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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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DOE OSTI2023

Natural Abundance Isotope Ratio Measurements of Organic Molecules Using 21 T FTICR MS

Subtle variations in stable isotope ratios at natural abundance are challenging to measure but can yield critical insights into biological, physical, and geochemical processes. Well established methods, particularly multi-collector, gas-source or plasma isotope ratio mass spectrometry (IRMS) are the gold standard for stable isotope measurement but inherent limitations in these approaches make them ill-suited to determining site-specific and multiply substituted isotopic abundances of all but a few compounds, or to characterizing mixtures or larger intact molecules. Additionally, Fourier transform mass spectrometry (FTMS), namely Orbitrap mass spectrometry, has recently demonstrated the ability to measure natural abundance isotope ratios with chemically informative accuracy and precision. Here, we report the first use of Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) for the accurate (<1‰) and precise (<1‰ standard error) simultaneous determination of $δ$ 13 C and $δ$ 15 N in caffeine isotopologues and provide a discussion of the critical instrumental parameters necessary to make such measurements. Finally, we report the ability to make these measurements with online liquid chromatography, expanding the ability of this technique to explore mixtures in the future.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

Measuring Cosmological Parameters with Type Ia Supernovae in redMaGiC Galaxies

Abstract Current and future cosmological analyses with Type Ia supernovae (SNe Ia) face three critical challenges: (i) measuring the redshifts from the SNe or their host galaxies; (ii) classifying the SNe without spectra; and (iii) accounting for correlations between the properties of SNe Ia and their host galaxies. We present here a novel approach that addresses each of these challenges. In the context of the Dark Energy Survey (DES), we analyze an SN Ia sample with host galaxies in the redMaGiC galaxy catalog, a selection of luminous red galaxies. redMaGiC photo- z estimates are expected to be accurate to σ Δ z /(1+ z ) ∼ 0.02. The DES-5YR photometrically classified SN Ia sample contains approximately 1600 SNe, and 125 of these SNe are in redMaGiC galaxies. We demonstrate that redMaGiC galaxies almost exclusively host SNe Ia, reducing concerns relating to classification uncertainties. With this subsample, we find similar Hubble scatter (to within ∼0.01 mag) using photometric redshifts in place of spectroscopic redshifts. With detailed simulations, we show that the bias due to using redMaGiC photo- z s on the measurement of the dark energy equation of state w is up to Δ w ∼ 0.01–0.02. With real data, we measure a difference in w when using the redMaGiC photo- z s versus the spec- z s of Δ w = 0.005. Finally, we discuss how SNe in redMaGiC galaxies appear to comprise a more standardizable population, due to a weaker relation between color and luminosity ( β ) compared to the DES-3YR population by ∼5 σ . These results establish the feasibility of performing redMaGiC SN cosmology with photometric survey data in the absence of spectroscopic data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

VERIFICATION OF TRISO FUEL BURNUP USING MACHINE LEARNING ALGORITHMS

Pebble Bed Reactors are fueled with fuel pebbles that are circulated multiple times through the reactor vessel before discharge. During the normal operation of a PBR, ejected pebbles are returned to the reactor or discharged depending on the fuel burnup and physical condition of the pebbles. The burnup measurement is usually based on detected radiation signatures of fission products accumulated in the pebble fuel over burnup. Previous research has shown that height of photopeaks of fission products, such as 134Cs, 137Cs, 154Eu, etc., can be used independently or in combination to infer or predict the level of burnup in the fuel. However, it remains challenging to measure such complex sources due to self-shielding effects, strong radiation background and intervening materials. Another operational challenge is the required high throughput of burnup measurement, which necessitates limited measurement time and thus impacts quality of measured gamma-ray spectra. Hence, advanced spectral analysis methods are needed to analyze the noisy gamma spectra and predict the burnup values. We propose to use machine learning (ML) method to interpret gamma-ray spectra and predict the burnup values of the pebbles. ML has achieved widespread success and adoption across a few domains that require pattern recognition and analysis in varied data types. In this work, we apply three proven ML approaches - multilayer perceptrons, convolutional neural networks, and transformers - to the task of predicting fuel burnup from measured gamma spectra, and compile a dataset of simulated spectra for training and validation of the ML models. In this paper, we will discuss the network architecture of these three ML approaches and compare the performance of the simplest of these (MLP) to a standard linear regression.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Measurement of the nuclear modification factor for muons from charm and bottom hadrons in Pb+Pb collisions at 5.02 TeV with the ATLAS detector

