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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The ezSpectra suite: An easy‐to‐use toolkit for spectroscopy modeling

Abstract A molecule's spectrum encodes information about its structure and electronic properties. It is a unique fingerprint that can serve as a molecular ID. Quantum chemistry calculations provide key ingredients for interpreting spectra, but modeling the spectra rarely ends there; it requires additional steps that entail combined treatments of electronic and nuclear degrees of freedom and account for specifics of the experimental setup (light energy, polarization, averaging over molecular orientations, temperature, etc.). This Software Focus article describes the ezSpectra suite, which currently comprises two stand‐alone open‐source codes: ezFCF and ezDyson . ezFCF calculates Franck–Condon factors, which yield vibrational progressions for polyatomic molecules, within the double‐harmonic approximation. ezDyson calculates absolute cross‐sections for photodetachment/photoionization processes and photoelectron angular distributions using Dyson orbitals computed by a quantum chemistry program. This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods Theoretical and Physical Chemistry > Spectroscopy Software > Simulation Methods

Gozem, Samer↗
DOE OSTI2025

Machine Learning in the Context of Laser-Induced Breakdown Spectroscopy

The integration of machine learning (ML) with Laser-Induced Breakdown Spectroscopy (LIBS) has revolutionized the analytical capabilities of LIBS. The combi-nation of both methods enables more accurate and efficient data analysis. While LIBS itself is a powerful technique for elemental analysis, the vast amount of spectral data it generates can be hard to interpret. Machine learning addresses these challenges by leveraging algorithms that can learn from data, identify patterns, and make predictions without explicit programming for the interpretation of each specific task. In LIBS application, ML techniques are used to enhance various analytical processes. For example, ML algorithms can classify materials based on their spectral fingerprints, predict the concentration of elements in a sample, and identify underlying patterns within complex datasets. Here, this application improves the precision of LIBS analyses while significantly reducing the time required for data processing and interpretation. In this chapter, the fundamental concepts of ML will be discussed first. Following this, the process of data splitting and the importance of feature selection will be examined. Several machine learning methods will then be closely examined, exploring how each can benefit LIBS analysis and highlighting their respective advantages and shortcomings. This structured approach will provide a comprehensive understanding of the integration of ML in the context of LIBS analysis.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

The SuperCam Instrument Suite on the NASA Mars 2020 Rover: Body Unit and Combined System Tests

The SuperCam instrument suite provides the Mars 2020 rover, Perseverance, with a number of versatile remote-sensing techniques that can be used at long distance as well as within the robotic-arm workspace. These include laser-induced breakdown spectroscopy (LIBS), remote time-resolved Raman and luminescence spectroscopies, and visible and infrared (VISIR; separately referred to as VIS and IR) reflectance spectroscopy. A remote micro-imager (RMI) provides high-resolution color context imaging, and a microphone can be used as a stand-alone tool for environmental studies or to determine physical properties of rocks and soils from shock waves of laser-produced plasmas. SuperCam is built in three parts: The mast unit (MU), consisting of the laser, telescope, RMI, IR spectrometer, and associated electronics, is described in a companion paper. The on-board calibration targets are described in another companion paper. Here we describe SuperCam’s body unit (BU) and testing of the integrated instrument. The BU, mounted inside the rover body, receives light from the MU via a 5.8 m optical fiber. The light is split into three wavelength bands by a demultiplexer, and is routed via fiber bundles to three optical spectrometers, two of which (UV and violet; 245–340 and 385–465 nm) are crossed Czerny-Turner reflection spectrometers, nearly identical to their counterparts on ChemCam. The third is a high-efficiency transmission spectrometer containing an optical intensifier capable of gating exposures to 100 ns or longer, with variable delay times relative to the laser pulse. This spectrometer covers 535–853 nm ( $105\text{--}7070~\text{cm}^{-1}$ Raman shift relative to the 532 nm green laser beam) with $12~\text{cm}^{-1}$ full-width at half-maximum peak resolution in the Raman fingerprint region. The BU electronics boards interface with the rover and control the instrument, returning data to the rover. Thermal systems maintain a warm temperature during cruise to Mars to avoid contamination on the optics, and cool the detectors during operations on Mars.Results obtained with the integrated instrument demonstrate its capabilities for LIBS, for which a library of 332 standards was developed. Examples of Raman and VISIR spectroscopy are shown, demonstrating clear mineral identification with both techniques. Luminescence spectra demonstrate the utility of having both spectral and temporal dimensions. Finally, RMI and microphone tests on the rover demonstrate the capabilities of these subsystems as well.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

