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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

PhotonIDs: ML-Powered Photon Identification System for Dark Count Elimination

Reliable single photon detection is the foundation for practical quantum communication and networking. However, today's superconducting nanowire single photon detector(SNSPD) inherently fails to distinguish between genuine photon events and dark counts, leading to degraded fidelity in long-distance quantum communication. In this work, we introduce PhotonIDs, a machine learning-powered photon identification system that is the first end-to-end solution for real-time discrimination between photons and dark count based on full SNSPD readout signal waveform analysis. PhotonIDs ~demonstrates: 1) an FPGA-based high-speed data acquisition platform that selectively captures the full waveform of signal only while filtering out the background data in real time; 2) an efficient signal preprocessing pipeline, and a novel pseudo-position metric that is derived from the physical temporal-spatial features of each detected event; 3) a hybrid machine learning model with near 98% accuracy achieved on photon/dark count classification. Additionally, proposed PhotonIDs ~ is evaluated on the dark count elimination performance with two real-world case studies: (1) 20 km quantum link, and (2) Erbium ion-based photon emission system. Our result demonstrates that PhotonIDs ~could improve more than 31.2 times of signal-noise-ratio~(SNR) on dark count elimination. PhotonIDs ~ marks a step forward in noise-resilient quantum communication infrastructure.

Linne, Karl C. [Chicago U.] (ORCID:000900091870358↗
DOE OSTI2022

On the use of vibronic coherence to identify reaction coordinates for ultrafast excited-state dynamics of transition metal-based chromophores

In this study, the question of whether one can use information from quantum coherence as a means of identifying vibrational degrees of freedom that are active along an excited-state reaction coordinate is discussed. Specifically, we are exploring the notion of whether quantum oscillations observed in single-wavelength kinetics data exhibiting coherence dephasing times that are intermediate between that expected for either pure electronic or pure vibrational dephasing are vibronic in nature and therefore may be coupled to electronic state-to-state evolution. In the case of a previously published Fe(ιι) polypyridyl complex, coherences observed subsequent to 1 A 1 → 1 MLCT excitation were linked to large-amplitude motion of a portion of the ligand framework; dephasing times on the order of 200–300 fs suggested that these degrees of freedom could be associated with ultrafast (~100 fs) conversion from the initially formed MLCT excited state to lower-energy, metal-centered ligand-field excited state(s) of the compound. Incorporation of an electronically benign but sterically restrictive Cu(ι) ion into the superstructure designed to interfere with this motion yielded a compound exhibiting a ~25-fold increase in the compound’s MLCT lifetime, a result that was interpreted as confirmation of the initial hypothesis. However, new data acquired on a different chemical system – Cr(acac') 3 (where acac' represents various derivatives of acetylacetonate) – yielded results that call into question this same hypothesis. Coherences observed subsequent to 4 A 2 → 4 T 2 ligand-field excitation on a series of molecules implicated similar vibrational degrees of freedom across the series, but exhibited dephasing times ranging from 340 fs to 2.5 ps without any clear correlation to the dynamics of excited-state evolution in the system. Taken together, the results obtained on both of these chemical platforms suggest that while identification of coherences can indeed point to degrees of freedom that should be considered as candidate modes for defining reaction trajectories, our understanding of the factors that determine the interplay across coherences, dephasing times, and electronic and geometric structure is insufficient at the present time to view this parameter as a robust metric for differentiating active versus spectator modes for ultrafast dynamics.