Heavy-flavour hadron production provides information about the transport properties and microscopic structure of the quark–gluon plasma created in ultra-relativistic heavy-ion collisions. A measurement of the muons from semileptonic decays of charm and bottom hadrons produced in Pb+Pb and pp collisions at a nucleon–nucleon centre-of-mass energy of 5.02 TeV with the ATLAS detector at the Large Hadron Collider is presented. The Pb+Pb data were collected in 2015 and 2018 with sampled integrated luminosities of 208 μb –1 and 38 μb –1 , respectively, and pp data with a sampled integrated luminosity of 1.17 pb –1 were collected in 2017. Muons from heavy-flavour semileptonic decays are separated from the light-flavour hadronic background using the momentum imbalance between the inner detector and muon spectrometer measurements, and muons originating from charm and bottom decays are further separated via the muon track's transverse impact parameter. Differential yields in Pb+Pb collisions and differential cross sections in pp collisions for such muons are measured as a function of muon transverse momentum from 4 GeV to 30 GeV in the absolute pseudorapidity interval |n| < 2. Nuclear modification factors for charm and bottom muons are presented as a function of muon transverse momentum in intervals of Pb+Pb collision centrality. The bottom muon results are the most precise measurement of b quark nuclear modification at low transverse momentum where reconstruction of B hadrons is challenging. The measured nuclear modification factors quantify a significant suppression of the yields of muons from decays of charm and bottom hadrons, with stronger effects for muons from charm hadron decays.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

A distributed temperature profiling system for vertically and laterally dense acquisition of soil and snow temperature

Abstract. Measuring soil and snow temperature with high vertical and lateral resolution is critical for advancing the predictive understanding of thermal and hydro-biogeochemical processes that govern the behavior of environmental systems. Vertically resolved soil temperature measurements enable the estimation of soil thermal regimes, frozen-/thawed-layer thickness, thermal parameters, and heat and/or water fluxes. Similarly, they can be used to capture the snow depth and the snowpack thermal parameters and fluxes. However, these measurements are challenging to acquire using conventional approaches due to their total cost, their limited vertical resolution, and their large installation footprint. This study presents the development and validation of a novel distributed temperature profiling (DTP) system that addresses these challenges. The system leverages digital temperature sensors to provide unprecedented, finely resolved depth profiles of temperature measurements with flexibility in system geometry and vertical resolution. The integrated miniaturized logger enables automated data acquisition, management, and wireless transfer. A novel calibration approach adapted to the DTP system confirms the factory-assured sensor accuracy of ±0.1 ∘C and enables improving it to ±0.015 ∘C. Numerical experiments indicate that, under normal environmental conditions, an additional error of 0.01 % in amplitude and 70 s time delay in amplitude for a diurnal period can be expected, owing to the DTP housing. We demonstrate the DTP systems capability at two field sites, one focused on understanding how snow dynamics influence mountainous water resources and the other focused on understanding how soil properties influence carbon cycling. Results indicate that the DTP system reliably captures the dynamics in snow depth and soil freezing and thawing depth, enabling advances in understanding the intensity and timing in surface processes and their impact on subsurface thermohydrological regimes. Overall, the DTP system fulfills the needs for data accuracy, minimal power consumption, and low total cost, enabling advances in the multiscale understanding of various cryospheric and hydro-biogeochemical processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Fine-Grained Application Energy and Power Measurements on the Frontier Exascale System

The increasing complexity and power/energy demands of heterogeneous exascale systems, such as the Frontier supercomputer, present significant challenges for measuring and optimizing power consumption in applications. Current tools either lack the resolution to capture fine-grained power and energy measurements, fail to validate in-band measurements against out-of-band power sensors, or cannot integrate this information with application performance events in a scalable manner. This paper introduces a novel open-source performance toolkit that integrates extended PAPI components with Score-P plugins to enable in-band, fine-grained power and energy measurements, while also supporting validation using power meter measurements for both CPUs and GPUs. One key contribution is the ability to perform millisecond-level power and energy measurements for AMD MI250X GPUs, mapping them to application performance events within a single trace and measurement system that scales. Our toolkit combines coarse-grained measurements from cray_pm counters with high-resolution metrics from rocm_smi and RAPL, converting GPU instantaneous accumulated energy into power to capture both transient and steady-state power behavior, a capability often missed by out-of-band and monitoring tools. By mapping these metrics to specific application regions, developers can identify energy hotspots, address inefficiencies in GPU kernel execution, and validate in-band measurements against external measurements. We demonstrate the effectiveness of this approach through case studies using benchmarks such as GPU rocblas_sgemm, BLIS c_blas_dgemm, and rocHPL, highlighting the variability of the measurements and the impact of transient power spikes on kernel-level efficiency.