The Linkage Between Electro-Chemical Mechanical Instabilities in Battery Materials

Battery chemistry must be diversified to achieve a sustainable energy landscape by effectively utilizing renewable energy sources. Alkali metal-ion, all-solid-state, metal–air batteries, and multivalent batteries offer unique cost, safety, raw material abundance, energy, and power density solutions. However, realizing these “beyond Li-ion batteries” must uncover their working principles and performance & property relationships. In this aspect, mitigating chemo-mechanical instabilities in the structure and surface of the electrodes plays a crucial role in their performance. Unfortunately, the coupling between electrochemical and mechanical interactions is often poorly understood due to a lack of operando characterization. Here, this review article explains the working principles of curvature measurement and digital image correlation for measuring stress and strain generations in battery materials. We provided specific examples of how these operando mechanical measurements shed light on instabilities in alkali metal ion electrodes, solid electrolytes, Li-O 2 batteries, and aqueous Zn-ion batteries. Operando mechanical measurements offer an effective way to map changes in the physical fingerprint of the battery materials, therefore providing crucial information to elucidate instabilities in battery materials.

25 ENERGY STORAGE↗
DOE OSTI2024

Data-Driven Surrogate Modeling with Microstructure-Sensitivity of Viscoplastic Creep in Grade 91 Steel

Abstract To support the development of advanced steel alloys tailored to withstand extreme conditions, it is imperative to account for the mechanical performance of components, while considering the influence of local microstructure on the macroscopic response. To this end, this study focuses on the development of microstructure-sensitive constitutive models for the mechanical response of Grade 91 steel exposed to extreme thermo-mechanical environments. Polynomial chaos expansion (PCE) surrogates are used to emulate high-fidelity polycrystal simulations of the viscoplastic response of Grade 91 steel as a function of the microstructure fingerprint (e.g., dislocations and precipitates). To cover a wide temperature–stress domain, two separate PCE surrogates—one that captures softening and the other that captures hardening behavior—are combined using another (sparse) Gaussian process regression model. The resulting constitutive creep surrogate model is integrated within the MOOSE finite element framework to simulate the intricate effects of microstructure, in particular MX-phase precipitates, on a component with a graded microstructure. Surrogate sensitivity analysis is applied to quantify the relevant impact of spatially varying microstructure on the creep response in a test-case involving a Grade 91 alloy with a prototypical weld.

36 MATERIALS SCIENCE↗
DOE OSTI2026

High sensitivity measurement of femtogram-level 238 Pu by thermal ionization mass spectrometry with correction of background 238 U

