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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Copper transformation, speciation, and detoxification in anoxic and suboxic freshwater sediments

The complex chemistry of copper (Cu) in freshwater sediments at low concentrations is not well understood. We evaluated the transformation processes of Cu added to freshwater sediments under suboxic and anoxic conditions. Freshwater sediments from three sources in Michigan with different characteristics (Spring Creek, River Raisin, and Maple Lake) were spiked with 30 or 60 mg kg -1 Cu and incubated under a nitrogen atmosphere. After 28-d, each treatment subset was amended with organic matter (OM) to promote anoxic conditions and evaluate its effects on Cu speciation. OM addition triggered a shift from suboxic to anoxic conditions, and sequential extractions showed that Cu accordingly shifted from acid-soluble to oxidizable fractions. Extended X-ray absorption fine-structure (EXAFS) spectroscopy revealed that Cu sulfides dominated all anoxic samples except for Spring Creek 30 mg kg -1 , where Cu(I) was predominantly complexed to thiol groups of OM. Covellite and chalcopyrite (CuFeS 2 ) were the predominant Cu species in nearly all anoxic samples, as determined by Raman spectroscopy, scanning electron microscopy, and X-ray absorption near-edge structure (XANES) spectroscopy. Copper reduction also occurred under suboxic conditions: for two of three sediments, around 80% had been reduced to Cu(I), while the remaining 20% persisted as Cu(II) complexed to OM. However, in the third coarsest (i.e., Spring Creek), around 50% of the Cu had been reduced, forming Cu(I)-OM complexes, while the remainder was Cu(II)-OM complexes. Toxicity tests showed that survival of H. azteca and D. magna were significantly lower in suboxic treatments. Anoxic sediments triggered a near-complete transformation of Cu to sulfide minerals, reducing its toxicity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Volatility-resolved chemical characterization of airborne particles

A method and apparatus for evaluating the chemical composition of airborne particles by sequentially collecting and analyzing airborne particles in-situ. The method includes: collecting particles; enlarging the particles through water condensation; accelerating the enlarged particles onto a surface to collect enlarged particles; and analyzing the enlarged particles by: isolating the surface; passing a carrier gas over the surface; heating the surface to thermally desorb collected particles into the carrier gas; transporting this evolved vapor into detectors; and assaying the evolved vapor as a function of a desorption temperature. The apparatus includes: a sample flow inlet; a condensational growth tube; a collection and thermal desorption (CTD) cell; a carrier gas source; a heater coupled to the CTD; one or more gas detectors; and a controller configured to operate valves, the heater, the growth tube, and the CTD cell in at least an in-situ sequential collection mode and analysis mode.

Isaacman-VanWertz, Gabriel↗
DOE OSTI2016

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers have high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30–60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. Furthermore, the proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Direct fabrication and characterization of vertically stacked Graphene/h-BN/Graphene tunnel junctions

We have used a lithography free technique for the direct fabrication of vertically stacked two-dimensional (2D) material-based tunnel junctions and characterized by Raman, AFM, XPS. We fabricated Graphene/h-BN/Graphene devices by direct deposition of graphene (bottom layer), h-BN (insulating barrier) and graphene (top layer) sequentially using a plasma enhanced chemical vapor deposition on Si/SiO 2 substrates. The thickness of the h-BN insulating layer was varied by tuning the plasma power and the deposition time. Samples were characterized by Raman, AFM, and XPS. The I-V data follows the barrier thickness dependent quantum tunneling behavior for equally doped graphene layers. The resonant tunneling behavior was observed at room temperature for oppositely doped graphene layers where hydrazine and ammonia were used for n-doping of one of the graphene layers. The resonance with negative differential conductance occurs when the band structures of the two electrodes are aligned. The doping effect of the resonant peak is observed for varying doping levels. The results are explained according to the Bardeen tunneling model.

