Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “HARDNESS”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Probing Cretaceous-Paleogene crustal thickness in southern Tibet using quartz-zircon chronobarometry

Knowledge of the crustal thickness history of southern Tibet during the India-Asia collision is key to understanding what deformation mechanisms accommodated northward propagating crustal shortening. Thermoisotopic models suggest that a relatively thin margin of southern Asia persisted from ca. 200 to 45 Ma whereas trace element paleodepth proxies are interpreted to indicate a thinning phase from ca. 100 to 65 Ma when the crust reached ∼30 km-thickness. As neither of these methods directly measures crustal thickness, resolution of this conflict awaits development of a method that can. Here, in this study, we place bounds on the thickening history of southern Tibet using coupled quartz-zircon thermobarometry and U-Pb geochronology of granitoid plutons in the Gangdese batholith. We find that crustal thicknesses were as high (or higher) as 60–75 km at 65 Ma, or 10–15 Ma prior to the onset of hard continental collision. Magmatic inflation in the lower crust likely contributed to crustal thickening and thermal weakening of the lower crust, suggesting that pure shear in the lower crust was likely the primary accommodation mechanism for N-S shortening during collision. These data are in partial agreement with results of thermoisotopic models of crustal thickness but contradict thickness histories derived from empirical trace element proxies.

Chronobarometry↗
DOE OSTI2020

Toward a scalable robust security-constrained optimal power flow using a proximal projection bundle method

Robust security-constrained optimal power flow (rSCOPF) aims to find the worst-case contingencies of alternating current optimal power flow (ACOPF) in power systems. With the rise of GPU architectures on the upcoming supercomputer architectures, optimization algorithms that rely on sparse linear algebra and indefinite linear systems are becoming increasingly hard to solve efficiently (e.g. interior-point method). To address this we revisit a maximin optimization formulation of the rSCOPF and the single-level mixed-integer semidefinite programming (MISDP) reformulation, which is obtained by taking the Lagrangian relaxation of the inner minimization ACOPF problem. In this paper, we focus on the development of a proximal projection bundle method (PPBM) for solving continuous relaxation node subproblems of the MISDP problem, based primarily on the well-known alternating direction method of multipliers. Cutting planes reminiscent of bundle method ideas are also applied in coordination with updates of the proximal parameter. The cutting-plane method can generate a large number of linear inequalities, leading to a large scale but decomposable quadratic programming (QP) subproblem that is amenable to GPUs. We present the numerical results on the IEEE 30, 57, 118, and 300-bus systems by using our PBMM method. We discuss the main computational bottleneck of our method, which is the time taken to solve each iteration of a QP subproblem instance of the PPBM, and how GPU architectures can accelerate this solution process.

bundle method↗
DOE OSTI2022

Power quality disturbances diagnosis: A 2D densely connected convolutional network framework

The fast and accurate diagnosis of power quality disturbances (PQD) aids in avoiding shutdowns and unnecessary procedures, concerning electric energy distribution systems. As such, a number of techniques have been tested and applied in order to reach this objective. Majority of the techniques applied are two-step based. On the first step, power quality disturbances features are extracted. Second step, considering features extracted, disturbance classification is implemented. Recently, relevant literature has presented data-driven signal processing-based approaches, as deep convolutional neural networks (DCNN), which can implement both processing steps while providing automated recognition of patterns and outliers in data. However, not considered by state-of-art, power quality disturbances are evolving in nature, while all possible regularities might not be represented in the dataset. In this work a 2 Dimension Densely Connected Convolutional Network (2D-DenseNet) framework is presented. Further, a case study with synthetic disturbance events are analyzed. Easy-to-implement formulation, built on the 2D-DenseNet, without hard-to-design parameters, highlight potential aspects for real-life implementation.

42 ENGINEERING↗
DOE OSTI2021

Multi-spatio-temporal scales PIV in a turbulent buoyant jet discharging in a linearly stratified environment

Time-resolved particle image velocimetry is implemented with a camera array and several laser sheets; this results in a multi-spatio-temporal scale system that is modular and flexible. The setup is optimized to capture global flow features, while locally resolving in space and time near the Kolmogorov scale. The apparatus relies extensively on machine vision CMOS cameras; they are inexpensive and stream to computer hard drive with virtually continuous time-resolved records (up to one hour for the current system). This leads to statistically converged data and also helps in minimizing down time between experimental runs. Details of the implementation and design of experiment are reported. The system instruments a vertical buoyant jet discharging in a linearly stratified environment. Refractive index matched aqueous solutions enable precise optical deployment. The density difference is 3% and the fluids have similar dynamic viscosity. The jet Reynolds number is 2.00 x 10 4 and is above the mixing transition. Such flows are typically challenging to instrument and few velocity field data are available to date. The velocity statistics are reported as well as first insights gained from the campaign.