Low-concentration plutonium isotopic measurements provide a valuable fingerprint to identify possible material origins in the context of environmental contamination monitoring, environmental tracing, nuclear safeguards, nuclear forensics, and treaty monitoring. Thermal ionization mass spectrometry (TIMS) has long been recognized as one of the most sensitive techniques for plutonium isotopic measurement, but has not generally been utilized for 238 Pu determination, especially at low concentrations, due to an isobaric interference from 238 U, prevalent as background. Here, this work demonstrates a new analytical technique for correction of background 238 U from the 238 Pu counts collected during a TIMS analysis. The technique takes advantage of the higher ionization temperature of U relative to Pu and uses a 235 U tracer added after plutonium purification chemistry for 238 U semi-quantitative determination. This technique has been successfully applied to the determination of 238 Pu concentration and the 238 Pu/ 239 Pu ratio in sample types including single-isotope standards, isotopic certified reference materials, matrix-containing environmental reference materials, and simulated nuclear detonation debris. The results have been directly compared on a sample-by-sample basis to alpha spectrometry results. The detection limit by this new technique is 0.23 fg 238 Pu, which was previously unachievable by mass spectrometry and is possible in around 1 h of analysis time post-chemistry compared to weeks of required counting time by alpha spectrometry (at the same atom amount). We also present original, high precision data for Pu isotope concentrations in IAEA-384, Fangataufa Sediment, including 242 Pu results for the first time. The new technique allows measurement of a key isotope, 238 Pu, that was previously not measured in small environmental or nuclear forensics collections.

238Pu↗
DOE OSTI2021

Electronic and optical properties of plutonium metal and oxides from Reflection Electron Energy Loss Spectroscopy

Reflection Electron Energy Loss Spectra (REELS) have been acquired on plutonium δ-Pu-Ga alloys, α-Pu 2 O 3 and PuO 2 . The position of the peaks attributable to the Pu 6p excitation can be used as ‘fingerprint’ for these species. X-ray Photoelectron Spectroscopy has been used to aid interpretation of the REELS spectra. The band gap of PuO 2 was determined from the onset of the energy loss in the REELS spectrum. The REELS data have been evaluated within the dielectric response theory by means of the QUEELS-ε(k, w)-REELS software. In this work, the Energy Loss Function, dielectric function, refractive index and extinction coefficient for these materials have been determined in the ultraviolet and extreme ultraviolet range and are compared to previously reported results.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Dynamics and lipid membrane coupling of the RAS-RAF complex revealed via multiscale simulations

To gain molecular and mechanistic insights into initiation of the RAS-RAF signaling cascade, we developed and used a combination of multiscale simulation and experimental approaches. The influence and impact of the membrane on RAS and RAF proteins is a factor we are just beginning to understand and appreciate in more detail. Molecular simulation is an ideal methodology to further study this complicated relationship between the membrane and associated proteins. Our previous work using Multiscale Machine-learned Modeling Infrastructure investigated different lipid compositions solely around the KRAS4b protein and the interplay between protein behavior and these membrane environments. Multiscale Machine-learned Modeling Infrastructure uses machine learning to couple adjacent simulation scales and has been efficiently scaled across some of the world’s largest high-performance computers. Recently, we have expanded this multiresolution framework to include the all-atom simulation scale and to incorporate the RAF RBDCRD domains. Here, we present the overall analysis results from this new simulation campaign comprising a mixture of RAS and RAF RBDCRD proteins. Approximately 35,000 coarse-grained and 10,000 all-atom molecular dynamics simulations were completed, sampled from a variety of protein/lipid composition configurations that were generated from a micron-scale continuum simulation containing hundreds of copies of the proteins. Our studies suggest that orientations of the RAS-RBDCRD complex on the membrane occupy distinct configurational states, and the spatial patterns of lipid arrangements around these different protein states are unique to each state. The extent and size of lipid “fingerprints” imposed on the membrane by the RAS-RBDCRD protein complex are significantly larger than observed for just the RAS protein on its own. These protein complexes strongly associate, but we do not observe statistically significant preferred protein-protein orientations. These observations indicate that spatial colocalization of RAS-RBDCRD proteins in the same vicinity may be assisted by specific membrane environments, acting to increase the probability of signaling complex formation.