2D-materials↗
DOE OSTI2024

Sequential Monte Carlo for Cut-Bayesian Posterior Computation

We propose a sequential Monte Carlo (SMC) method to efficiently and accurately compute cut-Bayesian posterior quantities of interest, variations of standard Bayesian approaches constructed primarily to account for model misspecification. We prove finite sample concentration bounds for estimators derived from the proposed method along with a linear tempering extension and apply these results to a realistic setting where a computer model is misspecified. We then illustrate the SMC method for inference in a modular chemical reactor example that includes submodels for reaction kinetics, turbulence, mass transfer, and diffusion. The samples obtained are commensurate with a direct-sampling approach that consists of running multiple Markov chains, with computational efficiency gains using the SMC method. Overall, the SMC method presented yields a novel, rigorous approach to computing with cut-Bayesian posterior distributions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Acquisition of STEM Images by Adaptive Compressive Sensing

Compressive Sensing (CS) allows a signal to be sparsely measured first and accurately recovered later in software [1]. In scanning transmission electron microscopy (STEM), it is possible to compress an image spatially by reducing the number of measured pixels, which decreases electron dose and increases sensing speed [2,3,4]. The two requirements for CS to work are: (1) sparsity of basis coefficients and (2) incoherence of the sensing system and the representation system. However, when pixels are missing from the image, it is difficult to have an incoherent sensing matrix. Nevertheless, dictionary learning techniques such as Beta-Process Factor Analysis (BPFA) [5] are able to simultaneously discover a basis and the sparse coefficients in the case of missing pixels. On top of CS, we would like to apply active learning [6,7] to further reduce the proportion of pixels being measured, while maintaining image reconstruction quality. Suppose we initially sample 10% of random pixels. We wish to select the next 1% of pixels that are most useful in recovering the image. Now, we have 11% of pixels, and we want to decide the next 1% of “most informative” pixels. Active learning methods are online and sequential in nature. Our goal is to adaptively discover the best sensing mask during acquisition using feedback about the structures in the image. In the end, we hope to recover a high quality reconstruction with a dose reduction relative to the non-adaptive (random) sensing scheme. In doing this, we try three metrics applied to the partial reconstructions for selecting the new set of pixels: (1) variance, (2) Kullback-Leibler (KL) divergence using a Radial Basis Function (RBF) kernel, and (3) entropy. Figs. 1 and 2 display the comparison of Peak Signal-to-Noise (PSNR) using these three different active learning methods at different percentages of sampled pixels. At 20% level, all the three active learning methods underperform the original CS without active learning. However, they all beat the original CS as more of the “most informative” pixels are sampled. One can also argue that CS equipped with active learning requires less sampled pixels to achieve the same value of PSNR than CS with pixels randomly sampled, since all the three PSNR curves with active learning grow at a faster pace than that without active learning. For this particular STEM image, by observing the reconstructed images and the sensing masks, we find that while the method based on RBF kernel acquires samples more uniformly, the one on entropy samples more areas of significant change, thus less uniformly. The KL-divergence method performs the best in terms of reconstruction error (PSNR) for this example [8].

Xie, Weiyi↗
DOE OSTI2019

TiO{sub 2} Photocatalyzed Oxidation of Drugs Studied by Laser Ablation Electrospray Ionization Mass Spectrometry

In drug discovery, it is important to identify phase I metabolic modifications as early as possible to screen for inactivation of drugs and/or activation of prodrugs. As the major class of reactions in phase I metabolism is oxidation reactions, oxidation of drugs with TiO{sub 2} photocatalysis can be used as a simple non-biological method to initially eliminate (pro)drug candidates with an undesired phase I oxidation metabolism. Analysis of reaction products is commonly achieved with mass spectrometry coupled to chromatography. However, sample throughput can be substantially increased by eliminating pretreatment steps and exploiting the potential of ambient ionization mass spectrometry (MS). Furthermore, online monitoring of reactions in a time-resolved way would identify sequential modification steps. Here, we introduce a novel (time-resolved) TiO{sub 2}-photocatalysis laser ablation electrospray ionization (LAESI) MS method for the analysis of drug candidates. This method was proven to be compatible with both TiO{sub 2}-coated glass slides as well as solutions containing suspended TiO{sub 2} nanoparticles, and the results were in excellent agreement with studies on biological oxidation of verapamil, buspirone, testosterone, andarine, and ostarine. Finally, a time-resolved LAESI MS setup was developed and initial results for verapamil showed excellent analytical stability for online photocatalyzed oxidation reactions within the set-up up to at least 1 h. .