42 ENGINEERING↗
DOE OSTI2025

Adaptive Interface-PINNs (AdaI-PINNs) for transient diffusion: Applications to forward and inverse problems in heterogeneous media

We model transient diffusion in heterogeneous materials using a novel physics-informed neural networks framework (PINNs) termed Adaptive interface physics-informed neural networks or AdaI-PINNs (Roy et al. arXiv preprint arXiv:2406.04626, 2024). AdaI-PINNs utilize different activation functions with trainable slopes tailored to each material region within the computational domain, allowing for a fully automated and adaptive PINNs approach to model interface problems with strongly and weakly discontinuous solutions. To enhance its performance in highly heterogeneous transient diffusion systems, we prescribe a suite of robust practices, including appropriate non-dimensionalization of equations, a biased sampling method, Glorot initialization, and the hard enforcement of boundary and initial conditions. Here we evaluate the efficacy of the proposed method on several benchmark forward and inverse problems. Comparative studies on one-dimensional and two-dimensional benchmark problems reveal that the modified AdaI-PINNs outperform its unmodified counterpart, achieving root-mean-square errors that are at least two orders of magnitude better in forward problems. For inverse problems, the maximum errors in the approximated diffusion coefficients by modified AdaI-PINNs are four orders of magnitude better than those of the unmodified version. Additionally, modified AdaI-PINNs demonstrate improved stability in problems with large material mismatches.

42 ENGINEERING↗
DOE OSTI2020

Reexamining supercritical gas adsorption theories in nano-porous shales under geological conditions

Adsorption is an important phenomenon in surface chemistry, especially for nano-porous shales. In the shale gas-in-place, adsorbed gas could contribute up to 85%. However, adsorption is hard to quantitatively characterize due to different adsorption mechanisms, patterns, surfaces, and pore sizes. Moreover, key thermodynamic parameters, such as the enthalpy of adsorption, are challenging to determine due to uncertainties in adsorbed gas densities used in constructing absolute isotherms. In this paper, we revisit the Brunauer, Emmett, and Teller (BET) model, analytically simplify Ono-Kondo (OK) models for subsurface shales, and compare commonly used mono- and multilayer adsorption models (e.g., Langmuir, supercritical Dubinin-Radushkevich (SDR), supercritical BET (SBET), and simplified OK (OKs) models) with recently proposed pressure-dependent adsorption densities to develop a practical and reliable methodology that can be used in the supercritical state, typical for subsurface black shale conditions.Three independent data sets were used for nitrogen and methane adsorption isotherms at different temperatures. Furthermore, we demonstrate that adsorption predicted by the SDR model is comparable or lower than that predicted by the SBET model, but higher than the amounts predicted by Langmuir and OK models. The nitrogen BET method tends to underestimate the accessible SSA for methane. Measurement of isosteric heat of adsorption is suggested instead of the experimental fitting method, due to the significant difference between the calculated results by two commonly used methods. Experimental fitting and simulation methods are also briefly reviewed to guide future research on shale gas adsorption.

58 GEOSCIENCES↗
DOE OSTI2021

Technological aspects in blanket design: Effects of micro-alloying and thermo-mechanical treatments of EUROFER97 type steels after neutron irradiation

Presently available data on neutron irradiation damage raise doubts on the feasibility of using EUROFER97 steel for a water-cooled starter blanket in a DEMO reactor, since the ductile-to-brittle transition temperature (DBTT) increases significantly for irradiation temperatures below 350°C. The additional DBTT shift caused by H and He transmutation can only be estimated based on very few results with isotopically tailored EUROFER97 steel. Conservative calculations show that the DBTT of EUROFER97 steel could exceed the operating temperature in water-cooled starter blankets within a relatively short time period. This paper presents results from a EUROfusion funded irradiation campaign that was performed in the High Flux Isotope Reactor at Oak Ridge National Laboratory. The paper compares ten newly developed reduced activation ferritic-martensitic (RAFM) steels irradiated to a nominal dose of 2.5 dpa at 300°C. The post-irradiation experiments using Small Specimen Test Technology included hardness, tensile, and fracture mechanics tests combined with fractography and microstructure analysis are presented. Results show that micro-alloying EUROFER97-type steels influenced the mechanical properties but a dominating impact on irradiation damage resistance could not be identified. In contrast, specific thermo-mechanical treatments lead to better DBTT behavior. Discussion about irradiation response to heat treatment conditions is also given. Here, despite requiring data also at high dpa values, the results indicate that with these modified materials an increased lifetime and potentially also an increased operating temperature window can be achieved compared to EUROFER97.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Adaptive elasticity policies for staging-based in situ visualization