Carpenter, Timothy S. [Lawrence Livermore National↗
DOE OSTI2025

Statistical distributions for transient transport

Here, this paper introduces the use of statistical distributions based on transport differential equations for clear distinction of transport modes within transient kinetic experiments. More specifically, novel techniques are developed for the transient data obtained through the Temporal Analysis of Products (TAP) reactor and are applicable to experiments where pulse response into a gas flow is used. The methodology allows distinguishing between two domains of diffusion transport in heterogeneous catalytic systems, i.e., Knudsen and non-Knudsen diffusion, using statistical fingerprints, and finding the transition domain. Two distribution parameters were obtained that directly result in coefficients that correspond to the concentration and the rate of transport. Using a linear relationship between the rate and concentration coefficients, Knudsen diffusion is revealed when the rate of transport is constant and non-Knudsen diffusion is confirmed when the rate of transport coefficient is a function of the concentration coefficient. As a result, accurate transport information can be extracted from experimental data even in the presence of comprising instrument drift or noise particularly when analyzing higher pressure pulse responses with complex transport. This enables more direct investigation of experiments influenced by gas-phase reactions.

TAP reactor↗
DOE OSTI2024

Graph neural networks for CO 2 solubility predictions in Deep Eutectic Solvents

Deep Eutectic Solvents (DESs) are a promising class of solvents for CO 2 capture. DESs are complex mixtures that can be designed to optimize CO solubility and overall capture process efficiency. However, the vast design landscape of DES mixtures makes experimental investigation prohibitive; as such, there is a need for computational models that can quickly and efficiently navigate the design space and inform data collection efforts. In this work, we propose Graph Neural Network (GNN) models for predicting CO 2 solubility for DESs; the GNN leverages a mixture graph representation that captures the molecular structure of the DES components as well as their intermolecular interactions. Here, we compare the GNN framework against alternative architectures (neural networks, graph convolution networks, and random forests) and data representations (molecular fingerprints, sigma profiles, and graphs). We show that the proposed approach offers superior predictive performance; specifically, we show that solubility can be predicted reliably directly from molecular structure (without the need of using sigma profiles as proposed in previous studies). This result is important, as obtaining sigma profiles requires expensive density functional theory computations. We also explored the ability of GNNs to predict solubility for new DES mixtures and operating conditions. We found that the model extrapolates across temperature reliably. However, we also found deficiencies in the ability of the model to predict solubility for DES mixtures, pressures, and molar ratio not included in the training sets; we show that this is due to an inherent lack of chemical diversity in datasets available in the literature. The proposed computational capabilities can thus help navigate the design space of DES and inform data collection efforts. Our models, data, and benchmarks are shared as Python code implemented in Jupyter notebooks.

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

Resolving Lonsdaleite's decade-long controversy: Atomistic insights into a metastable diamond polymorph

Lonsdaleite, a theoretically proposed hexagonal diamond polymorph, has remained at the center of a five-decade scientific controversy since its 1967 identification. While some studies claim it exhibits superior hardness through compression-induced structural changes, others contend it is merely a stacking-faulted cubic diamond. Meteoritic samples and synthetic preparations have yielded conflicting evidence, with even advanced characterisation techniques like XRD and TEM failing to provide definitive proof. In this work, we employ first-principles density functional theory (DFT) and molecular dynamics (MD) simulations to generate unambiguous theoretical fingerprints through XRD, Raman, and SAED patterns that distinguish true Lonsdaleite from cubic diamond and its defective variants. Our atomistic approach quantifies the thermodynamic metastability of Lonsdaleite under realistic pressure-temperature conditions, reveals distinct spectral signatures through simulated Raman and resolves the structural ambiguity through generalised stacking fault energy analysis. By establishing clear criteria for definitive identification, this study provides long-awaited clarity to the Lonsdaleite debate while offering a robust computational framework for characterising metastable carbon phases in meteoritic, synthetic and industrial materials.