Hernandez Mendoza, Oscar [ORNL] (ORCID:00000002538↗
DOE OSTI2021

Verification of Triso Fuel Burnup Using Machine Learning Algorithms

Pebble Bed Reactors are fueled with fuel pebbles that are circulated multiple times through the reactor vessel before discharge. During the normal operation of a PBR, ejected pebbles are returned to the reactor or discharged depending on the fuel burnup and physical condition of the pebbles. The burnup measurement is usually based on detected radiation signatures of fission products accumulated in the pebble fuel over burnup. Previous research has shown that height of photopeaks of fission products, such as 134 Cs, 137 Cs, 154 Eu, etc., can be used independently or in combination to infer or predict the level of burnup in the fuel. However, it remains challenging to measure such complex sources due to self-shielding effects, strong radiation background and intervening materials. Another operational challenge is the required high throughput of burnup measurement, which necessitates limited measurement time and thus impacts quality of measured gamma-ray spectra. Hence, advanced spectral analysis methods are needed to analyze the noisy gamma spectra and predict the burnup values. We propose to use machine learning (ML) method to interpret gamma-ray spectra and predict the burnup values of the pebbles. ML has achieved widespread success and adoption across a few domains that require pattern recognition and analysis in varied data types. In this work, we apply three proven ML approaches - multilayer perceptrons, convolutional neural networks, and transformers - to the task of predicting fuel burnup from measured gamma spectra, and compile a dataset of simulated spectra for training and validation of the ML models. In this paper, we will discuss the network architecture of these three ML approaches and compare the performance of the simplest of these (MLP) to a standard linear regression.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Mixing by internal gravity waves in stars: assessing numerical simulations against theory

ABSTRACT Here we present a study of radial chemical mixing in non-rotating massive main-sequence stars driven by internal gravity waves (IGWs), based on multidimensional hydrodynamical simulations with the fully compressible code MUSIC. We examine two proposed mechanisms of material mixing in stars by IGWs that are commonly quoted, relating to thermal diffusion and sub-wavelength shearing. Thermal diffusion provides a non-restorative effect to the waves, leaving material displaced from its previous equilibrium, while shearing arising within the waves drives weak localized flows, mixing the fluid there. Using IGW spectra from the simulations, we evaluate theoretical predictions of mixing rates due to these mechanisms. We show, for $20\, \mathrm{M}_\odot$ main-sequence stars, that neither of these mechanisms are likely to create mixing sufficient to correct inaccuracies in current stellar evolution models. Furthermore, we compare these predictions to results obtained from Lagrangian tracer particles, following a method recently used for global simulations of stellar interiors to measure mixing by IGWs in their radiative zones. We demonstrate that tracer particle methods face significant numerical challenges in measuring the small diffusion coefficients predicted by the aforementioned theories, for which they are prone to yielding artificially enhanced coefficients. Diffusion coefficients based on such methods are currently used with stellar evolution codes for asteroseismic studies, but should be viewed with caution. Finally, in a case where tracer particles do not suffer from numerical artefacts, we suggest that a diffusion model is not suitable for time-scales typically considered by 2D numerical simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Extreme compression of planetary gases: High-accuracy pressure-density measurements of hydrogen-helium mixtures above fourfold compression

Hydrogen (H 2 ) and helium (He), the most abundant elements in the universe, pose a unique challenge in measuring the equation of state of the mixture, owing to their differing physical properties. There remains a need for data with high enough precision to discriminate between existing equation of state (EOS) mix models in order to understand the internal structure of gas-giant planets. Here, we have measured the EOS of precompressed H 2 - He mixtures at conditions directly relevant to the planetary interiors using hypervelocity gas guns and Sandia’s Z machine with less than 10% uncertainty in density, enabling validation of mixture models. We precompressed 50:50 molar mixtures of H 2 -He to 0.1–0.2 GPa and directly measured particle velocity (in gas-gun experiments) and shock velocities (in Z-machine experiments). To complement the experimental efforts, we also computed the Hugoniots of precompressed H 2 -He mixtures using density-functional-theory-based molecular dynamics. Furthermore, we observe approximately 3- to 4.3-fold density compression at pressures up to 44 GPa.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Kohn anomalies and phonon anharmonicity in iridium