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2015

High Thermoelectric Performance in Copper Telluride

Recently, Cu 2-δ S and Cu 2-δ Se were reported to have an ultralow thermal conductivity and high thermoelectric figure of merit zT. Thus, as a member of the copper chalcogenide group, Cu 2-δ Te is expected to possess superior zTs because Te is less ionic and heavy. However, the zT value is low in the Cu 2 Te sintered using spark plasma sintering, which is typically used to fabricate high-density bulk samples. In addition, the extra sintering processes may change the samples’ compositions as well as their physical properties, especially for Cu 2 Te, which has many stable and meta-stable phases as well as weaker ionic bonding between Cu and Te as compared with Cu 2 S and Cu 2 Se. In this study, high-density Cu 2 Te samples were obtained using direct annealing without a sintering process. In the absence of sintering processes, the samples’ compositions could be well controlled, leading to substantially reduced carrier concentrations that are close to the optimal value. The electrical transports were optimized, and the thermal conductivity was considerably reduced. The zT values were significantly improved—to 1.1 at 1000 K—which is nearly 100% improvement. Furthermore, this method saves substantial time and cost during the sample’s growth. The study demonstrates that Cu 2-δ X (X=S, Se and Te) is the only existing system to show high zTs in the series of compounds composed of three sequential primary group elements.

14 SOLAR ENERGY↗
DOE OSTI2017

Sequential geophysical and flow inversion to characterize fracture networks in subsurface systems

Subsurface applications, including geothermal, geological carbon sequestration, and oil and gas, typically involve maximizing either the extraction of energy or the storage of fluids. Fractures form the main pathways for flow in these systems, and locating these fractures is critical for predicting flow. However, fracture characterization is a highly uncertain process, and data from multiple sources, such as flow and geophysical are needed to reduce this uncertainty. We present a nonintrusive, sequential inversion framework for integrating data from geophysical and flow sources to constrain fracture networks in the subsurface. In this framework, we first estimate bounds on the statistics for the fracture orientations using microseismic data. These bounds are estimated through a combination of a focal mechanism (physics-based approach) and clustering analysis (statistical approach) of seismic data. Then, the fracture lengths are constrained using flow data. In conclusion, the efficacy of this inversion is demonstrated through a representative example.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Reconstruction Techniques for Sparse Multistatic Linear Array Microwave Imaging

Sequentially-switched linear arrays are an enabling technology for a number of near-field microwave imaging applications. Electronically sequencing along the array axis followed by mechanical scanning along an orthogonal axis allows dense sampling of a two-dimensional aperture in near real-time. In this paper, a sparse multi-static array technique will be described along with associated Fourier-Transform-based and back-projection-based image reconstruction algorithms. Simulated and measured imaging results are presented that show the effectiveness of the sparse array technique along with the merits and weaknesses of each image reconstruction approach.

concealed-weapon detection↗
DOE OSTI2020

Application of end-of-shift respirable crystalline silica monitoring to construction