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

Chemical mechanisms and kinetic modeling of calcium aluminate cements hydration in diluted systems: Role of aluminium hydroxide formation

Calcium aluminate cements are niche cements used in the refractory industry and in non-structural applications for building chemistry with short return-to-service delay. The later applications use theses cements in combination with calcium sulfates for long-term stability. By being niche cements, the knowledge of calcium aluminate cements hydration is not as extensive as that of Portland cement. In the present paper, the calcium aluminate cements are studied in diluted suspensions as a function of different parameters such as the suspension concentration or the quantity of added calcium sulfates. The objective is to identify their baseline chemical mechanisms. This work demonstrates the essential role of hydroxide ions fluxes, i.e. quantity going in and out of the liquid phase per unit of time. The main quantitative flux is the formation of aluminium hydroxide but the activation of this reaction is difficult. This difficulty allows calcium aluminate to be used as cement by creating a dormant period (workability) for the overall reactivity. The identification of the key role of aluminium hydroxide formation explains the influence of the temperature, some mechanisms of setting admixtures and the early age of calcium aluminate cements.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Shifting modes of iron sulfidization at the onset of OAE-2 drive regional shifts in pyrite δ 34 S records

We report total reduced inorganic S isotope ratios (δ 34 S CRS ) shift toward more negative values across much of the southern North Atlantic just before the onset of the Cenomanian-Turonian Ocean Anoxic Event (OAE-2). At the same time, there is no parallel isotopic change in the significantly larger pool of kerogen (organic) S, which indicates that the distribution and S-isotope composition of sulfide in the environment likely did not drive the change in δ 34 S CRS . Here, we investigate possible explanations for the negative shift in δ 34 S CRS values and their divergence from organic S by isolating iron sulfides for morphological identification and grain-specific isotopic analysis using secondary ion mass spectrometry (SIMS). In pre- and syn-OAE-2 sedimentary rocks from Demerara Rise, we find four distinct morphologies of iron sulfides: pyrite framboids (1–20 μm diameter), irregular pyrite aggregates (1–38 μm diameter), large cemented pyrite aggregates (~60 μm diameter), and irregular and cemented aggregates of the pyrite polymorph marcasite (1–45 μm diameter). These different textural groups have distinct S-isotopic compositions that are largely consistent through the onset of OAE-2. As such, the secular change in bulk δ 34 S CRS values likely reflects the changing proportions of these phases stratigraphically across OAE-2. All textural groups feature resolvable intra-grain δ 34 S variability, suggesting that the environments in which they formed were characterized by dynamic sulfide δ 34 S values and/or by partial closed-system distillation. We use grain-specific δ 34 S distributions to rule out shoaling of the chemocline within the sediments as a mechanism for the observed decrease in δ 34 S CRS . Instead, we propose that changes in the reactivity of the iron species delivered to Demerara Rise over the ~200 kyr leading up to the onset of OAE-2 impacted the relative contributions of pyrite with S-isotope signatures reflecting the water column, shallow sediments, and deeper sediments to the bulk sedimentary δ 34 S CRS value. Specifically, the change in iron reactivity at the onset of OAE-2 favored the production of 34 S-depleted large, cemented aggregates and framboids at the expense of more 34 S-enriched irregular aggregates. Our results underscore that bulk δ 34 S CRS measurements integrate multiple reduced phases that form via distinct reaction mechanisms and potentially in different parts of the depositional environment. Grain-specific SIMS analyses dramatically enrich our ability to interpret pyrite isotopic patterns in the geologic record.

58 GEOSCIENCES↗
DOE OSTI2022

SAXS-guided unbiased coarse-grained Monte Carlo simulation for identification of self-assembly nanostructures and dimensions

Recent studies have shown that solvated amphiphiles can form nanostructured self-assemblies called dynamic binary complexes (DBCs) in the presence of ions. Since the nanostructures of DBCs are directly related to their viscoelastic properties, it is important to understand how the nanostructures change under different solution conditions. However, it is challenging to obtain a three-dimensional molecular description of these nanostructures by utilizing conventional experimental characterization techniques or thermodynamic models. To this end, we combined the structural data from small angle X-ray scattering (SAXS) experiments and thermodynamic knowledge from coarse-grained Monte Carlo (CGMC) simulations to identify the detailed three-dimensional nanostructure of DBCs. Specifically, unbiased CGMC simulations are performed with SAXS-guided initial conditions, which aids us to sample accurate nanostructures in a computationally efficient fashion. As a result, an elliptical bilayer nanostructure is obtained as the most probable nanostructure of DBCs whose dimensions are validated by scanning electron microscope (SEM) images. Then, utilizing the obtained molecular model of DBCs, here we could also explain the pH tunability of the system. Overall, our results from SAXS-guided unbiased CGMC simulations highlight that using potential energy combined with SAXS data, we can distinguish otherwise degenerate nanostructures resulting from the inherent ambiguity of SAXS patterns.