Elemental iridium presents surprising challenges for both inelastic neutron scattering (INS) and theoretical thermal transport calculations due to its high neutron absorption cross-section and strong electron-phonon interactions, respectively. Here, in this study, we overcome these challenges to measure temperature-dependent phonon dispersion curves, compare these with calculations based on density functional theory (DFT), and ultimately examine the electron-phonon limited transport behaviors of this material. Our DFT calculations demonstrate Kohn anomalies, near the 𝐾 point of the iridium Brillouin zone, indicating coupling between electrons and phonons. Strong electron-phonon coupling can compete with anharmonic effects to determine electrical and thermal transport behaviors and make the Kohn anomalies challenging to observe. Nonetheless, our INS measurements map these anomalies and other dispersion features over the Brillouin zone from 100 to 700 K. These measurements also uncover unexpectedly large mode specific Grüneisen parameters obtained from the temperature-dependent phonon energies, highlighting strong anharmonicity in iridium. DFT-based Boltzmann transport calculations demonstrate how anharmonicity and electron-phonon couplings determine electronic and lattice transport behaviors. Furthermore, we correlate the Kohn anomalies with calculated electron-phonon nesting functions, Fermi surfaces, and DFT-derived coupling strengths. This study provides detailed insights into the temperature-dependent mode-resolved lattice dynamics and anharmonicity, transport behavior, and electron-phonon interactions.

DFT↗
DOE OSTI2022

Measurement Uncertainty of Highly Asymmetrically Curved Elliptical Mirrors Using Multi-Pitch Slope Stitching Technique

Soft X-ray off-axis elliptical mirrors bring new challenges for X-ray mirror metrology. These highly asymmetrically curved elliptical cylindrical mirrors with a total slope range >10 mrad are extremely challenging to measure. Their total slope range exceeds the measuring range of most angular sensors used for X-ray mirror inspection. To overcome this problem, it is possible to stitch partial slope data by measuring the mirror at different pitch angles (multi-pitch angles). By revisiting the theory of the multi-pitch Nano-accuracy Surface Profiler (NSP), we derive the sampling position error on the mirror surface as a function of the mirror height profile and the measurement error of the pitch rotation center. When measuring “extreme”, highly asymmetrically curved, elliptical mirrors, the calculation of the mirror height profile with iterative reconstruction outperforms the classical “flat assumption” (i.e., assuming that the mirror sag is negligible). As demonstrated by our simulations, a proper tolerance evaluation on the measurement of pitch rotation center is needed to assess the measurement accuracy (systematic error) for these strongly aspherical mirrors using the multi-pitch NSP technique. Taking a real design of an “extreme” elliptical mirror as a case study, we conduct a Monte Carlo simulation to mimic the measurement and characterization process to analyze the impact of several error sources. With the measurement uncertainty of the pitch rotation center, the multi-pitch NSP measurement can estimate the grazing angle θ and the chief ray location x o with their uncertainties, as well as the slope residuals.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Laboratory tests of CO2 laser collective Thomson scattering for measurements of ion temperature in the divertor

Collective Thomson scattering (CTS) is a diagnostic method that measures the ion velocity distribution of a plasma. CO2 laser CTS measurements are challenging because of the inherently small Doppler broadening and scattering signals that are difficult to detect. We implemented a heterodyne detection scheme to measure spectrum changes of less than a GHz. To maximize the collected light at small scattering angles, we designed a unique light collection approach consisting of a customized conical-shaped (axicon) lens with a hole in the center. The axicon lens is used to collect the scattered light emitted within an annular cross-section from the scattering volume while the probe beam is passed through the hole at the center of the lens. The performance of the heterodyne detection scheme and annular collection approach was demonstrated using a Transverse Excited Atmospheric pressure CO2 laser with a pulse energy of 160 mJ at λ = 10.59 µm.