In situ processing aims to alleviate the growing gap between computation and I/O capabilities by performing data processing close to the data source. In situ processing is widely used to process data generated by multiple data sources, including observation data from edge devices or scientific observational facilities and the simulation data generated by scientific computation on a high-performance computing (HPC) platform. For a scientific workflow that is run on an HPC platform and composed of a simulation program and an in situ data analytics or visualization (abbreviated as ana/vis) task, there is an implicit assumption that the computing resources assigned to the workflow keep static during the workflow execution. However, with the converging trend between the HPC and cloud computing platform, running the in situ ana/vis task in an elastic way is promising to decrease its overhead and improve its resource utilization rate. Resource elasticity represents the ability to change resource configurations such as the number of computing nodes/processes during workflow execution. An elastic job may dynamically adjust resource configurations; it may use a few resources at the beginning and more resources toward the end of the job when interesting data appear. However, it is hard to predict a priori how many computing nodes/processes need to be added/removed during the workflow execution to adapt to changing workflow needs. How to efficiently guide elasticity operations, such as growing or shrinking the number of processes used for in situ analysis during workflow execution, is an open-ended research question. In this article, we present adaptive elasticity policies that adopt workflow runtime information collected during workflow execution to predict how to trigger the addition/removal of processes in order to minimize in situ processing overhead. Taking in situ visualization tasks as an example, we integrate the presented elasticity policies into a staging-based elastic workflow and evaluate its efficiency in multiple elasticity scenarios. Compared with the situation without elasticity or with a static elasticity policy that uses a fixed number of processes for each rescaling operation, the adaptive elasticity policy can save overhead in finding a proper resource configuration and improve resource utilization efficiency. Furthermore, one experiment illustrates that the adaptive elasticity policy saves 41% of core-hours compared with the situation without the resource elasticity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

QoS-aware edge AI placement and scheduling with multiple implementations in FaaS-based edge computing

Resource constraints on the computing continuum require that we make smart decisions for serving AI-based services at the network edge. AI-based services typically have multiple implementations (e.g., image classification implementations include SqueezeNet, DenseNet, and others) with varying trade-offs (e.g., latency and accuracy). The question then is how should AI-based services be placed across Function-as-a-Service (FaaS) based edge computing systems in order to maximize total Quality-of-Service (QoS). To address this question, we propose a problem that jointly aims to solve (i) edge AI service placement and (ii) request scheduling. These are done across two time-scales (one for placement and one for scheduling). Here we first cast the problem as an integer linear program. We then decompose the problem into separate placement and scheduling subproblems and prove that both are NP-hard. We then propose a novel placement algorithm that places services while considering device-to-device communication across edge clouds to offload requests to one another. Our results show that the proposed placement algorithm is able to outperform a state-of-the-art placement algorithm for AI-based services, and other baseline heuristics, with regard to maximizing total QoS. Additionally, we present a federated learning-based framework, FLIES, to predict the future incoming service requests and their QoS requirements. Our results also show that our FLIES algorithm is able to outperform a standard decentralized learning baseline for predicting incoming requests and show comparable predictive performance when compared to centralized training.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Temperature dependence of uranium and thorium partitioning in igneous zircons

Zircon is a key mineral in geochronology because of its chemical and physical durability and tendency to incorporate radioactive trace elements such as U and Th. Quantifying the partitioning of the actinide elements is critical to constrain initial non-secular equilibrium amounts of 230 Th in zircon. An excess or deficit of 206 Pb will be produced from such an initial excess/deficit of 230 Th from the secular equilibrium condition, which influences the calculated 206 Pb/ 238 U age (Schärer, 1984, Mattinson, 1973). However, there is no standard way to calculate Th/U partitioning ratios when applying age corrections to young igneous zircon, making uncertainties hard to estimate. To better understand U and Th partitioning of zircon/melt that is the cornerstone of the secular disequilibrium correction, zircon was synthesized in one-atmosphere experiments using basaltic andesite, andesite, and rhyolite starting materials, doped with Zr, U, and Th. Different experimental temperatures and oxygen fugacity conditions (ΔQFM−4 to ΔQFM+4) were explored to examine their effects on U and Th partitioning. In addition, we specifically quantify the effects of sector zoning, fractional crystallization, and melt composition on U and Th partitioning. By combining experimental and natural zircon data, we find that temperature has the primary control on the partitioning of U and Th in the zircon and calibrate an inverse relationship between these partition coefficients and crystallization temperatures. The calibrated equation can be applied to the 230 Th correction for an improvement in the accuracy of Th-corrected 206 Pb/ 238 U dates when the zircon crystallization temperature is known.