36 MATERIALS SCIENCE↗
DOE OSTI2023

How reliable is distribution of relaxation times (DRT) analysis? A dual regression-classification perspective on DRT estimation, interpretation, and accuracy

The distribution of relaxation times (DRT) has gained increasing attention and adoption in recent years as a versatile method for analyzing electrochemical impedance spectroscopy (EIS) data obtained from complex devices like fuel cells, electrolyzers, and batteries. The DRT deconvolutes the impedance without a priori specification of a generative model, which is especially useful for interpretation and model selection when the governing principles of the system under study are not fully understood. However, DRT estimation is an ill-posed inversion problem that must be addressed with a subjective choice of regularization and tuning, which leaves substantial risk of misleading interpretations of EIS data. In this work, we suggest a new classification view of the DRT inversion to clarify DRT estimation and interpretation. We introduce a dual regression-classification framework that unifies the classification and regression views of the DRT inversion with wide-reaching implications for DRT analysis. The dual framework is employed to demonstrate a new kind of DRT inversion algorithm and develop novel evaluation metrics that capture previously ignored aspects of DRT accuracy. These approaches are applied to both synthetic data and experimental spectra collected from a protonic ceramic fuel cell and a lithium-ion battery to illustrate their broad utility. The dual inversion algorithm shows promising performance for accurate DRT estimation and autonomous model identification, while the dual evaluation approach produces metrics that meaningfully assess the strengths and risks of DRT algorithms. Here this work provides valuable insight for both practical application of the DRT to experimental data and further development of EIS analysis methods.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The CHIMERAS project: design framework for the Collisionless HIgh-beta Magnetized Experiment Researching Astrophysical Systems

From the near-Earth solar wind to the intracluster medium of galaxy clusters, collisionless, high-beta, magnetized plasmas pervade our universe. Energy and momentum transport from large-scale fields and flows to small-scale motions of plasma particles is ubiquitous in these systems, but a full picture of the underlying physical mechanisms remains elusive. The transfer is often mediated by a turbulent cascade of Alfvénic fluctuations as well as a variety of kinetic instabilities; these processes tend to be multi-scale and/or multi-dimensional, which makes them difficult to study using spacecraft missions and numerical simulations alone. Meanwhile, existing laboratory devices struggle to produce the collisionless, high ion beta (β i ≳ 1), magnetized plasmas across the range of scales necessary to address these problems. As envisioned in recent community planning documents, it is therefore important to build a next generation laboratory facility to create a β i ≳ 1, collisionless, magnetized plasma in the laboratory for the first time. A working group has been formed and is actively defining the necessary technical requirements to move the facility towards a construction-ready state. Recent progress includes the development of target parameters and diagnostic requirements as well as the identification of a need for source-target device geometry. As the working group is already leading to new synergies across the community, we anticipate a broad community of users funded by a variety of federal agencies (including National Aeronautics and Space Administration, Department of Energy and National Science Foundation) to make copious use of the future facility.

astrophysical plasmas↗
DOE OSTI2021

Level structure of the T z = –1 nucleus 34 Ar and its relevance for nucleosynthesis in ONe novae

The 24 Mg+ 12 C fusion reaction was used to perform a detailed γ-ray spectroscopy study of the astrophysically important nucleus 34 Ar. In particular, an experimental setup, coupling the advanced γ-ray tracking array GRETINA with the well-established Argonne fragment mass analyzer (FMA), was employed to obtain excitation energies and spin-parity assignments for excited states in 34 Ar, both above and below the proton separation energy. For the first time, an angular distribution analysis of in-beam γ rays from fusion-evaporation reactions, using a tracking array, has been performed and Coulomb energy differences of analog states in the T = 1, A = 34 mirror system, explored from 0 to 6 MeV. Lastly, we present a comprehensive discussion of the astrophysical 33 Cl(p,γ) stellar reaction rate, together with implications for the identification of nova presolar grains from sulfur isotopic abundances.

