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NASA NTRS2016

Conversion and Extraction of Insoluble Organic Materials in Meteorites

We endeavor to develop and implement methods in our laboratory to convert and extract insoluble organic materials (IOM) from low car-bon bearing meteorites (such as ordinary chondrites) and Precambrian terrestrial rocks for the purpose of determining IOM structure and prebiotic chemistries preserved in these types of samples. The general scheme of converting and extracting IOM in samples is summarized in Figure 1. First, powdered samples are solvent extracted in a micro-Soxhlet apparatus multiple times using solvents ranging from non-polar to polar (hexane - non-polar, dichloromethane - non-polar to polar, methanol - polar protic, and acetonitrile - polar aprotic). Second, solid residue from solvent extractions is processed using strong acids, hydrochloric and hydrofluoric, to dissolve minerals and isolate IOM. Third, the isolated IOM is subjected to both thermal (pyrolysis) and chemical (oxidation) degradation to release compounds from the macromolecular material. Finally, products from oxidation and pyrolysis are analyzed by gas chromatography - mass spectrometry (GCMS). We are working toward an integrated method and analysis scheme that will allow us to determine prebiotic chemistries in ordinary chondrites and Precambrian terrestrial rocks. Powerful techniques that we are including are stepwise, flash, and gradual pyrolysis and ruthenium tetroxide oxidation. More details of the integrated scheme will be presented.

Locke, Darren R.↗

DOE OSTI2023

The kinetics of the PuO 2 to Pu 2 O 3 conversion

Here in an oxidizing environment, the oxide formed on plutonium (Pu) metal is composed of a plutonium dioxide (PuO 2 ) top layer and a thin cubic plutonium sesquioxide (Pu 2 O 3 ) middle layer. In a reducing environment, the PuO 2 layer auto-reduces to cubic Pu 2 O 3 . The speed and extent of this conversion depend on the combination of temperature and time. While PuO 2 provides a strong diffusion barrier against unwanted Pu corrosion by gaseous species (like hydrogen), Pu 2 O 3 does not, since its crystal structure has chains of oxygen vacancies. The kinetics of the PuO 2 reduction are, therefore, of fundamental interest and enable researchers to better protect Pu from corrosion. In this report, the oxygen-diffusion-limited kinetics of the dioxide to sesquioxide conversion were obtained by dynamically heating a PuO 2 -covered Pu sample from 294 to 418 K in a high-vacuum vessel equipped with an in situ spectroscopic ellipsometer. The physical/chemical constraints in the conversion process were combined with the ellipsometry method of multi-sample analysis to track the percentage of PuO 2 and to compute the extent of Pu 2 O 3 formation. The resulting diffusion coefficients were compared against and then combined with complementary literature data to produce a comprehensive set of kinetic parameters for reliably modeling oxide conversion over a larger temperature range than spanned by prior studies. The extracted thermal activation energy barrier (43.7 kJ/mol) and pre-exponential factor (5.0 × 10 -10 cm 2 /s) for the oxygen-diffusion-limited process can be used to accurately model the PuO 2 to Pu 2 O 3 transformation in vacuum and/or inert gas applications.

36 MATERIALS SCIENCE↗

DOE OSTI2023

SPRUCE Climate Warming and Elevated CO2 Rapidly Alter Peatland Soil Carbon Sources and Stability: Supporting Data