206Pb/238U dating↗
DOE OSTI2026

The need to consider regional supply chains and water usage in H 2 –steel transition

The iron and steel industry is one of the largest contributors to U.S. and global greenhouse gas emissions. Hydrogen can act as a promising reducing agent and clean energy carrier to decarbonize this sector, and has received significant attention in terms of process modelling, techno-economic analysis, and life cycle assessment in recent years. Policy incentives, hydrogen storage and transportation, and water stress levels are key factors that require significantly more consideration in order to realize hydrogen’s potential to decarbonize this industry. This review demonstrates the need for a systematic understanding and critical assessment of these areas, and their profound impacts on the decarbonization of the iron and steel sector. Furthermore, hydrogen and water supply face competition from other hard-to-decarbonize sectors, which should be considered on national and regional levels. Lastly, future research should also consider the impact of other environmental factors and hydrogen leak when deploying hydrogen at scale for industrial decarbonization.

Green steel↗
DOE OSTI2024

Modeling gas migration through clay-based buffer material using coupled multiphase fluid flow and geomechanics with stress-dependent gas permeability

A model for gas migration through clay-based buffer material is developed for modeling gas generation and migration associated with deep geologic nuclear waste disposal. The model is based on a multiphase fluid flow and geomechanics simulator that is adapted to consider enhanced gas flow when gas pressure is high enough to approach the confining stress magnitude. A key feature in the model is a direct coupling between gas permeability and stress, through a non-linear stress-dependent permeability function. The model was first tested and calibrated by modelling two different laboratory gas migration tests on Wyoming (MX-80) bentonite samples. The calibrated model was then applied to model gas migration through a bentonite buffer of a large-scale gas injection test (Lasgit) conducted at the Äspö Hard Rock Laboratory in Sweden. Observed preferential gas migration along interfaces (between compacted blocks and along the canister surface) required explicit representation of such interfaces in the model. The model with the stress-dependent gas permeability accurately captured observed experimental responses in terms of gas breakthrough time, peak gas pressure, and cumulative gas flow rates. The calibrated model was finally applied to simulate migration of hydrogen gas generated within a breached nuclear waste canister over 10,000 years, involving migration of much larger gas volumes. For the considered gas generation rate and host rock properties, the generated gas could migrate through the bentonite buffer and released into the surrounding host rock at a maximum gas pressure somewhat higher than the initial total stress, though a significant amount of hydrogen remained within the buffer. This modelling sets the stage for further detailed analysis of the impact of hydrogen gas generation on the long-term performance of nuclear waste repositories.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

A comparative analysis of numerical approaches for the description of gas flow in clay-based repository systems: From a laboratory to a large-scale gas injection test

There is nowadays a consensus among many countries that geological disposal is a favourable solution for the long-term management. Although different host formations and different barrier systems are under consideration around the world, clay-based materials form an important component for waste isolation in most national programmes. Hence, a good comprehension of the effect of gas flow on the hydro-mechanical behaviour of clay-based soils is essential, both at laboratory and field scale. Task B under the international cooperative project DECOVALEX-2023 has recently shown that, after some enhancement, models can be employed to reproduce laboratory scale tests, even with different sample geometries 37 . However, further work is required to understand whether they can be applied to simulate a large-scale experiment. Up-scaling of models for the advective transport of gas through clay-based low permeable material presents a number of problems related to the difficulty in obtaining consistent hydrogeological parameters and constitutive relationships at both laboratory and field scale. Based on a unique dataset from a large-scale gas injection test (Lasgit) performed at the Äspö Hard Rock Laboratory (Sweden), Task B within DECOVALEX-2023 has explored the refinement of these numerical strategies applied to the simulation of gas flow. Work performed within the task reveals that codes do not need to be substantially modified from the laboratory models to reproduce full-scale tests: indeed, model parameters calibrated and validated at laboratory scale have been applied to predict field scale gas flow at Lasgit, including peak gas pressure and injected cumulative gas volume. By means of (1) the introduction of interfaces between blocks to reflect the experimental configuration and the (2) adjustment of some parameters (e.g., higher permeability), the updated models are able to represent most of the key features observed in the experimental data, even at a large scale.