20 ≤ A ≤ 38↗
DOE OSTI2021

Magnetoelastic effects in the hyperhoneycomb Kitaev spin liquid

In recent years, several magnetic Mott insulators with strong spin-orbit coupling were suggested to be proximate to the Kitaev quantum spin liquid, whose one of the most exciting features is the fractionalization of spin excitations into itinerant Majorana fermions and static Z 2 fluxes. Unfortunately, the ground states of these systems cannot be easily captured by experiment, remaining featureless to conventional local probes. Here, we propose to study the signatures of fractionalized excitations by exploiting their coupling to the lattice vibrations, dubbed magnetoelastic coupling, which arises from the fact that the interaction between spins depends on the relative distance between them. We argue that the magnetoelastic coupling can lead to the distinct modification of the phonon dynamics, which can be observed by measuring renormalized phonon spectrum, the sound attenuation, and the phonon Hall viscosity. This makes the phonon dynamics a promising tool for the characterization and identification of quantum spin liquid phases. In this work, we focus on the magnetoelastic effects in the three-dimensional Kitaev model realized on the hyperhoneycomb lattice. Here, the hyperhoneycomb Kitaev spin liquid is particularly interesting since the strong Kitaev interaction was observed in the Kitaev magnet β-Li 2 IrO 3 , for which the spin-orbit entangled J eff = 1/2 moments of iridium ions form precisely the hyperhoneycomb lattice.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Agilent CRADA (Abstract)

The CRADA between Agilent Technologies Inc. and Battelle will focus on five software components as listed below: Prototype 4D Feature Finding functionality with a particular focus on recovering low level features and extending the bottom end dynamic range of IM-MS technology. Compare and contrast developments to current 4D Feature Finding capabilities. Highlight important algorithmic aspects employed. Implement the PNNL saturation correction algorithm. Agilent will give PNNL the needed data file access API and assistance in understanding it implementation and any needed instrumental aspects. Supported high resolution products to include Agilent’s TOF, QTOF and IM-QTOF mass spectrometers. PNNL will then work with Agilent to benchmark performance. Implementation of the PNNL Hadamard de-multiplexing algorithm. Agilent will give provide PNNL the needed date file access API access and as needed assistance in understanding the current Agilent multiplexed IM offering. PNNL will then work with Agilent on benchmark performance. Add ion mobility collision cross sections to existing and new metabolomic libraries for data analysis with Agilent’s informatics program MPP/ID Browser. PNNL will work with Agilent to create a software pipeline that takes data from chemical and metabolic standards and properly formats it for inclusion in MPP accessible libraries, using the collision cross section as a new separation dimension. Improvements of MPP multidimensional matching to identify metabolomic features using multiple characteristics beyond retention time and accurate mass. Most significantly matching will include analyte collision cross section with proposed support for sample fraction or RapidFire cartridge and fragmentation spectra. PNNL will work with Agilent to modify and improve the current MPP analysis pipeline to allow for creating, aligning, and identifying MS features defined by accurate mass, collision cross section and chromatographic retention time. As additional criteria such as fraction or RapidFire cartridge type are supported in the identification process, then they also will become part of the automation workflow. This includes the automation of said system to work with command line program (i.e. not a GUI) sufficient for programmatic execution in a pipeline.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Machine-Learning Assisted Identification of Battery Life Models

