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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Chemical signature characterization with hyperspectral imagery: novel deep learning model architectures and physically-motivated data augmentation techniques

The high spectral resolution afforded by Hyperspectral Imaging (HSI) sensors is poised to bring unprecedented advancements to signature characterization applications. Thus far, much of the research in the machine learning field devoted to HSI applications has focused on a few specific tasks like land-use land-cover classification. In land classification tasks, spatial information is very important, and model architectures are often designed to leverage spatial contexts. However, it is unclear how well these spatially-tuned models will translate to tasks where spectral information is critical, like the detection and characterization of chemicals. In this work, we compare spectral models (inputs are 1D spectra) and spatial-spectral models (inputs are 3D cubes) in the context of predicting chemical concentration maps. We find that spatial-spectral models perform the best, though we find a wide range in performance across the different architectures tested. Additionally, we find that model performance is impacted by the availability of training data, particularly in scenarios where the training data doesn't fully capture the true variance of real-world conditions. We find that data augmentation can help mitigate sparse coverage of observed parameter space (e.g., seasonal or geographic variability in ground cover), and present augmentation strategies that are tailored to hyperspectral data.

• Artificial intelligence (AI) / machine learning ↗
DOE OSTI2024

Detection of a Cobalt-Containing Interphase at the Li 6 PS 5 Cl-NMC111 Interface by In Situ μ XANES and EIS

Sulfide electrolyte all-solid-state lithium batteries (ASLBs) with uncoated Li-Ni x Mn y Co 1–x–y O 2 (NMC) cathodes suffer from a large capacity loss during initial cycling and an increase in cell impedance. Decomposition reactions are known to occur at the Li 6 PS 5 Cl-NMC111 interface due to incompatibility between the two materials. If a stabilizing coating is applied to the NMC, it delivers full capacity during initial charge. However, the loss in capacity during discharge still occurs. The interface was studied by μ XANES and through EIS analysis. A chemically-formed interphase was detected by μ XANES, evident from reduction of Co at an uncoated NMC particle surface. This interphase was produced by decomposition at rest. To study the effect of the interphase on electrochemically active surface area, piecewise in situ EIS was performed and the data was modeled using a transmission line model (TLM). The charge transfer resistance R CT was used to estimate the volume specific active surface area (a act ). The median value for a act was 296 cm –1 , a factor of 7.5 lower than the theoretical value of 2216 cm –1 . This provided evidence of a lower electrochemically active surface area in the ASLB.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Signaling from below: rodents select for deeper fruiting truffles with stronger volatile emissions

Many plant and fungal species use volatile organic compounds (VOCs) as chemical signals to convey information about the location or quality of their fruits or fruiting bodies to animal dispersers. Identifying the environmental factors and biotic interactions that shape fruit selection by animals is key to understanding the evolutionary processes that underpin chemical signaling. Using four Elaphomyces truffle species, we explored the role of fruiting depth, VOC emissions, and protein content in selection by five rodent species. We used stable isotope analysis of nitrogen (δ15N) in truffles to estimate fruiting depth, proton-transfer-reaction mass spectrometry to determine volatile emission composition, and nitrogen concentrations to calculate digestible protein of truffles. We coupled field surveys of truffle availability with truffle spore loads in rodent scat to determine selection by rodents. Despite presumably easier access to the shallow fruiting species, E. americanus (0.5-cm depth) and E. verruculosus (2.5-cm depth), most rodents selected for truffles fruiting deeper in the soil, E. macrosporus (4.1-cm depth) and E. bartlettii (5.0-cm depth). The deeper fruiting species had distinct VOC profiles and produced significantly higher quantities of odiferous compounds. Myodes gapperi (southern red-backed vole), a fungal specialist, also selected for truffles with high levels of digestible protein, E. verruculosus and E. macrosporus. Our results highlight the importance of chemical signals in truffle selection by rodents and suggest that VOCs are under strong selective pressures relative to protein rewards. Strong chemical signals likely allow detection of truffles deep within the soil and reduce foraging effort by rodents. Finally, for rodents that depend on fungi as a major food source, protein content may also be important in selecting truffles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Charged loops at the cosmological collider with chemical potential