Instruments & Instrumentation↗
DOE OSTI2024

Assessment of Flow-Enhanced Electrochemical Sensor Testing and Deployments

The goal of our activities in FY24 was to enable advanced materials accountancy for molten salt reactors (MSRs) through the development and optimization of robust flow-enhanced electrochemical sensors (FEES) using a safeguards-focused sensor testing platform called the modular flow instrumentation testbed (MFIT). Flow-enhanced electrochemical sensors are a type of electroanalytical sensor that have been developed at Argonne National Laboratory to be installed directly into MSR flow conduits to make measurements of the salt composition. These sensors represent a significant improvement in capabilities compared to earlier electroanalytical sensors that instead can only be operated in quiescent conditions. Previous work has focused on testing of the FEES in flowing conditions provided by the MFIT to assess the accuracy and precision of the sensor measurements. This year, the FEES technical readiness was increased by (1) demonstrating the use of optimized sensor techniques to achieve measurements in very high-concentration MSR-relevant salts, (2) leveraging new multimodal sensors and automation approaches to reduce measurement uncertainties, and (3) fabricating and deploying sensors to industrial partners to improve their ability to make measurements in challenging environments. Additionally, we also ran the sensors during complex system operations involving combined flow and purification activities to demonstrate safeguards-relevant measurements during online processing for MSRs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Cold gas mass measurements for the era of large optical spectroscopic surveys

ABSTRACT Gas plays an important role in many processes in galaxy formation and evolution, but quantifying the importance of gas has been hindered by the challenge to measure gas masses for large samples of galaxies. Data sets of direct atomic and molecular gas measurements are sufficient to establish simple scaling relations, but often not large enough to quantify three-parameter relations, or second-order dependences. As an alternative approach, we derive here indirect cold gas measurements from optical emission lines using photoionization models for galaxies in the Sloan Digital Sky Survey (SDSS) main galaxy sample and the PHANGS-MUSE survey. We calibrate the gas surface density measurements using xCOLD GASS and PHANGS-ALMA molecular gas measurements to ensure that our measurements are reliable. We demonstrate the importance of taking into account the scale dependence of the relation between optical depth (τ V ) and gas surface density (Σ gas ) and provide a general prescription to estimate Σ gas from τ V , metallicity, and the dust-to-metal ratio, at any arbitrary physical resolution. To demonstrate that the indirect cold gas masses are accurate enough to quantify the role of gas in galaxy evolution, we study the mass–metallicity relation of SDSS galaxies and show that as a third parameter gas mass is better than star formation rate at reducing the scatter of the relation, as predicted by models and simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Probing surface-adsorbate interactions through active particle dynamics

Adsorbate molecules present in a reaction mixture may bind to and block catalytic sites. Measurement of the surface coverage of these molecules via adsorption isotherms is critical for modeling and design of catalytic reactions on surfaces. However, it is challenging to measure isotherms in solution in a way that is directly relevant to catalytic activity under reaction conditions, particularly since adsorbates may bind with an enormous range of surface affinity parameters. Here we used the motion of self-propelled catalytic Janus particles, which employ the decomposition of hydrogen peroxide fuel as a propulsion mechanism, to determine the effective surface coverage of thioglycerol, furfural, and ethanol on a platinum surface as a function of concentration in aqueous solution by measuring the decrease in active motion due to the blocking of active sites. For strongly adsorbing thioglycerol, this effective coverage was compared and contrasted to the total adsorbed amount measured using inductively-coupled plasma analysis. Demonstrating the broad applicability of this approach, the surface affinity of the three adsorbates spanned more than four orders of magnitude. For each species, the adsorbate-mediated attenuation of active motion occurred over a wide concentration range and was well-described by a Langmuir isotherm. The strongly interacting thioglycerol had the highest affinity towards the surface (K a = 15.5 ± 4.3 mM –1 ) and fully deactivated the active particle motion at surface saturation. Furfural had an intermediate affinity (K a = 0.42 ± 0.07 mM –1 ) but did not fully block H 2 O 2 access to the surface at apparent saturation, consistent with a maximum fractional surface coverage of θ max = 0.67. Ethanol exhibited even lower affinity (K a = 0.0025 ± 2x10 -4 mM –1 ) and its coverage saturated at only θ max = 0.38. Analysis of isotherms at elevated temperatures enabled direct extraction of the enthalpies of adsorption. The degree of surface coverage at adsorbate saturation appeared to correlate with the relative energies of adsorption for the different adsorbate species and was consistent with adsorbate saturation of one of multiple active site populations towards H 2 O 2 decomposition. Furthermore, computational investigations into solvent effects on furfural adsorption showed good quantitative agreement with the experimental results. This work leverages unique properties of active particles to explore fundamental catalysis questions and demonstrates a novel paradigm for significant and experimentally accessible multidisciplinary research.