Predictive battery life models are commonly utilized to extrapolate degradation trends observed during accelerated aging tests for simulation of degradation in real-world applications. Thus, fitting accelerated aging data as accurately as possible and with low uncertainty is crucial for making believable projections of battery lifetime, but it is challenging to identify algebraic expressions that accurately fit multivariate degradation trends. A review of models published in literature reveal some common expressions for fitting calendar aging data, which is only dependent on temperature and state-of-charge, but no consistency across many models for fitting cycle aging data, indicating the need for a statistically rigorous data driven approach for developing empirical models. This talk will describe a machine-learning assisted method for identification of predictive battery life models utilizing bilevel optimization and symbolic regression. Bilevel optimization with cross-validation is used to statistically determine cell- and stress-dependent model parameters, while symbolic regression identifies both linear and multiplicative candidate expressions to predict stress-dependent degradation rates by selecting low-order subsets of features from a generated feature library. Because model expressions are identified empirically, it is crucial to ensure resulting models behave according to physical expectations, so the stability of models for interpolation or extrapolation is interrogated qualitatively through simulation and quantitatively through cross-validation and uncertainty quantification via bootstrap resampling. This model identification approach substantially improves upon models identified purely using expert judgement in terms of both accuracy and uncertainty. Model simulation and validation is then conducted by deriving a state-equation form of the predictive model, enabling simulation of battery aging under dynamic stresses. This enables validation of the predictive battery model on lab-based tests with varying conditions or on drive-cycle or application-cycle testing protocols. Parameter uncertainty can be carried forward into model simulation, giving lifetime estimates and confidence windows for cell- or system-level lifetime. The financial impact of battery model uncertainty can be estimated by incorporating uncertainty into a technoeconomic model.

battery↗
DOE OSTI2023

Correlative chemical and elemental nano-imaging of morphology and disorder at the nacre-prismatic region interface in Pinctada margaritifera

Abstract Understanding biomineralization relies on imaging chemically heterogeneous organic–inorganic interfaces across a hierarchy of spatial scales. Further, organic minority phases are often responsible for emergent inorganic structures from the atomic arrangement of different polymorphs, to nano- and micrometer crystal dimensions, up to meter size mollusk shells. The desired simultaneous chemical and elemental imaging to identify sparse organic moieties across a large field-of-view with nanometer spatial resolution has not yet been achieved. Here, we combine nanoscale secondary ion mass spectroscopy (NanoSIMS) with spectroscopic IR s -SNOM imaging for simultaneous chemical, molecular, and elemental nanoimaging. At the example of Pinctada margaritifera mollusk shells we identify and resolve ~ 50 nm interlamellar protein sheets periodically arranged in regular ~ 600 nm intervals. The striations typically appear ~ 15 µm from the nacre-prism boundary at the interface between disordered neonacre to mature nacre. Using the polymorph distinctive IR-vibrational carbonate resonance, the nacre and prismatic regions are consistently identified as aragonite ( $${\overline{\nu }}_{a}=860$$ ν ¯ a = 860 cm −1 ) and calcite ( $${\overline{\nu }}_{c}=880$$ ν ¯ c = 880 cm −1 ), respectively. We observe previously unreported morphological features including aragonite subdomains encapsulated in extensions of the prism-covering organic membrane and regions of irregular nacre tablet formation coincident with dispersed organics. We also identify a ~ 200 nm region in the incipient nacre region with less well-defined crystal structure and integrated organics. These results show with the identification of the interlamellar protein layer how correlative nano-IR chemical and NanoSIMS elemental imaging can help distinguish different models proposed for shell growth in particular, and how organic function may relate to inorganic structure in other biomineralized systems in general.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

ToF-SIMS spectral data analysis of Paenibacillus sp. 300A biofilms and planktonic cells