Tamayo-Mas, E↗
DOE OSTI2025

Ultra-high efficiency hydrogen production using a large-scale solid oxide electrolysis cell system

Efficient and cost-effective production of clean hydrogen is key to decarbonizing the production of hard-to-abate industries, such as chemicals, fuels, steel, cement and many other commodities that form the basis of modern societies. High-temperature steam electrolysis (HTSE) has recently become commercially available and offers opportunities for producing hydrogen at higher efficiency and lower cost than competing low temperature technologies. In this work, we report world record setting hydrogen production efficiency from large-scale prototype HTSE systems based on solid oxide electrolysis cell (SOEC) technology. Independent tests performed at Idaho National Laboratory (INL) employed a Bloom Energy 100 kW SOEC system to achieve a hydrogen production direct current specific electric energy consumption as low as 36.7 kWh per kilogram of hydrogen. Remarkably, similar high efficiencies in the range of 36–39 kW/kg-H2 were obtained over a wide range of hydrogen production rates and even during dynamic ramping as the hydrogen production and electric power consumption of the system were varied between 20 % and 100 % of nominal conditions. Furthermore, these test results validate previous projections that commercial SOEC systems can produce clean hydrogen at efficiencies approaching 100 % for less than 2 U S. dollars per kilogram when located near sources of inexpensive, low-grade heat and clean electricity.

08 HYDROGEN↗
DOE OSTI2020

Experimental verification of a crystal plasticity-based simulation framework for predicting microstructure and geometric shape changes: Application to bending and Taylor impact testing of Zr

This paper is concerned with experimental verification of a recently developed multi-scale simulation framework for plastic deformation of metallic materials from quasi-static to impact deformation conditions. The framework is a visco-plastic self-consistent (VPSC) polycrystalline model embedded in an implicit finite element method (FE-VPSC) to provide a microstructure-sensitive constitutive response at each material point. Each material point of the FEM model is a polycrystalline aggregate with crystallographic deformation mechanisms operating at the single crystal scale with their evolving activity based on a dislocation density-based hardening law and texture. Four beams and three cylinders machined in different orientations from a textured plate of high-purity zirconium are tested quasi-statically in 4-point bending and at speeds of 100 m/s, 170 m/s and 243 m/s during Taylor impact tests, respectively. The variation in dimensional changes resulting from different sample orientations in the plate with respect to loading directions is measured for each sample. Moreover, texture and twinning characterization is performed using electron backscattered diffraction (EBSD). The deformation processes and underlying evolution of microstructure are successfully simulated using the FE-VPSC framework. In doing so, the model parameters are optimized and validated across a broad range of strain rates and temperatures. Simulation results in terms of geometrical changes and microstructural evolution are compared with the experimental measurements. The model predicts anisotropic material flow resulting from the hard-to-deform crystallographic directions, the development of gradients in texture and twinning through the geometries, tension–compression asymmetry, as well as the extent of plasticity under impact.

42 ENGINEERING↗
DOE OSTI2023

Gradient process parameter optimization in additive friction stir deposition of aluminum alloys

As one of the most novel additive manufacturing methods, currently selection and optimization of processing parameters in additive friction stir deposition (AFSD) have mainly relied on experiments and subsequent characterization of microstructural and mechanical properties. Such approaches are both time- and resource-consuming. Therefore, an ultrasound elastography enhanced gradient process parameter optimization method was applied in the present work to obtain a window of optimized processing parameters for AFSD processing of aluminum alloy by varying both rotational and linear deposition speeds. Further, the quality of AFSD processed layer was investigated for physical nature of surface, dynamic elastic modulus, and microstructural aspects in cross-sections of the deposited layer. The efficiency in exploring process parameters was significantly enhanced by implementing a high-throughput screening experimental design based on application of gradient process parameters and continuous ultrasound elastographs. In addition, the applied ultrasonic elastography technique assisted in evaluating the homogeneity in microstructure and mechanical properties of AFSD sample over the entire gradients of the process parameters. The techniques adopted in current work can be further extended to identify suitable parameters for AFSD fabrication of components with desired mechanical properties such as hardness, fatigue, etc.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Relationship between the contact force strength and numerical inaccuracies in piecewise-smooth systems

