundance of 6.978 ± 0.095 dex. This measurement aligns with the lowest known oxygen abundances in galaxies to date. Given the relatively high uncertainty, this galaxy may have the lowest oxygen abundance ever found. Additionally, J0713+5608 exhibited an enhanced N/O ratio compared to the typical N/O ratio observed in metal-poor galaxies within the local Universe.

Astronomy & Astrophysics↗