Cosmological collider physics allows the detection of heavy particles at inflationary scales through their imprints on primordial non-Gaussianities. We study the chemical potential mechanism applied to a pair of charged scalars. We analytically evaluate the resulting one-loop contribution to the bispectrum, using the spectral decomposition. In this way we are able to determine the parametric dependencies for both the signal and the background. We show that a signal strength ${f}_{\text{NL}}\sim \mathcal{O}(0.01)$ can be obtained within theoretical control, potentially reachable by 21 cm tomography. As an application we consider the colored Higgs bosons in SU(5) supersymmetric orbifold grand unification with masses M ≲ 10$^{15}$ GeV.

Bodas, Arushi [Chicago U., EFI; Fermilab] (ORCID:0↗
DOE OSTI2023

Unusual modifications of protein biomarkers expressed by plasmid, prophage, and bacterial host of pathogenic Escherichia coli identified using top‐down proteomic analysis

Rationale Pathogenic bacteria often carry prophage (bacterial viruses) and plasmids (small circular pieces of DNA) that may harbor toxin, antibacterial, and antibiotic resistance genes. Proteomic characterization of pathogenic bacteria should include the identification of host proteins and proteins produced by prophage and plasmid genomes. Methods Protein biomarkers of two strains of Shiga toxin–producingEscherichia coli(STEC) were identified using antibiotic induction, matrix‐assisted laser desorption/ionization tandem time‐of‐flight (MALDI‐TOF‐TOF) tandem mass spectrometry (MS/MS) with post‐source decay (PSD), top‐down proteomic (TDP) analysis, and plasmid sequencing. Alphafold2 was also used to compare predicted in silico structures of the identified proteins to prominent fragment ions generated using MS/MS‐PSD. Strain samples were also analyzed with and without chemical reduction treatment to detect the attachment of pendant groups bound by thioester or disulfide bonds. Results Shiga toxin was detected and/or identified in both STEC strains. For the first time, we also identified the osmotically inducible protein (OsmY) whose sequence unexpectedly had two forms: a full and a truncated sequence. The truncated OsmY terminates in the middle of an α‐helix as determined by Alphafold2. A plasmid‐encoded colicin immunity protein was also identified with and without attachment of an unidentified cysteine‐bound pendant group (~307 Da). Plasmid sequencing confirmed top‐down analysis and the identification of a promoter upstream of the immunity gene that is activated by antibiotic induction, that is, SOS box. Conclusions TDP analysis, coupled with other techniques (e.g., antibiotic induction, chemical reduction, plasmid sequencing, and in silico protein modeling), is a powerful tool to identify proteins (and their modifications), including prophage‐ and plasmid‐encoded proteins, produced by pathogenic microorganisms.

Biochemistry & Molecular Biology↗
DOE OSTI2021

Intelligent Consequence Control by Aerial Reconnoiter Using Unmanned Systems

In a nuclear accident, or in the aftermath of an improvised nuclear device or radiological dispersal device detonation, radioactive materials may pose a severe health threat to individuals near the site of the incident. The Intelligent Consequence Control by Aerial Reconnoiter Using Unmanned Systems (ICARUS) does the dull, dirty, and dangerous (and, sometimes, deep) work of mapping and characterizing valuable information to enable a safe and appropriate response. ICARUS provides timely answers to the questions, “What is it?” “Where is it?”, and “How far does it extend?” Using commercial, off-the-shelf proven components, the integrated chemical, biological, radiological, nuclear, and explosives detection architecture for our drones provides a solution for collecting radiological, chemical, and optical information on developing complex situations, returning actionable data for determining if it is safe for further response efforts. ICARUS can determine and transmit the location, identity, and intensity of radionuclide contamination to a remote base station. It can deliver on the unexpected.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Np-237 LoD Measurement by TIMS-Multi-Ion Counting Total Evaporation [Poster]