A pilot project was conducted to determine the effect of common construction dusts as interferences in a new portable end-of-shift (EoS), direct-on-filter (DoF) sampling and analysis method for respirable crystalline silica (RCS), in this case, quartz. Construction dusts were prepared from plaster, drywall, cement and brick by grinding, aerosolizing, and collecting respirable dust with high flow rate cyclones. Filters were loaded with different levels of commercial α-quartz powder Min-u-Sil 5, and different levels of interfering dusts, singly and in combination. Samples were analyzed by Fourier Transform Infrared Spectroscopy (FTIR). Good correlations were found between nominal quartz loading (0 µg, 25 µg, 50 µg, and 100 µg) adjusted for quartz in the interfering dust and FTIR absorbance alone and in the presence of all interfering dusts. The slopes of the correlations were similar whether the loading was quartz without interference, or with plaster, drywall, and cement dusts, regardless of quantity. The results show that (a) plaster and drywall dusts do not interfere substantially; (b) cement does not interfere, but a change in the intercept suggests an effect on the background absorbance of the filter; and (c) in addition to having a substantial quartz content, brick dust contains an additional material, probably a silicate mineral, which interferes with the quartz peak. Thus, the presence of cement leads to lower quartz values and brick leads to higher values, but overall, 83% of the quartz contents predicted from the calibration data agreed within 50% of the adjusted nominal loadings within the range 20–110 µg. This result is encouraging given the high levels of interfering dusts. Nine samples loaded with smaller amounts of all four dusts together gave results within 25% of the adjusted nominal loadings. A single mixture addition of the dusts to the filter gave tighter variance in results than sequential additions. Unexpectedly, the two Certified Reference Materials (CRMs) 1878a and 1878b, gave different results when used to calibrate XRD analysis of Min-u-Sil 5.

42 ENGINEERING↗
DOE OSTI2021

Core-flood Effluent and Shale Surface Chemistries in Predicting Interaction between Shale, Brine, and Reactive Fluid

We report field and laboratory observations to date indicate that the efficiency of hydraulic fracturing, as it relates to hydrocarbon recovery, depends significantly on geochemical alterations to rock surfaces that diminish accessibility by partial or total plugging of the pore and fracture networks. This is caused by mineral scale deposition such as coating of fracture surfaces with precipitates, particle migration, and/or crack closure due to dissolution under stress. In reactive flow-through experiments, mineral reactions in response to acidic fluid injection significantly reduced system porosity and core permeability. The present study focuses on changes to fluid chemistry and shale surfaces (inlet and fracture walls) resulting from shale-fluid interactions and integrating these findings for an improved estimate of transport-related consequences. The reacted shale surfaces were examined by spatially-resolved scanning electron microscopy - energy dispersive spectroscopy (SEM-EDS) analysis. Importantly, inductively coupled plasma - mass spectrometry/optical emission spectroscopy (ICP-MS/OES) was utilized to probe the chemical evolution of the core-flood effluents. The three study cores selected from the Marcellus formation represent different mineralogies and structural features. In flow-through experiments, lab-generated brine and HCl-based fracture fluid (pH=2) were injected sequentially under effective stress (up to 500 psi) at reservoir temperature (80°C). SEM-EDS results confirmed by the ICP concentration trends showed significant Fe hydroxide precipitates in clay- and pyrite-rich outcrop samples due to partial oxidation of Fe-bearing phases in the case of intrusion of low salinity water-based fluids. Porosity reduction in the MSEEL (Marcellus Shale Energy and Environmental Laboratory) carbonate-rich sample is related to compaction of cores under stress due to matrix softening with substantial dissolution, and pore-filling by hydroxides, as well as barite and salts. Despite the same fluid compositions and experimental conditions used for both MSEEL samples, barite precipitation was much more intense in the MSEEL clay-rich sample due to its greater sorption capacity and additional sulfate source as well as fissile nature with multiple lengthwise cracks. ICP tests revealed time-resolved concentration trends in produced brine and reactive fluids that in turn complemented the pre-/post-reaction SEM-EDS observations.