DFT↗
DOE OSTI2023

Mastering the synergy between Na 3 V 2 (PO 4 ) 2 F 3 electrode and electrolyte: A must for Na-ion cells

Sodium-ion batteries are emerging as suitable energy storage devices for special applications such as high-power devices with the advantages of being cheaper and more sustainable than the Li-ion equivalents. The sodium ion cells consisting of polyanionic Na 3 V 2 (PO 4 ) 2 F 3 - hard carbon electrodes exhibit high power rate capabilities but limited cycle life, especially at high temperatures. To circumvent this drawback we herein conducted in-depth analyses of the origins of structural degradations occurring in Na 3 V 2 (PO 4 ) 2 F 3 electrodes upon long cycling. Vanadium dissolution with associated parasitic reactions is identified as one of the major reasons for cell failure. Its amount varies depending on the electrolyte, with NaTFSI-based electrolyte showing the least vanadium dissolution as the TFSI - anion decomposes without producing acidic impurities, in contrast to the NaPF 6 -based electrolyte. The dissolved vanadium species undergoes oxidation and reduction processes at the Na 3 V 2 (PO 4 ) 2 F 3 and HC electrodes, respectively, with the electrochemical signature of these processes being used as a fingerprint to identify state of health of the 18650 cells. Here, having found that surface reactivity is the primary cause of vanadium dissolution we provide methods to mitigate it by combining surface coating and optimized electrolyte formulation.

25 ENERGY STORAGE↗
DOE OSTI2025

A comprehensive review of diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) techniques in protonic ceramic cells (PCCs): Current status and future perspective

Protonic ceramic cells (PCCs) have emerged as a promising technology for power generation, energy storage, and value-added chemical synthesis, offering benefits such as fuel flexibility, low emissions, and efficient operation at intermediate temperatures (300–600 ​°C). Recently, significant breakthroughs in materials and manufacturing methods have markedly enhanced the performance of PCCs. However, establishing a fundamental understanding of their electrocatalytic reactions has gained less attention. As a fast and cost-effective method for physicochemical fingerprinting, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) has proven to be a surface-sensitive analytical tool for structural and functional studies. This review critically examines the most up-to-date applications of DRIFTS for characterizing key components of PCCs, including oxygen electrodes, protonic electrolytes, and hydrogen electrodes for different applications, with a focus on revealing hydration properties and catalytic reactions, and guiding rational material design. The challenges for advancing DRIFTS, including quantitative capabilities and operando applications for PCC investigations, are highlighted and strategies to tackle these challenges are discussed. Ultimately, this review underscores the critical role of DRIFTS in accelerating the development of high-performance and durable PCCs for next-generation energy solutions, offering methodologies and insights broadly applicable to a wide range of electrochemical energy conversion and storage technologies.

Diffuse Reflectance Infrared Fourier Transform Spe↗
DOE OSTI2022

Demonstration of low-level biogenic fuel content using quench curve and direct liquid scintillation counting (LSC) methods

In this work, an investigation into the direct method for liquid scintillation counting (LSC) quantification of biogenic fuel content in fuel blendstock is presented. This method development intentionally used a colored matrix (~99 wt%), fossil diesel fraction, and low-level biogenic fractions (~1 wt%) to determine the applicability of the LSC technique in colored blend mixtures. LSC procedures for quench correction, including the use of an instrument internal standard (Quantulus SQP values), color quench curves, and an internal 14 C standard spike on samples containing low-level amounts of biogenic gasoline, jet, and diesel mixed with fossil fuel, were compared. Samples were analyzed on both Perkin-Elmer Quantulus and Tri-Carb instruments, and the 14 C contents were compared with those determined by accelerator mass spectrometry (AMS). Results from the Tri-Carb instrument showed that percent differences of <10 % compared to AMS-reported values are achievable at 5-hour count times despite colored samples. A comparison between the impact of chemical and color quenching in the fuel samples showed that color quenching in highly colored samples reduces efficiency significantly more than chemical quenching, indicating that chemical quench curves are not appropriate for highly colored biofuel/fossil-fuel blended samples. Results indicate that both the direct method with internal spike quench correction and the use of a color-quench curve provide accurate results for 1 % biogenic fuel blends. Additionally, we have explored the use of Fourier transform infrared (FTIR) spectroscopy in measuring the biogenic content of the colored blended fuel samples. Preliminary results show the presence of biogenic carbon-derived fingerprints that are absent in fossil-derived sample. However, further work is needed to develop an FTIR-based quantitative method.