Requests for ultra-low-level 237 Np analyses highlight the importance of a robust chemical purification and measurement technique for Np. In FY2022, LANL is quantifying the instrumental 237 Np LoD. Need to incorporate a chemical purification procedure for TIMS-MICTE sample preparation. What is the recovery of the chemical purification procedure? What is the ultimate detection limit that can be achieved while incorporating a chemical purification procedure? We have adapted and refined the Pu TIMS-MICTE method for Np analyses. We have determined expected uncertainties for 237 Np TIMS-MICTE measurements. We have increased sensitivity through technique improvements. We have improved method reliability for Np analyses and increased throughput. Apply knowledge gained from progress made in FY2022 to further develop Np sample purification and analyses by TIMSMICTE.

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

Entangled Photon Spectroscopy

Conspectus The enhanced interest in quantum-related phenomena has provided new opportunities for chemists to push the limits of detection and analysis of chemical processes. As some have called this the second quantum revolution, a time has come to apply the rules learned from previous research in quantum phenomena toward new methods and technologies important to chemists. While there has been great interest recently in quantum information science (QIS), the quest to understand how nonclassical states of light interact with matter has been ongoing for more than two decades. Our entry into this field started around this time with the use of materials to produce nonclassical states of light. Here, the process of multiphoton absorption led to photon-number squeezed states of light, where the photon statistics are sub-Poissonian. In addition to the great interest in generating squeezed states of light, there was also interest in the formation of entangled states of light. While much of the effort is still in foundational physics, there are numerous new avenues as to how quantum entanglement can be applied to spectroscopy, imaging, and sensing. These opportunities could have a large impact on the chemical community for a broad spectrum of applications. Here, we discuss the use of entangled (or quantum) light for spectroscopy as well as applications in microscopy and interferometry. The potential benefits of the use of quantum light are discussed in detail. From the first experiments in porphyrin dendrimer systems by Dr. Dong-Ik Lee in our group to the measurements of the entangled two photon absorption cross sections of biological systems such as flavoproteins, the usefulness of entangled light for spectroscopy has been illustrated. These early measurements led the way to more advanced measurements of the unique characteristics of both entangled light and the entangled photon absorption cross-section, which provides new control knobs for manipulating excited states in molecules. The first reports of fluorescence-induced entangled processes were in organic chromophores where the entangled photon cross-section was measured. These results would later have widespread impact in applications such as entangled two-photon microscopy. From our design, construction and implementation of a quantum entangled photon excited microscope, important imaging capabilities were achieved at an unprecedented low excitation intensity of 10 7 photons/s, which is 6 orders of magnitude lower than the excitation level for the classical two-photon image. New reports have also illustrated an advantage of nonclassical light in Raman imaging as well. From a standpoint of more precise measurements, the use of entangled photons in quantum interferometry may offer new opportunities for chemistry research. Experiments that combine molecular spectroscopy and quantum interferometry, by utilizing the correlations of entangled photons in a Hong–Ou–Mandel (HOM) interferometer, have been carried out. The initial experiment showed that the HOM signal is sensitive to the presence of a resonant organic sample placed in one arm of the interferometer. In addition, parameters such as the dephasing time have been obtained with the opportunity for even more advanced phenomenology in the future.

36 MATERIALS SCIENCE↗
DOE OSTI2021

(S)TEM-EELS as an advanced characterization technique for lithium-ion batteries

Although the lithium-ion battery (LIB) has acquired commercial success as a sustainable power source, it still suffers from multiple challenges for the future applications. In order to further develop next-generation batteries, the dynamics of structure change, charge transfer, and ion diffusion occurring inside the battery need to be deeply understood by advanced characterization techniques. (Scanning) transmission electron microscopy-electron energy loss spectroscopy ((S)TEM-EELS) is an effective method for the nano-scale detection of structural and chemical information in materials. Herein, this review systematically introduces the advantages and fundamentals of (S)TEM-EELS and its unique applications in LIBs.