This data set reports a suite of complementary biogeochemical analyses of peat samples from the SPRUCE (Spruce and Peatland Responses Under Changing Environments) experiment. Results were collected using quantitative molecular analysis of bulk soil carbon to assess the stability of soil organic carbon following whole-ecosystem warming and exposure to elevated carbon dioxide concentrations (eCO2). Targeted soil organic carbon components include solvent-extractable compounds (alkanoic acids, alkanols, alkanes, steroids, and terpenoids), ester-bound hydrolysable biopolymers (cutin and suberin markers), lignin phenols, and pyrogenic carbon. Bulk peat samples were analysed by Soxhlet extraction and solid phase separation for solvent-extractable compounds, alkaline hydrolysis to extract hydrolysable biopolymers, copper (II) oxide oxidation to extract lignin phenols and benzene polycarboxylic acids (BPCAs) as an approximation of pyrogenic carbon. Samples were analysed by gas chromatography (GC) equipped with a flame ionization detector (GC-FID) and compound identification was performed on GC coupled to mass selective detector (MS) for solvent-extractable compounds, ester-bound hydrolysable biopolymers and lignin phenols, and high-performance liquid chromatograph (HPLC) for pyrogenic carbon. Results are presented in Ofiti et al. (accepted). The experimental work was conducted on samples collected in August 2018 at the SPRUCE climate manipulation experiment in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). Samples were collected and later analysed in a 10 cm increments over 0 to 50 cm depth and 25 cm intervals from 50 to 75 cm. Samples were analyzed for lignin phenols over 0 to 30 cm depth. This data set contains one file in comma separate (*.csv) format. This dataset contains data used to produce: Ofiti, N.O.E., Schmidt, M.W.I., Abiven, S., Hanson, P.J., Iversen, C.M., Wilson, R.M., Kostka, J.E., Wiesenberg, G.L.B., Malhotra, A. 2023. Climate warming and elevated CO2 rapidly alter peatland soil carbon sources and stability. Nat Commun 14, 7533. https://doi.org/10.1038/s41467-023-43410-z.

SPRUCE experiment, Marcell Experimental Forest, so↗

DOE OSTI2022

Ch3MS-RF: a random forest model for chemical characterization and improved quantification of unidentified atmospheric organics detected by chromatography–mass spectrometry techniques

Abstract. The chemical composition of ambient organic aerosols plays a critical role in driving their climate and health-relevant properties and holds important clues to the sources and formation mechanisms of secondary aerosol material. In most ambient atmospheric environments, this composition remains incompletely characterized, with the number of identifiable species consistently outnumbered by those that have no mass spectral matches in the literature or the National Institute of Standards and Technology/National Institutes of Health/Environmental Protection Agency (NIST/NIH/EPA) mass spectral databases, making them nearly impossible to definitively identify. This creates significant challenges in utilizing the full analytical capabilities of techniques which separate and generate spectra for complex environmental samples. In this work, we develop the use of machine learning techniques to quantify and characterize novel, or unidentifiable, organic material. This work introduces Ch3MS-RF (Chemical Characterization by Chromatography–Mass Spectrometry Random Forest Modeling), an open-source, R-based software tool, for efficient machine-learning-enabled characterization of compounds separated in chromatography–mass spectrometry applications but not identifiable by comparison to mass spectral databases. A random forest model is trained and tested on a known 130 component representative external standard to predict the response factors of novel environmental organics based on position in volatility–polarity space and mass spectrum, enabling the reproducible, efficient, and optimized quantification of novel environmental species. Quantification accuracy on a reserved 20 % test set randomly split from the external standard compound list indicates that random forest modeling significantly outperforms the commonly used methods in both precision and accuracy, with a median response factor percent error of −2 %, for modeled response factors, compared to > 15 %, for typically used proxy assignment-based methods. Chemical properties modeling, evaluated on the same reserved 20 % test set and an extrapolation set of species identified in ambient organic aerosol samples collected in the Amazon rainforest, also demonstrate robust performance. Extrapolation set property prediction mean absolute errors for carbon number, oxygen to carbon ratio (O : C), average carbon oxidation state (OSc‾), and vapor pressure are 1.8, 0.15, 0.25, and 1.0 (log(atm)), respectively. Extrapolation set out-of-sample R2 for all properties modeled are above 0.75, with the exception of vapor pressure. While predictive performance for vapor pressure is less robust compared to the other chemical properties modeled, random-forest-based modeling was significantly more accurate than other commonly used methods of vapor pressure prediction, decreasing the mean vapor pressure prediction error to 0.24 (log(atm)) from 0.55 (log(atm)) (chromatography-based vapor pressure prediction) and 1.2 (log(atm)) (chemical formula-based vapor pressure prediction). The random forest model significantly advances an untargeted analysis of the full scope of chemical speciation yielded by two-dimensional gas chromatography (GCxGC-MS) techniques and can be applied to gas chromatography coupled with electron ionization mass spectrometry (GC-MS) as well. It enables the accurate estimation of key chemical properties commonly utilized in the atmospheric chemistry community, which may be used to more efficiently identify important tracers for further individual analysis and to characterize compound populations uniquely formed under specific ambient conditions.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2021