Analysis of bacterial biofilms is particularly challenging and important with diverse applications from systems biology to biotechnology. Among the variety of techniques that have been applied, time-of-flight secondary ion mass spectrometry (ToF-SIMS) has many promising features in studying the surface characteristics of biofilms. ToF-SIMS offers high spatial resolution and high mass accuracy, which permit surface sensitive analysis of biofilm components. Thus, ToF-SIMS provides a powerful solution to addressing the challenge of bacterial biofilm analysis. This dataset covers ToF-SIMS analysis of Paenibacillus sp. 300A (300A) isolated from the Hanford site in Richland, WA. The strain is known to have metal and sulfur reducing properties and can be used for bioremediation, wastewater treatment, bioengineering and technology development. There is a current need to identify small molecules and fragments produced from bacterial biofilms. Static ToF-SIMS spectra of 300A were obtained using an IONTOF TOF-SIMS V instrument equipped with a 25 keV Bi 3 + metal ion gun. Identified molecules and molecular fragments are compared against known biological databases and the reported peaks have at least 65 ppm mass accuracy. These molecules range from lipids and fatty acids to flavonoids, quinolones, and other naturally occurring organic compounds. It is anticipated that the spectral identification of key peaks will assist detection of metabolites, extracellular polymeric substance molecules like polysaccharides, and biologically relevant small molecules using ToF-SIMS in future surface and interface research of bacterial biofilms.

Biofilms↗
DOE OSTI2020

An Improved Boosting to Amplify Signal with Isobaric Labeling (iBASIL) Strategy for Precise Quantitative Single-cell Proteomics

Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100×) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ~2500 proteins and precise quantification of ~1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

FY 23 Filtration of Hanford Tank 241-SY-101 Supernatant at 16 °C

Approximately 9 liters of supernatant from Hanford waste tank 241-SY-101 was delivered by Washington River Protection Solutions to the Radiochemical Processing Laboratory (RPL) at Pacific Northwest National Laboratory. The thirty-six SY-101 sample bottles were comprised of six sets of six samples, with each set pulled from a unique tank sampling level. Prior to testing, samples from each level were composited to provide nominally level-independent feed for dead end filtration and ion exchange testing. The composited 241-SY-101 supernatant was chilled to 16 °C for 1 week prior to testing. Filtration testing was then conducted using a backpulse dead-end filter (BDEF) system equipped with a feed vessel and a Mott inline filter Model 6610 (Media Grade 5) in the hot cells of the RPL. This was done to provide waste processing benchmarks for 200 West Area wastes in the West Area Risk Management project. The feed was filtered through the BDEF system at a targeted flux of 0.065 gpm/ft 2 . During filtration of the differential pressure required to effect filtration at 0.065 gpm/ft 2 increased little over the filtration campaign and never reached 2 psid (the Tank Side Cesium Removal system action limit). This indicates that the Media Grade 5 filter should perform well when processing SY-101 supernatant. After completing filtration of the SY-101 feed, the filter was cleaned. Solids concentrated from the backpulse solutions displayed calcium phosphate, aluminum oxides, aluminum-chromium nanoparticle agglomerates. Electron diffraction was used to determine the types of phases that were present in the solids. Most of the phases found were only weakly crystalline, possibly owing to their rapid precipitation during the process water treatment. The identifications of the phases therefore are tentative.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Multiscale Cryo Electron Microscopy Reveals Interfacial Degradation and Stabilization in Battery Electrodes