25 ENERGY STORAGE↗
DOE OSTI2025

Integrating N -glycan and CODEX imaging reveal cell-specific protein glycosylation in healthy human lung

Identifying cell-specific glycan structures in human lungs is critical for understanding the chemistry and mechanisms that guide cell–cell and cell–matrix interactions and determining nuanced functions of specific glycosylation. Our dual-modality omics platform, which uses matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to profile glycan chemistry at 50 μm × 50 μm scale, combined with co-detection by indexing (CODEX) to provide cell identification from the exact same tissue section, is a significant step in this direction. It enabled us to detect, differentiate, and reveal chemical properties of N-glycans in the various cell types of a human lung, suggesting the cell-specific function of distinct carbohydrate moieties. This innovative technological combination bridges the gap between the specific protein glycosylation and their cellular origin, paving the way for targeted studies in the lungs and many other human tissues where glycans mediate cell–cell recognition events.

Veličković, Dušan [Pacific Northwest National Labo↗
DOE OSTI2026

matsim-agents v1.0

matsim-agents is a multi-agent AI framework for atomistic materials simulation and discovery. It orchestrates large language models (LLMs), machine-learned interatomic potentials (MLIPs), and DFT codes into a single agentic loop running on laptops and DOE leadership-class supercomputers. MULTI-AGENT ORCHESTRATION A LangGraph state machine with three nodes: a Planner that converts a natural-language research objective into structured tasks; an Executor that dispatches atomistic tools and loops until the queue is empty; and an Analyst that summarizes results into a human-readable report. State is checkpointed after every step and human-in-the-loop gates can be inserted at any edge. HYPOTHESIS-DRIVEN DISCOVERY CHAT An interactive REPL (matsim-agents chat) that couples LLM dialogue with atomistic simulation. Chemical formulas are automatically detected in conversation turns and trigger a full crystal-phase exploration: structure generation → relaxation → stability scoring → result injection back into the conversation, creating a closed hypothesis-refinement loop. CRYSTAL PHASE ENUMERATION Given a composition, the phase explorer enumerates prototypes by stoichiometry: elemental (fcc/bcc/hcp/sc/diamond), binary 1:1 (rocksalt/CsCl/zincblende/ wurtzite/fluorite/rutile), ternary 1:1:3 (cubic perovskite), ternary 1:2:4 (perovskite + spinel), quaternary 1:1:2:6 (Fm-3m double perovskite). 2-D prototypes (graphene, h-BN, MoS2 2H/1T) and multilayer stacking are also supported via --include-2d and --num-layers. SUPERCELL GENERATION AND SITE DECORATION Auto-tiling to a minimum atom count (--min-atoms), explicit NxNxN tiling (--supercell), symmetry-distinct site decorations (--n-orderings), and isotropic lattice-scale sweeps (--lattice-scales) for volume bracketing. MLFF RELAXATION AND STABILITY SCORING HydraGNN (multi-headed GNN) drives structure relaxation via ASE with FIRE, BFGS, or BFGSLineSearch. Stability output: delta-E/atom ranking across phases and a max-residual-force dynamical-stability proxy. Other MLIPs (MACE, NequIP, Orb) can be plugged in through the same interface. DFT BACKENDS Quantum ESPRESSO pw.x and VASP 6.6 are first-class labellers. Both have validated GPU builds and SLURM/PBS launchers for three DOE platforms: Frontier (AMD MI250X, ROCm), Aurora (Intel PVC, oneAPI), Perlmutter (NVIDIA A100, CUDA). QE produces ~100 binaries (pw.x, ph.x, epw.x, ...). VASP supports scf, relax, vc-relax, and vc-relax-shape run types. ACTIVE-LEARNING LOOP matsim-agents al run CONFIG.yaml drives an iterative HydraGNN-DFT loop: MD generates candidates → ensemble/MC-dropout uncertainty selects the most informative → DFT labels them in parallel inside one allocation → dataset grows → HydraGNN retrains → repeat. DFT backend is a single YAML toggle (dft.backend: vasp | qe). LLM-generated seed structures are supported (no curated POSCAR library needed). Config uses ${VAR}, ${VAR:-default}, ${VAR:?msg} shell-style substitution for cross-user/cross-site portability. LLM BACKENDS Ollama (local, default), vLLM (HPC multi-GPU serving), OpenAI, Anthropic, HuggingFace Transformers+Accelerate. Selected at runtime via flag or env var with no code changes. HPC PORTABILITY Same Python entry points run on Frontier (ROCm 7.2), Aurora (oneAPI), and Perlmutter (CUDA 12). DFT and ML stacks are never co-loaded in the same shell; they couple through the scheduler and filesystem. Advanced multi-node launchers (serve, discovery-chat, single-relaxation, active-learning, QE warm-start) are provided for all three platforms. CODABENCH COMPETITION BUNDLE A self-contained benchmark: 159 atomistic test structures across 11 material classes, 5 tasks (formation energy, forces, ML relaxation, AI-DFT relaxation, phase stability ranking), public/private leaderboard split (30/70), and four ready-to-run baselines: MACE-MP-0, HydraGNN, UMA, AllScAIP.