Half of global methane emissions come from highly variable aquatic ecosystem sources

Atmospheric methane is a potent greenhouse gas that plays a major role in controlling the Earth’s climate. The causes of the renewed increase of methane concentration since 2007 are uncertain given the multiple sources and complex biogeochemistry. Here, we present a metadata analysis of methane fluxes from all major natural, impacted and human-made aquatic ecosystems. Our revised bottom-up global aquatic methane emissions combine diffusive, ebullitive and/or plant-mediated fluxes from 15 aquatic ecosystems. We emphasize the high variability of methane fluxes within and between aquatic ecosystems and a positively skewed distribution of empirical data, making global estimates sensitive to statistical assumptions and sampling design. We find aquatic ecosystems contribute (median) 41% or (mean) 53% of total global methane emissions from anthropogenic and natural sources. We show that methane emissions increase from natural to impacted aquatic ecosystems and from coastal to freshwater ecosystems. We argue that aquatic emissions will probably increase due to urbanization, eutrophication and positive climate feedbacks and suggest changes in land-use management as potential mitigation strategies to reduce aquatic methane emissions.

aquatic ecosystem↗

DOE OSTI2022

Machine learning approaches to streamline and enhance the analysis of multiscale imaging data for bioaerosol and soil particles

Bioaerosol and soil particles are ubiquitous in the environment. They are multicomponent and complex in nature displaying mixed inorganic and organic components. The way components are mixed in a bioaerosol sample is referred to as its mixing state. Soil particles are also a mixture of inorganic (mineral) and organic (soil organic matter) components. Bioaerosol particles contribute to a major fraction of coarse mode atmospheric particles, especially in the tropical areas, contributing up to 80 % of the particle mass concentration. The mixing state of particles is crucial to evaluate because it impacts several important environmental processes such as warm and cold cloud formation and radiation budget. Mixing states in aerosols are accompanied by chemical reactions across solid-liquid-gas interfaces. In this study, we utilized elemental compositions and microcopy images of thousands of atmospheric particles acquired by computer-controlled scanning electron microscope equipped with an energy-dispersive x-ray spectrometer to compute the mixing state of atmospheric particles. A 2D convolutional neural network (CNN), also known as convnet, was used to model the relationship between low resolution imaging data and higher resolution spectroscopy data, with the former as training input and the latter as target output. Two types of CNNs were implemented and tested; a basic CNN and an Inception-v3 network. For binary classification, the basic CNN achieved an accuracy of 84.29 % across all atom types, and the Inception-v3-like network achieved an accuracy 85.51 %. This study demonstrates the applicability of deep learning to handle large amounts of imaging/chemical spectroscopy data efficiently and evaluate particle mixing state from a range of environmental samples.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Assessing Gas-Phase Ion Reactivity of 50 Elements with NO and the Direct Application for 239 Pu in Complex Matrices Using ICP-MS/MS

Understanding the reactivity of metal cations with various reaction gases in ICP-MS/MS is important to determine the best gas to use for a given analyte/interference pair. In this study, nitric oxide (NO) was investigated as the reaction gas following previous experimental designs. The reactions with 50 elements were investigated to examine periodic trends in reactivity, validate theoretical modeling of reaction enthalpies as a method to screen reactant gases, and provide a baseline for potential in-line gas separation methods. ICP-MS/MS studies involving actinides are typically limited to Th, U and Pu, with analyses of Np and Am rarely reported in the literature. To date, only two previous methods have investigated the use of NO in ICP-MS/MS analyses. To showcase the utility of NO, a method was developed to measure 239 Pu in the presence of environmental matrix constituent and other actinides, like what could be expected from post-detonation debris, with no chemical separation prior to analysis. 239 Pu + was reacted to form 239 Pu 16 O + , eliminating interferences derived from the sample matrix by measuring 239 Pu + intensity at m/z = 255 ( 239 Pu 16 O + ). To validate NO for 238 U 1 H + interference removal in environmental matrices, standard reference materials were diluted to 1 mg per gram of solution and spiked to 0.05 pg/g of 239 Pu and 1 µg/g 238 U (Pu/U = 5 x 10 -8 ). Measured 239 Pu concentrations were within 6% of the spiked value. In conclusion, these results demonstrate that reliable 239 Pu measurements can be made at levels relevant to nuclear forensics without the need for extensive chemical matrix separation prior to analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