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

A Note on the Effects of Linear Topology Preservation in Monte Carlo Simulations of Knotted Proteins

Monte Carlo simulations are a powerful technique and are widely used in different fields. When applied to complex molecular systems with long chains, such as those in synthetic polymers and proteins, they have the advantage of providing a fast and computationally efficient way to sample equilibrium ensembles and calculate thermodynamic and structural properties under desired conditions. Conformational Monte Carlo techniques employ a move set to perform the transitions in the simulation Markov chain. While accepted conformations must preserve the sequential bonding of the protein chain model and excluded volume among its units, the moves themselves may take the chain across itself. We call this a break in linear topology preservation. In this manuscript, we show, using simple protein models, that there is no difference in equilibrium properties calculated with a move set that preserves linear topology and one that does not. However, for complex structures, such as those of deeply knotted proteins, the preservation of linear topology provides correct equilibrium results but only after long relaxation. In any case, to analyze folding pathways, knotting mechanisms and folding kinetics, the preservation of linear topology may be an unavoidable requirement.

Especial, João N. C. (ORCID:0000000254765370)↗
DOE OSTI2020

Robust Online Sequential RVFLNs for Data Modeling of Dynamic Time-Varying Systems with Application of an Ironmaking Blast Furnace

In a world where the increasing complexity of modern industrial processes brings difficulties for accurate mathematical modeling, taking advantage of data has become an efficient solution to complex dynamic process modeling issue. In this paper, we develop a novel robust online sequential version of random vector functional-link networks (RVFLNs) for data-driven modeling of dynamic time-varying system and applied it in a blast furnace (BF) ironmaking process. First, to overcome the time-varying dynamics of process and to enable the RVFLNs to learn online with avoiding data saturation, an improved online sequential version of RVFLNs (OS-RFVLNs) is first presented by online sequential learning with forgetting factor. This improved OS-RVFLNs algorithm is not only suitable for the real-time and large data transfer situation, but also can adjust the sensitivity of the algorithm to different samples with the help of the introduced forgetting factor. Second, since the output weights of the improved OS-RVFLNs as well as other RVFLNs algorithms are obtained by the least squares approach, a robustness problem may occur when the training dataset is contaminated with various outliers. To solve this problem, a Cauchy distribution weighted M-estimator is introduced to improve the robustness of the improved OS- RVFLNs. For this proposed robust OS-RVFLNs (R-OS- RVFLNs), since the weights of different outlier data are properly determined by the Cauchy distribution function, their corresponding contribution on modeling can be properly distinguished. Thus robust and better modeling results can be achieved. Experiments using actual industrial data of BF ironmaking process and comparative studies have demonstrated that the proposed method produces a better estimation accuracy and stronger robustness than other methods.

Blast furnace (BF), Modelling, Dynamic systems↗
DOE OSTI2025

Partitioned Quantum Subspace Expansion

We present an iterative generalisation of the quantum subspace expansion algorithm used with a Krylov basis. The iterative construction connects a sequence of subspaces via their lowest energy states. Diagonalising a Hamiltonian in a given Krylov subspace requires the same quantum resources in both the single step and sequential cases. We propose a variance-based criterion for determining a good iterative sequence and provide numerical evidence that these good sequences display improved numerical stability over a single step in the presence of finite sampling noise. Implementing the generalisation requires additional classical processing with a polynomial overhead in the subspace dimension. By exchanging quantum circuit depth for additional measurements the quantum subspace expansion algorithm appears to be an approach suited to near term or early error-corrected quantum hardware. Our work suggests that the numerical instability limiting the accuracy of this approach can be substantially alleviated in a parameter-free way.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Electron Transfer Dissociation of All Ions at All Times, MS{sup ETD}, in a Quadrupole Time-of-Flight (Q-ToF) Mass Spectrometer