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗
DOE OSTI2022

Complex-Valued Signal Denoising and Bayesian Optimization for Detection of Synthetic Opioids [Slides]

Overseas manufacturers ship synthetic opioids into the United States through international mail. Synthetic opioids are largely responsible for the overdose crisis in the United States. Nuclear Quadrupole Resonance (NQR) spectroscopy is a chemical analysis technique used for detection. The ultimate goal is to develop a technology capable of detecting the presence of synthetic opioids in unopened packages using NQR spectroscopy.

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

Lithological controls on soil geochemistry and clay mineralogy across Spodosols in the coastal temperate rainforest of southeast Alaska

The interaction of similar soil forming factors with different parent materials determines soil chemical weathering, influencing soil processes and properties. In the coastal temperate rainforests of southeast Alaska, Spodosols is the dominant soil order in well-drained parent materials regardless of the lithology. Yet, the role of lithology on chemical weathering, base cation depletion, and mineral transformation during pedogenesis remains elusive. Here, we established a lithosequence comprised of soils derived from tonalite, phyllite, slate, and metavolcanic rocks to test the hypothesis that despite the soils in southeast Alaska presenting similar taxonomy and morphology, the influence of lithology in chemical weathering intensity and mineralogy can be detected. We evaluated physicochemical properties, clay mineralogy, Fe-Al oxides, chemical weathering, and elemental mass balance on eleven Spodosols sampled along the lithosequence. We also propose a new weathering index, the Weathering Index for Spodosols (WISP), suitable to evaluate the weathering degree of soils with Al mobility and base-rich parent materials. This index fills a gap in traditional weathering indices that uses Al as an immobile element and/or does not evaluate the leaching of main base cations. We found the pedons across the lithosequence expressed similar physicochemical properties, with predominantly thick profiles, presenting andic properties, relatively thick spodic horizons, and thin E horizons. Podzolization imposed similar mineral transformation trends, mainly dissolution of chlorite, mica alteration to interstratified mica-vermiculite, and formation of smectite in E horizons. Kaolinite was detected in the soils from all lithologies, but only in trace amounts in phyllite soils. Fe oxides depth distribution was similar but with a higher concentration in the slate (44.5 ± 4.2 g/kg), followed by metavolcanic (31.6 ± 4.0 g/kg), phyllite (27.9 ± 3.8 g/kg), and tonalite soils (19.9 ± 5.7 g/kg) and predominantly as organometallic complexes (extracted by Na-pyrophosphate). The stronger weathering of chlorite and mica in the E horizons was reflected in larger losses of Mg and K, while Ca and Na were more depleted in the spodic horizons, suggesting plagioclase weathering. Slate soils were the most depleted in base cations, followed by phyllite, tonalite, and metavolcanic soils. The more depleted status of slate soils was supported by the higher WISP values (WISP = 62), followed by phyllite (WISP = 55), tonalite (WISP = 53), and metavolcanic soils (WISP = 45). Our results demonstrated that lithology controlled elemental depletion intensities, Fe oxide concentrations, and partially the clay fraction mineralogy in addition to podzolization acting as a dominant pedogenic process across all sites. These findings advance our understanding of the role of lithology on soil mineralogy/geochemistry that impacts critical soil functions, such as the soil carbon cycle, elemental fluxes, organo-mineral interactions, and solid-solution reactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Fiber optic system for direct detection of CO 2 leakage in carbon storage wells (Abbreviated Final Report)