09 BIOMASS FUELS↗
DOE OSTI2021

Experimental and theoretical determinations of hydrogen isotopic equilibrium in the system CH 4 —H 2 —H 2 O from 3 to 200°C

The stable isotopic composition of methane (CH 4 ) is commonly used to fingerprint natural gas origins. Over the past 50 years, there have been numerous proposals that both microbial and thermogenic CH 4 can form in or later attain hydrogen isotopic equilibrium with water (H 2 O) and carbon isotopic equilibrium with carbon dioxide (CO 2 ). Evaluation of such proposals requires knowledge of the equilibrium fractionation factors between CH 4 and H 2 O or CO 2 at the temperatures where microbial and thermogenic CH 4 form in or are found in the environment, which is generally less than 200°C. Experimental determinations of these fractionation factors are only available above 200°C, requiring extrapolation of these results beyond the calibrated range or the use of theoretical calculations at lower temperatures. Here, we provide a calibration of the equilibrium hydrogen isotopic fractionation factor for CH 4 and hydrogen gas (H 2 ) ( D α CH4(g)–H2(g) ) based on experiments using γ-Al 2 O 3 and Ni catalysts from 3 to 200°C. Results were regressed as a 2 nd order polynomial of 1000 × ln D α CH4(g)–H2(g) vs. 1/T (K -1 ) yielding: 1000 × l n D α C H 4 ( g ) - H 2 ( g ) = 3.5317 × 10 7 T 2 + 2.7749 × 10 5 T - 179.48 We combine this calibration with previous experimental determinations of hydrogen isotope equilibrium between H 2 , H 2 O(g), and H 2 O(l) and we provide an interpolatable experimental calibration of 1000 × ln D α CH4(g)–H2O(l) from 3 to 200°C. Our resulting 4th order polynomial is the following equation: 1000 × l n D α C H 4 ( g ) - H 2 O l = - 7.9443 × 10 12 T 4 + 8.7772 × 10 10 T 3 - 3.4973 × 10 8 T 2 + 5.4398 × 10 5 T - 382.05 At 3°C, the value from our calibration differs by 93‰ relative to what would be calculated based on the extrapolation of the only experimental calibration currently available to temperatures below its calibrated range (lowest temperature of 200°C; Horibe and Craig, 1995). We additionally provide new theoretical estimates of hydrogen isotopic equilibrium between CH 4 (g), H 2 (g), and H 2 O(g) and carbon isotopic equilibrium between CH 4 (g) and CO 2 (g) using Path Integral Monte Carlo (PIMC) calculations. Our PIMC calculations for hydrogen isotopic equilibrium between CH 4 and H 2 agree 1:1 with our experiments. Finally, we compile carbon and hydrogen isotopic measurements of CH 4 , CO 2 , and H 2 O from various environmental systems and compare observed differences between carbon and hydrogen isotopes to those expected based on isotopic equilibrium. We find that isotopic compositions of some microbial gases from marine sedimentary, coalbed, and shale environments are consistent with those expected for CH 4 H 2 O(l) hydrogen and CH 4 CO 2 carbon isotopic equilibrium. In contrast, microbial terrestrial and pure culture gases are not consistent with both CH 4 H 2 O(l) hydrogen and CH 4 CO 2 carbon isotopic equilibrium. Overall, these results are explained qualitatively using previously developed conceptual models that link free energy gradients available to microorganisms to the degree that their enzymes can promote isotope-exchange reactions between CH 4 , CO 2 , and H 2 O.