Data-independent mass spectral acquisition is particularly powerful when combined with ultra-performance liquid chromatography (LC) that provides excellent separation of most components present in a given sample. Data-independent analysis (DIA) consists of alternating full MS scans and scans with fragmentation of all ions within a selected m/z range, providing precursor masses and structure information, respectively. Fragmentation spectra are acquired either by sequential isolation and fragmentation of sliding m/z ranges or fragmenting all ions entering the MS instrument with no ion isolation, termed broadband DIA. Previously, broadband DIA has only been possible using collision induced dissociation (CID). Here, we report the use of electron transfer dissociation (ETD) as the fragmentation technique in broadband DIA instead of traditional collision induced dissociation (CID) during MS{sup E}. In this approach, which we refer to as MS{sup ETD}, we implement the inherent benefits provided by ETD, such as discrimination of leucine and isoleucine, in a DIA setup. The combination of DIA analysis and ETD fragmentation with supplemental CID energy provides a powerful platform to obtain information on all precursors and their sequence from a single experiment. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

A Comparative Study of Single-pulse and Double-pulse Laser-Induced Breakdown Spectroscopy with Uranium-containing Samples

Laser-induced breakdown spectroscopy (LIBS) holds potential advantages in special nuclear material (SNM) sensing and nuclear forensics which require rapid analysis, minimal sample preparation and stand-off distance capability. SNM, such as U, however, result in crowded emission spectra with LIBS, and characteristic emission lines are challenging to discern. It is well-known that double-pulse LIBS (DPLIBS) improves the signal intensity for analytes over conventional single-pulse LIBS (SPLIBS). This study investigates U signal in a glass matrix using DPLIBS and compares to signal features obtained using SPLIBS. DPLIBS involves sequential firing of 1.06 µm Nd:YAG pre-pulse and 10.6 µm TEA CO2 heating pulse in near collinear geometry. Optimization of experimental parameters including inter-pulse delay and energy follows identification of characteristic lines and signals for bulk analyte Ca and minor constituent analyte U for both DPLIBS and SPLIBS. Spatial and temporal coupling of the two pulses in the proposed DPLIBS technique yields improvements in analytical merits with negligible further damage to the sample compared to SPLIBS. Subsequently, the study discusses optimum plasma emission conditions of U lines and relative figures of merit in both SPLIBS and DPLIBS. Investigation into plasma characteristics also addresses plausible mechanisms related to observed U analyte signal variation between SPLIBS and DPLIBS.

Skrodzki, P. J.↗
DOE OSTI2025

Evaluating the feasibility of LA-ICP-TOF-MS for the analysis of environmental particle collections

Laser ablation-inductively coupled plasma-time-of-flight-mass spectrometry (LA-ICP-TOF-MS) was employed to rapidly analyze environmental particle samples collected using aerosol contaminate extractors (ACE). The ACE particle collectors were placed at various distances (0.5, 1.3, and 4.5 km) from a source that released Ru-bearing particles. Samples for measurement were then generated (as sub-samples) from the ACE collection plates via particle “lift off” with gunshot residue (GSR) tabs. The LA-ICP-TOF-MS method was employed such that 10+ samples could be analyzed in a single unattended analytical session. A 3 × 1 mm area of individual GSR tab samples were analyzed in less than 30 minutes. This provided spatially resolved elemental and isotopic measurements of the particulate content and confirmed the presence of Ru-bearing particles within the complex background environmental particle loading. As anticipated, measurements showed collectors closest to the source had the highest concentration of the released Ru-bearing particles, while all collectors, regardless of distance, contained similar levels of background particles (e.g., Fe and Sr). Sequential scanning electron microscopy – automated particle analysis (SEM-APA) and LA-ICP-TOF-MS analysis was employed for method validation and a demonstration of the multi-modal approach. The same 2-dimensional region was analyzed by both methods and the particles identified via SEM-APA were also detected using LA-ICP-TOF-MS, with 100% accuracy. Overall, LA-ICP-TOF-MS demonstrated its utility for rapid elemental and isotopic particle analysis from environmental air samples.

Manard, Benjamin T. [Oak Ridge National Laboratory↗