Electrochemical interfaces are dynamic systems, evolving based on their local environment and reactant surface structures. The electrode-electrolyte interface in Li-ion batteries can be protective, limiting parasitic reactions with the electrolyte to passivate the surface [1]. Additionally, this interphase has an impact on the Li-ion transport through that layer based on its composition, bonding environment, and thickness. These parameters are challenging to collect and may vary depending on the electrode surface site investigated relative to its spatial position in a coin cell. This study will detail a multiscale cryogenic electron microscopy approach where millimeter-scale cross-sections through the coin cell batteries were made using a cryogenic stage within a fs-laser plasma focused ion beam (laser PFIB) with complementary energy dispersive X-ray spectroscopy able to detect variations in the composition at electrode interfaces [2]. Microscale cross-sectioning and lamella sample preparation of battery electrodes was conducted at the Center for Integrated Nanotechnologies using a Ga-ion focused ion beam (FIB) with air-free and cryo-transfer [3], followed by nanoscale mapping of composition and bonding within the CEI through cryo-scanning transmission electron microscopy (cryo-STEM) electron energy loss spectroscopy [4]. This multiscale approach enabled identification of millimeter-scale features of a battery stack with visualization of degradation in electrodes such as cracks in cathode particles, gas evolution, and SEI evolution; microscale interfacial characteristics, such as heterogeneity in the SEI or barrier layer and identification of electrolyte networks to the electrode surfaces; and nanoscale measurement of the CEI thickness, mapping of transition metal bonding within the cathode particles to identify loss of active materials, and identification of beneficial electrolyte additives incorporated into the CEI structure. This multiscale approach allows for a statistical understanding of the primary mechanisms and parasitic degradation pathways that impact performance by limiting the ion transport pathways within Li+ batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Annotation of DOM metabolomes with an ultrahigh resolution mass spectrometry molecular formula library

Current approaches to analyzing metabolomic data often rely on matching MS/MS fragmentation data to sparse libraries or databases. This approach results in limited identification of features, often with less than 10% of the dataset being annotated. A complementary approach is to assign molecular formula to features based on accurate mass measurements, but the platforms commonly used for metabolomics do not have the needed accuracy or resolving power to do this robustly, particularly for larger molecules. Using our newly modified analysis tool, CoreMS, we generated a library of molecular formula from pooled samples analyzed with LC-21T FT-ICR MS. This library successfully annotated approximately 53.2% of features identified from the exometabolome of marine diatom Phaeodactylum tricornutum – a nearly ten-fold increase over the 5.9% annotation rate achieved using a conventional MS/MS library matching approach. Using this FT-ICR MS library approach, we were able to differentiate differences in the exometabolome of P. tricornutum in iron replete and iron limited conditions, with 668 metabolites being differentially expressed (p < 0.05, 2 x intensity difference) under these conditions. The traditional MS/MS fragmentation-based annotation approach only annotated 61 of these metabolites, while our novel pipeline annotated 450 metabolites and revealed 12 metabolites that were significantly more abundant under low iron conditions. Our results demonstrate the utility of ultrahigh resolution mass spectrometry for generating more comprehensive and confident molecular annotations.

21T-FTICR-MS, CoreMS↗
DOE OSTI2024

ToF-SIMS spectral analysis of Shewanella oneidensis MR-1 biofilms

Analysis of bacterial biofilms is particularly challenging and important with diverse applications from systems biology to biotechnology. Among the variety of techniques that have been applied, time-of-flight secondary ion mass spectrometry (ToF-SIMS) has many powerful features in studying the surface characteristics of biofilms. ToF-SIMS offers high spatial resolution, mass resolution, and mass accuracy, which permit surface sensitive analysis of biofilm components. Thus, ToF-SIMS provides a powerful solution to addressing the challenge of bacterial biofilm analysis. This dataset covers ToF-SIMS analysis of Shewanella oneidensis MR-1 isolated from freshwater lake sediment in New York state. The MR-1 strain is known to have metal and sulfur reducing properties and it can be used for bioremediation and wastewater treatment. There is a current need to identify small molecules and fragments produced from bacterial biofilms, especially those from extracellular polymeric substance (EPS). Static ToF-SIMS spectra of MR-1 were obtained using an IONTOF TOF.SIMS V instrument equipped with a 25 keV Bi$^+_3$ metal ion gun. Identified molecules and molecular fragments are compared against known biological databases and the reported peaks have at least 65 ppm mass accuracy. These molecules range from lipids, fatty acids, flavonoids, and quinolones to other naturally occurring organic compounds. It is anticipated that the mass spectral identification of key peaks will assist detection of metabolites, EPS molecules like polysaccharides, and biologically relevant small organic molecules using ToF-SIMS in future surface and interface research.

59 BASIC BIOLOGICAL SCIENCES↗