High-Frequency Greenhouse Gas Flux Measurement System Detects Winter Storm Surge Effects on Salt Marsh

The physical controlling factors on coastal plant communities are among the most dynamic of known ecosystems, but climate change alters coastal surface and subsurface hydrologic regimes, which makes rapid measurement of greenhouse gas fluxes critical. Greenhouse gas exchange rates in these terrestrial–aquatic ecosystems are highly variable worldwide with climate, soil type, plant community, and weather. Therefore, increasing data collection and availability should be a priority. Here, we demonstrate and validate physical and analytical modifications to automated soil–flux chamber measurement methods for unattended use in tidally driven wetlands, allowing the high–frequency capture of storm surge and day/night dynamics. Winter CO 2 flux from Sarcocornia perennis marsh to the atmosphere was significantly greater during the day (2.8 mg m –2 h –1 ) than the night (2.2 mg m –2 h –1 ) (p < 0.001), while CH 4 was significantly greater during the night (0.16 μg m –2 h –1 ) than the day (–0.13 μg m –2 h –1 ) (p = 0.04). The magnitude of CO 2 flux during the day and the frequency of CH 4 flux were reduced during a surge (p < 0.001). Surge did not significantly affect N 2 O flux, which without non–detects was normally distributed around –24.2 ng m –2 h –1 . Analysis of sustained–flux global potentials for increased storm surge frequency scenarios, 2020 to 2100, suggested that the marsh in winter remains an atmospheric CO 2 sink. The modeled results showed an increased flux of CO 2 to the atmosphere, while in soil, the uptake of CH 4 increased and N 2 O uptake decreased. We present analytical routines to correctly capture gas flux curves in dynamic overland flooding conditions and to flag data that are below detection limits or from unobserved chamber–malfunction situations. Storm surge is an important phenomenon globally, but event–driven, episodic factors can be poorly estimated by infrequent sampling. Here, deployment of this system in coastal marshes worldwide would permit its inclusion in flux calculations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Independent Analysis of Real-Time, Measured Performance Data From Microcogenerative Fuel Cell Systems Installed in Buildings

Pacific Northwest National Laboratory (PNNL) is working with industry to independently monitor up to 15 distinct 5 kW-electric (kWe) combined heat and power (CHP) high temperature (HT) proton exchange membrane (PEM) fuel cell systems (FCSs) installed in light commercial buildings. This research paper discusses an evaluation of the first six months of measured performance data acquired at a 1 s sampling rate from real-time monitoring equipment attached to the FCSs at building sites. Engineering performance parameters are independently evaluated. Based on an analysis of the first few months of measured operating data, FCS performance is consistent with manufacturer-stated performance. Initial data indicate that the FCSs have relatively stable performance and a long-term average production of about 4.57 kWe of power. This value is consistent with, but slightly below, the manufacturer's stated rated electric power output of 5 kWe. The measured system net electric efficiency has averaged 33.7%, based on the higher heating value (HHV) of natural gas fuel. This value, also, is consistent with, but slightly below, the manufacturer's stated rated electric efficiency of 36%. The FCSs provide low-grade hot water to the building at a measured average temperature of about 48.4 degrees C, lower than the manufacturer's stated maximum hot water delivery temperature of 65 degrees C. The uptime of the systems is also evaluated. System availability can be defined as the quotient of total operating time compared to time since commissioning. The average values for system availability vary between 96.1 and 97.3%, depending on the FCS evaluated in the field. Performance at rated value for electrical efficiency (PRVeff) can be defined as the quotient of the system time operating at or above the rated electric efficiency and the time since commissioning. The PRVeff varies between 5.6% and 31.6%, depending on the FCS field unit evaluated. Performance at rated value for electrical power (PRVp) can be defined as the quotient of the system time operating at or above the rated electric power and the time since commissioning. PRVp varies between 6.5% and 16.2%. Performance at rated value for electrical efficiency and power (PRVt) can be defined as the quotient of the system time operating at or above both the rated electric efficiency and the electric power output compared to the time since commissioning. PRVt varies between 0.2% and 1.4%. Optimization to determine the manufacturer rating required to achieve PRVt greater than 80% has been performed based on the collected data. For example, for FCS Unit 130 to achieve a PRVt of 95%, it would have to be down-rated to an electrical power output of 3.2 kWe and an electrical efficiency of 29%. The use of PRV as an assessment metric for FCSs has been developed and reported for the first time in this paper. For FCS Unit 130, a maximum decline in electric power output of approximately 18% was observed over a 500 h period in Jan. 2012.