The feasibility study focused on the development of new fiber for distributed chemical sensing that will allow direct detection of CO2 leakages in the environment. This is particularly important for monitoring well integrity for carbon capture and storage (CSS), which can provide early warning for an incoming well failure and potential CO2 leaking through it. We proposed Raman or IR interrogation within gas-filled Holey Fibers (HoFs) interleaved with Fiber Bragg Grating (FBG) sections, so that the location and concentration of the gases would be provided simultaneously. The methodology would overcome current roadblocks to using fiber optics for CO2 (and other gases) detection in wells with direct in-situ measurements of concentration along with other important parameters such as temperature and pressure. We were able to assess commercially available IR/Raman hollow core fiber and demonstrated detection of CO2 through them in our controlled environment setups at various pressure conditions. We have also established the ability of drilling precisely with fs-lases side holes to enable penetration of CO2 into the hollow core fiber and reduce diffusion rates. Open joint collars were also explored with double functionality: to obtain splice to solid core fiber critical for field deployment and create gas ingress locations. Both diffusion-only and pressurized fiber system have been constructed following COMSOL based semi-hybrid optical /fluidodynamics models. FBGs have been identified and procured and characterized. Along the work we leveraged internal modeling/design, photonics/laser characterization, optical fiber fabrication, and AM lab capabilities to design, develop and test in-house components or assemblies. Our results indicate the potential of HoF for CO2 downhole direct detection.

25 ENERGY STORAGE↗
DOE OSTI2025

A Synchrotron-Based Vacuum Ultraviolet Photoionization Mass Spectrometer-Coupled Microreactor To Probe Thermocatalysis

Vacuum ultraviolet photoionization (VUV-PI) mass spectrometry offers an isomer-selective and universal ionization with minimal fragmentation detection of organics in complex chemical systems such as pyrolysis and combustion. Here, in this study, we report a state-of-the-art experimental setup of a universal catalytic microreactor combined with a molecular beam to investigate the thermocatalytic oxidation of a heterogeneous system relevant for probing reactions at gas–solid interfaces. In strong contrast to traditional off-line analytical methods, this technique is capable of identifying and quantifying short-lived species (radicals) as well as stable products to decipher initial reaction steps via the detection of nascent products. The thermocatalytic oxidative degradation of exo-tetrahydrodicyclopentadiene (JP-10), a high energy-density hydrocarbon fuel, over solid titanium–aluminum–boron reactive mixed metal nanopowder (Ti-Al-B RMNP) is exploited to showcase potential applications. Overall, some 59 nascent gas-phase products are identified via photoionization efficiency (PIE) curves, including oxygenated species and hydrocarbons comprising closed-shell molecules and radicals. The critical temperature for complete oxidative decomposition of JP-10 was lowered by 450 K from 1400 K to 950 K, indicating an efficient thermocatalytic action of Ti-Al-B nanoparticles on JP-10. The enabling of a universal chemical microreactor along with VUV-PI mass spectrometry broadens the applicability of this technique to hydrocarbon fuel oxidation and pyrolysis characterization. This isomer-selective sensitive probing along with the detection of radical transients makes the aforementioned technique superior to other conventional analytical techniques such as microflow tube and pyrolysis-gas chromatography coupled with mass spectrometry for investigating similar pyrolysis reactions and comprehensive quantification.