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

All-optical single-shot complete electric field measurement of extreme ultraviolet free electron laser pulses

Recent advances in ultrafast extreme ultraviolet (EUV) and x-ray light sources provide direct access to fundamental time and length scales for biology, chemistry, and materials physics. However, such light pulses are challenging to measure due to the need for femtosecond time resolution at difficult-to-detect wavelengths. Also, single-shot measurements are needed because severe pulse-to-pulse fluctuations are common. Here we demonstrate single-shot, complete field measurements by applying a novel version of frequency resolved optical gating. An EUV free electron laser beam creates a transient grating containing the pulse’s electric field information, which is read out with a 400 nm probe pulse. By varying the time delay between two copies of the EUV pump, rather than between the pump and the probe, we separate the needed coherent wave mixing from the slow incoherent response. Because this approach uses photoionization, it should be applicable from the vacuum ultraviolet to hard x rays.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Versatile soil gas concentration and isotope monitoring: optimization and integration of novel soil gas probes with online trace gas detection

Abstract. Gas concentrations and isotopic signatures can unveil microbial metabolisms and their responses to environmental changes in soil. Currently, few methods measure in situ soil trace gases such as the products of nitrogen and carbon cycling or volatile organic compounds (VOCs) that constrain microbial biochemical processes like nitrification, methanogenesis, respiration, and microbial communication. Versatile trace gas sampling systems that integrate soil probes with sensitive trace gas analyzers could fill this gap with in situ soil gas measurements that resolve spatial (centimeters) and temporal (minutes) patterns. We developed a system that integrates new porous and hydrophobic sintered polytetrafluoroethylene (sPTFE) diffusive soil gas probes that non-disruptively collect soil gas samples with a transfer system to direct gas from multiple probes to one or more central gas analyzer(s) such as laser and mass spectrometers. Here, we demonstrate the feasibility and versatility of this automated multiprobe system for soil gas measurements of isotopic ratios of nitrous oxide (δ18O, δ15N, and the 15N site preference of N2O), methane, carbon dioxide (δ13C), and VOCs. First, we used an inert silica matrix to challenge probe measurements under controlled gas conditions. By changing and controlling system flow parameters, including the probe flow rate, we optimized recovery of representative soil gas samples while reducing sampling artifacts on subsurface concentrations. Second, we used this system to provide a real-time window into the impact of environmental manipulation of irrigation and soil redox conditions on in situ N2O and VOC concentrations. Moreover, to reveal the dynamics in the stable isotope ratios of N2O (i.e., 14N14N16O, 14N15N16O, 15N14N16O, and 14N14N18O), we developed a new high-precision laser spectrometer with a reduced sample volume demand. Our integrated system – a tunable infrared laser direct absorption spectrometry (TILDAS) in parallel with Vocus proton transfer reaction mass spectrometry (PTR-MS), in line with sPTFE soil gas probes – successfully quantified isotopic signatures for N2O, CO2, and VOCs in real time as responses to changes in the dry–wetting cycle and redox conditions. Broadening the collection of trace gases that can be monitored in the subsurface is critical for monitoring biogeochemical cycles, ecosystem health, and management practices at scales relevant to the soil system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Multi-pitch nano-accuracy surface profiler for strongly curved X-ray mirror metrology

We present our recent research and development effort on the Multi-Pitch Nano-accuracy Surface Profiler (MPNSP). This metrology instrument is developed to characterize strongly curved X-ray mirrors proposed to achieve diffraction-limited soft X-ray focusing for scientific applications at the synchrotron beamlines. The measurement process consists of forward-and-backward scans on the test mirror surface along its tangential direction at multiple pitch angles. Our research and development in this work aim to take the challenge of measuring strongly curved X-ray mirrors with a typical total slope range ≳10 mrad, while maintaining the Root Mean Square (RMS) value of measurement repeatability and self-consistency at 50 nrad RMS level. We first introduce the mechanical design, followed by a brief review of the mathematical model and the optimization algorithm for the MPNSP technique. By detecting the rotation axis of the mirror pitch with a machine vision approach, we can determine and then reduce the vertical distance between the pitch rotation axis and the test mirror surface to a sub-mm level. In addition, we describe a practical data acquisition procedure for strongly curved X-ray mirrors with a total slope range larger than the slope measuring range of the autocollimator used in the instrument. As a result, the proposed MPNSP measurements with different mirror orientations achieve remarkable self-consistency and reproducibility of < 50 nrad RMS in slope and < 0.5 nm RMS in height.

42 ENGINEERING↗