fuel cell, combined heat and power, CHP, PEM, prot↗

DOE OSTI2016

Gas cluster ion beam for the characterization of organic materials in submarine basalts as Mars analogs

The solar system contains large quantities of organic compounds that can form complex molecular structures. The processing of organic compounds by biological systems leads to molecules with distinctive structural characteristics; thus, the detection and characterization of organic materials could lead to a high degree of confidence in the existence of extra-terrestrial life. Given the nature of the surface of most planetary bodies in the solar system, evidence of life is more likely to be found in the subsurface where conditions are more hospitable. Basalt is a common rock throughout the solar system and the primary rock type on Mars and Earth. Basalt is therefore a rock type that subsurface life might exploit and as such a suitable material for the study of methods required to detect and analyze organic material in rock. Telluric basalts from Earth represent an analog for extra-terrestrial rocks where the indigenous organic matter could be analyzed for molecular biosignatures. This study focuses on organic matter in the basalt with the use of surface analysis techniques utilizing Ar gas cluster ion beams (GCIB); time of flight secondary ion mass spectrometry (ToF-SIMS), and x-ray photoelectron spectroscopy (XPS), to characterize organic molecules. Tetramethylammonium hydroxide (TMAH) thermochemolysis was also used to support the data obtained using the surface analysis techniques. The authors demonstrate that organic molecules were found to be heterogeneously distributed within rock textures. A positive correlation was observed to exist between the presence of microtubule textures in the basalt and the organic compounds detected. From the results herein, the authors propose that ToF-SIMS with an Ar GCIB is effective at detecting organic materials in such geological samples, and ToF-SIMS combined with XPS and TMAH thermochemolysis may be a useful approach in the study of extra-terrestrial organic material and life.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1992

The interstellar medium of M31. III - Narrow-band imagery in H alpha and (SII)

Deep CCD imagery in H alpha and (SII) is presented of the major spiral arms of M31 with particular attention given to the data reduction and the analysis of the (SII)/H alpha flux ratios. A diffuse ionized gas noted in the images is analyzed which shows higher (SII)/H alpha ratios, and 967 discrete nebulae are listed with gray-scale images, finding charts, and absolute fluxes. The differential H-alpha luminosity function is found to have a slope of -0.95 for brighter objects and flattens out below a critical level. The curve is shown to correspond to the point at which single-star ionization accounts for the H alpha luminosities and is consistent with previous observations. The catalog of objects and fluxes is the largest existing sample of this type, and the unresolved objects in the sample are considered to be planetary nebulae.

Walterbos, R. A. M.↗

NASA NTRS2004

Determination of Cluster Distances from Chandra Imaging Spectroscopy and Sunyaev-Zeldovich Effect Measurements: Analysis Methods and Initial Results - I

X-ray and Sunyaev-Zeldovich Effect data ca,n be combined to determine the distance to galaxy clusters. High-resolution X-ray data are now available from the Chandra Observatory, which provides both spatial and spectral information, and interferometric radio measurements of the Sunyam-Zeldovich Effect are available from the BIMA and 0VR.O arrays. We introduce a Monte Carlo Markov chain procedure for the joint analysis of X-ray and Sunyaev-Zeldovich Effect data. The advantages of this method are the high computational efficiency and the ability to measure the full probability distribution of all parameters of interest, such as the spatial and spectral properties of the cluster gas and the cluster distance. We apply this technique to the Chandra X-ray data and the OVRO radio data for the galaxy cluster Abell 611. Comparisons with traditional likelihood-ratio methods reveal the robustness of the method. This method will be used in a follow-up paper to determine the distance of a large sample of galaxy clusters for which high-resolution Chandra X-ray and BIMA/OVRO radio data are available.