This work studies the different types of behavior and inaccuracies that can occur when contact is not adequately accounted for in a dynamical system with freeplay, as the strength of the contact stiffness increases. The MATLAB® ode45 time integration solver, with the built-in Event Location capability, is first validated using past experimental data from a forced Duffing oscillator with freeplay. Next, numerical results utilizing event location are compared to results neglecting event location in order to highlight possible numerical errors and effects on multistable dynamical responses. Inaccuracies tend to occur in two different ways. First, neglecting event location can affect the boundaries between basins of attraction. Second, neglecting event location has little effect on the behaviors of the attractor solutions themselves besides merely resembling poorly converged solutions. Errors are less pronounced at the limits of soft or hard contact stiffness. Finally, this study shows the importance of accurately solving piecewise-smooth systems and the existing correlation between the strength of the contact force and possible numerical inaccuracies.

42 ENGINEERING↗
DOE OSTI2023

Accuracy and precision of ESI-Orbitrap-IRMS observations of hours to tens of hours via reservoir injection

Here, orbitrap isotope ratio mass spectrometry (Orbitrap-IRMS) has recently been applied to high-precision, natural-abundance isotope ratio measurements of a diverse range of compounds, including amino acids, oxyanions, fatty acids, and metals. These measurements can characterize many isotope ratios simultaneously at high (≈1.0‰) precision. In a successful experiment, observed precision will track the shot-noise limit and be limited by experimental time. Some isotope ratios, for example those involving 17 O in organic compounds or multiply-substituted (‘clumped’) isotopologues, require experimental times of hours to tens of hours to achieve desired precision, while current sample introduction techniques focus on observations on the order of seconds to tens of minutes. In this study, we characterize Orbitrap-IRMS performance for three long duration measurements (individual acquisitions ≥1 h and as long as 24 h) using an automated reservoir injection system coupled to a Q Exactive HF Orbitrap with an electrospray ionization (ESI) source. First, we characterize long-term intra-measurement stability through a 24-h long measurement of acetone. We report the following isotope ratios and precisions (as acquisition errors, errors on the observed ratio within this measurement (σ AE )): 13 C/ 12 C (σ AE = 0.07‰), 17 O/ 16 O (σ AE = 1.1‰), 18 O/ 16 O (σ AE = 0.3‰), and 13 C 13 C/ 12 C (σ AE = 0.65‰). The σ AE of each tracks the shot noise limit throughout and is limited by the challenging conditions (high resolution and low numbers of ions per scan) required for 17 O/ 16 O measurement in the presence of 13 C via Orbitrap. Second, we characterize inter-measurement stability via a sequence of seven 75-min analyses of perchlorate. We observe the following ratios and acquisition errors: 37 Cl/ 35 Cl (σ AE = 0.09‰); 17 O/ 16 O (σ AE = 1.6‰); 18 O/ 16 O (σ AE = 0.7‰), 37 Cl 17 O/ 35 Cl 16 O (σ AE = 2.7‰), and 37 Cl 18 O/ 35 Cl 16 O (σ AE = 1.2‰). However, we find that inter-measurement drift between acquisitions limits our accuracy and precision for standardized measurements (i.e., error on reported δ values) to ≈1‰ for the 37 Cl/ 35 Cl measurement. Hence, the benefits of low σ AE may not be fully realized. Third, we demonstrate accuracy via sample/standard comparisons of a methionine sample with 13 C enrichment of ≈20‰ relative to a known standard. Using a sequence of seven 60-min analyses, we recover the following isotope ratios and standardized precisions (i.e., error on reported δ values, denoted propagated acquisition errors, σ PAE ): 33 S/ 32 S (σ PAE = 1.0‰), 34 S/ 32 S (σ PAE = 0.7‰), 15 N/ 14 N (σ PAE = 2.1‰), 2 H/ 1 H (σ PAE = 3.2‰), 13 C/ 12 C (σ PAE = 0.4‰), 18 O/ 16 O (σ PAE = 1.6‰), & 13 C 13 C/ 12 C (σ PAE = 2.8‰) with confirmation of accurate results for the known 13 C/ 12 C and 13 C 13 C/ 12 C enrichments. Together, our results demonstrate the viability of Orbitrap-IRMS for long duration measurements of diverse sample types via an automated reservoir injection system. Inter-measurement stability remains a challenge; we expect our methods to be most applicable to extended measurements of hard-to-observe properties, such as 17 O in organics and clumped isotopologues.

58 GEOSCIENCES↗