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

Chemical characteristics of iron meteorite parent bodies

The projected relative abundances of the highly siderophile elements (HSE; Re, Os, Ir, Ru, Pt, and Pd) for bulk parent bodies of 10 magmatic iron meteorite groups/grouplet (IC, IIAB, IIC, IID, IIF, IIIAB, IIIF, IVA, IVB, and South Byron Trio) are broadly similar and show no resolvable differences between noncarbonaceous (NC) and carbonaceous (CC) genetic heritage. The processes driving genetic isotopic heterogeneity in the early Solar System, therefore, evidently did not leave discernable chemical fingerprints with respect to HSE relative abundances on the bulk planetesimal scale. By contrast, the absolute abundances of HSE projected for parent body cores, which reflect core size, are more variable and, on average, higher in CC bodies compared to NC bodies. Overall, bulk core chemical compositions, as well as core size, are linked to the distribution of Fe within a parent body, which is controlled by its oxidation state. The CC parent bodies are constrained to have formed under heterogeneous oxidizing conditions which were, on average, more oxidizing than those of the NC environment.

Hilton, Connor D.↗
DOE OSTI2020

X-Ray Fluorescence Microscopy: A Method of Measuring Ion Concentrations in the Ear

This technical note describes synchrotron x-ray fluorescence microscopy (XFM) as a method for measuring the concentrations of various elements in cross-sections of the ear at extremely high resolution. This method could be of great importance for addressing many open questions in hearing research. XFM uses synchrotron radiation to evoke emissions from many biologically relevant elements in the tissue. The intensity and wavelength of the emitted radiation provide a fingerprint of the tissue composition that can be used to measure the concentration of the elements in the sampled location. Here, we focus on energies that target biologically-relevant elements of the periodic table between magnesium and zinc. Since a highly focused x-ray beam is used, the spot size is well below 1 mu m and the samples can be scanned at a nanometer lateral resolution. This study shows that measurement of the concentrations of different elements is possible in a mid-modiolar cross-section of a mouse cochlea. Images are presented that indicate potassium and chloride "hot spots" in the spiral ligament and the spiral limbus, providing experimental evidence for the potassium recycling pathway and showing the cochlear structures involved. Scans of a section obtained from the incus, one of the middle ear ossicles, in a developing mouse have shown that zinc is not uniformly distributed This supports the hypothesis that zinc plays a special role in the process of ossification. Although limited by sophisticated sample preparation and sectioning, the method provides ample exciting opportunities, to understand the role of genetics and epigenetics on hearing mechanisms in ontogeny and phylogeny.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Development towards stable chlorine isotope measurements of astromaterials using the modified Middleton source of an accelerator mass spectrometer

The volatile element Cl can be lost during the formation and evolution of planetary bodies, leading to fractionation of its two stable isotopes 35 Cl and 37 Cl. Chlorine isotope variations (reported as δ 37 Cl in parts per thousand (‰) relative to Standard Mean Ocean Chloride, SMOC) are documented to exceed 80‰ between different lunar rock samples and have been variably interpreted as the fingerprint of degassing during accretion, magma ocean, or volcanic portions of lunar history. The large intersample and intrasample variations observed by both bulk isotope ratio mass spectrometry (IRMS) and in-situ secondary ion mass spectrometry (SIMS) methods are difficult to interpret in part because of a paucity of bulk Cl isotope measurements. This lack of high-precision bulk data is due to the relative rarity of IRMS laboratories capable of making these high precision measurements on small samples of precious planetary materials such as those returned by human or robotic exploration. Here we present a new method for performing high precision δ 37 Cl measurements using the modified Middleton ion source of an existing accelerator mass spectrometer. For samples with as little as 1 μg Cl–the equivalent of 2–4 mm 3 of a typical lunar rock sample–the average cathode accuracy is ~1‰. Finally, cathode reproducibility is typically ~1‰ (2σ) for samples with at least 10 μg of Cl, increasing to ~3–6‰ for aliquots with ~1–2 μg Cl, similar to published SIMS results and sufficient to study astromaterials from the Moon, Mars, or 4 Vesta, which have tens of ‰ observed variations.

07 ISOTOPE AND RADIATION SOURCES↗