Bonamente, Massimiliano↗

NASA NTRSDate not supplied

Aerothermodynamic Measurements in Hypersonic Non-Equilibrium Flows

High enthalpy arc-jets are unique facilities particularly suited for simulating complex flows in the aerospace field, such as the aerothermodynamics of a re-entry vehicle. Arc-jets are often used to evaluate important design factors such as heat shield materials and vehicle design. Characterization of these facilities is important, as studies often match specific in-flight environments during experiments. Due to the complex environment produced by an arc-jet, with effects such as thermodynamic and chemical non-equilibrium occurring in the flow, characterization experiments are significantly more difficult than in traditional blow-down wind tunnels. The current work aims to characterize an arc-jet facility in terms of flow temperature, velocity and unsteadiness, in a spatially-resolved analysis. To achieve this goal, a non-intrusive imaging technique called “planar laser-induced fluorescence” was performed in the NASA Langley Hypersonic Materials Environ-mental Test System arc-jet facility. The experimental data was analyzed to produce the quantitative measurements in multiple regions of the flow around a blunt body sample. A quasi-1D low fidelity solver was created to numerically simulate the flow to investigate non-equilibrium effects occur-ring outside the imaging region in the arc-jet nozzle. Unsteadiness in the test section was minimized by analyzing a subset of data assessing the gas injection location. Radial velocity, rotational temperature and translational temperature measurements are provided that can be used to validate future high-fidelity computational studies. The temperature measurements revealed rotational non-equilibrium potentially occurring in the flow. This work provides a methodology for characterizing arc-jet facilities, identifying and correcting sources of systematic error, and estimating the uncertainty associated with the quantitative measurements.

laser induced fluorescence↗

DOE OSTI2018

Criticality Safety Evaluation for 700 and 350 Gram Moderated Fissionable Equivalent (MFE) Criticality Control Areas (CCAs)

This evaluation is intended to generically apply to facilities and/or areas designated as CCAs that store and/or handle greater than 15 grams of fissionable material but no more than 700 grams of MFE. This evaluation includes facilities and/or areas designated as CCAs limited to no more than 350 grams of MFE. Activities performed in these CCAs may include general laboratory activities to include work in radiological areas, chemical procurement, material handling, sampling, imaging, non-destructive analysis, and disposing of nuclear and radiological materials. Materials included in these activities may include radioactive-contaminated oil, polychlorinated biphenyls (PCBs), and/or equipment. Fissionable materials may consist of transuranic (TRU) waste, sources containing fissionable material, uranium in various forms such as metal, oxide and silicide, however other forms of uranium and plutonium may be present. Fissionable materials may consist of fines from cutting, be solid forms mounted on a ring and embedded in epoxy or be in small volumes of dilute solutions resulting from cleaning or other processes. Major equipment located in these CCAs may include inert gas environment gloveboxes, fume hoods, ultrasonic testing equipment, hot presses, rolling mills, furnaces, gamma irradiators, autoclaves, machining equipment, tensile testing equipment, shears, forklifts and cranes.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2016

Effect of grain size on optical properties of iron oxide nanoparticles

In the present paper, iron oxide nanoparticles are successfully synthesized by the sol-gel method. The grain size is varied by sintering the nanoparticles at different temperature 400, 500, 600, 700 and 800 °C. Field emission scanning electron microscope (FESEM) image shows that the grains are uniformly distributed. The grain size increases from 15 nm to 35 nm with increasing the sintering temperature (400-800 °C). Energy dispersive X-ray spectroscopy (EDS) analysis shows that Fe is present in the stoichiometric ratio in all the synthesized samples. Fourier transform infrared spectroscopy (FTIR) spectra show that Fe-O stretching peaks appears at ∼495 cm{sup −1}. The value of energy band gap are found 2.75, 2.67, 2.62, 2.59, and 2.57 eV for the samples sintered at 400, 500, 600, 700 and 800 °C respectively. Therefore, the decrease in band gap with increasing the temperature has been observed. In this paper, the structural and optical properties have been explained on the basis of variation in the grain size with the temperature. The present studied samples more widely used in gas sensors and as catalysts.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2015