Paul, Dababrata [Univ. of Hawaii at Manoa, Honolul↗
DOE OSTI2023

Detecting driving potentials at the buried SiO 2 nanolayers in solar cells by chemical-selective nonlinear x-ray spectroscopy

We present an approach to selectively examine an asymmetric potential in the buried layer of solar cell devices by means of nonlinear x-ray spectroscopy. Detecting second harmonic generation signals while resonant to the SiO 2 core level, we directly observe existence of the band bending effect in the SiO 2 nanolayer, buried in the heterostructures of Al/LiF/SiO 2 /Si, TiO 2 /SiO 2 /Si, and Al 2 O 3 /SiO 2 /Si. Furthermore, the results demonstrate high sensitivity of the method to the asymmetric potential that determines performance of functional materials for photovoltaics or other optoelectronic devices.

14 SOLAR ENERGY↗
DOE OSTI2021

MetFish: a Metabolomics Pipeline for Studying Microbial Communities in Chemically Extreme Environments

Metabolites have essential roles in microbial communities, including as mediators of nutrient and energy exchange, cell-to-cell communication, and antibiosis. However, detecting and quantifying metabolites and other chemicals in samples having extremes in salt or mineral content using liquid chromatography-mass spectrometry (LC-MS)-based methods remains a significant challenge. Here, we report a facile method based on in situ chemical derivatization followed by extraction for analysis of metabolites and other chemicals in hypersaline samples, enabling for the first time direct LC-MS-based exometabolomics analysis in sample matrices containing up to 2 M total dissolved salts. The method, MetFish, is applicable to molecules containing amine, carboxylic acid, carbonyl, or hydroxyl functional groups, and it can be integrated into either targeted or untargeted analysis pipelines. In targeted analyses, MetFish provided limits of quantification as low as 1 nM, broad linear dynamic ranges (up to 5 to 6 orders of magnitude) with excellent linearity, and low median interday reproducibility (e.g., 2.6%). MetFish was successfully applied in targeted and untargeted exometabolomics analyses of microbial consortia, quantifying amino acid dynamics in the exometabolome during community succession; in situ in a native prairie soil, whose exometabolome was isolated using a hypersaline extraction; and in input and produced fluids from a hydraulically fractured well, identifying dramatic changes in the exometabolome over time in the well.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A Significant Increase in Detection of High-resolution Emission Spectra Using a Three-dimensional Atmospheric Model of a Hot Jupiter

High-resolution spectroscopy has opened the way for new, detailed study of exoplanet atmospheres. There is evidence that this technique can be sensitive to the complex, three-dimensional (3D) atmospheric structure of these planets. In this work, we perform cross-correlation analysis of high-resolution (R ∼ 100,000) CRIRES/VLT emission spectra of the hot Jupiter HD 209458b. We generate template emission spectra from a 3D atmospheric circulation model of the planet, accounting for temperature structure and atmospheric motions—winds and planetary rotation—missed by spectra calculated from one-dimensional models. In this first-of-its-kind analysis, we find that using template spectra generated from a 3D model produces a more significant detection (6.9σ) of the planet’s signal than any of the hundreds of one-dimensional models we tested (maximum of 5.1σ). We recover the planet’s thermal emission, its orbital motion, and the presence of CO in its atmosphere at high significance. Additionally, we analyzed the relative influences of 3D temperature and chemical structures in this improved detection, including the contributions from CO and H{sub 2}O, as well as the role of atmospheric Doppler signatures from winds and rotation. This work shows that the hot Jupiter’s 3D atmospheric structure has a first-order influence on its emission spectra at high resolution and motivates the use of multidimensional atmospheric models in high-resolution spectral analysis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