STAR FORMATION ACROSS THE W3 COMPLEX

We present a multi-wavelength analysis of the history of star formation in the W3 complex. Using deep, near-infrared ground-based images combined with images obtained with Spitzer and Chandra observatories, we identified and classified young embedded sources. We identified the principal clusters in the complex and determined their structure and extension. We constructed extinction-limited samples for five principal clusters and constructed K-band luminosity functions that we compare with those of artificial clusters with varying ages. This analysis provided mean ages and possible age spreads for the clusters. We found that IC 1795, the centermost cluster of the complex, still hosts a large fraction of young sources with circumstellar disks. This indicates that star formation was active in IC 1795 as recently as 2 Myr ago, simultaneous to the star-forming activity in the flanking embedded clusters, W3-Main and W3(OH). A comparison with carbon monoxide emission maps indicates strong velocity gradients in the gas clumps hosting W3-Main and W3(OH) and shows small receding clumps of gas at IC 1795, suggestive of rapid gas removal (faster than the T Tauri timescale) in the cluster-forming regions. We discuss one possible scenario for the progression of cluster formation in the W3 complex. We propose that early processes of gas collapse in the main structure of the complex could have defined the progression of cluster formation across the complex with relatively small age differences from one group to another. However, triggering effects could act as catalysts for enhanced efficiency of formation at a local level, in agreement with previous studies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

The modification of BaCe{sub 0.5}Zr{sub 0.3}Y{sub 0.2}O{sub 3–δ} with copper oxide: Effect on the structural and transport properties

The effect of the content of CuO additive on the sinterability, phase composition, microstructure, and electrical properties of BaCe{sub 0.5}Zr{sub 0.3}Y{sub 0.2}O{sub 3–δ} proton-conducting material is studied. Ceramic samples were produced by the citrate–nitrate synthesis method with the addition of 0, 0.25, 0.5, and 1% CuO. It is shown that the relative density of the samples containing 0.5 and 1% CuO is higher than 94% at a sintering temperature of 1450°C, whereas the relative density of the material is no higher than 85% at a lower content of the sintering additive. From the data of X-ray diffraction analysis and scanning electron microscopy, it is established that the introduction of a small CuO content (0.25%) is inadequate for single-phase and high-dense ceramics to be formed. The conductivity and scanning electron microscopy data show that the sample with BaCe{sub 0.5}Zr{sub 0.3}Y{sub 0.2}O{sub 3–δ} + 0.5% CuO composition possesses high total and ionic conductivities as well as a high degree of microstructural stability after hydrogen reduction of the ceramics. The citrate–nitrate method modified by the introduction of a small CuO content can be recommended for the production of single-phase, gas-tight, and high-conductivity electrolytes based on both BaCeO{sub 3} and BaZrO{sub 3}.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Multivariate Statistical Analysis of Orthogonal Mass Spectral Data for the Identification of Chemical Attribution Signatures of 3-Methylfentanyl

Critical to many modern forensic investigations is the chemical attribution of the origin of an illegal drug. This process greatly relies on identification of compounds indicative of its clandestine or commercial production. The results of these studies can yield detailed information on method of manufacture, sophistication of the synthesis operation, starting material source, and final product. In the present work, chemical attribution signatures (CAS) associated with the synthesis of the analgesic 3- methylfentanyl, N-(3-methyl-1-phenethylpiperidin-4-yl)-N-phenylpropanamide, were investigated. Six synthesis methods were studied in an effort to identify and classify route-specific signatures. These methods were chosen to minimize the use of scheduled precursors, complicated laboratory equipment, number of overall steps, and demanding reaction conditions. Using gas and liquid chromatographies combined with mass spectrometric methods (GC-QTOF and LC-QTOF) in conjunction with inductivelycoupled plasma mass spectrometry (ICP-MS), over 240 distinct compounds and elements were monitored. As seen in our previous work with CAS of fentanyl synthesis the complexity of the resultant data matrix necessitated the use of multivariate statistical analysis. Using partial least squares discriminant analysis (PLS-DA), 62 statistically significant, route-specific CAS were identified. Statistical classification models using a variety of machine learning techniques were then developed with the ability to predict the method of 3-methylfentanyl synthesis from three blind crude samples generated by synthetic chemists without prior experience with these methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